183
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Vegan Fertilizer for Container Citrus Tree

John posted the article • 0 comments • 183 views • 2017-11-24 03:39 • came from similar tags

 
Save Time and Jump to the specific Questions:
 02:43 What are the invertebrates used with aquaponics? 
03:24 How do I get tree collards? 
06:02 Have you ever used hugelkultur or Takakura Composting?
 10:35 Are coco fiber sheets the same as coco fiber lining?
 12:05 How should I treat wooden wine boxes to grow in outside?
 13:37 What kind of watering system should install to grow tree collards? 
14:57 Veganic Fertilizer for Container Citrus Tree? 
21:12 What advice do you have growing in the summer in Austin, Texas?
 25:00 Have you ever considered beneficial predatory mites?
 27:38 How about a video on LED lights or selling LED lights? 
29:11 Why can't a plant be trained to grow from zone to zone? 
32:22 Can I add limestone to my tomato plants?
 
 
 
  view all
 
Save Time and Jump to the specific Questions:
 02:43 What are the invertebrates used with aquaponics? 
03:24 How do I get tree collards? 
06:02 Have you ever used hugelkultur or Takakura Composting?
 10:35 Are coco fiber sheets the same as coco fiber lining?
 12:05 How should I treat wooden wine boxes to grow in outside?
 13:37 What kind of watering system should install to grow tree collards? 
14:57 Veganic Fertilizer for Container Citrus Tree? 
21:12 What advice do you have growing in the summer in Austin, Texas?
 25:00 Have you ever considered beneficial predatory mites?
 27:38 How about a video on LED lights or selling LED lights? 
29:11 Why can't a plant be trained to grow from zone to zone? 
32:22 Can I add limestone to my tomato plants?
 
 
 
 


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How can a Urban Farmer Makes $1000 a Week Growing Vegetables in Rental Home

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John posted a question • 1 users followed • 0 replies • 323 views • 2017-11-24 03:39 • came from similar tags

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Module 5: Ranking the Animals -5.7 Interpretation of Breeding Values and Accuracies

Emily posted the article • 0 comments • 248 views • 2017-11-21 07:24 • came from similar tags

Ranking the Animals - In Summary
 Before you move on to the assignments covering the whole module there is an animated video to watch, covering the most important topics that you learnt in this module on Ranking the animals. 

In a clip of about 10 minutes, you will get a summary of the principle of estimating breeding values (0:00 to 4:37), of the principle of accuracies of EBVs (4:37 to 6:51), and of the effect of using information on relatives on the accuracy of the estimated breeding value (6:51 to 10:45). 

Animation Estimated Breeding Value
 

 
 
video subtitle:
 
The success of animal breeding depends on the success of identifying the genetically best animals so that they can be used as parents to produce the next generation.
How can that be achieved? How can the genetically best animals be identified?
Let us consider a sheep farmer who wants to select a ram to mate with his ewes.
The most important breeding goal of the farmer is to increase the body weight of his sheep.
So which ram should he choose?
The challenge the farmer faces is how to identify the genetically best ram for breeding.
In other words, he needs to get a good impression of the genetic value of the ram as father of the next generation.
This is also called the breeding value of an animal.
If we would know the breeding values of the rams, we could rank them accordingly, and then choose the best ram for breeding.
But how can we obtain such a ranking of the animals?
To rank the animals, we would need to get insight in the breeding values of the rams.
The problem is that we cannot measure the true breeding value, but we can make an estimate of it.
The most basic method of ranking the rams would be by recording their own body weight, and rank them accordingly.
As the aim is to rank the rams such that the superior animals can be identified,
the weight of the individual rams is expressed relative to the average weight of all rams.
This way, animals that are heavier than average will obtain a positive value, and animals that are lighter will obtain a negative value.
Obviously, given the fact that the farmer wants to increase the weight of his sheep,
the interest is in the rams with positive values, and the larger the value the better.
Now we have ranked the rams according to their body weight, and we have determined which ones are better than average and how much.
But we still do not know whether this represents the ranking according to the genetic potential, or the breeding value of the rams.
What should we do to translate these relative performances of the rams into their estimated breeding values?
We need to find out how well the recorded body weights represent the genetic potential of the rams.
To achieve that we can make use of the heritability.
The heritability of a trait indicates how much of the variation among phenotypes in a population, so in this case body weight,
is due to additive genetic differences between the animals in the population, and how much is due to the environment.
The heritability is in fact a regression coefficient of the true breeding value of animals on their phenotype, where both are again expressed as deviations from the population average.
So the estimated breeding value equals a regression coefficient times the phenotype, expressed as deviation from the population average.
So although we do not know the true genetic potential, we can estimate the breeding value, in short EBV,
because we know the phenotype and the regression coefficient, which is in this case the heritability.
This procedure of using the phenotype and a regression coefficient to estimate the breeding value is the core principle of breeding value estimation.
Now let us go back to our sheep farmer.
He is considering using a ram that weighs 90 kilograms, but first he wants to know its estimated breeding value.
We know that the average ram in the population weighs 80 kilograms, and the heritability for body weight is 0.45.
Because in this case of own performance the regression coefficient of the true genetic potential of the rams on their phenotype is equal to the heritability,
we can estimate the breeding value of the ram as 0.45 times (90 minus 80) is equal to plus 4.5 kilograms.
This means that the genetic potential of the ram is estimated to be 4.5 kilograms higher than the population average.
Note that the EBV is expressed in units of the trait, in this case in kilograms.
Using the same approach, we can estimate the breeding values of each of the rams in the population, and rank them accordingly.
Some rams will have negative EBV, because their estimated genetic potential is lower than the population average.
These rams obviously will not be rams of choice for breeding, given that the breeding goal is to increase the body weight in the next generation.
This was quite a simple way to estimate a breeding value. But how accurate is an estimated breeding value?
The accuracy largely depends on the heritability of the trait that you want to estimate breeding values for.
The higher the heritability of a trait, the better the genetic potential of an animal can be estimated from its phenotype,
and the better ranking of animals on their EBVs represents the true genetic ranking of the animals.
Unfortunately, for traits of low heritability it is not so easy to accurately estimate the breeding value of an animal.
For such traits, the ranking according to EBV based on own performance will not necessarily represent the ranking according to the true breeding value of the animal.
To get some insight in this matter, imagine that you could create a plot with the true breeding value on the y-axis and the estimated breeding value on the x-axis.
Each EBV is linked to its accompanying true breeding value in a data-point.
If the EBVs are estimated accurately, the data points will be nicely on a straight line connecting each EBV to the true breeding value of equal size.
Unfortunately, it is very rarely the case that breeding values are estimated with such a high accuracy.
So why not? Why are we not always able to accurately estimate the breeding value of an animal?
We already briefly discussed the role of the heritability.
If the heritability is low, then the variation in phenotypes is only for a small proportion due to genetic differences between the animals.
So if we only use the information on the animals themselves to estimate the breeding value,
then the variation in EBV also will not only be due to genetic differences among the animals, but also due to environmental circumstances.
If you would now create such a plot of the estimated against the true breeding value, the points in your plot will not be on one line, but instead will form a cloud.
So what can we do to improve the accuracy of EBV?
There are two factors that can be improved: the quality of the phenotypes and the use of information of relatives.
We will not go into detail on how to improve phenotype recording, but we will show how we can use information of relatives.
For that, we can make use of the fact that related animals share part of their genetic potential.
The closer the relationship, the larger the shared part of their genetic potential.
So if we would also know the body weight of the father of the ram,
it would help to create a more accurately estimated breeding value for the ram, because the father and the ram share 50% of their genes.
If, in addition, we would also know the body weights of 5 brothers of the ram, it would add even more,
because the ram and his brothers also share 50% of their genetic information.
And body weights of 25 half-brothers again would add, even though the genetic relationship between the ram and his half-brothers is not as strong as with his full brothers, or his father.
In other words, not all information is equally valuable.
The closer the genetic relationship, the more valuable the information for estimating the breeding value of an animal.
However, there is only one father and there may be multiple brothers.
And multiple brothers (or sisters) are more informative for estimating the genetic potential of an animal than a single parent.
But offspring are even more valuable, because there can be multiple of them.
The more offspring are available, the more accurately we can estimate the breeding value of the animal.
If we have information on many offspring, we can even approach the 100% accuracy!
Then the EBV becomes equal to the tbv. That would be the ideal situation.
As we have seen, not all information is equally valuable for estimating breeding values.
How can we account for that when estimating breeding values?
The answer is in calculating the regression coefficient.
Let us consider the situation where we have information from 10 half-sibs on body weight.
Suppose they are 5 kilograms heavier than average.
The formula for calculating the regression coefficient is in this case...
Therefore, the EBV of the ram based on these half-sibs is...
Now we have two EBVs: one based on the own body weight and one based on half-sibs.
The question is now whether we can do better than that and combine the information.
We should not just sum these two EBVs. The solution is multiple regression.
The b-values cannot be calculated with the equations in the appendix anymore, because there is an overlap in information.
The rams itself and his half-sibs share a quarter of the genes and we need to account for that in calculating the b-values.
Therefore, we use an Excel sheet specifically designed to calculate b-values in case of multiple regression.
With this sheet the calculated b-values are 0.41 for own body weight and 0.33 for the half-sibs.
So when we fill in those values, we can obtain the EBV of the ram.
Generally speaking, the more phenotypic information there is on related animals, the more accurately we can estimate the breeding values.
In summary, the success of identifying the genetically best animals depends on the heritability of the trait,
and on the amount and quality of information we have on the phenotypic performance of the animal and its close relatives.
Those factors determine the accuracy of the estimated breeding value.
So the success of animal breeding depends on the collection of good quality data on many animals,
obviously in addition to keeping records of genetic relationships between the animals.
 
 
 
Working with Breeding Values and Accuracies
 
In breeding, we use the estimated breeding values to rank animals. Which aspects are taken into account in calculating the EBVs fully depends on the breeding goal that we determined earlier. Which traits have we defined as important traits for this population in the future? Which traits do we select the animals on, to improve the future generations? Which are the best animals to breed with?

You have now seen that you can calculate estimated breeding values, as well as accuracies, in different situations. 

Now take a few moments to think about the following question, and write down a short answer for yourself:

Should we select the animal with highest EBV or with the highest accuracy?

Now look back at the answer you chose at the beginning of this module, whether you would use information on the animals themselves, their parents, their siblings, or their offspring to select the best animals for breeding. In this module you learned how to make a decision like this based on the accuracy you can expect from different information sources.  

Breeding values and accuracies

A poultry breeding company is interested in selecting roosters for egg weight. The information that is available comes from 40 hens which are full sibs of the rooster. The heritability of egg weight is 0.40. We assume that the common environment is zero. 
 

 
  view all
Ranking the Animals - In Summary
 Before you move on to the assignments covering the whole module there is an animated video to watch, covering the most important topics that you learnt in this module on Ranking the animals. 

In a clip of about 10 minutes, you will get a summary of the principle of estimating breeding values (0:00 to 4:37), of the principle of accuracies of EBVs (4:37 to 6:51), and of the effect of using information on relatives on the accuracy of the estimated breeding value (6:51 to 10:45). 

Animation Estimated Breeding Value
 


 
 
video subtitle:
 
The success of animal breeding depends on the success of identifying the genetically best animals so that they can be used as parents to produce the next generation.
How can that be achieved? How can the genetically best animals be identified?
Let us consider a sheep farmer who wants to select a ram to mate with his ewes.
The most important breeding goal of the farmer is to increase the body weight of his sheep.
So which ram should he choose?
The challenge the farmer faces is how to identify the genetically best ram for breeding.
In other words, he needs to get a good impression of the genetic value of the ram as father of the next generation.
This is also called the breeding value of an animal.
If we would know the breeding values of the rams, we could rank them accordingly, and then choose the best ram for breeding.
But how can we obtain such a ranking of the animals?
To rank the animals, we would need to get insight in the breeding values of the rams.
The problem is that we cannot measure the true breeding value, but we can make an estimate of it.
The most basic method of ranking the rams would be by recording their own body weight, and rank them accordingly.
As the aim is to rank the rams such that the superior animals can be identified,
the weight of the individual rams is expressed relative to the average weight of all rams.
This way, animals that are heavier than average will obtain a positive value, and animals that are lighter will obtain a negative value.
Obviously, given the fact that the farmer wants to increase the weight of his sheep,
the interest is in the rams with positive values, and the larger the value the better.
Now we have ranked the rams according to their body weight, and we have determined which ones are better than average and how much.
But we still do not know whether this represents the ranking according to the genetic potential, or the breeding value of the rams.
What should we do to translate these relative performances of the rams into their estimated breeding values?
We need to find out how well the recorded body weights represent the genetic potential of the rams.
To achieve that we can make use of the heritability.
The heritability of a trait indicates how much of the variation among phenotypes in a population, so in this case body weight,
is due to additive genetic differences between the animals in the population, and how much is due to the environment.
The heritability is in fact a regression coefficient of the true breeding value of animals on their phenotype, where both are again expressed as deviations from the population average.
So the estimated breeding value equals a regression coefficient times the phenotype, expressed as deviation from the population average.
So although we do not know the true genetic potential, we can estimate the breeding value, in short EBV,
because we know the phenotype and the regression coefficient, which is in this case the heritability.
This procedure of using the phenotype and a regression coefficient to estimate the breeding value is the core principle of breeding value estimation.
Now let us go back to our sheep farmer.
He is considering using a ram that weighs 90 kilograms, but first he wants to know its estimated breeding value.
We know that the average ram in the population weighs 80 kilograms, and the heritability for body weight is 0.45.
Because in this case of own performance the regression coefficient of the true genetic potential of the rams on their phenotype is equal to the heritability,
we can estimate the breeding value of the ram as 0.45 times (90 minus 80) is equal to plus 4.5 kilograms.
This means that the genetic potential of the ram is estimated to be 4.5 kilograms higher than the population average.
Note that the EBV is expressed in units of the trait, in this case in kilograms.
Using the same approach, we can estimate the breeding values of each of the rams in the population, and rank them accordingly.
Some rams will have negative EBV, because their estimated genetic potential is lower than the population average.
These rams obviously will not be rams of choice for breeding, given that the breeding goal is to increase the body weight in the next generation.
This was quite a simple way to estimate a breeding value. But how accurate is an estimated breeding value?
The accuracy largely depends on the heritability of the trait that you want to estimate breeding values for.
The higher the heritability of a trait, the better the genetic potential of an animal can be estimated from its phenotype,
and the better ranking of animals on their EBVs represents the true genetic ranking of the animals.
Unfortunately, for traits of low heritability it is not so easy to accurately estimate the breeding value of an animal.
For such traits, the ranking according to EBV based on own performance will not necessarily represent the ranking according to the true breeding value of the animal.
To get some insight in this matter, imagine that you could create a plot with the true breeding value on the y-axis and the estimated breeding value on the x-axis.
Each EBV is linked to its accompanying true breeding value in a data-point.
If the EBVs are estimated accurately, the data points will be nicely on a straight line connecting each EBV to the true breeding value of equal size.
Unfortunately, it is very rarely the case that breeding values are estimated with such a high accuracy.
So why not? Why are we not always able to accurately estimate the breeding value of an animal?
We already briefly discussed the role of the heritability.
If the heritability is low, then the variation in phenotypes is only for a small proportion due to genetic differences between the animals.
So if we only use the information on the animals themselves to estimate the breeding value,
then the variation in EBV also will not only be due to genetic differences among the animals, but also due to environmental circumstances.
If you would now create such a plot of the estimated against the true breeding value, the points in your plot will not be on one line, but instead will form a cloud.
So what can we do to improve the accuracy of EBV?
There are two factors that can be improved: the quality of the phenotypes and the use of information of relatives.
We will not go into detail on how to improve phenotype recording, but we will show how we can use information of relatives.
For that, we can make use of the fact that related animals share part of their genetic potential.
The closer the relationship, the larger the shared part of their genetic potential.
So if we would also know the body weight of the father of the ram,
it would help to create a more accurately estimated breeding value for the ram, because the father and the ram share 50% of their genes.
If, in addition, we would also know the body weights of 5 brothers of the ram, it would add even more,
because the ram and his brothers also share 50% of their genetic information.
And body weights of 25 half-brothers again would add, even though the genetic relationship between the ram and his half-brothers is not as strong as with his full brothers, or his father.
In other words, not all information is equally valuable.
The closer the genetic relationship, the more valuable the information for estimating the breeding value of an animal.
However, there is only one father and there may be multiple brothers.
And multiple brothers (or sisters) are more informative for estimating the genetic potential of an animal than a single parent.
But offspring are even more valuable, because there can be multiple of them.
The more offspring are available, the more accurately we can estimate the breeding value of the animal.
If we have information on many offspring, we can even approach the 100% accuracy!
Then the EBV becomes equal to the tbv. That would be the ideal situation.
As we have seen, not all information is equally valuable for estimating breeding values.
How can we account for that when estimating breeding values?
The answer is in calculating the regression coefficient.
Let us consider the situation where we have information from 10 half-sibs on body weight.
Suppose they are 5 kilograms heavier than average.
The formula for calculating the regression coefficient is in this case...
Therefore, the EBV of the ram based on these half-sibs is...
Now we have two EBVs: one based on the own body weight and one based on half-sibs.
The question is now whether we can do better than that and combine the information.
We should not just sum these two EBVs. The solution is multiple regression.
The b-values cannot be calculated with the equations in the appendix anymore, because there is an overlap in information.
The rams itself and his half-sibs share a quarter of the genes and we need to account for that in calculating the b-values.
Therefore, we use an Excel sheet specifically designed to calculate b-values in case of multiple regression.
With this sheet the calculated b-values are 0.41 for own body weight and 0.33 for the half-sibs.
So when we fill in those values, we can obtain the EBV of the ram.
Generally speaking, the more phenotypic information there is on related animals, the more accurately we can estimate the breeding values.
In summary, the success of identifying the genetically best animals depends on the heritability of the trait,
and on the amount and quality of information we have on the phenotypic performance of the animal and its close relatives.
Those factors determine the accuracy of the estimated breeding value.
So the success of animal breeding depends on the collection of good quality data on many animals,
obviously in addition to keeping records of genetic relationships between the animals.
 
 
 
Working with Breeding Values and Accuracies
 
In breeding, we use the estimated breeding values to rank animals. Which aspects are taken into account in calculating the EBVs fully depends on the breeding goal that we determined earlier. Which traits have we defined as important traits for this population in the future? Which traits do we select the animals on, to improve the future generations? Which are the best animals to breed with?

You have now seen that you can calculate estimated breeding values, as well as accuracies, in different situations. 

Now take a few moments to think about the following question, and write down a short answer for yourself:

Should we select the animal with highest EBV or with the highest accuracy?

Now look back at the answer you chose at the beginning of this module, whether you would use information on the animals themselves, their parents, their siblings, or their offspring to select the best animals for breeding. In this module you learned how to make a decision like this based on the accuracy you can expect from different information sources.  

Breeding values and accuracies

A poultry breeding company is interested in selecting roosters for egg weight. The information that is available comes from 40 hens which are full sibs of the rooster. The heritability of egg weight is 0.40. We assume that the common environment is zero. 
 

 
 
494
Views

Module 5: Ranking the Animals -5.4 Breeding Value Estimation Using Multiple Information Sources

Emily posted the article • 0 comments • 494 views • 2017-11-21 07:15 • came from similar tags

Tutorial Clip 
 
To calculate the accuracy of an estimated breeding value based on a single type of information we can use the formulas presented in 5.3. With multiple information sources the calculations are more complicated as explained on the previous page. These calculations have been implemented in an excel tool called stselind.xls developed by Julius van der Werf (https://jvanderw.une.edu.au/). The next tutorial will introduce, step by step, how to use stselind.xls.
 

 
Video subtitle:
 
The aim of this video is to explain how the Excel sheet Selection_index can be used
to calculate the regression coefficients, otherwise known as b-values,
and to calculate the breeding value and to calculate its accuracy
when there are multiple information sources.
With this Excel-sheet you can play around a bit
to investigate the impact of multiple information sources
on the accuracy of estimated breeding values.
First, let’s take a look at the Excel sheet.
Here at the top, in the cells highlighted in orange,
we can fill in the values for the heritability of the trait,
the repeatability and the c squared, which is the proportion of variance
explained by the common environmental effect.
If the repeatability and c squared are not given,
we can set them to a value of zero.
Further down, in the cells highlighted in blue,
we can fill in how many records we have for each type of information:
own records, records of the dam, the sire,
records of full-sibs, records of half-sibs and records of progeny.
If we want to calculate the b-values and the accuracy for a new set of parameters,
we can click on Run
and the calculated b-values will appear in the column called ‘Index weight’
and the value for accuracy will appear in the purple cell.
The column ‘value of variate’ is not used in this course.
The yellow cells labelled P-matrix and G-matrix are outside the scope of this course.
The yellow cells with b-values and accuracy
are the same values as you see in the purple
and in the pink cells.
Let’s consider a situation where we want to calculate the b-values
and accuracy of the estimated breeding value
for litter size for a sow with one own observation,
an observation of the dam, 4 full-sibs and 20 half-sibs.
Let’s first fill in the heritability of 0.11;
we set the repeatability and c squared to zero.
Let’s now fill in the values where the sow has only an own observation.
If we click on Run, we obtain a b-value of 0.11
and the accuracy is 0.33.
We expect to see an accuracy of 0.33 since 0.33 is the square root of the heritability,
as we have seen before.
Let’s now say that we have a record of the dam of the sow for litter size
so we add that value to our sheet.
We click on Run, and we see that the b-value for the own records decreases a little bit.
This happens because there is some overlap in the information of the sow and her dam
since they share 50% of their DNA.
We can see that the accuracy increases from 0.33 to 0.36
because we have more information
and therefore, the estimated breeding value is more accurate.
When we add 4 records of full-sibs,
we see that the accuracy increases to 0.45.
The four full-sisters share 50% of their DNA with the sow of interest
and therefore, the information on their litter size
increases the accuracy of the estimated breeding value.
Then, when we add 20 half-sibs,
we see that the accuracy increases to 0.5
since the half-sisters share 25% of their DNA with the sow of interest.
So the accuracy of the estimated breeding value increases every time
when we add additional information of relatives .
In summary, the Excel sheet ‘Selection_index.xlsx’
can be used to calculate the accuracy of the estimated breeding values
for any combination of information available.
Furthermore, the b-values can be used to weigh
the different information sources when estimating the breeding value of an animal.
  view all
Tutorial Clip 
 
To calculate the accuracy of an estimated breeding value based on a single type of information we can use the formulas presented in 5.3. With multiple information sources the calculations are more complicated as explained on the previous page. These calculations have been implemented in an excel tool called stselind.xls developed by Julius van der Werf (https://jvanderw.une.edu.au/). The next tutorial will introduce, step by step, how to use stselind.xls.
 


 
Video subtitle:
 
The aim of this video is to explain how the Excel sheet Selection_index can be used
to calculate the regression coefficients, otherwise known as b-values,
and to calculate the breeding value and to calculate its accuracy
when there are multiple information sources.
With this Excel-sheet you can play around a bit
to investigate the impact of multiple information sources
on the accuracy of estimated breeding values.
First, let’s take a look at the Excel sheet.
Here at the top, in the cells highlighted in orange,
we can fill in the values for the heritability of the trait,
the repeatability and the c squared, which is the proportion of variance
explained by the common environmental effect.
If the repeatability and c squared are not given,
we can set them to a value of zero.
Further down, in the cells highlighted in blue,
we can fill in how many records we have for each type of information:
own records, records of the dam, the sire,
records of full-sibs, records of half-sibs and records of progeny.
If we want to calculate the b-values and the accuracy for a new set of parameters,
we can click on Run
and the calculated b-values will appear in the column called ‘Index weight’
and the value for accuracy will appear in the purple cell.
The column ‘value of variate’ is not used in this course.
The yellow cells labelled P-matrix and G-matrix are outside the scope of this course.
The yellow cells with b-values and accuracy
are the same values as you see in the purple
and in the pink cells.
Let’s consider a situation where we want to calculate the b-values
and accuracy of the estimated breeding value
for litter size for a sow with one own observation,
an observation of the dam, 4 full-sibs and 20 half-sibs.
Let’s first fill in the heritability of 0.11;
we set the repeatability and c squared to zero.
Let’s now fill in the values where the sow has only an own observation.
If we click on Run, we obtain a b-value of 0.11
and the accuracy is 0.33.
We expect to see an accuracy of 0.33 since 0.33 is the square root of the heritability,
as we have seen before.
Let’s now say that we have a record of the dam of the sow for litter size
so we add that value to our sheet.
We click on Run, and we see that the b-value for the own records decreases a little bit.
This happens because there is some overlap in the information of the sow and her dam
since they share 50% of their DNA.
We can see that the accuracy increases from 0.33 to 0.36
because we have more information
and therefore, the estimated breeding value is more accurate.
When we add 4 records of full-sibs,
we see that the accuracy increases to 0.45.
The four full-sisters share 50% of their DNA with the sow of interest
and therefore, the information on their litter size
increases the accuracy of the estimated breeding value.
Then, when we add 20 half-sibs,
we see that the accuracy increases to 0.5
since the half-sisters share 25% of their DNA with the sow of interest.
So the accuracy of the estimated breeding value increases every time
when we add additional information of relatives .
In summary, the Excel sheet ‘Selection_index.xlsx’
can be used to calculate the accuracy of the estimated breeding values
for any combination of information available.
Furthermore, the b-values can be used to weigh
the different information sources when estimating the breeding value of an animal.
 
161
Views

Module 5: Ranking the Animals -5.6 Breeding Value Estimation Using Genomic Information

Emily posted the article • 0 comments • 161 views • 2017-11-21 07:15 • came from similar tags

Using genomic information

Breeding values are estimated based on phenotypic information. After an animal is born it may take some time before we can obtain this phenotypic information. Think of reproduction traits where the information cannot be measured until the animals are adults. At a young age, the information is limited to the performance of the parents which limits the accuracy of the EBV. It would be very interesting to have a methodology that increases the accuracy of the EBV already at younger age, without having to wait. 

Genomic selection

With genomic selection it is possible to estimate the breeding value of an animal quite accurately without the need to wait for own performance or performance of a large number of offspring. Genomic selection is based on estimating the associations between genetic marker genotypes (SNP) and phenotypes on a group of animals that have information for both. These associations can subsequently be used to predict the so-called genomic breeding values (gEBV) for animals that have been genotyped for the SNP, but that don’t (yet) have own phenotypes. 

Using Genomic Information
 

 
 
  view all
Using genomic information

Breeding values are estimated based on phenotypic information. After an animal is born it may take some time before we can obtain this phenotypic information. Think of reproduction traits where the information cannot be measured until the animals are adults. At a young age, the information is limited to the performance of the parents which limits the accuracy of the EBV. It would be very interesting to have a methodology that increases the accuracy of the EBV already at younger age, without having to wait. 

Genomic selection

With genomic selection it is possible to estimate the breeding value of an animal quite accurately without the need to wait for own performance or performance of a large number of offspring. Genomic selection is based on estimating the associations between genetic marker genotypes (SNP) and phenotypes on a group of animals that have information for both. These associations can subsequently be used to predict the so-called genomic breeding values (gEBV) for animals that have been genotyped for the SNP, but that don’t (yet) have own phenotypes. 

Using Genomic Information
 


 
 
 
169
Views

Module 5: Ranking the Animals -5.5 Breeding Value Estimation Using BLUP

Emily posted the article • 0 comments • 169 views • 2017-11-21 07:15 • came from similar tags

What is BLUP?

In real life, we do not want to estimate breeding values for each animal by calculating regression coefficients. Furthermore, animals may perform in different environmental units such as different farms. Therefore, in real life, BLUP is used for breeding value estimation. BLUP stands for Best Linear Unbiased Prediction. It is a method to estimate breeding values while making use of the additive genetic relationships between animals, thereby simultaneously correcting the phenotypes for systematic effects. In this course, we will only explain the very basics of the method to show you what the possibilities are in animal breeding. You will also get an assignment to familiarize yourself with the output of BLUP.

What does BLUP do?

This all may sound quite complicated, but in a way BLUP does follow the simple genetic model P = A + E, and, in addition, provides estimates for systematic environmental effects. For example, if animals on one farm are fed much better than on another farm then ranking animals based on their weight would benefit the animals from the farm with the better nutrition. However, genetically the animals on both farms may be similar. Without taking this systematic influence of farm of origin into account, it is likely that the top ranking animals would mainly originate from the farm with the better feed. To be able to compare the performance of the animals more on their genetic potential it is important to take this farm effect into account and this is what BLUP does (if you provide the information about on which farm each animal was housed). 

The principle of BLUP is to determine the average weight of the animals on each farm and subtract the difference from the animals on the farm with the highest weight. So if animals on farm 1 weigh 100 kg on average and on farm 2 they weigh 120 kg on average, then you disadvantage the animals of farm 2 by subtracting 20 kg from their weight. 

Information is needed

Systematic effects can be estimated, provided that the information is present. For example, registration of the farm should be available for each animal. Other systematic effects that are often estimated are:

Sex (males are heavier than females, for example)
Country
Birth year 
Birth season
Year
Month of phenotype recording
If applicable, barn or pen number (housing location)
Treatment (in case of an experiment)

Critical issues in BLUP

Critical issue in correcting for systematic effects is that it only works well if genotypes are sufficiently spread across systematic environmental influences. So the animals on both farms need to be related, for example because the same fathers were used or because the fathers used on each farm were brothers. If the animals on both farms are unrelated, then part of the reason of the difference in weight may be a difference in genetic potential. And that is what you want to estimate so you do not want to lose that by correcting the weight. Artificial insemination allows for genetic links between farms because the same sires are used in many farms. In farm animal species where natural mating is common practice, such as in beef cattle and sheep, it often is impossible to estimate systematic farm effects accurately because lack of exchange of animals between farms results in poor genetic links between farms. In species where the sires are brought to their mates on various locations, as can be the case in horse or dog breeding, genetic links will not be a limiting factor, provided that the sires are used frequently.
 
  view all
What is BLUP?

In real life, we do not want to estimate breeding values for each animal by calculating regression coefficients. Furthermore, animals may perform in different environmental units such as different farms. Therefore, in real life, BLUP is used for breeding value estimation. BLUP stands for Best Linear Unbiased Prediction. It is a method to estimate breeding values while making use of the additive genetic relationships between animals, thereby simultaneously correcting the phenotypes for systematic effects. In this course, we will only explain the very basics of the method to show you what the possibilities are in animal breeding. You will also get an assignment to familiarize yourself with the output of BLUP.

What does BLUP do?

This all may sound quite complicated, but in a way BLUP does follow the simple genetic model P = A + E, and, in addition, provides estimates for systematic environmental effects. For example, if animals on one farm are fed much better than on another farm then ranking animals based on their weight would benefit the animals from the farm with the better nutrition. However, genetically the animals on both farms may be similar. Without taking this systematic influence of farm of origin into account, it is likely that the top ranking animals would mainly originate from the farm with the better feed. To be able to compare the performance of the animals more on their genetic potential it is important to take this farm effect into account and this is what BLUP does (if you provide the information about on which farm each animal was housed). 

The principle of BLUP is to determine the average weight of the animals on each farm and subtract the difference from the animals on the farm with the highest weight. So if animals on farm 1 weigh 100 kg on average and on farm 2 they weigh 120 kg on average, then you disadvantage the animals of farm 2 by subtracting 20 kg from their weight. 

Information is needed

Systematic effects can be estimated, provided that the information is present. For example, registration of the farm should be available for each animal. Other systematic effects that are often estimated are:

Sex (males are heavier than females, for example)
Country
Birth year 
Birth season
Year
Month of phenotype recording
If applicable, barn or pen number (housing location)
Treatment (in case of an experiment)

Critical issues in BLUP

Critical issue in correcting for systematic effects is that it only works well if genotypes are sufficiently spread across systematic environmental influences. So the animals on both farms need to be related, for example because the same fathers were used or because the fathers used on each farm were brothers. If the animals on both farms are unrelated, then part of the reason of the difference in weight may be a difference in genetic potential. And that is what you want to estimate so you do not want to lose that by correcting the weight. Artificial insemination allows for genetic links between farms because the same sires are used in many farms. In farm animal species where natural mating is common practice, such as in beef cattle and sheep, it often is impossible to estimate systematic farm effects accurately because lack of exchange of animals between farms results in poor genetic links between farms. In species where the sires are brought to their mates on various locations, as can be the case in horse or dog breeding, genetic links will not be a limiting factor, provided that the sires are used frequently.
 
 
231
Views

Module 5: Ranking the Animals -5.4 Breeding Value Estimation Using Multiple Information Sources

Emily posted the article • 0 comments • 231 views • 2017-11-21 07:09 • came from similar tags

Using Multiple Information Sources

Selection index

In real life, we often have information on different types of relatives for the animal who’s breeding value we want to estimate. In these cases, we would like to combine phenotypic information in an optimal way to estimate the breeding value. Again, we can use regression but now we extend to multiple regression. Within animal breeding this is called a selection index.

A cow may have information on her own milk production and the milk production of her dam. To estimate the breeding value by regression we would write the following equation:

Avoid double counting of phenotypic information

When we combine the phenotype of the animal and the phenotype of the dam in estimating the breeding value we see that the regression coefficients 0.284 and 0.107 were different from the regression with only one source of information. With only the own performance the regression is the heritability (0.3) or with only the phenotype of the dam the regression is half the heritability (0.15).

Why this difference? The reason is that the information of the animal itself and of the dam contain overlapping information about the same genes, those genes from the dam that were passed to the daughter. To avoid double counting of this information, the regression coefficients in a selection index with multiple information sources are lower than when only a single source of information is available.

To calculate the EBV from multiple sources, still the same 3 steps as for single source need to be taken:

Determine the phenotypic deviations of your information sources
Determine the regression coefficients
Combine the previous two to estimate the breeding value

With phenotypic information of multiple relatives, the EBV is the sum of phenotypic deviations times the multiple regression coefficients.

EBV=b1*(P1-mean)+b2*(P2-mean)+.....+bn*(Pn-mean)

 

 
 

 
 
Video subtitle:
 
In a previous clip, we showed how we can estimate breeding values.
We can, for example, use a record on own performance or on a group of offspring.
However, as you may have noticed, the estimated breeding values for those two cases may differ.
With own performance the estimate was +1.36 eggs,
whereas with offspring the estimate was +3.6 eggs.
Now we have a problem: which estimate should we use?
Ideally, we would like to have only a single estimated breeding value, with the maximum possible accuracy.
In this clip, I will show how we can estimate a single breeding value
by combining multiple information sources.
In the previous clip, you saw that breeding values can be estimated using simple regression.
The estimated breeding value is the product of a regression coefficient, denoted by b,
and the difference between the value of the information source and the population mean.
The regression coefficient is the slope of the regression line.
With own performance, for example, the regression coefficient is equal to heritability.
Suppose heritability of egg production is 0.34,
and that we have a chicken producing 80 eggs.
Mean egg production of the population is 76 eggs.
Then the estimated breeding value of the chicken is 0.34 x (80 – 76) = +1.36 eggs.
With multiple information sources, we can extend this approach
by using multiple regression rather than simple regression.
Let’s do an example.
Suppose we have two information sources: an own performance record
and the average egg production of six offspring.
Because we have two information sources, our regression equation now has two components;
one for own performance with regression coefficient b1,
and another for offspring performance with regression coefficient b2.
This is an example of multiple regression, because we regress on more than one information source.
The regression coefficients b1 and b2 can be calculated using specific software.
Those b-values depend on heritability, on the number of records,
and on the relationships between the animals.
The details of calculating the b-values are outside the scope of this clip.
Let’s continue with the example of the chicken that produced 80 eggs.
Suppose that her six offspring produced on average 81 eggs.
Using the software and a heritability of 0.34, we find that b1 = 0.25 and b2 = 0.54.
Thus the estimated breeding value of the chicken equals 0.25 x (80-76) + 0.54 x (81-76) = which together is +3.7 eggs.
In this way, we can get a single estimated breeding value
that optimally combines both sources of information.
If you want to combine multiple information sources, you cannot use simple regression.
Let’s look at what happens if we would use simple regression.
From the previous clip, you may remember that the b-value for own performance was 0.34,
and that the b-value for six offspring was 0.72.
If we were to use those b-values together,
then the estimated breeding value would be 4.96 eggs.
This value is much larger than the 3.7 eggs we get from multiple regression.
This illustrates that simple regression leads to double counting of information.
Double counting occurs because our information sources are not independent.
In this case, the offspring carry half of the alleles of the individual,
and both information sources therefore overlap.
Multiple regression takes this overlap into account.
Now you have seen how we can combine both information sources.
But what happens with the accuracy?
Let’s first look at the accuracies we had with a single information source.
With an own performance record, the accuracy equals the square-root of heritability,
which is 0.58.
With records on six offspring, the accuracy can be calculated with an equation, and equals 0.60.
When we combine both information sources, we can find the accuracy using specific software.
The result shows that accuracy equals 0.72.
This value is higher than the accuracies for a single information source.
In fact, when you combine information sources with multiple regression
you get the maximum possible accuracy.
The previous has shown how we can combine two information sources using multiple regression.
This multiple regression approach can be generalized to any number of information sources,
as illustrated by this equation.
In conclusion, we can estimate breeding values using regression.
With a single information source, we can use simple regression.
With multiple information sources, we have to use multiple regression.
By using multiple regression, we combine all information in the optimal way,
and maximize the accuracy of the estimated breeding value. view all
Using Multiple Information Sources

Selection index

In real life, we often have information on different types of relatives for the animal who’s breeding value we want to estimate. In these cases, we would like to combine phenotypic information in an optimal way to estimate the breeding value. Again, we can use regression but now we extend to multiple regression. Within animal breeding this is called a selection index.

A cow may have information on her own milk production and the milk production of her dam. To estimate the breeding value by regression we would write the following equation:

Avoid double counting of phenotypic information

When we combine the phenotype of the animal and the phenotype of the dam in estimating the breeding value we see that the regression coefficients 0.284 and 0.107 were different from the regression with only one source of information. With only the own performance the regression is the heritability (0.3) or with only the phenotype of the dam the regression is half the heritability (0.15).

Why this difference? The reason is that the information of the animal itself and of the dam contain overlapping information about the same genes, those genes from the dam that were passed to the daughter. To avoid double counting of this information, the regression coefficients in a selection index with multiple information sources are lower than when only a single source of information is available.

To calculate the EBV from multiple sources, still the same 3 steps as for single source need to be taken:

Determine the phenotypic deviations of your information sources
Determine the regression coefficients
Combine the previous two to estimate the breeding value

With phenotypic information of multiple relatives, the EBV is the sum of phenotypic deviations times the multiple regression coefficients.

EBV=b1*(P1-mean)+b2*(P2-mean)+.....+bn*(Pn-mean)

 

 
 


 
 
Video subtitle:
 
In a previous clip, we showed how we can estimate breeding values.
We can, for example, use a record on own performance or on a group of offspring.
However, as you may have noticed, the estimated breeding values for those two cases may differ.
With own performance the estimate was +1.36 eggs,
whereas with offspring the estimate was +3.6 eggs.
Now we have a problem: which estimate should we use?
Ideally, we would like to have only a single estimated breeding value, with the maximum possible accuracy.
In this clip, I will show how we can estimate a single breeding value
by combining multiple information sources.
In the previous clip, you saw that breeding values can be estimated using simple regression.
The estimated breeding value is the product of a regression coefficient, denoted by b,
and the difference between the value of the information source and the population mean.
The regression coefficient is the slope of the regression line.
With own performance, for example, the regression coefficient is equal to heritability.
Suppose heritability of egg production is 0.34,
and that we have a chicken producing 80 eggs.
Mean egg production of the population is 76 eggs.
Then the estimated breeding value of the chicken is 0.34 x (80 – 76) = +1.36 eggs.
With multiple information sources, we can extend this approach
by using multiple regression rather than simple regression.
Let’s do an example.
Suppose we have two information sources: an own performance record
and the average egg production of six offspring.
Because we have two information sources, our regression equation now has two components;
one for own performance with regression coefficient b1,
and another for offspring performance with regression coefficient b2.
This is an example of multiple regression, because we regress on more than one information source.
The regression coefficients b1 and b2 can be calculated using specific software.
Those b-values depend on heritability, on the number of records,
and on the relationships between the animals.
The details of calculating the b-values are outside the scope of this clip.
Let’s continue with the example of the chicken that produced 80 eggs.
Suppose that her six offspring produced on average 81 eggs.
Using the software and a heritability of 0.34, we find that b1 = 0.25 and b2 = 0.54.
Thus the estimated breeding value of the chicken equals 0.25 x (80-76) + 0.54 x (81-76) = which together is +3.7 eggs.
In this way, we can get a single estimated breeding value
that optimally combines both sources of information.
If you want to combine multiple information sources, you cannot use simple regression.
Let’s look at what happens if we would use simple regression.
From the previous clip, you may remember that the b-value for own performance was 0.34,
and that the b-value for six offspring was 0.72.
If we were to use those b-values together,
then the estimated breeding value would be 4.96 eggs.
This value is much larger than the 3.7 eggs we get from multiple regression.
This illustrates that simple regression leads to double counting of information.
Double counting occurs because our information sources are not independent.
In this case, the offspring carry half of the alleles of the individual,
and both information sources therefore overlap.
Multiple regression takes this overlap into account.
Now you have seen how we can combine both information sources.
But what happens with the accuracy?
Let’s first look at the accuracies we had with a single information source.
With an own performance record, the accuracy equals the square-root of heritability,
which is 0.58.
With records on six offspring, the accuracy can be calculated with an equation, and equals 0.60.
When we combine both information sources, we can find the accuracy using specific software.
The result shows that accuracy equals 0.72.
This value is higher than the accuracies for a single information source.
In fact, when you combine information sources with multiple regression
you get the maximum possible accuracy.
The previous has shown how we can combine two information sources using multiple regression.
This multiple regression approach can be generalized to any number of information sources,
as illustrated by this equation.
In conclusion, we can estimate breeding values using regression.
With a single information source, we can use simple regression.
With multiple information sources, we have to use multiple regression.
By using multiple regression, we combine all information in the optimal way,
and maximize the accuracy of the estimated breeding value.
146
Views

Module 5: Ranking the Animals -5.3 Calculation of Accuracies of Breeding Values

Emily posted the article • 0 comments • 146 views • 2017-11-21 07:09 • came from similar tags

Calculating Accuracies

Maximum accuracy

The formulas for calculating accuracies of selection for the same information source are given in the table below. From the table you can see that with only information on the parents, or only on the grand-parents, the accuracy of the EBV can never be as large as what can be achieved with own performance. The maximum accuracy that can be achieved can be determined by assuming a very large n. If n becomes very large, then the maximum rIH that can be achieved with full sib information is equal to 1412, which equals 0.707.

Common environment

If there is information on a group of related animals, for example a group of half sibs, then the animal and its sibs may share the same environment: a common environment. The variance explained by the common environmental effect is indicated by c2. Common environmental effects make it more difficult to disentangle the effect of genetics and environment. The common environmental effect has a negative influence on the accuracy.
 
  view all
Calculating Accuracies

Maximum accuracy

The formulas for calculating accuracies of selection for the same information source are given in the table below. From the table you can see that with only information on the parents, or only on the grand-parents, the accuracy of the EBV can never be as large as what can be achieved with own performance. The maximum accuracy that can be achieved can be determined by assuming a very large n. If n becomes very large, then the maximum rIH that can be achieved with full sib information is equal to 1412, which equals 0.707.

Common environment

If there is information on a group of related animals, for example a group of half sibs, then the animal and its sibs may share the same environment: a common environment. The variance explained by the common environmental effect is indicated by c2. Common environmental effects make it more difficult to disentangle the effect of genetics and environment. The common environmental effect has a negative influence on the accuracy.
 
 
145
Views

Module 5: Ranking the Animals -5.3 Calculation of Accuracies of Breeding Values

Emily posted the article • 0 comments • 145 views • 2017-11-21 07:00 • came from similar tags

Accuracy of Estimated Breeding Values

The accuracy of an EBV gives an indication of how well the EBV resembles the true breeding value. It is therefore an indication of the value of the EBV as a selection criterion. The accuracy of the breeding value estimation represents the correlation between the EBV and the true breeding value and has a value between 0 (inaccurate) and 1 (100% accurate).

Accuracy of Estimated Breeding Values
 

 
Video subtitle:
 
In the previous videos we discussed how breeding values can be estimated.
But how accurate are estimated breeding values?
Or in other words, how close is the estimated breeding value to the true breeding value?
If the estimated breeding value is inaccurate,
we may select the wrong animals as parents for the next generation.
In this video I will explain the accuracy of estimated breeding values
and how it can be calculated.
So the first question is how can we measure the accuracy of estimated breeding values?
This figure shows that the estimated breeding values deviate from the true breeding values:
the so-called prediction errors.
To measure how close the estimated breeding values are to the true breeding values,
we can use the correlation between estimated and true breeding values.
This correlation is called the accuracy and denoted as rIH.
The accuracy can vary between 0 and 1.
In these two examples, the accuracy is 0.51 in the left figure and 0.95 in the right figure.
In other words, the breeding values are more accurate in the right figure than in the left figure.
However, these figures assume that we know the true breeding value of an animal,
while in real life we cannot measure the true breeding value of each animal.
Fortunately, we can mathematically derive the accuracy of estimated breeding values.
For instance in the case of own performance, like milk production of this cow,
we can derive that the accuracy is equal to the square root of the heritability.
So the accuracy is higher when the heritability is higher.
In this table, you find equations to calculate the accuracy for a number of situations:
own performance, information of parents or grandparents
and information of full-sibs, half-sibs, or progeny.
Let’s have a closer look at two examples.
The first example is the case that we want to calculate the accuracy
of a rooster based on his paternal half-sisters or half-sibs.
The equation contains three variables: the number of half-sibs, the heritability
and the ratio of the common environmental variance to the phenotypic variance.
This figure shows that the accuracy increases with the number of half-sibs and with a higher heritability.
In this case, the maximum accuracy is 0.5,
because we only get information about the breeding value of the sire of this rooster
and we do not have any information about his dam and his own mendelian sampling term.
The second example is the case when we want to calculate the accuracy of the
breeding value of this Hereford bull for weaning weight based on his progeny.
This equation contains only two variables, the number of progeny and the heritability.
This figure shows that the accuracy increases when the number of progeny increases
and when the heritability is higher.
Furthermore, we see that the maximum accuracy is approaching one if we have many progeny,
because we get full information about the breeding value of this bull.
So in summary, the accuracy is the correlation between the estimated and the true breeding values.
The accuracy increases with heritability and with the amount of information available.
And we now have a set of equations to calculate the accuracy of estimated breeding values in a number of situations.
These equations can be used to design and optimize your breeding program.
 
 
 
  view all
Accuracy of Estimated Breeding Values

The accuracy of an EBV gives an indication of how well the EBV resembles the true breeding value. It is therefore an indication of the value of the EBV as a selection criterion. The accuracy of the breeding value estimation represents the correlation between the EBV and the true breeding value and has a value between 0 (inaccurate) and 1 (100% accurate).

Accuracy of Estimated Breeding Values
 


 
Video subtitle:
 
In the previous videos we discussed how breeding values can be estimated.
But how accurate are estimated breeding values?
Or in other words, how close is the estimated breeding value to the true breeding value?
If the estimated breeding value is inaccurate,
we may select the wrong animals as parents for the next generation.
In this video I will explain the accuracy of estimated breeding values
and how it can be calculated.
So the first question is how can we measure the accuracy of estimated breeding values?
This figure shows that the estimated breeding values deviate from the true breeding values:
the so-called prediction errors.
To measure how close the estimated breeding values are to the true breeding values,
we can use the correlation between estimated and true breeding values.
This correlation is called the accuracy and denoted as rIH.
The accuracy can vary between 0 and 1.
In these two examples, the accuracy is 0.51 in the left figure and 0.95 in the right figure.
In other words, the breeding values are more accurate in the right figure than in the left figure.
However, these figures assume that we know the true breeding value of an animal,
while in real life we cannot measure the true breeding value of each animal.
Fortunately, we can mathematically derive the accuracy of estimated breeding values.
For instance in the case of own performance, like milk production of this cow,
we can derive that the accuracy is equal to the square root of the heritability.
So the accuracy is higher when the heritability is higher.
In this table, you find equations to calculate the accuracy for a number of situations:
own performance, information of parents or grandparents
and information of full-sibs, half-sibs, or progeny.
Let’s have a closer look at two examples.
The first example is the case that we want to calculate the accuracy
of a rooster based on his paternal half-sisters or half-sibs.
The equation contains three variables: the number of half-sibs, the heritability
and the ratio of the common environmental variance to the phenotypic variance.
This figure shows that the accuracy increases with the number of half-sibs and with a higher heritability.
In this case, the maximum accuracy is 0.5,
because we only get information about the breeding value of the sire of this rooster
and we do not have any information about his dam and his own mendelian sampling term.
The second example is the case when we want to calculate the accuracy of the
breeding value of this Hereford bull for weaning weight based on his progeny.
This equation contains only two variables, the number of progeny and the heritability.
This figure shows that the accuracy increases when the number of progeny increases
and when the heritability is higher.
Furthermore, we see that the maximum accuracy is approaching one if we have many progeny,
because we get full information about the breeding value of this bull.
So in summary, the accuracy is the correlation between the estimated and the true breeding values.
The accuracy increases with heritability and with the amount of information available.
And we now have a set of equations to calculate the accuracy of estimated breeding values in a number of situations.
These equations can be used to design and optimize your breeding program.
 
 
 
 
136
Views

Module 5: Ranking the Animals -5.3 Calculation of Accuracies of Breeding Values

Emily posted the article • 0 comments • 136 views • 2017-11-21 07:00 • came from similar tags

Accuracy

If we would be able to estimate the breeding value with 100% accuracy, the estimated breeding value and the true breeding value (TBV) would be the same. If we were to plot the TBV against the EBV, then all data points would fit perfectly in line. The more the data points deviate from the regression line, the less certain you can be that the EBV indeed is representing the true breeding value: we say that the EBV are less accurate. 

A measure of the EBV accuracy is the correlation between the EBV and the true genetic deviation and has a value between 0 (inaccurate) and 1 (100% accurate). If the correlation between the estimated and true breeding values is 1, then you have managed to create the perfect EBV and the plot of EBV and TBV form a straight line. The more the correlation deviates from 1, the less accurate the EBV are. In that case, EBV and TBV form a cloud around the regression line.
 

 
 
 
Box : plots of true (TBV) and estimated breeding values (EBV) with the perfect regression line if EBV = TBV. On the left is an example of less accurate EBV, indicated by the cloud of data points with correlation between EBV and TBV of 0.76. On the right the EBV are estimated much more accurately and are almost the same as the TBV, resulting in a correlation between EBV and TBV of 0.98. 

In real life, we cannot produce a graph like in this figure because we do not know the true breeding value. But what we can do is estimate the accuracy of the estimated breeding value by equations that have been derived mathematically. view all
Accuracy

If we would be able to estimate the breeding value with 100% accuracy, the estimated breeding value and the true breeding value (TBV) would be the same. If we were to plot the TBV against the EBV, then all data points would fit perfectly in line. The more the data points deviate from the regression line, the less certain you can be that the EBV indeed is representing the true breeding value: we say that the EBV are less accurate. 

A measure of the EBV accuracy is the correlation between the EBV and the true genetic deviation and has a value between 0 (inaccurate) and 1 (100% accurate). If the correlation between the estimated and true breeding values is 1, then you have managed to create the perfect EBV and the plot of EBV and TBV form a straight line. The more the correlation deviates from 1, the less accurate the EBV are. In that case, EBV and TBV form a cloud around the regression line.
 

 
 
 
Box : plots of true (TBV) and estimated breeding values (EBV) with the perfect regression line if EBV = TBV. On the left is an example of less accurate EBV, indicated by the cloud of data points with correlation between EBV and TBV of 0.76. On the right the EBV are estimated much more accurately and are almost the same as the TBV, resulting in a correlation between EBV and TBV of 0.98. 

In real life, we cannot produce a graph like in this figure because we do not know the true breeding value. But what we can do is estimate the accuracy of the estimated breeding value by equations that have been derived mathematically.
149
Views

How Can We Calculate the Response to Selection?

Emily posted the article • 0 comments • 149 views • 2017-11-21 06:53 • came from similar tags

Now that you’ve seen and learnt about the different aspects of the formula to predict response to selection or genetic gain, let’s take an example and do the calculation together. Try to really understand and repeat what dr. Mario Calus does, so that you are able to do the calculations by yourself in the exercises that will follow after this video!
 

video subtitle:
Maximizing genetic gain is one of the focal points of a breeding program.
But how is genetic gain calculated?
Today we will demonstrate this by means of an example.
Let us first repeat the formula used to compute the genetic gain,
which is often also referred to as the response to selection per year.
The response to selection, denoted as capital R, is computed as the product of the selection intensity i,
the accuracy of selection r<sub>IH</sub>, and the genetic standard deviation (sigma A).
Finally, the genetic gain per year is obtained by dividing the response to selection by the generation interval L in years.
Let us consider the following example about running speed in horses, on a 2,000 metre long track.
In this case, the breeding goal is the racing time across 2,000 metres.
Let us assume that we select the 10% best offspring for breeding,
the genetic standard deviation is 3 seconds, the accuracy of selection is 0.24, and the generation interval is 10 years.
Now, the question is: what is the value of ∆G?
As a first step, we compute the response per generation, assuming that the accuracy is 1.
Now we need the value of the selection intensity, given that the proportion of selected animals is 10%.
In a table that gives the selection intensity as function of the proportion of selected animals,
we can find that this is 1.76.
Considering the value of the genetic standard deviation of 3 seconds, we can compute that the response per generation is 5.28 seconds.
As a second step, we replace the accuracy of 1 by its actual value of 0.24.
Keeping the other input parameters as before, we now get a value of 1.27 seconds per generation.
So we can see that having a relatively low accuracy of 0.24 yields a relatively low response,
compared to the maximum possible response with an accuracy of 1.
As a third and final step, we want to compute the genetic gain per year.
This involves dividing the response by the generation interval.
In this case, this is 10 years.
So, finally, we obtain that the genetic gain is 0.127 seconds per year.
So, in this example,
the assumed selection approach is expected to decrease the racing time in 2,000 metre races by 0.127 seconds per year.
 
  view all
Now that you’ve seen and learnt about the different aspects of the formula to predict response to selection or genetic gain, let’s take an example and do the calculation together. Try to really understand and repeat what dr. Mario Calus does, so that you are able to do the calculations by yourself in the exercises that will follow after this video!
 


video subtitle:
Maximizing genetic gain is one of the focal points of a breeding program.
But how is genetic gain calculated?
Today we will demonstrate this by means of an example.
Let us first repeat the formula used to compute the genetic gain,
which is often also referred to as the response to selection per year.
The response to selection, denoted as capital R, is computed as the product of the selection intensity i,
the accuracy of selection r<sub>IH</sub>, and the genetic standard deviation (sigma A).
Finally, the genetic gain per year is obtained by dividing the response to selection by the generation interval L in years.
Let us consider the following example about running speed in horses, on a 2,000 metre long track.
In this case, the breeding goal is the racing time across 2,000 metres.
Let us assume that we select the 10% best offspring for breeding,
the genetic standard deviation is 3 seconds, the accuracy of selection is 0.24, and the generation interval is 10 years.
Now, the question is: what is the value of ∆G?
As a first step, we compute the response per generation, assuming that the accuracy is 1.
Now we need the value of the selection intensity, given that the proportion of selected animals is 10%.
In a table that gives the selection intensity as function of the proportion of selected animals,
we can find that this is 1.76.
Considering the value of the genetic standard deviation of 3 seconds, we can compute that the response per generation is 5.28 seconds.
As a second step, we replace the accuracy of 1 by its actual value of 0.24.
Keeping the other input parameters as before, we now get a value of 1.27 seconds per generation.
So we can see that having a relatively low accuracy of 0.24 yields a relatively low response,
compared to the maximum possible response with an accuracy of 1.
As a third and final step, we want to compute the genetic gain per year.
This involves dividing the response by the generation interval.
In this case, this is 10 years.
So, finally, we obtain that the genetic gain is 0.127 seconds per year.
So, in this example,
the assumed selection approach is expected to decrease the racing time in 2,000 metre races by 0.127 seconds per year.
 
 
123
Views

Causes and Consequences of Trade-Offs(6.4 Trade-Offs in Predicting Genetic Gain )

Emily posted the article • 0 comments • 123 views • 2017-11-21 06:53 • came from similar tags

Now that you are able to perform calculations with the formula to predict genetic gain, let’s take it one step further and dive into the elements of the formula and their relationships. The formula is of course used to predict genetic gain in a given situation, but can also be used to optimise genetic gain by varying the different elements of the formula. However, the different elements of the formula are not independent of each other. In the following clip, dr. Mario Calus will tell you more about this. 
 

 
video subtitle:
 
 
The success of a breeding program is largely determined by the genetic gain per year, denoted by ∆G.
In previous clips, different components involved in ∆G and its computation have been discussed.
The challenge is that several trade-offs exist between the elements of ∆G.
In this lecture we will focus on those trade-offs
and on how to balance them to optimize genetic gain per year.
Let’s start with a brief recollection of the formula for ∆G.
Three of its components, indicated here in blue, are under the breeders’ control.
These are the selection intensity i, the accuracy rIH, and the generation interval L.
The fourth component, the genetic standard deviation, is assumed to have a fixed value.
Optimizing ∆G is a matter of balancing the selection intensity, the accuracy, and the generation interval.
Now we will show an example of a trade-off between the accuracy and the selection intensity.
Consider selection for a carcass traits in pigs,
with a heritability of 30% and a generation interval of 2 years.
The breeding program aims to select 10 animals.
Measuring this carcass trait for an animal, requires that the animal is slaughtered.
But of course, we don’t want to slaughter selection candidates.
Therefore, the trait is measured on a number of half-sibs.
For an individual, we can compute the expected accuracy of its breeding value,
based on the heritability and the number of half-sibs tested.
The formula as shown here, was previously mentioned in module 5.
The figure in this slide shows the relationship between the number of half-sibs tested
and the accuracy, which plateaus towards a value of one half.
All the half-sibs of the selection candidate are kept in a testing facility,
which has a maximum capacity of 5000 individuals.
So this means that the number of selection candidates
multiplied by the number of half-sibs tested per candidate, should not exceed 5000.
In the figure we show the trade-off between the number of selection candidates
and the number of half-sibs tested per candidate.
So for instance we can test 50 half-sibs of 100 candidates,
or we can test 100 half-sibs of 50 candidates.
So, the question is: which numbers will give us the highest genetic gain?
To answer this question, we evaluate the genetic gain for different numbers of selection candidates,
making use of all the other parameters that we know.
In this table we show the expected genetic gain when the number of selection candidates is:
50, 100, 200, or 500.
We can compute and plot the genetic gain for every possible number of selection candidates.
From this plot, we can see that the highest genetic gain is achieved when testing 21 half-sibs for each of a total of 236 selection candidates.
In addition to trade-offs between the selection intensity and the accuracy,
trade-offs can also exist between the accuracy and the generation interval.
Consider for instance a situation in meat sheep,
where a breeding value of a female sheep for a carcass trait may depend on measurements in its progeny.
The accuracy of the breeding value will increase
with every new litter reaching the age of slaughter.
At the same time, however, the generation interval will increase as well, which reduces the genetic gain per year.
Let’s briefly summarize the main messages of this lecture.
The genetic gain depends on three parameters that are under the breeders’ control:
the selection intensity, the accuracy of selection and the generation interval.
Several trade-offs may appear between these parameters.
Optimizing genetic gain per year in a breeding program
therefore requires careful balancing of these parameters.
 
  view all
Now that you are able to perform calculations with the formula to predict genetic gain, let’s take it one step further and dive into the elements of the formula and their relationships. The formula is of course used to predict genetic gain in a given situation, but can also be used to optimise genetic gain by varying the different elements of the formula. However, the different elements of the formula are not independent of each other. In the following clip, dr. Mario Calus will tell you more about this. 
 


 
video subtitle:
 
 
The success of a breeding program is largely determined by the genetic gain per year, denoted by ∆G.
In previous clips, different components involved in ∆G and its computation have been discussed.
The challenge is that several trade-offs exist between the elements of ∆G.
In this lecture we will focus on those trade-offs
and on how to balance them to optimize genetic gain per year.
Let’s start with a brief recollection of the formula for ∆G.
Three of its components, indicated here in blue, are under the breeders’ control.
These are the selection intensity i, the accuracy rIH, and the generation interval L.
The fourth component, the genetic standard deviation, is assumed to have a fixed value.
Optimizing ∆G is a matter of balancing the selection intensity, the accuracy, and the generation interval.
Now we will show an example of a trade-off between the accuracy and the selection intensity.
Consider selection for a carcass traits in pigs,
with a heritability of 30% and a generation interval of 2 years.
The breeding program aims to select 10 animals.
Measuring this carcass trait for an animal, requires that the animal is slaughtered.
But of course, we don’t want to slaughter selection candidates.
Therefore, the trait is measured on a number of half-sibs.
For an individual, we can compute the expected accuracy of its breeding value,
based on the heritability and the number of half-sibs tested.
The formula as shown here, was previously mentioned in module 5.
The figure in this slide shows the relationship between the number of half-sibs tested
and the accuracy, which plateaus towards a value of one half.
All the half-sibs of the selection candidate are kept in a testing facility,
which has a maximum capacity of 5000 individuals.
So this means that the number of selection candidates
multiplied by the number of half-sibs tested per candidate, should not exceed 5000.
In the figure we show the trade-off between the number of selection candidates
and the number of half-sibs tested per candidate.
So for instance we can test 50 half-sibs of 100 candidates,
or we can test 100 half-sibs of 50 candidates.
So, the question is: which numbers will give us the highest genetic gain?
To answer this question, we evaluate the genetic gain for different numbers of selection candidates,
making use of all the other parameters that we know.
In this table we show the expected genetic gain when the number of selection candidates is:
50, 100, 200, or 500.
We can compute and plot the genetic gain for every possible number of selection candidates.
From this plot, we can see that the highest genetic gain is achieved when testing 21 half-sibs for each of a total of 236 selection candidates.
In addition to trade-offs between the selection intensity and the accuracy,
trade-offs can also exist between the accuracy and the generation interval.
Consider for instance a situation in meat sheep,
where a breeding value of a female sheep for a carcass trait may depend on measurements in its progeny.
The accuracy of the breeding value will increase
with every new litter reaching the age of slaughter.
At the same time, however, the generation interval will increase as well, which reduces the genetic gain per year.
Let’s briefly summarize the main messages of this lecture.
The genetic gain depends on three parameters that are under the breeders’ control:
the selection intensity, the accuracy of selection and the generation interval.
Several trade-offs may appear between these parameters.
Optimizing genetic gain per year in a breeding program
therefore requires careful balancing of these parameters.
 
 
143
Views

6.5 The Effect of Mating and Mating and Genetic Gain(Module 6: Response to Selection )

Emily posted the article • 0 comments • 143 views • 2017-11-21 06:53 • came from similar tags

In the previous sections, you learnt how to predict the response to selection. By performing selection, we determine which animals will become parents of the next generation, and which animals will not reproduce at all. However, until now we have not looked into the combinations of parents. This is what we call mating. The central question here is: Which male fits best to a certain selected female animal? Which criteria do we use?

Watch the clip by dr. Piter Bijma to learn more about the process of mating. 
 

 
Video subtitle:
 
 
I guess everyone has some idea of the meaning of “mating”.
But what precisely does “mating” mean in animal breeding?
That is what I will explain in this clip.
Mating refers to the pairing of the selected sires and dams.
So mating occurs after selection.
With selection, we decide which individuals become parents of the next generations.
With mating, in contrast, we decide how the individuals that have already been selected as parents are combined to produce offspring.
Here you see four dogs, two males and two females.
Suppose we have selected those four dogs as parents of the next generation,
and now we want to mate them.
We could, for example, mate Jim with Jill, and Boris with Casey.
Alternatively, we could mate Jim with Casey and Boris with Jill.
Now what would be a good strategy to mate the selected parents?
A common strategy is “random mating”,
where sires and dams are just combined at random.
Random mating is used a lot, and is often a good choice.
However, we can do a bit better.
With random mating, for example, we may accidentally mate closely related individuals,
which would result in highly inbred offspring.
It is better to avoid such matings.
If Jim and Jill descend from the same father, for example, it is better not to mate them.
In this way we can avoid highly inbred offspring.
We can go a bit further and use mating to minimize the inbreeding of the offspring.
This is called minimum-coancestry mating.
With minimum-coancestry mating, the least related sires and dams are mated.
In this table you see the relationships between the sires and dams from the dog example.
The relationship is lowest between Jim and Casey, and between Boris and Jill.
Therefore, to minimize inbreeding in the offspring, we should mate Jim with Casey and Boris with Jill.
So far, we have only considered inbreeding.
However, sometimes we want to choose matings based on traits.
This is the case for so-called optimum traits, where intermediate values are preferred.
For such traits we can use compensatory mating.
Here you see teat length in dairy cattle as an example.
Cows with very short teats are difficult to milk,
whereas cows with very long teats have higher chance of mastitis.
So farmers prefer teats of intermediate length.
In this table, you see compensatory mating for teat length.
Cows with very short teats are mated to bulls that give daughters with very long teats, and vice versa.
In other words, we choose a bull that compensates the trait of the cow.
In this way, we can reduce the chance of getting offspring with extreme teat length.
In conclusion, mating refers to the paring of the sires and dams
that have been selected as parents for the next generation.
While random mating is common, mating can be used to avoid high inbreeding or to compensate for weaknesses of the parents.
  view all
In the previous sections, you learnt how to predict the response to selection. By performing selection, we determine which animals will become parents of the next generation, and which animals will not reproduce at all. However, until now we have not looked into the combinations of parents. This is what we call mating. The central question here is: Which male fits best to a certain selected female animal? Which criteria do we use?

Watch the clip by dr. Piter Bijma to learn more about the process of mating. 
 


 
Video subtitle:
 
 
I guess everyone has some idea of the meaning of “mating”.
But what precisely does “mating” mean in animal breeding?
That is what I will explain in this clip.
Mating refers to the pairing of the selected sires and dams.
So mating occurs after selection.
With selection, we decide which individuals become parents of the next generations.
With mating, in contrast, we decide how the individuals that have already been selected as parents are combined to produce offspring.
Here you see four dogs, two males and two females.
Suppose we have selected those four dogs as parents of the next generation,
and now we want to mate them.
We could, for example, mate Jim with Jill, and Boris with Casey.
Alternatively, we could mate Jim with Casey and Boris with Jill.
Now what would be a good strategy to mate the selected parents?
A common strategy is “random mating”,
where sires and dams are just combined at random.
Random mating is used a lot, and is often a good choice.
However, we can do a bit better.
With random mating, for example, we may accidentally mate closely related individuals,
which would result in highly inbred offspring.
It is better to avoid such matings.
If Jim and Jill descend from the same father, for example, it is better not to mate them.
In this way we can avoid highly inbred offspring.
We can go a bit further and use mating to minimize the inbreeding of the offspring.
This is called minimum-coancestry mating.
With minimum-coancestry mating, the least related sires and dams are mated.
In this table you see the relationships between the sires and dams from the dog example.
The relationship is lowest between Jim and Casey, and between Boris and Jill.
Therefore, to minimize inbreeding in the offspring, we should mate Jim with Casey and Boris with Jill.
So far, we have only considered inbreeding.
However, sometimes we want to choose matings based on traits.
This is the case for so-called optimum traits, where intermediate values are preferred.
For such traits we can use compensatory mating.
Here you see teat length in dairy cattle as an example.
Cows with very short teats are difficult to milk,
whereas cows with very long teats have higher chance of mastitis.
So farmers prefer teats of intermediate length.
In this table, you see compensatory mating for teat length.
Cows with very short teats are mated to bulls that give daughters with very long teats, and vice versa.
In other words, we choose a bull that compensates the trait of the cow.
In this way, we can reduce the chance of getting offspring with extreme teat length.
In conclusion, mating refers to the paring of the sires and dams
that have been selected as parents for the next generation.
While random mating is common, mating can be used to avoid high inbreeding or to compensate for weaknesses of the parents.

 
169
Views

6.6 Long Term Genetic Contributions and Inbreeding > Breeding and Inbreeding

Emily posted the article • 0 comments • 169 views • 2017-11-21 06:53 • came from similar tags

In the previous sections, we looked at selection, at predicting genetic gain and at the process of mating. The process of selection determines which alleles are transmitted to the next generation. Therefore, the choices made in a breeding program will always have consequences for the allele frequencies at the population level. The following clip by dr. Piter Bijma deals with inbreeding at the population level. 

In order to be able to understand this, it is important to recall what inbreeding is about. If you would like to refresh your knowledge on the concept and the consequences of inbreeding, we recommend you go back to module 3 and watch the clips on “Concept of inbreeding” and “Consequences of inbreeding”.
 
 
Video: Inbreeding at the Population Level
 

 
Video subtitle:
 
 
This clip deals with inbreeding at the population level.
In a previous clip, you have seen that mating of relatives leads to inbreeding.
In this pedigree, for example, the dogs Jim and Jill are related, so their offspring Donald is inbred.
Because inbreeding reduces health and fertility, we want to avoid it as much as possible.
However, can we always fully avoid inbreeding?
In this clip, I will explain the mechanisms that determine inbreeding at the population level.
This will show that inbreeding cannot be avoided.
Let us investigate inbreeding at the population level using an example.
Here you see two students, a male and a female.
To see whether they are related, we have to investigate their pedigree.
Together, both students have 4 parents, 8 grandparents, 16 great-grand parents, and so on.
So if we go up the pedigree, the number of ancestors quickly becomes very large,
and soon it will become larger than the population size.
This means that some of the ancestors must be the same individual.
In other words, because the number of ancestors doubles each generation, the two students must have ancestors in common.
Therefore, they must be related.
Now suppose both students like each other, and produce an offspring.
Because the students are related, the offspring must be inbred.
This example, therefore, demonstrates that inbreeding cannot be avoided.
It also implies that the average inbreeding coefficient of individuals in the population must increase over time.
In other words, the average inbreeding level in a population increases over time.
So now we know that inbreeding increases over time.
But how can we measure this increase, and what determines the speed of the increase?
On the population level, the increase of inbreeding is measured per generation, and expressed as the so-called “rate of inbreeding”.
The rate of inbreeding is denoted by the symbol ∆F.
Because inbreeding has negative consequences, breeders try to keep the rate below 1% per generation.
To keep the rate of inbreeding below 1%, we have to understand the factors that determine it.
So what determines the rate of inbreeding?
The most important factor is the population size.
That is, the number of breeding males and females per generation.
We can illustrate this with a simple example: suppose we have a population of N parents.
Together, these N parents carry 2N alleles.
Now suppose we make an offspring by randomly sampling two alleles out of the 2N alleles available.
Then what is the probability that this offspring is inbred?
The offspring is inbred only if it carries two identical alleles.
With 2N alleles, this probability is equal to 1/(2N).
You can see this as follows: whatever allele you sample as the first allele,
the probability that the second allele is the same simply equals 1/(2N).
Therefore, in a simple population, the rate of inbreeding is one divided by two times the population size.
Hence, smaller populations tend to show more inbreeding.
Beware that this equation holds only for simple populations,
where each parent has an equal chance of contributing offspring to the next generation.
However, also in more complex cases, the rate of inbreeding tends to be larger when the population is smaller.
So how many parents do we need to restrict the rate of inbreeding below 1%?
If we have a simple population, we need at least 50 parents per generation.
However, for more complex populations this value may be much larger.
A second important factor that determines inbreeding is the variation in the contribution of parents.
Some parents may contribute many offspring, while others contribute few.
Such variation increases the rate of inbreeding.
Most livestock species, for example, have two sexes, and the contribution of a parent differs between the sexes.
In cattle, for example, a selected bull usually gets more offspring than a selected cow.
A bull, therefore, makes a greater contribution to the next generation than a cow,
and this increases the rate of inbreeding compared to a species of a single sex.
A second reason for variation in contributions is the presence of elite animals.
The winner of the dog show, for example, may get many more offspring than an ordinary dog.
Again, this increases the rate of inbreeding.
Now let us look a bit further into the relationship between inbreeding and contributions.
Suppose we have an ancestor who contributes 10% of the genes in the current population.
How much does this ancestor contribute to the inbreeding?
To answer this question, let us take a sire and dam from the current population, and make an offspring.
Now we can calculate the probability that both genes in the offspring descend from the ancestor.
On average, 10% of the genes in the sire and dam come from the ancestor.
Therefore, the probability that both genes of the offspring descend from the ancestor is equal to the square of 10%, which is 1%.
This is illustrated by the area of the red square on the slide.
This result shows that the inbreeding due to an ancestor depends on the square of the contribution of this ancestor.
With a little mathematics, you can show that the total rate of inbreeding
is equal to the sum of the squared contributions of all ancestors, multiplied by a quarter.
Let us use an example to illustrate the consequences of this equation.
Suppose we have 10 dogs, 5 males and 5 females.
First consider the case where each dog has the same contribution.
In this case, each dog contributes 10%.
If we substitute this value into the equation, we get a rate of inbreeding of 2.5% per generation.
Now consider the case where one elite sire makes a large contribution.
Suppose this sire contributes 46% of the genes, the four other sires each contribute 1%, and the dams still contribute 10% each.
Substituting those values into the equation, gives a rate of inbreeding of 6.65%;
almost three times greater than with equal contributions.
Hence, this example illustrates that unequal contributions increase the rate of inbreeding.
In conclusion: inbreeding cannot be avoided,
small populations tend to show more inbreeding,
and unequal contributions of parents increase the rate of inbreeding.
  view all
In the previous sections, we looked at selection, at predicting genetic gain and at the process of mating. The process of selection determines which alleles are transmitted to the next generation. Therefore, the choices made in a breeding program will always have consequences for the allele frequencies at the population level. The following clip by dr. Piter Bijma deals with inbreeding at the population level. 

In order to be able to understand this, it is important to recall what inbreeding is about. If you would like to refresh your knowledge on the concept and the consequences of inbreeding, we recommend you go back to module 3 and watch the clips on “Concept of inbreeding” and “Consequences of inbreeding”.
 
 
Video: Inbreeding at the Population Level
 


 
Video subtitle:
 
 
This clip deals with inbreeding at the population level.
In a previous clip, you have seen that mating of relatives leads to inbreeding.
In this pedigree, for example, the dogs Jim and Jill are related, so their offspring Donald is inbred.
Because inbreeding reduces health and fertility, we want to avoid it as much as possible.
However, can we always fully avoid inbreeding?
In this clip, I will explain the mechanisms that determine inbreeding at the population level.
This will show that inbreeding cannot be avoided.
Let us investigate inbreeding at the population level using an example.
Here you see two students, a male and a female.
To see whether they are related, we have to investigate their pedigree.
Together, both students have 4 parents, 8 grandparents, 16 great-grand parents, and so on.
So if we go up the pedigree, the number of ancestors quickly becomes very large,
and soon it will become larger than the population size.
This means that some of the ancestors must be the same individual.
In other words, because the number of ancestors doubles each generation, the two students must have ancestors in common.
Therefore, they must be related.
Now suppose both students like each other, and produce an offspring.
Because the students are related, the offspring must be inbred.
This example, therefore, demonstrates that inbreeding cannot be avoided.
It also implies that the average inbreeding coefficient of individuals in the population must increase over time.
In other words, the average inbreeding level in a population increases over time.
So now we know that inbreeding increases over time.
But how can we measure this increase, and what determines the speed of the increase?
On the population level, the increase of inbreeding is measured per generation, and expressed as the so-called “rate of inbreeding”.
The rate of inbreeding is denoted by the symbol ∆F.
Because inbreeding has negative consequences, breeders try to keep the rate below 1% per generation.
To keep the rate of inbreeding below 1%, we have to understand the factors that determine it.
So what determines the rate of inbreeding?
The most important factor is the population size.
That is, the number of breeding males and females per generation.
We can illustrate this with a simple example: suppose we have a population of N parents.
Together, these N parents carry 2N alleles.
Now suppose we make an offspring by randomly sampling two alleles out of the 2N alleles available.
Then what is the probability that this offspring is inbred?
The offspring is inbred only if it carries two identical alleles.
With 2N alleles, this probability is equal to 1/(2N).
You can see this as follows: whatever allele you sample as the first allele,
the probability that the second allele is the same simply equals 1/(2N).
Therefore, in a simple population, the rate of inbreeding is one divided by two times the population size.
Hence, smaller populations tend to show more inbreeding.
Beware that this equation holds only for simple populations,
where each parent has an equal chance of contributing offspring to the next generation.
However, also in more complex cases, the rate of inbreeding tends to be larger when the population is smaller.
So how many parents do we need to restrict the rate of inbreeding below 1%?
If we have a simple population, we need at least 50 parents per generation.
However, for more complex populations this value may be much larger.
A second important factor that determines inbreeding is the variation in the contribution of parents.
Some parents may contribute many offspring, while others contribute few.
Such variation increases the rate of inbreeding.
Most livestock species, for example, have two sexes, and the contribution of a parent differs between the sexes.
In cattle, for example, a selected bull usually gets more offspring than a selected cow.
A bull, therefore, makes a greater contribution to the next generation than a cow,
and this increases the rate of inbreeding compared to a species of a single sex.
A second reason for variation in contributions is the presence of elite animals.
The winner of the dog show, for example, may get many more offspring than an ordinary dog.
Again, this increases the rate of inbreeding.
Now let us look a bit further into the relationship between inbreeding and contributions.
Suppose we have an ancestor who contributes 10% of the genes in the current population.
How much does this ancestor contribute to the inbreeding?
To answer this question, let us take a sire and dam from the current population, and make an offspring.
Now we can calculate the probability that both genes in the offspring descend from the ancestor.
On average, 10% of the genes in the sire and dam come from the ancestor.
Therefore, the probability that both genes of the offspring descend from the ancestor is equal to the square of 10%, which is 1%.
This is illustrated by the area of the red square on the slide.
This result shows that the inbreeding due to an ancestor depends on the square of the contribution of this ancestor.
With a little mathematics, you can show that the total rate of inbreeding
is equal to the sum of the squared contributions of all ancestors, multiplied by a quarter.
Let us use an example to illustrate the consequences of this equation.
Suppose we have 10 dogs, 5 males and 5 females.
First consider the case where each dog has the same contribution.
In this case, each dog contributes 10%.
If we substitute this value into the equation, we get a rate of inbreeding of 2.5% per generation.
Now consider the case where one elite sire makes a large contribution.
Suppose this sire contributes 46% of the genes, the four other sires each contribute 1%, and the dams still contribute 10% each.
Substituting those values into the equation, gives a rate of inbreeding of 6.65%;
almost three times greater than with equal contributions.
Hence, this example illustrates that unequal contributions increase the rate of inbreeding.
In conclusion: inbreeding cannot be avoided,
small populations tend to show more inbreeding,
and unequal contributions of parents increase the rate of inbreeding.
 
380
Views

How to Predict Genetic Gain-Predicting Genetic Gain

Emily posted the article • 0 comments • 380 views • 2017-11-21 06:38 • came from similar tags

The aim of any breeding program is to improve an animal population genetically. In the breeding goal, breeders defined the traits that are important, as well as the direction of change. Usually, the breeder wants to maximize this genetic improvement (called genetic gain or selection response), while minimizing any negative effects. 

But how can we predict the genetic response and which are the factors that contribute to a higher genetic gain? How can you influence these factors in your breeding program? In the video below, dr. John Bastiaansen teaches you how you can predict the genetic gain in a breeding program!
 



About Selection Intensity:
 
In the video, dr. John Bastiaansen explained how genetic gain in a breeding program can be predicted. You will practice the prediction using the formula later on in this module. For now, we would like to focus on and familiarize you with one particular aspect of the formula of genetic gain, which is the selection intensity. 
 

 
 
 
Selection intensity

This is what dr. John Bastiaansen explained in his video about the selection intensity: “Now we come to the selection intensity "i". 
A higher selection intensity means that a smaller percentage of the animals are selected as parents. 
Here we have a population of pigs that is sorted based on their weight.
The selection intensity depends on how many candidates you have and how many parents are needed. 
Selecting only a few parents from the high end of the distribution leads to a big difference in the size of the population.
If more parents are needed, the difference becomes smaller.
To predict genetic gain, we need to calculate the superiority of the parents in phenotypic standard deviation units.
This standardized difference is called the selection intensity, represented by the symbol "i".
Because "i" is standardized, its value depends only on the percentage of animals that is selected.
This is convenient because we can now define "i" independently of the trait that is being selected.
Values of "i" are published in tables like this one here. 
In one column, we look up the percentage of animals that is selected, for instance 10%. 
In the next column, we find the value for i, which is the superiority of the top 10% in standard deviation units, 1.76.

 
You can check this for yourself in the table above, which contains a part of the total table. 
 
 
subtitle:

By selecting the best candidates as parents to produce the next generation, you can improve the genetic level of a population.
This change is called genetic gain.
How much genetic gain we can get, depends on the proportion of the animals that is selected as parents.
It also depends on how accurately you have ranked the animals, and how much genetic variance there is for the trait.
This is the formula for predicting the genetic gain, or delta G.
Delta G tells us how much better the population gets each year.
To calculate genetic gain you multiply the selection intensity i, the accuracy of selection r<sub>IH</sub>,
and the genetic standard deviation sigma A.
Then you divide by the generation interval L.
Let us look at the four parameters in this equation one by one.
We start with a parameter we already know, the accuracy or "r<sub>IH</sub>".
This accuracy tells us how close the estimated breeding values resemble the true breeding values.
In the figure on the right, the estimates are closer to the true values, therefore the accuracy is higher.
Higher accuracy leads to higher genetic gain.
Another familiar parameter is sigma A, the additive genetic standard deviation.
When the genetic standard deviation is larger, the best animals are further away from the mean.
This also leads to higher genetic gain.
Now we come to the selection intensity "i".
A higher selection intensity means that a smaller percentage of the animals are selected as parents.
Here we have a population of pigs that is sorted based on their weight.
The selection intensity depends on how many candidates you have and how many parents are needed.
Selecting only a few parents from the high end of the distribution leads to a big difference in size with the population.
When more parents are needed, the difference becomes smaller.
To predict genetic gain, we need to calculate the superiority of the parents in phenotypic standard deviation units.
This standardized difference is called the selection intensity, represented by the symbol "i".
Because "i" is standardized, its value depends only on the percentage of animals that is selected.
This is convenient because we can now define "i" independent of the trait that is being selected.
Values of "i" are published in tables like this one here.
In one column we look up the percentage of animals that is selected, for instance 10%.
In the next column we find the value for i, which is the superiority of the top 10% in standard deviation units, 1.76.
When we multiply i, r<sub>IH</sub>, and sigma A we predict the genetic gain per generation.
To present the genetic gain as the improvement per year we divide by the generation interval "L".
L is the average age of selected parents when their offspring are born.
The generation interval varies a lot between species, and can also change depending on how you design your breeding program.
With these four parameters we have a general equation that predicts the genetic gain per year,
based on the selection intensity, the accuracy, the genetic standard deviation, and the generation interval.
 
  view all
The aim of any breeding program is to improve an animal population genetically. In the breeding goal, breeders defined the traits that are important, as well as the direction of change. Usually, the breeder wants to maximize this genetic improvement (called genetic gain or selection response), while minimizing any negative effects. 

But how can we predict the genetic response and which are the factors that contribute to a higher genetic gain? How can you influence these factors in your breeding program? In the video below, dr. John Bastiaansen teaches you how you can predict the genetic gain in a breeding program!
 




About Selection Intensity:
 
In the video, dr. John Bastiaansen explained how genetic gain in a breeding program can be predicted. You will practice the prediction using the formula later on in this module. For now, we would like to focus on and familiarize you with one particular aspect of the formula of genetic gain, which is the selection intensity. 
 

 
 
 
Selection intensity

This is what dr. John Bastiaansen explained in his video about the selection intensity: “Now we come to the selection intensity "i". 
A higher selection intensity means that a smaller percentage of the animals are selected as parents. 
Here we have a population of pigs that is sorted based on their weight.
The selection intensity depends on how many candidates you have and how many parents are needed. 
Selecting only a few parents from the high end of the distribution leads to a big difference in the size of the population.
If more parents are needed, the difference becomes smaller.
To predict genetic gain, we need to calculate the superiority of the parents in phenotypic standard deviation units.
This standardized difference is called the selection intensity, represented by the symbol "i".
Because "i" is standardized, its value depends only on the percentage of animals that is selected.
This is convenient because we can now define "i" independently of the trait that is being selected.
Values of "i" are published in tables like this one here. 
In one column, we look up the percentage of animals that is selected, for instance 10%. 
In the next column, we find the value for i, which is the superiority of the top 10% in standard deviation units, 1.76.

 
You can check this for yourself in the table above, which contains a part of the total table. 
 
 
subtitle:

By selecting the best candidates as parents to produce the next generation, you can improve the genetic level of a population.
This change is called genetic gain.
How much genetic gain we can get, depends on the proportion of the animals that is selected as parents.
It also depends on how accurately you have ranked the animals, and how much genetic variance there is for the trait.
This is the formula for predicting the genetic gain, or delta G.
Delta G tells us how much better the population gets each year.
To calculate genetic gain you multiply the selection intensity i, the accuracy of selection r<sub>IH</sub>,
and the genetic standard deviation sigma A.
Then you divide by the generation interval L.
Let us look at the four parameters in this equation one by one.
We start with a parameter we already know, the accuracy or "r<sub>IH</sub>".
This accuracy tells us how close the estimated breeding values resemble the true breeding values.
In the figure on the right, the estimates are closer to the true values, therefore the accuracy is higher.
Higher accuracy leads to higher genetic gain.
Another familiar parameter is sigma A, the additive genetic standard deviation.
When the genetic standard deviation is larger, the best animals are further away from the mean.
This also leads to higher genetic gain.
Now we come to the selection intensity "i".
A higher selection intensity means that a smaller percentage of the animals are selected as parents.
Here we have a population of pigs that is sorted based on their weight.
The selection intensity depends on how many candidates you have and how many parents are needed.
Selecting only a few parents from the high end of the distribution leads to a big difference in size with the population.
When more parents are needed, the difference becomes smaller.
To predict genetic gain, we need to calculate the superiority of the parents in phenotypic standard deviation units.
This standardized difference is called the selection intensity, represented by the symbol "i".
Because "i" is standardized, its value depends only on the percentage of animals that is selected.
This is convenient because we can now define "i" independent of the trait that is being selected.
Values of "i" are published in tables like this one here.
In one column we look up the percentage of animals that is selected, for instance 10%.
In the next column we find the value for i, which is the superiority of the top 10% in standard deviation units, 1.76.
When we multiply i, r<sub>IH</sub>, and sigma A we predict the genetic gain per generation.
To present the genetic gain as the improvement per year we divide by the generation interval "L".
L is the average age of selected parents when their offspring are born.
The generation interval varies a lot between species, and can also change depending on how you design your breeding program.
With these four parameters we have a general equation that predicts the genetic gain per year,
based on the selection intensity, the accuracy, the genetic standard deviation, and the generation interval.
 
 
152
Views

Module 6: Response to Selection > 6.1 Introduction > Welcome to Response to Selection!

Emily posted the article • 0 comments • 152 views • 2017-11-21 06:38 • came from similar tags

Welcome to Module 6 on Response to Selection! Now that you have learnt how you can rank the animals in your population, to decide which ones to choose to produce the next generation, it is time to proceed to the next step in the breeding program. 

Imagine a horse owner wants to breed faster racing horses, or a dog breeder wants to reduce inbreeding in the dog population, or maybe there is a chicken farmer who formulates a breeding goal to increasing the amount of eggs in laying hens. Imagine that they have just finished ranking their animals based on the estimated breeding values and are about to start producing the next generation. Of course, they are curious what they can expect in the next generation. How much faster than their parents will the new generation of racing horses be? How much can inbreeding be reduced in one generation? How many more eggs will the new generation of chickens be able to produce? Or, in other words, how can we predict the genetic gain that can be achieved? What will the selection response be?

In this Module 6 you will learn how to answer these questions!

Set-up of module 6

In this module, we teach you about response to selection. You will learn:

6.2 How to predict genetic gain

Which information do you need to be able to predict genetic gain and why?

6.3 Calculating response to selection

Here, you will be introduced to the formula to calculate response to selection or genetic gain yourself!

6.4 Trade-offs in predicting gain

Which choices influence the amount of genetic gain? How do they interact?

6.5 The effect of mating

Genetic gain is influenced not only by the selection of a ‘pool’ of parents, but also by the combinations of parents that are made. You will learn more about this in the section on mating. 

6.6 Long term genetic contributions

Is it wise to use the very best bull to mate with all cows of one generation? Why or why not?

6.7 Your own breeding program

Apply what you learnt in this module to your own breeding program with your animal species of choice! 

6.8 Module exam

Test your knowledge on module 6!

 
 
Image: Breeding program. The red circle shows the step on “Predicting selection response” that module 6 is about. 
 
 
 
  view all
Welcome to Module 6 on Response to Selection! Now that you have learnt how you can rank the animals in your population, to decide which ones to choose to produce the next generation, it is time to proceed to the next step in the breeding program. 

Imagine a horse owner wants to breed faster racing horses, or a dog breeder wants to reduce inbreeding in the dog population, or maybe there is a chicken farmer who formulates a breeding goal to increasing the amount of eggs in laying hens. Imagine that they have just finished ranking their animals based on the estimated breeding values and are about to start producing the next generation. Of course, they are curious what they can expect in the next generation. How much faster than their parents will the new generation of racing horses be? How much can inbreeding be reduced in one generation? How many more eggs will the new generation of chickens be able to produce? Or, in other words, how can we predict the genetic gain that can be achieved? What will the selection response be?

In this Module 6 you will learn how to answer these questions!

Set-up of module 6

In this module, we teach you about response to selection. You will learn:

6.2 How to predict genetic gain

Which information do you need to be able to predict genetic gain and why?

6.3 Calculating response to selection

Here, you will be introduced to the formula to calculate response to selection or genetic gain yourself!

6.4 Trade-offs in predicting gain

Which choices influence the amount of genetic gain? How do they interact?

6.5 The effect of mating

Genetic gain is influenced not only by the selection of a ‘pool’ of parents, but also by the combinations of parents that are made. You will learn more about this in the section on mating. 

6.6 Long term genetic contributions

Is it wise to use the very best bull to mate with all cows of one generation? Why or why not?

6.7 Your own breeding program

Apply what you learnt in this module to your own breeding program with your animal species of choice! 

6.8 Module exam

Test your knowledge on module 6!

 
 
Image: Breeding program. The red circle shows the step on “Predicting selection response” that module 6 is about. 
 
 
 
 
149
Views

What Have We Learned-Module 7: Animal Breeding in Practice

Emily posted the article • 0 comments • 149 views • 2017-11-21 06:30 • came from similar tags

In this video we will look back at the different steps of designing a breeding program and highlight what we learned about animal breeding along the way. During the design of your own breeding program you will have encountered a number of questions. For many of these questions you had to make a decision. These decisions should now be based on the animal breeding principles you learned in the different modules.
 
 

 
 
subtitle:
 
In the first module we gave you an introduction to animal breeding.
You learnt that there are 7 steps in setting up a breeding program.
All steps are important and you need to pay attention to all of them.
Try to memorize them!
After completing this module you should:
Understand the history of animal breeding.
Have an idea why animal breeding is performed.
and what we mean by “balanced breeding”.
You should also be able to describe the seven steps to set up a breeding program
In module two you learned about the breeding goal.
The breeding goal is a list of traits with breeding values that you want to improve.
The breeding goal should include all traits of importance,
irrespective of their heritability.
Each trait has a weight
that reflects its importance in the production system and the desired direction of change.
Traits can be weighted by economic values or “desired gains” weights.
After completing this module you are able to describe
the six characteristics of a breeding goal
and to Derive economic values for traits in a breeding goal in simple examples.
Module 3 was about collection of information
and the importance of family relationships.
Collection of information is vital to a breeding program.
There are two types of information:
phenotypes and family relationships.
Family relationships between animals are very important
and can be used to quantify additive genetic relationships and inbreeding.
Controlling inbreeding is important when relationships are used for breeding value estimation,
because related animals tend to have similar breeding values.
In this module you learned how to calculate inbreeding
and interpret these values and their consequences.
Now that you have completed this module
you are able to understand the concept of inbreeding.
And you are also able to Describe the consequences of inbreeding.
Furthermore, you can calculate additive genetic relationships
and inbreeding coefficients of animals based on a simple pedigree.
In module 4 we introduced the genetic models that we use to estimate breeding values.
Genetic models allow you to distinguish between genetic and non-genetic influences on phenotypes.
The parameters to describe the relative influence of these factors are heritability, repeatability
and common environmental effects.
Genetic models are the tools to rank the animals,
so that we can select the best.
This is a very important activity in breeding programs.
After completion of this module you will now know and understand:
the two most important genetic models: the transmission model
and the Mendelian sampling model.
You should also know what the following parameters mean:
heritability, repeatability and common environment ratio.
In module 5, we showed you how you can estimate breeding values.
You learned the skills and tools to estimate breeding values
and calculate accuracies in simple situations.
Then you made estimates in some more complex situations
where information is coming from multiple sources.
The important thing here is to know how to interpret the accuracies of the breeding values
and how to use these in making selection decisions.
At the end of the module,
you can estimate breeding values and predicted performance in simple situations,
and also calculate accuracy of the  breeding values.
Furthermore you can describe how phenotypes of animals from different farms can be used in breeding value estimation (BLUP)
In module 6 we introduced the so-called breeders equation to calculate the response to selection.
After ranking the animals you make selection decisions.
Different decisions lead to different outcomes in genetic improvement.
The breeders equation shows how intensity of selection,
accuracy, genetic variance of a trait, and the generation interval interact.
By using the breeders equation, you are able to predict the outcomes of different options
and to evaluate the trade-offs between the factors that influence genetic gain.
After completion of this module,
you are now able to calculate response to selection in simplified breeding schemes.
And to understand and describe the consequences of trade-offs between selection intensity,
accuracy and generation interval.
Module 7 was about animal breeding in practice.
Ownership of animals and reproductive capacity
are the main drivers of the design of breeding programs
and the dissemination of genetic improvement.
Breeding programs for chickens to grow meat globally
or chickens for local production systems can be different,
but the steps to design the breeding program are the same.
In module 7 we presented a practical example of a breeding program for chicken in Ethiopia.
Study the example carefully and you will see that we use the same principles taught in this course.
At the end of this module you should know the key factors that affect the structure of a breeding program.
And understand that breeding programs can have different structures. view all
In this video we will look back at the different steps of designing a breeding program and highlight what we learned about animal breeding along the way. During the design of your own breeding program you will have encountered a number of questions. For many of these questions you had to make a decision. These decisions should now be based on the animal breeding principles you learned in the different modules.
 
 


 
 
subtitle:
 
In the first module we gave you an introduction to animal breeding.
You learnt that there are 7 steps in setting up a breeding program.
All steps are important and you need to pay attention to all of them.
Try to memorize them!
After completing this module you should:
Understand the history of animal breeding.
Have an idea why animal breeding is performed.
and what we mean by “balanced breeding”.
You should also be able to describe the seven steps to set up a breeding program
In module two you learned about the breeding goal.
The breeding goal is a list of traits with breeding values that you want to improve.
The breeding goal should include all traits of importance,
irrespective of their heritability.
Each trait has a weight
that reflects its importance in the production system and the desired direction of change.
Traits can be weighted by economic values or “desired gains” weights.
After completing this module you are able to describe
the six characteristics of a breeding goal
and to Derive economic values for traits in a breeding goal in simple examples.
Module 3 was about collection of information
and the importance of family relationships.
Collection of information is vital to a breeding program.
There are two types of information:
phenotypes and family relationships.
Family relationships between animals are very important
and can be used to quantify additive genetic relationships and inbreeding.
Controlling inbreeding is important when relationships are used for breeding value estimation,
because related animals tend to have similar breeding values.
In this module you learned how to calculate inbreeding
and interpret these values and their consequences.
Now that you have completed this module
you are able to understand the concept of inbreeding.
And you are also able to Describe the consequences of inbreeding.
Furthermore, you can calculate additive genetic relationships
and inbreeding coefficients of animals based on a simple pedigree.
In module 4 we introduced the genetic models that we use to estimate breeding values.
Genetic models allow you to distinguish between genetic and non-genetic influences on phenotypes.
The parameters to describe the relative influence of these factors are heritability, repeatability
and common environmental effects.
Genetic models are the tools to rank the animals,
so that we can select the best.
This is a very important activity in breeding programs.
After completion of this module you will now know and understand:
the two most important genetic models: the transmission model
and the Mendelian sampling model.
You should also know what the following parameters mean:
heritability, repeatability and common environment ratio.
In module 5, we showed you how you can estimate breeding values.
You learned the skills and tools to estimate breeding values
and calculate accuracies in simple situations.
Then you made estimates in some more complex situations
where information is coming from multiple sources.
The important thing here is to know how to interpret the accuracies of the breeding values
and how to use these in making selection decisions.
At the end of the module,
you can estimate breeding values and predicted performance in simple situations,
and also calculate accuracy of the  breeding values.
Furthermore you can describe how phenotypes of animals from different farms can be used in breeding value estimation (BLUP)
In module 6 we introduced the so-called breeders equation to calculate the response to selection.
After ranking the animals you make selection decisions.
Different decisions lead to different outcomes in genetic improvement.
The breeders equation shows how intensity of selection,
accuracy, genetic variance of a trait, and the generation interval interact.
By using the breeders equation, you are able to predict the outcomes of different options
and to evaluate the trade-offs between the factors that influence genetic gain.
After completion of this module,
you are now able to calculate response to selection in simplified breeding schemes.
And to understand and describe the consequences of trade-offs between selection intensity,
accuracy and generation interval.
Module 7 was about animal breeding in practice.
Ownership of animals and reproductive capacity
are the main drivers of the design of breeding programs
and the dissemination of genetic improvement.
Breeding programs for chickens to grow meat globally
or chickens for local production systems can be different,
but the steps to design the breeding program are the same.
In module 7 we presented a practical example of a breeding program for chicken in Ethiopia.
Study the example carefully and you will see that we use the same principles taught in this course.
At the end of this module you should know the key factors that affect the structure of a breeding program.
And understand that breeding programs can have different structures.
123
Views

Factors that Influence the Structure

Emily posted the article • 0 comments • 123 views • 2017-11-21 06:25 • came from similar tags

The structure of breeding programs differs substantially between animal species. An important reason is the differences that exist in reproductive rate. Sows and hens can produce many more offspring than cows and mares, and some fish species can produce even more. Another important reason is the ownership of the animals which may even be different for the males and females of certain species.

Reproductive rate

Reproductive rates range from one offspring every few years to many thousands of offspring per year or even per month. In addition, the rate often differs between males and females. Males often have higher reproductive rates than females. This leads some programs to focus more on selection in males. The number of males needed is smaller which leads to higher selection intensities. An added advantage is that with fewer animals, the cost of keeping the breeding stock becomes smaller. 

Sometimes the biological reproduction rates can be enhanced by technological interventions. In dairy cattle breeding, artificial reproduction techniques such as artificial insemination (AI) and in vitro fertilization, in combination with embryo implantation, are well-developed and widely used in the breeding population. This provides the opportunity to produce large numbers of offspring from superior sires and dams, and disseminate the genes of these superior animals widely in the production population.

Ownership of breeding animals

In animal species that are kept for companionship or leisure purposes, control over the breeding program by the breed associations is very loose because the animals are owned by private owners. These private owners each decide individually on the breeding of their animals. In some species, like the major dairy cattle breeds, the males are owned by a breeding company or a group of breeders, and the females are privately owned. In both cases the breeding company or association depends on the breeding decisions of the private owners. Breeders can only completely control the breeding decisions when they own both the males and females in the breeding program.  view all
The structure of breeding programs differs substantially between animal species. An important reason is the differences that exist in reproductive rate. Sows and hens can produce many more offspring than cows and mares, and some fish species can produce even more. Another important reason is the ownership of the animals which may even be different for the males and females of certain species.

Reproductive rate

Reproductive rates range from one offspring every few years to many thousands of offspring per year or even per month. In addition, the rate often differs between males and females. Males often have higher reproductive rates than females. This leads some programs to focus more on selection in males. The number of males needed is smaller which leads to higher selection intensities. An added advantage is that with fewer animals, the cost of keeping the breeding stock becomes smaller. 

Sometimes the biological reproduction rates can be enhanced by technological interventions. In dairy cattle breeding, artificial reproduction techniques such as artificial insemination (AI) and in vitro fertilization, in combination with embryo implantation, are well-developed and widely used in the breeding population. This provides the opportunity to produce large numbers of offspring from superior sires and dams, and disseminate the genes of these superior animals widely in the production population.

Ownership of breeding animals

In animal species that are kept for companionship or leisure purposes, control over the breeding program by the breed associations is very loose because the animals are owned by private owners. These private owners each decide individually on the breeding of their animals. In some species, like the major dairy cattle breeds, the males are owned by a breeding company or a group of breeders, and the females are privately owned. In both cases the breeding company or association depends on the breeding decisions of the private owners. Breeders can only completely control the breeding decisions when they own both the males and females in the breeding program. 
137
Views

Structures of Breeding Programs

Emily posted the article • 0 comments • 137 views • 2017-11-21 06:25 • came from similar tags

The difference in reproductive rate and in ownership of animals leads to different structures of breeding programs. Here we present 3 different structures that are often found in animal breeding.

A flat structure
An open nucleus structure
A closed nucleus 

A flat breeding structure

In breeding programs with a flat structure, nearly all animals can potentially participate in breeding. In most cases, the breed association only has a strong vote in the selection of the males for breeding. Results of shows where animals are judged largely determine which males are used. This often results in a few “champion” males that are very widely used as sires in the whole population. This type of selection takes place in most breeds of dogs, sheep, and horses. All of these species tend to only perform directional selection in the males, where in some breeds the males are selected using more information than in others. 

An open nucleus structure

When the breeder owns both the males and at least a limited number of females, the structure becomes a nucleus. Selection among the females, and the males, is under the control of the breeder. Privately owned animals (usually females) can be invited to become part of the nucleus, which is why it is called an open nucleus. The best examples of open nucleus structures are the breeding programs for dairy cattle.

A closed nucleus structure

In the main breeding programs for pig and poultry production (pork, eggs and broiler meat), the commercial breeding companies have full control over all breeding activities. They own a limited number of breeding animals (i.e. their selection lines). In these lines, the companies determine the breeding goal, organize the data collection and the breeding value estimation, and decide which animals are selected and mated to produce a new generation. These pure line animals are not the ones that produce the final product: animals producing the meat or eggs for the market. The final product often consists of a cross between three or four different lines. After the breeding program is established, no new animals are introduced in the program. The mostly globally-operating breeding companies have different selection lines. These selection lines are separate breeding populations. To produce animals to lay eggs or to grow meat, contracted farmers multiply and cross the selection lines in a pyramidal structure.
 
 

 
 
Image: Pyramidal structure of a breeding program where selective breeding occurs in the top and farmers are supplied animals via multiplication steps in the middle of the pyramid.
 
 
  view all
The difference in reproductive rate and in ownership of animals leads to different structures of breeding programs. Here we present 3 different structures that are often found in animal breeding.

A flat structure
An open nucleus structure
A closed nucleus 

A flat breeding structure

In breeding programs with a flat structure, nearly all animals can potentially participate in breeding. In most cases, the breed association only has a strong vote in the selection of the males for breeding. Results of shows where animals are judged largely determine which males are used. This often results in a few “champion” males that are very widely used as sires in the whole population. This type of selection takes place in most breeds of dogs, sheep, and horses. All of these species tend to only perform directional selection in the males, where in some breeds the males are selected using more information than in others. 

An open nucleus structure

When the breeder owns both the males and at least a limited number of females, the structure becomes a nucleus. Selection among the females, and the males, is under the control of the breeder. Privately owned animals (usually females) can be invited to become part of the nucleus, which is why it is called an open nucleus. The best examples of open nucleus structures are the breeding programs for dairy cattle.

A closed nucleus structure

In the main breeding programs for pig and poultry production (pork, eggs and broiler meat), the commercial breeding companies have full control over all breeding activities. They own a limited number of breeding animals (i.e. their selection lines). In these lines, the companies determine the breeding goal, organize the data collection and the breeding value estimation, and decide which animals are selected and mated to produce a new generation. These pure line animals are not the ones that produce the final product: animals producing the meat or eggs for the market. The final product often consists of a cross between three or four different lines. After the breeding program is established, no new animals are introduced in the program. The mostly globally-operating breeding companies have different selection lines. These selection lines are separate breeding populations. To produce animals to lay eggs or to grow meat, contracted farmers multiply and cross the selection lines in a pyramidal structure.
 
 

 
 
Image: Pyramidal structure of a breeding program where selective breeding occurs in the top and farmers are supplied animals via multiplication steps in the middle of the pyramid.
 
 
 
181
Views

The Example of Broiler Chickens

Emily posted the article • 0 comments • 181 views • 2017-11-21 06:25 • came from similar tags

In commercial pigs, poultry, and fish programs, selection takes place in the top of the breeding program. Especially in pigs and chicken, and sometimes in fish, a few “multiplying generations” are needed to disseminate the selection response obtained in the top of the structure to the production animals. The (small) breeding population in the nucleus, the generations needed to increase the number of animals with improved genetic values, and the (large) production population is often depicted in the form of a pyramid. The figure below shows the structure of a poultry (broiler) breeding program. This pyramid has some more detail than the one in the previous section, but the general idea is the same. 

Within the commercial breeding scheme for broilers the selection response is realized in specialized lines. Usually a four-way cross is applied to produce the final broilers that are grown for their meat. Two lines are selected for fertility and egg quality (the “female” lines) and two lines for growth traits (the “male” lines). In the broiler structure the selection takes place at the top of the pyramid in the pure lines, resulting in a limited number of genetically superior animals. These superior animals are used in the pyramid as Great Grandparents. When the selected Great Grandparents are multiplied in sufficient numbers, they produce Grand-parents (see table 2). These Grand-parents are then crossed with grandparents from another line. The Grand-parent crosses result in F1 animals that are called Parents. These Parents are then mated to a F1 parent from cross between two other lines to produce the broilers. The pure line and the F1 animals (Parents) are often owned by the breeding company to protect the characteristics of their lines and the realized genetic improvement in these lines. 

In table 1, an example is given of the number of broilers that can be produced from 1 single hen in the nucleus. This pyramid involves 5 tiers. Taking all tiers together, one hen in the nucleus can have 2,880,000 descendants as broilers in the commercial tier. Parents in each tier are used for one year. This means that the genetic merit of the nucleus animals is expressed in the great grand-parent stock after one year, in the grand parent stock after two years and reaches 2,880,000 broilers after 5 years.

Table 1: Example of pyramidal structure for the dam lines of broilers involving 5 tiers and the number of offspring in each tier that descend from one hen in the nucleus.
  view all
In commercial pigs, poultry, and fish programs, selection takes place in the top of the breeding program. Especially in pigs and chicken, and sometimes in fish, a few “multiplying generations” are needed to disseminate the selection response obtained in the top of the structure to the production animals. The (small) breeding population in the nucleus, the generations needed to increase the number of animals with improved genetic values, and the (large) production population is often depicted in the form of a pyramid. The figure below shows the structure of a poultry (broiler) breeding program. This pyramid has some more detail than the one in the previous section, but the general idea is the same. 

Within the commercial breeding scheme for broilers the selection response is realized in specialized lines. Usually a four-way cross is applied to produce the final broilers that are grown for their meat. Two lines are selected for fertility and egg quality (the “female” lines) and two lines for growth traits (the “male” lines). In the broiler structure the selection takes place at the top of the pyramid in the pure lines, resulting in a limited number of genetically superior animals. These superior animals are used in the pyramid as Great Grandparents. When the selected Great Grandparents are multiplied in sufficient numbers, they produce Grand-parents (see table 2). These Grand-parents are then crossed with grandparents from another line. The Grand-parent crosses result in F1 animals that are called Parents. These Parents are then mated to a F1 parent from cross between two other lines to produce the broilers. The pure line and the F1 animals (Parents) are often owned by the breeding company to protect the characteristics of their lines and the realized genetic improvement in these lines. 

In table 1, an example is given of the number of broilers that can be produced from 1 single hen in the nucleus. This pyramid involves 5 tiers. Taking all tiers together, one hen in the nucleus can have 2,880,000 descendants as broilers in the commercial tier. Parents in each tier are used for one year. This means that the genetic merit of the nucleus animals is expressed in the great grand-parent stock after one year, in the grand parent stock after two years and reaches 2,880,000 broilers after 5 years.

Table 1: Example of pyramidal structure for the dam lines of broilers involving 5 tiers and the number of offspring in each tier that descend from one hen in the nucleus.
 
153
Views

The Horro Breeding Program

Emily posted the article • 0 comments • 153 views • 2017-11-21 06:25 • came from similar tags

 In the next 12 minutes, Dr. Tadelle Dessie will explain the history of this breeding program and why it is needed. He explains how all the steps of breeding program design were followed in developing this program. After the clip, you will answer a few questions about the structure of the Horro breeding program and why it was developed in the way explained in the clip. 
 
 



subtitle:
 
 
In this clip, we will show what a real breeding program for chickens looks like.
We will take you through the design step-by-step and explain in each step which choices were made, and why.
After seeing this clip,
you should have a good idea of the resources needed to set up and carry out a breeding program in practice.
In many developing countries, poultry offers poor people a pathway out of poverty.
A joint project was developed and implemented by Ethiopian Institute of Agriculture Research,
International Livestock Research Institute, and Wageningen University and Research.
The project was funded by the Koepon Foundation.
The aim was to improve the productivity of the village poultry production system in Ethiopia.
The breeding program was established in 2008 and focused on Horro chicken.
Horro is an indigenous chicken type named after the geographic region of
origin, located in the western part of Ethiopia near the Blue Nile gorge.
The population is highly diverse, both genetically as well as phenotypically.
The aim of the program was to make Horro chickens more profitable for the poor people in those regions
and to conserve the existing genetic diversity.
The program started with a survey to understand the production system and needs,
and constraints of smallholder chicken farmers in Ethiopia.
A total of 225 households were interviewed.
We wanted to understand the socio-economic characteristics of the production environments in different geographic regions,
and to understand the important functions of chickens in their households.
The questionnaire was also designed to collect general information on village poultry production, such as:
production objectives and goals, flock structure, breed choice and trait preferences, market preferences of specific traits,
and farmers' selection criteria and practices.
We found that most smallholder production systems maintained birds under scavenging regimens
in the backyards with little or no supplemental feeding,
no health care and very high mortality.
The main purpose of keeping chickens was the sale of eggs and live animals,
and the occasional slaughter of animals for home consumption.
The results of this study in Ethiopia showed that farmers across all geographic regions
rated growth and egg production as the traits they wanted to be improved the most.
The results from the survey were used to define the breeding goal "traits" and their relative importance in the production environment.
Production of eggs for consumption is the principal function of chickens in most regions,
followed by source of income from sales of eggs and live animals and meat for home consumption.
The market price of chickens is primarily dictated by weight,
but farmers rated growth of males and number of eggs followed by growth of females as traits they would like to see improved.
Therefore, the breeding goal was to develop a productive breed based on indigenous chicken genetic resources
that can survive and reproduce in the production environment of village farmers.
The breeding goal traits were increased egg production (number),
increased body weight, decreased age at first egg and increased survival.
The study was done at the Ethiopian Institute of Agricultural Research in Debre Zeit, Ethiopia.
The base population was established from 3,000 eggs purchased from various locations
in the Horro region, in Ethiopia.
Twenty sires (male chickens) and 260 dams (female chickens) were successfully hatched and raised.
After 18 weeks of age, a total of 240 females and 24 males were picked randomly and transferred to layer houses.
There they were kept in groups of 1 male with 10 females in separate pens.
Each pen had a trap nest for individual recording of egg production and pedigree.
Since the breeding program aimed at increasing body weight as well as at increasing egg production,
collection of information was done accordingly.
Phenotypic traits recorded were body weights at hatch and on weeks 2, 6, 8, 12 and 16, for males and females.
Age at first egg was recorded for each hen and egg production was recorded every month until 44 weeks of age.
The cumulative monthly egg production records were used for analysis.
Mortality was recorded when it happened.
The breeding program was started before parameter estimates for preferred traits were available.
As a result, selection was based on individual performance,
called "own performance" or "mass selection", until the 8th generation.
In the 8th generation, genetic parameters of growth
and egg production traits were estimated using genetic models implemented in statistical software.
Heritability for body weight at 16 weeks was 0.37, and for cumulative egg number it was 0.32.
These heritabilities correspond to an accuracy of 0.56 and 0.49 respectively
when using mass selection.
In 2017, the breeding program was in generation 9
and genetic parameters have been estimated based on full pedigree of 8 generations.
From now on, selection will be based on estimated breeding values rather than on mass selection.
The estimated breeding value indicates the value of the animal with respect to the breeding goal:
the lowest ones will have a negative effect on the breeding goal traits and the highest ones will improve breeding goal traits.
Birds will be ranked based on estimated breeding values and that ranking will be used to select future parents.
When, for example, a group of male birds with the highest breeding value for egg yield
are selected as cocks for the next generations,
their daughters will produce more eggs than the present generation of hens.
Selection creates progress in breeding goal traits.
The testing capacity of the station was limited in the number of pens with trap houses.
Therefore, each generation approximately 600 males and 600 females were produced
as selection candidates and recorded for body weight and egg production.
Females are selected based on own performance for egg production.
Males are selected based on the performance of their sisters.
Initially, 30 males and 300 females were selected to produce the next generation.
This corresponds to selected proportions of approximately 10-20% in the males and 50-60% in the females.
Each male was then mated to ten females.
Every generation of pure line Horro birds was kept to be used as parents for the coming generations
and for distribution of chicks to other centers.
This so-called nucleus flock is being kept at the Debre Zeit Agricultural Research Center.
Currently, the breed is being tested in five distinct agro-ecological zones by private sector multipliers and brooders.
In total 12,600 animals have been distributed for this test.
The aim is to compare the performance of the chickens in the different regions,
which show large differences in altitude, rainfall and temperature.
So far, cross breeding has not been considered in the breeding program.
Developing pure line Horro is the target of the breeding program, but in the future cross breeding might be considered.
Evaluation of the breeding program was conducted when the program was in generation 8.
We estimated breeding values of all generations to evaluate the trend of changes over the generations.
The genetic trends were positive for both traits under selection from generation 4 and 6 onwards.
A summary of the results of the chicken breeding program is shown here.
It shows that by generation 8, survival has improved from less than 50%
in the base generation to almost 100% in generation 8.
Body weight per bird at 16 weeks had increased substantially from 550 gram to 1100 gram.
Egg production tripled from 64 eggs per hen per year in the base generation to 172 eggs per hen per year by generation 8.
You have now seen a real-life example of the use of the breeding program scheme.
The example of the Horro chicken shows that a breeding program can be started with even modest resources.
In this breeding program, we used a relatively small laying house
which put limits on the testing capacity and the selection intensity.
Selection was on own performance which requires relatively little statistical skills.
Yet, the results after a few generations of selection show that
the improved Horro will have a major impact on the household economy of smallholder farmers.
The main objective of the breeding program in the future is to develop
a sustainable multiplication and delivery system by developing public-private partnerships (PPP). view all
 In the next 12 minutes, Dr. Tadelle Dessie will explain the history of this breeding program and why it is needed. He explains how all the steps of breeding program design were followed in developing this program. After the clip, you will answer a few questions about the structure of the Horro breeding program and why it was developed in the way explained in the clip. 
 
 




subtitle:
 
 
In this clip, we will show what a real breeding program for chickens looks like.
We will take you through the design step-by-step and explain in each step which choices were made, and why.
After seeing this clip,
you should have a good idea of the resources needed to set up and carry out a breeding program in practice.
In many developing countries, poultry offers poor people a pathway out of poverty.
A joint project was developed and implemented by Ethiopian Institute of Agriculture Research,
International Livestock Research Institute, and Wageningen University and Research.
The project was funded by the Koepon Foundation.
The aim was to improve the productivity of the village poultry production system in Ethiopia.
The breeding program was established in 2008 and focused on Horro chicken.
Horro is an indigenous chicken type named after the geographic region of
origin, located in the western part of Ethiopia near the Blue Nile gorge.
The population is highly diverse, both genetically as well as phenotypically.
The aim of the program was to make Horro chickens more profitable for the poor people in those regions
and to conserve the existing genetic diversity.
The program started with a survey to understand the production system and needs,
and constraints of smallholder chicken farmers in Ethiopia.
A total of 225 households were interviewed.
We wanted to understand the socio-economic characteristics of the production environments in different geographic regions,
and to understand the important functions of chickens in their households.
The questionnaire was also designed to collect general information on village poultry production, such as:
production objectives and goals, flock structure, breed choice and trait preferences, market preferences of specific traits,
and farmers' selection criteria and practices.
We found that most smallholder production systems maintained birds under scavenging regimens
in the backyards with little or no supplemental feeding,
no health care and very high mortality.
The main purpose of keeping chickens was the sale of eggs and live animals,
and the occasional slaughter of animals for home consumption.
The results of this study in Ethiopia showed that farmers across all geographic regions
rated growth and egg production as the traits they wanted to be improved the most.
The results from the survey were used to define the breeding goal "traits" and their relative importance in the production environment.
Production of eggs for consumption is the principal function of chickens in most regions,
followed by source of income from sales of eggs and live animals and meat for home consumption.
The market price of chickens is primarily dictated by weight,
but farmers rated growth of males and number of eggs followed by growth of females as traits they would like to see improved.
Therefore, the breeding goal was to develop a productive breed based on indigenous chicken genetic resources
that can survive and reproduce in the production environment of village farmers.
The breeding goal traits were increased egg production (number),
increased body weight, decreased age at first egg and increased survival.
The study was done at the Ethiopian Institute of Agricultural Research in Debre Zeit, Ethiopia.
The base population was established from 3,000 eggs purchased from various locations
in the Horro region, in Ethiopia.
Twenty sires (male chickens) and 260 dams (female chickens) were successfully hatched and raised.
After 18 weeks of age, a total of 240 females and 24 males were picked randomly and transferred to layer houses.
There they were kept in groups of 1 male with 10 females in separate pens.
Each pen had a trap nest for individual recording of egg production and pedigree.
Since the breeding program aimed at increasing body weight as well as at increasing egg production,
collection of information was done accordingly.
Phenotypic traits recorded were body weights at hatch and on weeks 2, 6, 8, 12 and 16, for males and females.
Age at first egg was recorded for each hen and egg production was recorded every month until 44 weeks of age.
The cumulative monthly egg production records were used for analysis.
Mortality was recorded when it happened.
The breeding program was started before parameter estimates for preferred traits were available.
As a result, selection was based on individual performance,
called "own performance" or "mass selection", until the 8th generation.
In the 8th generation, genetic parameters of growth
and egg production traits were estimated using genetic models implemented in statistical software.
Heritability for body weight at 16 weeks was 0.37, and for cumulative egg number it was 0.32.
These heritabilities correspond to an accuracy of 0.56 and 0.49 respectively
when using mass selection.
In 2017, the breeding program was in generation 9
and genetic parameters have been estimated based on full pedigree of 8 generations.
From now on, selection will be based on estimated breeding values rather than on mass selection.
The estimated breeding value indicates the value of the animal with respect to the breeding goal:
the lowest ones will have a negative effect on the breeding goal traits and the highest ones will improve breeding goal traits.
Birds will be ranked based on estimated breeding values and that ranking will be used to select future parents.
When, for example, a group of male birds with the highest breeding value for egg yield
are selected as cocks for the next generations,
their daughters will produce more eggs than the present generation of hens.
Selection creates progress in breeding goal traits.
The testing capacity of the station was limited in the number of pens with trap houses.
Therefore, each generation approximately 600 males and 600 females were produced
as selection candidates and recorded for body weight and egg production.
Females are selected based on own performance for egg production.
Males are selected based on the performance of their sisters.
Initially, 30 males and 300 females were selected to produce the next generation.
This corresponds to selected proportions of approximately 10-20% in the males and 50-60% in the females.
Each male was then mated to ten females.
Every generation of pure line Horro birds was kept to be used as parents for the coming generations
and for distribution of chicks to other centers.
This so-called nucleus flock is being kept at the Debre Zeit Agricultural Research Center.
Currently, the breed is being tested in five distinct agro-ecological zones by private sector multipliers and brooders.
In total 12,600 animals have been distributed for this test.
The aim is to compare the performance of the chickens in the different regions,
which show large differences in altitude, rainfall and temperature.
So far, cross breeding has not been considered in the breeding program.
Developing pure line Horro is the target of the breeding program, but in the future cross breeding might be considered.
Evaluation of the breeding program was conducted when the program was in generation 8.
We estimated breeding values of all generations to evaluate the trend of changes over the generations.
The genetic trends were positive for both traits under selection from generation 4 and 6 onwards.
A summary of the results of the chicken breeding program is shown here.
It shows that by generation 8, survival has improved from less than 50%
in the base generation to almost 100% in generation 8.
Body weight per bird at 16 weeks had increased substantially from 550 gram to 1100 gram.
Egg production tripled from 64 eggs per hen per year in the base generation to 172 eggs per hen per year by generation 8.
You have now seen a real-life example of the use of the breeding program scheme.
The example of the Horro chicken shows that a breeding program can be started with even modest resources.
In this breeding program, we used a relatively small laying house
which put limits on the testing capacity and the selection intensity.
Selection was on own performance which requires relatively little statistical skills.
Yet, the results after a few generations of selection show that
the improved Horro will have a major impact on the household economy of smallholder farmers.
The main objective of the breeding program in the future is to develop
a sustainable multiplication and delivery system by developing public-private partnerships (PPP).
155
Views

Module 7: Animal Breeding in Practice

Emily posted the article • 0 comments • 155 views • 2017-11-21 06:25 • came from similar tags

Welcome to the last module, in which we will look at animal breeding in practice. In the previous parts of the course, you learned about the tools and theory needed to design a breeding program. An important consideration in setting up a breeding program is how you are going to provide farmers with the genetically-improved animals. This is where you need to combine the biological features of your species and the needs of the owners of the animals. The structure of breeding programs can differ substantially between animal species and sometimes also between breeds. The reproductive rate is very different between species and this has an impact on what is possible when designing a program. Also, the ownership of animals can be different. In some species, the breeding animals are owned by the breeder. But in other species they are privately owned and the breeding organization can only give breeding advice while the owners decide. 

Breeding programs differ enormously in the number of genetically-improved animals they need to provide. For instance, the number of chickens or pigs that are kept for producing eggs and meat worldwide is very high. To disseminate the genetic progress of a breeding program in pigs and chickens to all these farmers requires a multiplication structure. In dairy cattle, the number of cows is also high, but one bull can produce a large number of semen doses to inseminate many cows therefore multiplication is not needed. On the other hand, some breeding programs serve a small population. You can think of more rare cattle, goat or sheep breeds that are only kept locally or breeds of companion animals that are kept by a small number of owners. 

Setup of module 7

In this module, you will find the following topics:

7.2 The structure of breeding programs

What are the important factors and how do they affect the structure of a breeding program?

7.3 A global breeding program

Here the breeding structure for a large cattle breed, Holstein Frisian, is introduced as an example of a breeding program that serves farmers worldwide.

7.4 A local breeding program

What is important when breeding for local conditions? We see the example of breeding for village chicken production in Ethiopia.  

7.5 Wrap-up: What have we learned in this course 

We will have a look back at the course and highlight what we have learned. We will look at some examples from the discussion forum and connect them to the genetic principles taught along this course. 

7.6 Your own breeding program

Reflect on the breeding program you designed during this course. Does it resemble one of the examples of existing breeding programs presented in this module? 

7.7 Module exam

Test your knowledge on module 7.
  view all
Welcome to the last module, in which we will look at animal breeding in practice. In the previous parts of the course, you learned about the tools and theory needed to design a breeding program. An important consideration in setting up a breeding program is how you are going to provide farmers with the genetically-improved animals. This is where you need to combine the biological features of your species and the needs of the owners of the animals. The structure of breeding programs can differ substantially between animal species and sometimes also between breeds. The reproductive rate is very different between species and this has an impact on what is possible when designing a program. Also, the ownership of animals can be different. In some species, the breeding animals are owned by the breeder. But in other species they are privately owned and the breeding organization can only give breeding advice while the owners decide. 

Breeding programs differ enormously in the number of genetically-improved animals they need to provide. For instance, the number of chickens or pigs that are kept for producing eggs and meat worldwide is very high. To disseminate the genetic progress of a breeding program in pigs and chickens to all these farmers requires a multiplication structure. In dairy cattle, the number of cows is also high, but one bull can produce a large number of semen doses to inseminate many cows therefore multiplication is not needed. On the other hand, some breeding programs serve a small population. You can think of more rare cattle, goat or sheep breeds that are only kept locally or breeds of companion animals that are kept by a small number of owners. 

Setup of module 7

In this module, you will find the following topics:

7.2 The structure of breeding programs

What are the important factors and how do they affect the structure of a breeding program?

7.3 A global breeding program

Here the breeding structure for a large cattle breed, Holstein Frisian, is introduced as an example of a breeding program that serves farmers worldwide.

7.4 A local breeding program

What is important when breeding for local conditions? We see the example of breeding for village chicken production in Ethiopia.  

7.5 Wrap-up: What have we learned in this course 

We will have a look back at the course and highlight what we have learned. We will look at some examples from the discussion forum and connect them to the genetic principles taught along this course. 

7.6 Your own breeding program

Reflect on the breeding program you designed during this course. Does it resemble one of the examples of existing breeding programs presented in this module? 

7.7 Module exam

Test your knowledge on module 7.
 
117
Views

What is a Breeding Value?

Emily posted the article • 0 comments • 117 views • 2017-11-21 06:09 • came from similar tags

What is a Breeding Value?

A breeding value is nothing more than a value that you give to a particular animal to indicate its value for breeding in a certain breeding program. This means that the breeding value depends on the traits you are looking at, which subsequently depends on the traits that you have defined as important for your breeding program. A breeding value is defined as a deviation from the population mean, meaning that animals with a positive breeding value have genetic potential that is better than the population average, and animals with a negative breeding value are less valuable than the population average. 

When you have determined the breeding values for a certain group of animals for a certain (combination of) trait(s), you will be able to rank the animals according to these breeding values. For example, if you want to have larger animals, you can rank the animals based on their breeding value for the trait “body size” and you can select the ones with the highest breeding value as parents for the next generation of animals. This enables you to select the best animals, those that you want to breed with in order to have an improved next generation!

Now you will get more explanation on the concept of breeding values and we will challenge you to estimate breeding values yourself.
 
This image shows Horro chickens at the Debrezeit research station in Ethiopia, with their estimated breeding values.
  view all
What is a Breeding Value?

A breeding value is nothing more than a value that you give to a particular animal to indicate its value for breeding in a certain breeding program. This means that the breeding value depends on the traits you are looking at, which subsequently depends on the traits that you have defined as important for your breeding program. A breeding value is defined as a deviation from the population mean, meaning that animals with a positive breeding value have genetic potential that is better than the population average, and animals with a negative breeding value are less valuable than the population average. 

When you have determined the breeding values for a certain group of animals for a certain (combination of) trait(s), you will be able to rank the animals according to these breeding values. For example, if you want to have larger animals, you can rank the animals based on their breeding value for the trait “body size” and you can select the ones with the highest breeding value as parents for the next generation of animals. This enables you to select the best animals, those that you want to breed with in order to have an improved next generation!

Now you will get more explanation on the concept of breeding values and we will challenge you to estimate breeding values yourself.
 
This image shows Horro chickens at the Debrezeit research station in Ethiopia, with their estimated breeding values.
 
116
Views

How to apply for oneacreland.com certification for your business.

oneacrelandadmin posted the article • 0 comments • 116 views • 2017-11-07 17:02 • came from similar tags

Step 1:Enter the  homepage of oneacreland.com and click the upper right corner image ,it's right of green post button.
 

Step 2:click the little Edit button in the middle of webpage.

Step 3:Around the upper right corner,you can see Apply for certification,then click it.

Step 4:upload your certification documents in the form and submit.and wait for approve.
 
Method 2: Juttst click the rul :https://www.oneacreland.com/%3 ... rify/ view all
Step 1:Enter the  homepage of oneacreland.com and click the upper right corner image ,it's right of green post button.
 

Step 2:click the little Edit button in the middle of webpage.

Step 3:Around the upper right corner,you can see Apply for certification,then click it.

Step 4:upload your certification documents in the form and submit.and wait for approve.
 
Method 2: Juttst click the rul :https://www.oneacreland.com/%3 ... rify/
181
Views

How to grow avocado?

HowgrowTV posted the article • 0 comments • 181 views • 2017-11-07 16:40 • came from similar tags

 
 
 

 
subtitle:


[Music] almost everything you've been told about how to choose an avocado how to ripen it and how to cut it is wrong but we've come straight to the source California family that's been farming avocados for decades and they are about to school on America's trendiest fruit avocados are an ancient Mexican fruit they weren't even grown in California until the 1900s and it took generations for American eaters to really embrace them first there was a name the Aztecs called them a lock-up which means testicle fruit American farmers tried alligator pear and butter pear finally they went with avocado the second issue was sweetness who ever liked a fruit though wasn't sweet avocados are like olives they get their flavor from natural oil not sugar in fact the first person to ever eat an avocado was a brave soul these things are rock solid on the tree and they will never ever soften until they come off by California law avocados not allowed to be picked until they reach at least 8 percent oil content if they're picked before that will never soften yeah I'm a geek mm-hmm yeah but no fork button over there okay and yeah yeah okay all right okay it's really it's difficult to see these because they're green right merriday the leaves are green and the avocados are green how long does it take to do a whole tree fondos minuto oh la la la la I love uh-huh drinks I mean look so it would take him 30 minutes to do this whole tree it would take me 90 minutes to do this okay see for the blade against the the stem and then you cut and it falls into the bag okay okay that looks like it it's different on the perfect to the worst do they get anything this would take me a year to do they would fire me in a heartbeat the curve of these blades right across the top of the avocado so they're perfect perfectly designed for this especially for collectors like me that is the easiest part of the job thank you the whole family has been farming this land for over 40 years and the oldest trees are over 40 feet tall they grow Hass avocados also for days bacon and Reed [Music] I'm on my way to meet Mimi hold to get all her avocado tips and tricks' me this is beautiful first stop busting the big mess on how to choose an avocado okay Mimi there are hacks all over the internet that you can tell a ripe avocado by picking out this little nub is that true no that's not true this little nub or the button is actually a piece of the stem and the stem and the skin protect the fruit once you remove either the stem or the skin then the air the oxygen can get into the avocado and turn it brown this part will probably get riper quicker and when they get it home they're going to be mad because I'll have to cut this end off and eat the rest of yeah so don't do that don't ruin my avocado so the only way of telling if they're ripe is to seal it and you're looking for just to barely give okay not be mushy then it's over not rock-hard either okay alright perfect for every moment the best way to choose an avocado Mimi says is to buy a firm green one and ripen it yourself on the kitchen counter avocados should never go in the fridge the cold changes their flavor you wouldn't put your olive oil in the fridge would you then Mimi gave me the skinny on how to best remove the flesh okay so some people think that you should just take a spoon and scoop it out that's what I do yeah and it's okay if you want to eat it that way hmm but if you want to get all the nutrients and make sure that you don't get any of the bad spots it's better to just peel it away and then you get a beautiful piece of fruit that was amazing it came off so easily I rarely see this darker green color because it usually comes away with the peel it's so good it's creamy it's bright its fruity you know you forget that avvocato is a suit like an apple like a pear it's obvious like something this other category I'm tempted to dig right in let's have a do after you an avocado farm is like no other farm I've ever been to the mature trees have grown so big it's like walking through a magical forest the ground is thick with fallen leaves I have to duck around in under branches in March the trees are laden with mature fruit but there are also buds lots of tiny buds ready to bloom and become next year's crop 99% of what Mimi's family now grows is Hass why because that's what the market demands the California avocado industry started with the fuerte but it's got a very thin skin so it's more easily bruised the bumpier thicker skins Hass and take a lot more knocks without showing blemishes and since we want avocados no matter where we live these can be shipped from California or Mexico without much law back on the farms the Holts family faces all kinds of challenges from insects to strong winter winds that knock the fruit off the tree but the biggest issue is keeping their trees hydrated extended drought has caused the state to ration water to farmers who say it's nearly impossible for them to care for their trees with that little water some like the Holtz's have drilled their own wells others have had to stump their trees it's a heartbreaking sight to see these once lush beautiful trees cut down to the stump as stumps they require much less water it's a tough decision for farmers it means shrinking their profits for several years but the amazing thing about avocado trees is that they can recover they can grow back and the ones that we grow from old stumps grow more vigorously it's inspiring new hope grown from old [Music] view all
 
 
 


 
subtitle:


[Music] almost everything you've been told about how to choose an avocado how to ripen it and how to cut it is wrong but we've come straight to the source California family that's been farming avocados for decades and they are about to school on America's trendiest fruit avocados are an ancient Mexican fruit they weren't even grown in California until the 1900s and it took generations for American eaters to really embrace them first there was a name the Aztecs called them a lock-up which means testicle fruit American farmers tried alligator pear and butter pear finally they went with avocado the second issue was sweetness who ever liked a fruit though wasn't sweet avocados are like olives they get their flavor from natural oil not sugar in fact the first person to ever eat an avocado was a brave soul these things are rock solid on the tree and they will never ever soften until they come off by California law avocados not allowed to be picked until they reach at least 8 percent oil content if they're picked before that will never soften yeah I'm a geek mm-hmm yeah but no fork button over there okay and yeah yeah okay all right okay it's really it's difficult to see these because they're green right merriday the leaves are green and the avocados are green how long does it take to do a whole tree fondos minuto oh la la la la I love uh-huh drinks I mean look so it would take him 30 minutes to do this whole tree it would take me 90 minutes to do this okay see for the blade against the the stem and then you cut and it falls into the bag okay okay that looks like it it's different on the perfect to the worst do they get anything this would take me a year to do they would fire me in a heartbeat the curve of these blades right across the top of the avocado so they're perfect perfectly designed for this especially for collectors like me that is the easiest part of the job thank you the whole family has been farming this land for over 40 years and the oldest trees are over 40 feet tall they grow Hass avocados also for days bacon and Reed [Music] I'm on my way to meet Mimi hold to get all her avocado tips and tricks' me this is beautiful first stop busting the big mess on how to choose an avocado okay Mimi there are hacks all over the internet that you can tell a ripe avocado by picking out this little nub is that true no that's not true this little nub or the button is actually a piece of the stem and the stem and the skin protect the fruit once you remove either the stem or the skin then the air the oxygen can get into the avocado and turn it brown this part will probably get riper quicker and when they get it home they're going to be mad because I'll have to cut this end off and eat the rest of yeah so don't do that don't ruin my avocado so the only way of telling if they're ripe is to seal it and you're looking for just to barely give okay not be mushy then it's over not rock-hard either okay alright perfect for every moment the best way to choose an avocado Mimi says is to buy a firm green one and ripen it yourself on the kitchen counter avocados should never go in the fridge the cold changes their flavor you wouldn't put your olive oil in the fridge would you then Mimi gave me the skinny on how to best remove the flesh okay so some people think that you should just take a spoon and scoop it out that's what I do yeah and it's okay if you want to eat it that way hmm but if you want to get all the nutrients and make sure that you don't get any of the bad spots it's better to just peel it away and then you get a beautiful piece of fruit that was amazing it came off so easily I rarely see this darker green color because it usually comes away with the peel it's so good it's creamy it's bright its fruity you know you forget that avvocato is a suit like an apple like a pear it's obvious like something this other category I'm tempted to dig right in let's have a do after you an avocado farm is like no other farm I've ever been to the mature trees have grown so big it's like walking through a magical forest the ground is thick with fallen leaves I have to duck around in under branches in March the trees are laden with mature fruit but there are also buds lots of tiny buds ready to bloom and become next year's crop 99% of what Mimi's family now grows is Hass why because that's what the market demands the California avocado industry started with the fuerte but it's got a very thin skin so it's more easily bruised the bumpier thicker skins Hass and take a lot more knocks without showing blemishes and since we want avocados no matter where we live these can be shipped from California or Mexico without much law back on the farms the Holts family faces all kinds of challenges from insects to strong winter winds that knock the fruit off the tree but the biggest issue is keeping their trees hydrated extended drought has caused the state to ration water to farmers who say it's nearly impossible for them to care for their trees with that little water some like the Holtz's have drilled their own wells others have had to stump their trees it's a heartbreaking sight to see these once lush beautiful trees cut down to the stump as stumps they require much less water it's a tough decision for farmers it means shrinking their profits for several years but the amazing thing about avocado trees is that they can recover they can grow back and the ones that we grow from old stumps grow more vigorously it's inspiring new hope grown from old [Music]

124
Views

How to grow SEEDLESS Watermelon

HowgrowTV posted the article • 0 comments • 124 views • 2017-11-07 16:40 • came from similar tags

 

 
 
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131
Views

How to grow blueberry and how the blueberry was tamed.

HowgrowTV posted the article • 0 comments • 131 views • 2017-11-07 16:40 • came from similar tags

 

 
subtitle:


yeah [Music] if I could nominate one fruit to be the national fruit of the United States it would be the blueberry sorry Apple American we spear sleeve guard our independence we cherish our freedom for even known to be a bit wild let's go with that because that my friends is also the spirit of the blueberry even though it's native to North America even though it's been growing here for thousands of years it remains totally untamed until very recently you know my grandmother never even saw a blueberry as a young woman and she ran a fruit stand in Brooklyn it wasn't until the early 1940s that farmed blueberries really took off nationwide before that if you wanted blueberries you had to find and pick them in the wild so why was it so hard to farm the blueberry to understand that we have to find out blueberries how does it grow our investigation starts with story Pine Barrens of New Jersey because official state fruit is the blueberry this is one small village the first place of the global blueberry business today at the National Historic Site and home to a big annual blueberry festival a century ago it was the first place anywhere to commercially farm the highbush blueberry wait wait stop the music we're not going to whitewash history to fully appreciate the blueberries place in American culture we have to go back to the huge role it played in the lives of our native people for then the blueberry was food it was medicine it was a spiritual symbol in fact they called them star berries for their perfect five pointed star at the blossom end they were a gift from the Great Spirit from groups to indigenous people use every part of the blueberry bush they brewed a tea for women in childbirth they boiled the blueberries down into a thick cough syrup they also dried them so they could be eaten to the long lean winter month the waves of European immigrants who came to this country embrace this new fruit but none of them is deeply at the Native American people it wasn't until 1911 that blueberries got serious attention again this time from the daughter of a cranberry farmer she lived right here at White's bog then New Jersey's largest cranberry farm Elizabeth Coleman white a heroine in the male-dominated stories of American agriculture she had the vision to expand her father's cranberry operation to include blueberries in the summer and so she invited Frederick Colville a botanist who had just made a groundbreaking blueberry discovery previously people had dug up wild blueberry bushes and replanted them in their best soil they nurtured them like they would any other fruit crop only to watch them die Koval figured out a strange but fundamental secret blueberries demand highly acidic soil silhouette can't support most other crops and Jersey's barren Pinelands were perfect for blueberries they grew wild everywhere but farming is all about growing a consistent crop so white and Cole set out to find the best of the wild blueberries that they could then cultivate and eventually crossbreed I should probably note here that there's not just one kind of blueberry just like there are many kinds of apples there are blueberries with different colors sizes tastes and textures white and distant opens to search the woods for large berries she named each plant they choose to cultivate after the person found it now to grow a whole field of rubles white and coal will use the same cloning a technique that's used today for that we're heading to Atlantic blueberry Company once the world's largest blueberry farm it's still the largest in New Jersey the US by the way is the worldwide leader in cultivated blueberries while Canada is tops for wild one what's the difference wild berries grow on low bushes found wild then fertilized and cared for like farmed one but we're following the story of the cultivated high Bush which provides the lion's share of the world's fresh blueberry the life of a blueberry bush begins in the nursery small cuttings from a chosen variety are planted and nurtured until they're strong enough to be transferred to the field a modest harvest can take five years but a bush bears fruit for up to 50 blueberries are born in the spring after the bush is blooming with bell-shaped flower you can see what the star shape at the tips of their petal when the berries emerge they're the lightest of green then they deepen into reddish pink and finally into their famous dusty blue to extend the season most farms grow at least three different blueberries ones that ripen early midseason and late so if you think your blueberries taste different throughout the summer you're right you learn all the same variety but there's an even deeper secret here the best blueberries ones with flavor that would knock your socks off they are not sold in stores the big farms don't grow them they're too risky the berries are too delicate for the bushes too sensitive but you might find these tasty ones at farmers markets they're also available in seed catalogs so you can grow your own that means you can pop these little powerhouses of vitamin C and a-plus antioxidants whenever you like when it's time to harvest blueberries don't make it easy they don't all ripen at the same time on the bush so Pickers need to harvest with as much care as we be seen taking only the right list of berries just to get something on is difficult okay ready gentlemen and it's a gentle I'm watching a gentle roll of the thumb that gets these off Oh Apple see that I'm not good [Music] [Applause] these guys have to have the lightest of hand this sort of frosted color of the blueberry is a protective coating for the bloom and if you touch them too much they turn really dark like that which means that the coating is off and it means that the shelf-life of these berries is cut by two or three days [Music] I really don't call them Pickers I call them professional harvester there's this idea that anybody can come out here and they're going to come up with a with a great quality berry I want to have no you don't want to see inside my bucket I know look at them look can I just work yeah you're gonna have a speaker got a good job I am NOT getting the hang of this and it was a very sold fresh or harvested by hand but usually after to picking machines do a final sweep shaking the bushes to release the remaining berry since they may suffer a few knobs they go straight to the freezer to be sold as frozen berries meanwhile hand picked berries hit the sorting line a color scanner weeds out under ripe berries anything that isn't blue these may go into juice purees even pet food the berries then drop onto a pressure plate softer over ripe berries moves slower than firm one so they rejected from the line and often wind up as frozen thanks to the pioneering work done right here in New Jersey a century ago blueberries are now farmed all over the world from New Zealand to the Netherlands and the antioxidant craze has helped global production triple in the last decade alone it's a huge accomplishment for a wild little American berry or maybe it was destiny after all the Native Americans think that blueberry was a divine gift and so did one of our most American of authors when I see as now in climbing one of our Hills huckleberry and blueberry bushes bent to the ground with fruit I think of them as fruits fit to grow on the most Olympian or heaven pointing Hill it does not occur to you at first that where such thoughts are suggested is Mount Olympus and that you who taste these berries are of God why and his only royal moment should man abdicate his throne [Music] wait before you go I have one small request we are getting closer and closer to 100,000 subscribers if all of you just asked one friend one person to subscribe to this channel then we would smash through 100,000 and if you're not subscribed go ahead and do it quick click that subscribe where is it is it here and there click that subscribe button wherever it is the more subscribers we have on this channel the more resources we have to make more videos so go do it do it let's get pick up your phone picked a text a friend right now Texas what yeah okay alright let's do this guy's thank you high five high five view all
 


 
subtitle:


yeah [Music] if I could nominate one fruit to be the national fruit of the United States it would be the blueberry sorry Apple American we spear sleeve guard our independence we cherish our freedom for even known to be a bit wild let's go with that because that my friends is also the spirit of the blueberry even though it's native to North America even though it's been growing here for thousands of years it remains totally untamed until very recently you know my grandmother never even saw a blueberry as a young woman and she ran a fruit stand in Brooklyn it wasn't until the early 1940s that farmed blueberries really took off nationwide before that if you wanted blueberries you had to find and pick them in the wild so why was it so hard to farm the blueberry to understand that we have to find out blueberries how does it grow our investigation starts with story Pine Barrens of New Jersey because official state fruit is the blueberry this is one small village the first place of the global blueberry business today at the National Historic Site and home to a big annual blueberry festival a century ago it was the first place anywhere to commercially farm the highbush blueberry wait wait stop the music we're not going to whitewash history to fully appreciate the blueberries place in American culture we have to go back to the huge role it played in the lives of our native people for then the blueberry was food it was medicine it was a spiritual symbol in fact they called them star berries for their perfect five pointed star at the blossom end they were a gift from the Great Spirit from groups to indigenous people use every part of the blueberry bush they brewed a tea for women in childbirth they boiled the blueberries down into a thick cough syrup they also dried them so they could be eaten to the long lean winter month the waves of European immigrants who came to this country embrace this new fruit but none of them is deeply at the Native American people it wasn't until 1911 that blueberries got serious attention again this time from the daughter of a cranberry farmer she lived right here at White's bog then New Jersey's largest cranberry farm Elizabeth Coleman white a heroine in the male-dominated stories of American agriculture she had the vision to expand her father's cranberry operation to include blueberries in the summer and so she invited Frederick Colville a botanist who had just made a groundbreaking blueberry discovery previously people had dug up wild blueberry bushes and replanted them in their best soil they nurtured them like they would any other fruit crop only to watch them die Koval figured out a strange but fundamental secret blueberries demand highly acidic soil silhouette can't support most other crops and Jersey's barren Pinelands were perfect for blueberries they grew wild everywhere but farming is all about growing a consistent crop so white and Cole set out to find the best of the wild blueberries that they could then cultivate and eventually crossbreed I should probably note here that there's not just one kind of blueberry just like there are many kinds of apples there are blueberries with different colors sizes tastes and textures white and distant opens to search the woods for large berries she named each plant they choose to cultivate after the person found it now to grow a whole field of rubles white and coal will use the same cloning a technique that's used today for that we're heading to Atlantic blueberry Company once the world's largest blueberry farm it's still the largest in New Jersey the US by the way is the worldwide leader in cultivated blueberries while Canada is tops for wild one what's the difference wild berries grow on low bushes found wild then fertilized and cared for like farmed one but we're following the story of the cultivated high Bush which provides the lion's share of the world's fresh blueberry the life of a blueberry bush begins in the nursery small cuttings from a chosen variety are planted and nurtured until they're strong enough to be transferred to the field a modest harvest can take five years but a bush bears fruit for up to 50 blueberries are born in the spring after the bush is blooming with bell-shaped flower you can see what the star shape at the tips of their petal when the berries emerge they're the lightest of green then they deepen into reddish pink and finally into their famous dusty blue to extend the season most farms grow at least three different blueberries ones that ripen early midseason and late so if you think your blueberries taste different throughout the summer you're right you learn all the same variety but there's an even deeper secret here the best blueberries ones with flavor that would knock your socks off they are not sold in stores the big farms don't grow them they're too risky the berries are too delicate for the bushes too sensitive but you might find these tasty ones at farmers markets they're also available in seed catalogs so you can grow your own that means you can pop these little powerhouses of vitamin C and a-plus antioxidants whenever you like when it's time to harvest blueberries don't make it easy they don't all ripen at the same time on the bush so Pickers need to harvest with as much care as we be seen taking only the right list of berries just to get something on is difficult okay ready gentlemen and it's a gentle I'm watching a gentle roll of the thumb that gets these off Oh Apple see that I'm not good [Music] [Applause] these guys have to have the lightest of hand this sort of frosted color of the blueberry is a protective coating for the bloom and if you touch them too much they turn really dark like that which means that the coating is off and it means that the shelf-life of these berries is cut by two or three days [Music] I really don't call them Pickers I call them professional harvester there's this idea that anybody can come out here and they're going to come up with a with a great quality berry I want to have no you don't want to see inside my bucket I know look at them look can I just work yeah you're gonna have a speaker got a good job I am NOT getting the hang of this and it was a very sold fresh or harvested by hand but usually after to picking machines do a final sweep shaking the bushes to release the remaining berry since they may suffer a few knobs they go straight to the freezer to be sold as frozen berries meanwhile hand picked berries hit the sorting line a color scanner weeds out under ripe berries anything that isn't blue these may go into juice purees even pet food the berries then drop onto a pressure plate softer over ripe berries moves slower than firm one so they rejected from the line and often wind up as frozen thanks to the pioneering work done right here in New Jersey a century ago blueberries are now farmed all over the world from New Zealand to the Netherlands and the antioxidant craze has helped global production triple in the last decade alone it's a huge accomplishment for a wild little American berry or maybe it was destiny after all the Native Americans think that blueberry was a divine gift and so did one of our most American of authors when I see as now in climbing one of our Hills huckleberry and blueberry bushes bent to the ground with fruit I think of them as fruits fit to grow on the most Olympian or heaven pointing Hill it does not occur to you at first that where such thoughts are suggested is Mount Olympus and that you who taste these berries are of God why and his only royal moment should man abdicate his throne [Music] wait before you go I have one small request we are getting closer and closer to 100,000 subscribers if all of you just asked one friend one person to subscribe to this channel then we would smash through 100,000 and if you're not subscribed go ahead and do it quick click that subscribe where is it is it here and there click that subscribe button wherever it is the more subscribers we have on this channel the more resources we have to make more videos so go do it do it let's get pick up your phone picked a text a friend right now Texas what yeah okay alright let's do this guy's thank you high five high five

114
Views

What’s the difference between peaches and nectarines?How to grow peach

HowgrowTV posted the article • 0 comments • 114 views • 2017-11-07 16:40 • came from similar tags

 

 
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143
Views

How to grow bell pepper?

HowgrowTV posted the article • 0 comments • 143 views • 2017-11-07 16:40 • came from similar tags

 

 
 
 
subtitle:


here's a tale of two peppers the green one costs half the price of the red but here's the thing they're the same peppers seriously so why you paying double for red to answer that we have to answer this pepper how does it grow [Music] now all peppers start out green at this stage they're mature but not yet ripe it's like a green tomato before it turns red it's sugars aren't fully developed the red yellow and orange bell peppers you buy in the store are all different varieties that have been bred to fully ripen at those colors bell peppers are great sources of vitamins A b6 and C but yellow peppers pack about three times more vitamin C than Reds [Music] in this episode I'm following the story of the red bell-pepper it takes three to four weeks for a pepper to go from green to chocolate color to finally read each week caring for it gets riskier translation more expensive see red peppers are super sensitive to extremes like a sudden heavy rain or a sharp temperature dip that's why most are grown in warm climates like California or Florida New Jersey is a top producing state for green peppers in South Jersey there's one farmer left growing Reds and open fields that's Bob Booth a legend among farmers his secret is in the soil Bob nourishes the land for three years before planting peppers or any crop on that plot how does he do this for starters he uses leaf compost in place of chemical fertilizer so this is just just leaves from people's backyard but so warm as the leaves break down they add rich organic matter to the soil this supplies vital nutrients to Bob's crops you have to be in it not for the year and now you have to think longer term and the next generation many farmers are fertilizing the crop daily or weekly through the irrigation system and it's almost as if the crop is treated like a junkie on cocaine we're letting the soil feel across you want to leave the land in better condition that when you took it on [Music] [Music] when the soil is ready Bob transplants the seedlings he's grown in the greenhouse yes it all starts from those tiny seeds inside your pepper when the plants are mature enough they flower and those flowers are pollinated simply by the wind as the fruit begins to grow Bob stakes the plants to keep them off the ground and he stays vigilant for fungus and insects that could easily wipe out his crop a crack as Tiny as this could let rain seep in and bacteria grow quickly causing the pepper to rot but it's about way more than just keeping these peppers alive bob has to satisfy our demand for cosmetically perfect peppers this is one that was jammed in tight and it's misshapen you couldn't put that in on the grocery store shelf that's a beautiful pepper perfect shape this is cosmetically perfect it's a number one this one is not morons up getting disposed back on the ground consumers would be surprised by the amount of waste or sort house that you have and not only in pepper but in all crops [Music] when the peppers are 80% red harvesters carefully break the stems by hand the peppers will finish coloring by the time they hit store shelves a couple days later this harvest crew spends hours with their backs bent over the peppers when they're done they move with impressive speed and unison to gather all the buckets this is the very definition of teamwork any peppers that are misshapen go to processors who cut them up Bob earns seven times less for these still perfectly delicious peppers [Music] as winter moves in the late season harvest is usually Bob's best he says a touch of cold weather actually sweetens his crop and since we now know that most of America's red peppers are grown in warm climates that means these peppers just might be the country's sweetest [Music] wait have you subscribed yet don't leave until you subscribe click that button is it here is it here or is it here click it [Music] view all
 


 
 
 
subtitle:


here's a tale of two peppers the green one costs half the price of the red but here's the thing they're the same peppers seriously so why you paying double for red to answer that we have to answer this pepper how does it grow [Music] now all peppers start out green at this stage they're mature but not yet ripe it's like a green tomato before it turns red it's sugars aren't fully developed the red yellow and orange bell peppers you buy in the store are all different varieties that have been bred to fully ripen at those colors bell peppers are great sources of vitamins A b6 and C but yellow peppers pack about three times more vitamin C than Reds [Music] in this episode I'm following the story of the red bell-pepper it takes three to four weeks for a pepper to go from green to chocolate color to finally read each week caring for it gets riskier translation more expensive see red peppers are super sensitive to extremes like a sudden heavy rain or a sharp temperature dip that's why most are grown in warm climates like California or Florida New Jersey is a top producing state for green peppers in South Jersey there's one farmer left growing Reds and open fields that's Bob Booth a legend among farmers his secret is in the soil Bob nourishes the land for three years before planting peppers or any crop on that plot how does he do this for starters he uses leaf compost in place of chemical fertilizer so this is just just leaves from people's backyard but so warm as the leaves break down they add rich organic matter to the soil this supplies vital nutrients to Bob's crops you have to be in it not for the year and now you have to think longer term and the next generation many farmers are fertilizing the crop daily or weekly through the irrigation system and it's almost as if the crop is treated like a junkie on cocaine we're letting the soil feel across you want to leave the land in better condition that when you took it on [Music] [Music] when the soil is ready Bob transplants the seedlings he's grown in the greenhouse yes it all starts from those tiny seeds inside your pepper when the plants are mature enough they flower and those flowers are pollinated simply by the wind as the fruit begins to grow Bob stakes the plants to keep them off the ground and he stays vigilant for fungus and insects that could easily wipe out his crop a crack as Tiny as this could let rain seep in and bacteria grow quickly causing the pepper to rot but it's about way more than just keeping these peppers alive bob has to satisfy our demand for cosmetically perfect peppers this is one that was jammed in tight and it's misshapen you couldn't put that in on the grocery store shelf that's a beautiful pepper perfect shape this is cosmetically perfect it's a number one this one is not morons up getting disposed back on the ground consumers would be surprised by the amount of waste or sort house that you have and not only in pepper but in all crops [Music] when the peppers are 80% red harvesters carefully break the stems by hand the peppers will finish coloring by the time they hit store shelves a couple days later this harvest crew spends hours with their backs bent over the peppers when they're done they move with impressive speed and unison to gather all the buckets this is the very definition of teamwork any peppers that are misshapen go to processors who cut them up Bob earns seven times less for these still perfectly delicious peppers [Music] as winter moves in the late season harvest is usually Bob's best he says a touch of cold weather actually sweetens his crop and since we now know that most of America's red peppers are grown in warm climates that means these peppers just might be the country's sweetest [Music] wait have you subscribed yet don't leave until you subscribe click that button is it here is it here or is it here click it [Music]

197
Views

The specific directions for drying each vegetable step by step

Isidore posted the article • 0 comments • 197 views • 2017-10-30 17:39 • came from similar tags

Select vegetables that are freshly picked, tender, and just mature enough to eat.Set out all ingredients and equipment. Wash and dry all utensils, counter tops, working surfaces, and your hands.Preheat your conventional oven to 140°F, or follow the manufacturer's directions for your electric dryer or dehydrator, or a convection or microwave oven.Wash the vegetables thoroughly, scrubbing with a brush if necessary, but handling them gently to avoid bruising.Cut, slice, or grate the food according to the recipe directions.Blanch the vegetables in small amounts at a time, according to recipe directions. For steam blanching, fill the blancher with just enough water to cover the bottom, but not to touch the basket or rack. For blanching by boiling, fill
the blancher about half full, then begin heating. After blanching, chill the vegetable pieces in ice water for the same amount of time the recipe gives for blanching in boiling water. 
     7.Drain the chilled vegetables well, blot them dry, then spread them in a single, even layer on cookie sheets or on the racks of an electric dryer. Don't crowd the vegetables on the sheet and don't prepare more vegetables than you can dry at one time.
     8.For conventional oven drying, put an oven thermometer toward the back of the tray. Put the tray on the top shelf in a preheated oven, and maintain an oven temperature of 140°F.
     9.For box drying, turn on the light bulb for 10 to 15 minutes to preheat the box. Place the tray on top of the box.
     10.For convection oven drying, place the racks
full of food into a cold oven. Set the temperature at 150°F. Open the oven door 1 to VA inches. Set the oven timer to the "stay on" position, or for as long as it will run, resetting as needed.

11. For drying in an electric dryer or dehydrator. or a microwave or convection oven, follow the manufacturer's directions.
 
12. For both oven and box drying, check the trays often, and stir the vegetables on the trays, moving the outside pieces to the center. For oven drying, turn the tray from front to back and — if drying more than 1 tray — change the trays from shelf to shelf for even drying. Check the trays more frequently during the last few hours of drying to prevent ' scorching. For microwave oven drying, follow the manufacturer's directions. Use the lower end of drying times given in the recipes as a guide for doneness when you're using a conventional, microwave, or convection oven. The upper range of drying times is a guide to doneness when you're using an electric dryer or dehydrator. 
 
 13.To test for doneness, remove sample pieces, cool, and then follow the recipe directions for testing for doneness. When the vegetables are completely dry, as described in each recipe, remove them from the oven or box and let stand until cooled. Test the vegetables again after cooling. If the food still shows some moisture, return it to the oven or dryer until completely dried. 
 
14.Turn the dried vegetables into a deep container, cover lightly with cheesecloth, and condition, stirring once a day for a week to 10 days. 
 
15. Pack into vapor/moistureproof, airtight containers or double plastic bags and store in a cool, dark, dry place for up to 12 months. 
 
16.To rehydrate, put the vegetables in a pan or bowl, and add just enough boiling water to cover — usually 2 cups of water per cup of dried vegetables, anywhere from 1/2 hour to several hours, depending on the vegetable. 
 
17.Cook vegetables in their soaking water until tender, or drain and add to recipes just as you would fresh vegetables. 
 
 
The recipes that follow give you specific directions for drying each vegetable. To prevent problems, keep these basic steps in mind when home drying foods. Remember that only the highest quality vegetables are suitable for drying.  view all
  1. Select vegetables that are freshly picked, tender, and just mature enough to eat.
  2. Set out all ingredients and equipment. Wash and dry all utensils, counter tops, working surfaces, and your hands.
  3. Preheat your conventional oven to 140°F, or follow the manufacturer's directions for your electric dryer or dehydrator, or a convection or microwave oven.
  4. Wash the vegetables thoroughly, scrubbing with a brush if necessary, but handling them gently to avoid bruising.
  5. Cut, slice, or grate the food according to the recipe directions.
  6. Blanch the vegetables in small amounts at a time, according to recipe directions. For steam blanching, fill the blancher with just enough water to cover the bottom, but not to touch the basket or rack. For blanching by boiling, fill

the blancher about half full, then begin heating. After blanching, chill the vegetable pieces in ice water for the same amount of time the recipe gives for blanching in boiling water. 
     7.Drain the chilled vegetables well, blot them dry, then spread them in a single, even layer on cookie sheets or on the racks of an electric dryer. Don't crowd the vegetables on the sheet and don't prepare more vegetables than you can dry at one time.
     8.For conventional oven drying, put an oven thermometer toward the back of the tray. Put the tray on the top shelf in a preheated oven, and maintain an oven temperature of 140°F.
     9.For box drying, turn on the light bulb for 10 to 15 minutes to preheat the box. Place the tray on top of the box.
     10.For convection oven drying, place the racks
full of food into a cold oven. Set the temperature at 150°F. Open the oven door 1 to VA inches. Set the oven timer to the "stay on" position, or for as long as it will run, resetting as needed.

11. For drying in an electric dryer or dehydrator. or a microwave or convection oven, follow the manufacturer's directions.
 
12. For both oven and box drying, check the trays often, and stir the vegetables on the trays, moving the outside pieces to the center. For oven drying, turn the tray from front to back and — if drying more than 1 tray — change the trays from shelf to shelf for even drying. Check the trays more frequently during the last few hours of drying to prevent ' scorching. For microwave oven drying, follow the manufacturer's directions. Use the lower end of drying times given in the recipes as a guide for doneness when you're using a conventional, microwave, or convection oven. The upper range of drying times is a guide to doneness when you're using an electric dryer or dehydrator. 
 
 13.To test for doneness, remove sample pieces, cool, and then follow the recipe directions for testing for doneness. When the vegetables are completely dry, as described in each recipe, remove them from the oven or box and let stand until cooled. Test the vegetables again after cooling. If the food still shows some moisture, return it to the oven or dryer until completely dried. 
 
14.Turn the dried vegetables into a deep container, cover lightly with cheesecloth, and condition, stirring once a day for a week to 10 days. 
 
15. Pack into vapor/moistureproof, airtight containers or double plastic bags and store in a cool, dark, dry place for up to 12 months. 
 
16.To rehydrate, put the vegetables in a pan or bowl, and add just enough boiling water to cover — usually 2 cups of water per cup of dried vegetables, anywhere from 1/2 hour to several hours, depending on the vegetable. 
 
17.Cook vegetables in their soaking water until tender, or drain and add to recipes just as you would fresh vegetables. 
 
 
The recipes that follow give you specific directions for drying each vegetable. To prevent problems, keep these basic steps in mind when home drying foods. Remember that only the highest quality vegetables are suitable for drying.