Accuracy Levels
I have performed scores of both large and small calculations during the last decade and without exception ASBV trait accuracy levels are randomized.
Table 1 below is a standard example.
1.33 is the Stirling 10 percentile cut-off. Only 3 of 11 make the grade.
The ASBV figures are taken after the 2nd to 5th weaning’s and as such reflect end of life record rather than prediction. Accuracy levels are randomized compared to the preferred position.
Table 1a continuation below uses 2 actual predictors.
If we delete the ET’s from the ID Wean NLW column, we have 1 mistake, 1 in the changeover zone and 9 correct.
In the ID Maiden NLW column, we have 1 mistake, 1 in the changeover zone and 12 correct.
The Co-Relative Function
ASBV = Actual x Co-Relatives (progeny, trait, flock, year and genomic)
WOOL Table 2
Test Analysis Run on 162 2016 Drop Stirling Male Progeny 250 Day Wool Actuals, Actual Ratios and A.S.B.V.’s plotted against Bodyweight Actuals in 10 percentile groups.
FAT Table 3
Test Analysis Run on 162 2016 Drop Stirling Male Progeny
250 Day Fat Actuals, Actual Ratios and A.S.B.V.’s plotted against Bodyweight Actuals in 10 percentile groups
EMD Table 4
Test Analysis Run on 162 2016 Drop Stirling Male Progeny 250 Day EMD Actuals, Actual Ratios and A.S.B.V.’s plotted against Bodyweight Actuals in 10 percentile groups.
ASBV CV’s have been elevated by approximately 1000% above the 2 actual systems in all 3 traits tables consistently. The addition of co-relatives is the sole evidence.
In 2012 I applied a simple co-relative to wean ratio. I granted the dams present lifetime figure to her progeny as a single year start figure at one year of age.
By 2018 I discontinued the practice because it randomized predictability albeit to a smaller extent but in the same way as the ASBV co-relatives.
Progeny predictability equals dam CV of trait actual multiplied by sire CV of trait actual. The act of conception already randomizes predictability enough without the addition of the co-relative multiplier effect.
The ASBV Accuracy Measure
There is an accuracy measure quoted for all ASBV trait measurements. It goes something like this. Number and spread of co-relative linkages multiplied by the heritability of co-relatives as a percentage of the number required for 100 percent accuracy, what ever that maybe. In short, the higher the value of the CV the more accurate the measure. Yet the Google definition of increased CV accuracy is, the lower the value the more precise the estimate, these two interpretations are in direct conflict.
Prediction Driver
Find the prediction driver and you eliminate prediction need. Einstein once said that there are dimensions in this world that we do not understand. Your excepted ideas are being challenged as you read this article and so your reading and understanding gene that you were given at conception hopefully is gaining strength. You may have heard the comment “you look like your grandparent”. It is more common than you may believe. They have matured and born considerably more challenge than your parents. Gene development may well exist in the energy dimension rather than the matter one where we at present scramble for answers but there is no doubt that challenge is not just the sexy smile of the challenge select marriage for the challenge environment is also an energy zone.
Conclusion
ASBV concentration on the total amalgam of individual predictions randomizes each individual’s predictability.
This flatline spread of the gene map will camouflage the spectrum edge that defines environmental challenge along the pathway of genetic progress.
The joker trumps all. Power is top down. Understand and you lead. Leadership is bottom up.