Mohammad Rifky | Independent Researcher (original) (raw)

Uploads

Papers by Mohammad Rifky

A research was conducted to study the effectivity of Test Day records using a Fixed Regression mo... more A research was conducted to study the effectivity of Test Day records using a Fixed Regression model for genetic evaluation of dairy cattle. The data were collected from first and second lactations of Frisian Holstein dairy cattle from 1989 to 2000 at PT Taurus Dairy Farm Sukabumi. A total of 7503 Test Day records recorded from 456 cows, 40 sires and 342 dams were collected. Variance components were estimated using the animal model with REML and Breeding Values were predicted using BLUP. The results showed that the peak of lactation was reached on day 35. Season was not clearly affecting Test Day. The genetic variance decreased along with the addition of the Test Day in 2 nd lactation up to test 3, and then decreased gradually up to the end of test. The estimation of heritability followed the same patern as the genetic variance. Genetic evaluation based on first lactation plus the first test and second lactation was sufficient for the evaluation of animals, while bulls should be prolonged up to the first three tests. Sari Penelitian ini bertujuan untuk mempelajari efektivitas catatan Test Day dengan model regresi tetap untuk evaluasi genetik produksi susu pada sapi perah berdasarkan laktasi satu dan dua. Data produksi susu berasaldari sapi perah Frisian Holstein periode laktasi satu dan dua dari tahun 1989-2000 di PT. Taurus Dairy Farm Sukabumi. Catatan Test Day sebanyak 7503 buah berasal dari 456 ekor sapi betina, 40 pejantan dan 342 ekor induk. Model yang digunakan adalah Model Regresi Tetap, varian komponen diduga dengan Animal Model dengan Restricted Maximum Likelihood (REML) dan Nilai Pemuliaan dengan Best Linier Unbiased Prediction (BLUP). Hasil analisis menunjukan hasil test ke-35 (TD2) merupakan puncak produksi. Pengaruh musim terhadap produksi susu Test Day mempunyai pola yang kurang jelas. Ragam genetik aditif pada laktasi dua menurun sejalan dengan penambahan catatan Test Day sampai dengan Test Day ke-3, setelah itu meningkat sampai akhir laktasi. Dugaan nilai heritabilitas mengikuti pola yang sama dengan ragam genetik. Evaluasi genetik berdasarkan laktasi satu penuh yang ditambah dengan satu catatan Test Day pada laktasi dua sudah cukup untuk mengevaluasi seluruh ternak, sedangkan untuk mengevaluasi pejantan, evaluasi harus diperpanjang sampai tiga catatan Test Day pada laktasi dua.

Genetic Environmental Heritability is proportion of variation that is genetic • Predicting Breedi... more Genetic Environmental Heritability is proportion of variation that is genetic • Predicting Breeding Values from phenotypic differences • Breeding values are used to rank and select animals in order to achieve genetic improvement • Predict the result of selection application IN REAL LIFE We can only see P We want to estimate A. need a model Phenotype = Genetics + Environment P = A + E 2 EBV Estimated Breeding Value …is that part of the phenotypic difference that you believe is due to genetics!

– the relative economic weights – genetic parameters (heritabilities, correlations) to determine ... more – the relative economic weights – genetic parameters (heritabilities, correlations) to determine the weights we put on the observed phenotypes Index = b 1 P 1 + b 2 P 2

Multi-trait selection – how to implement? • Need to combine – the relative economic weights – gen... more Multi-trait selection – how to implement? • Need to combine – the relative economic weights – genetic parameters (heritabilities, correlations) to determine the weights we put on the observed phenotypes Index = b 1 P 1 + b 2 P 2 Issues with MT selection • We have to spread our selection efforts over several traits, each of them weighted economically • Selection for one trait gives also a correlated response for other traits We need weights for selection criteria • Index = b 1 P 1 + b 2 P 2 + …. + b n P n Selection index with more information sources (multiple regression) p = vector with phenotypes (criteria) A = breeding objective (single trait here) var(p) = P = matrix = cov(p,A) = G = vector = A p weights: b = P-1 G Selection index with more information sources and with more objective traits (multiple regression) p = vector with phenotypes (criteria) H = breeding objective (multiple traits here) = a 1 A 1 + a 2 A 2 var(p) = P = matrix = cov(p,A) = G = matrix =

A joint evaluation of all animals, uses all additive genetic relationships uses all data on all a... more A joint evaluation of all animals, uses all additive genetic relationships uses all data on all animal jointly It works as a linear model (correcting different effects for each other), jointly estimates animal effects and fixed effects (herds) but has Selection Index properties (Regression with " heritability ")

A joint evaluation of all animals, uses all additive genetic relationships uses all data on all a... more A joint evaluation of all animals, uses all additive genetic relationships uses all data on all animal jointly It works as a linear model (correcting different effects for each other), jointly estimates animal effects and fixed effects (herds) but has Selection Index properties (Regression with " heritability ")  1 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 1 0 0 0 0 1

A research was conducted to study the effectivity of Test Day records using a Fixed Regression mo... more A research was conducted to study the effectivity of Test Day records using a Fixed Regression model for genetic evaluation of dairy cattle. The data were collected from first and second lactations of Frisian Holstein dairy cattle from 1989 to 2000 at PT Taurus Dairy Farm Sukabumi. A total of 7503 Test Day records recorded from 456 cows, 40 sires and 342 dams were collected. Variance components were estimated using the animal model with REML and Breeding Values were predicted using BLUP. The results showed that the peak of lactation was reached on day 35. Season was not clearly affecting Test Day. The genetic variance decreased along with the addition of the Test Day in 2 nd lactation up to test 3, and then decreased gradually up to the end of test. The estimation of heritability followed the same patern as the genetic variance. Genetic evaluation based on first lactation plus the first test and second lactation was sufficient for the evaluation of animals, while bulls should be prolonged up to the first three tests. Sari Penelitian ini bertujuan untuk mempelajari efektivitas catatan Test Day dengan model regresi tetap untuk evaluasi genetik produksi susu pada sapi perah berdasarkan laktasi satu dan dua. Data produksi susu berasaldari sapi perah Frisian Holstein periode laktasi satu dan dua dari tahun 1989-2000 di PT. Taurus Dairy Farm Sukabumi. Catatan Test Day sebanyak 7503 buah berasal dari 456 ekor sapi betina, 40 pejantan dan 342 ekor induk. Model yang digunakan adalah Model Regresi Tetap, varian komponen diduga dengan Animal Model dengan Restricted Maximum Likelihood (REML) dan Nilai Pemuliaan dengan Best Linier Unbiased Prediction (BLUP). Hasil analisis menunjukan hasil test ke-35 (TD2) merupakan puncak produksi. Pengaruh musim terhadap produksi susu Test Day mempunyai pola yang kurang jelas. Ragam genetik aditif pada laktasi dua menurun sejalan dengan penambahan catatan Test Day sampai dengan Test Day ke-3, setelah itu meningkat sampai akhir laktasi. Dugaan nilai heritabilitas mengikuti pola yang sama dengan ragam genetik. Evaluasi genetik berdasarkan laktasi satu penuh yang ditambah dengan satu catatan Test Day pada laktasi dua sudah cukup untuk mengevaluasi seluruh ternak, sedangkan untuk mengevaluasi pejantan, evaluasi harus diperpanjang sampai tiga catatan Test Day pada laktasi dua.

Genetic Environmental Heritability is proportion of variation that is genetic • Predicting Breedi... more Genetic Environmental Heritability is proportion of variation that is genetic • Predicting Breeding Values from phenotypic differences • Breeding values are used to rank and select animals in order to achieve genetic improvement • Predict the result of selection application IN REAL LIFE We can only see P We want to estimate A. need a model Phenotype = Genetics + Environment P = A + E 2 EBV Estimated Breeding Value …is that part of the phenotypic difference that you believe is due to genetics!

– the relative economic weights – genetic parameters (heritabilities, correlations) to determine ... more – the relative economic weights – genetic parameters (heritabilities, correlations) to determine the weights we put on the observed phenotypes Index = b 1 P 1 + b 2 P 2

Multi-trait selection – how to implement? • Need to combine – the relative economic weights – gen... more Multi-trait selection – how to implement? • Need to combine – the relative economic weights – genetic parameters (heritabilities, correlations) to determine the weights we put on the observed phenotypes Index = b 1 P 1 + b 2 P 2 Issues with MT selection • We have to spread our selection efforts over several traits, each of them weighted economically • Selection for one trait gives also a correlated response for other traits We need weights for selection criteria • Index = b 1 P 1 + b 2 P 2 + …. + b n P n Selection index with more information sources (multiple regression) p = vector with phenotypes (criteria) A = breeding objective (single trait here) var(p) = P = matrix = cov(p,A) = G = vector = A p weights: b = P-1 G Selection index with more information sources and with more objective traits (multiple regression) p = vector with phenotypes (criteria) H = breeding objective (multiple traits here) = a 1 A 1 + a 2 A 2 var(p) = P = matrix = cov(p,A) = G = matrix =

A joint evaluation of all animals, uses all additive genetic relationships uses all data on all a... more A joint evaluation of all animals, uses all additive genetic relationships uses all data on all animal jointly It works as a linear model (correcting different effects for each other), jointly estimates animal effects and fixed effects (herds) but has Selection Index properties (Regression with " heritability ")

A joint evaluation of all animals, uses all additive genetic relationships uses all data on all a... more A joint evaluation of all animals, uses all additive genetic relationships uses all data on all animal jointly It works as a linear model (correcting different effects for each other), jointly estimates animal effects and fixed effects (herds) but has Selection Index properties (Regression with " heritability ")  1 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 1 0 0 0 0 1

The writer has had frequent occasion to notice the want of some handy book embodying the principl... more The writer has had frequent occasion to notice the
want of some handy book embodying the principles
necessary to be understood in order to secure improvement
in Domestic Animals.
It has been his aim to supply this want.
In doing so he has availed himself freely of the
knowledge supplied by others, the aim being to furnish
a useful, rather than an original book.
If it serve in any measure to supply the need, and
to awaken greater interest upon a matter of vital importance
to the agricultural interests of the country,
the writer's purpose will be accomplished.

Log In