scholarly journals Recent Advances in Sire Evaluation Methods: A Review

2021 ◽  
Author(s):  
Amol Jagannath Talokar ◽  
Harshit Kumar ◽  
Arnav Mehrotra ◽  
Kaiho Kaisa ◽  
K.A. Saravanan ◽  
...  
Keyword(s):  
Least Squares ◽  
Least Squares Method ◽  
Error Variance ◽  
Multiple Trait ◽  
Index Method ◽  
Linear Unbiased Prediction ◽  
Sire Evaluation ◽  
Derivative Free ◽  
Best Linear Unbiased ◽  
Made In

This review deals with the various traditional and recent methods of sire evaluation. A sire evaluation is a method of prediction of sire’s next-generation produced by breeding with specified females and creating their records in a specific environment. Breeding worth of progeny tested sires are obtained through sire index method that assigns ranking to each sire based on their genetic merit. Numerous sire indices are broadly classified in two type’s viz., indices which are purely meant for ranking purposes and those which, besides, provide an estimate of the breeding worth of each sire. Sires can be evaluated in single or multiple herds. The statistical equations represent sire evaluation as linear or non-linear methods. Numerous methods can be incorporated as the advances are made in sire evaluation based on data structures, breeding approaches and selection methods. There are various approaches of sire evaluation such as Least Squares Method (LSM), Simple Regressed Least Squares (SRLS), Best Linear Unbiased Prediction (BLUP) and Derivative-Free Restricted Maximum Likelihood (DFREML) for single as well as multiple trait models which can be used to derive genetic worth of an individual. An efficient method of sire evaluation shows minimum within sire variance or error variance. 

Comparative efficiency of different multiple linear regression prediction equations of first lactation 305-day milk yield for sire evaluation in Murrah buffaloes

2018 ◽  
Author(s):  
Saroj Kumar Sahoo ◽  
Avtar Singh ◽  
G.S. Ambhore ◽  
S.K. Dash ◽  
P.P. Dubey
Keyword(s):  
Least Squares ◽  
Milk Yield ◽  
Best Linear Unbiased Prediction ◽  
Regression Equations ◽  
Linear Unbiased Prediction ◽  
Murrah Buffaloes ◽  
Sire Evaluation ◽  
Best Linear Unbiased ◽  
Animal Model Blup ◽  
Unbiased Prediction

In this study, first lactation 39059 weekly test-day milk yield records of 961 Murrah buffaloes were used to predict first lactation 305-day milk yield (FL305DMY) by stepwise backward regression method. The best single, two, three and four test day combinations were selected for prediction of FL305DMY based on adjusted R2 and RMSE values. The sires were evaluated for 305-day actual and predicted first lactation milk yield based on derived multiple regression equations using four methods viz. least squares (LSQ), simple regressed least squares (SRLS), best linear unbiased prediction sire model (BLUP-SM) and best linear unbiased prediction animal model (BLUP-AM) methods. The effectiveness of different sire evaluation methods were judged by error variance, coefficient of determination, coefficient of variation and spearman’s rank correlation. The accuracy of prediction of FL305DMY from weekly test day milk yields were observed to be best for TD-7 (48th day) and TD-22 (153rd day) combination with BLUP-AM as the most efficient method for sire evaluation. It was concluded that the FL305DMY can be predicted as early as 153rd day of lactation and further can be used for early genetic evaluation of Murrah sires.

scholarly journals Method of determining the distance to the object by analyzing its image blur

Vestnik MGSU ◽  
2015 ◽  
pp. 140-151 ◽  
Author(s):  
Aleksey Alekseevich Loktev ◽  
Daniil Alekseevich Loktev
Keyword(s):  
Least Squares ◽  
Statistical Approach ◽  
Evaluation Method ◽  
Least Squares Method ◽  
Focal Length ◽  
Error Variance ◽  
Method Of Least Squares ◽  
Automated Control ◽  
Image Blur

In modern integrated monitoring systems and systems of automated control of technological processes there are several essential algorithms and procedures for obtaining primary information about an object and its behavior. The primary information is characteristics of static and moving objects: distance, speed, position in space etc. In order to obtain such information in the present work we proposed to use photos and video detectors that could provide the system with high-quality images of the object with high resolution. In the modern systems of video monitoring and automated control there are several ways of obtaining primary data on the behaviour and state of the studied objects: a multisensor approach (stereovision), building an image perspective, the use of fixed cameras and additional lighting of the object, and a special calibration of photo or video detector.In the present paper the authors develop a method of determining the distances to objects by analyzing a series of images using depth evaluation using defocusing. This method is based on the physical effect of the dependence of the determined distance to the object on the image from the focal length or aperture of the lens. When focusing the photodetector on the object at a certain distance, the other objects both closer and farther than a focal point, form a spot of blur depending on the distance to them in terms of images. Image blur of an object can be of different nature, it may be caused by the motion of the object or the detector, by the nature of the image boundaries of the object, by the object’s aggregate state, as well as by different settings of the photo-detector (focal length, shutter speed and aperture).When calculating the diameter of the blur spot it is assumed that blur at the point occurs equally in all directions. For more precise estimates of the geometrical parameters determination of the behavior and state of the object under study a statistical approach is used to determine the individual parameters and estimate their accuracy. A statistical approach is used to evaluate the deviation of the dependence of distance from the blur from different types of standard functions (logarithmic, exponential, linear). In the statistical approach the evaluation method of least squares and the method of least modules are included, as well as the Bayesian estimation, for which it is necessary to minimize the risks under different loss functions (quadratic, rectangular, linear) with known probability density (we consider normal, lognormal, Laplace, uniform distribution). As a result of the research it was established that the error variance of a function, the parameters of which are estimated using the least squares method, will be less than the error variance of the method of least modules, that is, the evaluation method of least squares is more stable. Also the errors’ estimation when using the method of least squares is unbiased, whereas the mathematical expectation when using the method of least modules is not zero, which indicates the displacement of error estimations. Therefore it is advisable to use the least squares method in the determination of the parameters of the function.In order to smooth out the possible outliers we use the Kalman filter to process the results of the initial observations and evaluation analysis, the method of least squares and the method of least three standard modules for the functions after applying the filter with different coefficients.

Combined selection of progeny in crop breeding using best linear unbiased prediction

2012 ◽  
Vol 92 (3) ◽  
pp. 553-562 ◽  
Author(s):  
José Marcelo Soriano Viana ◽  
Vinícius Ribeiro Faria ◽  
Fabyano Fonseca e Silva ◽  
Marcos Deon Vilela de Resende
Keyword(s):  
Least Squares ◽  
Best Linear Unbiased Prediction ◽  
Pedigree Information ◽  
Crop Breeding ◽  
Additive Variance ◽  
Linear Unbiased Prediction ◽  
Best Linear Unbiased ◽  
Combined Selection ◽  
Selection Of ◽  
Unbiased Prediction

Viana, J. M. S., Faria, V. R., Fonseca e Silva, F. and Vilela de Resende, M. D. 2012. Combined selection of progeny in crop breeding using best linear unbiased prediction. Can. J. Plant Sci. 92: 553–562. Combined selection is an important strategy in crop breeding. As the classical index does not consider pedigree information, the objective of this study was to evaluate the efficiency of the best linear unbiased prediction (BLUP) methodology for combined selection of progeny. We analyzed expansion volume (EV) and grain yield of parents and inbred and non-inbred progeny from the popcorn population Viçosa. The BLUP analyses, single-trait and of the same character measured in parents and progeny (combined parent-family) were performed using the ASReml software. Because the experiments were balanced, the estimates of the additive variance from the BLUP and least squares analyses were generally equivalent. The accuracies of the BLUP analyses do not clearly establish the superior technique. The accuracy of the classical index tended to be higher than that obtained from BLUP analyses. There was equivalence between BLUP and least squares analyses relative to half-sib and inbred progeny selection, and superiority of the combined parent-family BLUP index for full-sib selection. The BLUP analyses also differed from the least squares analysis on the coincidence of selected parents. The populations obtained by selection based on BLUP of breeding values presented a lower effective size.

EVALUATION OF BEEF SIRES ACROSS BREEDS FOR CALVING EASE

1977 ◽  
Vol 57 (4) ◽  
pp. 635-645 ◽  
Author(s):  
L. R. SCHAEFFER ◽  
J. W. WILTON
Keyword(s):  
Maximum Likelihood ◽  
Scoring System ◽  
Variance Components ◽  
Error Variance ◽  
Best Linear Unbiased Prediction ◽  
Linear Unbiased Prediction ◽  
Calving Ease ◽  
Best Linear Unbiased ◽  
Maximum Likelihood Prediction ◽  
Unbiased Prediction

Agriculture Canada and Alberta Record of Performance calving ease records on 54,139 calves from 3,338 sires of 18 breeds were used to evaluate sires by comparisons across breeds of sire. An objective scoring system was applied to the calving ease codes to derive appropriate weights for each category rather than using percentage of unassisted births or assuming equal intervals between categories. Common sire and error variance components were assumed for all breeds of sire. Heritability of calving ease under the model used was estimated to be.10 by maximum likelihood. Prediction of sire values for calving ease scores of future calves were calculated by best linear unbiased prediction procedures. Shorthorn, Hereford, and Angus sires caused relatively few calving difficulties, while Maine-Anjou sires caused more difficulties. Age of dam and sex of calf differences were also important. The range of sire evaluations for calving ease was narrow, but the bulls in either extreme could be identified.

Study on Roundness Error Evaluation with Least-Squares Method Based on Nonlinear Optimization

2013 ◽  
Vol 765-767 ◽  
pp. 755-758 ◽  
Author(s):  
Zhen Tao Liu ◽  
Jian Xin Yang ◽  
Ben Zhao
Keyword(s):  
Least Squares ◽  
Nonlinear Optimization ◽  
Least Squares Method ◽  
Convergence Time ◽  
Error Evaluation ◽  
Nonlinear Constraint ◽  
Roundness Error ◽  
Advantages And Disadvantages ◽  
Derivative Free Optimization ◽  
Derivative Free

Roundness error evaluation software is developed based on two-dimensional circle fitting with least-squares method based on nonlinear optimization with constraints. The local derivative-free optimization algorithms of NLopt can solve nonlinear constraint problems by combining with augmented Lagrangian algorithm. The fitting precision and convergence time of each algorithm are analyzed by calculating the fitting results with same test data to find its advantages and disadvantages. It is shown that each algorithm has different behaviors from others on performance and stability. This work provides a good basis for choosing the appropriate algorithm for roundness error evaluation.

scholarly journals A comparison of different methods of estimating sire transmitting ability of some milk traits in a herd of Holstein Friesian cattle

2000 ◽  
Vol 43 (2) ◽  
pp. 115-122
Author(s):  
H. Atil ◽  
A. S. Khattab
Keyword(s):  
Least Squares ◽  
Milk Yield ◽  
Lactation Period ◽  
Milk Traits ◽  
Linear Unbiased Prediction ◽  
Age At First Calving ◽  
Holstein Friesian ◽  
Genetic And Phenotypic Correlations ◽  
Best Linear Unbiased ◽  
Friesian Cattle

Abstract. A total of 1931 normal first lactation records of Holstein Friesian cows kept at Dena Farm in Egypt during the period from 1987 to 1994 were used to estimate phenotypic and genetic parameters for 90 day milk yield (90 dMY), 305 day milk yield (305 dMY) and lactation period (LP). In addition, 76 bulls with at least ten daughters were used to compare three methods of sire transmitting ability. A least Squares analysis of variance show significant effect of month and year of calving and age at first calving for different traits studied, except the effect of age at first calving on LP. Heritability estimates for 90 dMY, 305 dMY and LP were 0.39 ± 0.08, 0.27 ± 0.07 and 0.14 ± 0.05, respectively. Genetic and phenotypic correlations between different traits were positive and significant. Sires with at least ten daughters were evaluated by best linear unbiased prediction (BLUP), least Squares means (LSM) and regression of the future daughters mean on the present daughters mean. The product moment correlations between different traits studied were positive and high (= 0.96).

A selection index for dairy cows

1983 ◽  
Vol 37 (3) ◽  
pp. 313-319 ◽  
Author(s):  
W. G. Hill ◽  
G. J. T. Swanson
Keyword(s):  
Dairy Cows ◽  
Selection Index ◽  
Best Linear Unbiased Prediction ◽  
Linear Unbiased Prediction ◽  
Genetic Base ◽  
Sire Evaluation ◽  
Selection Indices ◽  
Best Linear Unbiased ◽  
The Uk ◽  
Method Of Evaluation

ABSTRACTThe rationale for a method of computing selection indices for dairy cows is outlined. It uses predicted transmitting abilities of sires from a best linear unbiased prediction or similar method of evaluation together with mean transmitting abilities (cow indices) of dams to estimate herd genetic levels. Indices for individual cows are computed using deviations from those of contemporaries in the herd of her sire's transmitting ability, her dam's index and her own production in each lactation.The method is being used in the UK, cow indices being expressed as transmitting abilities relative to the same fixed genetic base as for sire evaluation.

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