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Estimation of carcass weight of Hanwoo (Korean native cattle) as a function of body measurements using statistical models and a neural network.

ABSTRACT: OBJECTIVE:The objective of this study was to develop a model for estimating the carcass weight of Hanwoo cattle as a function of body measurements using three different modeling approaches: i) multiple regression analysis, ii) partial least square regression analysis, and iii) a neural network. METHODS:Data from a total of 134 Hanwoo cattle were obtained from the National Institute of Animal Science in South Korea. Among the 372 variables in the raw data, 20 variables related to carcass weight and body measurements were extracted to use in multiple regression, partial least square regression, and an artificial neural network to estimate the cold carcass weight of Hanwoo cattle by any of seven body measurements significantly related to carcass weight or by all 19 body measurement variables. For developing and training the model, 100 data points were used, whereas the 34 remaining data points were used to test the model estimation. RESULTS:The R2 values from testing the developed models by multiple regression, partial least square regression, and an artificial neural network with seven significant variables were 0.91, 0.91, and 0.92, respectively, whereas all the methods exhibited similar R2 values of approximately 0.93 with all 19 body measurement variables. In addition, relative errors were within 4%, suggesting that the developed model was reliable in estimating Hanwoo cattle carcass weight. The neural network exhibited the highest accuracy. CONCLUSION:The developed model was applicable for estimating Hanwoo cattle carcass weight using body measurements. Because the procedure and required variables could differ according to the type of model, it was necessary to select the best model suitable for the system with which to calculate the model.

SUBMITTER: Lee DH

PROVIDER: S-EPMC7463082 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Estimation of carcass weight of Hanwoo (Korean native cattle) as a function of body measurements using statistical models and a neural network.

Lee Dae-Hyun DH Lee Seung-Hyun SH Cho Byoung-Kwan BK Wakholi Collins C Seo Young-Wook YW Cho Soo-Hyun SH Kang Tae-Hwan TH Lee Wang-Hee WH

Asian-Australasian journal of animal sciences 20191224 10

<h4>Objective</h4>The objective of this study was to develop a model for estimating the carcass weight of Hanwoo cattle as a function of body measurements using three different modeling approaches: i) multiple regression analysis, ii) partial least square regression analysis, and iii) a neural network.<h4>Methods</h4>Data from a total of 134 Hanwoo cattle were obtained from the National Institute of Animal Science in South Korea. Among the 372 variables in the raw data, 20 variables related to c ...[more]

PMID: 32054178

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Project description:This genome-wide association study (GWAS) was conducted to identify major loci that are significantly associated with carcass weight, and their effects, in order to provide increased understanding of the genetic architecture of carcass weight in Hanwoo. This genome-wide association study identified one major chromosome region ranging from 23 Mb to 25 Mb on chromosome 14 as being associated with carcass weight in Hanwoo. Significant Bonferroni-corrected genome-wide associations (P<1.52×10(-6)) were detected for 6 Single Nucleotide Polymorphic (SNP) loci for carcass weight on chromosome 14. The most significant SNP was BTB-01280026 (P = 4.02×10(-11)), located in the 25 Mb region on Bos taurus autosome 14 (BTA14). The other 5 significant SNPs were Hapmap27934-BTC-065223 (P = 4.04×10(-11)) in 25.2 Mb, BTB-01143580 (P = 6.35×10(-11)) in 24.3 Mb, Hapmap30932-BTC-011225 (P = 5.92×10(-10)) in 24.8 Mb, Hapmap27112-BTC-063342 (P = 5.18×10(-9)) in 25.4 Mb, and Hapmap24414-BTC-073009 (P = 7.38×10(-8)) in 25.4 Mb, all on BTA 14. One SNP (BTB-01143580; P = 6.35×10(-11)) lies independently from the other 5 SNPs. The 5 SNPs that lie together showed a large Linkage disequilibrium (LD) block (block size of 553 kb) with LD coefficients ranging from 0.53 to 0.89 within the block. The most significant SNPs accounted for 6.73% to 10.55% of additive genetic variance, which is quite a large proportion of the total additive genetic variance. The most significant SNP (BTB-01280026; P = 4.02×10(-11)) had 16.96 kg of allele substitution effect, and the second most significant SNP (Hapmap27934-BTC-065223; P = 4.04×10(-11)) had 18.06 kg of effect on carcass weight, which correspond to 44% and 47%, respectively, of the phenotypic standard deviation for carcass weight in Hanwoo cattle. Our results demonstrated that carcass weight was affected by a major Quantitative Trait Locus (QTL) with a large effect and by many SNPs with small effects that are normally distributed.

Dataset Information

Estimation of carcass weight of Hanwoo (Korean native cattle) as a function of body measurements using statistical models and a neural network.

Publications

Estimation of carcass weight of Hanwoo (Korean native cattle) as a function of body measurements using statistical models and a neural network.

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