Cargando…

Use of Multivariate Adaptive Regression Splines Algorithm to Predict Body Weight from Body Measurements of Anatolian buffaloes in Türkiye

SIMPLE SUMMARY: The present study was performed to estimate body weight (BW) from several body measurements, such as tail length (TL), shoulder height (SH), withers height (WH), body length (BL), chest circumference (CC), shank diameter (SD) and birth weight (BiW). The data set was taken from Muş Pr...

Descripción completa

Detalles Bibliográficos
Autores principales: Ağyar, Oğuz, Tırınk, Cem, Önder, Hasan, Şen, Uğur, Piwczyński, Dariusz, Yavuz, Esra
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9657142/
https://www.ncbi.nlm.nih.gov/pubmed/36359047
http://dx.doi.org/10.3390/ani12212923
_version_ 1784829617314463744
author Ağyar, Oğuz
Tırınk, Cem
Önder, Hasan
Şen, Uğur
Piwczyński, Dariusz
Yavuz, Esra
author_facet Ağyar, Oğuz
Tırınk, Cem
Önder, Hasan
Şen, Uğur
Piwczyński, Dariusz
Yavuz, Esra
author_sort Ağyar, Oğuz
collection PubMed
description SIMPLE SUMMARY: The present study was performed to estimate body weight (BW) from several body measurements, such as tail length (TL), shoulder height (SH), withers height (WH), body length (BL), chest circumference (CC), shank diameter (SD) and birth weight (BiW). The data set was taken from Muş Province of Türkiye. In this respect, 171 Anatolian buffaloes were used. To estimate the BW, different proportions of the training and test sets were used with the MARS (Multivariate Adaptive Regression Splines) algorithm. In conclusion, it could be suggested that the MARS algorithm may allow animal breeders to obtain an elite population and to determine the body measurements affecting BW as indirect selection criteria for describing the breed description of Anatolian buffalo and aiding sustainable meat production and rural development in Türkiye. ABSTRACT: Anatolian buffalo is an important breed reared for meat and milk in various regions of Türkiye. The present study was performed to estimate body weight (BW) from several body measurements, such as tail length (TL), shoulder height (SH), withers height (WH), body length (BL), chest circumference (CC), shank diameter (SD) and birth weight (BiW). The data set was taken from Muş Province of Türkiye. In this respect, 171 Anatolian buffaloes were used. To estimate the BW, different proportions of the training and test sets were used with the MARS algorithm. The optimal MARS was determined at a proportion of 70–30%. The MARS model displays the heaviest BW that can be produced by Anatolian buffalo according to tail length, body length, chest circumference and shoulder height. In conclusion, it could be suggested that the MARS algorithm may allow animal breeders to obtain an elite population and to determine the body measurements affecting BW as indirect selection criteria for describing the breed description of Anatolian buffalo and aiding sustainable meat production and rural development in Türkiye.
format Online
Article
Text
id pubmed-9657142
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-96571422022-11-15 Use of Multivariate Adaptive Regression Splines Algorithm to Predict Body Weight from Body Measurements of Anatolian buffaloes in Türkiye Ağyar, Oğuz Tırınk, Cem Önder, Hasan Şen, Uğur Piwczyński, Dariusz Yavuz, Esra Animals (Basel) Article SIMPLE SUMMARY: The present study was performed to estimate body weight (BW) from several body measurements, such as tail length (TL), shoulder height (SH), withers height (WH), body length (BL), chest circumference (CC), shank diameter (SD) and birth weight (BiW). The data set was taken from Muş Province of Türkiye. In this respect, 171 Anatolian buffaloes were used. To estimate the BW, different proportions of the training and test sets were used with the MARS (Multivariate Adaptive Regression Splines) algorithm. In conclusion, it could be suggested that the MARS algorithm may allow animal breeders to obtain an elite population and to determine the body measurements affecting BW as indirect selection criteria for describing the breed description of Anatolian buffalo and aiding sustainable meat production and rural development in Türkiye. ABSTRACT: Anatolian buffalo is an important breed reared for meat and milk in various regions of Türkiye. The present study was performed to estimate body weight (BW) from several body measurements, such as tail length (TL), shoulder height (SH), withers height (WH), body length (BL), chest circumference (CC), shank diameter (SD) and birth weight (BiW). The data set was taken from Muş Province of Türkiye. In this respect, 171 Anatolian buffaloes were used. To estimate the BW, different proportions of the training and test sets were used with the MARS algorithm. The optimal MARS was determined at a proportion of 70–30%. The MARS model displays the heaviest BW that can be produced by Anatolian buffalo according to tail length, body length, chest circumference and shoulder height. In conclusion, it could be suggested that the MARS algorithm may allow animal breeders to obtain an elite population and to determine the body measurements affecting BW as indirect selection criteria for describing the breed description of Anatolian buffalo and aiding sustainable meat production and rural development in Türkiye. MDPI 2022-10-25 /pmc/articles/PMC9657142/ /pubmed/36359047 http://dx.doi.org/10.3390/ani12212923 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Ağyar, Oğuz
Tırınk, Cem
Önder, Hasan
Şen, Uğur
Piwczyński, Dariusz
Yavuz, Esra
Use of Multivariate Adaptive Regression Splines Algorithm to Predict Body Weight from Body Measurements of Anatolian buffaloes in Türkiye
title Use of Multivariate Adaptive Regression Splines Algorithm to Predict Body Weight from Body Measurements of Anatolian buffaloes in Türkiye
title_full Use of Multivariate Adaptive Regression Splines Algorithm to Predict Body Weight from Body Measurements of Anatolian buffaloes in Türkiye
title_fullStr Use of Multivariate Adaptive Regression Splines Algorithm to Predict Body Weight from Body Measurements of Anatolian buffaloes in Türkiye
title_full_unstemmed Use of Multivariate Adaptive Regression Splines Algorithm to Predict Body Weight from Body Measurements of Anatolian buffaloes in Türkiye
title_short Use of Multivariate Adaptive Regression Splines Algorithm to Predict Body Weight from Body Measurements of Anatolian buffaloes in Türkiye
title_sort use of multivariate adaptive regression splines algorithm to predict body weight from body measurements of anatolian buffaloes in türkiye
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9657142/
https://www.ncbi.nlm.nih.gov/pubmed/36359047
http://dx.doi.org/10.3390/ani12212923
work_keys_str_mv AT agyaroguz useofmultivariateadaptiveregressionsplinesalgorithmtopredictbodyweightfrombodymeasurementsofanatolianbuffaloesinturkiye
AT tırınkcem useofmultivariateadaptiveregressionsplinesalgorithmtopredictbodyweightfrombodymeasurementsofanatolianbuffaloesinturkiye
AT onderhasan useofmultivariateadaptiveregressionsplinesalgorithmtopredictbodyweightfrombodymeasurementsofanatolianbuffaloesinturkiye
AT senugur useofmultivariateadaptiveregressionsplinesalgorithmtopredictbodyweightfrombodymeasurementsofanatolianbuffaloesinturkiye
AT piwczynskidariusz useofmultivariateadaptiveregressionsplinesalgorithmtopredictbodyweightfrombodymeasurementsofanatolianbuffaloesinturkiye
AT yavuzesra useofmultivariateadaptiveregressionsplinesalgorithmtopredictbodyweightfrombodymeasurementsofanatolianbuffaloesinturkiye