Publication: Use of Multivariate Adaptive Regression Splines Algorithm to Predict Body Weight from Body Measurements of Anatolian Buffaloes in Turkiye
| dc.authorscopusid | 57219517016 | |
| dc.authorscopusid | 56957224200 | |
| dc.authorscopusid | 24385660900 | |
| dc.authorscopusid | 36194275800 | |
| dc.authorscopusid | 6507081490 | |
| dc.authorscopusid | 57219054908 | |
| dc.authorwosid | Tırınk, Cem/Gry-5893-2022 | |
| dc.authorwosid | Ağyar, Oğuz/Aci-7478-2022 | |
| dc.authorwosid | Piwczyński, Dariusz/J-3375-2016 | |
| dc.authorwosid | Yavuz, Esra/Jvz-6727-2024 | |
| dc.contributor.author | Agyar, Oguz | |
| dc.contributor.author | Tirink, Cem | |
| dc.contributor.author | Onder, Hasan | |
| dc.contributor.author | Sen, Ugur | |
| dc.contributor.author | Piwczynski, Dariusz | |
| dc.contributor.author | Yavuz, Esra | |
| dc.contributor.authorID | Tirink, Cem/0000-0001-6902-5837 | |
| dc.contributor.authorID | Şen, Uğur/0000-0001-6058-1140 | |
| dc.contributor.authorID | Önder, Hasan/0000-0002-8404-8700 | |
| dc.contributor.authorID | Piwczyński, Dariusz/0000-0001-8298-2316 | |
| dc.date.accessioned | 2025-12-11T01:33:30Z | |
| dc.date.issued | 2022 | |
| dc.department | Ondokuz Mayıs Üniversitesi | en_US |
| dc.department-temp | [Agyar, Oguz] Adiyaman Univ, Kahta Vocat Sch, Dept Vet, TR-02400 Adiyaman, Turkey; [Tirink, Cem] Igdir Univ, Fac Agr, Dept Anim Sci, TR-76000 Igdir, Turkey; [Onder, Hasan] Ondokuz Mayis Univ, Dept Anim Sci, TR-55139 Samsun, Turkey; [Sen, Ugur] Ondokuz Mayis Univ, Dept Agr Biotechnol, TR-55139 Samsun, Turkey; [Piwczynski, Dariusz] Bydgoszcz Univ Sci & Technol, Fac Anim Breeding & Biol, Dept Anim Biotechnol & Genet, PL-85796 Bydgoszcz, Poland; [Yavuz, Esra] Sirnak Univ, Cizre Vocat Sch, Dept Accounting & Tax Practices, TR-73200 Sirnak, Turkey | en_US |
| dc.description | Tirink, Cem/0000-0001-6902-5837; Şen, Uğur/0000-0001-6058-1140; Önder, Hasan/0000-0002-8404-8700; Piwczyński, Dariusz/0000-0001-8298-2316; | en_US |
| dc.description.abstract | 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 Mus Province of Turkiye. 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 Turkiye. Anatolian buffalo is an important breed reared for meat and milk in various regions of Turkiye. 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 Mus Province of Turkiye. 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 Turkiye. | en_US |
| dc.description.sponsorship | Polish National Agency for Academic Exchange [PPI/APM/2019/1/00003] | en_US |
| dc.description.sponsorship | This article has been supported by the Polish National Agency for Academic Exchange under Grant No. PPI/APM/2019/1/00003. | en_US |
| dc.description.woscitationindex | Science Citation Index Expanded | |
| dc.identifier.doi | 10.3390/ani12212923 | |
| dc.identifier.issn | 2076-2615 | |
| dc.identifier.issue | 21 | en_US |
| dc.identifier.pmid | 36359047 | |
| dc.identifier.scopus | 2-s2.0-85141740885 | |
| dc.identifier.scopusquality | Q1 | |
| dc.identifier.uri | https://doi.org/10.3390/ani12212923 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12712/44563 | |
| dc.identifier.volume | 12 | en_US |
| dc.identifier.wos | WOS:000883861100001 | |
| dc.identifier.wosquality | Q1 | |
| dc.language.iso | en | en_US |
| dc.publisher | MDPI | en_US |
| dc.relation.ispartof | Animals | en_US |
| dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
| dc.rights | info:eu-repo/semantics/openAccess | en_US |
| dc.subject | Water Buffalo | en_US |
| dc.subject | Mars | en_US |
| dc.subject | Prediction | en_US |
| dc.subject | Biometric Properties | en_US |
| dc.title | Use of Multivariate Adaptive Regression Splines Algorithm to Predict Body Weight from Body Measurements of Anatolian Buffaloes in Turkiye | en_US |
| dc.type | Article | en_US |
| dspace.entity.type | Publication |
