Body weight prediction of Belgian Blue crossbred using random forest.

Belgian blue crossbred Random forest body weight morphometrics

Journal

Journal of advanced veterinary and animal research
ISSN: 2311-7710
Titre abrégé: J Adv Vet Anim Res
Pays: Bangladesh
ID NLM: 101647585

Informations de publication

Date de publication:
Mar 2024
Historique:
received: 03 08 2023
revised: 29 10 2023
accepted: 27 11 2023
medline: 29 4 2024
pubmed: 29 4 2024
entrez: 29 4 2024
Statut: epublish

Résumé

The aim of this study was to predict the body weight (BW) of a Belgian Blue X Friesian Holstein (BB X FH) crossbred in Indonesia based on morphometrics using random forest. A total of 26 BB X FH crossbreds were observed for BW, chest weight (CW), body length (BL), hip height (HH), wither height (WH), and chest girth (CG) from 0, 30, 60, 90, 120, 150, 180, 210, 240, 270, and 300 days of age. Stepwise regression and random forest were performed using R 3.6.1. The random forest results show that CG is an important variable in estimating BW, with an important variable value of 24.49%. Likewise, the results obtained by stepwise regression show that CG can be an indicator of selection for the BB X FH crossbred. The In conclusion, random forest produces a better model than stepwise regression. However, a good simple equation to use to estimate BW is CG.

Identifiants

pubmed: 38680810
doi: 10.5455/javar.2024.k763
pmc: PMC11055585
doi:

Types de publication

Journal Article

Langues

eng

Pagination

181-184

Informations de copyright

Copyright: © Journal of Advanced Veterinary and Animal Research.

Déclaration de conflit d'intérêts

The authors have no conflicts of interest to declare.

Auteurs

Lisa Praharani (L)

Research Center for Animal Husbandry, Research Organization for Agriculture and Food, National Research Innovation Agency of the Republic of Indonesia, Bogor, Indonesia.

Chalid Talib (C)

Research Center for Animal Husbandry, Research Organization for Agriculture and Food, National Research Innovation Agency of the Republic of Indonesia, Bogor, Indonesia.

Diana Andrianita Kusumaningrum (DA)

Research Center for Animal Husbandry, Research Organization for Agriculture and Food, National Research Innovation Agency of the Republic of Indonesia, Bogor, Indonesia.

Yeni Widiawati (Y)

Research Center for Animal Husbandry, Research Organization for Agriculture and Food, National Research Innovation Agency of the Republic of Indonesia, Bogor, Indonesia.

Santiananda Arta Asmarasari (SA)

Research Center for Animal Husbandry, Research Organization for Agriculture and Food, National Research Innovation Agency of the Republic of Indonesia, Bogor, Indonesia.

Supardi Rusdiana (S)

Research Center for Animal Husbandry, Research Organization for Agriculture and Food, National Research Innovation Agency of the Republic of Indonesia, Bogor, Indonesia.

Zultinur Muttaqin (Z)

Research Center for Animal Husbandry, Research Organization for Agriculture and Food, National Research Innovation Agency of the Republic of Indonesia, Bogor, Indonesia.

Ria Sari Gail Sianturi (RSG)

Indonesian Research Institute for Animal Production, Bogor, Indonesia.

Elizabeth Wina (E)

Indonesian Research Institute for Animal Production, Bogor, Indonesia.

Endang Sopian (E)

Research Center for Animal Husbandry, Research Organization for Agriculture and Food, National Research Innovation Agency of the Republic of Indonesia, Bogor, Indonesia.

Aqdi Faturahman Arrazy (AF)

Research Center for Animal Husbandry, Research Organization for Agriculture and Food, National Research Innovation Agency of the Republic of Indonesia, Bogor, Indonesia.

Umi Adiati (U)

Research Center for Animal Husbandry, Research Organization for Agriculture and Food, National Research Innovation Agency of the Republic of Indonesia, Bogor, Indonesia.

Ferdy Saputra (F)

Research Center for Animal Husbandry, Research Organization for Agriculture and Food, National Research Innovation Agency of the Republic of Indonesia, Bogor, Indonesia.

Classifications MeSH