Lisa Praharani, Chalid Talib, Diana Andrianita Kusumaningrum, Yeni Widiawati, Santiananda Arta Asmarasari, Supardi Rusdiana, Zultinur Muttaqin, Ria Sari Gail Sianturi, Elizabeth Wina, Endang Sopian, Aqdi Faturahman Arrazy, Umi Adiati, Ferdy Saputra
{"title":"使用随机森林预测比利时蓝杂交种的体重。","authors":"Lisa Praharani, Chalid Talib, Diana Andrianita Kusumaningrum, Yeni Widiawati, Santiananda Arta Asmarasari, Supardi Rusdiana, Zultinur Muttaqin, Ria Sari Gail Sianturi, Elizabeth Wina, Endang Sopian, Aqdi Faturahman Arrazy, Umi Adiati, Ferdy Saputra","doi":"10.5455/javar.2024.k763","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>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.</p><p><strong>Materials and methods: </strong>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.</p><p><strong>Results: </strong>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 <i>R</i> squared value obtained from the regression is 0.83, while the <i>R</i> squared value obtained from the random forest (0.86) is greater than the regression.</p><p><strong>Conclusion: </strong>In conclusion, random forest produces a better model than stepwise regression. However, a good simple equation to use to estimate BW is CG.</p>","PeriodicalId":14892,"journal":{"name":"Journal of Advanced Veterinary and Animal Research","volume":"11 1","pages":"181-184"},"PeriodicalIF":1.5000,"publicationDate":"2024-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11055585/pdf/","citationCount":"0","resultStr":"{\"title\":\"Body weight prediction of Belgian Blue crossbred using random forest.\",\"authors\":\"Lisa Praharani, Chalid Talib, Diana Andrianita Kusumaningrum, Yeni Widiawati, Santiananda Arta Asmarasari, Supardi Rusdiana, Zultinur Muttaqin, Ria Sari Gail Sianturi, Elizabeth Wina, Endang Sopian, Aqdi Faturahman Arrazy, Umi Adiati, Ferdy Saputra\",\"doi\":\"10.5455/javar.2024.k763\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>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.</p><p><strong>Materials and methods: </strong>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.</p><p><strong>Results: </strong>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 <i>R</i> squared value obtained from the regression is 0.83, while the <i>R</i> squared value obtained from the random forest (0.86) is greater than the regression.</p><p><strong>Conclusion: </strong>In conclusion, random forest produces a better model than stepwise regression. However, a good simple equation to use to estimate BW is CG.</p>\",\"PeriodicalId\":14892,\"journal\":{\"name\":\"Journal of Advanced Veterinary and Animal Research\",\"volume\":\"11 1\",\"pages\":\"181-184\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2024-03-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11055585/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Advanced Veterinary and Animal Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5455/javar.2024.k763\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/3/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q3\",\"JCRName\":\"AGRICULTURE, DAIRY & ANIMAL SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Advanced Veterinary and Animal Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5455/javar.2024.k763","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/3/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"AGRICULTURE, DAIRY & ANIMAL SCIENCE","Score":null,"Total":0}
引用次数: 0
摘要
研究目的本研究的目的是利用随机森林技术，基于形态计量学预测印度尼西亚比利时蓝X弗里斯兰荷斯坦（BB X FH）杂交种的体重（BW）：从 0、30、60、90、120、150、180、210、240、270 和 300 日龄开始，对 26 头 BB X FH 杂交母牛的体重、胸重（CW）、体长（BL）、臀高（HH）、枯高（WH）和胸围（CG）进行观察。使用 R 3.6.1 进行了逐步回归和随机森林分析：随机森林结果显示，CG 是估计体重的一个重要变量，其重要变量值为 24.49%。同样，逐步回归的结果表明，CG 可以作为 BB X FH 杂交品种的选择指标。回归得到的 R 平方值为 0.83，而随机森林得到的 R 平方值（0.86）大于回归：总之，随机森林比逐步回归能生成更好的模型。然而，用于估计 BW 的一个很好的简单方程是 CG。
Body weight prediction of Belgian Blue crossbred using random forest.
Objective: 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.
Materials and methods: 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.
Results: 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 R squared value obtained from the regression is 0.83, while the R squared value obtained from the random forest (0.86) is greater than the regression.
Conclusion: In conclusion, random forest produces a better model than stepwise regression. However, a good simple equation to use to estimate BW is CG.
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