{"title":"旁遮普中部牲畜舒适指数的计算","authors":"Aatralarasi S, Dhaliwal Lk, Kingra Pk, Puneet Malhotra, Gourav Jain","doi":"10.15406/jdvar.2024.13.00342","DOIUrl":null,"url":null,"abstract":"Climate change imposes detrimental heat stress, which disrupts the thermo-regulatory balance of cattle and buffaloes. Quantifying heat stress through bioclimatic indices is a vital step for identifying suitable mitigation/adaptation strategies. So, the trend of different comfort indices for cattle was computed (2000-2019) and used for estimating milk production as these indices provide a holistic view of the bovine’s thermoneutral status. The trend analysis of seasonal comfort index (CI) through box plot analysis indicated that Black Globe Humidity Index (BGHI) had shifted from ‘Low Impact’ to ‘High Impact’, Temperature Humidity Index (THI) had shifted from ‘Normal’ to ‘Danger’ and Comprehensive Climate Index (CCI) had shifted from ‘No stress’ to ‘Mild stress’ from winter to summer season indicating the impact of heat stress during the latter period. The milk production in April had a significant correlation with BGHI, Heat Load Index (HLI), Respiration Rate (RR), THI, CCI, and Equivalent Temperature Index (ETI). Milk production in May and June had a significant relationship with ETI and THI. Lactation-wise milk production analysis indicated that sixth lactation is related to ETI and HLI. Fourth and second lactation had a significant relation with all indices estimated and the first stage of lactation with BGHI, ETI, and RR. The CI with the highest correlation coefficients were used to develop a regression model for a respective month and lactation stage.","PeriodicalId":119303,"journal":{"name":"Journal of Dairy, Veterinary & Animal Research","volume":"146 4","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Computation of comfort indices for livestock in central Punjab\",\"authors\":\"Aatralarasi S, Dhaliwal Lk, Kingra Pk, Puneet Malhotra, Gourav Jain\",\"doi\":\"10.15406/jdvar.2024.13.00342\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Climate change imposes detrimental heat stress, which disrupts the thermo-regulatory balance of cattle and buffaloes. Quantifying heat stress through bioclimatic indices is a vital step for identifying suitable mitigation/adaptation strategies. So, the trend of different comfort indices for cattle was computed (2000-2019) and used for estimating milk production as these indices provide a holistic view of the bovine’s thermoneutral status. The trend analysis of seasonal comfort index (CI) through box plot analysis indicated that Black Globe Humidity Index (BGHI) had shifted from ‘Low Impact’ to ‘High Impact’, Temperature Humidity Index (THI) had shifted from ‘Normal’ to ‘Danger’ and Comprehensive Climate Index (CCI) had shifted from ‘No stress’ to ‘Mild stress’ from winter to summer season indicating the impact of heat stress during the latter period. The milk production in April had a significant correlation with BGHI, Heat Load Index (HLI), Respiration Rate (RR), THI, CCI, and Equivalent Temperature Index (ETI). Milk production in May and June had a significant relationship with ETI and THI. Lactation-wise milk production analysis indicated that sixth lactation is related to ETI and HLI. Fourth and second lactation had a significant relation with all indices estimated and the first stage of lactation with BGHI, ETI, and RR. The CI with the highest correlation coefficients were used to develop a regression model for a respective month and lactation stage.\",\"PeriodicalId\":119303,\"journal\":{\"name\":\"Journal of Dairy, Veterinary & Animal Research\",\"volume\":\"146 4\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-02-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Dairy, Veterinary & Animal Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15406/jdvar.2024.13.00342\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Dairy, Veterinary & Animal Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15406/jdvar.2024.13.00342","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Computation of comfort indices for livestock in central Punjab
Climate change imposes detrimental heat stress, which disrupts the thermo-regulatory balance of cattle and buffaloes. Quantifying heat stress through bioclimatic indices is a vital step for identifying suitable mitigation/adaptation strategies. So, the trend of different comfort indices for cattle was computed (2000-2019) and used for estimating milk production as these indices provide a holistic view of the bovine’s thermoneutral status. The trend analysis of seasonal comfort index (CI) through box plot analysis indicated that Black Globe Humidity Index (BGHI) had shifted from ‘Low Impact’ to ‘High Impact’, Temperature Humidity Index (THI) had shifted from ‘Normal’ to ‘Danger’ and Comprehensive Climate Index (CCI) had shifted from ‘No stress’ to ‘Mild stress’ from winter to summer season indicating the impact of heat stress during the latter period. The milk production in April had a significant correlation with BGHI, Heat Load Index (HLI), Respiration Rate (RR), THI, CCI, and Equivalent Temperature Index (ETI). Milk production in May and June had a significant relationship with ETI and THI. Lactation-wise milk production analysis indicated that sixth lactation is related to ETI and HLI. Fourth and second lactation had a significant relation with all indices estimated and the first stage of lactation with BGHI, ETI, and RR. The CI with the highest correlation coefficients were used to develop a regression model for a respective month and lactation stage.