{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T05:08:21Z","timestamp":1790053701888,"version":"4.0.1"},"reference-count":61,"publisher":"Cambridge University Press (CUP)","license":[{"start":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T00:00:00Z","timestamp":1790035200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Journal of Dairy Research"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Climate change, through intensified heat and cold stress, increasingly threatens dairy cattle productivity. This study quantified milk yield losses due to thermal stress and evaluated the genetic basis of climatic resilience in Sahiwal cattle using random regression models (RRMs). A total of 132,548 daily milk yield (DMY) records from 500 Sahiwal cows maintained at ICAR-National Dairy Research Institute, Karnal, India, were analysed. Climatic variables from the NASA POWER (National Aeronautics and Space Administration Prediction of Worldwide Energy Resources) database were used to estimate the comprehensive climatic index to characterize thermal stress risk. RRMs incorporating second-order Legendre polynomials for additive genetic effects and fourth-order polynomials for permanent environmental effects provided the best fit. Heat stress was the primary climatic factor affecting productivity, causing an average milk loss of 53.54\u00a0kg per animal in a standard first lactation of 305\u00a0days, while cold stress resulted in a 2.78\u00a0kg loss during the first lactation. According to the study, the combined effects of temperature and humidity make the monsoon season \u2013 especially July \u2013 more stressful than the pre-monsoon summer season. Since heat stress accounted for approximately 95% of the observed milk loss, the study also demonstrated how severe heat stress is compared to cold stress in the study location. Resilience traits had heritability values ranging from 0.06 for total milk loss due to heat stress to 0.19 for r-Auto due to thermal stress. Except for skew, which measures skewness from DMY deviations and the degree of asymmetry in the records, most resilience traits showed positive genetic relationships with productivity. Heat stress effects were most severe during mid-lactation, whereas cold stress predominantly affected the early and late lactations. These findings provide critical insights for developing climate-resilient dairy management strategies and genetic selection programmes to mitigate the severity of climatic stress under the climate change scenarios.<\/jats:p>","DOI":"10.1017\/s0022029926102404","type":"journal-article","created":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T04:51:56Z","timestamp":1790052716000},"page":"1-13","source":"Crossref","is-referenced-by-count":0,"title":["Modelling the impacts of thermal stress on milk production in Sahiwal cows using random regression models integrated with NASA POWER data"],"prefix":"10.1017","author":[{"given":"P.","family":"Priyadharshini","sequence":"first","affiliation":[{"id":[{"id":"https:\/\/ror.org\/03ap5bg83","id-type":"ROR","asserted-by":"publisher"}],"name":"ICAR-National Dairy Research Institute"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rani","family":"Alex","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/03ap5bg83","id-type":"ROR","asserted-by":"publisher"}],"name":"ICAR-National Dairy Research Institute"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gopal","family":"Gowane","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/03ap5bg83","id-type":"ROR","asserted-by":"publisher"}],"name":"ICAR-National Dairy Research Institute"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sabyasachi","family":"Mukherjee","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/03ap5bg83","id-type":"ROR","asserted-by":"publisher"}],"name":"ICAR-National Dairy Research Institute"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Phoebe C.","family":"Lalremruati","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/03ap5bg83","id-type":"ROR","asserted-by":"publisher"}],"name":"ICAR-National Dairy Research Institute"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vikas","family":"Vohra","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/03ap5bg83","id-type":"ROR","asserted-by":"publisher"}],"name":"ICAR-National Dairy Research Institute"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9020-778X","authenticated-orcid":false,"given":"Thiruvothur Venkatesan","family":"Raja","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/03ap5bg83","id-type":"ROR","asserted-by":"publisher"}],"name":"ICAR-National Dairy Research Institute"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"56","published-online":{"date-parts":[[2026,9,22]]},"reference":[{"key":"S0022029926102404_ref30","doi-asserted-by":"publisher","DOI":"10.1007\/s00484-024-02774-7"},{"key":"S0022029926102404_ref68","doi-asserted-by":"publisher","DOI":"10.3168\/jds.S0022-0302(98)75895-3"},{"key":"S0022029926102404_ref43","doi-asserted-by":"publisher","DOI":"10.1007\/s00484-007-0136-1"},{"key":"S0022029926102404_ref71","doi-asserted-by":"publisher","DOI":"10.1016\/j.jtherbio.2018.08.005"},{"key":"S0022029926102404_ref34","unstructured":"Hahn, GL , McQuigg, JD and Decker, WL (1970) Probability of occurrence of cloud cover during summer daytime hours. 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