Impact of heat stress on cattle systems: Responses of production metrics to thermal stress

• Heat stress (HS) exhibited distinct time-lagged effects in beef and dairy systems. • Milk yield showed a strong negative response to HS with a 5-day lag. • Cattle liveweight rose initially, then declined sharply, peaking at a 14-day lag. • THI threshold of 70 identified for dairy; results for beef were inconclusive. • Insights from dairy systems can inform HS adaptation in extensive beef production. Heat stress (HS), a major consequence of climate change, significantly impairs cattle production and poses a threat to global food security. Assessing HS impacts in extensive production systems is challenging due to the diverse landscape and management practices. We evaluated the temporal HS effects on extensive beef and intensive dairy systems to identify thermal thresholds and inform adaptive strategies for sustaining productivity. The dataset comprised 1.3 million liveweight (LW) observations from 82,026 beef cattle over two years and 2,254 herd-average milk yield (MY) and compositional records from ∼300 Holstein dairy cows over seven years. The maximum temperature-humidity index (THI max ) was derived from climate data corresponding to production metrics. Cross-correlation analysis estimated lagged THI max effects, while linear regression and generalised additive models (GAM) assessed production impacts. We found an immediate (lag = 0 days) response of HS that increased LW ( b 1 = 0.0549 ± 0.0077, P < 0.0001), which progressively declined over time, reaching the highest negative influence at a 14-day lag ( b 1 = −0.0596 ± 0.0076, P < 0.0001). For MY, a delayed and substantial negative effect was observed at a 5-day lag ( b 1 = −0.0466 ± 0.0055, P < 0.0001), with similar patterns observed for protein and fat percentages at varying lags. Dairy cattle exhibited a THI threshold of 70, whereas thresholds for beef cattle remained inconclusive. Insights from dairy systems could inform HS impact assessment, the development of adaptive strategies, and the setting of regional thresholds for extensive beef production to sustain productivity and animal welfare.

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Publication Details

Journal
Computers and Electronics in Agriculture
Published
2025-11-04
DOI
https://doi.org/10.1016/j.compag.2025.111143
Citations
1
Primary Topic
Effects of Environmental Stressors on Livestock
Type
article
Field-Weighted Citation Impact
1.19
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article

Impact of heat stress on cattle systems: Responses of production metrics to thermal stress

1 citations
Computers and Electronics in Agriculture
Effects of Environmental Stressors on Livestock
1.19
article

Impact of heat stress on cattle systems: Responses of production metrics to thermal stress

article en
1 citations

Abstract

• Heat stress (HS) exhibited distinct time-lagged effects in beef and dairy systems. • Milk yield showed a strong negative response to HS with a 5-day lag. • Cattle liveweight rose initially, then declined sharply, peaking at a 14-day lag. • THI threshold of 70 identified for dairy; results for beef were inconclusive. • Insights from dairy systems can inform HS adaptation in extensive beef production. Heat stress (HS), a major consequence of climate change, significantly impairs cattle production and poses a threat to global food security. Assessing HS impacts in extensive production systems is challenging due to the diverse landscape and management practices. We evaluated the temporal HS effects on extensive beef and intensive dairy systems to identify thermal thresholds and inform adaptive strategies for sustaining productivity. The dataset comprised 1.3 million liveweight (LW) observations from 82,026 beef cattle over two years and 2,254 herd-average milk yield (MY) and compositional records from ∼300 Holstein dairy cows over seven years. The maximum temperature-humidity index (THI max ) was derived from climate data corresponding to production metrics. Cross-correlation analysis estimated lagged THI max effects, while linear regression and generalised additive models (GAM) assessed production impacts. We found an immediate (lag = 0 days) response of HS that increased LW ( b 1 = 0.0549 ± 0.0077, P < 0.0001), which progressively declined over time, reaching the highest negative influence at a 14-day lag ( b 1 = −0.0596 ± 0.0076, P < 0.0001). For MY, a delayed and substantial negative effect was observed at a 5-day lag ( b 1 = −0.0466 ± 0.0055, P < 0.0001), with similar patterns observed for protein and fat percentages at varying lags. Dairy cattle exhibited a THI threshold of 70, whereas thresholds for beef cattle remained inconclusive. Insights from dairy systems could inform HS impact assessment, the development of adaptive strategies, and the setting of regional thresholds for extensive beef production to sustain productivity and animal welfare.

Computers and Electronics in AgricultureVol. 240
The University of Sydney (AU), Charles Sturt University (AU), Bangladesh Livestock Research Institute (BD)
Zero hunger
Openalex Percentile: Top 17%
Effects of Environmental Stressors on Livestock
1.19
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