Comparative analysis of thermal indices for modeling cold and heat stress in US dairy systems

Quantifying the effect of thermal stress on milk yields is essential to effectively manage present and future risks in dairy systems. Despite the existence of numerous heat indices designed to communicate stress thresholds, little information is available regarding the accuracy of different indices in estimating milk yield losses from both cold and heat stress at large spatiotemporal scales. To address this gap, we comparatively analyzed the performance of existing thermal indices in capturing US milk yield response to both cold and heat stress at the national scale. We selected 4 commonly used thermal indices: the temperature-humidity index (THI), black globe humidity index (BGHI), adjusted temperature-humidity index (THIadj), and comprehensive climate index (CCI). Using a statistical panel regression model with observational and reanalysis weather data from 1981 to 2020, we systematically compared the patterns of yield sensitivities and statistical performance of the 4 indices. We found that the US state-level milk yield variability was better explained by the THIadj and CCI, which combine the effects of temperature, humidity, wind, and solar radiation. Our analysis also reveals continuous and nonlinear responses of milk yields to a range of cold to heat stresses across all 4 indices. This implies that solely relying on fixed thresholds of these indices to model milk yield changes may be insufficient to capture cumulative thermal stress. Cold extremes reduced milk yields comparably to those affected by heat extremes on the national scale. Additionally, we found large spatial variability in milk yield sensitivities, implying further limitations to the use of fixed thresholds across locations. Moreover, we found decreased yield sensitivity to thermal stress in the most recent 2 decades, suggesting adaptive changes in management to reduce weather-related risks.

Estimation of the economic impact of heat stress on the Chilean dairy regions by using two comfort thermal indices

The study aimed to estimate economic losses associated with heat stress in the eight dairy production regions (DPR), defined by the Dairy Chilean Consortium, using two comfort thermal indices, namely, the temperature-humidity index (THI) and the THI adjusted for solar radiation and wind speed (THIa). Hourly records from 19 weather stations (Nov - Mar 2017-2022) were collected to estimate the comfort thermal indices. The economic impact was estimated considering a critical threshold of 65 for both indices and the effect of higher values on loss in milk yield, days open, culling rate, and deaths. There were differences in the number of hours above the threshold among DPRs, independent of the thermal index used (P < 0.01). The greatest values were observed in DPRs I, II, and VIII, which concentrate most dairy cows. Average losses in milk yield were between 2.0 and 6.4 times higher when THIa was used instead of THI, which also depends on the DPR (P < 0.01). These estimations coincide with those observed empirically by producers. The lowest average economic losses per cow during the summer season (5 seasons average) occurred in DPR VI (US $ 91.5), and the highest losses were observed in DPR I (US $ 184.2) both using THIa. At the country level, economic losses fluctuate between US $ 29.0 and 108.4 million per summer season, depending on the comfort thermal index used. Finally, heat stress impacts negatively and significantly the Chilean dairy sector, which is highly dependent on the DPR.

Behavioural responses related to increasing core body temperature of grazing dairy cows experiencing moderate heat stress

Exposure to direct solar radiation, high ambient temperature, lack of wind movement, coupled with own metabolic heat production, makes grazing dairy cows vulnerable to heat stress. In pastures, it would be beneficial to monitor heat stress by observable changes in behaviour. We hypothesised that grazing dairy cows exhibit behavioural changes due to increasing heat load in temperate climate. Over two consecutive summers, 38 full-time grazing Holstein dairy cows were investigated in 12 experimental periods of up to 3 consecutive days where the cows were repeatedly exposed to various levels of moderate heat load determined by the comprehensive climate index (CCI). The CCI defines the ambient climate conditions, combining air temperature, relative humidity, solar radiation and wind speed. Vaginal temperature (VT) was automatically measured as an indicator of heat stress. In addition, as a less invasive method, we investigated if reticular temperature (RET) can be indicative of heat stress on pastures. Walking activity, lying-, feeding, and ruminating durations were recorded continuously with sensors. Respiration rate (RR), proximity to and competition at the water trough, social licking, self-licking, inter-individual distance, and fly intensity were directly observed. Data were analysed in the morning (0900-1100 h) and during the hottest time of day when cows were on pasture (1230-1430 h). The VT and RET showed similar patterns in relation to the CCI, suggesting that RET can be suitable for continuous monitoring of heat stress on pastures. In the morning, the cow's VT and RET did not relevantly react to the CCI. During the period 1230-1430 h, the cow's mean VT (mean vaginal temperature (VTMEAN); range: 37.7-40.3 °C) and mean RET (mean reticular temperature; range: 37.0-41.1 °C) were positively related to the mean CCI (mean comprehensive climate index) in this period (mean ± SD: 25.9 ± 5.71 °C). For cows with greater VTMEAN, an increased mean RR and decreased durations of walking, lying, feeding, and ruminating were found. These cows were also more likely to be in proximity to the water trough and to have small inter-individual distances. Changes in these traits seem to reflect behavioural adaptations to heat stress in a temperate climate and could be used to detect the heat stress in individual dairy cows on pastures.

The effect of climate index on growth values from birth to breeding in Akkaraman sheep

Under specific agroclimatic conditions, growth is an adaptability parameter resulting in reduced performance with decreasing animal comfort of a sheep breed. In this study, a total of 1011 lambs' live weights (LW) and average daily weight gains (ADG) in 16 different farms between 2018 and 2020 (birth to 18 months) were determined in Akkaraman herds raised in Çankırı Province of Turkey. Comprehensive Climate Index (CCI) was examined to determine the effect of climate. Thermal comfort limits in CCI values were classified as CCI-1.cold (≤ 5 ℃), CCI-2.comfort (5-25 ℃), and CCI-3.warm (≥ 25 ℃). The climatic values that all lambs examined were exposed to according to index value groups in periods from birth to 18 months of age were prepared daily. The lambs were exposed to comfort environment in the majority of the days in the MP0-3 (77.7%) and MP12-18 (50.1%) periods. The lambs mostly in the MP3-6 period (72.2%) were above the warm stress threshold, but in the MP6-12 period, 54.7% were above the cold stress threshold. Overall mean LW of lambs at birth, at 3, 6, 12, and 18 months were 4.29 kg, 35.1 kg, 39.1 kg, 45.4 kg, and 52.6 kg, while the ADG values between birth-3 months, 3-6 months, 6-12 months, and 12-18 months were 341.8 g, 54.5 g, 42.9 g, and 56.8 g respectively. Periodically, CCI values were realized as 10-15, 25-30, and 18-22 in the growth periods of 0-3, 3-6, and 12-18 months, respectively, and ADG values of the lambs were found to be similar within their own periods. However, when the CCI values of the lambs increase to 5 and above in the 06-12-month period, there is a decrease in their live weight. As a result, climatic index values did not have a negative effect on the growth and development values of lambs in cold conditions in general, but warm conditions affected the animals negatively.

The Anti-Müllerian Hormone as Endocrine and Molecular Marker Associated with Reproductive Performance in Holstein Dairy Cows Exposed to Heat Stress

Anti-Müllerian hormone (AMH) is proposed as a biomarker for fertility in cattle, yet this associative relationship appears to be influenced by heat stress (HS). The objective was to test serum AMH and AMH-related single nucleotide polymorphisms (SNPs) as markers potentially predictive of reproductive traits in dairy cows experiencing HS. The study included 300 Holstein cows that were genotyped using BovineSNP50 (54,000 SNP). A genome-wide association study was then executed. Nine intragenic SNPs within the pathways that influence the AMH gene were found important with multiple comparisons adjustment tests (p < 1.09 × 10-6). A further validation study was performed in an independent Holstein cattle population, which was divided into moderate (MH; n = 152) and severe heat-stressed (SH; n = 128) groups and then subjected to a summer reproductive management program. Serum AMH was confirmed as a predictor of fertility measures (p < 0.05) in MH but not in the SH group. Cows were genotyped, which revealed four SNPs as predictive markers for serum AMH (p < 0.01), reproductive traits (p < 0.01), and additional physiological variables (p < 0.05). These SNPs were in the genes AMH, IGFBP1, LGR5, and TLR4. In conclusion, serum AMH concentrations and AMH polymorphisms are proposed as predictive markers that can be used in conjunction with genomic breeding value approaches to improve reproductive performance in Holstein cows exposed to summer HS conditions.

Heat stress adaptation in cows - Physiological responses and underlying molecular mechanisms

Heat stress is a key abiotic stressor for dairy production in the tropics which is further compounded by the ongoing climate change. Heat stress not only adversely impacts the production and welfare of dairy cows but severely impacts the economics of dairying due to production losses and increased cost of rearing. Over the years, selection has ensured development of high producing breeds, however, the thermotolerance ability of animals has been largely overlooked. In the past decade, the ill effects of climate change have made it pertinent to rethink the selection strategies to opt for climate resilient breeds, to ensure optimum production and reproduction. This has led to renewed interest in evaluation of the impacts of heat stress on cows and the underlying mechanisms that results in their acclimatization and adaptation to varied thermal ambience. The understanding of heat stress and associated responses at various level of animal is crucial to device amelioration strategies to secure optimum production and welfare of cows. With this review, an effort has been made to provide an overview on temperature humidity index as an important indicator of heat stress, general effect of heat stress in dairy cows, and impact of heat stress and subsequent response at physiological, haematological, molecular and genetic level of dairy cows.

Determination of climatologically suitable places in Türkiye for feedlot cattle production using the Comprehensive Climate Index model

The purpose of this study was to determine climatologically suitable places to raise feedlot cattle in Türkiye. The Comprehensive Climate Index (CCI), a model that enables one to quantify beef cattle performance based on environmental conditions (temperature, relative humidity, wind speed, solar radiation) at any time in the year, was used to predict dry matter intake (DMI), average daily gain (ADG), and feed efficiency (FE) of feedlot cattle. Thirty years of daily average temperature, relative humidity, and wind speed values were obtained for 15 cities, namely, Antalya, Balikesir, Çorum, Diyarbakir, Edirne, Elazig, Erzincan, Erzurum, Eskisehir, Isparta, Izmir, Kayseri, Konya, Sivas, and Van. Measured daily solar radiation values were not available and values were calculated based on a formula that takes hemisphere, latitude, and day of the year into account. Since mostly dairy breed calves are placed into a feedlot in Türkiye, the Holstein option in the CCI model was chosen to calculate the maintenance energy requirement. Based on previous feedlot feeding studies conducted in Türkiye, it was assumed that calves would be placed on feed at 250 kg and be marketed at 520 kg, that the diet would have 2600 kcal/kg metabolic energy, and that DMI would be 2.31% of the body weight. Results indicate that cattle raised in Antalya (the hottest place) and Erzurum (the coldest place) had the lowest and highest DMI, respectively (P<0.05). Summer months depressed the DMI of cattle in hotter cities and winter months increased the DMI of cattle in colder cities (P<0.05). Feedlot cattle raised in hotter and colder regions of Türkiye had lower ADG than other places having a more temperate climate (P<0.05). In general, cattle raised in a hotter climate had better FE than those raised in a cold climate (P<0.05).

Vaginal temperature modeling in Holstein cows and cluster analysis by the cophenetic correlation coefficient

The objective was to establish a model for the prediction and characterization of vaginal temperature in Holstein cows, based on environmental predictors and thermal comfort indices, through cluster analysis, validation by the cophenetic correlation coefficient, and multiple regression analysis. The micrometeorological characterization of the site was carried out by recording the air temperature (T_air), the relative humidity (RH), the black globe temperature (BGT), the black globe temperature and humidity (BGHI), and dew point temperature (TDP). The recording of vaginal temperature (Tv) was performed in eight dairy cows using temperature sensors, equipped with data loggers, coupled with intravaginal devices. The data were analyzed using descriptive statistics and cluster analysis (CA) by using the hierarchical agglomerative method based on the value of the cophenetic correlation coefficient (CCC >0.70), in which representative physiological models were established, characterizing the Tv through multiple regression. In the afternoon the coefficient of variation (CV) was low for all variables, indicating homogeneity of the meteorological variables and efficiency of the ventilation system. The temperature and humidity index (THI) was mild only on the morning. There was a variation of 0.28 °C of Tv between shifts, sufficient to characterize the condition of comfort and stress of the animal, with values above 39 °C indicating animal stress. Tv showed strong correlation with BGT, T_air, TDP and RH, assuming that physiological variables, such as Tv, tend to have greater relationship with abiotic variables. Empirical models were established for estimating Tv based on the analyses performed in this study. Model 1 is recommended for TDP ranges of 14.00-21.00 °C and RH of 30-100%, while model 2 can be used for T_air situations up to 35 °C. The regression models for estimating Tv are promising for characterizing the thermal comfort of dairy cows housed in compost barn systems.

Genetic Markers Associated with Milk Production and Thermotolerance in Holstein Dairy Cows Managed in a Heat-Stressed Environment

Dairy production in Holstein cows in a semiarid environment is challenging due to heat stress. Under such conditions, genetic selection for heat tolerance appears to be a useful strategy. The objective was to validate molecular markers associated with milk production and thermotolerance traits in Holstein cows managed in a hot and humid environment. Lactating cows (n = 300) exposed to a heat stress environment were genotyped using a medium-density array including 53,218 SNPs. A genome-wide association study (GWAS) detected six SNPs associated with total milk yield (MY305) that surpassed multiple testing (p < 1.14 × 10^-6). These SNPs were further validated in 216 Holstein cows from two independent populations that were genotyped using the TaqMan bi-allelic discrimination method and qPCR. In these cows, only the SNPs rs8193046, rs43410971, and rs382039214, within the genes TLR4, GRM8, and SMAD3, respectively, were associated (p < 0.05) with MY305, rectal temperature (RT), and respiratory rate. Interestingly, these variables improved as the number of favorable genotypes of the SNPs increased from 0 to 3. In addition, a regression analysis detected RT as a significant predictor (R² = 0.362) for MY305 in cows with >1 favorable genotype, suggesting this close relationship was influenced by genetic markers. In conclusion, SNPs in the genes TLR4, GRM8, and SMAD3 appear to be involved in the molecular mechanism that regulates milk production in cows under heat-stressed conditions. These SNPs are proposed as thermotolerance genetic markers for a selection program to improve the milk performance of lactating Holstein cows managed in a semiarid environment.

Short-term physiological responses to moderate heat stress in grazing dairy cows in temperate climate

Even in temperate climate regions, an increase in ambient temperature and exposure to solar radiation can cause heat stress in lactating dairy cows. We hypothesised that grazing dairy cows exhibit short-term physiological changes due to increasing heat load under moderate climate conditions. Over two consecutive summers, 38 lactating Holstein dairy cows were studied in a full-time grazing system. Data were collected in 10 experimental periods of up to three consecutive days with a moderate comprehensive climate index (CCI). The individual animals' vaginal temperature (VT), heart rate, and locomotor activity data were automatically monitored with sensors. Blood samples and proportional whole milk samples were collected at afternoon milking. The concentrations of beta-hydroxybutyrate, glucose, non-esterified fatty acids, urea nitrogen, plasma thyroxine and triiodothyronine were analysed in blood plasma, and fat, protein, lactose, urea nitrogen, cortisol, Na⁺, K⁺, and Cl^- concentrations were analysed in milk. The daily distribution of VT recordings greater than 39 °C showed a circadian rhythm with a proportion of recordings of 2% and lower during the night and a percentage of 10% or higher in the afternoon. The cows' maximal daily vaginal temperature (VT_MAX) between 0830 and 1430 h was positively related to the mean daily CCI in the same time period (CCI_MEAN; mean and SD 23.6 ± 5.4 °C). Cows with greater VT_MAX had an increased mean heart rate, plasma glucose and milk cortisol concentrations and decreased concentrations of plasma thyroxine and triiodothyronine. The concentration of Na⁺ in milk was lower, and the concentration of K⁺ in milk tended to be higher in cows with increased VT_MAX. For beta-hydroxybutyrate, non-esterified fatty acids and urea nitrogen concentrations in plasma and fat and lactose concentrations in milk no relationships were found in terms of increasing VT. For milk urea nitrogen and protein concentrations, the proportion of total variance explained by inter-individual or -period variance was high. In conclusion, changes observed in milk and blood likely reflected short-term physiological responses to moderate heat stress. In particular, milk cortisol and Na⁺ may be useful traits for timely monitoring of heat stress in individual cows because their inter-individual variances were relatively small and samples can be collected non-invasively.

A systematic review of the effects of silvopastoral system on thermal environment and dairy cows' behavioral and physiological responses

Does the silvopastoral system (SPS) promote a satisfactory thermal environment for dairy cows to perform their natural behaviors and perform a suitable thermoregulatory function? To answer this, peer-reviewed articles, written in English and evaluating the effects of silvopastoral systems on thermal environment, dairy cows' behavior, and physiology were used in this systematic review; additionally, a bibliometric approach was performed. Web of Science and Google Scholar were used to compile the literature. The resulting articles (1448) underwent a 4-step appraisal process and resulted in 19 articles that fitted our inclusion criteria. Microclimate variables and thermal comfort indicators were the most researched topics (discussed in 89% of studies); 47% of studies addressed cattle behavior and 36% physiological responses. Our review highlights different benefits of silvopastoral systems for grazing dairy cows. For example, the SPS provides a more comfortable thermal environment than treeless pasture, which increases feeding behaviors; furthermore, dairy cows in SPS show lower drinking events, surface temperature, and respiratory rate than cows raised in treeless pasture. However, for nine of the variables related to cows' behavior (e.g., resting, rumination) and physiology responses (e.g., internal temperature), the results of the studies were unclear. Furthermore, behaviors associated with lying down (e.g., idling and rumination) and milk production in SPS were explored only in six and two studies, respectively. These findings provide consistent evidence that the silvopastoral systems are beneficial to thermal comfort of dairy cows; nonetheless, the effect on cows' behavioral and physiological responses is still scarce and unclear.

Understanding the relationship between weather variables and intake in beef steers

The relationship between weather variables and dry matter intake (DMI) in beef steers was examined using daily intake data from 790 beef steers collected through a computer-controlled feeding system in nonsummer months. Daily data were condensed into weekly averages (N = 13,895 steer-weeks). The variables considered to predict DMI (2.50 to 23.60 kg/d) were body weight (197 to 796 kg), dietary net energy for maintenance (NEm; 0.79 to 2.97 Mcal/kg), ambient temperature (-23.73 °C to 21.40 °C), range of temperature (2.79 °C to 19.43 °C), dew point (-27.84 °C to 14.34 °C), wind speed (2.08 to 6.49 m/s), solar radiation (30.8 to 297.1 W/m2), and 2-wk lag (average of previous 2 wk's values) and monthly lag (average of previous 4 wk's values) of each weather variable. Toeplitz variance-covariance structure for repeated measures was used to determine the model to predict DMI, while accounting for the effects of body weight, dietary NEm, and other variables in the model. Two-week lag of ambient temperature interacted (P ≤ 0.005) with 2-wk lag of range of temperature, monthly lag of wind speed, 2-wk lag of solar radiation, and dew point to predict DMI. Interactions (P = 0.0001) between 2-wk lag of range of temperature vs. dew point and monthly lag of wind speed vs. 2-wk lag of solar radiation were also detected. This study reports important weather variables associated with differences in DMI of growing and finishing steers and will help improve the accuracy of DMI prediction equations for beef cattle. Improvements in the accuracy of predicting DMI should give producers better tools to plan and execute efficient feeding management programs. The R2 of the overall model was 0.8891.

Impact of shade in beef feedyards on performance, ear temperature, and heat stress measures

A 2-yr study (year 1: March to September 2017; year 2: February to August 2018) was conducted using crossbred steers (year 1: n = 1677; initial body weight [BW] = 372 kg, SD = 47; year 2: n = 1713; initial BW = 379 kg, SD = 10) in a commercial feedyard study in Eastern NE to determine the effects of shade on cattle performance, ear temperature, and cattle activity. Two treatments were evaluated using a randomized complete block design (n = 5 blocks based on arrival). Treatments were assigned randomly to pens and consisted of five pens without shade (NO SHADE) and five pens with shade (SHADE). Ear temperatures were collected throughout the trials using biometric sensing ear tags on a subset of cattle. Panting scores were collected using a 5 point scale determined visually based on the level of panting occurring on the same subset of steers a minimum of twice weekly from June 8 to August 21 in year 1 and May 29 to July 24 in year 2 by one trained individual each year. In year 1, no differences (P ≥ 0.24) were observed for growth performance or carcass characteristics. Dry matter intake (DMI) and average daily gain (ADG) were greater (P ≤ 0.04) for SHADE cattle in year 2. Over the entire feeding period in year 1, greater (P < 0.01) ear temperature was observed for NO SHADE cattle, but cattle movement was not different (P = 0.38) between treatments. When evaluating the entire feeding period in year 2, cattle movement and ear temperature were not different (P ≥ 0.80) between treatments. Cattle in the SHADE treatment had lower (P ≤ 0.04) panting scores in years 1 and 2. These data suggest that providing shade can lessen the negative influence of heat events on DMI and was an effective way to reduce heat stress in feedlot operations, but only impacted ADG if heat events were close to the cattle slaughter date.

Research and application of a new multilevel fuzzy comprehensive evaluation method for cold stress in dairy cows

Effective and comprehensive evaluation of cold stress is critical for healthy dairy cow breeding in the winter. Previous studies on dairy cow cold stress have considered thermal environmental factors but not physiological factors or air quality. Therefore, this study aimed to propose a multilevel fuzzy comprehensive evaluation (FCE) method for cold stress in dairy cows based on the analytic hierarchy process (AHP) and a genetic algorithm (GA). First, the AHP was used to construct an evaluation index system for cold stress in dairy cows from 3 dimensions: thermal environment (temperature, relative humidity, wind speed, and illumination), physiological factors (respiratory rate, body surface temperature), and air quality [NH₃, CO₂, inhalable particulate matter (PM₁₀)]. Second, the consistency test of the judgment matrix was transformed into a nonlinear constrained optimization problem and solved using the GA. Next, based on fuzzy set theory, the comment set and membership function were established to classify the degree of cold stress into 5 levels: none, mild, moderate, high, and extreme. Then, the degree of cold stress in cows was obtained using multilevel fuzzy comprehensive judgment. To investigate the effect of illumination indicators on cold stress in dairy cows, 24 prelactation cows from the south and north sides were selected for a 117-d comprehensive cold stress evaluation. The results showed that the mean mild cold stress durations were 605.3 h (25.22 d) and 725.5 h (30.23 d) and the moderate cold stress durations were 67.2 h (2.8 d) and 96 h (4.0 d) on the south and north sides, respectively. Simultaneously, generalized linear mixed model showed that there were significant correlations between the daily cold stress duration and milk yield, feeding time, lying time, and active steps in the cows on both sides. This method can reasonably indicate cow cold stress conditions and better guide cold protection practices in actual production.

Solar radiation and temperature as predictor variables for dry matter intake in beef steers

Solar radiation may be an important weather variable that has not been included in previous dry matter intake (DMI) prediction models. Solar radiation affects the overall effective ambient temperature, which in turn contributes to the net gain of heat in an animal’s body. This experiment examined ambient temperature and solar radiation with DMI in beef steers. Data from 790 beef steers collected between 2011 and 2018 using an Insentec feeding system was used. Daily data was condensed into weekly averages (n = 13,895 steer-weeks). The variables considered for this study were DMI (2.50 to 23.60 kg/d), body weight (197 to 796 kg), calculated dietary energy density (NEm; 0.79 to 2.97 Mcal/kg), ambient temperature (-23.73 to 21.40°C), two-week lag of ambient temperature (-20.73 to 23.56°C), monthly lag of ambient temperature (-17.95 to 22.74°C), solar radiation (30.8 to 297.1 W/m2), two-week lag of solar radiation (34.6 to 272 W/m2) and monthly lag of solar radiation (43.7 to 256.6 W/m2). Residuals of DMI fitting week of the year (fixed) and experiment (random) were used to generate scatter plots with other explanatory variables to identify if non-linear relationships existed. Body weight and NEm had both linear and quadratic relationships with DMI, while the relationship with DMI for other variables was linear. The MIXED procedure of SAS with Toeplitz variance-covariance structure was used to determine the final model of DMI. After accounting for body weight and NEm in the model, two-week lag of ambient temperature and monthly lag of solar radiation interacted together (P = 0.0001), and this accounted for 0.7790 (R2) variation in DMI and improved the model fit. Therefore, these two variables and their interactions should be considered in DMI prediction equations of beef steers.

Predictive Models of Dairy Cow Thermal State: A Review from a Technological Perspective

Simple Summary

Heat stress in cattle is broadly defined as a physiological condition in which body temperature rises, and the animals are no longer able to adequately dissipate body heat to maintain thermal equilibrium due to environmental factors. Dairy cattle are particularly sensitive to heat stress because of the higher metabolic rate needed for milk production. Due to global warming and the expected growth of milk production in warmer regions, an increase in the occurrence of heat stress can only be avoided with the use of environmental control systems. However, most available systems were developed to take corrective measures or are not accurate enough to effectively prevent heat stress, as there is not yet an automated technological solution that considers all the environmental and animal variables that determine the occurrence of this condition. Further, these systems must be connected in time to prevent this condition in cattle but also disconnected when they are no longer needed, as their use raises major economic and environmental concerns regarding energy and water consumption. This review describes and discusses three types of predictive models that can make these systems more effective in preventing heat stress and more efficient in the use of energy and water.

Abstract

Dairy cattle are particularly sensitive to heat stress due to the higher metabolic rate needed for milk production. In recent decades, global warming and the increase in dairy production in warmer countries have stimulated the development of a wide range of environmental control systems for dairy farms. Despite their proven effectiveness, the associated energy and water consumption can compromise the viability of dairy farms in many regions, due to the cost and scarcity of these resources. To make these systems more efficient, they should be activated in time to prevent thermal stress and switched off when that risk no longer exists, which must consider environmental variables as well as the variables of the animals themselves. Nowadays, there is a wide range of sensors and equipment that support farm routine procedures, and it is possible to measure several variables that, with the aid of algorithms based on predictive models, would allow anticipating animals’ thermal states. This review summarizes three types of approaches as predictive models: bioclimatic indexes, machine learning, and mechanistic models. It also focuses on the application of the current knowledge as algorithms to be used in the management of diverse types of environmental control systems.

Thermodynamic assessment of heat stress in dairy cattle: lessons from human biometeorology

A versatile meteorological index for predicting heat stress in dairy cattle remains elusive. Despite numerous attempts at developing such indices and widespread use of some, there is growing skepticism about the accuracy and adequacy of the existing indices as well as the general statistical approach used to develop them. At the same time, precision farming of high-yielding animals in a drastically changing climate calls for more effective prediction and alleviation of heat stress. The present paper revisits classical work on human biometeorology, particularly the apparent temperature scale, to draw inspiration for advancing research on heat stress in dairy cattle. The importance of a detailed, mechanistic understanding of heat transfer and thermoregulation is demonstrated and reiterated. A model from the literature is used to construct a framework for identifying and characterizing conditions of potential heat stress. New parameters are proposed to translate the heat flux calculations based on heat-balance models into more tangible and more useful meteorological indices, including an apparent temperature for cattle and a thermoregulatory exhaustion index. A validation gap in the literature is identified as the main hindrance to the further development and deployment of heat-balance models. Recommendations are presented for systematically addressing this gap in particular and continuing research within the proposed framework in general.

Cooling temperature humidity index-days as a heat load indicator for milk production traits

Well-defined and accurate climatic indicators are important for evaluating heat stress in dairy cattle. This is imperative for sound management decisions for mitigating production losses. The most popular indicator for heat stress is the temperature humidity index (THI). Other heat stress indicators have been developed but remain largely unexploited. There is, therefore, possibly room to improve the THI and explore new indicators suitable for predicting production losses due to heat stress in dairy cattle. In this study, we apply the degree-day concept to develop temperature humidity index-day (THI-day). We defined the cooling THI-day as the hourly cumulative THI units above the heat stress threshold for milk production traits over the entire day. We then modeled reaction norms for cooling THI-day to analyze the effect of cumulative heat load expressed by THI-day on milk production traits. Milk performance records were from 16,216,145 monthly test-day records for the Fleckvieh breed for the period 2010 to 2019 in southern Bavaria, Germany. Individual cow records were averaged by herd and test-day resulting in 797,455 herd test-day records from 9,726 herds. Weather data for the same period were provided by the German Meteorological Service. Results indicated that cooling THI-day provided significant (p &lt; 0.001) additional information to the conventional THI models. We found out that reaction norm models of average herd milk yield that do not account for the cumulative heat load tend to underestimate the effects of heat stress on milk production traits. Reaction norms modeled with cooling THI-day were more plausible for milk production traits that have a defined heat stress threshold including milk yield, protein yield, and milk urea.

Vulnerability assessments in dairy cattle farms based on individual sensitivity to heat stress

Climate change (CC) is expected to increase temperatures and the frequency of extreme weather events, which renewed interest in heat stress (HS) effects on dairy cattle farms. Resilience is a key concept that should be considered to better understand the dairy farms exposure to HS and to combat CC-related risks. Thus, this study aimed to investigate the aspects of HS vulnerability for Tunisian dairy cattle farming systems. Historical milk test-day records from official milk recording were merged with temperature and humidity data provided by public weather stations. Firstly, different models relying in two heat load indices were applied for HS exposure assessment. Secondly, broken line models were used to estimate HS thresholds, milk losses, and rates of decline of milk production associated with temperature-humidity index (THI) across parities. Thirdly, individual cow responses to HS estimated using random regression model were considered as key measures of dairy farming system sensitivity assessment to HS. Dairy farms are annually exposed for 5 months to high THI values above 72 in Tunisia. The tipping points, at which milk yield started to decline over parities with 3-day average THI, ranged between 65 and 67. The largest milk decline per unit of THI above threshold values was 0.135 ± 0.01 kg for multiparous cows. The milk losses estimated due to HS in the Holstein breed during the summer period (June to August) ranged between 110 and 142 kg/cow in north and south, respectively. A high HS sensitivity was proved especially in dairy farms characterized by large herd size and high milk production level. Hence, providing knowledge of dairy farms vulnerability to HS may provide the basis for developing strategies to reduce HS effects and plan for CC adaptation.

Evaluation of environmental and physiological indicators in lactating dairy cows exposed to heat stress

This study aimed to better understand environmental heat stress and physiological heat strain indicators in lactating dairy cows. Sixteen heat stress indicators were derived using microenvironmental parameters that were measured at the surrounding of cows and at usual fixed locations in the barn by using handheld and fixed subarea sensors, respectively. Twenty high-producing Holstein-Friesian dairy cows (> 30.0 kg/day) from an intensive dairy farm were chosen to measure respiration rate (RR), vaginal temperature (VT), and body surface temperature of forehead (FT), eye (ET), and muzzle (MT). Our results show that microenvironments measured by the handheld sensor were slightly warmer and drier than those measured by the fixed subarea sensor; however, their derived heat stress indicators correlated equally well with physiological indicators. Interestingly, ambient temperature (T_a) had the highest correlations with physiological indicators and the best classification performance in recognizing actual heat strain state. Using segmented mixed models, the determined T_a thresholds for maximum FT, mean FT, RR, maximum ET, mean ET, VT, mean MT, and maximum MT were 24.1 °C, 24.2 °C, 24.4 °C, 24.6 °C, 24.6 °C, 25.3 °C, 25.4 °C, and 25.4 °C, respectively. Thus, we concluded that the fixed subarea sensor is a reliable tool for measuring cows' microenvironments; T_a is an appropriate heat stress indicator; FT, RR, and ET are good early heat strain indicators. The results of this study could be helpful for dairy practitioners in a similar intensive setting to detect and respond to heat strain with more appropriate indicators.

Climate change impacts shifting landscape of the dairy industry in Hawai`i

Proper knowledge and understanding of climatic variability across different seasons are important in farm management. To learn more about the potential effects of climate change on dairying in Hawaii, we conducted a study on site-specific climate characterization using several variables including rainfall, wind speed (WS), solar radiation, and temperature, at two dairy farms located on Hawai`i Island, Hawai`i, in Ookala named “OK DAIRY” and in Upolu Point named “UP DAIRY.” Temperature–humidity index (THI) and WS variations in the hottest four months (June to September) were analyzed to determine when critical thresholds that affect animal health are exceeded. Rainfall data were used to estimate the capacity of forage production in 6-mo wet (November to April) and dry (May to October) seasons. Future projections of temperature and rainfall were assessed using mid- and end-century gridded data products for low (RCP 4.5) and high emissions (RCP 8.5) scenarios. Our results showed that the “OK DAIRY” site received higher rainfall than the “UP DAIRY” site, favoring grass growth and forage availability. In addition, the “UP DAIRY” site was more stressful for animals during the summer (THI 69 to 73) than the “OK DAIRY” site (THI 67 to 70) as the THI exceeded the critical threshold of 68, which is conducive for high-lactating cattle. On the “UP DAIRY” site, the THI did not drop below 68 during the summer nights, which created fewer opportunities for cattle to recover from heat stress. Future projections indicated that air temperature would increase 1.3 to 1.8 °C by mid-century and 1.6 to 3.2 °C by the end-century at both farms, and rainfall will increase at the “OK DAIRY” site and decrease at the “UP DAIRY” site by the end-century. The agriculture and livestock industries, particularly the dairy and beef subsectors in Hawai`i, are vulnerable to climate changes as higher temperatures and less rainfall will have adverse effects on cattle. The findings in this study demonstrated how both observed and projected changes in climate support the development of long-term strategies for breeding and holistic livestock management practices to adapt to changing climate conditions.

Multi-week prediction of livestock chill conditions associated with the northwest Queensland floods of February 2019

The compound extreme weather event that impacted northern Queensland in February 2019 featured record-breaking rainfall, persistent high wind gusts and relatively cold day-time temperatures. This caused livestock losses numbering around 500,000 in the northwest Queensland Gulf region. In this study, we examine the livestock chill conditions associated with this week-long compound weather event and its potential for prediction from eleven world-leading sub-seasonal to seasonal (S2S) forecast systems. The livestock chill index combines daily rainfall, wind and surface temperature data. Averaged over the event week, the potential heat loss of livestock was in the moderate to high category, with severe conditions on the day of peak rainfall (5 February). Using calibrated forecasts from the Bureau of Meteorology's S2S forecast system, ACCESS-S1, a 1-week lead prediction showed a 20–30% probability of extreme livestock chill conditions over the northwest Queensland Gulf region, however the highest probabilities were located to the west of where the greatest livestock impacts were observed. Of the remaining ten S2S systems, around half predicted a more than 20% chance of extreme conditions, more than twice the climatological probability. It appears that the prediction accuracy arose from the skilful forecasts of extreme rainfall, as opposed to cold day-time temperature and strong wind forecasts. Despite a clear association between the observed extreme weather conditions and an active Madden–Julian Oscillation (MJO) event stalling in the western Pacific, the majority of 1-week lead S2S forecasts showed little indication of a slow-down in the MJO. As the livestock chill index was developed for southern Australian sheep, it may not be the best metric to represent the effects of exposure on tropical cattle breeds. Hence, this study draws attention to the need for tailored diagnostics that better represent the cold effects of summer tropical cyclones and tropical depressions on northern Australian livestock.

Increasing importance of heat stress for cattle farming under future global climate scenarios

In the last decades, livestock species have been severely affected by heat stress because of increasing temperatures, which has threatened animal welfare and decreased production. Based on thermal comfort indices and ensemble climate projections, we analyzed the current and future global spatiotemporal patterns of the heat exposure of cattle in 10 agroclimatic zones. The results show that ~7% of the global cattle population is currently exposed to dangerous heat conditions. This percentage is projected to increase to ~48% before 2100 under a scenario of growing emissions. Tropical agroclimatic zones are expected to face an early increase in the exposure to intense heat before 2050. Heat exposure was negatively correlated with the socioeconomic variables, showing that poor and livestock-dependent tropical countries are the most affected. Our results demonstrate the near-future consequences of heat stress on livestock, emphasizing the limited time available to implement effective abatement strategies.

Automated Monitoring of Cattle Heat Stress and Its Mitigation

Climate change related global warming is likely to continue, despite all mitigation measures taken by humans, due to the lag effect of long-term anthropogenic activities. Warming of the atmosphere can impact worldwide cattle production directly by compromising health, welfare and productivity, and indirectly by reducing the quality and quantity of animal feed. Under warm thermal conditions, cattle adjust their physiological and behavioural responses as an integral part of thermoregulation to maintain internal body temperature within a safe range. However, a greater intensity and duration of heat exposure can exceed thermoregulatory capacity leading to an increase in internal body temperature beyond the normal limit that ultimately evokes different animal responses to heat. In cattle, response to heat stress can be visually observed as elevated respiration rate or panting, but continuous visual monitoring is labour intensive, time consuming and subjective. Therefore, different weather-based indices have been developed such as the temperature humidity index (THI) and heat load index (HLI) which are commonly used weather-based indices for monitoring cattle heat stress at commercial level. However, the thermal comfort level of cattle based on weather-based indices has limited use at a microclimatic and individual animal level. Varying sensor-based approaches have shown promise to shift the focus of heat stress management to the individual level. Monitoring individual animal response and mitigation strategies for isolated heat-susceptible cattle could save on heat management costs whilst improving animal welfare and productivity. Here we review the technologies that enable automatic, continuous, and real-time cattle heat stress monitoring and mitigation under commercial conditions. Future platforms for autonomous monitoring and mitigation of heat stress in cattle are likely to be based on minimally-invasive smart technologies either singly, or in an integrated system, enabling real-time solutions to animal responses under various production systems and environmental conditions.

Developing of a model to predict lying behavior of dairy cows on silvopastoral system during the winter season

Lying behavior is an important indicator of the cows' welfare and health. In this study, we evaluate the effect of the physical environment on dairy cows' behaviors raised on a silvopastoral system through a predictive model. There was a difference (p<0.01) in soil surface temperature (SST) and black globe-humidity index (BGHI) between the shaded and sunny areas of the silvopastoral system. The BGHI was the variable most important to classify the cows' decision to seek shaded or sunny areas, while the soil surface temperature affected the choice for the area to perform the lying behaviors. In order to understand the influence of these parameters on cows' lying behavior, we developed another predictive model relating the SST and BGHI with cows lying at shaded and sunny areas. There was significance (p<0.01) for all model parameters. The odds of cows lying increased by approximately 2% with each degree of SST. In contrast, the probability of the cows lying in the shaded areas was 35% less than in sunny areas. The model developed in this study was efficient in identifying changes in the behavior of dairy cows in relation to physical environment. The BGHI influenced the areas used by cows to performing their standing behavior, while the areas used for lying behavior were influenced by the SST.

The Quest for Genes Involved in Adaptation to Climate Change in Ruminant Livestock

Livestock radiated out from domestication centres to most regions of the world, gradually adapting to diverse environments, from very hot to sub-zero temperatures and from wet and humid conditions to deserts. The climate is changing; generally global temperature is increasing, although there are also more extreme cold periods, storms, and higher solar radiation. These changes impact livestock welfare and productivity. This review describes advances in the methodology for studying livestock genomes and the impact of the environment on animal production, giving examples of discoveries made. Sequencing livestock genomes has facilitated genome-wide association studies to localize genes controlling many traits, and population genetics has identified genomic regions under selection or introgressed from one breed into another to improve production or facilitate adaptation. Landscape genomics, which combines global positioning and genomics, has identified genomic features that enable animals to adapt to local environments. Combining the advances in genomics and methods for predicting changes in climate is generating an explosion of data which calls for innovations in the way big data sets are treated. Artificial intelligence and machine learning are now being used to study the interactions between the genome and the environment to identify historic effects on the genome and to model future scenarios.

Evaluation of Thermal Indices as the Indicators of Heat Stress in Dairy Cows in a Temperate Climate

Many thermal indices (TIs) have been developed to quantify the severity of heat stress in dairy cows. Systematic evaluation of the representative TIs is still lacking, which may cause potential misapplication. The objectives of this study were to evaluate the theoretical and actual performance of the TIs in a temperate climate. The data were collected in freestall barns at a commercial dairy farm. The heat transfer characteristics of the TIs were examined by equivalent air temperature change (ΔTeq). One-way ANOVA and correlation were used to test the relationships between the TIs and the animal-based indicators (i.e., rectal temperature (RT), respiration rate (RR), skin temperature (ST), and eye temperature (ET)). Results showed that the warming effect of the increased relative humidity and the chilling effect of the increased wind speed was the most reflected by the equivalent temperature index (ETI) and the comprehensive climate index (CCI), respectively. Only the equivalent temperature index for cows (ETIC) reflected that warming effect of solar radiation could obviously increase with increasing Ta. The THI and ETIC showed expected relationships with the RT and RR, whereas the CCI and ETIC showed expected relationships with the ST and ET. Moreover, CCI showed a higher correlation with RT (r = 0.672, p < 0.01), ST(r = 0.845, p < 0.01), and ET (r = 0.617, p < 0.01) than other TIs (p < 0.0001). ETIC showed the highest correlation with RR (r = 0.850, p < 0.01). These findings demonstrated that the CCI could be the most promising thermal index to assess heat stress for housed dairy cows. Future research is still needed to develop new TIs tp precisely assess the microclimates in cow buildings.

Modeling of Heat Stress in Sows Part 2: Comparison of Various Thermal Comfort Indices

Heat stress has an adverse effect on the production performance of sows, and causes a large economic loss every year. The thermal environment index is an important indicator for evaluating the level of heat stress in animals. Many thermal indices have been used to analyze the environment of the pig house, including temperature and humidity index (THI), effective temperature (ET), equivalent temperature index of sows (ETIS), and enthalpy (H), among others. Different heat indices have different characteristics, and it is necessary to analyze and compare the characteristics of heat indices to select a relatively suitable heat index for specific application. This article reviews the thermal environment indices used in the process of sow breeding, and compares various heat indices in four ways: (1) Holding the value of the thermal index constant and analyzing the equivalent temperature changes caused by the relative humidity. (2) Analyzing the variations of ET and ETIS caused by changes in air velocity. (3) Conducting a comparative analysis of a variety of isothermal lines fitted to the psychrometric chart. (4) Analyzing the distributions of various heat index values inside the sow barn and the correlation between various heat indices and sow heat dissipation with the use of computational fluid dynamics (CFD) technology. The results show that the ETIS performs better than other thermal indices in the analysis of sows' thermal environment, followed by THI2, THI4, and THI7. Different pigs have different heat transfer characteristics and different adaptability to the environment. Therefore, based on the above results, the following suggestions have been given: The thermal index thresholds need to be divided based on the adaptability of pigs to the environment at different growth stages and the different climates in different regions. An appropriate threshold for a thermal index can provide a theoretical basis for the environmental control of the pig house.

Use of the Comprehensive Climate Index to estimate heat stress response of grazing dairy cows in a temperate climate region

The aim of the study was to assess the effect of the summer thermal environment on physiological responses, behaviour, milk production and its composition on grazing dairy cows in a temperate climate region, according to the stage of lactation. Twenty-nine Holstein Friesian multiparous cows were randomly selected and divided into two groups, according to the days in milk, as mid-lactation (99 to 170 d in milk, n = 15) and late lactation (225 to 311 d in milk, n = 14). The comprehensive climate index (CCI) was used to classify the hour of each day as thermoneutral or heat stress, considering a threshold value of CCI of 20°C. Data were collected for 16 d (summer 2017) and analysed as a completely randomized 2 × 2 factorial arrangement with repeated measurements over time. Vaginal temperature increased with CCI ≥ 20°C. Respiration rates were dependent on the thermal condition, regardless of days in milk. There was an interaction between the time of day and the CCI category for activity and rumination. Grazing activity decreased by 17.6% but lying down, standing, and shaded animals increased by 1.6, 9.8, and 6.3% respectively when CCI ≥ 20°C. Over 80% of cows presented a panting score ≥1. However, milk production and composition (fat, protein, and lactose concentrations as well as somatic cell count) were not affected by the thermal condition, although there was a numerical (non-significant) decrease in afternoon milk protein concentration on days with CCI ≥ 20°C, while urea in milk increased. In conclusion, thermal condition challenged grazing dairy cows' behaviour and physiology independent of the stage of lactation but had little or no effect on milk production.

The effects of heat stress on the behaviour of dairy cows – a review

Heat stress in livestock is a function of macro- and microclimatic factors, their duration and intensity, the environments where they occur and the biological characteristics of the animal. Due to intense metabolic processes, high-producing dairy cows are highly vulnerable to the effects of heat stress. Disturbances in their thermoregulatory capability are reflected by behavioural, physiological and production changes. Expression of thermoregulatory behaviour such as reduction of activity and feed intake, searching for a cooler places or disturbances in reproductive behaviours may be very important indicators of animal welfare. Especially maintain of standing or lying position in dairy cattle may be a valuable marker of the negative environmental impact. Highly mechanized farms with large numbers of animals have the informatic system can detect alterations automatically, while small family farms cannot afford these type of equipments. Therefore, observing and analysing behavioural changes to achieve a greater understanding of heat stress issue may be a key factor for developing the effective strategies to minimize the effects of heat stress in cattle. The aim of this review is to present the state of knowledge, over the last years, regarding behavioural changes in dairy cows (Bos Taurus) exposed to heat stress conditions and discuss some herd management strategies provided mitigation of the overheat consequences.

Recent Advances on Early Detection of Heat Strain in Dairy Cows Using Animal-Based Indicators: A Review

In pursuit of precision livestock farming, the real-time measurement for heat strain-related data has been more and more valued. Efforts have been made recently to use more sensitive physiological indicators with the hope to better inform decision-making in heat abatement in dairy farms. To get an insight into the early detection of heat strain in dairy cows, the present review focuses on the recent efforts developing early detection methods of heat strain in dairy cows based on body temperatures and respiratory dynamics. For every candidate animal-based indicator, state-of-the-art measurement methods and existing thresholds were summarized. Body surface temperature and respiration rate were concluded to be the best early indicators of heat strain due to their high feasibility of measurement and sensitivity to heat stress. Future studies should customize heat strain thresholds according to different internal and external factors that have an impact on the sensitivity to heat stress. Wearable devices are most promising to achieve real-time measurement in practical dairy farms. Combined with internet of things technologies, a comprehensive strategy based on both animal- and environment-based indicators is expected to increase the precision of early detection of heat strain in dairy cows.

Climate sensitivity of milk production traits and milk fatty acids in genotyped Holstein dairy cows

The aim of this study was the evaluation of climate sensitivity via genomic reaction norm models [i.e., to infer cow milk production and milk fatty acid (FA) responses on temperature-humidity index (THI) alterations]. Test-day milk traits were recorded between 2010 and 2016 from 5,257 first-lactation genotyped Holstein dairy cows. The cows were kept in 16 large-scale cooperator herds, being daughters of 344 genotyped sires. The longitudinal data consisted of 47,789 test-day records for the production traits milk yield (MY), fat yield (FY), and protein yield (PY), and of 20,742 test-day records for 6 FA including C16:0, C18:0, saturated fatty acids (SFA), unsaturated fatty acids (UFA), monounsaturated fatty acids (MUFA), and polyunsaturated fatty acids (PUFA). After quality control of the genotypic data, 41,057 SNP markers remained for genomic analyses. Meteorological data from the weather station in closest herd distance were used for the calculation of maximum hourly daily THI. Genomic reaction norm models were applied to estimate genetic parameters in a single-step approach for production traits and FA in dependency of THI at different lactation stages, and to evaluate the model stability. In a first evaluation strategy (New_sire), all phenotypic records from daughters of genotyped sires born after 2010 were masked, to mimic a validation population. In the second strategy (New_env), only daughter records of the new sires recorded in the most extreme THI classes were masked, aiming at predicting sire genomic estimated breeding values (GEBV) under heat stress conditions. Model stability was the correlation between GEBV of the new sires in the reduced data set with respective GEBV estimated from all phenotypic data. Among all test-day production traits, PY responded as the most sensitive to heat stress. As observed for the remaining production traits, genetic variances were quite stable across THI, but genetic correlations between PY from temperate climates with PY from extreme THI classes dropped to 0.68. Genetic variances in dependency of THI were very similar for C16:0 and SFA, indicating marginal climatic sensitivity. In the early lactation stage, genetic variances for C18:0, MUFA, PUFA, and UFA were significantly larger in the extreme THI classes compared with the estimates under thermoneutral conditions. For C18:0 and MUFA, PUFA, and UFA in the middle THI classes, genetic correlations in same traits from the early and the later lactation stages were lower than 0.50, indicating strong days in milk influence. Interestingly, within lactation stages, genetic correlations for C18:0 and UFA recorded at low and high THI were quite large, indicating similar genetic mechanisms under stress conditions. The model stability was improved when applying the New_env instead of New_sire strategy, especially for FA in the first stage of lactation. Results indicate moderately accurate genomic predictions for milk traits in extreme THI classes when considering phenotypic data from a broad range of remaining THI. Phenotypically, thermal stress conditions contributed to an increase of UFA, suggesting value as a heat stress biomarker. Furthermore, the quite large genetic variances for UFA at high THI suggest the consideration of UFA in selection strategies for improved heat stress resistance.

Effects of Outdoor Stocking Density on Growth, Feather Damage and Behavior of Slow-Growing Free-Range Broilers

Access to pasture is a main benefit of free-range broiler housing systems, yet the level of outdoor stocking density on broiler animal welfare remains unsettled. The growth, feather damage, pasture ranging and behaviors were assessed for 150 mixed-sex, slow-growing Freedom Rangers from 5 to 11 weeks of age of with free access to either a high outdoor stocking density pasture (0.5 m2 per bird) or a low outdoor stocking density pasture (2.5 m2 per bird). The probability (mean, 95% CI) of tail feather damage was greater for the high-density (23.1%, 16.3 to 31.7%) compared to the low-density group (11.9%, 7.1 to 19.3%). The percent of observations resulting in sunbathing and aggressive attacks (i.e., pecking and fighting behaviors) were greater for the high-density (1.0%, 0.6 to 1.8% and 0.5%, 0.2 to 1.3%, respectively) compared to the low-density group (0.3%, 0.1 to 0.7% and 0.1%, 0.0 to 0.4%, respectively). Furthermore, an interaction between treatment and age indicated that birds in the high-density group displayed greater stretching (during weeks 7 to 10) and panting (during weeks 6 and 9). Results of this study suggest that additional outdoor pasture space may be positively associated with broiler welfare.

Heat stress will detrimentally impact future livestock production in East Africa

Climate change-induced increases in temperature and humidity are predicted to impact East African food systems, but the extent to which heat stress negatively affects livestock production in this region is poorly understood. Here we use ERA-Interim reanalysis data to show that the frequency of 'Severe/Danger' heat events for dairy cattle, beef cattle, sheep, goats, swine and poultry significantly increased from 1981 to 2010. Using a multi-model ensemble of climate change projections for 2021-2050 and 2071-2100 (under representative concentration pathway (RCP) 4.5 and 8.5 by the coordinated regional-climate downscaling experiment for Africa (CORDEX-AFRICA)), we show that the frequency of dangerous heat-stress conditions and the average number of consecutive days with heat stress events will significantly increase, particularly for swine and poultry. Our assessment suggests that 4-19% of livestock production occurs in areas where dangerous heat stress events are likely to increase in frequency from 2071 to 2100. With demand for animal products predicted to grow in East Africa, production-specific heat-stress mitigation measures and breeding programmes for increasing heat tolerance are urgently needed for future livestock sector productivity-and future food security-in East Africa.

Spatiotemporal variations on infrared temperature as a thermal comfort indicator for cattle under agroforestry systems

With the expanding use of thermal assessment techniques in beef cattle, infrared thermography has become a promising tool for assessing the environment for animal thermal comfort. Goals of this study were: (1) to evaluate cattle thermal comfort in agroforestry systems with different shade availability (2) to verify the spatiotemporal variations of infrared temperature inside agroforestry systems, and; (3) to test infrared thermography as a potential tool to assess animal thermal comfort indices in agroforestry systems. A trial was carried out between June 2015 and February 2016, covering Central-Brazil's dry winter and rainy summer seasons, respectively. The experimental area of Embrapa Beef Cattle is located in Campo Grande (Mato Grosso do Sul), coordinates 20°24'53″ S, 54°42'26″ W and 558 m altitude. The 12 ha plot has two agroforestry systems varying shade availability. Traditional Black Globe Temperature and Humidity Index, Heat Load Index and Radiation Thermal Load were determined, from measurements using digital thermo-hygrometers, with datalogger. Surface temperature and humidity of tree canopies and pasture were determined using an infrared thermographic camera. Results show spatiotemporal variations in infrared temperature. This means that the environment inside agroforestry systems is not homogeneously comfortable for cattle, and the system with the lowest shade availability has the greatest heat accumulation area. Weak to strong associations were identified between infrared variables and thermal comfort indices (0.08 = r ≤ 0.75). Positive relationships were also obtained and equally well explained by the Black Globe Temperature and Humidity Index and Heat Load Index (0.55 = R² ≤ 0.94). We conclude that infrared thermography can be used as a tool to assess thermal comfort indices in agroforestry systems and to determine onset of animal thermal stress from environment and heat body accumulation.

Genetic parameter estimation for beef bull semen attributes

Improvements in bull reproductive performance are necessary to optimize the efficiency of cattle production. Female fertility has been enhanced through assisted reproductive technologies as well as genetic selection; however, improving beef bull fertility has been largely ignored. Phenotypes routinely collected at bull semen collection facilities are believed to affect fertility and provide the phenotypes necessary for a genetic evaluation. The first objective of this study was to determine the significant fixed effects for modeling beef bull fertility using data from bull semen collection facilities. The second objective was to estimate variance components, heritabilities, repeatabilities, and correlations between beef bull semen attributes. Beef bull fertility phenotypes including volume (VOL), concentration (CONC), number of spermatozoa (NSP), initial motility (IMot), post-thaw motility (PTMot), 3-h post-thaw motility (3HRPTMot), percentage of normal spermatozoa (%NORM), primary abnormalities (PRIM), and secondary abnormalities (SEC) were obtained from two bull semen collection facilities. A total of 1,819 Angus bulls with 50,624 collection records were analyzed. Of the fixed class and covariate effects tested, the significant class effects were collection location and collection day within year and the significant covariate effects included age at collection, days since previous collection, and cumulative comprehensive climate index (CCI). For this study, the CCI was calculated for a 75-d period including the 61-d spermatogenesis cycle and 14-d epididymal transit time. The 75 d prior to collection accounted for the environmental stress a bull may have experienced over the course of development of the spermatozoa, which was more significant than the CCI calculated for collection day or spermatogenesis start date. Pre-thaw beef bull semen traits had low heritability estimates of 0.11 ± 0.02 (VOL), 0.09 ± 0.02 (CONC), 0.08 ± 0.02 (NSP), and 0.12 ± 0.03 (IMot). Heritabilities of post-thaw beef bull semen attributes were more variable at 0.10 ± 0.02 (PTMot), 0.05 ± 0.04 (3HRPTMot), 0.10 ± 0.04 (%NORM), 0.03 ± 0.03 (PRIM), and 0.18 ± 0.04 (SEC). Correlations of breeding values for these traits with scrotal circumference (SC) expected progeny difference (EPD) are low. The low to moderate heritability estimates indicate that genetic improvement can be made in beef bull semen quality traits if new tools are developed to augment the scrotal circumference EPD that are currently available within the industry.

Climate change vulnerability of confined livestock systems predicted using bioclimatic indexes in an arid region of México

Climate change is a major world-wide challenge to livestock production because food security is likely to be compromised by increased heat stress of the animals. The objective of this study was to characterize, using bioclimatic indexes, two livestock regions located in an arid zone of México, and to use this information to predict the impact of global warming on animal production systems of these regions located in the state of Baja California (México). A 5-year database (i.e., 2011 to 2015) consisting of about one million data points from two zones (i.e., coast, valley) from four meteorological stations in the north of Baja California were used. Bioclimatic indexes were constructed for the four types of livestock production systems most common in this region, being: dairy cattle, beef cattle, sheep, pigs. The temperature-humidity index (THI) thresholds used to classify heat stress were determined and scaled for each livestock species as: THI_beef and THI_pig 74 units; THI_milk 72 units; and THI_sheep 23 units. Statistical differences between indices were detected (P < 0.01) during summer for the valley and coast zones as (THI_beef = 72.9 and 51.8; THI_milk = 80.6 and 67.4; THI_pigs = 83.9 and 65.2; THI_sheep = 29.5 and 20.1 units). Coast zone weather did not suggest vulnerability of livestock production systems to heat stress at any time of the year, but heat stress risk during summer for valley zone dairy cattle, sheep and pigs was classified as severe, but lower for feedlot cattle. Prediction models showed significant adjustment just in the coastal zone for THImilk, THIsheep, and THIsheep, suggesting more impact of global warming during summer in the coastal zone. Use of management strategies to reduce heat load of domestic animals during summer in northern Baja California is essential to maintain their productivity, with more emphasis in the valley zone.

Efficacy of Broilers as a Method of Face Fly (Musca autumnalis De Geer) Larva Control for Organic Dairy Production

The objective of this study was to evaluate Freedom-Ranger broiler chickens as a method to control face fly (Musca autumnalis De Geer) larvae in cow dung pats on pasture. Ninety-nine pats in three replicates were inoculated with first-instar larvae and exposed to one of four treatment conditions for 3 to 4 days: (1) an environment-controlled greenhouse (GH); (2) pasture without broilers (NEG); (3) pasture with 25 broilers stocked at a low density of 2.5 m2 of outdoor area per broiler (LOW); and (4) pasture with 25 broilers stocked at a high density of 0.5 m2 of outdoor area per broiler (HIGH). Broiler behaviors and weather conditions were recorded twice daily. Survival rates of larvae (mean, 95% CI) were similar for pats in the NEG (4.4%, 2-9%), LOW (5.6%, 3-11%), and HIGH (3.2%, 2-7%) groups, and was greatest for larvae reared in the GH (54.4%, 36-72%) group compared to all other groups. The proportion of broilers observed pasture ranging was 14.0% (6-28%) but was negatively related to solar radiation. Broilers were never observed foraging in pats. Results indicate that use of broilers may not be an effective method for controlling larvae of dung pat breeding flies.

Evaluation of thermal indices based on their relationships with some physiological responses of housed lactating cows under heat stress

Thermal indices as environmental risk indicators have been used to assess heat stress of dairy cows. The present study aimed to evaluate the predictive performance of the typical cattle-related thermal indices by comparing their prediction to heat stress levels and associations with some physiological responses. The study was conducted from August to September 2019 in a naturally ventilated barn in Jiangsu, China. Nine typical cattle-related thermal indices, i.e., temperature-humidity index (THI), black globe temperature index (BGHI), equivalent temperature index, effective temperature (ET) for dairy cows, respiratory rate predictor (RRP), adjusted temperature-humidity index (THIadj), heat load index (HLI), comprehensive climate index (CCI), and equivalent temperature index for cattle (ETIC), were evaluated. Respiration rate (RR) and body surface temperature (BST) were collected twice per day from a total of 287 lactating cows, 18 of which were continuously measured vaginal temperature (VT). Over the experimental period, the average daily RR, VT, and BST were 55.8 breaths/min, 38.7 °C, and 32.3 to 36.4 °C that depend on body positions, respectively. The study found that the prediction of THI, BGHI, THIadj, and CCI was closer to the actual heat stress conditions which were mild to moderate heat stress. Correlation analyses showed that RR, VT, and BST correlated most closely with effective temperature (r = 0.580; P < 0.05), BGHI (r = 0.642; P < 0.05), and CCI (r = 0.849; P < 0.05). In this evaluation, based on the comprehensive performance of CCI in the relatively accurate prediction to heat stress level and duration, detection on environmental differences between standing and lying zone, and correlations with some physiological responses, CCI is seemingly the promising thermal index to assess heat stress of housed dairy cows.

Micro- and Macroenvironmental Conditions and Stability of Terrestrial Models

Environmental variables can have profound effects on the biological responses of research animals and the outcomes of experiments dependent on them. Some of these influences are both predictable and unpredictable in effect, many are challenging to standardize, and all are influenced by the planning and conduct of experiments and the design and operation of the vivarium. Others are not yet known. Within the immediate environment where the research animal resides, in the vivarium and in transit, the most notable of these factors are ambient temperature, relative humidity, gaseous pollutant by-products of animal metabolism and physiology, dust and particulates, barometric pressure, electromagnetic fields, and illumination. Ambient temperatures in the animal housing environment, in particular those experienced by rodents below the thermoneutral zone, may introduce degrees of stress and thermoregulatory compensative responses that may complicate or invalidate study measurements across a broad array of disciplines. Other factors may have more subtle and specific effects. It is incumbent on scientists designing and executing experiments and staff responsible for animal husbandry to be aware of, understand, measure, systematically record, control, and account for the impact of these factors on sensitive animal model systems to ensure the quality and reproducibility of scientific studies.

Impact of summer heat stress on the thermal environment of bovine female genital tract

Summer heat stress (HS) is associated with a reduction in conception rate, increase in services per conception, and early embryonic death. However, the impact of summer HS on the thermal environment of different regions of the bovine female genital tract remains unknown. This study aimed to elucidate the effect of summer HS on the thermal environment of different regions of the genital tract in the cow. Three non-pregnant Japanese Black cows were investigated using a specially designed digital thermometer to record the temperatures of the rectum (RT), vagina (VT), cervix (CT), uterine body (UBT), and uterine horns (UHT) on days 0, 1, 2, 3, and 8 of the estrous cycle (day 0 = heat) in February (winter), May (spring), and August (summer). During the experiment, the temperature humidity index (THI) was recorded. THI during summer was higher (P ˂ 0.001) than in winter and spring (78.45 ± 0.32 vs. 60.26 ± 1.20 and 68.51 ± 0.80, respectively) and was higher than the alert THI indicating HS (i.e., THI > 73). Consequently, the VT, CT, UBT, and UHT were elevated during summer HS (P < 0.05) in comparison to winter and spring. THI was positively correlated (P < 0.01) with RT, VT, CT, UBT, and UHT. Linear regression revealed that VT, CT, UBT, and UHT increased by 0.05 °C per unit of THI. VT was more highly correlated than RT with THI and with the temperature of other regions of genital tract. HS induced increases in the temperatures of different regions of the female genital tract. The relationship between THI and VT could be incorporated into a mathematical model to predict the thermal load of HS on different regions of the female genital tract.

Methods to quantify heat stress in ruminants: Current status and future prospects

The physiology of hyperthermia or heat stress in mammals is complex. It is a totally systemic condition that in varying degrees involves all organs, tissues and body fluid compartments. The nature and magnitude of the response is influenced by animal specific characteristics (e.g. age, diet, body condition, gender, reproductive stage), environment and animal management. Given the multifaceted nature of heat stress, and the varied ruminant production systems based in varied geoclimatic zones, it has been difficult to find appropriate measures of heat stress for production ruminants. This has become an urgent challenge as production systems intensify globally in a warming climate. Bioclimatic indices such as the Temperature-Humidity Index (THI) have evolved to incorporate some measure of animal physiology. However, these indices do not have strong relationships with core temperature trajectories and altered respiratory dynamics of animals with excessive heat load. In recent decades, the careful physiology studies of the 1950-80s, have given way to numerous studies trialling a plethora of new technologies and computational approached to measure heat stress. Infrared thermography of body surface temperatures, automated measures of respiration rate and radiotelemetry of internal body temperatures are the most intensively researched. The common goal has been to find the 'holy grail' decision-making threshold or timepoint as to the animal's wellbeing. Are we making any progress?

Infrared thermography for microclimate assessment in agroforestry systems

In agroforestry systems, trees modify climatic parameters over a given area and create a complex microclimate through interactions between topography, plant composition and organizational structure of trees. In this way, indicators such as surface temperature of tree canopy and pasture, monitored by infrared thermography, are important to monitor the thermal environment of animal production and pasture establishment. Goals of this study were (1) to evaluate temporal and local variations of temperature and humidity leaf surface of tree canopy and pasture in agroforestry systems by infrared remote sensing and, (2) to validate infrared thermography as a potential tool for assessment microclimate in agroforestry systems. The study was carried out between June 2015 and February 2016 in an experimental area located at 54°370'W, 20°270'S and 530 m altitude, in Brazil. Surface temperatures and humidity of tree canopy and pasture in two agroforestry systems with different densities and tree spatial arrangements were determined using infrared thermography. Air, black globe and dew point temperatures, relative humidity and wind speed were measured using digital thermo-hygrometers with datalogger. Moderate to strong associations have been identified between microclimate parameters and those monitored by means of thermography measurements (0.45 ≥ r ≤ 0.78), suggesting positive relationships and equally well explained by air temperature, black globe temperature and relative air humidity (R² = 0.68 ≥ R² ≤ 0.98). Variations in hourly averages of temperatures and humidity of pasture and tree canopy show similar patterns between seasons, with consistently higheraverages during summer and under full sun, indicating the existence of a thermal band with leaf temperatures above air temperature. Therefore, this work's findings support use of infrared thermography as a tool for microclimate assessment in agroforestry systems.

Heat stress in dairy calves from birth to weaning

This Research Reflection collects current knowledge on the effects of heat stress in dairy calves. Chapters cover the concept of foetal programming, animal-based and environmental indicators of heat stress in the postnatal period, and methods of heat stress abatement. Conclusions for further research about economic efficiency, research methodology and an integrated approach of pre- and postnatal heat stress are also proposed.

Predicting rectal temperature and respiration rate responses in lactating dairy cows exposed to heat stress

Milk production and time effects are considered related to heat stress but they have not yet been combined in predictive models. In two parts, this study aimed to develop new models to predict heat stress (rectal temperature and respiration rate) of lactating dairy cows by inputting predictors, including ambient temperature (T_a), relative humidity (RH), wind speed (WS), milk yield (MY), and time blocks. In the first part of the study, we built the quantitative foundation for the second part, including the regression relation between respiration rate and rectal temperature (to convert predicted respiration rate to predicted body temperature), as well as between rectal temperature and respiration rate when heat stress was triggered (to recognize whether herds were under stress). In the second part, we built models that combined the abovementioned predictors to predict respiration rate. In part I, data were obtained from 45 high-producing Holstein cows within a T_a range of 9.5 to 30.8°C. We found a very strong correlation between mean respiration rate (MRR) and mean rectal temperature (MRT), where MRT = 0.021 × MRR + 37.6 (R² = 0.925), suggesting that for each 4.8 breaths per minute (bpm) increase of MRR, MRT would be expected to increase by 0.1°C. Rectal temperature was determined to be 38.6°C when heat stress was triggered, which corresponded to a respiration rate of 48 bpm. In part II, data were obtained in 3 stalls within a T_a range of 6.9 to 33.3°C over 3 time blocks, all of which were the 90 min preceding milking (0630-0800, 1230-1400, and 1830-2000 h). We found a nonlinear response of MRR to T_a, which could be linearized by the quadratic term of T_a. The response of MRR was the highest in the 0630-0800 h block, followed by 1230-1400 h, and finally 1830-2000 h. We proposed a model combining 3 time blocks (R² = 0.836): MRR in 0630-0800 h was determined to 56.28 + (-3.40 + 0.11 × T_a + 0.02 × RH) × T_a - 0.21 × RH - 2.82 × WS + 0.62 × MY; MRR in 1230-1400 h and 1830-2000 h were 4.6 and 10.3 bpm lower than that in 0630-0800 h, respectively (reducing the intercept of the expression in 0630-0800 h). Compared with temperature-humidity index equations, the proposed model performed better at suppressing prediction error, and had better sensitivity and accuracy in recognizing whether heat stress was triggered.