A comparison of THI indices leads to a sensible heat-based heat stress index for shaded cattle that aligns temperature and humidity stress

Effect of dietary electrolyte balance and arginine to lysine ratio on hematological, antioxidant and immunological traits in dual-purpose breeding hens under cyclic heat stress condition

A total of 245 hens and 35 cocks (32 weeks age) were assigned to seven treatment groups (five replicates with seven hens and one cock) to investigate the effect of dietary electrolyte balance (DEB) and arginine to lysine ratio (Arg/Lys) on birds' physiological and biochemical traits under cyclic heat stress (CHS) condition. Birds were housed in an environmentally controlled facility having four sectors. The first group (positive control, PC) was kept under thermoneutral conditions and fed diet with DEB of 180 mEq and Arg/Lys of 1.25, whereas the other six treatments were kept in the second sector under CHS and fed diet with DEB and Arg/Lys equal to: 180 mEq and 1.25 (negative control, NC); 250 mEq and 1.25; 320 mEq and 1.25; 180 mEq and 1.37; 250 mEq and 1.37; 320 mEq and 1.37, respectively. Hens on NC group had significantly decreased red blood cells (RBCs), white blood cells (WBCs) and its fractions. The groups fed different DEB and Arg/Lys in diet significantly enhanced the blood parameters and plasma lipid profile compared NC group. Hens under CHS fed on 250 and 320 DEB with 1.37 Arg/Lys recorded the lowest concentration of low-density lipoprotein (LDL) compared with the other groups. Triiodothyronine (T3) activity was not differed among groups, while T4 activity in layer exposed to CHS (NC group) recorded the highest activity compared to PC. From findings, it can be concluded that laying hens fed a diet having DEB 250 mEq with 1.37 Arg/Lys could be successfully applied to counteract the adverse effect of CHS and to improve blood hematological and biochemical traits, antioxidants, and immunity response.

Bioclimatic thermal stress indices and their relationships with andrological characteristics in hair rams

This study evaluated relationships among reproductive parameters and the bioclimatic indices: temperature and humidity index (THI), equivalent temperature index (ETI), black globe temperature and humidity index (BGTHI), and thermal comfort index (TCI), during the first 45 days of spermatogenesis (SP-45) and during the 15 days of sperm transit through the epididymis (STP-15) that preceded the reproductive assessments (ReA). Such information is useful in determining the optimal breeding season in Northeast Brazil. Santa Inês rams (n = 25) underwent two ReA in three periods of the year (D-P = dry; R-P = rainy and RD-P = rainy/dry transition), and the bioclimatic indices were calculated at the corresponding SP-45 and STP-15 timepoints prior to each ReA. Sperm kinetic parameters in D-P were depressed compared to R-P and RD-P (P < 0.05). The index values had an antagonistic relationship with most parameters and regression analysis demonstrated that the BGTHI and the TCI had a negative association with the progressive motility, curvilinear, straight line, and average path velocities, and a positive association with slow sperm in the ejaculate in SP-45 and STP-15 phases (P < 0.01). Semen quality kinetics is affected throughout the year by the environment and it is apparent that it is impaired in D-P and better in R-P and RD-P seasons. The BGTHI and TCI measured in the sperm production phase classified the environment most coherently and presented better association with the behavior of sperm kinetics.

Effects of isoenergetic supplementation as water use mitigation strategy on water footprint and health of nursing bull calves

Sustainable livestock systems focus on mitigating natural resource use such as water. Dietary management strategies can significantly reduce the water footprint of livestock animals; however, animal health is of concern when animals reduce water intake due to subacute dehydration. To evaluate potential consequences of this nutritional management intervention, a total of 23, 60 ± 3 days old nursing Holstein bull calves, weighing 94.7 ± 12.07 kg, were distributed in a completely randomized design and received one of three diets. Control was a basal diet composed of a non-medicated milk replacer (milk replacer; n = 7), and the additional two diets, were composed of the same non-medicated milk replacer in addition to either lipid [n = 8; milk replacer + menhaden fish oil (3 %)] or soluble carbohydrate [n = 8; milk replacer + corn starch (7%) isoenergetic to fat group] supplements. Animals were offered ad libitum mineral mix and water, as well as 120 g/day of a composite mix of dried microbrewery's spent grains. Data were analyzed as linear and generalized linear mixed models with diet as a fixed effect and animal as random utilizing R studio (R Core Team, 2021, Vienna, Austria; SAS Inst., Cary, NC). Within supplementation groups, lipid supplemented calves had the highest lymphocyte (63.24 vs 57.69 counts/100 lymphocytes; P < 0.033), and lowest neutrophil counts (29.3 vs 35.3 counts/100 lymphocytes; P < 0.047). Supplementation significantly increased total serum protein (P = 0.001) and skin moisture (P < 0.011), with carbohydrate group having the highest skin moisture (5.30 vs 3.99; P < 0.047). Supplementation also decreased fecal fluidity scores (P < 0.001) with no significant change in serum electrolytes (P > 0.256). No significant differences were found amongst treatments for the ingestive behavior (P > 0.338). The carbohydrate-supplemented calves significantly decreased all daily water footprints compared to the control and fat-supplemented groups: blue a 47.55 L decrease, (P < 0.001), green a 265.62 L decrease (P = 0.005), and gray a 55.87 L decrease (P = 0.009) water footprint, as well as total water footprint (369.04 L, P = 0.004). Our results indicate the potential to maintain animal performance while increasing water use efficiency through diet supplementation tailored to mitigate water use, without adverse effects on animal health.

Effect of Environmental and Farm-Associated Factors on Live Performance Parameters of Broilers Raised under Commercial Tropical Conditions

Although temperature, relative humidity, and farm-associated factors are known to affect broiler live performance, data about the impact of these variables under commercial operations are still scarce. This study aimed to evaluate the effect of temperature, relative humidity, a thermal humidity index, management, and farm-associated factors on BW, BW gain, feed conversion ratio (FCR), and mortality of broilers raised to 35 d under commercial tropical conditions. The data analyzed included performance records of Ross 308 AP broiler flocks placed between 2018 and 2020. Environmental monitoring information was obtained from electronic sensors that captured data hourly from 80 flocks in 29 farms. Farm-associated factors were gathered using a survey of 86 farms. Three data analyses were conducted in parallel. Correlation analyses, one-way ANOVA, and machine learning techniques were employed. Results indicated that BW and BW gain were reduced, and FCR worsened (p < 0.001) up to 21 d when chickens were mainly exposed to temperatures 2.5 °C lower than the recommended optimums for each age period. At the same time, mortality at 28 and 35 d increased. In conclusion, all farm-associated factors affected chicken live performance. Variable importance analysis indicated that performance results at 14 and 21 d were significant to predict BW at 35. At the same time, sex, distance between the hatchery and farm, and farm altitude accounted for the most significant contributions from the farm-associated factors.

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.

Heat wave exposure impairs reproductive performance in primiparous sows and gilts in a tropical environment

We studied the effects of heat waves (HW), defined as three consecutive days with an ambient temperature ≥ 25 °C and a temperature and humidity index (THI) > 74, on the reproductive performance of sows. Meteorological data were obtained from the National Institute of Meteorology and reproductive data from a commercial farm with 51,578 inseminations and 49,103 pregnancies from September 5, 2013, to July 12, 2019. Sows were divided into the following groups according to the parity order: group 1 (sows that did not experience HW on the day of insemination) and group 2 (sows exposed to HW on the day of insemination). The percentage of days that pregnant sows were exposed to HW was calculated as 0 to 25% (1), 26 to 50% (2), 51 to 75% (3), and > 75% (4). Out of a total of 2137 days, there were 160 HW and more than 10 HW per month, except in May, June, and July. Gilts in group 2 showed a decrease in the percentage of gestation (98.21% and 98.78%, respectively, P = 0.0267) and the percentage of births compared with those in group 1 (95.53% and 96.61, respectively, P = 0.0065). Primiparous sows in group 2 had a higher percentage of abortions than gilts in group 1 (3.20% and 2.42%, respectively; P = 0.0334). Sows exposed to more than 50% HW during gestation produced more mummified piglets than sows exposed to less than 50% HW. The number of stillborn piglets was higher in sows exposed to temperatures above 25% HW during gestation. The occurrence of heat waves in gilts and primiparous sows impairs reproductive performance.

Haemonchus contortus Parasitism in Intensively Managed Cross-Limousin Beef Calves: Effects on Feed Conversion and Carcass Characteristics and Potential Associations with Climatic Conditions

The objectives of the study were: (a) to study the effect of Haemonchus spp. on the growth performance characteristics of fattening calves, (b) to assess any potential effects on carcass characteristics and (c) to investigate the potential role of climatic conditions in the process of the infection. The study was conducted for 201 days in an intensively managed cross-Limousin herd. The animals were divided into two equal groups: those receiving anthelmintic treatment (AT) and the untreated (C) controls. The same nutritional regime was applied to both groups and the feed consumption was calculated daily. Standard parasitological examinations were performed at weekly intervals. At slaughter, carcasses were weighed and assessed for conformation and fat cover classes. Climatic variables were obtained for the location of the farm and a temperature-humidity index was calculated. Before anthelmintic treatment with ivermectin, there was no difference in parasitic burdens between the two groups: 544 (AT) vs. 554 (C) epg, whilst after it, counts were 0 and 450–700 epg, respectively, with over 96% of larvae identified as Haemonchus spp. and, later, confirmed as Haemonchus contortus. It was concluded that treated animals had a higher average total bodyweight gain, higher feed conversion ratio and carcass yield of superior quality than controls. There was a difference between the two groups in the pattern of reduction of dry matter intake as the temperature-humidity index increased.

Bioclimatic zoning for dairy cows in Brazil by statistical modeling

BACKGROUND

Climate conditions affect animal welfare directly, influencing milk production. The Midwest region is the largest cattle-producing region in Brazil. The objective of this study was to elaborate on bioclimatic zoning for dairy cattle in the Midwest region of Brazil. Air temperature (Ta, °C) and relative humidity (%, RH) data from a 30-year historical series (1989-2019) collected by the National Aeronautics and Space Administration/Prediction of Worldwide Energy Resources (NASA/POWER) platform were used. The Temperature and Humidity Index (THI) was determined for the hottest and coldest months. Milk production losses due to climate factors in the Midwest of Brazil for two daily production levels, 10 kg Milk (PL10) and 25 kg Milk (PL25), were estimated.

RESULTS

The Midwest presented three THI classifications throughout the year: 'normal', 'alert', and 'critical alert'. The entire Midwest region was classified as 'normal' (THI < 70) between autumn and winter. The decrease in milk production (DMP) during the autumn and winter presented no loss for both production levels (PL10 and PL25).

CONCLUSION

On the other hand, a 1 to 2 kg reduction in milk production was observed for cows with a PL25 production level between spring and summer in the southern Midwest region, while cows with a PL10 production level showed no reduction in milk production. Only the cities of Sinop and Cuiabá did not present a 'critical alert' during spring/summer for the risk of heat stress. © 2021 Society of Chemical Industry.

Estimating milk production losses by heat stress and its impacts on greenhouse gas emissions in Korean dairy farms

Meteorological disasters caused by climate change like heat, cold waves, and unusually long rainy seasons affect the milk productivity of cows. Studies have been conducted on how milk productivity and milk compositions change due to heat stress (HS). However, the estimation of losses in milk production due to HS and hereby environmental impacts of greenhouse gas (GHG) emissions are yet to be evaluated in Korean dairy farms. Dairy milk production and milk compositions data from March to October 2018, provided by the Korea Dairy Committee (KDC), were used to compare regional milk production with the temperature-humidity index (THI). Raw data for the daily temperature and relative humidity in 2018 were obtained from the Korea Meteorological Administration (KMA). This data was used to calculate the THI and the difference between the maximum and minimum temperature changing rate, as the average daily temperature range, to show the extent to which the temperature gap can affect milk productivity. The amount of milk was calculated based on the price of 926 won/kg from KDC. The results showed that the average milk production rate was the highest within the THI range 60–73 in three regions in May: Chulwon (northern region), Hwasung (central region), and Gunwi (southern region). The average milk production decreased by 4.96 ± 1.48% in northern region, 7.12 ± 2.36% in central region, and 7.94 ± 2.57% in southern region from June to August, which had a THI range of 73 or more, when compared to May. Based on the results, the level of THI should be maintained like May. If so, the farmers can earn a profit of 9,128,730 won/farm in northern region, 9,967,880 won/farm in central region, and 12,245,300 won/farm in southern region. Additionally, the average number of cows raised can be reduced by 2.41 ± 0.35 heads/farm, thereby reducing GHG emissions by 29.61 ± 4.36 kg CO₂eq/day on average. Overall, the conclusion suggests that maintaining environmental conditions in the summer that are similar to those in May is necessary. This knowledge can be used for basic research to persuade farmers to change farm facilities to increase the economic benefits and improve animal welfare.

An Appropriate Genetic Approach for Improving Reproductive Traits in Crossbred Thai-Holstein Cattle under Heat Stress Conditions

Thailand is a tropical country affected by global climate change and has high temperatures and humidity that cause heat stress in livestock. A temperature−humidity index (THI) is required to assess and evaluate heat stress levels in livestock. One of the livestock types in Thailand experiencing heat stress due to extreme climate change is crossbred dairy cattle. Genetic evaluations of heat tolerance in dairy cattle have been carried out for reproductive traits. Heritability values for reproductive traits are generally low (<0.10) because environmental factors heavily influence them. Consequently, genetic improvement for these traits would be slow compared to production traits. Positive and negative genetic correlations were found between reproductive traits and reproductive traits and yield traits. Several selection methods for reproductive traits have been introduced, i.e., the traditional method, marker-assisted selection (MAS), and genomic selection (GS). GS is the most promising technique and provides accurate results with a high genetic gain. Single-step genomic BLUP (ssGBLUP) has higher accuracy than the multi-step equivalent for fertility traits or low-heritability traits.

Environmental Heat Exposure Among Pet Dogs in Rural and Urban Settings in the Southern United States

With advancing global climate change, heat-related illnesses and injuries are anticipated to become more prevalent for humans and other species. Canine hyperthermia is already considered an important seasonal emergency. Studies have been performed on the risk factors for heat stroke in canine athletes and military working dogs; however there is limited knowledge on environmental risk factors for the average pet dog. This observational study explores variation in individually experienced environmental temperatures of pet dogs (N = 30) in rural and urban environments in central Alabama. Temperature data from dogs and their owners was collected using wearable personal thermometers. Demographic data on the dogs was collected using a brief survey instrument completed by their owners. Dogs included in the study varied in signalment, activity level, and home environment. Linear mixed effects regression models were used to analyze repeated measure temperature and heat index values from canine thermometers to explore the effect of environmental factors on the overall heat exposure risk of canine pets. Specifically, the heat exposures of dogs were modeled considering their owner's experienced temperatures, as well as neighborhood and local weather station measurements, to identify factors that contribute to the heat exposure of individual dogs, and therefore potentially contribute to heat stress in the average pet dog. Results show hourly averaged temperatures for dogs followed a diurnal pattern consistent with both owner and ambient temperature measurements, except for indoor dogs whose recordings remained stable throughout the day. Heat index calculations showed that owners, in general, had more hours categorized into the National Weather Station safe category compared to their dogs, and that indoor dogs had a greater proportion of hours categorized as safe compared to outdoor dogs. Our results suggest that the risk of the average pet dog to high environmental heat exposure may be greater than traditional measures indicate, emphasizing that more localized considerations of temperature are important when assessing a dog's environmental risk for heat-related injury or illness.

Thermal Comfort Index for Lactating Water Buffaloes under Hot and Humid Climate

Simple Summary

Heat stress drastically affects the productive and reproductive performance of animals in addition to causing welfare issues. Therefore, thermal comfort is an important consideration to avoid performance losses and other adverse effects of heat stress on animal physiology under various production systems. Moreover, it is becoming more important under the recent scenario of climate change. The present study was conducted to develop a thermal comfort index for buffaloes. Physiological parameters of buffaloes and environmental variables were recorded to develop the index models through typical correlation. The most accurate model was based on body surface temperature, rectal temperature and respiratory rate and can be used effectively to indicate the state of thermal comfort in buffaloes under hot and humid climate.

Abstract

Heat stress results in serious performance losses and adversely affects animal health and welfare under various production systems. This study was conducted to develop a thermal comfort model for lactating buffaloes under hot and humid climate. Twenty Nili-Ravi buffaloes were randomly enrolled for this one-year study. Physiological parameters including rectal temperature (RT), respiratory rate (RR), and body surface temperature (BST) and environmental variables such as wet bulb temperature (WBT), dew point temperature (DPT), and black globe temperature (BGT) were recorded twice a week on each Tuesday and Thursday (n = 1602 and 1560, respectively) at 8:00 am and 2:30 pm. Moreover, ambient temperature (AT, °C) and relative humidity (RH, %), at an interval of every 30 min were recorded. We used a typical correlation analysis to build the index models for thermal comfort. The results revealed that AT positively correlated with BGT, WBT, DPT, BST, RT, and RR, while RH negatively correlated with RT. Moreover, a physiological index model consisting of BST, RT and RR (P1 = 0.578 × BST + 0.047 × RT + 0.429 × RR) and an environmental index model (E1 = 0.881 × AT + 0.194 × RH + 0.455 × BGT − 0.347 × WBT + 0.032 × DPT) proved to be a more accurate index as a pair to reveal the state of thermal comfort in lactating buffaloes. Moreover, these models correlated well with physiological variables, indicating that this this pair of index models can be used to effectively evaluate the thermal comfort in buffaloes.

Spatial variability and exploratory inference of abiotic factors in barn compost confinement for cattle in the semiarid

The assessment of environmental conditions in the creation of dairy cattle in feedlots must be carried out to identify possible causes of stress and assist producers in the decision-making process. The objective was to characterize the abiotic factors and bed temperature, in the comfort conditions of dairy cows, through geostatistics and exploratory data inference, in a Compost Barn System in the Brazilian semiarid region. The data were obtained in a milk production unit, located in the municipality of Lajedo, Pernambuco, Brazil. The variables air temperature (Tair), relative humidity (RH), wind speed (WS), illuminance (Lux), skin temperature (Ts), bed temperature (Tb) were recorded and the temperature index was determined and humidity (THI). Data were recorded at 9:00 a.m., 12:00 p.m., and 03:00 p.m., over 5 days in the summer season. For geostatistical analysis, the classic semivariances were determined. The principal component analysis was performed to establish an index that characterized the condition of animal comfort. The variables Tair, RH, Tb, and THI showed a low coefficient of variation for all times. The best fit to the models of the semivariograms was the Gaussian at 9:00 a.m. and 03:00 p.m., and the spherical at 12:00 p.m. The Tb spatial variability was low for all studied hours. Tair showed a strong correlation with Tb, due to the process of heat transfer by convection from the floor to the environment. Geostatistics and exploratory data analysis allowed the establishment of a comfort index for Compost Barn production systems in the Brazilian semiarid region (R² = 0.996; p < 0.0001).

Non-Invasive Sheep Biometrics Obtained by Computer Vision Algorithms and Machine Learning Modeling Using Integrated Visible/Infrared Thermal Cameras

Live sheep export has become a public concern. This study aimed to test a non-contact biometric system based on artificial intelligence to assess heat stress of sheep to be potentially used as automated animal welfare assessment in farms and while in transport. Skin temperature (°C) from head features were extracted from infrared thermal videos (IRTV) using automated tracking algorithms. Two parameter engineering procedures from RGB videos were performed to assess Heart Rate (HR) in beats per minute (BPM) and respiration rate (RR) in breaths per minute (BrPM): (i) using changes in luminosity of the green (G) channel and (ii) changes in the green to red (a) from the CIELAB color scale. A supervised machine learning (ML) classification model was developed using raw RR parameters as inputs to classify cutoff frequencies for low, medium, and high respiration rate (Model 1). A supervised ML regression model was developed using raw HR and RR parameters from Model 1 (Model 2). Results showed that Models 1 and 2 were highly accurate in the estimation of RR frequency level with 96% overall accuracy (Model 1), and HR and RR with R = 0.94 and slope = 0.76 (Model 2) without statistical signs of overfitting.

Artificial Intelligence Applied to a Robotic Dairy Farm to Model Milk Productivity and Quality based on Cow Data and Daily Environmental Parameters

Increased global temperatures and climatic anomalies, such as heatwaves, as a product of climate change, are impacting the heat stress levels of farm animals. These impacts could have detrimental effects on the milk quality and productivity of dairy cows. This research used four years of data from a robotic dairy farm from 36 cows with similar heat tolerance (Model 1), and all 312 cows from the farm (Model 2). These data consisted of programmed concentrate feed and weight combined with weather parameters to develop supervised machine learning fitting models to predict milk yield, fat and protein content, and actual cow concentrate feed intake. Results showed highly accurate models, which were developed for cows with a similar genetic heat tolerance (Model 1: n = 116, 456; R = 0.87; slope = 0.76) and for all cows (Model 2: n = 665, 836; R = 0.86; slope = 0.74). Furthermore, an artificial intelligence (AI) system was proposed to increase or maintain a targeted level of milk quality by reducing heat stress that could be applied to a conventional dairy farm with minimal technology addition.

Review: Challenges for dairy cow production systems arising from climate changes

The so-called global change refers to changes on a planetary scale. The term encompasses various issues like resource use, energy development, population growth, land use and land cover, carbon and nitrogen cycle, pollution and health, and climate change. The paper deals with challenges for dairy cattle production systems in Europe arising from climate change as one part of global changes. Global warming is increasing, and therefore ecosystems, plant and animal biodiversity, and food security and safety are at risk. It is already accepted knowledge that the direct and indirect effects of global warming in combination with an increasing frequency of weather extremes are a serious issue for livestock production, even in moderate climate zones like Central Europe. The potential and already-measurable effects of climate change (including increase in temperature, frequency of hot days and heat waves), in particular the challenges on grassland production, fodder quality, nutrition in general, cow welfare, health as well as performance of dairy production, will be reviewed. Indirect and direct effects on animals are correlated with their performance. There are clear indications that with selection for high-yielding animals the sensitivity to climate changes increases. Cumulative effects (e.g. higher temperature plus increased pathogen and their vectors loads) do strengthen these impacts. To cope with the consequences several possible adaptation and mitigation strategies must be established on different levels. This includes changes in the production systems (e.g. management, barn, feeding), breeding strategies and health management.

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.

Variations in the Temperature-Humidity Index and Dorsal Fat Thickness during the Last Trimester of Gestation and Early Postpartum Period Affect Fertility of Bos indicus Cows in the Tropics

In order to measure the influence of the temperature-humidity index (THI) and the variation of fat thickness on reproductive performance, ninety-two Bos indicus cows kept under grazing conditions were used in two farms in Veracruz (Mexico) and Puntarenas (Costa Rica). THI was calculated with the average environmental temperature and relative humidity. Measurements of fat thickness (FAT) were taken two weeks apart from the last trimester of gestation to approximately 80 days postpartum (dpp). Natural breeding was used in both farms. Time to conception was calculated based on the interval from days at risk to conception (DRC), which had to be at least 28 dpp. THI was between 65.4 ± 2.9 and 73.2 ± 1.5 in Veracruz and 75.4 ± 0.26 and 76.5 ± 0.55 in Puntarenas. Variations in THI were observed in Puntarenas whereas in Veracruz THI variations were more prominent. In Veracruz, loss of fat during the last trimester of gestation was on average 8.5%, whereas in the postpartum period it was 18.4% (P = 0.042). In Puntarenas, the variation in the last trimester of gestation was on average 18.7% and in the postpartum period was 10.5% (P = 0.012). The relative change in FAT in Veracruz was 36.7%, and in Puntarenas it was 29.3%. Overall, 60% of the cows became pregnant. FAT decreased the interval of DRC (R²=0.06; P=0.033) with a high relationship (R²=0.76; P< 0.0001) between THI and time to conception, in both farms. In conclusion, THI levels influence the reproductive performance in early postpartum period affecting DRC.