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

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.

Transcriptome analysis reveals the mechanism of chronic heat stress on meat quality of broilers

Background

Chronic heat stress has a negative impact on poultry meat quality. Although this has been extensively investigated, previous studies have primarily focused on metabolic alterations and oxidative stress in the pectoralis major (PM) muscle under chronic heat stress, and not all of the underlying molecular mechanisms are completely understood.

Methods

A total of 144 male Arbor Acres broilers (28 d old) were randomly allocated into 3 treatment groups: (1) the normal control (NC) group, with broilers raised at 22 °C and fed a basal diet; (2) the heat stress (HS) group, with birds raised at 32 °C and fed a basal diet; and (3) the pair-fed (PF) group, with birds raised at 22 °C and fed the amount of feed equal to the feed consumed on the previous day by the HS group. The experiment lasted for 14 d.

Results

Chronic heat stress decreased the average daily feed intake and average daily gain, increased feed:gain ratio (P < 0.05); and increased drip loss, cooking loss, shear force, hardness, and decreased pH, redness (a*); and springiness of PM muscle (P < 0.05). Furthermore, chronic heat stress decreased muscle fiber density, increased connective tissue, and led to intracellular vacuolation. The transcriptome analyses indicated that the effect of chronic heat stress on meat quality was not only related to metabolism and oxidative stress, but also to signal transduction, immune system, transport and catabolism, cell growth and death, and muscle structure.

Conclusions

Chronic heat stress has a negative impact on the growth performance, meat quality, and the PM muscle structure of broilers. Transcriptome analysis revealed a comprehensive understanding of the mechanism of the chronic heat stress-induced deterioration of broiler meat quality at the transcriptional level.

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.

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.

The relationships between environmental parameters in livestock pen and physiological parameters of Holstein dairy cows

There has been an increase in temperature and the incidence of extreme weather events, such as heat wave, due to global warming, which has promoted the incidence of livestock diseases. Therefore, it is important to examine the effect of changes in environmental parameters on livestock performance. The aim of this study was to examine the relationship between ambient environmental conditions in livestock pen and the physiological parameters of Holstein dairy cows. The results showed that there was a decrease in the red blood cell counts, hemoglobin concentrations, and mean corpuscular hemoglobin concentration of the cows with increasing pen temperature, wet bulb globe temperature (WBGT), and temperature humidity index (THI). Additionally, high daily variation in temperature caused a decrease in the serum albumin levels of the cows. Moreover, the lowest serum calcium, inorganic phosphorus, and magnesium concentrations were observed in November, and were negatively correlated with the 24-hr temperature, WBGT, and THI range of the pen prior to sampling. Multiple regression analysis showed a positive correlation between serum cortisol concentration and 24-hr WBGT range of the pen prior to samplings and packed cell volume. However, serum cortisol and total protein concentrations were negatively correlated. Overall, the findings of the study suggest that large variation in temperature induced stress in the cows, which could be overcome by increased water consumption and improved protein digestion and absorption by the animals, and the addition of minerals, such as calcium to the diet.

Evaluation of the Best Region for Measuring Eye Temperature in Dairy Cows Exposed to Heat Stress

Eye temperature (ET) has long been used for predicting or indicating heat stress in dairy cows. However, the region of interest (ROI) and temperature parameter of the eye have not been standardized and various options were adopted by previous studies. The aim of this study was to determine the best ROI for measuring ET as the predictor of heat stress in dairy cows in consideration of repeatability and validity. The ET of 40 lactating Holstein dairy cows was measured using infrared thermography. The mean and maximum temperature of five ROIs—medial canthus (MC), lateral canthus, eyeball, whole eye (WE), and lacrimal sac (LS)—were manually captured. The results show that the ET of left eyes was slightly higher than that of right eyes. The ET taken in MC, WE, and LS within 2 min had a moderate to substantial repeatability. The maximum temperature obtained at the LS had the highest correlation coefficients with respiration rate and core body temperature (all p < 0.001). Therefore, the maximum temperature of LS should be considered by future studies that want to use ET as the predictor or indicator of heat stress in dairy cows.

The effects of cow-related factors on rectal temperature, respiration rate, and temperature-humidity index thresholds for lactating cows exposed to heat stress

The objectives of this study were to investigate the effects of the cow-related factors on rectal temperature (RT) and respiration rate (RR) of lactating dairy cows under different heat stress (HS) conditions and establish the temperature-humidity index (THI) thresholds at which RT and RR begin to increase for cows in China. Cow-related factors included body posture (standing and lying), milk yield (<26 kg/d, ≥ 26-39 kg/d, and ≥39 kg/d), days in milk (≤60 d, > 60 and ≤ 150 d, and >150 d), and parity (1, 2, and ≥3). Records of RT, RR, and individual characteristics were collected from July to October 2020 on a commercial dairy farm in Northern China, where 826 Holstein lactating cows were measured. Using the broken-stick regression models and the entire dataset, the THI thresholds for RT and RR were 69.8 and 67.1, respectively. Therefore, the heat stress conditions during this study were classified according to the THI levels as thermoneutrality (TN, 60 < THI ≤ 67), mild (67 < THI ≤ 72), moderate (72 < THI ≤ 80), and severe (80 < THI ≤ 86). Results showed that lying cows exhibited the higher RT and RR but the lower THI threshold for RT (68.8 vs. 70.7) and RR (65.6 vs. 68.4) than standing cows; milk yield is positively associated with the values of RT and RR under TN or HS conditions, and the THI thresholds for RT (70.2 vs. 70.0 vs. 68.0) and RR (68.1 vs. 64.7 vs. 64.7) were progressively lower for low-yielding, middle-yielding, and high-yielding cows; there was a significant increase in RT and RR in early-lactation cows compared to late-lactation cows under TN or HS conditions (P < 0.001), and the lowest THI threshold (67.8 for RT and 64.7 for RR) was observed in early-lactation cows, followed by mid-lactation cows (68.2 for RT and 65.3 for RR) and late-lactation cows (70.0 for RT and 67.3 for RR); the effects of parity were not significant on RT (P > 0.05), but significant on RR (P < 0.001). The THI thresholds for RT (69.2) and RR (66.0) were lowest for cows in 3rd-parity and higher, followed by cows in 2nd-parity (70.0 for RT and 68.9 for RR) and 1st-parity (70.7 for RT and 66.6 for RR). This study highlighted the great significance of considering the cow-related factors in heat stress responses and THI threshold assessment. For dairy cows in China, we suggest that cooling should be initiated when THI reaches 65 to 66.

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.

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.