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Heat stress with measurable effects in dairy cattle is a growing concern in temperate regions. Heat stress in temperate regions differs between environments with different geophysical characteristics. Microclimates specific to each environment were found to greatly impact at what level heat stress occurs and will occur in the future. The landlocked state of Baden-Württemberg, Germany, provides several different environments, hence, a good case-study. Temperature Humidity Index (THI) from 17 weather stations for the years 2003-2022 was calculated and milking yields from 22 farms for the years 2017-2022 were collected. The occurrences and evolving patterns of heat stress were analysed with use of a Temperature Humidity Index (THI), and the effect of heat stress on milk yield was analysed based on milking records from Automated Milking Systems (AMS). Daily average THI was calculated using hourly readings of relative humidity and ambient temperature, disregarding solar radiation and wind, as all animals were permanently stabled. Based on studies conducted in Baden-Württemberg and neighbouring regions, cited ahead in the section of Temperature Humidity Index, THI = 60 was the threshold for heat stress occurrence. Findings show that the heat stress period varied between stations from 64 to 120 days with THI ≥ 60 in a year. This aligns with yearly and summer averages, also steadily increasing from May to September. Length of heat stress period was found to increase 1 extra day every year. Extreme weather events such as heat waves did not increase the heat stress period of that year in length but increased the average THI. Milk yield was found to be significantly (α = 0.05) different between counties grouped into different zones according to heat stress severity and rate of increase in daily average THI. Future attempts at managing heat stress on dairy cattle farms in the temperate regions should account for microclimate, as geographical proximity does not mean that the increase in heat stress severity will be the same in the two neighbouring areas.

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The present study was undertaken to determine the effect of heat stress on milk production (test day milk yield) and compositional traits (fat%, protein%, fat yield, protein yield) as well as to observe the pattern of response to increasing heat load on these traits in Jersey crossbred cows, maintained at ICAR-National Dairy Research Institute, Eastern Regional Station, Kalyani, West Bengal, India. The weather information, obtained from the NASA POWER database based on the location of the farm latitude and longitude, was used to calculate the Temperature Humidity Index (THI). To analyze the data, a linear model was fitted to the milk production and compositional records, which were adjusted for additive genetic effect of animal, permanent environmental effect of animals and known environmental sources of variations. Subsequently, a segmented linear regression model was fitted, and the least squares estimates of production and composition traits in different classes of THI were used as the dependent variable. Two THI break-points (BP) for milk yield and one THI BP for fat yield, protein %, and protein yield were found. The first and second BP for milk yield was at THI 59 and 77, respectively, with a significant decline in milk yield of -0.04 kg/unit of THI at second BP. The BP for fat and protein yield was at THI 76, with a decline rate of -1.18 and - 0.61 g/unit of THI increase, respectively. The findings revealed the significant adverse effects of THI on milk production and composition traits in Jersey crossbred cattle.

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In livestock, temperature, humidity, and Temperature-Humidity Index (THI) affect the welfare, yields, health and viability of animals. This study aimed to develop optimal temperature, humidity, and THI thresholds for dairy farms in temperate climate regions using a fuzzy logic model. THI values were calculated using three different literature-derived equations, considering different temperature and humidity situations in dairy farms. The Mamdani-type fuzzy logic method was utilized to formulate linguistic expressions for temperature, humidity, and THI values. According to the THI thresholds, the areas below the Receiver Operating Characteristic (ROC) were found to be significant (p < 0.001) in all fuzzy algorithms. The study found 100% harmony with the THI thresholds of 66 and 72 for cattle in temperate climates, but only 73.6% harmony with the threshold of 74 for cattle adapted to tropical climate. Briefly, in temperate dairy farms, the fuzzy logic revealed that the optimal temperature, humidity and THI values should be between 14-18.5°C, 65-70% and 52.5-64.5, respectively. However, further research is required to understand the impact of thresholds determined by fuzzy logic on dairy cow production and welfare.

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Accelerometer-based technologies can be utilized for precision monitoring of feeding behaviors, but limited information is available regarding the impact of varying environmental conditions on sensor performance. The objective of this study was to determine if a commercially available ear-tag sensor (CM; CowManager SensOor, Agis Automatisering BV) could accurately quantify eating and rumination time under heat stress conditions. Data obtained from CM sensors was compared with data collected using an automated gold standard (RW; Rumiwatch System; Itin+Hoch). Automated measurements were obtained from 2 experiments in which cattle were exposed to heat stress conditions. In the principal study (Experiment 1), 3428 h of data were collected from 9 Holstein × Angus steers (470.9 ± 23.9 kg) subjected to either thermoneutral (TN; 21.0°C; 64.0% humidity; temperature-humidity index [THI] = 67; 12- and 12-h light and dark cycle; n = 1714 h), or heat stress conditions (HS; cyclical daily temperatures to mimic diurnal patterns; 0800 - 2000 h: 33.6°C, 40.0% RH, THI: 83.5; 2000 - 0800 h: 23.2°C, 70.0% RH; THI: 70.3; n = 1714 h). Data (n = 719 h) from 6 Holstein x Angus steers (487.9 ± 9.1 kg) were obtained from a subsequent experiment (Experiment 2) to confirm consistency of ear-tag accelerometer performance under elevated THI (HS conditions as described above). In Experiment 1, CM was capable of quantifying rumination time with high accuracy under TN conditions (concordance correlation coefficient [CCC]: 0.75 - 0.81). Overall, agreement between CM and the automated gold standard declined 6 - 7% during HS, which was most apparent later in the day when cattle had been subjected to HS for multiple hours (moderate agreement; CCC: 0.68). Accuracy for rumination time was also only moderate for data collected during Experiment 2 (CCC: 0.55 - 0.61). In contrast, CM reported total eating (eating with the head down + head up while masticating) time with moderate accuracy for TN (CCC: 0.53 - 0.54), only achieved negligible to low accuracy during HS (CCC: 0.39 - 0.44 [Experiment 1] and 0.17 - 0.34 [Experiment 2]). Sensor performance did improve when CM eating time was compared specifically to the time spent with the head down reported by RW; HS still negatively influenced sensor performance, however, with high agreement during TN (CCC: 0.72 - 0.73) but low to moderate agreement during HS (CCC: 0.65 - 0.69 [Experiment 1] and 0.40 - 0.58 [Experiment 2]). Results of this study suggest accuracy of ear-tag accelerometers may be impaired when cattle are subjected to heat stress.

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The present study investigates the susceptibility of two imported dairy cattle breeds to Algerian local climatic conditions, with a primary focus on heat stress (HS) and its repercussions on fertility traits. The dataset comprises 20,926 artificial insemination records involving 6,191 Prim'Holstein and 5,279 Montbéliarde cows. The animals originated from three distinct agro-ecological regions: littoral (L), semi-arid (SA), and arid (Ar), characterized by average annual Temperature-Humidity Index (THI) values of 75.2, 69.53, and 74.75, respectively. Logistic and linear regression models were performed to analyze the relationship between the THI on the AI day, season, and agro-ecological origin of the animals with the Conception Rate at 1st Artificial Insemination (CR 1stAI), Conception Risk (CR), Services per Conception (SPC), and reproductive period (RP). The results demonstrated a significant negative impact (P < 0.001) of THI > 72 compared to THI ≤ 72 on CR1st AI and CR for both cattle breeds (Prim'Holstein: -49.7% and - 17%, respectively; Montbéliarde: -20.7% and - 15%, respectively). Seasonal effects revealed a notably higher CR1stAI in winter and spring (≈ 25%) for Prim'Holstein and Montbéliarde cows compared to summer (19.41%) and autumn (19.12%), respectively. Furthermore, a reduced likelihood of conception at 1stAI and subsequent AI was observed during summer (0.839) and autumn (0.818) compared to winter for the Montbéliarde cows. Taking into account the littoral region as a reference, the likelihood of 1stAI success increased for both breeds in the SA region and decreased for the Ar region (P < 0.001). SPC increased for both breeds in THI > 72 categories (Prim'Holstein: 6.3%, Montbéliarde: 7.1%, P < 0.01), in the Ar region (Prim'Holstein: 30.9%, Montbéliarde: 26%, P < 0.001), and in the SA region (4%, P < 0.05) compared to the L region No significant seasonal effect on SPC was observed for either breed (P > 0.05). The RP increased in the THI > 72 category (Prim'Holstein: 4.1%, Montbéliarde: 7.4%, P < 0.001) and in the Ar region (Prim'Holstein: 122%, Montbéliarde: 73.4%) for both breeds. RP decreased in autumn compared to winter (Prim'Holstein: 15.3%, Montbéliarde: 8.4%). This study underscores the adverse impact of mild to severe heat stress (HS) and related factors (season, region) on fertility of Prim'Holstein and Montbéliarde cows under Algerian conditions, emphasizing the necessity for heat stress mitigation strategies, especially in adverse littoral humid and Saharan-arid environmental conditions.

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Heat stress (HS) is one of the key factors affecting an animal's immune system and productivity, as a result of a physiological reaction combined with environmental factors. This study examined the short-term effects of heat stress on cow behavior, as recorded by innovative technologies, and its impact on blood gas parameters, using 56 of the 1070 cows clinically evaluated during the second and subsequent lactations within the first 30 days postpartum. Throughout the experiment (from 4 June 2024 until 1 July 2024), cow behavior parameters (rumination time min/d. (RT), body temperature (°C), reticulorumen pH, water consumption (L/day), cow activity (h/day)) were monitored using specialized SmaXtec boluses and employing a blood gas analyzer (Siemens Healthineers, 1200 Courtneypark Dr E Mississauga, L5T 1P2, Canada). During the study period, the temperature-humidity index (THI), based on ambient temperature and humidity, was recorded and used to calculate THI and to categorize the data into four THI classes as follows: 1-THI 60-63 (4 June 2024-12 June 2024); 2-THI 65-69 (13 June 2024-18 June 2024); 3-THI 73-75 (19 June 2024-25 June 2024); and 4-THI 73-78 (26 June 2024-1 July 2024). The results showed that heat stress significantly reduced rumination time by up to 70% in cows within the highest THI class (73 to 78) and increased body temperature by 2%. It also caused a 12.6% decrease in partial carbon dioxide pressure (pCO2) and a 32% increase in partial oxygen pressure (pO2), also decreasing plasma sodium by 1.36% and potassium by 6%, while increasing chloride by 3%. The findings underscore the critical need for continuous monitoring, early detection, and proactive management to mitigate the adverse impacts of heat stress on dairy cow health and productivity. Recommendations include the use of advanced monitoring technologies and specific blood gas parameter tracking to detect the early signs of heat stress and implement more timely interventions.

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The bovine embryo production industry has seen significant growth over the past two decades, particularly in the production of in vitro produced embryos. This growth, driven by advancements in cryopreservation, in vitro culture mediums, ovum pick-up (OPU) procedures, ultrasonography devices, and embryo transfer (ET) has been notable. Particularly, ET is crucial for disseminating high genetic merit and amplifying foreign breeds by importing frozen embryos. This retrospective study aimed to assess factors affecting conception per embryo transfer (CPET) in Holstein-Friesian cattle in South Korea from October 2008 to July 2022. We evaluated type of embryo breed, type of embryo production (fresh and frozen; in vitro and in vivo production), recipient conditions including estrus type, corpus luteum quality, parity (nulliparous heifers, primiparous, and multiparous cows), and the daily mean temperature-humidity index (THI) as an index for heat stress. Type of embryo breed and estrus had no significant impact on CPET. However, we observed higher CPET in recipients with good quality corpus luteum, nulliparous heifers, and surrogates receiving fresh in vitro and frozen in vivo embryos. Importantly, CPET was not adversely affected by mild heat stress conditions (up to daily mean THI 76), indicating that using frozen in vivo embryos produced by multiple ovulation embryo transfer and fresh in vitro embryos by OPU-ET can help alleviate the subfertility issues in dairy cattle caused by global warming in Korea.

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Global warming caused by climate change is a challenge for dairy farming, especially in sub-Saharan countries. Under high temperatures and relative humidity, lactating dairy cows suffer from heat stress. The objective of this study was to investigate the effects and relationship of heat stress (HS) measured by the temperature-humidity index (THI) regarding the physiological parameters and milk yield and composition of lactating Holstein Friesian crossbred dairy cows reared in the humid coastal region of Tanzania. A total of 29 lactating Holstein Friesian x Zebu crossbred dairy cows with 50% (HF50) and 75% (HF75) Holstein Friesian gene levels in the second and third months of lactation were used. The breed composition of Holstein Friesians was determined based on the animal recording system used at the Tanzania Livestock Research Institute (TALIRI), Tanga. The data collected included the daily temperature, relative humidity, daily milk yield, and physiological parameters (core body temperature, rectal temperature, respiratory rate, and panting score). THI was calculated using the equation of the National Research Council. The THI values were categorized into three classes, i.e., low THI (76-78), moderate THI (79-81), and high THI (82-84). The effects of THI on the physiological parameters and milk yield and composition were assessed. The effects of the genotype, the parity, the lactation month, and the interaction of these parameters with THI on the milk yield, milk composition, and physiological parameters were also investigated. The results show that THI and its interaction with genotypes, parity, and the lactation month had a highly significant effect on all parameters. THI influenced (p ˂ 0.05) the average daily milk yield and milk fat %, protein %, lactose %, and solids-not-fat %. As the THI increased from moderate to high levels, the average daily milk yield declined from 3.49 ± 0.04 to 3.43 ± 0.05 L/day, while the fat % increased from 2.66 ± 0.05% to 3.04 ± 0.06% and the protein decreased from 3.15 ± 0.02% to 3.13 ± 0.03%. No decline in lactose % was observed, while the solid-not-fat % declined from 8.56 ± 0.08% to 8.55 ± 0.10% as the THI values increased from moderate to high. Also, the THI influenced physiological parameters (p ˂ 0.05). The core body temperature (CBT), rectal temperature (RT), respiratory rate (RR) and panting score (PS) increased from 35.60 ± 0.01 to 36.00 ± 0.01 °C, 38.03 ± 0.02 to 38.30 ± 0.02 °C, 62.53 ± 0.29 to 72.35 ± 0.28 breaths/min, and 1.35 ± 0.01 to 1.47 ± 0.09, respectively, as the THI increased from low to high. The THI showed a weak positive correlation with the average daily milk yield and fat percentage, whereas the protein, lactose, and solids-not-fat percentages showed negative relationships with THI (p ≤ 0.05). CBT, RT, RR, and PS showed positive relationships (p ≤ 0.05) with THI. These negative relationships indicate that there is an antagonistic correlation between sensitivity to HS and the level of production. It is concluded that the THI, the genotype, the parity, and the lactation month, along with their interactions with THI, significantly influenced the milk yield, milk composition, and physiological parameters of lactating Holstein Friesian dairy crosses at THI thresholds ranging from 77 to 84.

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The study aims to develop an abnormal body temperature probability (ABTP) model for dairy cattle, utilizing environmental and physiological data. This model is designed to enhance the management of heat stress impacts, providing an early warning system for farm managers to improve dairy cattle welfare and farm productivity in response to climate change. The study employs the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm to analyze environmental and physiological data from 320 dairy cattle, identifying key factors influencing body temperature anomalies. This method supports the development of various models, including the Lyman Kutcher-Burman (LKB), Logistic, Schultheiss, and Poisson models, which are evaluated for their ability to predict abnormal body temperatures in dairy cattle effectively. The study successfully validated multiple models to predict abnormal body temperatures in dairy cattle, with a focus on the temperature-humidity index (THI) as a critical determinant. These models, including LKB, Logistic, Schultheiss, and Poisson, demonstrated high accuracy, as measured by the AUC and other performance metrics such as the Brier score and Hosmer-Lemeshow (HL) test. The results highlight the robustness of the models in capturing the nuances of heat stress impacts on dairy cattle. The research develops innovative models for managing heat stress in dairy cattle, effectively enhancing detection and intervention strategies. By integrating advanced technologies and novel predictive models, the study offers effective measures for early detection and management of abnormal body temperatures, improving cattle welfare and farm productivity in changing climatic conditions. This approach highlights the importance of using multiple models to accurately predict and address heat stress in livestock, making significant contributions to enhancing farm management practices.

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As climate change intensifies, heat stress mitigation for pigs becomes more important. Trials involving induced heat waves are useful to test several measures (e.g. reduced stocking density) at a faster rate, but only when accurately evaluated and validated. In the present study, we investigated the suitability of an artificial heating protocol at different pig weights (experiment 1). The impact of different stocking densities on fattening pigs during an artificial heat wave (experiment 2) was also investigated. Experiment 1: Forty 20-week-old pigs weighing 96.5 ± 7.3 kg (W100) and forty 17-week-old pigs weighing 72.7 ± 9.9 kg (W70) were housed in two compartments. An artificial heat wave (heat load) was induced for 3 days. During 3-day periods before, during and after the heat load, physiological parameters (respiration rate (RR), rectal temperature (Trectal), skin temperature (Tskin) and behavior) were measured and average daily feed intake was observed. Ambient temperature, relative humidity and temperature-humidity index (THI) were monitored. Experiment 2: A total of 150 fattening pigs were randomly divided into three treatment groups: SD1.3 (1.3 m2/pig), SD1.0 (1.0 m2/pig) and SD0.8 (0.8 m2/pig). All pens had a total pen surface of 4.88 m2, corresponding with 4, 5 and 6 fattening pigs in the SD1.3, SD1.0 and SD0.8 groups, respectively. The heat load was induced for 7 days on week 21. Respiration rate and Trectal were observed as in experiment 1. Average daily gain and average daily feed intake were also noted. During the heat load, THI reached ≥ 75 (78.4 (experiment 1) and 78.6 (experiment 2)), even when relative humidity decreased to ± 45%. Every physiological parameter showed significant increases during the heat load. The prolonged heating protocol in experiment 2 also provoked significant decreases in average daily feed intake (15%) and average daily gain (19%) for all groups. Weight within the studied range of 70-100 kg did not have a significant impact on any of the parameters. However, Tskin was affected by both weight and heat load (P < 0.05), where Tskin from W100 was always lower in comparison to W70. In addition, we found that 0.8 m2/pig doubled the increase of Trectal during the heat load, namely SD0.8 (0.22 °C) compared to SD1.0 (0.12 °C) (P = 0.033) and SD1.3 (0.13 °C) (P = 0.053). This suggests that pigs housed at higher densities are less able to regulate their internal heat production. However, RR and performances were not significantly affected by heat load in this experimental set-up. A stocking density of 1.0 m2/animal may be sufficient to mitigate some negative effects of heat stress.

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As high temperature and relative humidity (RH) are the main environmental factors causing heat stress, the temperature-humidity index (THI) serves as an indicator of heat stress in livestock animals. This study aimed to determine the effects of heat stress on the laying performance, physiological responses, egg quality, and blood profile of laying hens by subjecting them to environmental conditions with varying THI levels (68-85) for 28 days. The indicators of laying performance, such as feed intake (-30%) and egg production rate (-11%), significantly decreased in the hens exposed to severe heat stress (33 °C, 66% RH) compared to those exposed to thermoneutral conditions (21 °C, 68% RH). Moreover, severe heat stress reduced the egg yolk color, eggshell thickness and strength, and Haugh units of the eggs produced by the laying hens. Furthermore, a significant increase in serum K+ and a decrease in Na+ levels were observed in the hens subjected to severe heat stress compared with those under thermoneutral conditions. Our results indicate that heat stress alters the physiological responses and metabolism of laying hens, resulting in a lower egg quality and production rate.

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Heat stress in pigs negatively affects welfare, health, and performance. Osmoprotectants and antioxidants may alleviate oxidative damage during hot periods. We investigated whether an additive-enriched feed can reduce negative effects in pigs during summer conditions. Sixty growing-finishing pigs were allocated into two groups: the control (CF) and summer feed (SF) group. The CF group contained 0.4 mg/kg inorganic selenium and 100 ppm vitamin E, while the SF group contained 0.3 mg/kg inorganic selenium, 0.1 mg/kg selenomethionine, 200 ppm vitamins E and C, and 0.2% betaine. Feed was offered ad libitum. Respiration rate, rectal and skin temperature, behaviour, and weight gain were assessed weekly. Daily measurements of these parameters were performed during a 3-day heat wave (temperature humidity index (THI) ≥ 75) and during an artificial heating period. Individual average daily water intake (ADWI) and feed intake were measured using RFID systems. The ADWI of the SF group did not change during heat load while it increased for the CF group. Independent of dietary treatment, increases in ∆THI or the THI were accompanied by significant increases in both respiration rate and skin temperature. In conclusion, the SF may induce a reduced need to increase ADWI during hot periods. In addition, mainly skin temperatures and especially respiration rates revealed the sensitivity of pigs to heat stress.

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This study evaluates the response of dairy cows to short and extended heat stressing conditions (from 1 to 28 days), as expressed in changes in their behavior. Due to climate change, heat stress and strong heat waves are frequently affecting the productivity and behavior of dairy cows. In the five years under study from 2018 to 2022, two were characterized by extremely strong heat waves occurring in the region analyzed in this study (Northern Italy). The dairy cattle farm involved in this study is located in Northern Italy and includes about 1 600 Holstein Friesian lactating dairy cows. Phenotypic data were provided by the Afimilk system and compromised behavioral and productive traits. Behavioral traits analyzed were activity, rest time, rest bouts, rest ratio, rest per bout and restlessness. Production traits were daily milk yield, average milking time, somatic cell count, fat percentage, protein percentage and lactose percentage. Climate data came from the National Aeronautics and Space Administration/Prediction of Worldwide Energy Resources database. Heat stress was analyzed considering Temperature-Humidity Index (THI) averaged over 28 different time windows of continuous heat stress. Results showed that rest time and milk yield were the two traits most affected by the increased THI. Rest time was immediately affected by high THI, showing a marked decrease already from 1d window and maintaining this all over the other windows. Furthermore, results show that rest time and rest ratio were only slightly negatively correlated with milk yield (-0.14 and -0.15). In addition, heat stress has a different effect depending on parity and lactation stages on the studied traits. In conclusion, the results indicate that heat stress increases activity and compromises milk production, rest time and milk quality traits. Results further suggest that rest time can be a better parameter than activity to describe the effects of heat stress on dairy cattle. The novel approach used in this study is based on the use of different time windows (up to 28 days) before the emergence of undesired THI and allows to identify the traits that are immediately influenced by the undesirable THI values and those that are influenced only after a prolonged heat stress period.

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Extreme weather conditions, like heatwave events, are becoming more frequent with climate change. Animals often modify their behaviour to cope with environmental changes and extremes. During heat stress conditions, individuals change their spatial behaviour and increase the use of shaded areas to assist with thermoregulation. Here, we suggest that for social species, these behavioural changes and ambient conditions have the potential to influence an individual's position in its social network, and the social network structure as a whole. We investigated whether heat stress conditions (quantified through the temperature humidity index) and the resulting use of shaded areas, influence the social network structure and an individual's connectivity in it. We studied this in free-ranging sheep in the arid zone of Australia, GPS-tracking all 48 individuals in a flock. When heat stress conditions worsened, individuals spent more time in the shade and the network was more connected (higher density) and less structured (lower modularity). Furthermore, we then identified the behavioural change that drove the altered network structure and showed that an individual's shade use behaviour affected its social connectivity. Interestingly, individuals with intermediate shade use were most strongly connected (degree, strength, betweenness), indicating their importance for the connectivity of the social network during heat stress conditions. Heat stress conditions, which are predicted to increase in severity and frequency due to climate change, influence resource use within the ecological environment. Importantly, our study shows that these heat stress conditions also affect the animal's social environment through the changed social network structure. Ultimately, this could have further flow on effects for social foraging and individual health since social structure drives information and disease transmission.

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Nowadays climate change is affecting the planet's biodiversity, and livestock practices must adapt themselves to improve production without affecting animal welfare. This work investigates the influence that some climatic parameters such as Environment Temperature, Relative Humidity, Thermal excursion and Temperature-Humidity Index (THI), can have on milk quantity and quality in two different dairy species (buffaloes and cows) raised on the same farm. A further aim was to understand if THI threshold used for cows could also be used for buffaloes. The climatic parameters were recorded daily through a meteorological station located inside the farm. Milk quantity (converted into ECM) and quality (Fat Percentage-FP; Protein Percentage-PP; Somatic Cell Count-SCC) were measured. Data were analyzed with Spearman's correlation index, separately for buffaloes and cows. The results indicate a greater sensitivity of cows to heat stress and a strong negative correlation of the ECM with meteorological data (p < 0.01). The results of this study may stimulate the use of integrated technologies (sensors, software) in the dairy sector, since the IoT (sensors, software) helps to enhance animal well-being and to optimize process costs, with a precision livestock farming approach.

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OBJECTIVE: This study was conducted to assess effects of heat stress on growth performance, physiological parameters, and blood profiles of Hanwoo steers during early-fattening period in climate chambers. METHODS: Four Hanwoo steers (body weight, 454.3±10.9 kg; age, 14±0.1 month) were allocated into four levels of temperature-humidity index (THI) in a 4×4 Latin square design for 21 days (pre-adaptation, 7 d; heat stress, 7 d; post-adaptation, 7 d) per period. Experimental treatments were assigned according to THI chart based on National Institute Animal Science (NIAS, 2022): Comfort (25.5°C to 26.5°C, 60%; THI 73 to 75), Mild (28°C to 29°C, 60%; THI 77 to 79), Moderate (29.5°C to 30.5°C, 80%; THI 82 to 84), and Severe (31°C to 32°C, 80%; THI 85 to 86) in separate climatic controlled chambers. RESULTS: The dry matter intake (DMI) of the formula feed was lower in Severe compared to Mild and Comfort (p<0.05). The DMI of rice straw was the lowest in Severe and lower in Moderate than Comfort and Mild (p<0.05). Both average daily gain and feed conversion ratio of Severe and Moderate were lower than those of Mild and Comfort (p<0.05). Water intake was the highest in Severe and lower in Moderate compared with Comfort and Mild (p<0.05). Heart rate and rectal temperature increased as THI level increased (p<0.05). Glucose was the lowest in Severe and lower in Moderate compared to Comfort (p<0.05). On the contrary, non-esterified fatty acid was the highest in Severe and lower in Moderate compared with Comfort (p<0.05). Blood urea nitrogen of Moderate and Severe were higher than those of Comfort and Mild (p<0.05). Cortisol increased as THI increased (p<0.05). CONCLUSION: This study demonstrated the negative effects of heat stress on the performance and physiological responses of Hanwoo steers during the early-fattening period. In addition, it is judged that the THI chart for Hanwoo steers of National Institute of Animal Science (2022) was properly calculated.

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Identifying and selecting genotypes tolerant to heat stress might improve reproductive traits in dairy cattle, including oocyte and embryo production. The temperature-humidity index (THI) was used, via random regression models, to investigate the impact of heat stress on genetic parameters and breeding values of oocyte and embryo production in Gir dairy cattle. We evaluated records of total oocytes (TO), viable oocytes (VO), cleaved embryos (CE), and viable embryos (VE) from dairy Gir donors. Twenty-four models were tested, considering age at ovum pick-up (AOPU) and THI means as a regressor in the genetic evaluation. We computed THI in eight periods, from 0 to 112 days before ovum pick-up, which were adjusted by different orders of Legendre polynomials (second, third, and fourth). The best-fit model according to Akaike's information criterion (AIC) and Model Posterior Probabilities (MPP) considered Legendre polynomials of third order and THI means of 112 days for TO, fourth order and 56 days for VO, second order and 28 days for CE, and second order and 42 days for VE, respectively. The heritability (h2) estimates across AOPU and THI scales ranged from 0.34 to 0.62 for TO, 0.31 to 0.58 for VO, 0.26 to 0.39 for CE, and 0.15 to 0.26 for VE, respectively. The fraction of the phenotypic variance explained by the permanent environment in different AOPU and THI scales ranged from 0.03 to 0.25 for TO, 0.05 to 0.26 for VO, 0.09 to 0.36 for CE, and 0.15 to 0.27 for VE, respectively. Spearman's rank correlation between the estimated breeding values in different AOPU and THI scale from the top 5% sires and females ranged from 0.18 to 0.90 for TO, 0.31 to 0.95 for VO, 0.14 to 0.85 for CE, and 0.47 to 0.94 for VE, respectively. The h2 estimates for all evaluated traits varied from moderate to high magnitude across AOPU and THI scales, indicating that genetic selection can result in rapid genetic progress for the evaluated traits. There was a reranking among the best animals in different AOPU and THI. It is possible to select dairy Gir cattle tolerant to heat stress to improve oocyte and embryo production.

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Climate change is expected to increase the number of heat wave events, leading to prolonged exposures to severe heat stress (HS) and the corresponding adverse effects on dairy cattle productivity. Modelling dairy cattle productivity under HS conditions is complicated because it requires comprehending the complexity, non-linearity, dynamicity, and delays in animal response. In this paper, we applied the System Dynamics methodology to understand the dynamics of animal response and system delays of observed milk yield (MY) in dairy cows under HS. Data on MY and temperature-humidity index were collected from a dairy cattle farm. Model development involved: (i) articulation of the problem, identification of the feedback mechanisms, and development of the dynamic hypothesis through a causal loop diagram; (ii) formulation of the quantitative model through a stock-and-flow structure; (iii) calibration of the model parameters; and (iv) analysis of results for individual cows. The model was successively evaluated with 20 cows in the case study farm, and the relevant parameters of their HS response were quantified with calibration. According to the evaluation of the results, the proposed model structure was able to capture the effect of HS for 11 cows with high accuracy with mean absolute percent error <5%, concordance correlation coefficient >0.6, and R2 > 0.6, except for two cows (ID #13 and #20) with R2 less than 0.6, implying that the rest of the nine animals do not exhibit heat-sensitive behaviour for the defined parameter space. The presented HS model considered non-linear feedback mechanisms as an attempt to help farmers and decision makers quantify the animal response to HS, predict MY under HS conditions, and distinguish the heat-sensitive cows from heat-tolerant cows at the farm level.

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The objective of this study was to devise an optimal method for estimating air temperatures outside pig farms to be able to evaluate the genetic performance of pigs. Using daily temperature data from Japan Meteorological Agency meteorological stations, we investigated the optimal number of observation weather stations (number of records), and methods of estimating outside temperature when temperature records are missing. We also considered the possibility of using relative humidity data. Our results showed that it is possible to use records from the three nearest weather stations to estimate off-farm ambient temperatures. We also concluded that estimates of outside temperatures when records are missing can be made by using data from at least one weather station that holds a full set of data. The correlation coefficients between the true THI (temperature-humidity index) and the estimated THI and the average daily temperature were almost the same, indicating that the daily average temperature can be used instead of estimated THI.

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This current study addresses the knowledge gap regarding the influence of seasons, months, and THI on milk yield, composition, somatic cell counts (SCC), and total bacterial counts (TBC) of dairy farms in northeastern regions of Iran. For this purpose, ten dairy herds were randomly chosen, and daily milk production records were obtained. Milk samples were systematically collected from individual herds upon delivery to the dairy processing facility for subsequent analysis, including fat, protein, solids-not-fat (SNF), pH, SCC, and TBC. The effects of seasons, months, and THI on milk yield, composition, SCC, and TBC were assessed using an analysis of variance. To account for these effects, a mixed-effects model was utilized with a restricted maximum likelihood approach, treating month and THI as fixed factors. Our investigation revealed noteworthy correlations between key milk parameters and seasonal, monthly, and THI variations. Winter showed the highest milk yield, fat, protein, SNF, and pH (p < 0.01), whereas both SCC and TBC reached their lowest values in winter (p < 0.01). The highest values for milk yield, fat, and pH were recorded in January (p < 0.01), while the highest protein and SNF levels were observed in March (p < 0.01). December marked the lowest SCC and TBC values (p < 0.01). Across the THI spectrum, spanning from -3.6 to 37.7, distinct trends were evident. Quadratic regression models accounted for 34.59%, 21.33%, 4.78%, 20.22%, 1.34%, 15.42%, and 13.16% of the variance in milk yield, fat, protein, SNF, pH, SCC, and TBC, respectively. In conclusion, our findings underscore the significant impact of THI on milk production, composition, SCC, and TBC, offering valuable insights for dairy management strategies. In the face of persistent challenges posed by climate change, these results provide crucial guidance for enhancing production efficiency and upholding milk quality standards.