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.

The environment in livestock and poultry houses plays an important role in the growth and reproduction of livestock and poultry. In order to obtain the environmental conditions of livestock and poultry houses in a timely and reliable manner, and eliminate adverse environmental factors, scholars have been exploring various methods to obtain and predict environmental factors. This paper reviewed the literature from the last 10 years, specifically focusing on technologies for detecting environmental factors in livestock and poultry houses, which can be mainly divided into three categories: research on the environmental monitoring and control of livestock and poultry houses based on detection equipment and wireless sensor technology; research on the distribution and regularity of environmental factors in livestock and poultry houses based on a mathematical model; research on the environmental simulation and detection of livestock and poultry houses based on computer technology. The current testing methods have their advantages and disadvantages. When studying environmental factors, researchers should choose the most appropriate method for data acquisition according to the actual situation. The proposed recommendations for achieving this goal are as follows: (1) The control of environmental factors should be combined with the physiological response of livestock and poultry. The needs of animals should be considered; (2) Novel approaches need to be developed to integrate energy requirements into the environmental regulation of livestock and poultry houses; (3) It is necessary to research and develop control models and strategies that can predict the environment in the houses, and the transient simulation method should be further explored; (4) Improve environmental detection and control accuracy through the coupling of different technologies.

Detecting the early signs of heat stress is highly important in dairy farming. The surface temperature (ST) of cattle can reflect their thermal status and using such a measuring method can be efficient and non-invasive. However, few studies have reported the temperature-humidity index (THI) thresholds for ST. This study aimed to identify the critical THI thresholds for the ST of dairy cows and to evaluate the effects of the lactation stage and the lactation number. The study included 233 Holstein lactating cows from July 2020 to October 2020 in a temperate climate in China. There were 1556 records of the rectal temperature, and the maximum ST (STmax) and average ST (STave) of the head, eye, cheek, ear, neck, trunk, udder, foreleg, and hindleg were recorded. Air temperature and relative humidity were recorded to calculate the average THI. Physiological data were collected twice daily (08:00–12:00, 14:00–16:00). The critical THI thresholds were determined using the breakpoints of piecewise linear models. The significance of breakpoints was tested using the Davies test. A one-way ANOVA was used to test the effect of the lactation stage (0–60 DIM, 61–200 DIM, 201–300 DIM, DIM is days in milk) and the lactation number (1, 2, 3+) on the THI thresholds. The results showed that the rectal temperature was significantly positively correlated with all the ST variables (0.57 ≤ r ≤ 0.71, p < 0.01). The critical THI thresholds for STmax (mean of 76.1 THI, range of 73.6 to 77.9 THI) were significantly higher than those for STave (mean of 72.6 THI, range of 69.1 to 77.2 THI) (p < 0.01). The lactation stage only significantly affected the thresholds for STmax (p < 0.05), and the lactation number did not significantly influence the thresholds for both STmax and STave (p > 0.05). This study concluded that the STave was more appropriate to define thresholds than the STmax. The threshold for the STave of the cheek (69.1 THI) was the lowest among the thresholds, indicating that the STave of the cheek could be a prior ST variable to determine critical THI thresholds. Our findings demonstrated the potential of using ST variables to define critical THI thresholds.

Advances in smart animal husbandry necessitate efficient pig behavior monitoring, yet traditional approaches suffer from operational inefficiency and animal stress. We address these limitations through a lightweight YOLOv8n architecture enhanced with SPD-Conv for feature preservation during downsampling, LSKBlock attention for contextual feature fusion, and a dedicated small-target detection head. Experimental validation demonstrates superior performance: the optimized model achieves a 92.4% mean average precision (mAP@0.5) and 87.4% recall, significantly outperforming baseline YOLOv8n by 3.7% in AP while maintaining minimal parameter growth (3.34M). Controlled illumination tests confirm enhanced robustness under strong and warm lighting conditions, with performance gains of 1.5% and 0.7% in AP, respectively. This high-precision framework enables real-time recognition of standing, prone lying, lateral lying, and feeding behaviors in commercial piggeries, supporting early health anomaly detection through non-invasive monitoring.

Ventilation and heating can be necessary for pig production during winter in China. However, it is challenging to balance the ventilation rate and heat loss due to the ventilation. Therefore, it is essential to design the minimum ventilation and heating load properly in order to reduce energy loss. In this paper, a VBA (Visual Basic for Applications) model based on energy balance is established. Meteorological data, pig body masses, outdoor temperatures, feeding densities, and building envelope thermal insulance factors were involved in the model. A model pig house with a length and width of 110 m × 15 m was used to investigate the ventilation, heating time, load, and power consumption in different climate zones, i.e., Changchun, Beijing, Nanning, Wuhan, and Guiyang, representing five major climate regions in China. Based on the simulation results, the models of minimum ventilation and heating load were fitted. The results showed that there is a logarithmic relationship between the minimum ventilation volume and body mass, R² = 0.9673. The R² of heating load models for nursery pigs and fattening pigs were 0.966 and 0.963, respectively, considering the feeding area, the outside temperature, the body masses of the nursery and fattening pigs, and the thermal insulance factor of the enclosure. The heating requirements of commercial pig houses within the same building envelope followed the trend in Changchun > Beijing > Guiyang > Wuhan > Nanning. Increasing the building envelope’s thermal insulance factor or using precision heating could reduce the pig house’s power consumption. The analysis of the heating load and energy consumption of winter pig houses in various climate regions provided a reference for precise environmental control and the selection of building thermal insulance factors in China.