The temperature inside broiler houses is crucial to broiler health, welfare, and productivity. High stocking density in broiler houses can easily lead to nonuniform temperature conditions, which would cause broilers to suffer cold and heat stress. It is essential to assess the temperature distribution inside broiler houses and investigate the factors that affect temperature uniformity. Therefore, in this study, temperature, wind velocity, and differential pressure were monitored in the aisle, at the sidewall inlet, and outside the sidewalls of a commercial stacked-deck cage broiler house in Northeast China aiming to continuously monitor the temperature throughout the entire fattening period. Results show that the maximum temperature difference increased from 1.85 °C to 6.43 °C, while the daily fluctuation increased from 2.27 °C to 5.80 °C. The highest temperature was consistently recorded at the side of the exhaust fans (p < 0.001) in the longitudinal direction. In the lateral direction, the temperature difference varies periodically with solar radiation. The average temperature at the southern location (23.58 ± 1.97 °C), which faces the sun, was higher than that at the northern location (23.35 ± 1.38 °C), which is in the shade, during periods of solar radiation (p < 0.001) at the last testing period. However, without solar radiation, the northern location recorded a warmer temperature (23.19 ± 1.41 °C) compared to the southern location (22.30 ± 1.67 °C) (p < 0.001). The lateral temperature differences are strongly positively correlated with solar radiation and wind speed (p < 0.001). In conclusion, the inside temperature nonuniformity and fluctuation increased as the broiler age increased, which affected the production performance of broilers. Nonuniform solar radiation and wind speed can lead to differences in the inlet temperature and air volume between both sidewalls, thereby affecting the uniformity of the lateral temperature inside the house.

Hypochlorous acid has been attempted as an additive to animal drinking water in practical animal farming processes for water microbial quality control. Despite its potential, there is still a knowledge gap concerning the effects of hypochlorous acid on both poultry growth performance and gut microbial load. To address this gap, an animal study was conducted using flow cytometry to quantify the age-related microbial load in broiler manure and gut contents. We observed that the effect on growth performance was sustained only during the starter phase, with no significant impact throughout the entire production cycle. The treatment could reduce the microbial load of both fresh broiler manure and cecal contents. Despite this convergence in the duodenum, significant differences in microbial loads between the control and treatment groups persisted in the manure and cecal contents throughout the later stages. Our findings demonstrate that consuming low-concentration hypochlorous acid water over the long term can lower the microbial load in the broiler gut throughout the entire growth cycle without impacting overall growth performance. Future research on drinking or feed additives should incorporate microbial absolute quantification methods to achieve a more precise assessment of microbiota.

Poultry are the primary source of heat and moisture in confined livestock housing systems. Accurate measurement of poultry heat and moisture production (HMP) is critical for intelligent and sustainable livestock farming, including effective environmental control, energy analysis, and reliable facility simulations. Currently, the indirect calorimetry method is widely applied, but it has estimation uncertainties and high construction costs. Meanwhile, the direct calorimetry method, despite its higher accuracy, is limited by complex equipment design and its sensitivity to environmental variations. This study developed an innovative data-driven poultry HMP monitoring system designed to improve measurement accuracy while reducing operational complexity and costs. The monitoring system comprises a poultry rearing chamber and a data acquisition subsystem. To accurately monitor the HMP inside the chamber, a dynamic heat and moisture prediction (DHMP) model was developed, and its parameters were identified by integrating experimental data with the Non-dominated Sorting Genetic Algorithm II (NSGA-II). Experimental data were collected under various heating and humidification power settings and ambient temperature conditions to train and validate the DHMP model. The results demonstrate that the DHMP model has good adaptability to ambient temperature variations across different heating power conditions. In validation datasets, the mean absolute percentage errors for heating and humidification power predictions were 3.30 % and 3.71 %, respectively, with corresponding root mean square error values of 0.961 W and 0.389 g·h⁻¹. Field experiments further confirmed that the HMP values predicted by the system closely match those reported in the literature, supporting the reliability of the system. Based on cost statistics, the total manufacturing cost was reduced by approximately 50 %-80 % compared with existing calorimetry methods. The developed data-driven HMP monitoring system effectively overcomes the limitations of traditional calorimetry methods in terms of complexity and high costs, providing an innovative and practical approach for accurately monitoring poultry physiological parameters to support precision environmental control and production management.