In this paper, a heterogeneous composite catalyst Cu₂O/(001)TiO₂ was prepared by the impregnation-reduction method. The crystal form, highly active facet content, morphology, optical properties, and the photogenerated electron-hole recombination rate of the as-prepared catalysts were investigated. The performance of Cu₂O/(001)TiO₂ was appraised by photocatalytic degradation of ammonia under sunlight and was compared with lone P25, Cu₂O, and (001)TiO₂ at the same reaction conditions. The results showed that 80% of the ammonia concentration (120 ± 3 ppm) was removed by Cu₂O/(001)TiO₂, which was a higher degradation rate than that of pure P25 (12%), Cu₂O (12%), and (001)TiO₂ (15%) during 120 min of reaction time. The reason may be due to the compound’s (Cu₂O/(001)TiO₂) highly active (001) facets content that increased by 8.2% and the band gap width decreasing by 1.02 eV. It was also found that the air flow impacts the photocatalytic degradation of ammonia. Therefore, learning how to maintain the degradation effect of Cu₂O/(001)TiO₂ with ammonia will be important in future practical applications.

Local heating of the activity area for nursing piglets is crucial for piglet health and the energy efficiency of barn climate control. Traditional heating methods using lamps or covers lack precise control, result in significant energy waste, and cannot be dynamically adjusted according to piglet age or changing environmental temperatures. To address these issues, this study designed a Programmable Logic Controller (PLC)-based thermal insulation box for nursing piglets, utilizing a strip heater instead of the conventional round heating lamp. The design incorporates a movable thermal insulation box that dynamically adjusts the heater’s power based on the real-time monitoring of environmental temperatures and target temperatures specific to piglet age. First, in a controlled laboratory environment, the study tested and compared the spatial temperature uniformity, temporal stability, and power consumption of the new thermal insulation box versus traditional heating methods. Subsequently, animal trials were conducted in a farrowing barn using eight sows with similar farrowing dates as test subjects. The new thermal insulation box was installed in one group, and the traditional heating lamp in the control group. During the trial, ambient temperature, insulation area temperature, piglet behavior, growth performance, and power consumption were recorded. The results showed that compared to the control group, the new system reduced average temperature fluctuations in the insulation area by 31.6% and spatial temperature variation by 78.3%. During animal trials, the average temperatures directly under the heater for the new system versus the control in the insulation area were 39.7 ± 0.2 °C and 30.2 ± 1.4 °C in the first week, 40.9 ± 0.5 °C and 31.6 ± 0.7 °C in the second week, and 32.3 ± 1.5 °C and 28.6 ± 1.7 °C in the third week—significantly (p < 0.05) higher in the test group. The new system also reduced total energy consumption by 58.3%. The usage rate of the thermal insulation area by piglets in the test and control groups was 47.5 ± 5.3% and 42.1 ± 6.6%. The daily weight gain of piglets in the test group was 9.8% higher than that of the control group, also significantly (p < 0.05) higher. This intelligent thermal insulation box enables precise and dynamic temperature control, reducing heating energy consumption and supporting improved piglet health and welfare.

The rational design of artificial lighting systems in pig housing can enhance animal welfare, thereby boosting gilt health and reproductive performance while improving economic metrics for swine farms. To identify the optimal light environments for gilts under artificial illumination, we conducted self-selection-based photic preference testing, ultimately providing actionable insights for welfare-centric precision lighting protocols in modern pig production. In this study, a dynamic multi-chromatic self-selection system was developed, integrating programmable RGBW-LED arrays for spectral control, inter-compartment access channels for autonomous gilt movement, and real-time image recognition technology to investigate light color preferences. Twenty-four gilts (nulliparous female pigs) were housed for five weeks in pens with white, yellow, green, blue, or red light (100 lux), and they were given free access to all of the chromatic zones through inter-compartment channels. A YOLOv8n-based deep learning framework was used to quantify their spatiotemporal distribution, activity levels, and eating behavior. The key findings were the following: (1) a significant preference for green light environments (21.29 ± 3.77% distribution proportion) (p < 0.05), peaking at 6:00–13:00 and 18:00–20:00; (2) the average activity was the highest in a white light environment (25.49 ± 0.77%), significantly exceeding yellow (22.69 ± 0.63%) and green light (21.55 ± 0.61%) (p < 0.05); and (3) the daily feed consumption under green light was the lowest, significantly lower than that under white, blue, and red light (p < 0.05). The findings from this study offer insights into the light environment preferences of gilts, which could improve animal welfare.