C. vulgaris has a positive effect on the removal of nutrients from pig farm biogas slurry. However, swine wastewater often contains heavy metal ions, such as Cu (II), which may have impacts on the nutrient removal performance of C. vulgaris. Additionally, the heavy metal ions in wastewater can be adsorbed by microalgae. In this study, the stress effect of Cu (II) on the growth of Chlorella vulgaris, the Cu (II) removal by microalgae, and the effect of different concentrations of Cu (II) on the nutrient removal efficiency of C. vulgaris in biogas slurries were explored. The results showed that the microalgae biomass of microalgae on the sixth day of the experiment was the highest in the treatment with a Cu (II) concentration of 0.5 mg/L, which was 30.1% higher than that of the 2.5 mg/L group. C. vulgaris had higher removal efficiencies of Cu (II) at a Cu (II) concentration of 0.1~1.5 mg/L. The–OH, C=O, –COOH, and C–O groups on the surface of the algal cells play a significant role in the removal of Cu (II). The removal rates of COD, NH₃–N, TN, and TP by C. vulgaris at a Cu (II) concentration of 0.5 mg/L were the highest, which were 89.0%, 53.7%, 69.6%, and 47.3%, respectively.

Body temperature measurement is a very important task in the sow breeding process. The authors used an infrared camera to detect the temperature of the body surface of the sows, relying on calculating the average of the infrared image temperature in the ear root region. Based on the grayscale value of the target image of the infrared image and the corresponding temperature value of 180 infrared images, a G‐T (Gray‐Temperature ) model was established by linear least squares method, which achieved temperature inversion of each pixel of the target pig. For the different growth stages and different breeds of sows, the R‐square of the all established models is greater than 0.95. The average relative error of the model inversion of the body temperature was only 0.076977%. This means that the body temperature of the sows could be detected without relying on the software. Based on the G‐T model, the authors design a kind of sow's ear root recognition and body surface temperature detection algorithm for different sow population scenarios.

Combined treatments were designed based on iron-carbon micro-electrolysis treatment (ICME), physical adsorption (PA) with zeolite (Z) or vermiculite (V) and microalgae cultivation (MC, Chlorella vulgaris) for removing pollutants from swine wastewater (SW): ICME + MC (IM), ICME + Z + MC (IZM) and ICME + V + MC (IVM). Results showed that the minimum total nitrogen (TN) of 43.66 mg L−1, NH4+-N of 1.33 mg−1 and total phosphorus (TP) of 0.14 mg−1 were obtained by IVM, while the minimum chemical oxygen demand (COD) was 105 mg−1 via IM. During the process of combined treatments, ICME contributed most to the removal of TN (84.52% by IZM), TP (97.78% by IVM and IZM) and COD (62.44% by IVM), and maximum NH4+-N removal (55.64%) was obtained by MC procedure in IM process. Vermiculite performed better than zeolite during all the combined treatments. Besides, the maximum cell dry weight (CDW, 0.74 g−1) of C. vulgaris was obtained by IM on day 13. The results provide an efficient integrated method for swine wastewater treatment.

In recent years, animal cleanliness during production has gradually attracted increasing attention. Although pigs by nature tend to excrete in dark and humid corners, in the prevalent highly intensive pig production, excessive stocking density often restricts the ability of pigs to excrete at designated points, thereby leading to pollution of the pens. To study the effect of stocking density on pen cleanliness and the relevant pig behavior, a total of 216 Landrace × Yorkshire × Duroc hybrid pigs were randomly grouped at 0.5, 0.7, or 0.9 m² per pig at 59 ± 3 days of age. The temporal and spatial distributions of lying and excreting behavior of pigs were monitored on days 1, 7, and 35 after transfer, and the cleanliness of pig pens under three stocking densities was scored. The results showed that there were no significant differences in excreting or lying time rhythms among the three treatments. In the initial and stable periods of group transfer, the excretion rate of pigs on slatted floors was significantly higher than that on solid floors at 0.9 m²/pig (p < 0.01). During the group stabilization stage and at the end of the experiment, the lying rate of pigs on solid floors under 0.9 m²/pig was 10.81%, that is, 7.43% higher than that of 0.7 m²/pig, and the differences were significant. Judging from the pollution score of the solid floors, the three stocking densities all showed more serious pollution at the corners, and the pollution score of the pens with a density of 0.9 m²/pig was lower than that of the pens with a density of 0.5 and 0.7 m²/pig. The analysis of whether pigs had corresponding behaviors in specific functional areas showed that pigs at a density of 0.9 m²/pig had a 10.14% lower lying rate on slatted floors (the expected excretion area) than on solid floors, whereas the densities of 0.5 and 0.7 m²/pig showed the opposite pattern. Pigs at a density of 0.9 m²/pig had lower excretion rates in both corners of the solid floors (the desired lying area) than that of the 0.5 m²/pig group (p < 0.05) and 0.7 m²/pig group (p > 0.05). These results indicate that when the effective occupied space of pigs was larger, specific behaviors were more likely to occur in the set functional areas, and the cleanliness of the pen was higher. Under the conditions of this experiment, the recommended stocking density for growing pigs was 0.9 m²/pig. Of course, a larger space may be more beneficial to animal health and welfare, but the economic costs must also be considered.

Lighting is an important environmental parameter in livestock farming, which can affect the physiology and behavior of animals, and it can regulate animal production. To explore the comprehensive effects of light intensity and duration on the performance, behavior, and physiological indicators of piglets, a 3 × 2 two-factor experiment (three levels of lighting intensity × two lighting durations) was conducted. The three light intensities used were high (100–120 lux), medium (40–50 lux), and low (5–20 lux). The two lighting durations were 8 h and 10 h of light per day. The experiment used a total of six lighting combinations, which corresponded with the six test units. A total of 96 Landrace–Yorkshire hybrid piglets, with an initial body weight of 13.23 ± 0.18 kg, were randomly assigned to six lit units, four pens per unit, and four piglets per pen. The results showed that lighting intensity and duration had no significant effect on the average daily feed intake, average daily gain, feed/gain, or water consumption of pigs (p > 0.05). For IgM, the main effect caused by the light duration was significant. When the light intensity was 5–20 lux and 40–50 lux, the serum IgM levels of piglets in the 10 h/day light group were 45.80% and 39.54% higher than those in the 8 h/day group, respectively (p < 0.05). For SOD and GSH-Px, the interaction between the lighting duration and intensity was significant (p < 0.05). In the 8 h/day light group, the serum SOD levels of piglets at light intensities of 5–20 lux and 40–50 lux were significantly higher than those at 100–120 lux (p < 0.05). When the light intensity was 5–20 lux and 40–50 lux, the SOD level in the 8 h/day group was significantly higher than that of the 10 h/day group (p < 0.05). The main effect of lighting duration on lying down and abnormal behavior was significant (p < 0.05). In the 8 h/day light group, the abnormal behavior of piglets under a light intensity of 5–20 lux was twice that of 40–50 lux (p < 0.05), and the lying percentage of piglets under a light intensity of 40–50 lux was 14.03% higher than that of piglets under a light intensity of 5–20 lux (p < 0.05). Overall, under the conditions used in this study, although extending the duration of light with an intensity of 40–50 lux to 10 h can improve some immune-related indicators, the extent of this effect was limited. The recommended lighting scheme for piglet houses is a light intensity of 40–50 lux and a lighting duration of 8 h. However, the range of lighting conditions set in this study was still very limited, and various environmental factors must be comprehensively considered in an actual production setting.

In this study, we propose an intelligent drinking water controller based on programmable logic controller (PLC) specifically designed for pig breeding, which significantly reduces the water waste caused by the use of traditional drinking bowls by regulating the frequency and flow of water release. In addition, the drinking water system has a tracking and recording function, which can record the frequency and duration with which fattening pigs drink water in each pen in detail, thus providing farmers with a wealth of pig health and behavior data to help optimize breeding management decisions. In order to deeply analyze the effects of the intelligent drinking water controller on the growth, resources environment and economic benefits of fattening pigs under the condition of large-scale breeding, a single factor comparison experiment was designed.In this experiment, 84 fattening pigs were selected and distributed in 12 pens. Among them, six pens were randomly designated as the control group;the pig in this group used ordinary drinking water bowls for the water supply. The other six pens were designated as the experimental group;the pigs in this group used the intelligent drinking water controller. The experimental results showed that in the experimental group with the intelligent drinking water controller, the average daily water waste per finishing pig was only 0.186 L (p < 0.05), accounting for only 25.98% of the average daily water waste per pig in the control group (p < 0.05). In terms of water quality, the intelligent drinking water controller also showed better performance, and the performance indicators were effectively reduced, with the highest reduction reaching 39.86%, which greatly reduced water pollution. Compared with the traditional drinking bowl, the average daily weight increment of fattening pigs in the pen using the intelligent drinking water controller was increased by 0.02 kg. In terms of long-term benefits, the PLC-based intelligent drinking water controller significantly improves the economic returns of the farm and has a positive impact on pig health. The high frequency data collection of the pigs’ drinking habits through the intelligent drinking water controller can also provide data support for the subsequent establishment of a pig water-drinking behavior analysis model.