Plant lodging is one of the most essential phenotypes for soybean breeding programs. Soybean lodging is conventionally evaluated visually by breeders, which is time-consuming and subject to human errors. This study aimed to investigate the potential of unmanned aerial vehicle (UAV)-based imagery and machine learning in assessing the lodging conditions of soybean breeding lines. A UAV imaging system equipped with an RGB (red-green-blue) camera was used to collect the imagery data of 1266 four-row plots in a soybean breeding field at the reproductive stage. Soybean lodging scores were visually assessed by experienced breeders, and the scores were grouped into four classes, i.e., non-lodging, moderate lodging, high lodging, and severe lodging. UAV images were stitched to build orthomosaics, and soybean plots were segmented using a grid method. Twelve image features were extracted from the collected images to assess the lodging scores of each breeding line. Four models, i.e., extreme gradient boosting (XGBoost), random forest (RF), K-nearest neighbor (KNN) and artificial neural network (ANN), were evaluated to classify soybean lodging classes. Five data preprocessing methods were used to treat the imbalanced dataset to improve classification accuracy. Results indicate that the preprocessing method SMOTE-ENN consistently performs well for all four (XGBoost, RF, KNN, and ANN) classifiers, achieving the highest overall accuracy (OA), lowest misclassification, higher F1-score, and higher Kappa coefficient. This suggests that Synthetic Minority Oversampling-Edited Nearest Neighbor (SMOTE-ENN) may be a good preprocessing method for using unbalanced datasets and the classification task. Furthermore, an overall accuracy of 96% was obtained using the SMOTE-ENN dataset and ANN classifier. The study indicated that an imagery-based classification model could be implemented in a breeding program to differentiate soybean lodging phenotype and classify lodging scores effectively.

Long-term anaerobic co-digestion of swine manure (SM) and corn stover (CS) was conducted using semi-continuously loaded digesters under mesophilic conditions. A preliminary test was first conducted to test the effects of loading rates, and results indicated the 3 g-VS L⁻¹ d⁻¹ was the optimal loading rate. Based on the preliminary results, a verification replicated test was conducted with 3 g-VS L⁻¹ d⁻¹ loading rate and different SM/CS ratios (1:1, 2:1 and 1:2). Results showed that a SM/CS ratio of 2/1 was optimal, based on maximum observed methane-VS_des generation and carbon conversion efficiency (72.56 ± 3.40 mL g⁻¹ and 40.59%, respectively). Amplicon sequencing analysis suggested that microbial diversity was increased with CS loading. Amino-acid-degrading bacteria were abundant in the treatment groups. Archaea Methanoculleus could enhance biogas and methane productions.

Concentrations of critical aerial pollutants within animal farms are important to the health of animals and farm staff and can be reduced via manure management, ventilation control, and barn design. This study characterized measurements of ammonia (NH₃), total suspended particle (TSP), and airborne microbial communities of a large-scale pig-fattening house, as well as their correlations with environmental variables in Southwestern China. Monitoring was conducted for 15 consecutive days during both August and January, at various locations inside the pig house. The concentrations of NH₃ and TSP averaged 3.22 and 0.55 mg m⁻³, respectively, while the average number of airborne microbial colonies was 3.91 log cfu m⁻³. The aerial pollutant concentrations displayed significant seasonal differences (p < 0.05). Specifically, concentrations in winter were significantly higher than those in summer (p < 0.05), and the 07:00 measurements were the highest among the three measurement times. The concentrations were significantly correlated with indoor temperature and relative humidity. In summer, TSP concentration was negatively correlated with temperature (correlation coefficient = −0.732), while NH₃ concentration was positively correlated with temperature (correlation coefficient = 0.58). In winter, TSP and NH₃ concentrations were negatively correlated with relative humidity (correlation coefficients = −0.739 and −0.713, respectively), while the airborne microbial colonies were not correlated with either humidity or temperature in summer or winter. These findings confirm that the aerial pollutant concentrations in a Southwestern China pig-fattening house exhibited significant seasonal and diurnal variations. Air quality can be improved by more precise ventilation control as observed by the correlation of concentrations with ventilation control, indoor temperature, and humidity.

Fine particulate matter (PM), including PM_2.5 in pig houses, has received increasing attention due to the potential health risks associated with PM. At present, most studies have analyzed PM_2.5 in Chinese pig houses utilizing natural ventilation. These results, however, are strongly affected by the internal structure and regional environment, thus limiting their applicability to non-mechanically ventilated pig houses. This experiment was carried out in an environmentally controlled pig house. The animal feeding operation and manure management in the house were typical for Southwest China. To reduce the influence of various environmental factors on PM_2.5, the temperature and humidity in the house were maintained in a relatively stable state by using an environmental control system. The concentration of PM_2.5 in the pig house was monitored, while the biological contents and chemical composition of PM_2.5 were analyzed, and feed, manure, and dust particles were scanned using an electron microscope. Moreover, bacterial and fungal contents and some water-soluble ions in PM_2.5 were identified. The results showed that the concentration of PM_2.5 in the pig house was strongly affected by pig activity, and a phenomenon of forming secondary particles in the pig house was found, although the transformation intensity was low. The concentration of PM_2.5 had negative correlations of 0.27 and 0.18 with ammonia and hydrogen sulfide, respectively. Interestingly, a stronger correlation was observed between ammonia and hydrogen sulfide and ammonia and carbon dioxide concentrations (the concentration of ammonia had stronger positive correlations with hydrogen sulfide and carbon dioxide concentrations at +0.44 and +0.59, respectively). The main potential sources of PM_2.5 production were feed and manure. We speculate that manure could contribute to the broken, rough, and angular particles that formed the pig house PM_2.5 that easily adhered to other components.

Antibiotic-resistant microorganisms are drawing a lot of attention due to their severe and irreversible consequences on human health. The animal industry is considered responsible in part because of the enormous volume of antibiotics used annually. In the current research, veterinary antibiotic (VA) degradation, finding the threshold of removal and recognizing the joint effects of chlortetracycline (CTC) and Tylosin combination on the digestion process were studied. Laboratory scale anaerobic digesters were utilized to investigate potential mitigation of VA in swine manure. The digesters had a working volume of 1.38 L (in 1.89-L glass jar), with a hydraulic retention time (HRT) of 21 days and a loading rate of 1.0 g-VS L⁻¹ d⁻¹. Digesters were kept at 39 ± 2 °C in incubators and loaded every two days, produced biogas every 4 days and digester pH were measured weekly. The anaerobic digestion (AD) process was allowed 1.5 to 2 HRT to stabilize before adding the VAs. Tests were conducted to compare the effects of VAs onto manure nutrients, volatile solid removal, VA degradation, and biogas production. Concentrations of VA added to the manure samples were 263 to 298 mg/L of CTC, and 88 to 263 mg/L of Tylosin, respectively. Analysis of VA concentrations before and after the AD process was conducted to determine the VA degradation. Additional tests were also conducted to confirm the degradation of both VAs dissolved in water under room temperature and digester temperature. Some fluctuations of biogas production and operating variables were observed because of the VA addition. All CTC was found degraded even only after 6 days of storage in water solution; thus, there was no baseline to estimate the effects of AD. As for Tylosin, 100% degradation was observed due to the AD (removal was 100%, compared with 24–40% degradation observed in the 12-day water solution storage). Besides, complete Tylosin degradation was also observed in the digestate samples treated with a mixture of the two VAs. Lastly, amplicon sequencing was performed on each group by using the 50 most variable operational taxonomic units (OTUs)s and perfect discriminations were detected between groups. The effect of administration period and dosage of VAs on Phyla Firmicutes Proteobacteria, Synergistetes and Phylum Bacteroides was investigated. These biomarkers’ abundance can be employed to predict the sample’s treatment group.