Wheat powdery mildew caused by Blumeria graminis f. sp. tritici ( Bgt) is one of the most serious wheat diseases in the world. Biological control is considered an environmentally safe approach to control plant diseases. Here, to develop effective biocontrol agents for controlling wheat powdery mildew, antagonistic strain XZ16-1 was isolated and identified as Bacillus subtilis based on the morphological, biochemical, and physiological characteristics and 16S rDNA sequence. The culture filtrate of B. subtilis XZ16-1 and its extracts had a significant inhibitory effect on the spore germination of Bgt. Moreover, the therapeutic and prevention efficacy of the 100% culture filtrate on wheat powdery mildew reached 81.18 and 83.72%, respectively, which was better than that of chemical fungicide triadimefon. Further antimicrobial mechanism analysis showed that the XZ16-1 culture filtrate could inhibit the development of powdery mildew spores by disrupting the cell membrane integrity, causing reductions in the mitochondrial membrane potential, and inducing the accumulation of reactive oxygen species in the spores. Biochemical detection indicated that XZ16-1 could solubilize phosphate, fix nitrogen, and produce hydrolases, lipopeptides, siderophores, and indole-3-acetic acid. Defense-related enzymes activated in wheat seedlings treated with the culture filtrate indicated that disease resistance was induced in wheat to resist pathogens. Furthermore, a 10⁶ CFU/ml suspension of XZ16-1 increased the height, root length, fresh weight, and dry weight of wheat seedlings by 77.13, 63.46, 76.73, and 19.16%, respectively, and showed good growth-promotion properties. This study investigates the antagonistic activity and reveals the action mechanism of XZ16-1, which can provide an effective microbial agent for controlling wheat powdery mildew.

(1) Background: Soybean storage quality is crucial for subsequent processing and consumption, making it essential to explore an objective, rapid, and non-destructive technology for assessing its quality. (2) Methods: crude fatty acid value is an important indicator for evaluating the storage quality of soybeans. In this study, three types of soybeans were subjected to accelerated aging to analyze trends in crude fatty acid values. The study focused on acquiring raw spectral information using hyperspectral imaging technology, preprocessing by the derivative method (1ST, 2ND), multiplicative scatter correction (MSC), and standard normal variate (SNV). The feature variables were extracted by a variable iterative space shrinkage approach (VISSA), competitive adaptive reweighted sampling (CARS), and a successive projections algorithm (SPA). Partial least squares regression (PLSR), support vector machine (SVM), and extreme learning machine (ELM) models were developed to predict crude fatty acid values of soybeans. The optimal model was used to visualize the dynamic distribution of these values. (3) Results: the crude fatty acid values exhibited a positive correlation with storage time, functioning as a direct indicator of soybean quality. The 1ST-VISSA-SVM model was the optimal predictive model for crude fatty acid values, achieving a coefficient of determination (R²) of 0.9888 and a root mean square error (RMSE) of 0.1857 and enabling the visualization of related chemical information. (4) Conclusions: it has been confirmed that hyperspectral imaging technology possesses the capability for the non-destructive and rapid detection of soybean storage quality.

(1) In order to accurately judge the new maturity of wheat and better serve the collection, storage, processing and utilization of wheat, it is urgent to explore a fast, convenient and non-destructively technology. (2) Methods: Catalase activity (CAT) is an important index to evaluate the ageing of wheat. In this study, hyperspectral imaging technology (850–1700 nm) combined with a BP neural network (BPNN) and a support vector machine (SVM) were used to establish a quantitative prediction model for the CAT of wheat with the classification of the ageing of wheat based on different storage durations. (3) Results: The results showed that the model of 1ST-SVM based on the full-band spectral data had the best prediction performance (R² = 0.9689). The SPA extracted eleven characteristic bands as the optimal wavelengths, and the established model of MSC-SPA-SVM showed the best prediction result with R² = 0.9664. (4) Conclusions: The model of MSC-SPA-SVM was used to visualize the CAT distribution of wheat ageing. In conclusion, hyperspectral imaging technology can be used to determine the CAT content and evaluate wheat ageing, rapidly and non-destructively.

Boring pests such as Sitophilus zeamais (S. zeamais) are major threats in grain storage. However, how these pests affect the proteins of stored grains remains largely unknown. Here we aimed to investigate the effect of S. zeamais infestation on wheat protein during postharvest storage. In this study, wheat grain infested by S. zeamais was sampled at egg (4 d), larval (20 d), pupal (35 d), and adult stages (45 d), respectively. The protein’s physicochemical and structural properties and the edible quality of whole wheat noodle were analyzed. The results showed that S. zeamais infestation significantly decreased the quality of wheat protein by altering its constitution and structure properties. Especially, compared with the control, the content of wet and dry gluten, gluten index, sodium dodecyl sulfate sedimentation volume, sulfhydryl groups, and disulfide bonds in insect-infested wheat decreased by 19.40, 5.42, 18.40, 8.12, 29.13, and 14.30%, respectively, during the storage period of one life cycle of S. zeamais. Additionally, the proportions of wheat protein fractions (albumin [1.16-fold], globulin [0.96-fold], gliadin [1.16-fold], and glutenin [0.95-fold]) and secondary structures (α-helix [0.91-fold], β-fold [0.96-fold], β-turn [1.06-fold], and random coil [1.05-fold]) of protein changed significantly, and the gluten network structure was broken in S. zeamais-infested wheat. Furthermore, the color of whole wheat noodle became darker, cooking loss rate increased, and textural properties (hardness, adhesiveness, springiness, cohesiveness, chewiness, and resilience) decreased as well. The results in the present study provided new insights for analyzing the quality deterioration mechanism and further quality improvement of boring pests-infested wheat grain.