Salt is recognized as one of the most major factors that limits soybean yield in acidic soils. Soil enzyme activity and bacterial community have a critical function in improving the tolerance to soybean. Our aim was to assess the activities of soil enzyme, the structure of bacteria and their potential functions for salt resistance between Salt-tolerant (Salt-T) and -sensitive (Salt-S) soybean genotypes when subject to salt stress. Plant biomass, soil physicochemical properties, soil catalase, urease, sucrase, amylase, and acid phosphatase activities, and rhizosphere microbial characteristics were investigated in Salt-T and Salt-S soybean genotypes under salt stress with a pot experiment. Salt stress significantly decreased the soil enzyme activities and changed the rhizosphere microbial structure in a genotype-dependent manner. In addition, 46 ASVs which were enriched in the Salt-T geotype under the salt stress, such as ASV19 (Alicyclobacillus), ASV132 (Tumebacillus), ASV1760 (Mycobacterium) and ASV1357 (Bacillus), which may enhance the tolerance to soybean under salt stress. Moreover, the network structure of Salt-T soybean was simplified by salt stress, which may result in soil bacterial communities being susceptible to external factors. Salt stress altered the strength of soil enzyme activities and the assembly of microbial structure in Salt-T and Salt-S soybean genotypes. Na⁺, NO₃⁻–N, NH₄⁺–N and Olsen-P were the most important driving factors in the structure of bacterial community in both genotypes. Salt-T genotypes enriched several microorganisms that contributed to enhance salt tolerance in soybeans, such as Alicyclobacillus, Tumebacillus, and Bacillus. Nevertheless, the simplified network structure of salt-T genotype due to salt stress may render its bacterial community structure unstable and susceptible.

Although crop rotations have been widely shown as an effective approach for improving yield or soil quality in the long term, the relationship between crop rotations and quality traits of crop or biochar-based fertilization is still unclear. To address this, we conducted a long-term field experiment in the Heilongjiang province of China to investigate the effects of crop rotation and biochar-based fertilizer application on the crop yield, soil parameters, crop quality, and agronomic traits in 2014–2020. The effects of rotations on crop production and soil properties were evaluated with the average yield variability during the 7 years of this study. Our results showed that the diversified corn and soybean rotations had a significant positive effect on average crop yield compared with their monocultures. The corn yield was enhanced by 0.6 Mg ha⁻¹ (5.4%) in the corn–soybean–corn (CSC) crop sequence compared with monoculture corn. Similarly, soybean yield was enhanced by 0.21 Mg ha⁻¹ (9.7%) in the soybean–corn–corn (SCC) crop sequence compared with monoculture soybean. However, a negative effect of crop rotations was detected on the protein content of soybean compared with the monoculture soybean, while a positive effect was detected on oil content. Additionally, no differences were detected in crop yield between biochar-based fertilization and mineral fertilization treatments, but a significant positive effect of biochar-based fertilization was observed for any crop on both protein and oil content. A significant effect of crop rotation was found on the percentage of total soil N (TN), available soil N (AN), and available soil K (AK) content. The SSS crop sequence treatment illustrated the highest TN values at 0.18%. The CCC crop sequence treatment increased AN and AK content by 9.1% and 7.8%, respectively, compared with SSS (p < 0.05). We conclude that crop rotations increase crop yield and biochar-based fertilizer application, improving crop quality traits in the long term. Thus, the addition of biochar-based fertilizer could efficiently enhance the yield and quality of crop in the rotation cropping system. The findings of this study may provide useful information for designing sustainable cropping systems based on rotations.

Introduction: Soybean, as a globally significant crop, has garnered substantial attention due to its agricultural importance. The utilization of molecular approaches to enhance grain yield in soybean has gained popularity.Methods: In this study, we conducted a genome-wide association study (GWAS) using 156 Chinese soybean accessions over a two-year period. We employed the general linear model (GLM) and the mixed linear model (MLM) to analyze three agronomic traits: pod number, grain number, and grain weight. Results: Our findings revealed significant associations between qgPNpP-98, qgGNpP-89 and qgHGW-85 QTLs and pod number, grain number, and grain weight, respectively. These QTLs were identified on chromosome 16, a region spanning 413171bp exhibited associations with all three traits. Discussion: These QTL markers identified in this study hold potential for improving yield and agronomic traits through marker-assisted selection and genomic selection in breeding programs.

The stink bug, Riptortus pedestris (Fabricius) (Hemiptera: Alydidae), is a highly destructive pest that significantly damages legume crops in East and South Asia. Neonicotinoid insecticides containing thiamethoxam are widely used to control R. pedestris in soybean fields. However, the current knowledge on the impact of different thiamethoxam concentrations on R. pedestris growth and reproduction is lacking and insufficient. The present study investigated the effects of thiamethoxam on the biological traits of R. pedestris after treatment with LC₁₀ (19.8 mg/L), LC₂₀ (31.6 mg/L), LC₃₀ (44.2 mg/L), LC₄₀ (58.9 mg/L), and LC₅₀ (77.0 mg/L) concentrations. These five thiamethoxam concentrations (LC₁₀~LC₅₀) reduced adult longevity and fecundity in the F₁ generation females. Thiamethoxam treatment also significantly decreased the population trend index, intrinsic rate of increase, net reproductive rate, gross reproductive rate, and finite rate of increase and increased the mean generation time. These results show that thiamethoxam hinders and suppresses the development and growth of the F₁ population of R. pedestris. Thiamethoxam is recommended for spray control during peak adult emergence, as it not only has a controlling effect on the parental generation but also a negative impact on the F₁ generations.

The core of saline-alkali land improvement is planting suitable plants. Planting rice in saline-alkali land can not only effectively improve saline-alkali soil, but also increase grain yield. However, traditional identification methods for saline-alkali-tolerant rice varieties require tedious and time-consuming field investigations based on growth indicators by rice breeders. In this study, the visualization method of Python data processing was used to analyze the Raman spectroscopy of japonica rice in order to study a simple and efficient identification method of saline-alkali-tolerant japonica rice varieties. Three saline-alkali-tolerant japonica varieties and three saline-alkali-sensitive japonica varieties were collected from control and saline-alkali-treated fields, respectively, and the Raman spectra of 432 samples were obtained. The data preprocessing stage used filtering-difference method to process Raman spectral data to complete interference reduction and crests extraction. In the feature selection stage, scipy.signal.find_peaks (SSFP), SelectKBest (SKB) and recursive feature elimination (RFE) were used for machine feature selection of spectral data. According to the feature dimension obtained by machine feature selection, dataset partitioning by K-fold CV, the typical linear logistic regression (LR) and typical nonlinear support vector machine (SVM) models were established for classification. Experimental results showed that the typical nonlinear SVM identification model based on both RFE machine feature selection and six-fold CV dataset partitioning had the best identification rate, which was 94%. Therefore, the SVM classification model proposed in this study could provide help in the intelligent identification of saline-alkali-tolerant japonica rice varieties.

Herbivorous insects having variable numbers of generations annually depending on climate and day length conditions are increasingly breeding additional generations driven by elevated temperature under the scenario of global warming, which will increase insect abundance and result in more frequent damage events. Theoretically, this relies on two premises, i.e., either an evolutionary shift to facultative diapause for an insect behaving an obligatory diapause or developmental plasticity to alter voltinism productively for an insect with facultative diapause before shortening photoperiods inducing diapause. Inter-population evidence supporting the premise (theory) comes primarily from a model system with voltinism linked to thermal gradients across latitude. We examined the intra-population evidence in the field (47°24′ N, 123°68′ E) with Ostrinia furnacalis, one of the most destructive pests, on corn in Asia and Pacific islands. The species was univoltine in high latitudinal areas (≤46° N). Divergence of the diapause feature (obligatory and facultative) was observed within the field populations from 2016 to 2021. Warmer climates would provoke more facultative diapause individuals to initiate a second generation, which will significantly drive the population to evolve toward facultative diapause (multi-voltinism). Both divergent diapause and temperature must be considered for accurate prediction of phenology and population dynamics in ACB.