The situation that China's soybean imports have broken through new highs and the import sources are highly concentrated,and the degree of dependence on import is rising,led to severe risks for the availability and stability of soybean import source,threatening China's food security.In this paper,the dependence risk of China's soybean import was examined both on the whole and individually,and the generation mechanism of China's soybean import dependence risk was analyzed and examined through constructing a model.The results showed that,there were import dependency risk for China's soybean imports from the United States and Brazil,two top source countries for China's soybean imports,which indicated that the risk situation is severe.It is,on the one hand,due to the strong supply capacity of major soybean exporting countries,which makes it easy for China to depend highly on them,and on the other hand,due to the increasing demand for soybean imports in China,which makes the dependence risk of China's soybean import increasing.Based on the research results,suggestions are proposed to establish a sound and comprehensive soybean risk monitoring and warning system,improve diversified soybean import layout,enhance the resilience of soybean supply chain and domestic soybean production capacity.
Salt stress is one of the important environmental factors affecting the growth,development and yield of soybean.NAC family transcription factors are important genes in plant response to salt stress,but their functions have not been fully elucidated in soybean.To identity new genes that control salt tolerance in soybean,in this study,the whole genome analysis,cluster analysis and transcriptome data of soybean plants under salt stress were first used to identify NAC genes induced by salt stress.Secondly,the haplotype,salt tolerance index and nucleic acid polymorphism of NAC genes induced by salt stress in roots were analyzed.We identified 182 NAC genes in the soybean genome and divided them to 7 subfamilies.We found that the expression of 18 NAC genes were significantly up-regulated under salt stress,among which eight NAC genes were expressed in roots,which might be related to response to salt stress.An important gene NAC23 that may respond to salt stress was identified.Our results also showed that the Hap1 haplotype of NAC23 may promote the tolerance of cultivated soybean to salt stress,and this gene was subjected to strong artificial selection.These results provide new insights for the comprehensive analysis of the relationship between NAC gene and soybean salt tolerance,and provide gene resources and new ideas for breeding new varieties of highly resistant crops.
Genotype Imputation(GI)is a technique that uses existing genotype information to infer unobserved or incomplete genotypes.This study aims to explore efficient imputation methods for handling incomplete data in soybean genomic sequencing,with the goal of improving data processing speed and efficiency.Real soybean reference panel genotype data was used in the study,and the data was subjected to complete random missingness at rates of 2％,5％,10％,and 25％.A GPU-acceleratedrandom forest machine learning algorithm was employed to construct imputation models and fill in the missing data at different missingness rates.Additionally,the accuracy and performance of different processors were compared and analyzed.The research results demonstrate that the GPU-accelerated random forest algorithm achieves excellent imputation accuracy in the soybean genome.Compared to mainstream genotype imputation software,this method provides at least a fourfold computational time advantage.Therefore,the GPU-accelerated genotype imputation strategy can be applied to large-scale genotype data processing,improving the speed and efficiency of soybean genotype data processing while reducing computational time and resource consumption.
To solve the complex background interference problem of existing convolutional neural networks in soybean leaf disease classification,an improved ConvNeXt algorithm is proposed,and two common diseases of soybean as well as healthy leaves are classified and identified.By adding multiple attention modules to the traditional ConvNeXt algorithm,the network is made more capable of focusing on discriminative features and the LeakyReLu activation function is chosen instead of the ReLu activation function to avoid the neuron deactivation phenomenon.In addition,the robustness of the network was improved by performing data enhancement on the dataset to diversify the disease dataset.The results showed that the improved ConvNeXt algorithm outperforms the original ConvNeXt,ResNet50 and Swin Transformer,all three comparison models,in terms of average classification accuracy on the test set.The average recognition accuracy on the data enhanced test set reached 85.42％,and the research results can provide reference for solving the classification of soybean leaf disease images under complex background information interference.
Soybean plants are very sensitive to boron deficiency.Under boron deficiency treatment,the patterns of change in growth,development and protective enzyme activity of soybean seedlings were investigated.In this study,Mengke 9 was used as a test material.At the soybean seedling stage,two treatments were set up of boron deficiency(B-)and full nutrition(CK),respectively.Patterns of changes in photosynthetic physiological parameters,dry matter accumulation and protective enzyme activity were analysed in the different treatments,which performed correlation analysis.The results showed that soybean plant height,SPAD value,fluorescence value and dry matter accumulation were significantly reduced under boron deficiency treatment.Compared to the full nutrition treatment under T6(8 d)treatment time,soybean plant height was reduced by 12.54％,SPAD value by 27.33％,fluorescence value by 4.41％and dry matter accumulation by 28.25％.Soybean seedlings under B-deficiency treatment and allotrophic conditions,protective enzyme activities(SOD,APX,CAT and POD)showed an increasing and then decreasing trend with increasing stress time.Malondialdehyde(MDA)content showed a constant increase.Among these,the enzyme activities of the plant showed higher roots than leaves.The dry matter accumulation of soybean was positively correlated with plant height,SPAD value,fluorescence value and APX activity,positively correlated with SOD,CAT,POD activity,and negatively correlated with MDA content.These results showed that boron deficiency inhibited the growth and development of soybean seedlings.These results showed that boron deficiency inhibited the growth and development of soybean seedlings.In the early stages of stress,the activity of these protective enzymes increased,which is maintained normal growth of soybean.However,the activity of these enzymes decreased significantly with time under stress.
