Convolutional neural network (CNN) can be used to quickly identify crop seed varieties. 1200 seeds of ten soybean varieties were selected, hyperspectral images of both the front and the back of the seeds were collected, and the reflectance of soybean was derived from the hyperspectral images. A total of 9600 images were obtained after data augmentation, and the images were divided into a training set, validation set, and test set with a 3:1:1 ratio. Pretrained models (AlexNet, ResNet18, Xception, InceptionV3, DenseNet201, and NASNetLarge) after fine-tuning were used for transfer training. The optimal CNN model for soybean seed variety identification was selected. Furthermore, the traditional machine learning models for soybean seed variety identification were established by using reflectance as input. The results show that the six models all achieved 91% accuracy in the validation set and achieved accuracy values of 90.6%, 94.5%, 95.4%, 95.6%, 96.8%, and 97.2%, respectively, in the test set. This method is better than the identification of soybean seed varieties based on hyperspectral reflectance. The experimental results support a novel method for identifying soybean seeds rapidly and accurately, and this method also provides a good reference for the identification of other crop seeds.

Background: Phosphorus (P) is essential for plant growth and development, and low-phosphorus (LP) stress is a major factor limiting the growth and yield of soybean. Long noncoding RNAs (lncRNAs) have recently been reported to be key regulators in the responses of plants to stress conditions, but the mechanism through which LP stress mediates the biogenesis of lncRNAs in soybean remains unclear. Results: In this study, to explore the response mechanisms of lncRNAs to LP stress, we used the roots of two representative soybean genotypes that present opposite responses to P deficiency, namely, a P-sensitive genotype (Bogao) and a P-tolerant genotype (NN94156), for the construction of RNA sequencing (RNA-seq) libraries. In total, 4,166 novel lncRNAs, including 525 differentially expressed (DE) lncRNAs, were identified from the two genotypes at different P levels. GO and KEGG analyses indicated that numerous DE lncRNAs might be involved in diverse biological processes related to phosphate, such as lipid metabolic processes, catalytic activity, cell membrane formation, signal transduction, and nitrogen fixation. Moreover, lncRNA-mRNA-miRNA and lncRNA-mRNA networks were constructed, and the results identified several promising lncRNAs that might be highly valuable for further analysis of the mechanism underlying the response of soybean to LP stress. Conclusions: These results revealed that LP stress can significantly alter the genome-wide profiles of lncRNAs, particularly those of the P-sensitive genotype Bogao. Our findings increase the understanding of and provide new insights into the function of lncRNAs in the responses of soybean to P stress.

The Sec14 domain is an ancient lipid-binding domain that evolved from yeast Sec14p and performs complex lipid-mediated regulatory functions in subcellular organelles and intracellular traffic. The Sec14 family is characterized by a highly conserved Sec14 domain, and is ubiquitously expressed in all eukaryotic cells and has diverse functions. However, the number and characteristics of Sec14 homologous genes in soybean, as well as their potential roles, remain understudied. In this study, we identified 77 Sec14 genes in the soybean genome that were unevenly distributed across 19 chromosomes. Based on the classification method used for Arabidopsis Sec14 members, GmSec14s can be categorized into three classes: GmPITP1 to GmPITP37, GmSFH1 to GmSFH25, and GmPATL1 to GmPATL15. Structural analysis of the GmSec14 genes revealed that the SFH subfamily contained more introns than the other subfamilies. A total of 10 conserved protein motifs were detected within GmSec14 proteins, with each subfamily possessing unique motifs. Two tandem duplications and 73 segmental duplications were identified among the GmSec14 genes. Additionally, a large number of cis-acting elements, particularly those related to plant hormones, were abundant in the promoter regions of the GmSec14 genes. Tissue expression analysis of the GmSec14 genes indicated that they exhibited distinct tissue-specific expression patterns. In response to salt stress, multiple genes were found to be either upregulated or downregulated. In contrast, the majority of genes were downregulated under drought stress conditions. Notably, 12 GmSec14 genes exhibited significant alterations in expression following salt or drought stress, suggesting a potential role for these genes in stress response mechanisms. Furthermore, the protein interaction network and miRNA regulation associated with GmSec14s were predicted to elucidate the potential functions of GmSec14 members. This study provides a systematic and comprehensive examination of the Sec14 gene family in soybean, which will facilitate further functional research into their roles in response to salt and drought tolerance.