Aquaporins (AQPs) are one diverse family of membrane channel proteins that play crucial regulatory roles in plant stress physiology. However, the heat stress responsiveness of AQP genes in soybean remains poorly understood. In this study, 75 non-redundant AQP encoding genes were identified in soybean. Multiple sequence alignments showed that all GmAQP proteins possessed the conserved regions, which contained 6 trans-membrane domains (TM1 to TM6). Different GmAQP members consisted of distinct Asn-Pro-Ala (NPA) motifs, aromatic/arginine (ar/R) selectivity filters and Froger’s positions (FPs). Phylogenetic analyses distinguished five sub-families within these GmAQPs: 24 GmPIPs, 24 GmTIPs, 17 GmNIPs, 8 GmSIPs, and 2 GmXIPs. Promoter cis-acting elements analyses revealed that distinct number and composition of heat stress and hormone responsive elements existed in different promoter regions of GmAQPs. QRT-PCR assays demonstrated that 12 candidate GmAQPs with relatively extensive expression in various tissues or high expression levels in root or leaf exhibited different expression changes under heat stress and hormone cues (abscisic acid (ABA), l-aminocyclopropane-l-carboxylic acid (ACC), salicylic acid (SA) and methyl jasmonate (MeJA)). Furthermore, the promoter activity of one previously functionally unknown AQP gene-GmTIP2;6 was investigated in transgenic Arabidopsis plants. The beta-glucuronidase (GUS) activity driven by the promoter of GmTIP2;6 was strongly induced in the heat- and ACC-treated transgenic plants and tended to be accumulated in the hypocotyls, vascular bundles, and leaf trichomes. These results will contribute to uncovering the potential functions and molecular mechanisms of soybean GmAQPs in mediating heat stress and hormone signal responses.

Tonoplast intrinsic proteins (TIPs), a sub-family of aquaporins (AQPs), are known to play important roles in plant abiotic stress responses. However, evidence for the promoters of TIPs involvement in abiotic stress processes remains scarce. In this study, the promoter of the vegetable soybean GmTIP1;6 gene, which had the highest similarity to TIP1-type AQPs from other plants, was cloned. Expression pattern analyses indicated that the GmTIP1;6 gene was dramatically induced by drought, salt, abscisic acid (ABA), and methyl jasmonate (MeJA) stimuli. Promoter analyses revealed that the GmTIP1;6 promoter contained drought, ABA, and MeJA cis-acting elements. Histochemical staining of the GmTIP1;6 promoter in transgenic Arabidopsis corroborated that it was strongly expressed in the vascular bundles of leaves, stems, and roots. Beta-glucuronidase (GUS) activity assays showed that the activities of the GmTIP1;6 promoter were enhanced by different concentrations of polyethylene glycol 6000 (PEG 6000), NaCl, ABA, and MEJA treatments. Integrating these results revealed that the GmTIP1;6 promoter could be applied for improving the tolerance to abiotic stresses of the transgenic plants by promoting the expression of vegetable soybean AQPs.

Herbicide phytotoxicity represented a critical constraint on crop safety in soybean–corn intercropping systems, where early detection of herbicide stress is essential for implementing timely mitigation strategies to preserve yield potential. Current methodologies lack rapid, non-invasive approaches for early-stage prediction of herbicide-induced stress. To develop and validate a spectral-feature-based prediction model for herbicide concentration classification, we conducted a controlled experiment exposing three-leaf-stage vegetable soybean (Glycine max L.) seedlings to aqueous solutions containing three concentrations of nicosulfuron herbicide (0.5, 1, and 2 mL/L) alongside a water control. Hyperspectral imaging of randomly selected seedling leaves was systematically performed at 1, 3, 5, and 7 days post-treatment. We developed predictive models for herbicide phytotoxicity through advanced machine learning and deep learning frameworks. Key findings revealed that the ResNet-18 deep learning model achieved exceptional classification performance when analyzing the 386–1004 nm spectral range at day 7 post-treatment: 100% accuracy in binary classification (herbicide-treated vs. water control), 93.02% accuracy in three-class differentiation (water control, low/high concentration), and 86.53% accuracy in four-class discrimination across specific concentration gradients (0, 0.5, 1, 2 mL/L). Spectral analysis identified significant reflectance alterations between 518 and 690 nm through normalized reflectance and first-derivative transformations. Subsequent model optimization using this diagnostic spectral subrange maintained 100% binary classification accuracy while achieving 94.12% and 82.11% accuracy for three- and four-class recognition tasks, respectively. This investigation demonstrated the synergistic potential of hyperspectral imaging and deep learning for early herbicide stress detection in vegetable soybeans. Our findings established a novel methodological framework for pre-symptomatic stress diagnostics while demonstrating the technical feasibility of employing targeted spectral regions (518–690 nm) in field-ready real-time crop surveillance systems. Furthermore, these innovations offer significant potential for advancing precision agriculture in intercropping systems, specifically through refined herbicide application protocols and yield preservation via early-stage phytotoxicity mitigation.

Plasma membrane intrinsic proteins (PIPs), one sub-family of aquaporins (AQPs), are responsible for plant abiotic stress responses. However, little information is currently available about the stress responsiveness of the PIP promoter in vegetable pea. In the present study, one novel promoter of PsPIP2-4 which shared high similarity to the PIP2-type AQPs from other plants, was isolated. Quantitative real-time PCR (qRT-PCR) assays suggested that PsPIP2-4 was predominantly expressed in leaves and abundantly induced by abiotic stress treatments (polyethylene glycol (PEG) 6000, NaCl, and methyl jasmonate (MeJA)). Further, the promoter activity of PsPIP2-4 was verified in transgenic tobacco plants. Beta-glucuronidase (GUS) staining driven by the PsPIP2-4 promoter confirmed that it was mainly detected in the leaves of transgenic seedlings, especially in the guard cells. Exposure of transgenic seedlings to various environmental stimuli proved that the promoter activity of PsPIP2-4 was abundantly strengthened by osmotic, salt, and MeJA stresses. This research provides one stress-inducible promoter enabling targeted gene expression under abiotic stresses and demonstrates its usefulness in the genetic improvement of plant stress resistance.

This study aimed to explore the role of the trehalose-6-phosphate synthase (TPS) gene family in the adaptation of peas to environmental stress. A comprehensive analysis of the PsTPS gene family identified 20 genes with conserved domains and specific chromosomal locations. Phylogenetic analysis delineated evolutionary relationships, while gene structure analysis revealed compositional insights, and motif analysis provided functional insights. Cis-regulatory element identification predicted gene regulation patterns. Tissue-specific and stress-induced expression profiling highlighted eight genes with ubiquitous expression, with PsTPS15 and PsTPS18 displaying elevated expression levels in roots, nodules, and young stems, and PsTPS13 and PsTPS19 expression downregulated in seeds. Transcriptome analysis identified a differential expression of 20 PsTPS genes, highlighting the significance of 14 genes in response to drought and salinity stress. Notably, under drought conditions, the expression of PsTPS4 and PsTPS6 was initially upregulated and then downregulated, whereas that of PsTPS15 and PsTPS19 was downregulated. Salinity stress notably altered the expression of PsTPS4, PsTPS6, and PsTPS19. Taken together, these findings elucidate the regulatory mechanisms of the PsTPS gene family and their potential as genetic targets for enhancing crop stress tolerance.