Methyl jasmonate (MJ) is an important plant growth regulator, involved in plant defense against abiotic stresses, however its possible function in response to metal stress is poorly understood. In the present study, the effect of MJ on physiological and biochemical changes of the plants exposed to arsenic (As) stress were investigated in two Brassica napus L. cultivars (ZS 758 – a black seed type, and Zheda 622 – a yellow seed type). The As treatment at 200 µM was more phytotoxic, however its combined application with MJ resulted in significant increase in leaf chlorophyll fluorescence, biomass production and reduced malondialdehyde content compared with As stressed plants. The application of MJ minimized the oxidative stress, as revealed via a lower level of reactive oxygen species (ROS) synthesis (H2O2 and OH-) in leaves and the maintenance of high redox states of glutathione and ascorbate. Enhanced enzymatic activities and gene expression of important antioxidants (SOD, APX, CAT, POD), secondary metabolites (PAL, PPO, CAD) and induction of lypoxygenase gene suggest that MJ plays an effective role in the regulation of multiple transcriptional pathways which were involved in oxidative stress responses. The content of As was higher in yellow seeded plants (cv. Zheda 622) as compared to black seeded plants (ZS 758). The application of MJ significantly reduced the As content in leaves and roots of both cultivars. Findings of the present study reveal that MJ improves ROS scavenging through enhanced antioxidant defense system, secondary metabolite and reduced As contents in both the cultivars.

Rapeseed is a significant oil crop, and the size and length of its pods affect its productivity. However, manually counting the number of rapeseed pods and measuring the length, width, and area of the pod takes time and effort, especially when there are hundreds of rapeseed resources to be assessed. This work created two state-of-the-art deep learning-based methods to identify rapeseed pods and related pod attributes, which are then implemented in rapeseed pots to improve the accuracy of the rapeseed yield estimate. One of these methods is YOLO v8, and the other is the two-stage model Mask R-CNN based on the framework Detectron2. The YOLO v8n model and the Mask R-CNN model with a Resnet101 backbone in Detectron2 both achieve precision rates exceeding 90%. The recognition results demonstrated that both models perform well when graphic images of rapeseed pods are segmented. In light of this, we developed a coin-based approach for estimating the size of rapeseed pods and tested it on a test dataset made up of nine different species of Brassica napus and one of Brassica campestris L. The correlation coefficients between manual measurement and machine vision measurement of length and width were calculated using statistical methods. The length regression coefficient of both methods was 0.991, and the width regression coefficient was 0.989. In conclusion, for the first time, we utilized deep learning techniques to identify the characteristics of rapeseed pods while concurrently establishing a dataset for rapeseed pods. Our suggested approaches were successful in segmenting and counting rapeseed pods precisely. Our approach offers breeders an effective strategy for digitally analyzing phenotypes and automating the identification and screening process, not only in rapeseed germplasm resources but also in leguminous plants, like soybeans that possess pods.

Cyclophilins, a type of peptidyl-prolyl cis-trans isomerase, function as important molecular chaperones in a series of biological processes. However, the expression pattern and signal transduction pathway of cyclophilins are still unclear. Here, we showed that the promoter of OsCYP2 could function as a tissue-specific promoter by GUS staining. Moreover, we found that the promoter sequence contained not only core elements but also inducible elements. Then, the ABA-responsive element was used for cDNA library screening, and the transcription factor MYC2-like was identified by a yeast one-hybrid assay and confirmed through an electrophoretic mobility shift assay. Furthermore, the relative expression showed that MYC2-like was induced by abscisic acid. In addition, MYC2-like overexpression enhanced salt tolerance in transformants and partially restored the cyp2-RNAi line. In summary, we explored a novel transcriptional signal mediated by MYC2-like, a potential regulator of salt stress-related physiological processes in rice.

Soybean, a globally significant and versatile crop, serves as a vital source of both oil and protein. However, environmental factors such as soil salinization pose substantial challenges to its cultivation, adversely affecting both yield and quality. Enhancing the salt tolerance of soybeans can mitigate yield losses and promote the development of the soybean industry. Members of the plant-specific transcription factor family NAC play crucial roles in plant adaptation to abiotic stress conditions. In this study, we screened the soybean GmNAC family genes potentially involved in the salt stress response and identified 18 GmNAC genes that may function during the early stages of salt stress. Among these, the GmNAC035 gene exhibited a rapid increase in expression within one hour of salt treatment, with its expression being induced by abscisic acid (ABA) and methyl jasmonate (MeJA), suggesting its significant role in the soybean salt stress response. We further elucidated the role of GmNAC035 in soybean salt tolerance. GmNAC035, a nuclear-localized transcriptional activator, enhances salt tolerance when overexpressed in Arabidopsis, reducing oxidative damage and boosting the expression of stress-responsive genes. It achieves this by regulating key stress response pathways, including the SOS pathway, calcium signaling, and ABA signaling. These findings highlight the potential of GmNAC035 as a genetic engineering target to improve crop salt tolerance.