Identification of arsenic-tolerant varieties and candidate genes of tolerance in spring wheat (Triticum aestivum L.)

Metabolomics profiling reveals the detoxification and tolerance behavior of two bread wheat (Triticum aestivum L.) varieties under arsenate stress

The present study conducted metabolomics profiling (targeted and untargeted) in the roots of two wheat varieties (BARANI-70 and NARC-09) under arsenate stress in a hydroponic experiment. The findings indicated a better growth response of BARANI-70 compared to the NARC-09. From amino acid profiling, a total of 26 amino acids (AAs) were quantified in roots. BARANI-70 showed higher induction of stress-responsive AAs compared to the NARC-09. From untargeted metabolomics, a total of 136 metabolites were identified: AAs, fatty acids, purines, carnitines, LysoPCs, and others. The KEGG pathway identified pathways such as linoleic acid metabolism, TCA cycle, glutathione metabolism, and aminoacyl-tRNA biosynthesis that were regulated to improve the defense of tolerant variety. BARANI-70 emerged as a tolerant variety based on the psychological response, As accumulation, and behavior of stress-responsive metabolites. This study should facilitate the breeding of low-As accumulating wheat varieties for future application to ensure sustainable production and food safety.

Multiomics Explore the Detoxification Mechanism of Nanoselenium and Melatonin on Bensulfuron Methyl in Wheat Plants

Combining nanoselenium (nano-Se) and melatonin (MT) was more effective than treatment alone against abiotic stress. However, their combined application mitigated the toxic effects of bensulfuron methyl, and enhanced wheat growth and metabolism has not been studied. Metabolomics and proteomics revealed that combining nano-Se and MT markedly activated phenylpropanoid biosynthesis pathways, elevating the flavonoid (quercetin by 33.5 and 39.8%) and phenolic acid (vanillic acid by 38.8 and 48.7%) levels in leaves and roots of wheat plants. Interstingly, beneficial rhizosphere bacteria in their combination increased (Oxalobacteraceae, Nocardioidaceae, and Xanthomonadaceae), which positively correlated with the enhancement of soil urease and fluorescein diacetate enzyme activity (27.0 and 26.9%) and the allelopathic substance levels. To summarize, nano-Se and MT mitigate the adverse effects of bensulfuron methyl by facilitating interactions between the phenylpropane metabolism of the plant and the beneficial microbial community. The findings provide a theoretical basis for using nano-Se and MT to remediate herbicide-contaminated soil.

Arsenic accumulation pattern in water-soil-rice systems: A study of tolerance mechanisms and associated health risks

Regardless of the daunting challenge of arsenic (As) contamination in Pakistan, literature on tolerance and responsible factors in paddy fields remain elusive. In this regard, we aimed to explore physiochemical factors responsible for As availability in water-soil-rice systems. The study highlighted rice defense mechanisms to mitigate As toxicity on growth and yield. In the present study, basmati rice samples were collected along with irrigation and soil samples from control (<10 μg/L), low (11-25 μg/L), medium (26-100 μg/L), and high (>100 μg/L) contaminated regions. Oxidative stress markers (MDA and H2O2) and antioxidant enzymatic assays (SOD, CAT, POD, APX) were measured by spectrophotometer. The Durov diagram was constructed by using Grapher software to identify prevalent water types in irrigation wells. Total As was measured in water, soil, and rice tissues by hydride generation-atomic absorption spectroscopy (HG-AAS). The Durov diagram showed that the majority of irrigation water was Ca-Mg-Cl type. Furthermore, the FTIR analysis identified different organic compounds, i.e., OH, CC, CI, and CBr, particularly in soil from high regions. The results indicated higher accumulation and translocation of As in the water-soil-rice system from a high region compared to control and other regions. Phenotypic traits, i.e., grain yield, biological yield, chlorophyll, and root parameters were significantly impacted under high As-contaminated region. A concentration-dependent increase was indicated in oxidative stress and antioxidant activities except for APX. Risk assessment indicated a higher hazard quotient (1.09) and carcinogenic risk (5.0 × 10-03) due to grain consumption in high As-contaminated regions. The present study emphasized the need for strict regulations and policies to mitigate As calamity at the local level and protect human health.

SCGNet: efficient sparsely connected group convolution network for wheat grains classification

Introduction

Efficient and accurate varietal classification of wheat grains is crucial for maintaining varietal purity and reducing susceptibility to pests and diseases, thereby enhancing crop yield. Traditional manual and machine learning methods for wheat grain identification often suffer from inefficiencies and the use of large models. In this study, we propose a novel classification and recognition model called SCGNet, designed for rapid and efficient wheat grain classification.

Methods

Specifically, our proposed model incorporates several modules that enhance information exchange and feature multiplexing between group convolutions. This mechanism enables the network to gather feature information from each subgroup of the previous layer, facilitating effective utilization of upper-layer features. Additionally, we introduce sparsity in channel connections between groups to further reduce computational complexity without compromising accuracy. Furthermore, we design a novel classification output layer based on 3-D convolution, replacing the traditional maximum pooling layer and fully connected layer in conventional convolutional neural networks (CNNs). This modification results in more efficient classification output generation.

Results

We conduct extensive experiments using a curated wheat grain dataset, demonstrating the superior performance of our proposed method. Our approach achieves an impressive accuracy of 99.56%, precision of 99.59%, recall of 99.55%, and an F 1-score of 99.57%.

Discussion

Notably, our method also exhibits the lowest number of Floating-Point Operations (FLOPs) and the number of parameters, making it a highly efficient solution for wheat grains classification.

Phenomic profiling to reveal tolerance mechanisms and regulation of ascorbate-glutathione cycle in wheat varieties (Triticum aestivum L.) under arsenic stress

The potential of arsenic (As) tolerant and sensitive varieties of wheat (Triticum aestivum L.) has yet to be explored despite of alarming situation of arsenic toxicity. To fill this gap, the study aimed to explore the role of antioxidants, phytochelatins, and ascorbate-glutathione for As tolerance in wheat. A total of eight varieties were exposed to different arsenate treatments (0, 1, 5, 10, 50, 100, 200, 500, 1000, 2000, and 10,000 μM) initially to screen effective treatment as well as contrasting varieties via Weibull distribution frequency for further analysis. The Weibull analysis found 200 μM as the most effective treatment in the present study. Selected varieties were analyzed for accumulation of total As and As speciation, oxidative stress (malondialdehyde, hydrogen peroxide), antioxidants (superoxide dismutase, catalase, peroxidase), phytochelatins, and ascorbate-glutathione cycle (glutathione-S-transferase, glutathione reductase, glutathione peroxidase, ascorbate peroxidase). Tolerant varieties showed less accumulation and translocation of total As, arsenate, and arsenite to the shoots compared with sensitive varieties under 200 μM treatment. Low concentration in tolerant varieties correlated with better growth and development response. Tolerant varieties showed higher induction of metabolites (glutathione, phytochelatins) compared to sensitive ones. Furthermore, tolerant varieties showed better performance of antioxidant and ascorbate-glutathione cycle enzymes in response to As exposure. The findings of the present study provided great insight into the wheat tolerance mechanism upon As exposure between contrasting varieties.