Drought is a serious factor limiting rice production, and it leads to huge economic losses. Considering the current and projected global food demand, increasing productivity of drought-prone crops has become critical. In order to achieve the production target, rice drought-tolerant germplasm resources are an important prerequisite for the development of water-saving cultivation. Through multi-indicator measurement, the stress effect of drought on rice was clarified and a preliminary drought resistance identification index system was established based on the response of plant the germination, seedling and adult stages of rice and materials suitable for dry cultivation were screened. The results showed that relative root length, relative root weight and relative shoot weight were most affected by drought stress at the germination stage, while root length and root dry weight were positively correlated with the drought survival proportion at the seedling stage; high net photosynthetic rates and antioxidant enzyme activities are maintained in the late period in strongly drought-tolerant varieties. In this experiment, two drought-resistant varieties were screened, there was a high consistency in the screening of drought-tolerant varieties at the germination and seedling stages, with their joint screening showing the same performance as at the adult stage. The drought-resistant varieties at the adult stage can promote seed filling and ensure group yield by prolonging photosynthesis time and enhancing antioxidant enzyme activity, which can provide theoretical support and material basis for future variety screening and evaluation, as well as rice dry-crop cultivation.

Food is the paramount necessity of the people. With the progress of society and the improvement of social welfare system, the living standards of people all over the world are constantly improving. The development of medical industry improves people’s health level constantly, and the world population is constantly climbing to a new peak. With the continuous development of deep learning in recent years, its advantages are constantly displayed, especially in the aspect of image recognition and processing, it drives into the distance. Thanks to the superiority of deep learning in image processing, the combination of remote sensing images and deep learning has attracted more attention. To simulate the four key factors of rice yield, this article tries a regression model with a combination of various characteristic independent variables. In this article, the selection of the best linear and nonlinear regression models is discussed, the prediction performance and significance of each regression model are analyzed, and some thoughts are given on estimation of actual rice yield.

Salt stress is an important environmental factor affecting crop growth and development. One of the important ways to improve the salt tolerance of rice is to identify new salt-tolerance genes, reveal possible mechanisms, and apply them to the creation of new germplasm and the breeding of new varieties. In this study, the salt-sensitive japonica variety Tong 35 (T35) and salt-tolerant japonica variety Ji Nongda 709 (JND709) were used. Salt stress treatment with a 150 mmol/L NaCl solution (the control group was tested without salt stress treatment simultaneously) was continued until the test material was collected after the rice germination period. Twelve cDNA libraries were constructed, and 5 comparator groups were established for transcriptome sequencing. On average, 9.57G of raw sequencing data were generated per sample, with alignment to the reference genome above 96.88% and alignment to guanine-cytosine (GC) content above 53.86%. A total of 16,829 differentially expressed genes were present in the five comparison groups, of which 2390 genes were specifically expressed in T35 (category 1), 3306 genes were specifically expressed in JND709 (category 2), and 1708 genes were differentially expressed in both breeds (category 3). Differentially expressed genes were subjected to gene ontology (GO), functional enrichment analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, which revealed that these genes belonged to three main classes: molecular function, cellular components, and biological processes. KEGG pathway analysis showed that the significantly enriched pathways for these differentially expressed genes included phenylpropane biosynthesis, phytohormone signaling, and the interaction of plants with pathogens. In this study, we provided a reference for studying the molecular mechanism underlying salt tolerance during germination.

Research has long been associated with human life. In the effort to make a living, many experts who have contributed to the modernization of traditional research methods by conducting various research activities. In this process, professionals, from farmers to senior researchers, have done their part by developing plants that can tolerate or resist to disease. The growing population, climate change and plant disease are having a devastating effect on food security. In particular, it is essential to increase food production by producing high yielding crops of good quality, that may ensure food security. Recently, different gene- editing technologies have been developed. These techniques have been applied in many research fields and their development has provided economic benefits to farmers. Agrobacterium-mediated and biolistic methods are very important techniques for transforming genetic materials in plants. Genome- editing technologies are recent and highly applied in plant research to improve genes associated with yield, disease resistance and drought resistance. For example, Zinc-finger Nucleases (ZFNS), Transcription Activator-like Effector Nucleases (TALEN), and Clustered Regularly Interspaced Short Palindromic Repeats system (CRISPR/ Cas9) methods are now widely applied by researchers and are playing a positive role in increasing production and productivity. Of the gene- editing technology, CRISPR/ Cas9 is widely applied in plant breeding programme as it is easy to use and cost-effective. In this review, we mainly focus on peanut plant, which is an important oil-bearing allotetraploid crop. Therefore, peanut gene editing-technology could increase the oleic acid content in edible peanut oil. Thus, genome editing and gene transformation technologies are extensively explored in this review.

Genome editing-mediated haploid inducer systems (HISs) present a promising strategy for enhancing breeding efficiency in legume crops, which are vital for sustainable agriculture due to their nutritional benefits and ability to fix nitrogen. Traditional legume breeding is often slow and complicated by the complexity of legumes’ genomes and the challenges associated with tissue culture. Recent advancements have broadened the applicability of HISs in legume crops, facilitating a reduction in the duration of the breeding cycle. By integrating genome editing technology with haploid breeding systems, researchers can achieve precise genetic modifications and rapidly produce homozygous lines, thereby significantly accelerating the development of desired traits. This review explores the current status and future prospects of genome editing-mediated HISs in legumes, emphasizing the mechanisms of haploid induction; recent breakthroughs; and existing technical challenges. Furthermore, we highlight the necessity for additional research to optimize these systems across various legume species, which has the potential to greatly enhance breeding efficiency and contribute to the sustainability of legume production.

Peanut, with high oil content, has been a major oil and food crop globally. The compositions of the fatty acids are the common factors in determining the oil quality. In the present study, an F2 segregated population with 140 individuals derived from the cross of Weihua8 (a cultivar) and 12L49 (a line with high oleic acid concentration) was used to construct a genetic map and conduct QTL mapping analysis. A total of 103 polymorphic SSR primers were utilized for genotyping the RILs and finally generating the SSR loci. Within the 103 SSR loci, a genetic linkage map, covering a total length of 3592.35 cM of the whole peanut genome, was constructed. Based on the genetic map, sixteen QTLs located on nine linkage groups related to peanut fatty acids were finally identified. Among them, four QTLs were detected associated with various traits simultaneously, which showed genetic stability in relation to fatty acids of peanut. Except for the QTLs for oleic acid, linoleic acid, and linolenic acid, three novel QTLs for arachidic acid and behenic acid were also detected. These QTLs might be helpful for further fine mapping analysis and marker-assisted selection of fatty acids in peanut.