Vegetables are a cornerstone of the human diet, and the importance of vegetables for human health and nutrition cannot be understated. Vegetables are susceptible to a number of biotic and abiotic stressors along with the cumulative pressure of climate change. Climate change is a major driver of the abiotic stress in modern-day vegetable production. Vegetable cropping systems must be resilient to climate change, so that production practices can achieve economic profitability and environmental sustainability. Environmental stressors, such as flooding, drought, and extreme temperatures, pose a severe threat to vegetable crop production, and total crop failures are common. Vegetable grafting, a plant surgical technique that is eco-friendly, rapid, and efficient, is currently the best alternative approach to climate change-resilient plant production that addresses these abiotic stressors. In this review, we document the success of this plant propagation technique using a review of vegetable grafting research results published in the scientific literature.
α-amylase is an important enzyme involved in starch degradation to provide energy to the germinating seedling. The present study was conducted to reveal structural and functional evolution of this gene among higher plants. Discounting polyploidy, most plant species showed only a single copy of the gene making multiple isoforms in different tissues and developmental stages. Genomic length of the gene ranged from 1472 bp in wheat to 2369 bp in soybean, and the size variation was mainly due to differences in the number and size of introns. In spite of this variation, the intron phase distribution and insertion sites were mostly conserved. The predicted protein size ranged from 414 amino acid (aa) in soybean to 449aa in Brachypodium. Overall, the protein sequence similarity among orthologs ranged from 56.4 to 97.4 %. Key motifs and domains along with their relative distances were conserved among plants although several species, genera, and class specific motifs were identified. The glycosyl hydrolase superfamily domain length varied from 342aa in soybean to 384aa in maize and sorghum while length of the C-terminal β-sheet domain was highly conserved with 61aa in all monocots and Arabidopsis but was 59aa in soybean and Medicago. Compared to rice, 3D structure of the proteins showed 89.8 to 91.3 % similarity among the monocots and 72.7 to 75.8 % among the dicots. Sequence and relative location of the five key aa required for the ligand binding were highly conserved in all species except rice.
Background: Pigeonpea has remarkable contribution in flourishing the Indian agricultural economy but over the decades, its productivity has remained stagnant. Presence of genetic diversity in breeding population is the key to develop high yielding varieties. Therefore the current study was aimed to explore genetic divergence among pigeonpea genotypes. Methods: A set of 178 pigeonpea germplasm lines were evaluated in randomized block design to assess the genetic divergence and clustering pattern of pigeonpea genotypes. Observations on various yield component traits were recorded. For the estimation of the Fe and Zn content ICP-OES (Perkin Elmer USA) was used. Mahalanobis D2 analysis was carried out to assess the genetic divergence. Result: Wide range of genetic diversity was revealed among lines for eleven traits studied. Mahalanobis D2 analysis grouped all the genotypes into eleven non-overlapping clusters. The inter cluster D2 values indicated that cluster IV and XI (21046.45) were the most diverse and cluster V and cluster VII (60.67) were the less diverse. Out of the eleven characters studied days to maturity, plant height and yield per plot contributed 93.32 per cent of the total divergence. Based on mean performances, cluster XI and cluster II were found to be beneficial for early flowering and early maturity genotypes, cluster V and cluster VII for number of pods per plant and yield per plot, respectively. The highest mean value for grain iron and zinc content was recorded in cluster III rendering simultaneous improvement for these traits. Therefore, trait-wise selection of diverse parents from different clusters would be desirable and beneficial.
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