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作 者:Rushita D.Parmar Vaishali G.Varsani Vijay Parmar Suhas Vyas Dushyant Dudhagara
机构地区:[1]Department of Life Sciences,Bhakta Kavi Narsinh Mehta University,Junagadh,Gujarat,India
出 处:《Oil Crop Science》2024年第2期102-110,共9页中国油料作物学报(英文版)
基 金:Bhakta Kavi Narsinh Mehta University for providing support through the SCORE(Scheme for Concurrent Research Enhancement-2023),Department of Life Sciences,Junagadh.
摘 要:The manuscript explores the complex interplay between groundnut genotypes,salt tolerance and hormonal influence,shedding light on the dynamic responses of three specific groundnut genotypes,KDG-128,TG-37 A and GG-20,to salt treatments and gibberellic acid(GA3).The study encompasses germination,plant growth,total protein content and oil content as key parameters.Through comprehensive analysis,it identifies TG-37 A and KDG-128 as salt-tolerant genotypes,and GG-20 as salt-susceptible genotypes,which highlighting the potential for targeted breeding efforts to develop more resilient groundnut varieties.Moreover,the quantification of protein and oil content under different treatments provides vital data for optimizing nutritional profiles in groundnut cultivars.Principal Component Analysis(PCA) underscores the significance of the first principal component(PC1)in explaining the majority of variance,capturing primary trends and differences in plant length.Analysis of Variance(ANOVA) and hierarchical analysis confirm the presence of statistically significant differences in protein and oil content among the genotypes.Pearson's correlation coefficient matrix analysis reveals strong positive correlations between plant length and protein content,plant length and oil content,and a moderately positive correlation between protein content and oil content.These findings provide valuable insights into groundnut physiology,salt tolerance,and nutritional composition,with implications for future research in sustainable agriculture and crop improvement.
关 键 词:GROUNDNUT Salt tolerance GENOTYPES Salt-hormone interaction Protein and oil content Statistical analysis
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