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Functional mechanisms of drought tolerance in maize through phenotyping and genotyping under well watered and water stressed conditions |
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| Institution: | 1. The Key Laboratory of Plant Cell Engineering and Germplasm Innovation, School of Life Sciences, Shandong University, Shanda South Road 27, Jinan 250100, Shandong, China;2. The State Key Lab of Crop Biology, College of Life Sciences, Shandong Agricultural University, Daizong Street 61, Taian 271018, Shandong, China;3. Department of Resources and Environment, Heze University, Daxue Road 2269, Heze 274000, Shandong, China;1. Department of Biochemistry, NRS Medical College, Kolkata, India;2. Department of Biochemistry, Manipal College of Medical Sciences, Pokhara, Nepal;1. Plant Virology Research Center, College of Agriculture, Shiraz University, Shiraz, Iran;2. Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St. Lucia 4072, QLD, Australia;1. College of Agronomy, Henan University of Science and Technology, Luoyang, Henan Province 471003, China;2. Institute of Plant Protection Research, Henan Academy of Agricultural Sciences, Henan Key Laboratory for Control of Crop Diseases and Insect Pests, IPM Key Laboratory in Southern Part of North China for Ministry of Agriculture, Zhengzhou, Henan Province 450002, China;1. College of Agronomy, Henan University of Science and Technology, Luoyang, Henan Province 471003 China;2. College of Pharmacy, Zhengzhou Railway Vocational & Technical college, Zhengzhou, Henan Province, 451460 China;3. Farmland Irrigation Research Institute, Chinese Academy of Agricultural Sciences, Xinxiang 453002, China |
| Abstract: | Developing tolerant genotypes is crucial for stabilizing maize productivity under drought stress conditions as it is one of the most important abiotic stresses affecting crop yields. Twenty seven genotypes of maize (Zea mays L.) were evaluated for drought tolerance for three seasons under well watered and water stressed conditions to identify interactions amongst various tolerance traits and grain yield as well as their association with SSR markers. The study revealed considerable genetic diversity and significant variations for genotypes, environment and genotype × environment interactions for all the traits. The ranking of genotypes based on drought susceptibility index for morpho-physiological traits was similar to that based on grain yield and principal component analysis. Analysis of trait – trait and trait – yield associations indicated significant positive correlations amongst the water relations traits of relative water content (RWC), leaf water potential and osmotic potential as well as of RWC with grain yield under water stressed condition. Molecular analysis using 40 SSRs revealed 32 as polymorphic and 62 unique alleles were detected across 27 genotypes. Cluster analysis resulted in categorization of the genotypes into five distinct groups which was similar to that using principal component analysis. Based on overall performance across seasons tolerant and susceptible genotypes were identified for eventual utilization in breeding programs as well as for QTL identification. The marker-trait association analysis revealed significant associations between few SSR markers with water relations as well as yield contributing traits under water stressed conditions. These associations highlight the importance of functional mechanisms of intrinsic tolerance and cumulative traits for drought tolerance in maize. |
| Keywords: | Drought tolerance Morpho-physiological traits Genetic diversity SSR markers PCA Correlation Association analysis DSI"} {"#name":"keyword" "$":{"id":"kw0050"} "$$":[{"#name":"text" "_":"drought susceptibility index LWP"} {"#name":"keyword" "$":{"id":"kw0060"} "$$":[{"#name":"text" "_":"leaf water potential PCA"} {"#name":"keyword" "$":{"id":"kw0070"} "$$":[{"#name":"text" "_":"principal component analysis PIC"} {"#name":"keyword" "$":{"id":"kw0080"} "$$":[{"#name":"text" "_":"polymorphism information content QTL"} {"#name":"keyword" "$":{"id":"kw0090"} "$$":[{"#name":"text" "_":"quantitative trait loci RWC"} {"#name":"keyword" "$":{"id":"kw0100"} "$$":[{"#name":"text" "_":"relative water content SAHN"} {"#name":"keyword" "$":{"id":"kw0110"} "$$":[{"#name":"text" "_":"sequential agglomerative hierarchical and nested clustering methods SSR"} {"#name":"keyword" "$":{"id":"kw0120"} "$$":[{"#name":"text" "_":"simple sequence repeat UPGMA"} {"#name":"keyword" "$":{"id":"kw0130"} "$$":[{"#name":"text" "_":"unweighted pair group method using arithmetic means |
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