Volume 11, Issue 32 (12-2019)                   jcb 2019, 11(32): 100-115 | Back to browse issues page


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RAHI A R, Najafi Zarini H, Ranjbar G, Ghajar Spanlou M. (2019). Evaluation of Tolerance of Some Soybean Genotypes to Drought Stress. jcb. 11(32), 100-115. doi:10.29252/jcb.11.32.100
URL: http://jcb.sanru.ac.ir/article-1-971-en.html
Department of Breeding and Plant Genetics, Sari Agricultural Sciences and Natural Ressoures University
Abstract:   (2752 Views)
     In order to recognize the soybean tolerant genotypes, a greenhouse as factorial experiment was conducted in form of randomized complete block design with three repetition in 2017 in Damavand. The first factor contained 15 soybean genotypes and second factor included two levels of normal irrigation and irrigation disruption in time of podding. The traits included plant height, reproductive branches no., number of leaves, chlorophyll a, chlorophyll b, chlorophyll total, carotenoids, days to flowering, days to fifty percent podding, number of  flowers, dry weight of plant leaves, main stem nodes no, nodes in the, branches no, total dry stem weight, plant dry weight, first pod height of soil, days to harves, total pod no, dry weight of pod, pods length, seed pod no, seeds per plant, harvest index, weigh one hundred seeds and yield per plant. The analysis variance results showed that the reaction of soybean genotypes to conditions of drought stress and lack of stress were different. The genotypes of 1, 4, 10, 14 and 15 represented high yield in both conditions of drought stress and normal conditions. Analysis of phenotypic correlation showed that the seed yield has a positive correlation with seeds per plant, harvest index, total  dry weight of pods, weight dry of plant. Stepwise regression analysis for seed yield showed 99 % of variation of yield, as a dependent variable justified. In the path analysis for grain yield the maximum positive direct effects were related to weight dry of plant and weigh one hundred seeds that showed important characteristics in relation to grain. Principal component analysis used to study the relationship between indices. Two first components could explain more than 85% of variations of indices. Cluster decomposition divided the genotypes into 5 groups and genotypes 1, 9, 10, 14 and 15 were set in one group. These genotypes have good yield in both environments according to the mean.

 
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Type of Study: Research | Subject: General
Received: 2018/05/23 | Revised: 2020/02/2 | Accepted: 2018/09/30 | Published: 2020/01/13

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