پديد آورندگان :
غديري، عادل دانشگاه فردوسي مشهد - دانشكده كشاورزي , رضواني مقدم، پرويز دانشگاه فردوسي مشهد - دانشكده كشاورزي - گروه زراعت , قرباني، رضا دانشگاه فردوسي مشهد - دانشكده كشاورزي - گروه زراعت , باقري، عبدالرضا دانشگاه فردوسي مشهد - دانشكده كشاورزي - گروه بيوتكنولوژي و بِه نژادي گياهان زراعي , بهشتي، عليرضا مركز تحقيقات كشاورزي و منابع طبيعي استان خراسان رضوي
چكيده لاتين :
IntroductionLegumes such as Pinto Bean (Phaseolus vulgaris L.), in addition to the value of food and proteins production, they are able to fix biological nitrogen and therefore, are desirable for planting in sustainable agricultural systems in order to strengthen and preserve soil fertility. Low input farming systems (LIFS), which are a part of sustainable agricultural systems was defined as a way to optimize the use of ecological inputs and to minimize the use of inputs such as chemical fertilizers and pesticides in every time and every place to reduce the cost of production, reduce pollution of groundwater and surface water, reduce of pesticide residues in food, reduce total risk in agriculture and an increase in short and long term profitability of agriculture. Evaluation and identification of the suitable cropping plant cultivars for planting in low-input agricultural systems has begun three decades ago, in the world. The aim of this study was to identify of pinto bean genotypes suitable for cultivation in low input crop management system and use them in breeding programs and the cultivar release process of this crop.
Material & MethodsIn order to evaluate Pinto bean genotypes (Phaseolus vulgaris L.) in terms of response to low input crop management, 559 Pinto bean genotypes were evaluated using augmented design in both conventional, and low-input crop management conditions. According to grain yield of genotypes in the two conditions, MP, GMP, TOL, STI and SSI were calculated and then, the correlation between the index and the main component analysis was performed. All Statistical analysis, correlation estimates, factor analysis and graphs performed using SPSS software.
Results & DiscussionAccording to correlation between grain yield in optimal and low input conditions (r=0.34**, n=559), it was found that genotype selection based on grain yield in both conditions can identify genotypes with high yield and stable production. The correlation between grain yield in conventional condition and MP, GMP, STI, SSI and TOL was positive and significant. In addition, the grain yield in low input condition had a positive significant correlation with GMP, MP and STI. Negative significant correlation was shown between grain yield in low input condition and SSI and TOL. According to cluster analysis, the bean genotypes were placed in 5 cluster that genotypes in cluster 2, in term of GMP and STI were 76% and 181% higher than overall average and in term of SSI and TOL were 60% and 48.5% lower than overall average, respectively. Therefore, they were selected as the best genotypes for cultivation in low input conditions. Based on the main component analysis on five indexes and YP and YS in evaluated genotypes, it was observed that two main component explained 97.8 percent of the total variation. The first and two principle components explained 61.8% and 35.9% of total variation, respectively. The highest positive factor in the linear combination of the first component was related to Yp, YS, MP, GMP and STI. Therefore, this component was called as yield component and tolerance to low input conditions. Because of high levels of these indicators are favorable, due to the positive and high values of these component, to select genotypes were acted that have a higher grain yield in both conventional and low input conditions. The highest positive factor in the linear combination of second component was related to SSI, TOL and a little Yp and the highest negative factor was related to Ys. So this component was called as sensitive to low input conditions. The genotypes that had lower values of second component had the least sensitive to low input conditions. According to biplot of two main components, genotypes were classified into four groups. Genotypes that were in the A zone, in terms of the tolerance index to low input conditions (MP, GMP and STI) have higher values than average and in terms of the sensitivity index to low input conditions (SSI) have lower values than average so they were most suitable genotypes.
ConclusionAccording to grain yield and tolerance indexes to low in put condition, the group 1 genotypes (Ks-21184, Ks-92021, Ks-21119, Ks-21280, Ks-21461, Ks-21362, Ks-92198, Ks-21671, Ks-21673 and Ks-21236) as the best genotypes for cultivation in low input farming systems (LIFS) were identified and selected.
