Authors:A. Etminan, A. Pour-Aboughadareh, R. Mohammadi, L. Shooshtari, M. Yousefiazarkhanian, and H. Moradkhani
In the present study, efficiency of the artificial neural network (ANN) method to identify the best drought tolerance indices was investigated. For this purpose, 25 durum genotypes were evaluated under rainfed and supplemental irrigation environments during two consecutive cropping seasons (2011–2013). The results of combined analysis of variance (ANOVA) revealed that year, environment, genotype and their interaction effects were significant for grain yield. Mean grain yield of the genotypes ranged from 184.93 g plot–1 under rainfed environment to 659.32 g plot–1 under irrigated environment. Based on the ANN results, yield stability index (YSI), harmonic mean (HM) and stress susceptible index (SSI) were identified as the best indices to predict drought-tolerant genotypes. However, mean productivity (MP) followed by geometric mean productivity (GMP) and HM were found to be accurate indices for screening drought tolerant genotypes. In general, our results indicated that genotypes G9, G12, G21, G23 and G24 were identified as more desirable genotypes for cultivation in drought-prone environments. Importantly, these results could provide an evidence that ANN method can play an important role in the selection of drought tolerant genotypes and also could be useful in other biological contexts.
In acid soil, Al is solubilised into a phytotoxic form, Al(H2O)63+ which is known as Al3+. Al toxicity is the primary growth-limiting factor for plants in acid soils. Breeding of rice for Al tolerance are important approach for increasing grain yield in acid soils. In the present endeavour, rice genotypes were screened at seedling stage based on vigour index, root tolerance index and hematoxylin staining in stressed nutrient solutions to select the tolerant genotype(s) against Al toxicity. It was observed that use of different screening indices for Al toxicity tolerant genotypes of rice have given different results. Thus, screening of tolerant genotypes using one index may lead to inappropriate conclusion. Comparing all the selection indices it was found that Radhunipagal and UBKVR-16 were the common genotypes which fallen into tolerant class for every index. Finally genotypes were grouped into different clusters using D2 statistic to find out whether the tolerant genotypes fall into one cluster. Those two Al toxicity tolerance genotypes were grouped into one cluster, which strengthens our findings.
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