Characterization of New Salt-Tolerant Rice Genotypes with Superior Agronomical and Cooking Traits

Abstract

Soil salinity is one of the major constraints affecting rice production worldwide. Goal of this research was evaluation of salt tolerance of new mutant rice germplasm and characterization of new salttolerant mutant rice promising lines with superior qualitative and quantitative traits. Salt tolerance of 56 promising mutant rice lines and 8 commercial and standard cultivars was investigated on standard evaluation scale of IRRI in an Augmented Design in salt affected soils of a rice farm with EC 6.5 dSm-1 in Pirbazar region of Rasht, Guilan province of Iran. Then, yield and yield components of 13 selective salt-tolerant promising lines were evaluated in a three replicated randomized complete block design in the same farm in the second year. Yield and yield components and some cooking parameters of these genotypes were analyzed. Mean analysis, principal component factor and biplot analysis of traits related to yield of studied genotypes under salt stress represented that promising line HM5-250-42-1-E (M12) was the most salt-tolerant genotype. The promising line produced 80% higher paddy yield than its famous parental landrace Hashemi in salt affected soils. Also, this promising line had some superior cooking parameters than other genotypes even the most famous Iranian high-quality landraces Hashemi and Tarom Mahalli. It seems that promising line M12 (HM5-250-42-1-E) is an ideal option for development of rice cultivation and production particularly in regions that are faced with salinity problem.

Evaluating the performance of diverse wheat genotypes under arid climatic conditions

“…The wheat varieties of cluster-1 viz., FSD-08, Ujala-16, Fakhr-e-Bhakhar-19 and Akbar-19 proved most suitable for Layyah conditions in Pakistan and to have the highest values for yield. Cluster analysis is a useful tool for choosing high-yielding wheat varieties(Hallajian et al, 2020;Kamran et al, 2020;Khan et al, 2021). A principal component analysis was performed, which represented 95% of the total variation in the data (Al-Naggar et al, 2020; Mohi-Ud-Din et al, 2021).…”