Drought is considered a major threat to rice production. This study aimed to determine the effects of drought stress on the estimates of heterosis and the combining ability of rice genotypes for the number of days to 50% heading, plant height, number of panicles per plant, panicle length, number of filled grains per panicle, and grain yield per plant. Field experiments were conducted at the Rice Research and Training Center, Kafr El Sheikh, Egypt, during the rice-growing season in 2018 and 2019. Eight rice genotypes (Giza178, Giza179, Sakha106, Sakha107, Sakha108, WAB1573, NERICA4, and IET1444) were crossed in a half-diallel cross in the rice-growing season in 2018, which yielded a wide range of variability in numerous agronomic traits and drought tolerance measurements. In 2019, these parents and their 28 F1 crosses were produced by employing a three-replication randomized complete block design under normal and water stress conditions. The results showed remarkable differences across the studied genotypes under normal and water stress conditions. Under both conditions, Sakha107 was the best general combiner for earliness and short stature. Giza179 and Sakha108 were the best general combiners for grain yield per plant and one or more of its characteristics. Furthermore, in both normal and water stress conditions, Giza179 exhibited the highest general combining ability effects for all attributes that were evaluated. Under normal and water stress conditions, the Giza179 × Sakha107 cross demonstrated substantial and desirable specific combining ability effects on all the examined traits, which suggested that it could be considered for use in rice hybrid breeding programs. Therefore, we recommend that these vital indirect selection criteria to be considered for improving rice grain yield under drought conditions.
This work was carried out to select cotton genotypes adapted to semi-arid climate conditions cultivated under irrigation for high yields and the standards of the fiber quality properties required by the textile industry. Also to determine the predicted and realized gains from different selection indices to improve some economic characters under water stress conditions. Except for lint percentage and Pressley index, F4 generation reduced PCV and GCV values for all studied characters due to reduction in genetic variability and heterozygosity due to different selection procedures that exhausted a significant part of variability. Except for fiber length and micronaire reading, mean performance in the F4 generation was revealed to be higher than those in the F3 generation for all studied characters. However, micronaire reading was lower (desirable) in F4 than F3 generation. Generally, genotypic correlations were higher than phenotypic correlations. Direct selection for lint index (Ped.3) was the most efficient in improving lint cotton yield/plant and bolls/plant. However, the multiplicative index involving all studied characters (I.5) exhibited the highest values for boll weight. Also, the Ped.2 index (direct selection for lint percentage) proved to be the most efficient in improving seed and lint indexes. Direct selection for lint cotton yield/plant (Ped.1) could produce the highest desirable values for lint percentage and seed per boll with a relatively reasonable yield. A selection index involving yield and its components (I.3) is recommended in improving uniformity index, fiber strength, and micronaire reading. The superior five families released from these indices in F4 generation exceeded the better parent for lint cotton yield/plant, bolls/plant, boll weight, seeds/boll, lint index, and reasonable fiber traits. These families could be continued to further generations as breeding material for developing water deficit tolerant genotypes.
Rice is a major staple food crop all over the world. Recent climate change trends forecast an increase in drought severity, necessitating the creation of novel drought-tolerant rice cultivars in order to continue rice production in this ecosystem. This study was carried out at the experimental farm of the rice research and training center (RRTC) using the randomized complete block design (RCBD) to assess the impact of water scarcity on eight rice varieties by identifying differences in physiological and biochemical responses among drought-sensitive and resistant rice varieties, in addition applying two PCR-based molecular marker systems ISSR and SCoT to assess the genetic diversity among the studied rice varieties. The results revealed that, Water shortage stress significantly reduced relative water content, total chlorophyll content, grain yield, and yield characteristics. while, it significantly raised proline content and antioxidant enzyme activity (CAT, APX, and SOD). The combined analysis of variance demonstrated that the mean squares for environments, varieties, and their interaction were highly significant for all investigated traits, suggesting that the germplasm used in the study had significant genetic diversity from one environment (normal irrigation) to another (water deficit) and could rank differently in both of them. Mean performance data showed that, Puebla and Hispagran varieties were selected as the most favourable varieties for most physiological and biochemical parameters studied, as well as yield traits which recorded the highest desirable values under both irrigation treatments. They were recommended for use in rice hybrid breeding programmes for water scarcity tolerance. Genetic Similarity and Cluster Analysis revealed that, the both molecular markers exhibited comparable genetic diversity values but a higher level of polymorphism was represented by ISSR. This indicates the high efficiency of both markers in discriminating the tested varieties. The dendrogram generated by ISSR and SCoT markers combined data divided the varieties into two major clusters. Cluster I consisted of the genotype Sakha 106. Cluster II retained seven varieties, which were further divided into two sub-clusters; Sakha 101, Sakha 105, Sakha 106, Sakha 107 constituted the first subgroup, while Giza 177, Hispagran, and Puebla formed the second one.
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