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The evergreen tree olive (Olea europaea L.) is the only species of the genus Olea that produces edible fruits with high ecological and economic value. This tree species has developed a series of physiochemical mechanisms to tolerate drought stress and grow under adverse climatic environments. One of these mechanisms is photosynthesis activities, so that as yet little information achieved about the relations between olive production and photosynthetic parameters under drought conditions. An experiment was carried out during two consecutive years (2015–2017) to study the response of 20 different olive tree cultivars (Olea europaea L.) to drought stress. Several parameters like net photosynthetic rate (PN), stomatal conductance (GS), transpiration rate (TE), photosynthetic pigments (total chlorophyll, chlorophyll a, b and carotenoid) and fruit yield were measured. The results of combined analysis of variance for fruit yield and other measured traits showed that year, drought treatment, cultivar main effects and their interactions were highly significant. The results indicated that drought stress reduced all traits, however GS (42.80%), PN (37.21%) and TE (37.17%) significantly affected by drought. Lower reduction in photosynthetic performance (PN, GS and TE) in the cultivar T7 compared to other olive cultivars allowed them to maintain better fruit yield. Principal component analysis (PCA) identified two PCs that accounted for 82.04 and 83.27% of the total variation in photosynthetic parameters under optimal and drought stress conditions, respectively. Taken together, mean comparison, relative changes due to drought and biplot analysis revealed that cultivars ‘T7’, ‘Roghani’, ‘Koroneiki’, ‘Korfolia’ and ‘Abou-satl’ displayed better response against drought stress. According to our results, one olive cultivar namely ‘T7’, could be used in olive breeding programs to improve new high yielding cultivars with drought tolerance for use in the drought-prone environments.
In order to evaluate the relationship between traits affecting the seed yield of the garden cress, phenotypic correlations between seed yield and yield components were detected, direct and indirect effects of yield components on yield and its role in the description of diversity were estimated, and the experiment was conducted in a randomized complete block design with three replications in 2017. The ANOVA showed that the difference among accessions was significant for all traits. There was a significant phenotypic correlation between yield and most of the traits. The highest value of phenotypic correlation was obtained between seed yield and the ‘thousand seed weight’ (0.97). The regression analysis showed that the seed yield was highly influenced by the ‘thousand seed weight’, leaf height and the number of seeds per silique of the lateral branches and the main axis. These three traits constituted about 89% of changes in the total yield, while the ‘thousand seed weight’ was the most effective trait that entered the model and explained 51% of the variation. The path analysis of phenotypic correlation showed that the ‘thousand seed weight’ had the greatest direct effect on the yield (7.21). The ‘thousand seed weight’ had a positive indirect impact on other traits as well. As a result of the factor analysis, 3 independent factors explained about 79.33% of the yield variation. These factors consisted of the number of seeds per silique of the lateral branches, the number of seeds per silique of the main axis and the ‘thousand seed weight’.
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