Everbearing strawberry cultivars provide fruit during the summer–fall period when June-bearing strawberries are unavailable, but their breeding progress has been constrained by complex trait interactions. To characterize segregation patterns and evaluate phenotypic diversity, we developed an F₁ population from a cross between two everbearing cultivars, ‘Charlotte’ and ‘Flamenco’. Twenty selected progenies were evaluated for 30 quantitative traits encompassing vegetative vigor, inflorescence structure, fruit morphology, firmness, and biochemical composition. Substantial variation was observed among lines, with several individuals exceeding parental performance for key traits such as fruit size, soluble solids content, and sucrose accumulation. Principal component analysis revealed three major axes of variation: fruit composition (sugars and acids), vegetative vigor, and fruit size and morphology. K-means clustering grouped the progeny into three phenotypic classes, representing high-sugar, large-fruited, or vigorous growth types. Notably, some lines combined favorable attributes across classes, such as high sweetness and large fruit, indicating the potential to overcome typical trade-offs between yield and quality. These findings provide a practical framework for breeding selection and highlight superior progeny as immediate candidates for clonal advancement or as parents in future crossing. The results also establish a foundation for integrating phenotypic classifications with molecular tools to accelerate the development of high-value everbearing strawberries.
The development of rice seedlings stressed by drought and salt is shown by different morphometric and colorimetric traits. These distinctions can be used to understand the response of plants to challenging conditions. Therefore, this study aimed to assess the efficacy of image-based phenotyping in the early testing of rice plants and observe how the plants respond to both drought and salinity. A stress tolerance index with multivariate analysis was used for the selection of the most important traits. The experiment consisted of 2 factors, namely the degree of environmental stress and rice genotype. Furthermore, the degree of environmental stress comprised normal (NaCl and PEG 0%), drought (10% PEG), salinity (60 mM NaCl), as well as a combination of moderate drought and salinity (5% PEG + 30 mM NaCl). The results showed that both morphometric (area, convex hull, bounding area, perimeter, centermassy) and colorimetric (CIVE, VARI, RGBVI, MGRVI, NDI, GLI, NGRDI) can be used as selection characters.
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Chinese jujube (
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Eight advanced breeding lines of cowpea [
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Poor seed yield remains a great challenge for cowpea production in sub-Sahara Africa and continuous evaluation of available genetic resource to develop high and stable yielding varieties is the panacea to this regional food security conundrum. In this study, 21 cowpea breeding lines were evaluated for phenotypic analysis of seed yield components for two years in a randomized complete block design of 3 replications. All the yield components exhibited significant genotypic variation, while flowering, pod maturity and seed yield traits recorded significant variation for years and its interactions. These cowpeas, which are predominantly early-medium maturing biotypes, exhibited relative phenotypic stability for the yield components across years (seasons) except seed yield, being a final product of complex physiological process. Relationships between flowering/pod maturity and seed size were positive and significant. By contrast, pods/plant, seeds/plant and total seed yield recorded negative correlations with pod maturity. However, seeds/plant and pods/plant are the most contributory components to seed-yield with correlation coefficients of
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Perennial poor fruit-set and variability in tree yield are among major problems of cashew nut production. Thus, development of improved stable genotypes would be a sustainable strategy to address this perpetual problem in order to boost income and livelihood of many smallholder farmers of this important commodity crop. Here, we have applied additive main effect and multiplicative interaction (AMMI) and genotype, genotype by environment (GGE) biplot analysis to a 3-year multi-locational trial data on nine yield component characters of cashew to evaluate phenotypic stability across diverse environments. Variance analysis showed significant variability in the cashew genotypes and strong influence of genotype by environment (GxE) on tree yield as none of the genotypes was stable for any of the yield components across locations. GxE data showed that a substantial portion of the variation was explained by the genotype (highly heritable), accounting for between 10% and 87% of the variation, while the environment accounted for between 0.7% and 37%. Data showed significant higher values of interaction (GxE) than the respective values for environment, and were mostly captured and could be explained by the first principal component axis (IPCA 1) for all the yield component characters. There was an inverse relationship between stability and yield as the best three yielding genotypes (KT_26, IW_222 and IW_31) were found to be the most unstable. Among the yield component tested, hermaphrodite flowers per panicle, nuts per panicle, nuts per tree, nut weight, and tree fruiting efficiency were identified to be critical components for nut yield. Although there was wide variation between the three environments evaluated, the data effectively identified two mega-environments (ME), and two superior genotypes (IW_222 and KT_26) suitable for these two mega-environments. The GxE complex exposes the short-comings of broad recommendations of common agronomic-husbandry technologies across diverse cashew ecologies as each mega-environment would require specific adaptable technologies for optimal plant output. Above all, the data presented here underscore the importance of multi-locational evaluation of genotypes for varietal development in cashew.
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