Backcrosses in a segregating population of Passiflora mediated by morphoagronomic and resistance traits

Santos, Valquíria Oliveira dos; Viana, Alexandre Pío; Preisigke, Sandra da Costa; Santos, Eileen Azevedo

doi:10.1590/1678-4499.20180470

Cited by 9 publications

(5 citation statements)

References 18 publications

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“…Then, destructive and non-destructive data from the backcross M/K//K and F5 samples were used for validating the predicting mode. Such generations were chosen due to their optimal diversity, as they consistently exhibited robust segregation characteristics [60][61][62].…”

Section: Development Of the Fruit Fresh Weight Estimation Modelmentioning

confidence: 99%

Combining Image-Based Phenotyping and Multivariate Analysis to Estimate Fruit Fresh Weight in Segregation Lines of Lowland Tomatoes

Farid,

Anshori,

Rossi

et al. 2024

Agronomy

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The fruit weight is an important guideline for breeders and farmers to increase marketable productions, although conventionally it requires destructive measurements. The combination of image-based phenotyping (IBP) approaches with multivariate analysis has the potential to further improve the line selection based on economical trait, like fruit weight. Therefore, this study aimed to evaluate the potential of image-derived phenotypic traits as proxies for individual fruits weight estimation using multivariate analysis. To this end, an IBP experimentation was carried out on five populations of low-land tomato. Specifically, the Mawar (M; 10 plants), Karina (K; 10 plants), and F2 generation cross (100 lines) samples were used to extract training data for the proposed estimation model, while data derived from M/K//K backcross population (35 lines) and F5 population (50 lines) plants were used for destructive and non-destructive validation, respectively. Several phenotypic traits were extracted from each imaged tomato fruit, including the slice and whole fruit area (FA), round (FR), width (FW), height (FH), and red (RI), green (GI) and blue index (BI), and used as inputs of a genetic- and multivariate-based method for non-destructively predicting its fresh weight (FFW). Based on this research, the whole FA has the greatest potential in predicting tomato FFW regardless to the analyzed cultivar. The relevant model exhibited high power in predicting FFW, as explained by R2-adjusted, R2-deviation and RMSE statistics obtained for calibration (81.30%, 0.20%, 3.14 g, respectively), destructive (69.80%, 0.90%, 4.46 g, respectively) and non-destructive validation (80.20%, 0.50%, 2.12 g, respectively). These results suggest the potential applicability of the proposed IBP approach in guiding field robots or machines for precision harvesting based on non-destructive estimations of fruit weight from image-derived area, thereby enhancing agricultural practices in lowland tomato cultivation.

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Section: Development Of the Fruit Fresh Weight Estimation Modelmentioning

confidence: 99%

Combining Image-Based Phenotyping and Multivariate Analysis to Estimate Fruit Fresh Weight in Segregation Lines of Lowland Tomatoes

Farid,

Anshori,

Rossi

et al. 2024

Agronomy

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“…Resistance genes to CABMV were incorporated from the interspecific cross between cv. UENF Rio Dourado and P. setacea (wild species with resistance allele for CABMV and seed dormancy) (Santos et al 2019, Preisigke et al 2020. However, the seed germination potential was not analyzed after the successive generations of backcrossing and recombination of cv.…”

Section: Introductionmentioning

confidence: 99%

Genetic gain in Passiflora seed traits from recurrent selection among full-sib families

Rodrigues

Vieira

Souza

et al. 2023

Crop Breed. Appl. Biotechnol.

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The germination potential must be considered in the selection of passion fruit genotypes, since vigorous seeds originate seedlings with a higher growth rate, resulting in superior plants with high agronomic performance. This study proposes to estimate genetic parameters and selection gain for seed traits of full-sib families (FSF) of passion fruit under recurrent selection for resistance to the cowpea aphid-borne mosaic virus (CABMV). Physical and physiological seed traits of 86 FSF were evaluated; genetic parameters, genotypic correlations between traits and genetic gains were estimated using four selection indices. There were significant differences and genetic variability between families and positive genetic correlations between variables. The best distribution of genetic gains was obtained by the Mulamba and Mock index, using the heritability coefficient and arbitrary weights. This index selected the best 26 families in terms of seed characteristics to compose the second cycle of recurrent selection for resistance to CABMV.

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“…https://doi.org/10.1590/ 1678-4499.20230063 In this scenario, the passion fruit breeding program at the Universidade Estadual do Norte Fluminense Darcy Ribeiro (UENF) seeks sources of resistance to CABMV to incorporate resistance genes into a passion fruit population (Santos et al 2019, Preisigke et al 2020a, 2020b. After crossing for the introgression of resistance genes and successive generations of backcrossing and recombinations, the program began studies with recurrent selection (Santos et al 2015a, Preisigke et al 2020a, 2020b, Mendes et al 2022.…”

Section: Introductionmentioning

confidence: 99%

Genetic divergence for seed traits in Passiflora full-sib families under recurrent selection for resistance to the cowpea aphid-borne mosaic virus

et al. 2023

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Investigating the physiological potential of seeds and genetic divergence between families is essential to identify promising materials for the generation of improved populations. This study was undertaken to examine the germination potential and estimate genetic divergence between Passiflora full-sib families (FSFs) based on physical and physiological seed traits. The experiment was consisted of 86 FSFs from the first cycle of recurrent selection for resistance to the cowpea aphid-borne mosaic virus. Seeds were evaluated for 19 physical and physiological traits. Dissimilarity estimates were obtained by generalized Mahalanobis distance, and the method unweighted pair group method with arithmetic mean was employed for cluster formation. The FSFs showed high germination potential and seed vigor, with mean of 92.4%, 5.68 e 5.81 cm for germination, germination speed index (GSI) and shoot length of seedlings, respectively. Cluster analysis resulted in four groups formed, being Group I composed by 68 FSF more the control Passiflora edulis. The trait 1,000-seed weight (TSW) was the trait that most contributed to explaining the dissimilarity between families, with 31.9%. The trait GSI (physiological), TSW (physical), as well as traits provided by the GroundEye ® system (CIELab-b, hue, and circumference of seeds), were efficient in determining genetic divergence detected between the families of passion fruit. These traits can be taken as a basis in the selection of genotypes with higher physiological seed quality.

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Backcrosses in a segregating population of Passiflora mediated by morphoagronomic and resistance traits

Cited by 9 publications

References 18 publications

Combining Image-Based Phenotyping and Multivariate Analysis to Estimate Fruit Fresh Weight in Segregation Lines of Lowland Tomatoes

Combining Image-Based Phenotyping and Multivariate Analysis to Estimate Fruit Fresh Weight in Segregation Lines of Lowland Tomatoes

Genetic gain in Passiflora seed traits from recurrent selection among full-sib families

Genetic divergence for seed traits in Passiflora full-sib families under recurrent selection for resistance to the cowpea aphid-borne mosaic virus

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