Phenotypic diversity and alternative methods for characterization and prediction of pulp yield in passion fruit (Passiflora spp.) germplasm

The present study provides an assessment of the genetic variability of different genotypes of Passiflora using physical and chemical descriptors and digital image analysis to quantify leaf, flower and fruit coloration as well as to develop and validate mathematical models for the prediction of passion fruit pulp weight without seeds by regression analysis. A total of 132 Passiflora genotypes belonging to different species were evaluated. Eleven quantitative physical and chemical descriptors were submitted to principal component and cluster analysis. The coloration was determined through RGB color space by digital images analysis. The equations were developed through multiple linear regression and cross-validation was used to validate the models. The first principal component (50.6% of total variance) was associated with fruit weight, diameter and length and peel weight, while the second (22.4%) was associated with fruit weight, fruit length, peel weight, peel thickness, soluble solids, fruit length/fruit diameter ratio and fruit length and diameter. Physical and chemical descriptors showed significant diversity among genotypes. In the cluster analysis, the genotypes BGP007 and BGP009 were most closely related, while BGP349 and BGP177 were distinct. The analysis of coloration using digital images allowed detecting greater variability in the color of leaves, flowers, fruits, and pulp. The analysis of digital images is a practical method for ascertaining the color of plant parts in the field or laboratory. The high phenotypic diversity detected in the present study can be used in passion fruit breeding programs through hybridizations. Regression analysis of physical traits revealed five models that could be used to estimate the pulp weight in two equations (13 and 15), which showed the highest R2 values and lowest RMSE and MAE. This model can be reliably adopted for estimation of the pulp weight without seeds of passion fruits (P. edulis Sims).

Automated summary

The study assessed the genetic variability of different genotypes of Passiflora using physical and chemical descriptors and digital image analysis, developed mathematical models for predicting passion fruit pulp weight, and found significant diversity among genotypes. Digital image analysis proved to be a practical method for detecting color variability in plant parts.