Introducing Three-Dimensional Scanning for Phenotyping of Olive Fruits Based on an Extensive Germplasm Survey

ShinyFruit: interactive fruit phenotyping software and its application in blackberry

Introduction

Horticultural plant breeding programs often demand large volumes of phenotypic data to capture visual variation in quality of harvested products. Increasing the throughput potential of phenomic pipelines enables breeders to consider data-hungry molecular breeding strategies such as genome-wide association studies and genomic selection.

Methods

We present an R-based web application called ShinyFruit for image-based phenotyping of size, shape, and color-related qualities in fruits and vegetables. Here, we have demonstrated one potential application for ShinyFruit by comparing its estimates of fruit length, width, and red drupelet reversion (RDR) with ImageJ and analogous manual phenotyping techniques in a population of blackberry cultivars and breeding selections from the University of Arkansas System Division of Agriculture Fruit Breeding Program.

Results

ShinyFruit results shared a strong positive correlation with manual measurements for blackberry length (r = 0.96) and ImageJ estimates of RDR (r = 0.96) and significant, albeit weaker, correlations with manual RDR estimation methods (r = 0.62 - 0.70). Neither phenotyping method detected genotypic differences in blackberry fruit width, suggesting that this trait is unlikely to be heritable in the population observed.

Discussion

It is likely that implementing a treatment to promote RDR expression in future studies might strengthen the documented correlation between phenotyping methods by maximizing genotypic variance. Even so, our analysis has suggested that ShinyFruit provides a viable, open-source solution to efficient phenotyping of size and color in blackberry fruit. The ability for users to adjust analysis settings should also extend its utility to a wide range of fruits and vegetables.

The Status of Genetic Resources and Olive Breeding in Tunisia

The olive tree, an iconic symbol of the Mediterranean basin, is the object of growing international interest in the production of olive oil for the world food market. In Tunisia, which is the fourth-largest producer of olive oil in the world, the production of olives and olive oil is of great socio-economic importance. Cultivation is widespread from north to south, but it is carried out using traditional techniques that results in extremely irregular production levels. To maintain their competitiveness on the international market, Tunisian producers must improve the quality of the oil through breeding plans that enhance the rich genetic heritage that is still not adequately exploited. The objective of this review is to present the state of olive breeding in Tunisia, illustrating the opportunities available for a better use of the rich Tunisian genetic heritage, the challenges it must face, and the need to multiply the efforts for sustainability, even in the light of the challenges posed by climate changes.