2026-04-14T02:28:18Zhttps://recercat.cat/oai/requestoai:recercat.cat:20.500.12327/14032025-10-22T11:12:53Zcom_2072_4428com_2072_4427col_2072_487898
RECERCAT
author
Zingaretti, Laura M.
author
Monfort, Amparo
author
Pérez-Enciso, Miguel
other
Producció Vegetal
group
Genòmica i Biotecnologia
2025-10-22T11:12:53Z
2025-10-22T11:12:53Z
2021-05-12
Zingaretti, Laura M., Amparo Monfort, and Miguel Pérez-Enciso. 2021. "Automatic Fruit Morphology Phenome And Genetic Analysis: An Application In The Octoploid Strawberry". Plant Phenomics 2021: 1-14. doi:10.34133/2021/9812910.
2643-6515
http://hdl.handle.net/20.500.12327/1403
https://doi.org/10.34133/2021/9812910
Automatizing phenotype measurement will decisively contribute to increase plant breeding efficiency. Among phenotypes, morphological traits are relevant in many fruit breeding programs, as appearance influences consumer preference. Often, these traits are manually or semiautomatically obtained. Yet, fruit morphology evaluation can be enhanced using fully automatized procedures and digital images provide a cost-effective opportunity for this purpose. Here, we present an automatized pipeline for comprehensive phenomic and genetic analysis of morphology traits extracted from internal and external strawberry (Fragaria x ananassa) images. The pipeline segments, classifies, and labels the images and extracts conformation features, including linear (area, perimeter, height, width, circularity, shape descriptor, ratio between height and width) and multivariate (Fourier elliptical components and Generalized Procrustes) statistics. Internal color patterns are obtained using an autoencoder to smooth out the image. In addition, we develop a variational autoencoder to automatically detect the most likely number of underlying shapes. Bayesian modeling is employed to estimate both additive and dominance effects for all traits. As expected, conformational traits are clearly heritable. Interestingly, dominance variance is higher than the additive component for most of the traits. Overall, we show that fruit shape and color can be quickly and automatically evaluated and are moderately heritable. Although we study strawberry images, the algorithm can be applied to other fruits, as shown in the GitHub repository.
eng
Attribution 4.0 International
Automatic Fruit Morphology Phenome and Genetic Analysis: An Application in the Octoploid Strawberry
info:eu-repo/semantics/article