Automatic Fruit Morphology Phenome and Genetic Analysis: An Application in the Octoploid Strawberry
Ver/Abrir
Fecha de publicación
2021-05-12ISSN
2643-6515
Resumen
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.
Tipo de documento
Artículo
Versión del documento
Versión publicada
Lengua
English
Materias (CDU)
633 - Cultivos y producciones
Páginas
14
Publicado por
American Association for the Advancement of Science
Publicado en
Plant Phenomics
Citación
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.
Número del acuerdo de la subvención
MINECO/Programa Estatal de fomento de la investigación científica y técnica de excelencia/SEV-2015-0533/ES/ /
MICIU/Programa Estatal de generación del conocimiento y fortalecimiento científico y tecnológico del sistema I+D+I y Programa Estatal de I+D+I orientada a los retos de la sociedad/CEX2019-000902-S/ES/ /
MINECO/Programa Estatal de I+D+I orientada a los retos de la sociedad/AGL2016-78709-R/ES/UTILIZACION DE SECUENCIAS COMPLETAS PARA LA MEJORA DE ESPECIES DOMESTICAS/
MICIU/Programa Estatal de generación del conocimiento y fortalecimiento científico y tecnológico del sistema I+D+I y Programa Estatal de I+D+I orientada a los retos de la sociedad/PID2019-108829RB-I00/ES/Deep is beautiful: Deep learning applications to genomic prediction/
Program
Genòmica i Biotecnologia
Este ítem aparece en la(s) siguiente(s) colección(ones)
- ARTICLES CIENTÍFICS [2829]
Excepto si se señala otra cosa, la licencia del ítem se describe como http://creativecommons.org/licenses/by/4.0/