RT info:eu-repo/semantics/article
T1 A Computer Vision‐Based Methodology to Estimate Fruit Colour Diversity in Ornamental Pepper (Capsicum spp.)
A1 Santos, Marcos Bruno da Costa
A1 Melo, Raylson de Sá
A1 Sousa, Victor Eduardo de Carvalho
A1 Medeiros, Artur Mendes
A1 Pessoa, Angela M. dos S.
A1 Silva, Silvokleio da Costa
A1 Nascimento, Antonia Maiara Marques do
A1 Barroso, Priscila Alves
K1 Breeding programs
K1 Genetic diversity
K1 Image processing
K1 Ornamental plants
K1 Phenotyping
K1 Principal component analisys
K1 Biotecnología agraria
K1 Agricultural biotechnology
K1 Ingeniería Agrícola
K1 Agricultural engineering
AB Fruit colour diversity within different ripening stages confers ornamental value for pepper plants. Using images can be helpful in analysing the fruit colour-related genetic diversity and enable selecting accessions for ornamental purposes by avoiding subjectiveness. This study aimed to evaluate the phenotypic diversity among accessions of ornamental pepper using image processing techniques to identify fruit colours. Photos from 40 fruits from each of 12 accessions were captured by a camera from a smartphone. Separate channels and colour indices were extracted from the images to analyse the accessions using both dendrogram and principal components analysis. Dendrogram analysis allowed separating accessions with predominance of dark fruits from those whose fruits showed lighter and more vivid colours, with a cophenetic correlation coefficient of 0.811. The VARI and NGRDI vegetation indices were efficient in discriminating fruits with a predominance of green colour, and the BGI could be used to discriminate accessions with predominantly reddish-brown fruits. The proposed method can be used in small-scale breeding programs for accurately assessing the development of varieties regarding their fruit colour diversity.
PB Wiley
SN 0179-9541
YR 2024
FD 2024-11
LK http://hdl.handle.net/10259/9787
UL http://hdl.handle.net/10259/9787
LA eng
NO We would like to acknowledge the financial support provided by theNational Council for Scientific and Technological Development–CNPQ(408444/2021-5). We also thank the Federal University of Piaui andthe Research Group on Statistics and Plant Breeding (NPE 3M) for theirvaluable contribution to this study.
DS Repositorio Institucional de la Universidad de Burgos
RD 22-dic-2024