RODRIGUEZ Gustavo Ruben
LocAnalyzer : A computer vision method to count locules in tomato fruits
SPETALE, FLAVIO E.; MURILLO, JAVIER; VAZQUEZ, DANA V.; CACCHIARELLI, PAOLO; RODRÍGUEZ, GUSTAVO R.; TAPIA, ELIZABETH
COMPUTERS AND ELETRONICS IN AGRICULTURE
ELSEVIER SCI LTD
Año: 2020 vol. 173
Fruit production represents an important economic resource for many countries. The size and shape of fruits are crucial in production systems because they aﬀect the market value. Particularly, in tomatoes (Solanum lycopersicum), the number of seed-containing cavities within each fruit, called locules, aﬀects these attributes. The number of locules is also relevant for genotype-phenotype association studies designed to accelerate tomato breeding programs. Traditionally, the determination of the number of locules was performed through a visual inspection ofa crosssectionofthe fruit,a laborious, time-consuming, and highlysubjective task. Inthiswork,an automatic computer vision method for the identiﬁcation and counting of the number of locules in tomato fruit images, called LocAnalyzer, is presented. The aim of LocAnalyzer is to speed up the processing time and reduce the subjectivity relative to the traditional manual approach for locule counting. The method was tested on two real tomato datasets. Promising results in terms of accuracy, precision, and recall measures were obtained, suggesting the potential usefulness of the approachfor the development ofa tool for the automatic measurement of other internal tomato attributes. Additionally, an experiment comparing the capacity of domain experts and LocAnalyzer in the identiﬁcation of the number of locules was performed. The fact that expert-LocAnalyzer intergroup dispersion is smaller than expert-expert dispersion suggests that LocAnalyzer could be used as a gold standard for counting the number of locules. The proposed method, which is freely available, was implemented in the R programming language, and a web-based application was developed for online tests.