title: GiNA, an Efficient and High-Throughput Software for Horticultural Phenotyping.
abstract: Traditional methods for trait phenotyping have been a bottleneck for research in many crop species due to their intensive labor, high cost, complex implementation, lack of reproducibility and propensity to subjective bias. Recently, multiple high-throughput phenotyping platforms have been developed, but most of them are expensive, species-dependent, complex to use, and available only for major crops. To overcome such limitations, we present the open-source software GiNA, which is a simple and free tool for measuring horticultural traits such as shape- and color-related parameters of fruits, vegetables, and seeds. GiNA is multiplatform software available in both R and MATLAB® programming languages and uses conventional images from digital cameras with minimal requirements. It can process up to 11 different horticultural morphological traits such as length, width, two-dimensional area, volume, projected skin, surface area, RGB color, among other parameters. Different validation tests produced highly consistent results under different lighting conditions and camera setups making GiNA a very reliable platform for high-throughput phenotyping. In addition, five-fold cross validation between manually generated and GiNA measurements for length and width in cranberry fruits were 0.97 and 0.92. In addition, the same strategy yielded prediction accuracies above 0.83 for color estimates produced from images of cranberries analyzed with GiNA compared to total anthocyanin content (TAcy) of the same fruits measured with the standard methodology of the industry. Our platform provides a scalable, easy-to-use and affordable tool for massive acquisition of phenotypic data of fruits, seeds, and vegetables.
authors.affiliation: University of Wisconsin, Department of Horticulture, Madison, Wisconsin, United States of America.|Instituto Nacional de Investigaciones Forestales y Agrícolas y Pecuarias, Aguascalientes, Mexico.
authors.forename: Luis
authors.initials: L
authors.lastname: Diaz-Garcia
authors.affiliation: University of Wisconsin, Department of Horticulture, Madison, Wisconsin, United States of America.
authors.forename: Giovanny
authors.initials: G
authors.lastname: Covarrubias-Pazaran
authors.affiliation: University of Wisconsin, Department of Horticulture, Madison, Wisconsin, United States of America.
authors.forename: Brandon
authors.initials: B
authors.lastname: Schlautman
authors.affiliation: University of Wisconsin, Department of Horticulture, Madison, Wisconsin, United States of America.|USDA-ARS, Vegetable Crops Research Unit, University of Wisconsin, Madison, Wisconsin, United States of America.
authors.forename: Juan
authors.initials: J
authors.lastname: Zalapa
mesh_terms: D000383:Agriculture; D000465:Algorithms; D018556:Crops, Agricultural / Q000033:anatomy & histology / Q000254:growth & development / Q000378:metabolism; D058871:Organic Agriculture; D010641:Phenotype; D010858:Pigmentation; D015203:Reproducibility of Results; D012984:Software