title: Spectral Knowledge (SK-UTALCA): Software for Exploratory Analysis of High-Resolution Spectral Reflectance Data on Plant Breeding.
abstract: This article describes public, free software that provides efficient exploratory analysis of high-resolution spectral reflectance data. Spectral reflectance data can suffer from problems such as poor signal to noise ratios in various wavebands or invalid measurements due to changes in incoming solar radiation or operator fatigue leading to poor orientation of sensors. Thus, exploratory data analysis is essential to identify appropriate data for further analyses. This software overcomes the problem that analysis tools such as Excel are cumbersome to use for the high number of wavelengths and samples typically acquired in these studies. The software, Spectral Knowledge (SK-UTALCA), was initially developed for plant breeding, but it is also suitable for other studies such as precision agriculture, crop protection, ecophysiology plant nutrition, and soil fertility. Various spectral reflectance indices (SRIs) are often used to relate crop characteristics to spectral data and the software is loaded with 255 SRIs which can be applied quickly to the data. This article describes the architecture and functions of SK-UTALCA and the features of the data that led to the development of each of its modules.
authors.affiliation: Plant Breeding and Phenomic Center, Facultad de Ciencias Agrarias, PIEI Adaptación de la Agricultura al Cambio Climático, Universidad de Talca Talca, Chile.
authors.forename: Gustavo A
authors.initials: GA
authors.lastname: Lobos
authors.affiliation: Escuela de Agronomía, Pontificia Universidad Católica de ValparaísoQuillota, Chile; Department of Viticulture and Oenology, Faculty of AgriSciences, Stellenbosch UniversityMatieland, South Africa.
authors.forename: Carlos
authors.initials: C
authors.lastname: Poblete-Echeverría
keywords: collinearity; noise; outlier; phenomic; phenotyping; scan; spectral reflectance index (SRI); wavelength