title: A multivariate regression model for detection of fumonisins content in maize from near infrared spectra.
abstract: Fumonisins are mycotoxins produced by Fusarium species that commonly live in maize. Whereas fungi damage plants, fumonisins cause disease both to cattle breedings and human beings. Law limits set fumonisins tolerable daily intake with respect to several maize based feed and food. Chemical techniques assure the most reliable and accurate measurements, but they are expensive and time consuming. A method based on Near Infrared spectroscopy and multivariate statistical regression is described as a simpler, cheaper and faster alternative. We apply Partial Least Squares with full cross validation. Two models are described, having high correlation of calibration (0.995, 0.998) and of validation (0.908, 0.909), respectively. Description of observed phenomenon is accurate and overfitting is avoided. Screening of contaminated maize with respect to European legal limit of 4 mg kg(-1) should be assured.
authors.affiliation: Dept. of Mathematics and Computer Science - Research Center Norbert Wiener, University of Udine, via delle Scienze 206, 33100 Udine, Italy. dlrca@uniud.it
authors.forename: Della Riccia
authors.initials: DR
authors.lastname: Giacomo
authors.forename: Del Zotto
authors.initials: del Z
authors.lastname: Stefania
mesh_terms: D000821:Animal Feed / Q000032:analysis*; D000818:Animals; D002417:Cattle; D005506:Food Contamination / Q000032:analysis*; D037341:Fumonisins / Q000032:analysis*; D006801:Humans; D016018:Least-Squares Analysis; D015999:Multivariate Analysis; D019265:Spectroscopy, Near-Infrared / Q000379:methods*; D003313:Zea mays / Q000737:chemistry*
chemical_list: D037341:Fumonisins
keywords: Calibration; Full-cross validation; Fumonisins; Multivariate regression; NIR spectroscopy; PLS inference; Statistical model