2026-04-13T02:36:43Zhttps://recercat.cat/oai/request
oai:recercat.cat:2072/4749542025-07-29T22:49:29Zcom_2072_98col_2072_378192
RECERCAT author Goi, Arianna author Manuelian, Carmen L author Currò, Sarah author De Marchi, M 2019 The pet food industry is interested in performing fast analyses to control the nutritional quality of their products. This study assessed the feasibility of near-infrared spectroscopy to predict mineral content in extruded dry dog food. Mineral content in commercial dry dog food samples (n = 119) was quantified by inductively coupled plasma optical emission spectrometry and reflectance spectra (850-2500 nm) captured with FOSS NIRS DS2500 spectrometer. Calibration models were built using modified partial least square regression and leave-one-out cross-validation. The best prediction models were obtained for S (coefficient of determination; R2 = 0.89), K (R2 = 0.85), and Li (R2 = 0.74), followed by P, B, and Sr (R2 = 0.72 each). Only prediction models for S and K were adequate for screening purposes. This study supports that minerals are difficult to determine with NIRS if they are not associated with organic molecules. open access Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original. https://creativecommons.org/licenses/by/4.0/ Dog Dog nutrition Extruded pet food NIR Prediction of mineral composition in commercial extruded dry dog food by near-infrared reflectance spectroscopy Article