Ruben Urraca1, Andres Sanz-Garcia2, Javier Tardaguila3, Maria P Diago3. 1. Universidad de La Rioja, 26006, Logroño, Spain. 2. Division of Biosciences, University of Helsinki, Viikinkaari, 5 E, P.O. Box 56, 00014, Helsinki, Finland. 3. Instituto de Ciencias de la Vid y del Vino, University of La Rioja, CSIC, Gobierno de La Rioja, 26006, Logroño, Spain.
Abstract
BACKGROUND: Recent studies have reported the potential of near infrared (NIR) spectral analysers for monitoring the ripeness of grape berries as an alternative to wet chemistry methods. This study covers various aspects regarding the calibration and implementation of predictive models of total soluble solids (TSS) in grape berries using laboratory and in-field collected NIR spectra. RESULTS: The performance of the calibration models obtained under laboratory conditions indicated that at least 700 berry samples are required to assure enough prediction accuracy. A statistically significant error reduction (ΔRMSECV = 0.1°Brix) with P < 0.001 was observed when measuring berries without epicuticular wax, which was negligible from a practical point of view. Under field conditions, the prediction errors (RMSEP = 1.68°Brix, and SEP = 1.67°Brix) were close to those obtained with the laboratory dataset (RMSEP = 1.42°Brix, SEP = 1.40°Brix). CONCLUSION: This work clarifies several methodological factors to develop a protocol for in-field assessing TSS in grape berries using an affordable, non-invasive, portable NIR spectral analyser.
BACKGROUND: Recent studies have reported the potential of near infrared (NIR) spectral analysers for monitoring the ripeness of grape berries as an alternative to wet chemistry methods. This study covers various aspects regarding the calibration and implementation of predictive models of total soluble solids (TSS) in grape berries using laboratory and in-field collected NIR spectra. RESULTS: The performance of the calibration models obtained under laboratory conditions indicated that at least 700 berry samples are required to assure enough prediction accuracy. A statistically significant error reduction (ΔRMSECV = 0.1°Brix) with P < 0.001 was observed when measuring berries without epicuticular wax, which was negligible from a practical point of view. Under field conditions, the prediction errors (RMSEP = 1.68°Brix, and SEP = 1.67°Brix) were close to those obtained with the laboratory dataset (RMSEP = 1.42°Brix, SEP = 1.40°Brix). CONCLUSION: This work clarifies several methodological factors to develop a protocol for in-field assessing TSS in grape berries using an affordable, non-invasive, portable NIR spectral analyser.
Authors: Jing Sheng Ng; Syahidah Akmal Muhammad; Chin Hong Yong; Ainolsyakira Mohd Rodhi; Baharudin Ibrahim; Mohd Noor Hidayat Adenan; Salmah Moosa; Zainon Othman; Nazaratul Ashifa Abdullah Salim; Zawiyah Sharif; Faridah Ismail; Simon D Kelly; Andrew Cannavan Journal: Foods Date: 2022-08-10