Postharvest quality of apple predicted by NIR-spectroscopy: Study of the effect of biological variability on spectra and model performance |
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| Authors: | Els Bobelyn Anca-Sabina Serban Mihai Nicu Jeroen Lammertyn Bart M Nicolai Wouter Saeys |
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| Institution: | 1. Flanders Centre of Postharvest Technology, Willem de Croylaan 42, B-3001 Leuven, Belgium;2. BIOSYST-MeBioS, Katholieke Universiteit Leuven, Willem de Croylaan 42, Box 2428, B-3001 Leuven, Belgium;3. Department of Environmental Engineering and Management, Technical University of Iasi, Bd. D. Mangeron 71A, Iasi 700050, Romania;1. LCC, CNRS & University of Toulouse (UPS, INPT), 31077 Toulouse, France;2. LAAS, CNRS & University of Toulouse (UPS, INSA, IAES), 31077 Toulouse, France;3. Department of Chemistry, University of Bath, Bath BA2 7AY, UK;1. Beijing Research Center of Intelligent Equipment for Agriculture, Beijing, 100097, China;2. National Research Center of Intelligent Equipment for Agriculture, Beijing, 100097, China;1. CEOT, Universidade do Algarve, Campus de Gambelas, 8005-189 Faro, Portugal;2. MED, Universidade do Algarve, Campus de Gambelas, 8005-189 Faro, Portugal;3. Physics Department, Universidade do Algarve, Campus de Gambelas, 8005-189 Faro, Portugal;1. College of Mechanical and Electronic Engineering, Northwest A&F University, Yangling, Shaanxi 712100, China;2. Beijing Research Center of Intelligent Equipment for Agriculture, Beijing 100097, China;3. National Research Center of Intelligent Equipment for Agriculture, Beijing 100097, China;4. Key Laboratory of Agri-Informatics, Ministry of Agriculture, Beijing 100097, China;5. Beijing Key Laboratory of Intelligent Equipment Technology for Agriculture, Beijing 100097, China;1. School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China;2. National Engineering Research Center of Intelligent Equipment for Agriculture, Beijing100097, China;3. College of Engineering, China Agricultural University, Beijing 100083, China |
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| Abstract: | The effect of cultivar, season, shelf-life and origin on the accuracy of near infrared (NIR) calibration models for the soluble solids content (SSC) and firmness of apple was studied based on a large spectral data set based on approximately 6000 apple fruit from different cultivars, origins, shelf-life exposure time and seasons. To interpret the variance in the spectra with respect to biological variability, functional analysis of variance (FANOVA) was used. From the FANOVA analysis it was concluded that the effects of cultivar, origin and shelf-life exposure time on the NIR spectra were all significant. The largest differences in the spectra were found around the water absorption peaks (970, 1170 and 1450 nm). External validations using independent data sets showed that the accuracy of the models increased considerably when more variability was included in the calibration data set. In general the RMSEP for predictions of the SSC were in the range 0.6–0.8 °Brix, while for Magness Taylor firmness it was 5.9–8.8 N, depending on the cultivar. It was shown that atypical data can lead to large validation errors. It is, therefore, important to collect a calibration data set which is sufficiently representative for future samples to be analyzed with the developed calibration models and to develop simple procedures for model adaptation during practical use. |
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