Non-Destructive Measurement of Quality Parameters of Apple Fruit by Using Visible/Near-Infrared Spectroscopy and Multivariate Regression Analysis

Behzad Hasanzadeh, Yousef Abbaspour-Gilandeh (), Araz Soltani-Nazarloo, Eduardo De La Cruz-Gámez, José Luis Hernández-Hernández and Miriam Martínez-Arroyo ()
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Behzad Hasanzadeh: Department of Biosystems Engineering, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran
Yousef Abbaspour-Gilandeh: Department of Biosystems Engineering, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran
Araz Soltani-Nazarloo: Department of Biosystems Engineering, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran
Eduardo De La Cruz-Gámez: National Technology of Mexico/Acapulco Institute of Technology, Acapulco 39905, Guerrero, Mexico
José Luis Hernández-Hernández: National Technological of Mexico/Chilpancingo Institute of Technology, Chilpancingo 39070, Guerrero, Mexico
Miriam Martínez-Arroyo: National Technology of Mexico/Acapulco Institute of Technology, Acapulco 39905, Guerrero, Mexico

Sustainability, 2022, vol. 14, issue 22, 1-16

Abstract: The quality assessment and grading of agricultural products is one of the post-harvest activities that has received considerable attention due to the growing demand for healthy and better-quality products. Recently, various non-destructive methods have been used to evaluate the quality of agricultural products, which are very desirable and faster and more economical than destructive methods. Optical methods are one of the most important non-destructive methods that use the high speed of light detection and computer data processing and are able to evaluate the quality and classification of products with high accuracy. Among the optical methods, visible–near-infrared (Vis/NIR) spectroscopy is considered one of the most accurate methods. In this research, Vis/NIR spectroscopy technology was used in the spectral range of 350–1150 nm for non-destructive detection of some quality parameters including pH, TA, SSC, and TP of two varieties of Red Delicious and Golden Delicious apples. Various pre-processing models were developed to predict the parameters, which brought the desired results with high accuracy so that pH prediction results were for yellow apples (RMSEC = 0.009, r c = 0.991, SDR = 2.51) and for red apples (RMSEC = 0.005, r c = 0.998, SDR = 2.56). The results for TA were also (RMSEC = 0.003, r c = 0.996, SDR = 2.51) for red apples and (RMSEC = 0.001, r c = 0.998, SDR = 2.81) for yellow apples. The results regarding SSC were for red apples (RMSEC = 0.209, rc = 0.990 and SDR = 2.82) and for yellow apples (RMSEC = 0.054, SDR = 2.67 and rc = 0.999). In addition, regarding TP, the results were for red apples (RMSEC = 0.2, r c = 0.989, SDR = 2.05) and for yellow apples (RMSEC = 1.457, r c = 0.998, SDR = 1.61). The obtained results indicate the detection of the mentioned parameters with high accuracy by visible/infrared spectroscopic technology.

Keywords: spectroscopy; multivariate regression analysis; computational intelligence; apple (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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