JOURNAL ARTICLE

NON-DESTRUCTIVE MEASUREMENT OF ACIDITY, SOLUBLE SOLIDS, AND FIRMNESS OF JONAGOLD APPLES USING NIR-SPECTROSCOPY

Abstract

In this study the potential of visible and near infrared spectroscopy (380-1650 nm) as a non-destructivemeasurement technique for measuring quality characteristics of Jonagold apples is evaluated. A relation has beenestablished between the reflectance spectra recorded with a bifurcated optical fibre and fruit parameters such as the pH,the soluble solids content, the stiffness factor and other texture parameters such as the elastic modulus of the flesh. Thedata were analyzed with multivariate calibration techniques such as principal component analysis (PCA), principalcomponent regression (PCR) and partial least squares analysis (PLS). The impact of the data preprocessing on theprediction performance has also been investigated. The prediction models indicate a good to excellent predictionperformance. The best pH model has a standard error of prediction (SEP) of 0.068 and a correlation between predictedand measured values (r) of 0.93. The proposed model for the stiffness factor has a SEP of 2.49 and an r-value of 0.90. Forthe soluble solids content model a SEP of 0.61 and an r-value of 0.82 is obtained. It has been shown that the pH modelhas a physico-chemical background. The prediction performance of the model for the elastic modulus, however, was notyet satisfactory (SEP = 0.26, r = 0.75).

Keywords:
Partial least squares regression Principal component analysis Chemistry Principal component regression Analytical Chemistry (journal) Calibration Near-infrared spectroscopy Multivariate statistics Spectroscopy Materials science Mathematics Optics Chromatography Statistics

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Citation History

Topics

Spectroscopy and Chemometric Analyses
Physical Sciences →  Chemistry →  Analytical Chemistry
Postharvest Quality and Shelf Life Management
Life Sciences →  Agricultural and Biological Sciences →  Plant Science
Plant Physiology and Cultivation Studies
Life Sciences →  Agricultural and Biological Sciences →  Plant Science
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