Determination of mango physiological indices by near-infrared spectrometry

• Published in: Postharvest biology and technology Vol. 19; no. 3; pp. 245 - 252
• Main Authors: Schmilovitch, Ze’ev, Mizrach, Amos, Hoffman, Aharon, Egozi, Haim, Fuchs, Yoram
• Format: Journal Article
• Language: English
• Published: New York, NY Elsevier B.V 01.07.2000; Elsevier Science
• Subjects: Acidity; Agronomy. Soil science and plant productions; Biological and medical sciences; Firmness; Fundamental and applied biological sciences. Psychology; General agronomy. Plant production; Harvesting. Postharvest. Storage; Mango; Near-infrared; Nondestructive; Quality; Spectrometry; Sugar; Vegetative propagation. Sowing and planting. Harvesting; Nondestructive; Spectrometry; Quality; Near-infrared; Mango; Firmness; Acidity; Sugar; Production quality; Soluble solids; Mangifera indica; Forecast model; Softening; Soluble sugars; Non destructive method; Near infrared spectrometry; Dicotyledones; Angiospermae; Carbohydrate; Spermatophyta; Fruit tree; Measurement accuracy; Maturity; Anacardiaceae
• ISSN: 0925-5214; 1873-2356
• DOI: 10.1016/S0925-5214(00)00102-2

The objectives of the study were to evaluate the use of near-infrared (NIR) spectrometry in measuring the physiological properties of mango fruit, cv. ‘Tommy Atkins’ and to establish relationships between the nondestructive NIR spectral measurements and the major physiological properties and quality indices of mango fruit. These include softening of the flesh, total soluble solids content and acidity. Intact mango fruit were measured by reflectance NIR in 1200–2400 nm range. NIR models were developed based on multi-linear regression (MLR), principal component analysis (PCA) and partial least square (PLS) regression with respect to the reflectance and its first derivative, the logarithms of the reflectance reciprocal and its second derivative. The above regression models, related the NIR spectra to storage period, firmness, sugar content and acidity. The best combination, based on the prediction results, was MLR models with respect to the second derivative logarithms of the reflectance reciprocal. Predictions with MLR models resulted standard errors of prediction (SEP) of 1.223, 0.161, 17.14 and 37.03, and coefficients of determination of 0.9276, 0.6085, 0.8226 and 0.9380 for TSS, acidity, firmness and storage period, respectively. It was concluded that by using the NIR spectrometry measurement system, in the appropriate spectral range, it is possible to nondestructively assess the maturity factors of mango fruit.