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Determination of mango physiological indices by near-infrared spectrometry
Year:
2000
Source of publication :
Postharvest Biology and Technology
Authors :
Egozi, Haim
;
.
Fuchs, Yoram
;
.
Hoffman, Aharon
;
.
Mizrach, Amos
;
.
Schmilovitch, Ze'ev
;
.
Volume :
19
Co-Authors:
Schmilovitch, Z., Inst. of Agricultural Engineering, A.R.O., Volcani Ctr., P.O. B., Bet Dagan, Israel
Mizrach, A., Inst. of Agricultural Engineering, A.R.O., Volcani Ctr., P.O. B., Bet Dagan, Israel
Hoffman, A., Inst. of Agricultural Engineering, A.R.O., Volcani Ctr., P.O. B., Bet Dagan, Israel
Egozi, H., Inst. of Agricultural Engineering, A.R.O., Volcani Ctr., P.O. B., Bet Dagan, Israel
Fuchs, Y., Inst. Technol. Storage Agric. Prod., A.R.O., Volcani Ctr., P.O. B., Bet Dagan, Israel
Facilitators :
From page:
245
To page:
252
(
Total pages:
8
)
Abstract:
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. (C) 2000 Elsevier Science B.V.
Note:
Related Files :
acidity
Firmness
Mang o
Near-infrared
Nondestructive
Quality
Spectrometry
sugar
Show More
Related Content
More details
DOI :
10.1016/S0925-5214(00)00102-2
Article number:
Affiliations:
Database:
Scopus
Publication Type:
article
;
.
Language:
English
Editors' remarks:
ID:
29355
Last updated date:
02/03/2022 17:27
Creation date:
17/04/2018 00:46
Scientific Publication
Determination of mango physiological indices by near-infrared spectrometry
19
Schmilovitch, Z., Inst. of Agricultural Engineering, A.R.O., Volcani Ctr., P.O. B., Bet Dagan, Israel
Mizrach, A., Inst. of Agricultural Engineering, A.R.O., Volcani Ctr., P.O. B., Bet Dagan, Israel
Hoffman, A., Inst. of Agricultural Engineering, A.R.O., Volcani Ctr., P.O. B., Bet Dagan, Israel
Egozi, H., Inst. of Agricultural Engineering, A.R.O., Volcani Ctr., P.O. B., Bet Dagan, Israel
Fuchs, Y., Inst. Technol. Storage Agric. Prod., A.R.O., Volcani Ctr., P.O. B., Bet Dagan, Israel
Determination of mango physiological indices by near-infrared spectrometry
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. (C) 2000 Elsevier Science B.V.
Scientific Publication
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