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Provedor de dados:  CIGR Journal
País:  China
Título:  Near-Infrared Spectroscopy for Non-Destructive Prediction of Maturity and Eating Quality of ‘Carabao’ Mango (Mangifera indica L.) Fruit
Autores:  Polinar, Yvonne Q.
Yaptenco, Kevin Fernandez
Peralta, Engelbert K.
Agravante, Josephine U.
Data:  2019-04-30
Ano:  2019
Palavras-chave:  Agricultural / biosystems engineering
Chemometrics
Horticulture Near-infrared
Mango
Sweetness
Maturity
Eating quality
Philippines
Resumo:  Near-infrared (NIR) spectroscopy was assessed in predicting maturity and eating quality of ‘Carabao’ mango fruit. A total of 1,200 fruits were harvested at the green stage at four different harvest dates [100, 110, 120 and 125 days after flower induction (DAFI)]. Fruits were scanned at the green and table-ripe stage (TRS) using NIR reflectance spectroscopy. The fruits were then measured destructively for the determination of dry matter (DM) content at the green stage, total soluble solids (TSS) and sensory attributes at the TRS. The best calibration models were achieved using partial least square regression (PLSR) analysis for predicting DM, TSS and maturity in the short wavelength region of 700 - 990 nm at 2-nm increment. Principal component analysis-linear discriminant analysis (PCA-LDA) was also used in classifying fruits according to maturity (in terms of DAFI) and eating quality (in terms of overall acceptability or OA). Based on R2 values, PLSR models are suitable for quality assurance according to maturity (R2 = 0.946, RMSECV = 2.229) and could be used for screening green fruits according to DM (R2 = 0.774, RMSECV = 1.091%). The calibration model for predicting TSS (R2 = 0.839, RMSECV = 1.282) of ripe fruit using NIR spectra at TRS could be used in research but with caution. For classifying fruits according to DAFI and OA, PCA-LDA gave good results using NIR spectra at the green stage with a success rate of 88% and 86%, 72% and 70% for calibration and validation, respectively.  The findings indicate the potential of near- infrared (NIR) spectroscopy for non-destructive prediction of maturity and quality parameters of mango. The results of the study could serve as the basis for quality control and automatic sorting system for various commodities.
Tipo:  Info:eu-repo/semantics/article
Idioma:  Inglês
Identificador:  http://www.cigrjournal.org/index.php/Ejounral/article/view/5152
Editor:  International Commission of Agricultural and Biosystems Engineering
Relação:  http://www.cigrjournal.org/index.php/Ejounral/article/view/5152/2930
http://www.cigrjournal.org/index.php/Ejounral/article/downloadSuppFile/5152/2307
Formato:  application/pdf
Fonte:  Agricultural Engineering International: CIGR Journal; Vol 21, No 1 (2019): CIGR Journal; 209-219

1682-1130
Direitos:  Copyright (c) 2019 Agricultural Engineering International: CIGR Journal
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