Article ID Journal Published Year Pages File Type
4909257 Journal of Food Engineering 2017 9 Pages PDF
Abstract

•Vis/NIRS quantified sweetness and flavour of 'Valencia' oranges and 'Star Ruby' grapefruit.•Partial least square models accurately predicted TSS, TA, TSS:TA ratio and BrimA.•Results demonstrated importance of integrating multi-seasonal dataset in PLS models.•Vis/NIRS can be used for bench marking sweetness and flavour of individual citrus fruit.

Sweetness and flavour are desirable attributes used for quality control and assurance of citrus fruit, which are largely determined by total soluble solids (TSS), titrable acidity (TA) and TSS: TA ratio. However, the accuracies of TSS, TA and TSS: TA as flavour indices have been recently criticised. BrimA (Brix minus acids), on the other hand, is an accurate organoleptic parameter that has been shown to be highly related to sweetness and flavour of citrus fruit. In this study, the ability of visible to near infrared spectroscopy (Vis/NIRS), in reflectance mode, to non-destructively quantify BrimA, TSS, TA and TSS: TA ratio of 'Valencia' orange and 'Star Ruby' grapefruit was evaluated. Vis/NIR spectral data was acquired using a laboratory bench-top monochromator NIR Systems. Reference measurements and spectral datasets were subjected to partial least square (PLS) regression analysis. The best prediction models were observed for BrimA of 'Valencia' oranges with the coefficient of determination (R2) = 0.958; root mean square error of prediction (RMSEP) = 0.006 and residual predictive deviation (RPD) = 3.96, followed by TSS: TA ratio (R2 = 0.958; RMSEP = 0.605; RPD = 4.92). Good models for predicting flavor of grapefruit were also attained, with TSS having the best model (R2 = 0.896, RMSEP = 0.308 and RPD = 2.94), followed by BrimA (R2 = 0.858; RMSEP = 0.429; RPD = 2.45). These results demonstrated the ability of Vis/NIRS to non-destructively predict sweetness and flavour attributes of oranges and grapefruit. Vis/NIRS was recommended as a possible fast and accurate technique to be used for fruit discrimination based on flavour parameters during packing and for pricing of fruit in the market.

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Physical Sciences and Engineering Chemical Engineering Chemical Engineering (General)
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