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Near infrared (NIR) and mid infrared (MIR) spectral acquisition modes were compared for predicting organoleptic and phytochemical quality attributes of pomegranate juice. Three Fourier transform infrared (FT-IR) spectrometers namely, a FT-NIR spectrometer, FT-MIR spectrometer in attenuated total reflection mode and FT-MIR spectrometer in transmission mode were used. Calibration models were constructed by subjecting the spectral data to partial least squares regression analysis. The models were assessed based on their overall performance (lower root mean square error of prediction, the number of latent variables and residual predictive deviation). The predictive abilities of the instruments for juice quality attributes were statistically compared using Bland and Altman, and Passing-Bablok. The outcomes are critically discussed, which showed the suitability of the FT-MIR spectrometer in transmission mode for predicting selected quality attributes of pomegranate juice. [ABSTRACT FROM AUTHOR]

Fruits with thick rind have been reported to interfere with the measurement of internal quality of non-destructive near infrared spectroscopy. This review provides an overview of issues related to the use of near infrared spectroscopy for measuring internal and external quality attributes of horticultural produce with thick rinds. The use of other non-destructive techniques for assessing internal and external quality thick rind fruit, such as hyperspectral and multispectral imaging systems, X-ray micro-computed tomography, nuclear magnetic resonance and Raman spectroscopy are also discussed. A concise summary of research and potential commercial application for each of the techniques is highlighted. [ABSTRACT FROM AUTHOR]

Fruits with thick rind have been reported to interfere with the measurement of internal quality of non-destructive near infrared spectroscopy. This review provides an overview of issues related to the use of near infrared spectroscopy for measuring internal and external quality attributes of horticultural produce with thick rinds. The use of other non-destructive techniques for assessing internal and external quality thick rind fruit, such as hyperspectral and multispectral imaging systems, X-ray micro-computed tomography, nuclear magnetic resonance and Raman spectroscopy are also discussed. A concise summary of research and potential commercial application for each of the techniques is highlighted. [ABSTRACT FROM AUTHOR]

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 (R 2 ) = 0.958; root mean square error of prediction (RMSEP) = 0.006 and residual predictive deviation (RPD) = 3.96, followed by TSS: TA ratio (R 2 = 0.958; RMSEP = 0.605; RPD = 4.92). Good models for predicting flavor of grapefruit were also attained, with TSS having the best model (R 2 = 0.896, RMSEP = 0.308 and RPD = 2.94), followed by BrimA (R 2 = 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. [ABSTRACT FROM AUTHOR]

A portable NIR device, the SCiO™ molecular sensor (Consumer Physics Inc., Israel) operating in the range 740–1070 nm, was used to determine some ripening parameters, namely total soluble solids (TSS), titratable acidity (TA), and pH, of Primitivo wine grape cultivar. Data of Primitivo berries trained to Guyot (unilateral) and bush-vine (named in Italy as 'Alberello'), were collected in the vineyard with the device and compared with laboratory analysis during the 2019 and 2020 seasons. The calibration models provided similar results for both Guyot and Alberello; the TSS model with R2 = 0.97, RMSE = 1.33, and RPD = 5.76 for Guyot and with R2 = 0.97, RMSE = 1.41, and RPD = 5.31 for Alberello were the best models. Finally, the calibrated models were validated on a different dataset showing that the device is eligible for non-destructive assessments of ripening parameters of wine grape cultivars. The best results were obtained for the TSS model validation with R2 = 0.95; RMSE = 1.86, RPD = 4.07 for Guyot and R2 = 0.92, RMSE = 2.53, RPD = 3.17 for Alberello. • NIR was tested as a predictive tool for the determination of ripening parameters in grape. • Primitive wine grape cultivar was trained to two systems (Guyot and bush-vine). • TSS, TA and pH predictions were successful for both systems. • Pre-processing techniques with 1st derivative and SNV resulted in better performances. [ABSTRACT FROM AUTHOR]