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Abstract Rind biochemical properties play major roles in defence mechanisms against the incidence of rind physiological disorders of citrus fruit during cold storage. Hence, multivariate calibration models were developed to rapidly and non-destructively determine rind biochemical properties of citrus fruit from visible to near-infrared (Vis/NIR) spectra acquired by Vis/NIR spectroscopy using partial least square regression algorithm. To achieve optimum models for determination of each rind biochemical property, several mathematical pre-processing methods were explored, including no pre-treatment. However, special emphases were given to the best model statistics in terms of coefficient of determination (R2) and residual predictive deviation (RPD). Models were performed by critical examination of different wavelength ranges (visible, near-infrared and full regions) and combinations of fruit harvested from different production regions and acquired before (week 0) and after (week 9) cold storage. Results obtained showed excellent models for determining parameters such as sucrose (R2 = 0.99 and RPD = 11.42), total flavonoids (R2 = 0.99 and RPD = 12.37), and chlorophyll b (R2 = 0.97 and RPD = 5.67). This study reported the first application of Vis/NIR and chemometrics in determining the rind biochemical properties of 'Marsh' grapefruit rapidly and non-destructively. [ABSTRACT FROM AUTHOR]

Highlights: [•] Fruit from inside the canopy were more susceptible to RBD disorder than outside fruit. [•] Vis/NIRS PLS models predicted rind fructose, glucose and sucrose with accuracy. [•] Vis/NIRS PCA model was able to non-destructively classify fruit based on tree canopy. [•] Models based on pre-storage spectra gave better prediction of RBD than post-storage. [Copyright &y& Elsevier]

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]

Postharvest RP is a progressive rind physiological disorder affecting citrus fruit during postharvest storage, reducing external quality of the fruit. The disorder develops 3–5 weeks after harvest, making it difficult to detect during grading and sorting in commercial packing lines. The Vis/NIR spectroscopy and associated chemometric analytical methods were explored for non-destructive prediction of ‘Marsh’ grapefruit ( Citrus x paradisi MacFad) susceptibility to rind pitting. Reflectance Vis/NIR spectral data was acquired from fruit, just after harvest, using a laboratory bench-top monochromator NIR System equipped with a quartz halogen lamp and lead sulfide detector. Reference measurements for calibrating and validating PLS models included visual scores of RP and rind physico-chemical variables related to the disorder. The spectral data was correlated to RP scores and rind physico-chemical properties after eight weeks in cold storage and a week in shelf life. Good prediction of RP was obtained (R 2 p  = 0.78; RPD = 2.03; RMSEP = 1.41). Prediction models for rind physicochemical properties successfully developed and validated included rind total antioxidant capacity (R 2 p  = 0.95), β carotene (R 2 p  = 0.99), total carotenoids (R 2 p  = 0.92), chlorophyll a (R 2 p  = 0.89), chlorophyll b (R 2 p  = 0.93), dry matter (R 2 p  = 0.88), sucrose (R 2 p  = 0.91), glucose (R 2 p  = 0.93) and fructose (R 2 p  = 0.94). Principal component analysis successfully segregated fruit based on canopy position and susceptibility to rind pitting disorder. The ability of Vis/NIR spectroscopy coupled with chemometric analysis to cluster fruit based on canopy position is recommended as a secondary approach to discriminate fruit with high susceptibility to RP since RP occurrence was high on fruit from outside canopy. [ABSTRACT FROM AUTHOR]

Harvest maturity of avocado fruit is currently determined using indices such as mesocarp oil content, dry matter (DM) or moisture content (MC), both measured destructively using representative samples of a batch in an orchard. Although useful, destructive techniques are time-consuming and results reflect properties of specific produce evaluated. In this study, the feasibility of near-infrared spectroscopy (NIRS) as a rapid non-destructive method for predicting maturity parameters of individual avocado fruit was evaluated. NIRS prediction results showed that MC and DM were predicted accurately, with residual predictive deviation (RPD) of 2.00 and 2.13 respectively. However, models for predicting oil content, though promising, were not accurate, with RPD value of less than 1.0. The good prediction statistics between NIRS predicted MC and DM content demonstrated the potential of this system for non-destructive evaluation of avocado fruit maturity status. The stability and accuracy of models developed over two seasons, 2013 and 2014, to predict maturity parameters of avocado fruit demonstrated model robustness. NIRS combined with PLS models developed in this study are recommended for non-destructive evaluation of individual avocado fruit maturity status. [ABSTRACT FROM AUTHOR]