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Near-infrared spectroscopy (NIRS) is an alternative analytical method that can be used to quantify protein content in sweetpotato. It is relatively cheaper and efficient than other methods. This study was conducted to develop NIRS-based models for quantifying protein content of sweetpotato for selection or wide-area production of recommended varieties. A pool of 104 sweetpotato varieties were sampled and roots scanned using NIR spectrometer. Calibration models were developed by subjecting spectral and reference datasets to partial least squares regression. Several pre-processing methods were investigated. Models that yielded the highest coefficient of determination (R 2 ), residual predictive deviation (RPD) and lowest root mean square error of calibration (RMSEC) and prediction (RMSEP) were selected. Optimal model performances were obtained using second derivative pre-processing, showing the highest values of R 2 v , RMSEP and RPD v of 0.98, 0.29, and 4.0, respectively. The regression analysis indicated that informative NIR bands for quantifying protein content of sweetpotatoes ranged between 1600 and 2200 nm. The results demonstrated that NIRS is capable of predicting protein content on sweetpotatoes, rapidly and accurately. Therefore, the NIRS model developed in this study may help to quantify protein composition of sweetpotato for rapid screening of germplasm in breeding programs with high throughput and accuracy. [ABSTRACT FROM AUTHOR]

The determination and quantification of sugars is important for quality control and assurance of horticultural produce. This review discusses analytical methods for determination of sugars and sweetness of fresh and processed fruit and vegetables, including the use of destructive and non-destructive instrumental techniques to evaluate sugar composition and characterize taste profile or sweetness. From the standard hand-held refractometer to the hydrometer, electronic tongue and high pressure liquid chromatography (HPLC) equipped with different detectors, a wide range of devices have been used to determine sugar composition and sweetness of many fruit and vegetable products. Although chromatographic techniques are very accurate and useful, they require extensive sample preparation based on solvent extraction and hence are generally time-consuming and expensive. Visible to near infrared spectroscopy (vis/NIRS) has been proposed as an interesting alternative to traditional methods due to its rapidity, simplicity, cost effectiveness and potential for routine analysis if proper calibration and validation steps were developed. Current trends favour analytical methods that are simple to use, quick and non-destructive. The prospects for using emerging technologies such as hyperspectral imaging and nuclear magnetic resonance for non-destructive assessment of sugar content and sweetness of fresh and processed horticultural food products are also discussed. [ABSTRACT FROM AUTHOR]

Highlights: [•] NIR methods for non-destructive composition analysis of oranges was investigated. [•] NIR with emission head gave best predictions of mass, colour index and vitamin C. [•] Using an integrating sphere gave best prediction of TSS. [•] NIR with emission head can evaluate external and internal characteristics. [ABSTRACT FROM AUTHOR]

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]

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]

Highlights • This review shows moisture and oil contents are used for nut quality evaluation. • Fatty acid composition and rancidity are major determinants of nut quality. • Non-invasive analytical methods for evaluating quality of nuts have become popular. • Vis/NIRS is the utmost promising non-destructive technology for future application. • Research is required to test hyperspectral imaging and X-ray-CT for nut quality evaluation. Abstract Moisture content (MC), oil content (OC), fatty acid composition and rancidity are considered as major determinants of quality of nuts. These parameters are destructively quantified from a batch of representative samples used to estimate quality of nuts of an entire orchard. Although destructive techniques are helpful, they involve extensive sample preparation and solvent extractions, are slow, expensive and obtained results specifically reflect the properties of the evaluated produce. Recently, non-invasive analytical methods and instruments for evaluating quality of various produce have become popular with researchers putting more effort in developing them. Non-destructive methods are an alternative to traditional methods for inspection of internal quality parameters because they are fast, simple and cost-effective. In this review, invasive and non-invasive analytical methods and instruments for evaluating MC, OC, fatty acid composition and rancidity in different nuts are discussed. This paper also reviews the implementation of visible to near infrared spectroscopy, nuclear magnetic resonance and X-ray computed tomography on nuts for evaluation of quality attributes. Technical challenges and future possibilities for commercial use of these non-invasive methods for quality evaluation of nuts are presented. [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]