Non-Destructive Measurement of the Internal Quality of Citrus Fruits Using a Portable NIR Device

Abstract

Citrus industry has grown exponentially as a result of increasing demand on its consumption making it stand high among other fruit crops. Therefore, the citrus sector seeks rapid, ease and non-destructive approaches to evaluate in real-time and in situ the external and internal changes in physical and nutritional quality at any stage of fruit development or storage. In particular, vitamin C is among the most important micronutrients for consumers, but its measurement relies on laborious analytical methodologies. In this study, a portable near-infrared spectroscopy (NIRS) sensor was used in combination with chemometrics to develop robust and accurate models to study the ripeness of several citrus fruits (oranges, lemons, clementines, tangerines, Tahiti limes) and their vitamin C content. Ascorbic acid, dehydroascorbic acid and total vitamin C were determined by HILIC-HPLC-UV, while soluble solids and total acidity were evaluated by standard analytical procedures. Partial least squares regression (PLSR) was used to build regression models which revealed suitable performance regarding the prediction of quality and ripeness parameters in all tested fruits. Models for ascorbic acid, dehydroascorbic acid, total vitamin C, soluble solids, total acidity and juiciness showed Rcv2 = 0.77 – 0.87, Rcv2 = 0.29 – 0.79, Rcv2 = 0.77 – 0.86, Rcv2 = 0.75 – 0.97, Rcv2 = 0.24 – 0.92, and Rcv2 = 0.38 – 0.75, respectively. Prediction models of oranges and Tahiti limes showed good to excellent performance regarding all latent variables. The resulting models confirmed that NIRS technology is a time and cost-effective approach to predict citrus fruit quality, which can easily be used by the various stakeholders from the citrus industry.

Ripening assessment of ‘Ortanique’ (Citrus reticulata Blanco x Citrus sinensis (L) Osbeck) on tree by SW-NIR reflectance spectroscopy-based calibration models

“…Both the rind thickness (Wang et al, 2016), its biochemical (Jamshidi et al, 2014), and bulk optical properties of the various citrus fruit (Sun et al, 2020a(Sun et al, ,b, 2021, have been reported to influence the vis-NIR spectral data, urging to choose the most similar fruit for the comparison. For SSC in IV there are mainly two groups of results: most studies presented RMSEP ~ 0.6 to 0.8 % and R 2 ~ 0.5 to 0.9, where the results obtained in the current study fit; there is also a smaller group of two reports claiming considerably better results, with RMSEP ~ 0.3 to 0.4 % and R 2 ≥ 0.9, although the low number of samples in Santos et al (2020) requires a critical regard. The fact that different spectral ranges yield approximately equal results suggests that SSC may be assessed either in the SW-NIR (700-1100 nm) or in the NIR (1000-2500 nm) ranges.…”

“…The worse results of this work are most probably related to the low SW-NIR light penetration in the pulp of 'Ortanique', as previously reported for various thick rind fruit (Arendse et al, 2018). In turn, for ascorbic acid, Santos et al (2020) obtained a model for tangerine with R 2 = 0.868 and RMSE = 2.360 mg/100 mL and for clementine with R 2 = 0.767 and RMSE = 3.714 mg/100 mL in the spectral range 900-1700 nm. Xudong et al (2009) obtained a model for vitamin C with R = 0.81 and RMSEP = 2.7 mg/100 mL in the spectral range 400− 1040 nm.…”

Evaluating the Efficacy of Gum Arabic-Zinc Oxide Nanoparticles Composite Coating on Shelf-Life Extension of Mandarins (cv. Kinnow)

“…'Kinnow' mandarin fruit coated with the gum arabic enriched with ZnO-NPs at different concentrations showed a steady increase in CCI value during the 40 days of storage. The respiration rate, as well as the occurrence and severity of postharvest physiological disorders such as rind pitting and chilling injury on the surface of the fruit, influence the CCI of citrus fruit (Santos et al, 2021); thus, this might have contributed to the observed CCI values in this study.…”

Non‐invasive and rapid quality assessment of thermal processed and canned tender jackfruit: NIR spectroscopy and chemometric approach

“…The SE P values of the AA (0.311 mg/100 g F.W), TPC (0.028 mg GAE/g D.W.), and TFC (1.537 mg RE/g D.W.) were almost 1.5–2 times the SE L (AA = 0.18 mg/100 g F.W; TFC = 0.97 mg RE/g D.W; TPC = 0.02 mg GAE/g D.W.) which indicates the excellent performance of the developed PLSR models (Mahanti et al ., 2020). The statistical results obtained in the present study for AA ( R 2 = 0.762; RPD = 2.059) estimation were better than the results reported in the previous studies for spinach ( R 2 = 0.33; RPD = 1.21) (Pérez‐Marín et al ., 2019), acerola ( R 2 = 0.65) (Malegori et al ., 2017), and citrus fruits ( R 2 = 0.77–0.87) (Santos et al ., 2021). Similarly, the PLSR model developed in the present study to assess the TFC ( R 2 = 0.938; RPD = 4.018) in tender jack fruit was better than the results reported by the previous studies on apple ( R 2 = 0.86) (Giovanelli et al ., 2014), and goji berry ( R 2 = 0.91; RMSE = 0.38 mg/g) (Tingting et al ., 2016).…”