Rapid Assessment of Taste Indicators in Orange Juice Using a Handheld Near-infrared Scanner in Transflectance Mode

We evaluated the capability of near-infrared (NIR) transflectance spectroscopy coupled with multivariate analysis to develop predictive regression models that quantify taste indicators, i.e., soluble solids, titratable acidity (TA), citric acid, sucrose, glucose, and fructose, in orange juice (sample size = 123). The NIR spectra were collected in transflectance mode using a handheld scanner with a series of reflectors that provide three distinct pathlengths (0.50 mm, 0.80 mm, and 2 mm) across the juice samples. Reference data were collected using automatic titrators for TA, refractometer for Brix, and high-performance liquid chromatography (HPLC) for organic acids and sugars. Orange juice samples represented a diverse genetic pool of Hamlin and Valencia varieties harvested at different maturity stages providing a unique range of concentration for each parameter (Brix, 4.3–12.3%, and TA 0.8–3.5 g citric acid/L). Pattern recognition analysis correlated the spectral data to reference values using partial least square regression. Results showed better performance using 0.50 mm and 0.80 mm pathlengths, R pre ≥ 0.82, root mean square error of prediction (RMSEP) range 0.14–6.87, residual prediction deviation (RPD) range 1.2–8.3, residual error rate (RER) range 2.7–30 compared to the 2 mm pathlength (R pre ≥ 0.72, RMSEP range 0.27–4.47, RPD range 1.2–1.7, RER range 5.2–7.8). We demonstrated that a field deployable NIR scanner can provide reliable prediction using a transflectance approach using algorithms that were synchronized for cloud computing using R programming, providing easy accessibility for analysis. This technology offers orange breeders and growers an affordable, rapid (10 s), and accurate solution for in-field, real-time monitoring of taste indicators in orange juice, which can help expedite critical decision-making processes in the field (harvest timing, process optimization, and aid in breeding research).