Near-infrared (NIR) Spectrometer for Simultaneous Non-Destructive Determination of Quality Parameters in Baobab (Adansonia digitata L.) Fruit Pulp

Abstract

ABSTRACT

Baobab fruit pulp (BFP) is regarded as a ‘superfruit’ due to its remarkable nutrient density and associated potent benefits. The surge in demand for BFP has led to the need for quality control to guarantee quality and compliance with regulatory standards. Total titratable acidity (TTA), total soluble solids (TSS), vitamin C, and moisture content (MC) are among the attributes used for assessing the quality of BFP. These attributes are normally determined through time-consuming and destructive wet-chemistry processes. In this study, the potential of a portable near-infrared (NIR) spectrometer paired with chemometrics of partial least square regression (PLSR) was evaluated for simultaneous, rapid, and non-destructive assessment of BFP quality. Baobab fruits were sampled in Kilifi County and analyzed in the JKUAT post-harvest laboratory. The pulp for 240 fruits was extracted, and scanned using a NIR spectrometer (Wavelength 900-1700 nm) (Model: NIR-S-G1, Tellspec, Toronto, Canada) to obtain spectral data, and subsequently subjected to wet-chemistry analyses for reference data acquisition. Collected data were partitioned into two subsets; the training set and the test set. The PLSR algorithm was adopted to establish the correlation between spectral and reference measurements and construct predictive models for BFP quality parameters. The models' performance was assessed in terms of coefficient of prediction (R²P), root mean square error of prediction (RMSEP), residual predictive deviation (RPD), and bias. All constructed models attained R²P and RPD of above 0.63 and 2.00, respectively, bias of less than 2.12, and RMSEP of below 10% of the average reference measurements for all the parameters. The findings indicated that a portable NIR spectrometer coupled with chemometrics of PLSR has the potential to serve as a quick screening tool for the efficient, accurate, and non-invasive assessment of parameters defining the quality of BFP.