Quality evaluation of tender jackfruit using near-infrared reflectance spectroscopy

Value addition of fresh tender jackfruit (Artocarpus heterophyllus L.) for vegetable purpose has gained much popularity due to its inherent nutritional and health benefits. For industries involved in value addition of tender jackfruit, rapid characterization of raw material is essential for screening and routine quality evaluation. But, conventional reference methods of quality evaluation are not suitable as they involve the use of chemicals, expensive, laborious and time consuming subject to the number of samples to be analyzed. As a promising alternative, the present study examined the performance of near-infrared spectroscopy (NIRS) as a novel approach to estimate pH, total soluble solid, titrable acidity, firmness and toughness of tender jackfruit. Partial least square regression (PLSR) models were used to establish linkage between reflectance spectra (1100-2450 nm) and quality attributes of fresh tender jackfruit. Based on residual prediction deviation (RPD) criteria, accuracy of PLSR model of titrable acidity was noted to be excellent (RPD=3.96) while good estimation was possible in case of firmness-tendril (RPD=2.61). Accuracy level suitable for coarse quantitative estimation (RPD=2.12) was noted in case of total soluble solids. The PLSR models of all other attributes were found to be capable of discriminating their low and high values (1.5