Quality evaluation of tender jackfruit using near-infrared reflectance spectroscopy

Abstract

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

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近红外反射光谱法评价菠萝蜜品质

鲜嫩菠萝蜜（Artocarpus heterophyllus L.）因其固有的营养和健康益处而广受欢迎。对于涉及嫩菠萝蜜增值的行业来说，原料的快速表征对于筛选和常规质量评估至关重要。但是，传统的质量评估参考方法并不适用，因为它们涉及化学品的使用，昂贵、费力且耗时，取决于要分析的样本数量。作为一种很有前途的替代方法，本研究考察了近红外光谱（NIRS）作为一种新的方法来评估菠萝蜜的pH、总可溶性固体、可滴定酸度、硬度和韧性的性能。采用偏最小二乘回归（PLSR）模型建立了鲜嫩菠萝蜜反射光谱（1100-2450nm）与品质属性之间的联系。根据残差预测偏差（RPD）标准，可滴定酸度的PLSR模型的准确度非常好（RPD=3.96），而在硬度卷须的情况下（RPD=2.61）可能有良好的估计。在总可溶性固体的情况下，适用于粗略定量估计的准确度水平（RPD=2.12）。发现所有其他属性的PLSR模型能够区分其低值和高值（1.5

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