Abstract
Rice is a staple food in Vietnam, and the concern about rice is much greater than that for other foods. Preventing fraud against this product has become increasingly important in order to protect producers and consumers from possible economic losses. The possible adulteration of this product is done by mixing, or even replacing, high-quality rice with cheaper rice. This highlights the need for analytical methodologies suitable for its authentication. Given this scenario, the present work aims at testing a rapid and non-destructive approach to detect adulterated rice samples. To fulfill this purpose, 200 rice samples (72 authentic and 128 adulterated samples) were analyzed by near infrared (NIR) spectroscopy coupled, with partial least squares-discriminant analysis (PLS-DA) and soft independent modeling of class analogies (SIMCA). The two approaches provided different results; while PLS-DA analysis was a suitable approach for the purpose of the work, SIMCA was unable to solve the investigated problem. The PLS-DA approach provided satisfactory results in discriminating authentic and adulterated samples (both 5% and 10% counterfeits). Focusing on authentic and 10%-adulterated samples, the accuracy of the approach was even better (with a total classification rate of 82.6% and 82.4%, for authentic and adulterated samples, respectively).
Highlights
Rice (Oryza sativa L.) has increasingly become a hugely important staple food worldwide, and its consumption has surged as a result of population growth, changing food preferences, and urbanization [1]
partial least squares-discriminant analysis (PLS-DA) is based on expressing the classification problem as a regression one, which can be solved by PLS [49,50,51]
PLS-DA selection was based on the combination of pre-processing and model complexity leading to the lowest mean classification error, whereas for soft independent modeling of class analogies (SIMCA) the maximum efficiency was sought
Summary
Rice (Oryza sativa L.) has increasingly become a hugely important staple food worldwide, and its consumption has surged as a result of population growth, changing food preferences, and urbanization [1]. Vietnam is among the top-five leading net exporters of rice and, while quantity is no longer the main problem, high quality is important to serve the high-end market segments. The export market, and the domestic market is facing the same problem: high volume but low value. It is estimated that more than 130 different types of rice brand exist on the market, and no brand accounts for more than 3% of the market. This means that Vietnam’s rice market is considered as “fragmented”, and only a few businesses have a clear vision for branding
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