Plant proteins play a major role in human nutrition, especially in developing countries where it is needed to utilize proteins from all accessible food sources to curtail food and nutritional difficulties (Okpuzor et al., 2010). The cultivation of Cucumeropsis manniiseeds also known internationally as melon seed or as ‘Egushi’ (in Yoruba, Nigeria) (Fajinmi et al., 2022) or ‘Agushi’(Hausa, Ghana) (Lawal et al., 2023), is an important crop for food security in West Africa not only providing a source of income for the rural people in West African countries, but also as a source of protein and additional essential nutrients (Fajinmi et al., 2022).
Melon seeds are prepared for consumption by parching and removing the seed from the kernel which is usually milled into powder, ground into paste or molded into balls. It is used both as a condiment and a thickener which improves the flavor and palatability of foods (Arthur et al., 2020). Melon seeds are high in essential amino acids, vital micronutrients, polyunsaturated fatty acids and phenolic compounds.
Increasing demand for plant-based proteins has elicited suspicions of fraudulent practices among some producers of melon seed powder. Melon seed powder is predisposed to food adulteration in the supply chain because it is produced locally with little or no supervision or regulation by Ghanaian food regulators (Lawal et al., 2023) The powder is suspected to be adulterated with carbohydrate-rich foods including maize, dried-milled cassava (gari) and soy flour to boost its quantity for increased profit. This conversely causes digestive problems and allergic reactions among consumers and food sellers incur losses from low-standard foods prepared from such products (FDA, 2015).
Current methods for authenticating foods are laborious and time consuming necessitating rapid and reliable techniques for detecting adulteration in foods. Spectroscopic techniques combined with multivariate data analysis methods form a promising strategy to overcome the drawbacks and can effectively be used to detect adulteration of different food products (Mozhayeva et al., 2014).This study therefore seeks to develop models to rapidly detect and quantify adulterants in powdered melon seed samples using a handheld NIR spectrometer. The study employs visualization, classification models, and regression techniques to predict dried cassava flour (gari), soybean and maize in melon seed powder.
Melon seed powder samples containing 0–50 %w/w maize, gari and soy were prepared in triplicates and scanned using a handheld NIRS device. Physicochemical analysis such as proximate and colour were conducted on the samples after which they were analysed using NIRS with chemometrics. Proximate composition and color were significantly (p<0.05) affected by adulterant presence in melon seed powder. Classification models using linear discriminant analysis yielded accuracies of adulterant classification that were further confirmed by the high sensitivity, specificity and precision of the models (higher than 80 % in all cases).
Low errors (RMSEC 3.28, RMSECV 3.92, RMSEP 6.87) % w/w, limits of detection and quantification and high coefficients (R2 0.96, R2CV 0.94, R2PRED 0.81) % w/w, indicative of reliable partial least squares models were obtained for the prediction of adulterants, protein, carbohydrate, total colour change, fat and lightness.
Overall, Savitisky-Golay smoothing filter yield the best results in all LDA analysis. NIRS is a viable option for rapid non-invasive authentication of melon seed powder. The handheld device presents an added advantage of remote analysis. Instruments with other wavelength ranges can be explored in a similar approach study but with a higher sample size for more rigorous applications.
댓글