Feasibility study on quantification and authentication of the cassava starch content in wheat flour for bread-making using NIR spectroscopy and digital images

This works proposed a feasibility study on NIR spectroscopy and chemometrics-assisted color histogram-based analytical systems (CACHAS) to determine and authenticate the cassava starch content in wheat flour. Prediction results of partial least squares (PLS) achieved coefficient of correlation (r(pred)) of 0.977 and root mean square error of prediction (RMSEP) of 1.826 mg kg(-1) for the certified additive-free wheat flour, while r(pred) of 0.995 and RMSEP of 1.004 mg kg(-1) were obtained for the commercial wheat flour containing chemical additives. Additionally, Data-Driven Soft Independent Modelling of Class Analogy (DD-SIMCA) presented similar predictive ability using NIR and CACHAS for the certified wheat flour, authenticating all target samples, besides correctly recognizing samples that could represent a fraud. No satisfactory results were obtained for the commercial wheat flour. Therefore, NIR spectroscopy is more useful to offer definitive quantitative and qualitative analysis, while CACHAS can only provide an alternative preliminary analysis.

Automated summary

The study showed that NIR spectroscopy and CACHAS can be used to determine the cassava starch content in wheat flour, with NIR spectroscopy being more suitable for definitive quantitative and qualitative analysis, while CACHAS can only provide an alternative preliminary analysis.