Discrimination of rice varieties using smartphone-based colorimetric sensor arrays and gas chromatography techniques.

• A low-cost smartphone-based colorimetric sensor array system was fabricated. • Volatile compounds of rice varieties were identified using GC–MS. • Sensor array system and SPME-GC–MS were able to effectively differentiate rice varieties. • Developed system could offer a viable option for field applications of laboratory-based smart technique. A smartphone-based colorimetric sensor array system was established for discrimination of rice varieties having different geographical origins. Purposely, aroma profiling of nine rice varieties was performed using solid-phase microextraction gas chromatography-mass spectrometry. Alcohols, aldehydes, alkanes, ketones, heterocyclic compounds, and organic acids represent the abundant compounds. Colorimetric sensor array system produced a characteristic color difference map upon its exposure to volatile compounds of rice. Discrimination of rice varieties was subsequently achieved using principal component analysis, hierarchical clustering analysis, and k-nearest neighbors. Rice varieties from same geographical source were clustered together in the scatter plot of principal component analysis and hierarchical clustering analysis dendrogram. The k-nearest neighbors algorithm delivered optimal results with discrimination rate of 100% for both calibration and prediction sets using sensor array system. The smartphone-based colorimetric sensor array system and gas chromatography technique were able to effectively differentiate rice varieties with the advantage of being simple, rapid, and low-cost. [ABSTRACT FROM AUTHOR]