Determination of semolina adulteration by NIR spectroscopy

Oblitas-Cruz J.; Cieza-Rimarachin Y.; Castro-Silupu W. · Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology (2022) · DOI: 10.18687/laccei2022.1.1.69

Resumen

The objective was to implement a semolina percentage recognition system using near-infrared spectroscopy (NIR) and multivariate data analysis. For this purpose, 6 samples were analyzed with different percentages of semolina(20, 40, 60, 80 and 100 %). Samples were repeated 20 times. The observed NIR spect rum was absorbance in the range of 1100 and 2500 nm. In order to reduce the data, the analysis of main components was used by testing 24 classification models, from whichthe one that reached the highest level of precision was the Linear Support Vector Machine (SVM) algorithm, reaching 98.8%, achieving fairly satisfactorydiscrimination with values of PC1 (99.7%), PC2 (0.3%) and PC3 (0.1%), reaching a total cumulative variation of the contribution of the first 3 P Cs of 99.9%. Partial Least Regression (PLS) models applied to NIR-spectra showed R2 between 0.9388. These values demonstrated that NIR spectroscopy can be used for the identification and quantification of fiber added to semolina.

Instituciones: Universidad Nacional de Cajamarca; Universidad Nacional de Frontera; Universidad Privada del Norte