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Determination of semolina adulteration by NIR spectroscopy

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Date of Conference

July 18-22, 2022

Published In

"Education, Research and Leadership in Post-pandemic Engineering: Resilient, Inclusive and Sustainable Actions"

Location of Conference

Boca Raton


Oblitas, Jimy

Cieza, Yuleyci

Castro, Wilson


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 spectrum 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 which the one that reached the highest level of precision was the Linear Support Vector Machine (SVM) algorithm, reaching 98.8%, achieving fairly satisfactory discrimination 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 PCs 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.

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