Innovation Owner
Mr. CHISANUPONG FURAT
Student
Details
This research utilizes Near-Infrared Spectroscopy (FT-NIR) to detect adulteration and classify the storage age of Khao Dawk Mali 105 rice. The developed models achieved 96.3% accuracy in age classification and demonstrated high predictive capability for adulteration levels.
This research aims to investigate the adulteration of Khao Dawk Mali 105 rice based on storage age using Near-Infrared Spectroscopy (NIRS) with Fourier Transform Near-Infrared Spectroscopy (FT-NIR) in the wavenumber range of 12,500 – 4,000 cm-1 (800 – 2,500 nm). Storage duration significantly impacts the quality of cooked rice. This research is divided into two parts:
- Separation by storage age: Investigating the feasibility of separating rice according to storage age (1, 2, and 3 years). The best model, created using an Ensemble method combined with Second Derivative, achieved an accuracy of 96.3%.
- Adulteration investigation: Investigating adulteration levels from 0% to 100%. The best model was created using Gaussian Process Regression (GPR) combined with Smoothing + Multiplicative Scatter Correction (MSC), with coefficients of determination (r²) of 0.92, RMSEP of 8.6%, bias of 0.9%, and prediction ability (RPD) of 3.6.
This demonstrates that the adulteration model can be applied to separate rice by storage age. Additionally, the color values of rice with different storage ages show differences in L* and b* values.
Objective
The objectives are to apply NIRS techniques to classify Khao Dawk Mali 105 rice by storage age (1, 2, and 3 years) and to predict the percentage of adulteration between rice of different storage ages.
- To apply NIRS techniques to classify groups of KDML 105 rice based on storage ages of 1, 2, and 3 years.
- To apply NIRS techniques to predict the percentage of adulteration in KDML 105 rice between 1-year-old rice and 2-year-old rice, as well as between 1-year-old rice and 3-year-old rice.