Rice Labeling according to Grain Quality Features Using Laser-Induced Breakdown Spectroscopy

Area of Science:

• Analytical Chemistry
• Spectroscopy
• Agricultural Science

Background:

• Rice quality inspection is vital for consumer protection and market value.
• Current visual and image-based methods for rice quality assessment are subjective and inefficient for large-scale analysis.
• Laser-induced breakdown spectroscopy (LIBS) provides rapid elemental composition analysis, offering a potential objective alternative.

Purpose of the Study:

• To evaluate the performance of Laser-induced breakdown spectroscopy (LIBS) for objective rice grain quality labeling.
• To develop and optimize a LIBS-based classification model for different rice quality types.
• To compare the accuracy and efficiency of LIBS against traditional quality inspection methods.

Main Methods:

• Collected LIBS spectra from rice samples numerically classified as Type 1, 2, and 3.
• Applied various spectral processing techniques, including smoothing and normalization.
• Utilized k-nearest neighbors (k-NN) classification, incorporating principal component analysis (PCA) for variable selection and optimal k-value determination.

Main Results:

• The optimized LIBS method, using spectrum smoothing, normalization, and the first fifteen principal components (PCs) with k=9, achieved 94% overall prediction accuracy.
• The classification model demonstrated high performance with sensitivities ranging from 90% to 100% and specificities from 92% to 100%.
• The LIBS approach proved to be objective, avoiding the subjectivity inherent in visual inspection methods.

Conclusions:

• LIBS is a highly effective and objective analytical technique for classifying rice grain quality.
• The developed LIBS-based method offers significant advantages in terms of speed and accuracy over conventional inspection techniques.
• This rapid, chemical-response-guided analysis enhances the reliability of rice quality assessment in the food industry.