Rapid Determination of Nutmeg Shell Content in Ground Nutmeg Using FT-NIR Spectroscopy and Machine Learning

Area of Science:

• Food Science
• Analytical Chemistry
• Spectroscopy

Background:

• Ground nutmeg is vulnerable to adulteration due to its widespread use.
• Detecting adulterants like nutmeg shell is crucial for ensuring spice authenticity.

Purpose of the Study:

• To develop and validate a method for detecting nutmeg shell in ground nutmeg.
• To assess the efficacy of Fourier transform near-infrared (FT-NIR) spectroscopy for this purpose.

Main Methods:

• Analysis of authentic nutmeg and nutmeg shell samples using FT-NIR spectroscopy.
• Chemometric analysis, including principal component analysis (PCA) and support vector machine regression (SVM).
• Quantification of shell content in mixtures ranging from 0% to 50%.

Main Results:

• PCA demonstrated clear separation based on shell content.
• SVM regression achieved a high coefficient of determination (R² = 0.944) for predicting shell content.
• The prediction model exhibited a limit of detection of 1.5% nutmeg shell.

Conclusions:

• FT-NIR spectroscopy is a suitable technique for the rapid detection and quantification of nutmeg shell adulteration.
• The developed method ensures the quality and authenticity of ground nutmeg products.