Microbial Contamination Assessment of Lettuce using NIR Hyperspectral Imaging: Case Study on Escherichia coli

Document Type : Research Paper


1 Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, University College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran

2 Agricultural Engineering Research Institute, Agricultural Research Education and Extension Organization (AREEO), Karaj, Iran


Development of non-destructive detection methods to rapidly assess the safety of agricultural products in terms of microbial contamination due to the increasing demand for safe ones is very important. In this research, a non-destructive optical method based on NIR hyperspectral imaging with (PLS-DA) method for rapid detection of microbial contaminated lettuce class (contaminated with Escherichia coli) from control class (with no contamination) was developed. To this end, dimensionality reduction (Spatial preprocessing) and spectral preprocessing were performed using (PCA) and Standard Normal Variate (SNV) with Mean Centering (MC) methods. The results of PLS-DA analysis showed the good ability in classification of control class and contaminated ones with different microbial population with high accuracy of 90% and class error of 0.008. Besides, the spectral region of 1400 to 1500 nm and the wavelength of 1200 nm were selected as the most important wavelengths that provide the most information for target identification and group classification using Variable Importance in Projection (VIP) score of the loading plot for PLS-DA. In general, the result showed that the NIR hyperspectral imaging method with PLS-DA analysis could be a fast and accurate method for real-time and non-destructive detection of microbial contamination in lettuce samples and classification of different classes (safe and contaminated).


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