Related Experiment Video
Updated: Jul 13, 2025
Chemical Analysis of Water-accommodated Fractions of Crude Oil Spills Using TIMS-FT-ICR MS
Published on: March 3, 2017
A method to assess industrial paraffin contamination levels in rice and its transferability analysis based on
Zhentao Wang1, Ruidong Wang2, Yuhang Chu1
1College of Engineering, Northeast Agricultural University, Harbin 150030, China; Heilongjiang Provincial Key Laboratory of Modern Agricultural Equipment Technology in Northern Cold Regions, Harbin 150030, China.
Abstract:
Accurate assessment of industrial paraffin contamination levels (IPCLs) in rice is critical for food safety. However, time-consuming and labor-intensive experiments to produce labels for targeted adulterated rice have hindered the development of IPCL estimation methods. In this paper, a transfer learning method (TCA-LSSVR) has been developed. The algorithm integrates transfer component analysis (TCA) with domain adaptive capabilities to produce accurate estimates. Rice from 7 different regions and 3 industrial paraffins were used to generate 4,680 samples from 9 datasets for benchmarking. The test results showed that the established algorithm achieved good estimation performance in various modelling strategies, and only 20 % of off-site samples were needed to supplement the source dataset, the average determination coefficient R2 reached 0.7045, the average RMSE reached 0.140 %, and the average RPD reached 2.023. This work highlights the prospect of rapidly developing a new generation of adulteration detection algorithms using only previous trial data.
