Recently, CNIS expert Dr. Ma Shaojin published a paper titled Classification of oatmeal residue levels on bowls using fluorescence imaging: Toward an intelligent method for assessing dishwasher cleaning performance was published in the internationally renowned journal Food Research International.
The ability of dishwashers to remove food soiling poses an important challenge for food safety, which is directly related to the classification of energy and water efficiency grades of dishwashers. Currently, the cleaning performance index (CPI) relies on subjective visual inspection. The method has problems such as individual bias and poor reproducibility.
Therefore, the research team introduced a fluorescence imaging-based method. Rice bowls soiled with oat flakes-made porridge were selected as the target to be tested. The excitation-emission matrix (EEM) analysis identified an optimal 365-nm excitation wavelength for fluorescence imaging, and the You Only Look Once (YOLO) and Focal Modulation-YOLO (FM-YOLO)-based recognition model was established. The model showed that the Blue-channel after chromatic adaptation (CA_Bchannel) performed best. Compared to YOLO, FM-YOLO demonstrates superior performance in key indicators, such as precision rate, and recall rate. A correction method was proposed to eliminate the influence of the bowl-shaped surface on the calculation of the soiled area, and based on this, a cleaning performance evaluation method was established using the soiling area obtained by FM-YOLO. This study provides scientific basis and technical support for the precise classification of energy and water efficiency grades of dishwashers.
The Food Research International is an internationally renowned journal in the field of food engineering, focusing on significant novel and high impact research in food science, technology, engineering and nutrition. It is among the Tier 1 journals in the science journal ranking system of the Chinese Academy of Sciences, with an impact factor of 8.
Dr. Ma Shaojin is from the Key Laboratory of Energy Efficiency, Water Efficiency and Greenization of State Administration for Market Regulation (SAMR), and the Branch of Resource and Environment Standardization of CNIS. This research was supported by SAMRs science and technology program and CNISs self-funded research project. The corresponding author is CNIS Researcher Bai Xue.