Application of image analysis combined with regression models to estimate the reduction of Escherichia coli and Salmonella spp. on vegetable surfaces after washing

Escherichia coli, a bacterium indicating improper hygiene practices during food production, is commonly found in the intestines of humans and animals, while Salmonella spp. are dangerous bacteria that cause typhoid fever and severe diarrhea. These pathogens have been found in fresh vegetables. This study investigated how the vegetable surface characteristics influenced bacterial adhesion. The reduction of bacteria during the washing process was assessed using different concentrations and types of chemicals. The relationships between variables obtained from image analysis techniques and bacterial adhesion on vegetable surfaces were also evaluated. The most effective way to inhibit bacteria was by washing with 2.0% lactic acid, with bacterial reduction from an initial concentration of 8.74 to 2.92 log CFU/m<sup>2</sup>. Pearson's correlation with the highest r value was surface area (A) with values ranging from 0.764 to 0.993, followed by surface roughness (R) with values between 0.019 and 0.986, and Fractal dimension (FD) with values between - 0.510 and - 0.992. The correlation between A and the number of bacteria (E. coli and Salmonella) was the highest, with surface area influencing bacterial adhesion to the vegetable surface. Greater surface roughness was associated with a higher initial bacterial load, making the A value a good predictor of changes in bacteria during washing with organic acids at various concentrations.

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Journal
Bioresources and Bioprocessing
Published
2026-01-05
DOI
https://doi.org/10.1186/s40643-025-00992-4
Primary Topic
Bacterial biofilms and quorum sensing
Type
article
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article

Application of image analysis combined with regression models to estimate the reduction of Escherichia coli and Salmonella spp. on vegetable surfaces after washing

Chanthima Phungamngoen, Yardfon Tanongkankit, Nattavong Fuangpaiboon, Natthawuddhi Donlao et al.
Bioresources and Bioprocessing
Bacterial biofilms and quorum sensing
article

Application of image analysis combined with regression models to estimate the reduction of Escherichia coli and Salmonella spp. on vegetable surfaces after washing

Chanthima Phungamngoen, Yardfon Tanongkankit, Nattavong Fuangpaiboon, Natthawuddhi Donlao, Utthapon Issara, Jinhu Tian, Lovedeep Kaur, Farida Chengsa-ard, Jaspreet Singh, Pimnibha Hirunsorn, Thanakorn Rojanakorn
article en

Abstract

Escherichia coli, a bacterium indicating improper hygiene practices during food production, is commonly found in the intestines of humans and animals, while Salmonella spp. are dangerous bacteria that cause typhoid fever and severe diarrhea. These pathogens have been found in fresh vegetables. This study investigated how the vegetable surface characteristics influenced bacterial adhesion. The reduction of bacteria during the washing process was assessed using different concentrations and types of chemicals. The relationships between variables obtained from image analysis techniques and bacterial adhesion on vegetable surfaces were also evaluated. The most effective way to inhibit bacteria was by washing with 2.0% lactic acid, with bacterial reduction from an initial concentration of 8.74 to 2.92 log CFU/m<sup>2</sup>. Pearson's correlation with the highest r value was surface area (A) with values ranging from 0.764 to 0.993, followed by surface roughness (R) with values between 0.019 and 0.986, and Fractal dimension (FD) with values between - 0.510 and - 0.992. The correlation between A and the number of bacteria (E. coli and Salmonella) was the highest, with surface area influencing bacterial adhesion to the vegetable surface. Greater surface roughness was associated with a higher initial bacterial load, making the A value a good predictor of changes in bacteria during washing with organic acids at various concentrations.

Bioresources and BioprocessingVol. 13(1)
Rajamangala University of Technology (TH), Khon Kaen University (TH), Maejo University (TH), Mae Fah Luang University (TH), Riddet Institute (NZ), Massey University (NZ), Zhejiang University (CN)
Zero hunger
Openalex Percentile: Top 97%
Bacterial biofilms and quorum sensing
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