Development of a visible/near-infrared spectroscopic system with unique software for rapid and non-destructive detection of nitrate-contaminated leafy and fruity vegetables

• A system with software was developed to detect nitrate-contaminated vegetables. • It had good results for prediction of nitrate content in both spinach and cucumber. • It had excellent results for screening spinach based on maximum nitrate limits. • It is possible to add other models for other vegetables to the designed software. A visible/near-infrared (Vis/NIR) spectroscopic system with unique software was developed for rapid and non-destructive detection of nitrate-contaminated vegetables (spinach and cucumber). The system included a spectral measurement unit to collect Vis/NIR spectra of vegetable samples. Another part of the system was models developed for prediction of nitrate content in the samples. The system also included models developed for discrimination against unsafe vegetables from safety samples based on standard maximum nitrate level limit. User-friendly software was also designed for the system as a graphical user interface based on the models developed for each type of vegetable. This software can readout, pre-process, and analyze the spectral data on-line, as well as represent the results rapidly. Evaluation of system performance indicated excellent results for screening unknown spinach samples (accuracy = 92.31%, sensitivity = 100%). The system was also able to predict nitrate concentrations in samples well with a prediction correlation coefficient (r p ) of 0.75, a standard error of prediction (SEP) of 685.45, and a ratio of performance to deviation (RPD) of 1.52. The designed system had acceptable performance for screening the unknown cucumbers (accuracy = 72.22%, sensitivity = 76.74%) and good results for prediction of nitrate concentration in the samples (r p = 0.87, SEP = 60.92, RPD = 2.07). Consequently, the developed system is suitable for fast, low-cost and non-destructive preliminary screening such vegetables in terms of nitrate contamination.

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Publication Details

Journal
Measurement Food
Published
2025-12-23
DOI
https://doi.org/10.1016/j.meafoo.2025.100274
Primary Topic
Spectroscopy and Chemometric Analyses
Type
article
Field-Weighted Citation Impact
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article

Development of a visible/near-infrared spectroscopic system with unique software for rapid and non-destructive detection of nitrate-contaminated leafy and fruity vegetables

Bahareh Jamshidi, Najmeh Yazdanfar, Jamshid Jamshidi
Measurement Food
Spectroscopy and Chemometric Analyses
article

Development of a visible/near-infrared spectroscopic system with unique software for rapid and non-destructive detection of nitrate-contaminated leafy and fruity vegetables

Bahareh Jamshidi, Najmeh Yazdanfar, Jamshid Jamshidi
article en

Abstract

• A system with software was developed to detect nitrate-contaminated vegetables. • It had good results for prediction of nitrate content in both spinach and cucumber. • It had excellent results for screening spinach based on maximum nitrate limits. • It is possible to add other models for other vegetables to the designed software. A visible/near-infrared (Vis/NIR) spectroscopic system with unique software was developed for rapid and non-destructive detection of nitrate-contaminated vegetables (spinach and cucumber). The system included a spectral measurement unit to collect Vis/NIR spectra of vegetable samples. Another part of the system was models developed for prediction of nitrate content in the samples. The system also included models developed for discrimination against unsafe vegetables from safety samples based on standard maximum nitrate level limit. User-friendly software was also designed for the system as a graphical user interface based on the models developed for each type of vegetable. This software can readout, pre-process, and analyze the spectral data on-line, as well as represent the results rapidly. Evaluation of system performance indicated excellent results for screening unknown spinach samples (accuracy = 92.31%, sensitivity = 100%). The system was also able to predict nitrate concentrations in samples well with a prediction correlation coefficient (r p ) of 0.75, a standard error of prediction (SEP) of 685.45, and a ratio of performance to deviation (RPD) of 1.52. The designed system had acceptable performance for screening the unknown cucumbers (accuracy = 72.22%, sensitivity = 76.74%) and good results for prediction of nitrate concentration in the samples (r p = 0.87, SEP = 60.92, RPD = 2.07). Consequently, the developed system is suitable for fast, low-cost and non-destructive preliminary screening such vegetables in terms of nitrate contamination.

Measurement FoodVol. 21
Chemistry and Chemical Engineering Research Center of Iran (IR), Agricultural Research & Education Organization (IR), Agricultural Biotechnology Research Institute of Iran (IR)
Peace, Justice and strong institutions
Openalex Percentile: Top 42%
Spectroscopy and Chemometric Analyses
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