Method and system for chromogenic array-based food testing
Inventors
ZHANG, BOCE • Yu, Hengyong • Luo, Yaguang • Liu, Xiaobo
Assignees
US Department of Agriculture USDA • University of Massachusetts Amherst
Publication Number
US-12265073-B2
Publication Date
2025-04-01
Expiration Date
2039-11-05
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Abstract
A chromogenic assay includes a substrate comprising an array of 5 or more dyes which react with volatile organic compounds, wherein the dyes are chromogenic when reacted with volatile organic chemical biomarkers, wherein the volatile organic chemical biomarkers comprise acids, alcohols, aldehydes, alkenes, amines, antioxidants, aromatic compounds, esters, ethylene, lactones, ketones, organosulfur compounds, sulfides, reactive oxygen species, terpenes, or a combination thereof. A method of detecting volatile organic chemical biomarkers includes contacting the chromogenic assay with a sample or sample headspace, wherein the sample or sample headspace is suspected of containing volatile organic chemical biomarkers, and identifying, based on a colorimetric pattern on the chromogenic assay after contacting, the source of the volatile organic chemical biomarkers. Also included are articles and systems including the chromogenic assay.
Core Innovation
The invention is a chromogenic assay comprising a substrate with an array of 5 or more dyes that react with volatile organic chemical (VOC) biomarkers. These dyes are chromogenic upon reaction with VOCs such as acids, alcohols, aldehydes, alkenes, amines, antioxidants, aromatic compounds, esters, ethylene, lactones, ketones, organosulfur compounds, sulfides, reactive oxygen species, and terpenes. The assay detects these biomarkers by producing distinct colorimetric patterns, enabling identification of sources of VOCs.
The invention further includes methods of detecting VOC biomarkers by contacting the chromogenic assay with a sample or its headspace suspected of containing the VOCs, and identifying, based on the observed colorimetric pattern, the source of the biomarkers. Additionally, the invention comprises articles incorporating the chromogenic assay and systems that integrate the assay with machine learning databases and algorithms for automated pattern recognition and analysis.
The problem addressed arises from significant challenges in food security related to food safety and post-harvest food waste, both largely impacted by microorganisms. Existing methods for viable pathogen detection in food are time-consuming, limited in multiplex detection without customization, and generally unsuitable for continuous, non-destructive surveillance. Additionally, current technologies have difficulty accurately quantifying viable pathogens and differentiating among complex VOC background from food matrices and physiological changes, resulting in unreliable detection. There is an urgent need for cost-effective, versatile, and user-friendly technologies that provide rapid, multiplex, and accurate detection and quantification of viable pathogens and monitor food quality and spoilage.
Claims Coverage
The claims include two independent claims covering a chromogenic assay and a method of detecting volatile organic chemical biomarkers using the assay. The inventive features focus on the composition of the assay and its method of use.
Chromogenic assay with a specific array of dyes
A chromogenic assay comprising a substrate with an array of 10 or more dyes which react with volatile organic chemical (VOC) biomarkers. Each dye is chromogenic upon reaction with VOCs including acids, alcohols, aldehydes, alkenes, amines, antioxidants, aromatic compounds, esters, ethylene, lactones, ketones, organosulfur compounds, sulfides, reactive oxygen species, and terpenes. The dye array specifically includes 2,4-dinitrophenylhydrazine (phenylhydrazine), 4,4′-azodianiline (dianiline), pararosaniline (fuchsine), bromophenol blue, nitrazine yellow, chlorophenol red, Tollen's reagent, Benedict's reagent, zinc nitrate, and sodium nitroprusside.
Method of detecting volatile organic chemical biomarkers
A method comprising contacting the chromogenic assay with a sample or sample headspace suspected of containing VOC biomarkers and detecting the VOC biomarkers based on a colorimetric pattern developed on the assay after contact.
The claims collectively cover the composition of a chromogenic assay with a defined array of dyes that respond to a broad spectrum of VOC biomarkers and a method utilizing the assay for detecting and identifying VOC sources via colorimetric patterns.
Stated Advantages
Enables rapid and accurate detection and quantification of viable pathogens in food matrices.
Allows multiplex detection of multiple microbial contaminants without the need for customization of recognition elements.
Suitable for downstream non-destructive and continuous surveillance and monitoring of food safety and quality.
Capable of differentiating microbial pathogens at strain-level fidelity and detecting very low microbial loads under different storage temperatures, including refrigeration.
Integration with machine learning algorithms provides automated pattern recognition to improve accuracy, reduce human error, and enable end-user applications such as consumer point-of-care testing.
Can monitor physiological changes in food due to ripening, aging, or environmental factors, thus enabling comprehensive food quality assessment and spoilage monitoring.
The chromogenic assay does not require direct contact with food, minimizing safety concerns even when some dyes are toxic.
Documented Applications
Detection and multiplex quantification of viable foodborne pathogens in liquid media, solid media, and real food matrices.
Continuous and on-demand monitoring of food quality and safety including pathogen detection, probiotic status monitoring, and authenticity verification of fermented or aged foods and beverages.
Monitoring temperature abuse history of packaged fresh produce and foods in supply chains to prevent spoilage and outbreaks.
Preharvest monitoring of diseases and pathogens on edible plants, livestock, and poultry.
Postharvest monitoring in climate-controlled shipping containers, storage facilities, and various packaging formats including modified atmosphere packaging.
Integration with machine learning and smartphone technology for automated, user-friendly detection and quantification in industrial QA/QC and consumer point-of-care testing.
Quality monitoring and physiological state assessment of fresh produce, climacteric produce, meat, poultry, seafood, spices, dairy, grain, eggs, and beverages.
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