Droplet digital <scp>PCR</scp> for detection of allergenic peanut in food ingredients

Abstract Background Peanut is regulated as a major food allergen in the United States. Food products containing peanut must be labeled according to the Food, Drug, and Cosmetics (FD&amp;C) Act, and accurate labeling requires effective detection methods. Polymerase chain reaction (PCR)‐based methods are highly sensitive, specific, and robust for this purpose. Digital PCR is the latest generation of PCR technology and offers potential advantages over more established PCR techniques, but very few studies report the evaluation of digital PCR for use in food allergen detection. Results In this work, a multiplex digital PCR assay was evaluated for the detection of peanut in food ingredients at levels ranging from 0.1 mg/kg (ppm) to 10 6 mg/kg (100% peanut), and it was compared to a real‐time PCR assay. Both digital and real‐time PCR detected peanut effectively at all levels in all food ingredients. Digital PCR had limits of detection (LOD) at 0.1 mg/kg for all three targets and limits of quantification (LOQ) at 1–10 mg/kg depending on the target. Real‐time PCR had LOD at 0.1–10 mg/kg depending on the target, and LOQ at 100 mg/kg. Conclusions Digital PCR was both more precise and more sensitive than real‐time PCR for detection of peanut spiked into food ingredients. While more testing is needed to determine the relative effects of complex food matrices and processing, these early results show that digital PCR is an innovative method that can help ensure chemical food safety through sensitive, precise detection of DNA from allergenic foods such as peanut.

Authors

Institutions

Publication Details

Journal
JSFA reports
Published
2025-06-19
DOI
https://doi.org/10.1002/jsf2.70013
Citations
1
Primary Topic
Biosensors and Analytical Detection
Type
article
Field-Weighted Citation Impact
0.67

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Droplet digital PCR for detection of allergenic peanut in food ingredients

Anne C. Eischeid
1 citations
JSFA reports
Biosensors and Analytical Detection
0.67
article

Droplet digital PCR for detection of allergenic peanut in food ingredients

Anne C. Eischeid
article en
1 citations

Abstract

Abstract Background Peanut is regulated as a major food allergen in the United States. Food products containing peanut must be labeled according to the Food, Drug, and Cosmetics (FD&amp;C) Act, and accurate labeling requires effective detection methods. Polymerase chain reaction (PCR)‐based methods are highly sensitive, specific, and robust for this purpose. Digital PCR is the latest generation of PCR technology and offers potential advantages over more established PCR techniques, but very few studies report the evaluation of digital PCR for use in food allergen detection. Results In this work, a multiplex digital PCR assay was evaluated for the detection of peanut in food ingredients at levels ranging from 0.1 mg/kg (ppm) to 10 6 mg/kg (100% peanut), and it was compared to a real‐time PCR assay. Both digital and real‐time PCR detected peanut effectively at all levels in all food ingredients. Digital PCR had limits of detection (LOD) at 0.1 mg/kg for all three targets and limits of quantification (LOQ) at 1–10 mg/kg depending on the target. Real‐time PCR had LOD at 0.1–10 mg/kg depending on the target, and LOQ at 100 mg/kg. Conclusions Digital PCR was both more precise and more sensitive than real‐time PCR for detection of peanut spiked into food ingredients. While more testing is needed to determine the relative effects of complex food matrices and processing, these early results show that digital PCR is an innovative method that can help ensure chemical food safety through sensitive, precise detection of DNA from allergenic foods such as peanut.

JSFA reportsVol. 5(9)
United States Food and Drug Administration (US)
U.S. Food and Drug Administration
Openalex Percentile: Top 30%
Biosensors and Analytical Detection
0.67
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.