Evaluating a rapid enzymatic assay vs. ultra-high performance liquid chromatography for free asparagine determination in pea and lentil seeds
Bibliographic record
Abstract
Acrylamide, a class 2 A carcinogen, raises significant food safety concerns. The free amino acid asparagine (ASN) is a precursor of acrylamide formation in foods after high-temperature processing; therefore, accurate measurement of free ASN is essential for risk assessment. This study aimed to compare free ASN determination methods, using a novel rapid enzymatic assay with an established ultra-high-performance liquid chromatography (UHPLC) method, in seeds of field pea ( Pisum sativum L.) and lentil ( Lens culinaris ), important crops and sources of plant-based protein. Quality parameters, such as sensitivity, percentage error, and precision were evaluated. The rapid enzymatic assay demonstrated consistent low percentage error (< 1.7 %) and high precision (CV% < 1.20) compared to the UHPLC technique (error from 4.9 % to 14.8 % and CV% < 0.94). A high Pearson correlation ( r > 0.996) between techniques confirmed the enzymatic assay’s reliability for routine asparagine quantification in simple laboratory and industrial settings. These findings support the potential of using a reliable, rapid, and user-friendly technique that eliminates the requirements of sophisticated instrumentation and complex sample preparation for free ASN analysis, and underscore the need for further research on pulse flour to manage acrylamide risks effectively in processed foods. • Free asparagine (ASN) is a marker for acrylamide risks in processed products. • Novel enzymatic assay effectively measures free ASN in field peas and lentils. • Enzymatic method shows high precision and sensitivity, comparable to UHPLC. • High correlation with UHPLC demonstrates reliability of the enzymatic rapid assay. • Method facilitates practical monitoring of acrylamide risk in crop samples.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".