Fumonisin in Tortillas Produced in Small-Scale Facilities and Effect of Traditional Masa Production Methods on This Mycotoxin
Bibliographic record
Abstract
Four small tortilla plants were visited in Cameron County, Texas, where observations were made on their production methods. Samples of liquids and solids were collected at each stage of the nixtamalization process, and the pH was recorded. Samples were analyzed for fumonisin B(1) (FB(1)) using an immunoaffinity column/HPLC method chosen for its sensitivity for FB(1). It was found that production methods were highly variable among the producers visited, with major differences particularly in the amount of lime added and boiling times. As reported by others working in Mexico and Central America, FB(1) was found in some tortillas. This led to studies of the effects of the various recipes and across a greater range of initial FB(1) concentration/damaged corn than has typically been reported. Five initial concentrations of FB(1) were tested using irradiated corn kernels inoculated with Fusarium verticillioides MRC 826 as the source of FB(1). The amount of FB(1) detected in the masa and tortillas decreased as the concentration of Ca(OH)(2) increased, and boiling time had no apparent effect. Unexpectedly, as the initial concentrations were increased in the corn prior to nixtamalization, greater percentage reductions in FB(1) were observed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".