Quantitative Determination of Ochratoxin a in Must
Bibliographic record
Abstract
For quantitative analysis of ochratoxin A in must we have used the analytical method known as HPLC-FD and previously used the immunoaffinity clean-up procedure for extraction of ochratoxin A by high immunoaffinity columns. We have determined the quantity of OTA in 30 must samples. Samples that are analyzed have been taken in the vineyards of Kosovo, concretely in southern part of Kosovo, in Rahoveci and Suhareka region. The results of all analyzed samples have been below the limit allowed by EU for ochratoxin A i.e. 2 ng/ml and as such in the future do not pose a risk to human health. The must grape represents the grape juice from which by means of certain technological processes, in particular alcoholic fermentation process created wine booze. A quantitative determination of ochratoxin A in must is very important to have in early stage of the technological process of winemaking an overview regarding the presence or not of substances dangerous to human health as is in this case the mycotoxin known as ochratoxin A. Ochratoxin A, N-[(3R)-(5-chloro-8-hydroxy-3-methyl-1-oxo-7-isochromanyl) carbonyl]-L-phenylalanine, is a mycotoxin produced by certain species of Aspergillus and Penicillium filamentous fungi. The OTA levels in must and wine depend on different factors such as the climate, the date of harvesting and different wine-making procedures. The Penicillium species that is associated with ochratoxin A production, Penicillium verrucosum, is a common storage spices and is the source of ochratoxin A in crops in the cool temperate regions such as Canada, eastern and north western Europe and parts of South America. It grows only at temperatures below 30°C and at a lower water activity. Penicillium species may produce ochratoxin at temperatures as low as 5°C (Risk Assessment Studies, http://www.cfs.gov.hk/). Aspergillus species appears to be limited to conditions of high humidity and temperature growing in the tropical and subtropical climates and is the source of contamination for coffee and cocoa beans, spices, dried vine fruit, grape juice and wine. Aspergillus ochraceus is the best known species of ochratoxin – producing Aspergillus. It grows at moderate temperatures and at a high water activity and is a significant source of ochratoxin A in cereals. It infects coffee beans usually during sun-drying causing contamination in green coffee (Risk Assessment Studies, http://www.cfs.gov.hk/). Aspergillus carbonarius is highly resistant to sunlight and survives sun-drying because of its black spores and therefore grows at high temperatures. It is associated with maturing fruits and is the source of ochratoxin A in grapes, dried vine fruits, and wine and is also another source of ochratoxin A in coffee (Risk Assessment Studies, http://www.cfs.gov.hk/) Aspergillus niger is another minor source of ochratoxin A production in infected coffee beans and dried vine fruits. The mycotoxin has been detected in various food stuffs such as dried fruits, coffee, maize, sorghum, wheat, pulses and wine (Marquardt et al, 1992; Steyn et al, 1999). Therefore, using musts with low OTA levels will be possible to produce wines with toxin levels below the limits set by the European Commission (EC) 2 μg/kg (Ponsone et al.2010).
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".