Effects of Electron-Beam Radiation on Nutritional Parameters of Portuguese Chestnuts (Castanea sativa Mill.)
Bibliographic record
Abstract
Chestnuts are a widely consumed fruit around the world, with Portugal being the fourth biggest producer in Europe. Storage of these nuts is an important step during processing, and the most widely used fumigant was banned in the European Union under the Montreal Protocol because of its toxicity. Recently, radiation has been introduced as a cheap and clean conservation method. Previous studies of our research group proved that γ radiation had no negative effect on the nutritional value of chestnuts; in fact, storage time had a much bigger influence on the chestnut quality. In the present study, we report the effect of a less ionizing radiation, electron beam, with doses of 0, 0.5, 1, 3, and 6 kGy in the nutritional value of chestnuts (ash, energy, fatty acids, sugars, and tocopherols), previously stored at 4 °C for 0, 30, and 60 days. The storage time seemed to reduce fat and energetic values but reported a tendency for higher values of dry matter. With regard to fatty acids, there was a higher detected quantity of C20:2 in non-irradiated samples and four fatty acids were only detected in trace quantities (C6:0, C8:0, C10:0, and C12:0). γ-Tocopherol decreased during storage time but did not alter its quantity for all of the radiation doses (as like α-, β-, and δ-tocopherol); in fact, these compounds were present in higher concentrations in the irradiated samples. Sucrose and total sugars were lower in non-irradiated samples, and raffinose was only detected in irradiated samples. Electron-beam irradiation seems to be a suitable methodology, because the effects on chemical and nutritional composition are very low, while storage time seems to be quite important in chestnut deterioration.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".