Dose‐Dependent Effects of Gamma Irradiation on Microbiological, Antioxidant, and Functional Properties of Buckwheat, Cowpea, Oat, and Brown Rice Flour
Bibliographic record
Abstract
The present investigation was conducted to analyze the impact of the gamma irradiation dose on the microbiological, structural, and functional properties of buckwheat, cowpea, oat, and brown rice flour. The results showed that as the irradiation dose increased, there was a significant reduction in the total bacterial count (TBC) and the total yeast and mold count (TYMC). Specifically, a decrease of 60.67% was observed in TBC and 63.49% in TYMC compared to unirradiated samples, even at a dose of 5 kGy. In addition, there was a significant increase in the total phenolic content of all flour samples (8% for cowpea to 56.48% for buckwheat) after exposure to irradiation. In particular, buckwheat flour exhibited the highest DPPH inhibition capacity of 79.80% when irradiated at 15 kGy, outperforming the other flour samples. However, the FTIR spectra remained unchanged. The application of irradiation to cereals and legumes has recently been recognized as an innovative method to address the issues caused by insects and pests. Gamma irradiation can be applied to the product after packaging, reducing the risk of cross‐contamination. Additionally, this technique is nonthermal and does not leave any residues. The dietary value, sensory, and other quality parameter characteristics of pseudocereals and cereal‐related products can be preserved by subjecting them to controlled irradiation doses.
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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".