Combined Gamma Irradiation and Hydrothermal Treatments did not adversely affect the Nutritional Characteristics of African Bush Mango (Irvingia gabonensis) Seeds and the Oil Quality
Bibliographic record
Abstract
The need to preserve the nutrients in a food sample while ensuring microbiological safety has led to researches on different hurdle techniques. To this end, this study aimed at evaluating the effect of gamma irradiation and hydrothermal treatment in a hurdle arrangement on the physicochemical and functional properties of bush mango (Irvingia gabonensis) seed, as well as investigation of its impact on quality attributes of the oil. The Irvingia gabonensis samples were divided into raw, cooked, cooked and irradiated at 10 kGy, and irradiated at 5 kGy and 10 kGy, respectively. Proximate composition, minerals, antinutritive factors, oil quality and amino acid profile were determined in the differently treated samples. It was observed that increase in gamma irradiation dose, as well as the hurdle treatment, reduced the protein content of the samples. Tannins, iodine value and free fatty acid were all reduced with increased irradiation dose and additional hydrothermal treatment. On the other hand, no significant difference was observed in water and oil absorption capacities and foaming stability of the seed samples. The amino acid profile indicated various increases in isoleucine, valine, threonine, glutamic acid, alanine, and tyrosine as irradiation dose increased, while lysine, glycine, leucine, phenylalanine and methionine showed decreases. It could be deduced from the findings that, apart from increased saturation of the seed oil, the hurdle arrangement of gamma irradiation and cooking did not adversely affect the nutritional status of the bush mango seed.
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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".