Effect of gamma radiation on morphological, biochemical, and physiological aspects of plants and plant products
Bibliographic record
Abstract
Research on the basic interaction of radiation with biological systems has contributed to human society through various applications in medicine, agriculture, pharmaceuticals and in other technological developments. In the agricultural sciences and food technology sectors, recent research has elucidated the new potential application of radiation for microbial decontamination due to the inhibitory effect of radiation on microbial infestation. The last few decades have witnessed a large number of pertinent works regarding the utilization of radiation with special interest in γ-rays for evolution of superior varieties of agricultural crops of economic importance. In this review, general information will be presented about radiation, such as plant specificity, dose response, beneficial effects, and lethality. A comparison of different studies has clarified how the effects observed after exposure were deeply influenced by several factors, some related to plant characteristics (e.g., species, cultivar, stage of development, tissue architecture, and genome organization) and some related to radiation features (e.g., quality, dose, duration of exposure). There are many beneficial uses of radiation that offer few risks when properly employed. In this review, we report the main results from studies on the effect of γ-irradiations on plants, focusing on metabolic alterations, modifications of growth and development, and changes in biochemical pathways especially physiological behaviour.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".