PHYSICAL, PHYSIOLOGICAL AND CHEMICAL CHANGES IN POTATO AS INFLUENCED BY<i>ERWINIA CAROTOVORA</i>INFECTION
Bibliographic record
Abstract
Bacterial soft rot, caused by Erwinia carotovora ssp. carotovora (Ecc), is a major disease in stored potatoes. The pathogen causes different physical, physiological and chemical changes in potatoes, which may affect the acceptability of raw and processed products. This study was carried out to evaluate the effect of disease severity on different physico-chemical and physiological properties of raw and cooked potatoes and to select the parameters most responsive to disease severity. Potatoes were inoculated with bacteria and incubated at 20C for different lengths of time to produce different levels of disease. As incubation time increased the volume of disease (VDS) increased, which in turn influenced the respiration rate (RR). In both raw and cooked potatoes, the physical changes (texture and color) associated with the progress of disease were reduced hardness, firmness and L value, and increased a and b values and total color difference (ΔE). The chemical changes were reduced ascorbic acid and pH, and increased reducing sugars, total sugars and titrable acidity along with the activities of peroxidase and polyphenol oxidase. The changes in physical and chemical parameters of raw and cooked potatoes during storage were described by fractional conversion equation models. All parameters were quite sensitive to disease except reducing sugars, peroxidase and PPO activity. The correlation matrix indicated that several of the quality parameters were related and thus most of them could be successfully used to predict tuber quality from disease.
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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) | 0.000 | 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".