Effect of maturity and variety on the textural quality of green snap beans
Bibliographic record
Abstract
Rheological measurements on intact fresh snap beans (Phaseolus vulgaris v.) and purees made from raw beans were used to assess the effect of variety and sieve size on the textural characteristics of green snap beans. Seed length, percentage dry matter and physical fiber measurements were used as textural quality indicators. Four varieties of green snap beans (Tendercrop, Rainier, Harvester and BBL 290) were tested in 1971 and 1972. Each variety was harvested five times in each year. Adverse environmental conditions in 1971 caused bean textural quality to be higher in 1972 than in 1971. The four varieties tested showed significant differences with Rainier exhibiting the best textural quality while Harvester generally showed the poorest quality. Tests involving the resistance to shearing of intact bean pods were carried out using the Ottawa Texture Measuring System and the Food Technology Corporation's Texture Test System (formerly the Kramer shear press). Viscosity tests were performed on purees composed of macerated raw green bean tissue and water. Results were obtained from spread test using a simplified Adams-type consistometer and from rotating coaxial cylinder tests using a Brookfield RVT Synchro-Lectric Viscometer fitted with a small sample adapter. The Brookfield data were then fitted to the power-law equation. Rheological parameters showed highly significant interrelationships in most instances. Viscous properties of purees (spread, m, n and yield stress) were highly correlated with percentage dry matter of the beans. Peak force readings of the Kramer shear press and the Ottawa Texture Measuring System were significantly correlated with all textural quality and viscometric parameters.
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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 | 0.001 |
| 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".