A Controlled Agitation Process for Improving Quality of Canned Green Beans during Agitation Thermal Processing
Bibliographic record
Abstract
This work introduces the concept of a controlled agitation thermal process to reduce quality damage in liquid-particulate products during agitation thermal processing. Reciprocating agitation thermal processing (RA-TP) was used as the agitation thermal process. In order to reduce the impact of agitation, a new concept of "stopping agitations after sufficient development of cold-spot temperature" was proposed. Green beans were processed in No. 2 (307×409) cans filled with liquids of various consistency (0% to 2% CMC) at various frequencies (1 to 3 Hz) of RA-TP using a full-factorial design and heat penetration results were collected. Corresponding operator's process time to impart a 10-min process lethality (Fo ) and agitation time (AT) were calculated using heat penetration results. Accordingly, products were processed again by stopping agitations as per 3 agitation regimes, namely; full time agitation, equilibration time agitation, and partial time agitation. Processed products were photographed and tested for visual quality, color, texture, breakage of green beans, turbidity, and percentage of insoluble solids in can liquid. Results showed that stopping agitations after sufficient development of cold-spot temperatures is an effective way of reducing product damages caused by agitation (for example, breakage of beans and its leaching into liquid). Agitations till one-log temperature difference gave best color, texture and visual product quality for low-viscosity liquid-particulate mixture and extended agitations till equilibration time was best for high-viscosity products. Thus, it was shown that a controlled agitation thermal process is more effective in obtaining high product quality as compared to a regular agitation thermal process.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| 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 | 0.001 |
| 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 teacher head, 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".