Processing conditions for micronization of peas (Pisum sativum) and an in vitro evaluation of the product
Bibliographic record
Abstract
Tempering and storage conditions were investigated for the processing of peas using infrared heat (micronization). The criteria for evaluation of processing conditions included the extent to which starch was gelatinized, the extract viscosity of the peas and the availability of lysine in the peas. In the initial study using the pea (Pisum sativum) cultivar Croma, a tempering level of 24% moisture was selected for the micronization treatment as it resulted in significant increases (p£0.05) in starch gelatinization, while maintaining available lysine levels and reducing extract viscosity. With minor exceptions, which included a decrease in available lysine for the cultivar Carneval, similar results were obtained when these conditions were applied to four other pea cultivars (two yellow and two green) in a second study. Storage at room temperature (22oC) was able to preserve these characteristics, and there was no benefit to storing at a lower temperature of 4 o C for up to 6 weeks. Differences in available lysine for the yellow Carneval and unknown cultivars, seen immediately after processing, were not a factor following storage. The production of micronized peas suitable for incorporation into animal feed is possible if the appropriate moisture content during tempering is selected.
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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) | 0.001 | 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 | 0.001 |
| 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".