Solubility Differences of Major Storage Proteins of Brassicaceae Oilseeds
Bibliographic record
Abstract
Abstract Seeds of six commercially produced Brassica juncea, Brassica napus and Sinapis alba varieties representing high‐glucosinolate condiment‐type and low‐glucosinolate canola‐type were studied for solubility characteristics of the predominant seed storage proteins (SSPs). The non‐protein nitrogen components such as glucosinolates, nucleic acids, betaine, choline and sinapine contributed 3.1–5.2% and 7.9–10.8% for the total N content of low‐ and high‐glucosinolate meals, respectively. The cruciferin and napin which are the predominant SSPs of crucifers were purified from these seeds and used to confirm soluble protein types under the conditions provided. The napins were soluble between pH 2 and 4 but not the cruciferins. Strong alkaline pH brought both cruciferin and napin into solution. In general, the SSP solubility was increased due to the presence of NaCl or CaCl2 salts in the medium. The effect of CaCl2 on solubility was more positive than NaCl for all the seed types except S. alba at neutral and alkaline pH. Presence of salts indeed reduced solubility of S. alba SSPs at alkaline pH. The medium pH and salt ions and their ionic strength can be manipulated to achieve selective solubility of napin and cruciferin of Brassicaceae seed meals.
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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) | 0.001 | 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".