Non-Nutrients in Chickpea and Cowpea, Their Role and Methods to Remove Them
Bibliographic record
Abstract
High oral doses can cause symptoms, such as hyperpnea, shortness of breath, headache, palpitations, vomiting, bradycardia, unconsciousness, and even death in some cases. Moreover, saponins interfere with the digestion of proteins and vitamins, and mineral absorption in the gut. In chickpea and cowpea, tannins are available as both hydrolyzable and condensed forms. Furthermore, animals feed intake and efficiency, growth rate, and protein digestibility are negatively impacted by tannins. The traditional methods for processing chickpea and cowpea seeds, like dehulling, milling, soaking, boiling/cooking, roasting, germination, and fermentation are labor-intensive. Since the majority of the non-nutritive components of chickpea and cowpea seeds are water-soluble, soaking is the best method to remove them. These include dielectric and infrared heating, microwave cooking, high hydrostatic pressure, enzymic treatment, and so on.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.001 |
| 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".