Barley carbohydrate composition varies with genetic and abiotic factors
Bibliographic record
Abstract
Changes in chemical quality arising from genetic composition of different barley varieties as well as non-genetic factors were investigated by comparing samples from different seasons and locations. The samples (15), consisting of different varieties originating from Norway and Canada, were analysed for polysaccharide composition as well as total protein content. The results revealed differences in chemical parameters between the hulled and hull-less varieties, especially in carbohydrate composition. Also, variations within the types were found, which indicated that factors other than the presence or lack of hull may also influence the carbohydrate composition. As expected, varieties grown at the same location in both seasons had a lesser variation in their grain composition between the growing periods than varieties grown at different locations. Changing the growth location from Canada to Norway also gave an increase in starch and insoluble fibre, but decreased the amount of β-glucan, protein and soluble fibre. Promising varieties for the food industry are samples with an atypical starch characteristic without hull, due to higher levels of the proposed health-beneficial components. Also, the commercial Norwegian variety, Olve, had an advantageous grain composition and is a promising variety for food uses.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".