Bibliographic record
Abstract
Barley (Hordeum vulgare) is a versatile crop with three principal end-uses: feed, food, and malt. Each end-use of barley requires different characteristics, but hull adherence and β-glucan content are important for each of the three classes. Most of the barley grown in the United States has an adhering hull, but a small percentage of the barley grown is hull-less, or “naked”. Naked barley shows potential as a crop that can be used for food, feed, and malt. This review covers research on breeding naked barley for multiple applications: feed, food, malting, brewing, and distilling. As a feed, naked barley contains higher levels of protein than covered barley or corn; based on numerous reports that naked barley is superior to covered barley for swine feed, breeders in Canada began breeding naked barley for swine feed in the 1970s. Barley foods are on the rebound due to fiber and whole grain nutrition health benefits. Breeders have been developing naked barley with increased levels of β-glucan for human consumption. Naked barley can present an opportunity to the malting and brewing community through significantly higher levels of malt extract and improved beer quality. Malting barley has traditionally been covered, but due to the potential advantages, breeders have begun developing naked lines specifically for brewing and distilling. Grower, producer, processer, and consumer communities with interests in innovation, health, and sustainability stand to benefit directly from breeders working to develop new multiuse barley varieties.
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 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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".