The impact of barley nitrogen fertilization rate on barley brewing using a commercial enzyme (Ondea Pro)
Bibliographic record
Abstract
Two Australian (Buloke and Commander) and two Canadian (CDC Meredith and Bentley) barley varieties were grown under four levels of nitrogen fertilization (0, 20, 40 and 80 kg ha−1). Barley samples were assessed by barley brewing with the Ondea Pro enzyme cocktail for mashing analysis and were compared with typical malt brewing quality specifications. The study observed that increased nitrogen fertilization resulted in increased barley kernel nitrogen content which significantly impacted a range of wort quality parameters including increased soluble nitrogen, free amino nitrogen and barley beta-amylase level, but also reduced extract, barley Kolbach index, β-glucan and colour. Increased grain nitrogen had relatively little effect on apparent attenuation limit, lautering and barley limit dextrinase level. Knowledge of the effects of interactions between barley of different qualities (e.g. nitrogen content) and the Ondea Pro enzymes on wort quality will result in enhanced barley to directly and efficiently brew good quality beer, to better satisfy the quality expectations of brewers. Copyright © 2018 The Institute of Brewing & Distilling
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".