Winter cereal species, cultivar, and harvest timing affect trade-offs between forage quality and yield
Bibliographic record
Abstract
Volatile feed costs and extreme weather events are contributing to greater economic risk and precarity throughout much of the United States dairy industry. These challenges have prompted dairy farmers to seek ways to reduce feed imports without compromising milk production. For organic dairy farmers, the need to produce more homegrown forage is exacerbated by the high cost and limited supply of organic feed. Integrating winter cereals for forage as part of a double-cropping system is a potential solution, but increasing the amount of forage in dairy cow rations can reduce milk production if the forages are not managed for optimal quality. Organically managed field experiments in Maryland (MD) and New York (NY) were conducted to address two primary objectives: (1) determine the yield and quality of winter cereals—four cultivars each for barley (Hordeum vulgare L.), cereal rye (Secale cereale L.), and triticale (× Triticosecale Wittm. ex A. Camus.)—grown as forage and harvested at different crop growth stages, and (2) evaluate the trade-offs between yield and quality in relation to winter cereal phenology and harvest date. Mean yield at a commonly harvested growth stage, swollen boot (Zadoks 45), was 1.3, 2.2, and 2.2 Mg ha−1 in MD and 1.8, 2.5, and 2.9 Mg ha−1 in NY for barley, cereal rye, and triticale, respectively. Mean relative forage quality (RFQ) at the same growth stage was 180, 158, and 163 in MD and 179, 156, and 157 in NY for the three species. Overall, cereal rye reached swollen boot stage the earliest, barley produced the highest RFQ and retained high quality the longest, and cereal rye and triticale produced the highest yields. Based on these results, farmers should consider barley cultivars if quality is the priority and winter-hardiness is not a concern; cereal rye cultivars if an early harvest is most important; and triticale cultivars if greater harvest schedule flexibility would be most valuable. These findings can be used to better meet the needs of dairy farmers, enhance double-cropping system performance, and improve the synchronization of harvest timing with the specific needs of lactating dairy cows, dry cows, heifers, and calves.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".