Effects of sustainable agronomic intensification in a forage production system of perennial grass and silage corn on nutritive value and predicted milk production of dairy cattle
Bibliographic record
Abstract
The objectives were to determine the effects of incrementally applied improved nutrient management, alternative cropping practices, and advanced production technologies in a dual forage system of perennial grass and silage corn on nutrient composition and in vitro ruminal fiber digestibility of the forages and, using these data as inputs into the Cornell Net Carbohydrate and Protein System, to predict milk production, indicators of nitrogen (N) utilization, and N excretion of dairy cattle. Farm management systems (farmlets) included a conventional system with whole manure slurry broadcast to a late maturing corn hybrid and grass harvested with 5 cuts per year (F1); improved nutrient management with a separated manure system where the sludge was applied to corn and the liquid was applied to grass (F2); improved nutrient management and alternative cropping practices with separated manure, an early maturing corn hybrid interseeded with a relay winter cover crop, and grass harvested with 3 cuts per year (F3); and improved nutrient management and alternative cropping practices combined with advanced production technologies that included irrigation and a nitrification inhibitor (F4). The field trial was a randomized complete block design over 2 yr with 4 blocks each divided into grass and corn, 4 subplots within each block for each crop, and 2 replicates within each subplot. Diets were formulation with 60% forage and 40% concentrate where the grass and corn as silage was proportional to yield for land allocations of grass and corn of 80:20, 60:40, 40:60, and 20:80. Data were analyzed using the MIXED procedure of SAS (SAS Institute Inc.). The intensified management systems (F2, F3, and F4) increased the crude protein (CP) concentration of corn with no effects on starch concentration [32.1% dry matter (DM)] compared with the conventional system (F1). Decreasing cuts of grass from 5 to 3 reduced the CP concentration in the spring harvest (15.8% vs. 12.5% DM), and increased fiber concentration and reduced digestibility in the spring, summer, and fall harvests. A common concentrate was formulated for the conventional farmlet and then combined with the forages for each farmlet within each land allocation. Forages grown under intensified management to improve N capture increased the CP concentration of the diets. However, reducing the number of cuts of grass from 5 to 3, combined with the corn and relay crop to increase yield, reduced milk production across all land allocations. To complement the nutritive value of the forages grown under each management system and land allocation, the concentrates were reformulated, which reduced dietary CP, improved the indicators of N utilization (e.g., milk urea N and milk N efficiency), reduced N excretion, and improved milk yield with no differences among the farmlets. Increasing land allocated to corn supported higher milk yield at lower dietary CP concentrations (16.5% vs. 15.4% DM) with improved milk N efficiency and lower N excretion. Intensified agronomic management increased the CP of the combined forages decreasing the need for supplemental CP in the concentrate and could reduce the importation of feed N to the farm.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".