Milk performance and rumen microbiome of dairy cows as affected by the inclusion of corn silage or corn shredlage in a total mixed ration
Bibliographic record
Abstract
Corn silage (CS) is the most common forage used to feed dairy cows with inclusion rates typically around 20-40% of the diet DM. In recent years, the use of corn shredlage (SDL) has been proposed as a substitute for CS. Corn SDL is produced by a method which involves shredding the corn plant into unusually long sections and crushing the corn kernels. The objective of this study was to provide additional data on the effect of feeding SDL vs CS on milking performance and rumen microbial ecosystem. A total of 212 000 kg of whole plant were harvested on the same day and ensiled in two adjacent bunker silos of ~100,000 kg each. One silo was processed using a theoretical length of cut (LOC) of 26 mm (SDL) and other was harvested using a 16-mm LOC (CS). Both corn plants were treated at the rate of 100 ml/ton with a commercial inoculant (Magniva Platinum 1, Lallemand, France) to supply 150 000 CFU of Lactobacillus hilgardii CNCM I-4785 and 150 000 CFU of L. buchneri NCIMB 40 788 per gram of fresh material. Sixty lactating Holstein cows (648 ± 66.6 kg of BW; 44.4 ± 9.9 kg/d of milk yield; 155 ± 75 DIM) were split into two groups and fed the same total mixed ration (15.2% CP, 30.8% NDF on a DM basis) containing either 32.7% CS or 32.7% SDL, on a DM basis, for 7 weeks. Individual feed intake and milk production and composition were monitored daily. Also, at 50 d of study (completion), a rumen sample was obtained from every cow, and DNA extracted and submitted to high-throughput sequencing to evaluate potential changes in rumen microbiota. Data were analyzed using a mixed-effects model which accounted for the fixed effects of treatment, week of study, and their two-way interaction, plus the random effect of cow. Cows on SDL had a greater DMI toward the end of the study, but milk yield and composition were not affected by dietary treatments. As result, feed efficiency was greater in cows fed CS than in those fed SDL toward the end study. There were no major changes in the relative abundances of the different microbial populations in the rumen between both groups of cows. It is concluded that SDL increases DMI of cows, but this increase is not followed by improvements in production.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".