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Record W3194103627 · doi:10.3168/jds.2021-20408

Diets varying in ratio of sweet sorghum silage to corn silage for lactating dairy cows: Feed intake, milk production, blood biochemistry, ruminal fermentation, and ruminal microbial community

2021· article· en· W3194103627 on OpenAlexaff
Shaoxun Tang, Xin Yu, Zhenping Hou, Fujiang Hou, K. A. Beauchemin, Wenzhu Yang, Duanqin Wu

Bibliographic record

VenueJournal of Dairy Science · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsAgriculture and Agri-Food Canada
FundersScience and Technology Program of Hunan ProvinceLanzhou University
KeywordsLactoseDry matterSilageLactationAnimal scienceFood scienceChemistrySomatic cell countFermentationTotal mixed rationBiologyIce calving

Abstract

fetched live from OpenAlex

The objective of this study was to investigate the effects of partial substitution of corn silage (CS) with sweet sorghum silage (SS) in the diets of lactating dairy cows on dry matter (DM) intake, milk yield and composition, blood biochemistry, and ruminal fermentation and microbial community. Thirty mid-lactation Holstein dairy cows [mean ± standard deviation; 639 ± 42.0 kg of body weight; 112 ± 24.0 d in milk (DIM)] were assigned to 3 groups (n = 10/treatment) by considering parity, milk yield, and DIM. The cows were fed ad libitum total mixed rations containing 55% forage and 45% concentrate, with only the proportion of CS and SS varying in 3 treatments (DM basis): SS0 (0% substitution of CS), 40% CS and 0% SS; SS25 (25% substitution of CS) , 30% CS and 10% SS; and SS50 (50% substitution of CS) , 20% CS and 20% SS. Dry matter intake and milk protein concentration tended to linearly decrease with increasing proportion of SS in the diet. Yields of milk (mean ± standard deviation, 30.9 ± 1.12 kg/d), 4% fat-corrected milk (30.0 ± 0.81 kg/d), energy-corrected milk, milk protein, lactose, and total solids, concentrations of milk fat, lactose, somatic cell counts, and milk efficiency did not differ among diets. The concentrations in blood of urea nitrogen, phosphorus, aspartate aminotransferase, and malondialdehyde linearly increased with increasing SS proportion. Blood IgA decreased with increasing SS substitution rate, but blood IgG and IgM were not different among diets. Ruminal pH did not differ among diets, whereas ruminal NH 3 -N concentration quadratically changed such that it was greater for SS50 than for SS0 and SS25. Molar proportions of propionate and acetate to propionate ratio were less for SS25 than for SS0. Although the diversity and general ruminal microbial community structure were not altered by partially replacing CS with SS, the relative abundances of predominant bacteria were affected by diets at the phylum and genus levels. Firmicutes and Bacteroidetes were dominant phyla in the ruminal bacterial community for all diets, and their relative abundance linearly decreased and increased, respectively, with increasing SS substitution rate. Prevotella_1 and Ruminococcaceae_NK4A214_group were detected as the most and the second most abundant genera, with their relative abundance linearly increased and decreased, respectively, with increasing SS substitution rate. The relative abundance of Fibrobacter linearly increased with increasing dietary SS proportion, with greater abundance observed for SS25 and SS50 than for SS0. These results suggest that substitution of CS with SS altered the relative abundances of some predominant bacteria; however, these changes had little effect on ruminal fermentation and milk yield. Under the current experimental conditions, substituting up to 50% of CS with SS had no negative effects on milk yield, indicating that SS can partially replace CS in the diets of high-producing lactating dairy cows without adding extra grain, when diets are fed for a short time. As the effects of substituting CS with SS depend upon the chemical composition and digestibility of these silages and the nutrient requirements of the cows, additional grain may be required in some cases to compensate for the lower starch content of SS.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.030
GPT teacher head0.269
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations32
Published2021
Admission routes1
Has abstractyes

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