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Influence of an inoculant containing Lentilactobacillus hilgardii, Lentilactobacillus buchneri, and Pediococcus pentosaceus on the aerobic stability and nutrient degradability of whole-plant corn ensiled at different dry matter levels

2025· article· en· W4417137606 on OpenAlexfundno aff
Xia Liu, N. Romero, S. Cronin, E.B. da Silva, L. Kung, T.F. Gressley

Bibliographic record

VenueAnimal Feed Science and Technology · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsnot available
FundersLallemand
KeywordsMicrobial inoculantSilageDry matterLactobacillus buchneriInoculationFermentationNutrient

Abstract

fetched live from OpenAlex

Two experiments were conducted to evaluate the effects of an inoculant containing Lentilactobacillus hilgardii CNCM-I-4785, Lentilactobacillus buchneri NCIMB 40788, Pediococcus pentosaceus NCIMB 12455, β-glucanase, and xylanase on the fermentation profile, aerobic stability, and nutrient degradability of whole-plant corn silage. In Experiment 1, a brown midrib corn hybrid was harvested at 35.4 % dry matter (DM) and ensiled for 14 and 90 d. In Experiment 2, a conventional corn hybrid was harvested at either a low DM content (26.2 %) or a high DM content (39.7 %) and ensiled for 30, 60, 120, and 180 d. In Experiment 1, inoculation increased acetic acid concentrations at both 14 and 90 d and markedly improved aerobic stability at 90 d (+ 360 h). In Experiment 2, inoculation increased acetic acid concentrations at 60, 120, and 180 d in both DM levels and at 30 d only in low DM. Inoculation improved aerobic stability at 30 (+ 30 h), 120 (+111 h), and 180 d (+ 89 h) across both DM levels. At 60 d, the increase in stability by inoculation was greater in low DM (+ 58 h) than in high DM silage (+ 36 h). Inoculation enhanced starch degradability by 9.8 %age points at 90 d in Experiment 1, and by 4.7 and 2.7 %age points at 120 and 180 d, respectively, in Experiment 2. Overall, the inoculant effectively enhanced aerobic stability and starch degradability across two hybrids and three distinct DM levels.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.391
Threshold uncertainty score0.957

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.016
GPT teacher head0.220
Teacher spread0.204 · 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 teacher head, 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

Citations0
Published2025
Admission routes1
Has abstractyes

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