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Record W4405230982 · doi:10.1093/jas/skae369

Evaluation of kernel processing and processor type in whole-plant sorghum silage: effects on nutrient digestibility and animal performance in backgrounding beef heifers

2024· article· en· W4405230982 on OpenAlexaff
Federico Podversich, Leandro Abdelhadi, Sergio Roskopf, Gleise M Silva, Emmanuel Angeli, Gustavo Juan Hein, Hugo H. Ortega, Martin Ruiz‐Moreno, José Carlos Batista Dubeux, Nicolás DiLorenzo

Bibliographic record

VenueJournal of Animal Science · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsUniversity of Alberta
FundersUniversidad Nacional de La Plata
KeywordsSilageSorghumNutrientKernel (algebra)Animal scienceAgronomyBeef cattleMathematicsBiology

Abstract

fetched live from OpenAlex

Two experiments were conducted to assess the effects of feeding whole-plant sorghum silage (WPSS) with different kernel processing techniques (KP). Experiment 1 contrasted KP for WPSS on intake and apparent total tract digestibility (ATTD) in beef heifers (n = 24, 13 ± 1 mo, 267 ± 10.9 kg of initial body weight [BW]) housed in individual pens (36 m2). Grain sorghum was harvested at hard dough, switching the kernel processor to obtain the WPSS treatments: A) unprocessed (UNP), B) conventionally processed (CONV), and C) shredlage processed (SHRD). Heifers (8/treatment) received ad libitum WPSS from their respective treatment, plus soybean meal top-dressed at 0.5% BW/d (DM basis). Feed, and feces were collected for 5 d; feed was offered once daily, and orts were collected the following day. Fecal samples were collected twice daily, and ATTD was determined using indigestible neutral detergent fiber (NDF) as a marker. Data were analyzed as a completely randomized design, with heifer as the experimental unit, and the following contrasts were performed 1) Processing: UNP vs. (CONV + SHRD) and 2) Processor: CONV vs. SHRD. Processing WPSS increased the ATTD of starch by 4.5% (P = 0.01), reduced fecal starch by 27.5% (P = 0.01), and reduced the change of NDF from feed to orts by 39% (P < 0.01). Heifers fed SHRD had 6.6% greater ATTD of NDF than CONV-fed heifers (P = 0.04). Experiment 2 evaluated the effects of feeding either SHRD or CONV-processed WPSS on growth performance of beef heifers. Whole-plant grain sorghum was harvested at the hard-dough stage, switching the KP as in experiment 1. Angus heifers (n = 96, 15 ± 1 mo, 249.6 ± 28.6 kg of BW) were blocked by initial BW, and randomly assigned to pens (8 heifers/pen, 6 pens/treatment). Diets consisted, all on a DM basis, of WPSS, either SHRD or CONV, at 90.5%, expeller soybean meal at 7.0%, and a vitamin-mineral-protein concentrate at 2.5%. After 14-d of adaptation, growth was measured for 56 d, and feed was offered once daily. Data were analyzed using a randomized complete block design with the pen as the experimental unit. Heifers fed CONV had a 9.6% greater gain-to-feed ratio (P = 0.05) and a 7.4% greater Kleiber ratio (P = 0.05) than SHRD-fed heifers. Apparent net energy of gain tended to be 7.1% greater in CONV-fed heifers (P = 0.06). In conclusion, kernel processing WPSS increased starch digestibility and reduced fecal starch concentration. Using SHRD increased NDF digestibility and feeding CONV-processed WPSS resulted in enhanced growth performance.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.040
GPT teacher head0.299
Teacher spread0.259 · 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 designBench or experimental
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

Citations2
Published2024
Admission routes1
Has abstractyes

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