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Nutrient profile and availability of co‐products from bioethanol processing

2011· article· en· W1514014504 on OpenAlexafffund
Arash Azarfar, Arjan Jonker, I. K. Hettiarachchi‐Gamage, Peiqiang Yu

Bibliographic record

VenueJournal of Animal Physiology and Animal Nutrition · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsUniversity of Saskatchewan
FundersUniversity of Saskatchewan
KeywordsChemistryDistillers grainsStarchDry matterNutrientFood scienceCarbohydrateRumenSugarBiofuelAgronomyAnimal scienceBiologyBiotechnologyFermentationBiochemistry

Abstract

fetched live from OpenAlex

Bioethanol production in North America has led to the production of considerable quantities of different co-products. Variation in nutrient profiles as well as nutrient availability among these co-products may lead to the formulation of imbalanced diets that may adversely affect animal performance. This study aimed to compare three types of dried distiller's grains with solubles [100% wheat DDGS (WDDGS); DDGS blend1 (BDDGS1, corn to wheat ratio 30:70); DDGS blend2 (BDDGS2, corn to wheat ratio 50:50)] and their different batches within DDGS type with regard to: (i) protein and carbohydrate sub-fractions based on Cornell Net Carbohydrate and Protein System (CNCPS); (ii) calculated energy values; and (iii) rumen degradation of dry matter (DDM), organic matter (DOM), crude protein (DCP), neutral detergent fibre (DNDF) and starch (Dstarch) at 36 and 72 h of ruminal incubations. Wheat DDGS had a lower intermediately (PB2, 136.4 vs. 187.4 g/kg DM) and a higher slowly degradable true protein (PB3, 142.2 vs.105.3 g/kg DM) than BDDGS1, but similar to those of BDDGS2. Sugar (CA4) was higher, whereas starch (PB1) and digestible fibre (PB3) were lower in WDDGS than in BDDGS1 and BDDGS2. All carbohydrate sub-fractions determined differed significantly between the two batches of BDDGS2. The BDDGS2 had the highest calculated energy values (TDN, DE(3×) , ME(3×) , NEL(3×) , NE(m) and NE(g) ) among the three DDGS types. The energy values were slightly different between the batches of the three DDGS types. At all incubation times, wheat DDGS had a significantly higher (p < 0.05) DDM, DOM, DCP and DNDF than both DDGS blends. Differences were observed between different batches within DDGS types with regard to in situ rumen degradation of DM, OM, CP, NDF and starch. In conclusion, differences were observed in protein and carbohydrate sub-fractions and in situ ruminal degradation of DM, OM, CP, NDF and starch among the three DDGS types and different batches within DDGS type. This indicates that the nutrients supplied to ruminants may not only differ among different types of DDGS but it may also differ among different batches within DDGS type.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.649
Threshold uncertainty score0.252

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.042
GPT teacher head0.249
Teacher spread0.208 · 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 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

Citations17
Published2011
Admission routes2
Has abstractyes

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