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Record W3016045732 · doi:10.1071/an19472

Nutrient concentrations and profile of non-structural carbohydrates vary among different Brassica forages

2020· article· en· W3016045732 on OpenAlex
Juan Pablo Keim, Mónica Gandarillas, Daniel Benavides, Jaime Cabanilla, Rubén Pulido, Óscar Balocchi, Annick Bertrand

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnimal Production Science · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsBrassicaForageFructoseStarchBiologySucroseSugarAgronomyNutrientContext (archaeology)CarbohydrateFood scienceBiochemistryEcology

Abstract

fetched live from OpenAlex

Context Brassica forages are used in times of seasonal shortage to fulfil nutritional requirements of beef cattle, dairy cows, sheep or pigs. Although brassicas have been reported with high concentrations of readily fermentable carbohydrate, details have not been fully described and there is little information about the non-structural carbohydrate (NSC) profiles of Brassica forages. Aim The study was designed to evaluate nutrient concentrations, as well as NSC levels and constituents, of the main Brassica forages and to determine differences among varieties. Methods Five varieties of each of the four main forage brassicas (summer turnip, forage rape, kale and swede) were grown in plots and harvested for chemical analysis of the nutrient concentrations and NSC profiles of leaf and bulb (turnip and swede) and leaf and stem (rape and kale) components. Key results Brassica species differed in the amounts and types of NSC; swede had the highest concentration of NSC, mainly comprising sugars (glucose and fructose), followed by kale (with similar proportions of glucose, sucrose and fructose), turnip (with similar concentrations of glucose and starch and slightly lower fructose), and forage rape (in which starch was the main NSC). Forage chemical composition and NSC profile of plant organs varied among varieties of individual Brassica forages; for example, there were significant differences among swede varieties for concentrations of starch and sugar (total and profile) in bulbs. Conclusions Brassica forages differed with respect to quantities and types of NSC; swede had higher concentrations, mainly composed of glucose and fructose, followed by kale with similar proportions of glucose, sucrose and fructose, and turnip with NSC represented by glucose, starch and slightly lower fructose; and finally, forage rape, in which starch was the main NSC. Chemical composition, as well as NSC profile of plant organs (leaves, bulbs or stems), varied among varieties of Brassica species. Implications The approach described here has implications for ration formulation and is useful when considering the nutritional and dietary requirements of the animals of interest, because the type of Brassica, the variety and the proportion of plant organs can affect animal 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.

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 score0.592
Threshold uncertainty score0.301

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.021
GPT teacher head0.241
Teacher spread0.220 · 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