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Record W4361215906 · doi:10.3920/jiff2022.0164

Factors affecting the decision-making process of using insect-based products in animal feed formulations

2023· article· en· W4361215906 on OpenAlex

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

VenueJournal of Insects as Food and Feed · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect Utilization and Effects
Canadian institutionsUniversité Laval
FundersEuropean Commission
KeywordsPalatabilityDefattingFish mealFood scienceBiologyMealLimitingNutrientBiotechnologyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Insect meals are promising alternative feed ingredients although their application is still not commonplace. Their inclusion requires the consideration of various factors to optimise growth, animal welfare, and feed costs. The insect meal form (whole or defatted) impacts the level of inclusion, in particular in feeds where low amount of lipids is needed (e.g. poultry). From a nutritional point of view, the factors that influence the insect meal characteristics include insect species, rearing substrates and production processes. Processing (drying, defatting) can dramatically influence the nutrient digestibility and availability that requires assessment through in vivo or in vitro trials, with differences being observed in relation to the entity of the defatting process as well. The inclusion of full-fat or defatted meal may impact the final product quality (fatty acid profile). Low digestibility of chitin is also a limiting factor. Studies to increase the digestibility of insect meals using additives are ongoing. For these reasons, when different insect protein suppliers are used for feed production, chemical analyses need to be performed. In addition to the nutritional aspect, in some species (i.e. fish), a physical evaluation of the feed is necessary. In particular, the high fat content of whole larvae meal may increase the mixture viscosity and decrease the pellet stability, resulting in nutrient loss. Palatability affects feed ingestion; though insect meals seem well accepted, some palatability issues have been reported at high inclusion levels. It is however not clear if these issues are due to the level of inclusion or to some intrinsic characteristics of the meal used. Finally, the crucial factor for the future practical incorporation of insect meals in animal feeds is the availability and consistency of the supply. Without large and consistent quantities, it will be difficult for feed producers to incorporate these alternative ingredients within their production processes.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.809
Threshold uncertainty score0.184

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.058
GPT teacher head0.297
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