MétaCan
Menu
Back to cohort
Record W4288766322 · doi:10.26443/msurj.v17i1.179

Potential for use of Spent Substrate of Pleurotus Mushrooms Grown on Urban Waste as Feed for Dairy Cattle

2022· article· en· W4288766322 on OpenAlexafffund
Liesl Van Wyk

Bibliographic record

VenueMcGill Science Undergraduate Research Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicFungal Biology and Applications
Canadian institutionsMcGill University
FundersMcGill University
KeywordsOysterMushroomPleurotusWaste managementFood scienceEnvironmental sciencePulp and paper industryBiotechnologyBiologyEngineeringEcology

Abstract

fetched live from OpenAlex

Mushroom wastes are available in high volumes, with 5 million tons of spent mushroom substrate (SMS) being disposed of globally every year. Due to this high availability, various forms of SMS have been researched for their use as alternative animal feeds. Additionally, experimental techniques can be used to grow certain mushroom species, such as oyster mushrooms (Pleurotus sp.) on various lignocellulosic waste materials. Therefore, the SMS from Pleurotus sp. grown on these waste materials may offer a promising conversion from a waste material to a low-cost, nutritionally sufficient feed. However, little research has been done to determine if feeds from Pleurotus SMS specifically grown on urban waste substrates offer the same benefits. Given rising awareness on circularity and urban self-sufficiency, growing mushrooms on urban waste is a promising solution which should be investigated. This paper assesses the feasibility of using SMS from golden oyster mushrooms (Pleurotus citrinopileatus) grown on urban waste as dairy cattle feed, comparing substrate ratios to determine which would result in the most desirable protein and fiber contents. SMS from three experimental substrates of cardboard and spent coffee grounds (SCG) were compared to traditional dairy cattle feeds. Treatments 2 and 3 were found to be suitable for use as additives to traditional feeds in small replacement amounts. However, both treatments also had high fiber content, which may affect practicality of use as feeds.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.066
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.112
GPT teacher head0.383
Teacher spread0.271 · 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.

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

Citations5
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueMcGill Science Undergraduate Research JournalSame topicFungal Biology and ApplicationsFrench-language works237,207