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Record W3188710009 · doi:10.13031/trans.14613

The Manitoba Land Calculator: A Tool to Estimate Land Requirements for Manure Application in Manitoba, Canada

2021· article· en· W3188710009 on OpenAlexaffabout
Roniele Cordeiro, Petra Loro, Marcos R. C. Cordeiro, Clay Sawka, Kim Ominski, Don Flaten

Bibliographic record

VenueTransactions of the ASABE · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicAgriculture Sustainability and Environmental Impact
Canadian institutionsUniversity of ManitobaAgriculture Food and Rural DevelopmentGenome Prairie
Fundersnot available
KeywordsLivestockManureNutrient managementManure managementLand useEnvironmental scienceSustainabilityProduction (economics)Agricultural scienceCalculatorNutrientAgroforestryAgricultural engineeringGeographyAgronomyEngineeringComputer scienceForestryEcologyBiologyEconomics

Abstract

fetched live from OpenAlex

Highlights The Manitoba Land Calculator is a tool to estimate land requirements for new and expanding livestock operations. This new tool reflects Manitoba production practices and recent advances in animal and crop performance. Considerably more land is needed for management of manure phosphorus than when only nitrogen is considered. Sufficient land for application of manure supports the environmental sustainability of livestock production. Abstract. The planning of new livestock and poultry facilities or expansion of existing facilities should ensure sufficient land for manure application. Decision support tools used to establish land requirements for manure nutrients should take into consideration advances in animal genetics, performance, feeding strategies, and available feeds. This article presents a new tool for estimating land requirements for new and expanding pig, beef, dairy, and poultry operations in the province of Manitoba, Canada. The Manitoba Land Calculator (MLC) estimates land requirements for manure nitrogen (N) and phosphorus (P). It uses a mass balance approach to estimate nutrient excretion by livestock and poultry based on typical Manitoba feeding practices, weight gain, and production cycles. Crop nutrient utilization and removals can be calculated for 20 common crops grown in Manitoba using reliable long-term yields and farm-specific crop areas. Two case studies (pig and poultry) were selected from the Livestock Technical Review Public Registry on the Government of Manitoba website to illustrate the inputs and outputs associated with the MLC. The results indicated that land requirements increased by 4.6-fold and 5.7-fold for the poultry and pig operations, respectively, compared to the previous provincial methodology due to the inclusion of P in the model. Securing additional land during the planning stages will support the implementation of nutrient stewardship principles that ensure the long-term environmental sustainability of livestock operations. Keywords: Animal production, Land requirements, Livestock and poultry, Manure, Mass balance, Nutrient excretion.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.029
Threshold uncertainty score0.213

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0070.011
Science and technology studies0.0020.000
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.002

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 head0.009
GPT teacher head0.237
Teacher spread0.228 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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

Citations0
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueTransactions of the ASABESame topicAgriculture Sustainability and Environmental ImpactFrench-language works237,207