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Record W4400133928 · doi:10.1002/agj2.21622

A review of intercropping systems in Western Canada

2024· review· en· W4400133928 on OpenAlex
Vengai Mbanyele, Rebecca Oiza Enesi, Lana Shaw, Linda Yuya Gorim

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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAgronomy Journal · 2024
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicAgronomic Practices and Intercropping Systems
Canadian institutionsUniversity of Alberta
FundersWestern Grains Research Foundation
KeywordsIntercroppingAgronomyCanolaSativumHordeum vulgareCrop rotationCropPisumBrassicaBiologyMathematicsPoaceaeHorticulture

Abstract

fetched live from OpenAlex

Abstract Intercropping is gaining interest from Western Canadian producers who are looking for information on how to incorporate intercrops into their production systems. This review summarizes agronomic research on intercropping from the last 40 years in Western Canada and discusses the potential challenges of integrating intercropping into existing crop rotations while identifying challenges and possible solutions. Reviewed literature indicates that several intercrop combinations have been tested in small plots involving up to four crops simultaneously grown, with over 60% comprising pulse–oilseed combinations followed by pulse–cereal combinations at ∼30%. The land equivalent ratio (LER) for pulse–oilseed and pulse–cereal averaged 1.11 and 1.13, respectively. Key agronomic factors that influenced LER in different intercrop combinations have been summarized, and the relationship of N and seeding rate with crop grain LER and partial land equivalent ratio has been assessed. While the relationship between N rate and LER was unclear in pulse–oilseed combinations such as pea ( Pisum sativum L.)–canola ( Brassica napus L.), LER decreased linearly with increasing N rate ( p < 0.004) in pea–barley ( Hordeum vulgare L.) intercrop. We highlighted that incorporating intercrops into current rotations will decrease crop rotation lengths with possible implications for disease management. There are many logistical challenges to intercropping but new technology may help producers to adapt.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.890
Threshold uncertainty score0.877

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.059
GPT teacher head0.299
Teacher spread0.240 · 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