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Record W3005726044 · doi:10.1002/agj2.20182

Economics of pulse crop frequency and sequence in a wheat‐based rotation

2020· article· en· W3005726044 on OpenAlexaffabout
Mohammad Khakbazan, Yantai Gan, Manjula Bandara, Jianzhong Huang

Bibliographic record

VenueAgronomy Journal · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgronomic Practices and Intercropping Systems
Canadian institutionsBrandon UniversityAlberta Ministry of Agriculture and ForestryAgriculture Food and Rural DevelopmentAgriculture and Agri-Food Canada
Fundersnot available
KeywordsCrop rotationCropField peaAgronomyCroppingBiologySativumBrassicaCropping systemMathematicsAgricultureEcology

Abstract

fetched live from OpenAlex

Abstract Pulse crops (PC) have become an essential part of cropping systems in the northern Great Plains. Despite agronomic benefits of rotating pulses with cereal crops, knowledge of the economics of PC frequency and sequence in a rotation is limited. A field study was conducted from 2010 to 2014 at three locations in western Canada to evaluate the effects of rotating a cereal crop with a range of PC at different frequencies and sequences on the economic returns and risk of both the entire rotation and each individual crop. Crops in rotation included spring wheat ( Triticum aestivum L.) (W), field pea ( Pisum sativum L.) (P), chickpea ( Cicer arietinum L.) (C), lentil ( Lens culinaris Medik) (L), and Oriental mustard ( Brassica juncea L.) (M). Thirteen 4‐yr‐cycle crop rotation treatments, along with a continuous wheat treatment as a baseline, were included. Treatments were arranged in a randomized complete block design with four replicates at each site‐year. The net revenue (NR) was defined as the income remaining after paying all monetary, land and ownership, and labor costs. Crop rotation had a significant effect on average annual NR. The most profitable rotations were L–L–L–W and P–M–L–W. These rotations provided CAN$330 and $235 yr –1 ha –1 higher NR, respectively, than the baseline, and were most preferable by risk‐averse producers. The economic ranking of the rotations remained the same with different crop price scenarios. Preceding PC also had a positive impact on the succeeding wheat crop NR.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.598
Threshold uncertainty score0.231

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.046
GPT teacher head0.240
Teacher spread0.194 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations14
Published2020
Admission routes2
Has abstractyes

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