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Record W2888604768 · doi:10.1016/j.agsy.2018.07.016

A meta-analysis approach to examining the greenhouse gas implications of including dry peas (Pisum sativum L.) and lentils (Lens culinaris M.) in crop rotations in western Canada

2018· article· en· W2888604768 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAgricultural Systems · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicAgriculture Sustainability and Environmental Impact
Canadian institutionsSaskatchewan Research Council (Canada)
FundersU.S. Environmental Protection Agency
KeywordsSativumPisumCropGreenhouse gasAgronomyCrop rotationEnvironmental scienceCrop residueBiologyHorticultureAgriculture

Abstract

fetched live from OpenAlex

This study used a meta-analytic approach to systematically examine changes in greenhouse gas (GHG) emissions intensities (i.e., carbon footprints) between pulse-containing and pulse-free crop rotations in western Canada. A systematic literature review was conducted to identify published literature relevant to the goal of the analysis and meta-analysis was conducted to determine statistically significant differences in GHG emissions between pulse-free and pulse-containing crop rotations. Four pulse-free reference rotations (cereal-cereal [CC]; oilseed-cereal [OC]; oilseed-oilseed [OO]; and cereal-oilseed [CO]) were compared to rotations where the first crop in each two-year sequence was replaced with either dry pea (Pisum sativum L.) or lentil (Lens culinaris M.). Two scenarios were considered. The first scenario investigated the effects of dry peas and lentils when synthetic nitrogen (N) applied to cereal and oilseed crops grown after pulses was not reduced (i.e., no change) (NN). The second scenario (NCR) investigated the effect of dry peas and lentils when synthetic N application rates were reduced to the maximum extent possible (i.e., credit) to maintain subsequent crop yields. Pooled analyses demonstrated that, in general, cereal and oilseed crops grown after a dry pea or lentil crop had similar or reduced GHG emissions compared to those grown after a cereal or oilseed. The GHG emissions from cereal and oilseed crops grown after dry peas and lentils were higher in NN (888–987 kg CO2e/ha; 286–598 kg CO2e/t) than in NCR (311–978 kg CO2e/ha; 116–598 kg CO2e/t), suggesting that emissions were reduced to a greater extent when pulse crops offset the N fertilizer requirements of a subsequent crop compared to when they were used to provide N to maximize crop yields. In two-year rotations, the inclusion of pulses reduced GHG emissions compared to all reference rotations in both NN (savings of 475–719 kg CO2e/ha over two years [area basis]; 164–496 kg CO2e/t over two years [yield basis]) and NCR (savings of 489–1185 kg CO2e/ha over two years [area basis]; 335–610 kg CO2e/t over two years [yield basis]), mostly as a result of reduced synthetic N requirements of the whole rotation. The results of the analysis are presented by crop for each pulse-free and pulse-containing cropping sequence for each scenario to allow for flexibility in comparing GHG emissions from various rotations.

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)0.000
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 score0.133
Threshold uncertainty score0.453

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.063
GPT teacher head0.258
Teacher spread0.195 · 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