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Record W4307066736 · doi:10.1002/csc2.20864

Comparative assessment of early season soybean cultivars in organic and conventional production system for morphological and agronomic traits

2022· article· en· W4307066736 on OpenAlexaffabout
Torin Boyle, Mohsen Yoosefzadeh-Najafabadi, Istvan Rajcan

Bibliographic record

VenueCrop Science · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoybean genetics and cultivation
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsBiologyCanopyCultivarAgronomyOrganic farmingNutrientGrowing seasonBotanyAgricultureEcology

Abstract

fetched live from OpenAlex

Abstract Organic production systems differ from the conventional system, especially because of the insect pest, weed, disease, and nutrient management. Therefore, there has been a focus on increasing performance stability in soybean [ Glycine max (L.) Merr.] cultivars specifically adapted for organic farms. The objective of this study was to conduct a comparative assessment of Maturity Group 0 soybean genotypes grown in both organic and conventional conditions for several traits important in the organic soybean production system, such as early season canopy development, root morphology, nodule production, and nutrient use efficiency. A soybean panel consisting of 33 cultivars was grown in four environments (two locations × two years) on an organic farm and conventional production system farm in Southern Ontario, Canada. Significant differences among genotypes were observed for root morphology and canopy development in the organic environment only. Early season canopy development, root length, nodule mass, and nutrient use efficiency were related to yield in both environments. In addition, yield rank correlations between genotypes in two locations were significant in 2014 ( r = .57) and 2015 ( r = .31), and some large crossover effects were observed in both tested years. The principal components analysis for these and other agronomic traits showed that resource acquisition traits such as canopy development, root length, and nodule mass were more closely related to yield in the organic system than nutrient use efficiency. Overall, the results of this study may be useful for soybean breeders interested in developing cultivars adapted to the organic production system.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.952
Threshold uncertainty score0.233

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 head0.038
GPT teacher head0.275
Teacher spread0.237 · 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

Citations2
Published2022
Admission routes2
Has abstractyes

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