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Record W2949778760 · doi:10.5539/jas.v11n9p213

Conversion Efficiency of Photosynthetically Active Radiation for Soybean Cultivations in Spatial Arrangements

2019· article· en· W2949778760 on OpenAlexvenueno aff
Braulio Otomar Caron, Ana Paula Rockenbach, Denise Schmidt, Thaise Dieminger Engroff, Felipe Schwerz, Júlia Renata Schneider

Bibliographic record

VenueJournal of Agricultural Science · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoybean genetics and cultivation
Canadian institutionsnot available
FundersConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsPhotosynthetically active radiationInterceptionLeaf area indexCultivarAgronomyHorticultureEnvironmental scienceMathematicsBotanyBiologyPhotosynthesisEcology

Abstract

fetched live from OpenAlex

The objective of this paper was to assess the efficiency of photosynthetically active radiation (PAR) intercepted in dried phytomass of soybean cultivars of determinate and indeterminate growth habits in different spatial arrangements. All experiments were carried out during the 2013/2014 crop year, two soybean cultivars (BMX Ativa RR/determinate and BMX Turbo RR/indeterminate) in a spatial arrangements (45, crossed, 20, 20 × 40, 20 × 60, 20 × 80 cm). Starting from first emergence up to the point of maturation, 14 phytomass assessment were evaluated with seven days interval, in which one plant was sampled per repetition. Greater conversion efficiencies of solar radiation were obtained in paired arrangements. Paired arrangements, and 20 cm, lead to a greater leaf area index, and possibly a greater interception of the diffused radiation and an increase of conversion efficiency and the overall cultivation productivity of BMX Ativa RR and BMX Turbo RR.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.011
GPT teacher head0.225
Teacher spread0.214 · 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 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
Published2019
Admission routes1
Has abstractyes

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Same venueJournal of Agricultural ScienceSame topicSoybean genetics and cultivationFrench-language works237,207