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Record W4391683706 · doi:10.55905/oelv22n2-049

Impact of defoliation at the reproductive stage in different leaves of the soybean plant

2024· article· en· W4391683706 on OpenAlexaff
Victor Augusto da Costa Escarela, Aracy Camilla Tardin Pinheiro Bezerra, Thiago Lopes Silva, Júlio Cezar Batista Dos Santos, Luciana Celeste Carneiro, Deivid Lopes Machado, Cláudio Hideo Martins da Costa, Simério Carlos Silva Cruz

Bibliographic record

VenueOBSERVATÓRIO DE LA ECONOMÍA LATINOAMERICANA · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoybean genetics and cultivation
Canadian institutionsImpact
FundersFundação de Amparo à Pesquisa do Estado de GoiásCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsStage (stratigraphy)BiologyAgronomyHorticulture

Abstract

fetched live from OpenAlex

Inadequate phytosanitary management can cause a significant reduction in the leaf area of soybean, which directly impacts its yield. The aim of this study was to evaluate the impact of defoliation in the lower, middle and upper leaves of the canopy, at three reproductive stages, on soybean yield, as a tool for improving phytosanitary management. The design was randomized blocks in 3x3+1 factorial scheme, with 4 replicates. The 10 treatments resulted from the combination of 3 defoliation positions on the plant (lower, middle and upper leaves) and 3 phenological stages of the crop (R1, R3 and R5), in addition to a control without defoliation. Morphological and production components and grain yield were evaluated. The data were subjected to analysis of variance and, when a significant difference was identified, the means were subjected to the Dunnett test. It was observed that plants showed a reduction in height in treatments with defoliation in the upper leaves at R1 and R3 stages. For the variables thousand-grain weight and grain yield there was difference only when defoliation was performed at the R5 stage in the upper leaves, resulting in a 16.6% loss in grain yield compared to the control. The soybean crop tolerates a defoliation level of 33.3% up to the R4 stage, in any of the leaves, without significant reduction in grain yield. Upper leaves, from the R5 stage, should be prioritized in the applications of phytosanitary products, which aim to reduce the damage caused by defoliation.

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 score0.095
Threshold uncertainty score0.740

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 head0.021
GPT teacher head0.244
Teacher spread0.223 · 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
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueOBSERVATÓRIO DE LA ECONOMÍA LATINOAMERICANASame topicSoybean genetics and cultivationFrench-language works237,207