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Record W3009658162 · doi:10.5539/jas.v12n4p128

Induced Defoliation and Corn Productivity Performance

2020· article· en· W3009658162 on OpenAlexvenueno aff
Wellington Junior Candido da Silva, Flávio Carlos Dalchiavon

Bibliographic record

VenueJournal of Agricultural Science · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCrop Yield and Soil Fertility
Canadian institutionsnot available
FundersInstituto Federal de Mato Grosso
KeywordsRandomized block designSowingCropAgronomyBiologyPhenologyGrain yieldProductivityDry weightYield (engineering)Horticulture

Abstract

fetched live from OpenAlex

Due to the change in the environment, diseases and insects can reduce the leaf area of agricultural crops. The objective of this study was to determine the impact of induced defoliation on the vegetative and reproductive phases of corn on its agronomic characteristics. The experiment was carried out in the experimental area of the Mato Grosso Federal Institute of Education, Science and Technology, Campo Novo do Parecis campus, in a second crop system in the 2017/2018 agricultural year, with sowing in March. This study used a randomized complete block design, consisting of 24 treatments and three replications, comprising eight phenological stages. The treatments were performed from the fourth leaf stage (V4) to physiological maturation (R5), with defoliation in the lower, middle and upper thirds of the plant. The characteristics evaluated were: plant height, stem diameter, ears insertion height, ears length, ears diameter, ears weight, number of rows per ears, number of grains per row, weight of grain per ears, prolificity; harvest index, weight of one thousand grains and grain yield. Defoliation between the fourth (V4) and twelfth leaves (V12) does not interfere in the evaluated characteristics. Grain and ear weight are interfered when defoliation occurs in the middle and upper third of plants in V12. Defoliation between flowering (R1) and beginning of grain filling (R2) negatively affects the weight of one thousand grains, grain and ear weight, and may reduce grain yield by up to 30%. Defoliation in the upper third of the plant significantly reduces the diameter and length of ears, grain and corn ear of the corn crop.

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 score0.938
Threshold uncertainty score0.185

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.032
GPT teacher head0.217
Teacher spread0.185 · 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

Citations3
Published2020
Admission routes1
Has abstractyes

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