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Record W2971674009 · doi:10.1093/jee/toz215

Evaluation of Tactics for Management of Sugarcane Aphid (Hemiptera: Aphididae) in Grain Sorghum

2019· article· en· W2971674009 on OpenAlexfundno aff
Phillip Joseph Haar, G. David Buntin, Alana L. Jacobson, Adrian J. Pekarcik, M. O. Way, Ali A. Zarrabi

Bibliographic record

VenueJournal of Economic Entomology · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect-Plant Interactions and Control
Canadian institutionsnot available
FundersBayer CanadaAgricultural Research ServiceNational Institute of Food and AgricultureUnited Sorghum Checkoff Program
KeywordsBiologyAphidAgronomySorghumSowingAphididaeClothianidinIntegrated pest managementPEST analysisHorticulturePesticideImidacloprid

Abstract

fetched live from OpenAlex

The invasive sugarcane aphid, Melanaphis sacchari (Zehntner), is a devastating new pest of grain sorghum. Studies were conducted utilizing an integrated approach of four management tactics: planting date, insecticidal seed treatment, a foliar-applied insecticide, and plant resistance. Experiments were conducted in 2016 and 2017 at Griffin, Tifton, and Plains Georgia, and in 2016 in Texas, Alabama, and Oklahoma, United States. Early planting was effective in reducing damage and increasing yields when compared to the late planting. Use of a resistant variety reduced cumulative aphid-days, plant injury and usually prevented significant yield loss. Foliar application of flupyradifurone when aphids reached an economic threshold, was an effective management tactic preventing aphid injury and yield loss. Use of clothianidin seed treatment also reduced aphid injury and yield loss of the susceptible hybrid but generally did not prevent injury and yield loss of the resistant hybrid. We conclude that an earlier planting date coupled with a resistant variety and judicious use of an efficacious foliar-applied insecticide can effectively manage sugarcane aphid on grain sorghum. An insecticide seed treatment also may be useful to reduce the risk of sugarcane aphid damage to seedlings of susceptible hybrids.

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)0.001
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 score0.581
Threshold uncertainty score0.705

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.025
GPT teacher head0.271
Teacher spread0.246 · 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

Citations39
Published2019
Admission routes1
Has abstractyes

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