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Record W2554452064 · doi:10.4236/jacen.2016.54023

Synthesis of Southern Corn Rootworm Pheromone from S-Citronellol and Its Field Evaluation

2016· article· en· W2554452064 on OpenAlexaff
Thangaiah Subramanian, Meiling Webb, Ganga Viswanathan Bhagavathy, Annett Rozek, Bheema Rao Paraselli, Kamlesh R. Chauhan

Bibliographic record

VenueJournal of Agricultural Chemistry and Environment · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEntomopathogenic Microorganisms in Pest Control
Canadian institutionsTerramera (Canada)
Fundersnot available
KeywordsCitronellolPheromoneWestern corn rootwormBiologyPhosphonium saltWittig reactionSex pheromoneYield (engineering)PopulationPEST analysisAgronomyBotanyChemistryOrganic chemistryGeraniolEssential oilPhysicsSalt (chemistry)

Abstract

fetched live from OpenAlex

Southern rootworm (Diabrotica undecimpunctata howardi) affects several plants such as soybean, sorghum, wheat, cucumber, alfalfa, cucurbits and it is most damaging to corn and peanuts. The pheromone based “attract and kill” strategy is one of the powerful ways to control pest population. To address our key objective of the practical utility of the synthetic pheromone, we have developed a simple synthetic strategy to produce gram scale southern corn rootworm pheromone in nine simple steps starting from S-Citronellol. The present strategy takes advantage of the existing chiral center of commercially available S-Citronellol. To get the basic carbon skeleton of the pheromone, the main step in the synthetic strategy is coupling of aliphatic units through Wittig reaction. The phosphonium salt from a non-functionalized aliphatic bromide followed by Wittig reaction improved the overall yield in the multistep synthesis of this pheromone. The large-scale production of pheromone enabled us to test it in the field.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score1.000

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)0.0010.000

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 head0.007
GPT teacher head0.172
Teacher spread0.165 · 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.

Study designBench or experimental
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

Citations1
Published2016
Admission routes1
Has abstractyes

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