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Record W4411722055 · doi:10.1093/jee/toaf101

An evaluation of insecticide and nitrogen fertility programs in dry bulb onions in the treasure valley of Eastern Oregon and Southwest Idaho in 2019 to 2021

2025· article· en· W4411722055 on OpenAlexaboutno aff
Gina A Greenway, Silvia I. Rondon, Anitha Chitturi, Willliam Buhrig, Stuart R. Reitz

Bibliographic record

VenueJournal of Economic Entomology · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGarlic and Onion Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyAgronomyBulbHuman fertilizationNitrogenToxicologyNitrogen fertilizerAgricultural scienceCropProfitability indexFertilizerAgroforestryHorticultureBusinessFinance

Abstract

fetched live from OpenAlex

Field studies were conducted at Oregon State University, Malheur Experiment Station, Ontario, Oregon, from 2019 to 2021 for evaluation of optimal use of insecticides and in-season nitrogen fertilization to maximize profitability of dry bulb onion production. Insecticide programs included a control, a calendar-based weekly program, and an action threshold-based integrated pest management program. Nitrogen fertility was evaluated at two levels, standard and reduced. The standard nitrogen fertility program was based on recommended rates determined from soil and tissue tests. The reduced program delivered nitrogen at 50% of the recommended amount. Results pertaining to optimal use of insecticides were inconclusive. Each year of the study resulted in a different outcome relating to best practices for timing and delivering insecticide applications, indicating the need for more research. Standard nitrogen fertilization programs optimized profit in all 3 years of the study. The greater overall profitability of the standard fertilization program provides evidence to support using and following recommendations from soil and tissue tests for economically advantageous management of in-season nitrogen fertilization of dry bulb onions. The relative value of benefits from every dollar spent on nitrogen fertilizer during each year of the study was also evaluated using benefit-cost ratios. Even when the price of nitrogen was high relative to the value of the crop, investment in nitrogen still produced positive economic benefits.

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)0.002
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 score0.047
Threshold uncertainty score0.968

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.058
GPT teacher head0.300
Teacher spread0.242 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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