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Record W2106510734 · doi:10.1093/jee/97.6.2079

Rapid Method to Screen Resistance of Potato Plants Against Myzus persicae (Homoptera: Aphididae) in the Laboratory

2004· article· en· W2106510734 on OpenAlexaff
Vincent Le Roux, Julien Saguez, Charles Vincent, Philippe Giordanengo

Bibliographic record

VenueJournal of Economic Entomology · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect-Plant Interactions and Control
Canadian institutionsInstitut de Recherche et de Développement en AgroenvironnementAgriculture and Agri-Food Canada
Fundersnot available
KeywordsMyzus persicaeHomopteraBiologyAphididaeHorticultureSolanum tuberosumBotanyAphidPEST analysis

Abstract

fetched live from OpenAlex

With the objective to develop a potato, Solanum tuberosum L., resistance program against aphids, we propose a rapid screening method with Myzus persicae (Sulzer) in the laboratory. We aimed to optimize the duration of the whole procedure and to decrease the frequency of measurements. In a first experiment, intrinsic rate of natural increase (r(m)) values were compared between adult aphids reared throughout their entire life and adults reared only during a period equivalent to their prereproductive period. No significant differences were observed. In a second experiment, four groups of aphids were distinguished according to the sampling frequency, i.e., those whose biological parameters were evaluated every single, second, third, and fourth day. Except for the fourth-day experiment, the r(m) values estimated on aphids reared on the three potato lines were not significantly different whatever sampling frequency of single, second, or third day used to check aphids. Thus, screening efforts in laboratory can be largely optimized by evaluating adult aphids only during a period equivalent to their prereproductive period and assessing M. persicae populations every third day. Our method is reliable and adapted to screen a large number of potato plants against M. persicae because it allows an average 70% reduction in the time required for the whole experimental process.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.748
Threshold uncertainty score0.144

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)0.0000.000

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 head0.015
GPT teacher head0.248
Teacher spread0.233 · 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 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

Citations20
Published2004
Admission routes1
Has abstractyes

Explore more

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