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Complexities in the Implementation and Maintenance of Integrated Pest Management in Potato

2024· review· en· W4402249817 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnnual Review of Entomology · 2024
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicPotato Plant Research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsIntegrated pest managementPEST analysisAgriculturePest controlAgroforestryCrop rotationCrop protectionBiologyBiotechnologyBusinessRisk analysis (engineering)EcologyMarketing

Abstract

fetched live from OpenAlex

Integrated pest management (IPM) is an educated and systematic effort to use multiple control techniques to reduce pest damage to economically acceptable levels while minimizing negative environmental impacts. Although its benefits are widely acknowledged, IPM is not universally practiced by farmers. Potato farming, which produces one of the most important staple crops in the world, provides a good illustration of the issues surrounding IPM adoption. Potatoes are attacked by a complex of insect pests that can inflict catastrophic crop losses. Potato production has gone through the processes of consolidation and intensification, which are linked to increased pest problems, particularly selection for insecticide-resistant pest populations. While use of insecticides remains the most common method of pest control in potatoes, other techniques, including crop rotation and natural enemies, are also available. In addition, there are effective monitoring techniques for many potato pests. However, reliable economic thresholds are often lacking. Potato ecosystems are complex and diverse; therefore, the knowledge necessary for developing ecologically based pest management is not easily obtained or transferable. Furthermore, potato systems change with the arrival of new pest species and the evolution of existing pests. Modern technological advances, such as remote sensing and molecular biotechnology, are likely to improve potato IPM. However, these tools are not going to solve all problems. IPM is not just about integrating different techniques; it is also about integrating the efforts and concerns of all stakeholders. The collaboration of farmers and scientists in agricultural research is needed to foster the development of IPM systems that are appropriate for grower implementation and thus more likely to be adopted. Additional emphasis also needs to be placed on the fact that not only does IPM decrease degradation of the environment, but it also improves the economic well-being of its practitioners.

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.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.950
Threshold uncertainty score0.227

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.060
GPT teacher head0.397
Teacher spread0.337 · 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