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Record W3003168789

Dataset for: Presence of seed-borne pest and pathogens on/in the seed produced by farmers in the province of Cotopaxi

2019· article· en· W3003168789 on OpenAlexaboutno aff
Israel Navarrete Cueva, Jorge Andrade, Conny Almekinders, P.C. Struik

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicNematode management and characterization studies
Canadian institutionsnot available
Fundersnot available
KeywordsPEST analysisCropHorticultureAgricultureBiologyGeographyAgricultural scienceAgronomyEcology
DOInot available

Abstract

fetched live from OpenAlex

Seed degeneration (PSD) threats potato production in developing countries. PSD is defined as the accumulation of pest and pathogens in/on the seed tuber due to the successive cycles of vegetative propagation leading potentially to a yield and quality reduction (Thomas-Sharma et al., 2016; Pl. Path. [vol 65, issue 1]). However, the understanding of PSD in the Andes is deficient due to the limited comprehension of the spatial distribution of potato seed- and soil- borne pests and pathogens. For this reason, 260 farmers´ seed lots and fields were surveyed in the province of Cotopaxi-Ecuador from September to October 2018. The survey was implemented using a stratified sampling design (stratum = Cantons of Latacunga, Pujili, Salcedo and Saquisili). The sample size was defined based on the seed replacement rate reported by farmers in a pilot study previously implemented. In each place, farmers kindly provided a sample of (1 to 10) potato seed tubers depending on their willingness. In addition to it, a soil sample was collected from the closest field to the house after farmers provided oral consent. Symptoms and damages on the seed tubers caused by insects and fungi were visually inspected following the methodology suggested by James (1971, [Canadian pl. dis. survey {vol. 51}]) and the photography guide of the main pests and pathogens of the potato crop in Ecuador (Montesdeoca et al., 2013)(Reported in sheet coined Insects and Fungi). Virus identification was carried out on plantlets coming from the tubers assessed previously. This was performed by using the kits and the protocol for DAS-ELISA manufactured and suggested by CIP (2007). Six viruses were identified: PVX, PVS, PVY, APLV, PLRV, and APMoV (Reported in sheet coined Virus). Forty three soil samples out of the 260 were selected depending on the farmers’ field altitude and landscape location (Reported in sheet coined nematodes). These were sent to the laboratory of Plant Protection of the National Agriculture Research Center (INIAP) for nematodes identification. Nematodes were identified according to the methodologies of Oostenbrink (1960) and Fenwick (1940). It is expected that this database contributes to a deeper knowledge about the presence of seed-borne pests and pathogens in the tropical highlands of Ecuador and to design better seed system interventions.;The dataset contains data about presence of seed-borne pest and pathogens on/in the seed produced by farmers in the province of Cotopaxi.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.706
Threshold uncertainty score0.062

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)0.0000.000

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 head0.017
GPT teacher head0.229
Teacher spread0.212 · 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
Published2019
Admission routes1
Has abstractyes

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