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Record W2970121015 · doi:10.5539/jas.v11n15p97

Migdolus fryanus Damage Causes Decrease in the Starch Content in Manihot esculenta

2019· article· en· W2970121015 on OpenAlexvenueno aff
Júlio César Guerreiro, Ana Paula Azevedo, Renan R. Espessato, Vanda Pietrowski, Rudiney Ringenberg, Pedro J. Ferreira-Filho, Rerison Catarino da Hora, Evandro Pereira Prado, Thaise Mylena Pascutti

Bibliographic record

VenueJournal of Agricultural Science · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCassava research and cyanide
Canadian institutionsnot available
FundersUniversidade de São PauloCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsStarchManihot esculentaCropHorticultureAgronomyBiologyPEST analysisBotanyFood science

Abstract

fetched live from OpenAlex

The beetle M. fryanus causes serious damage to cassava in Brazil. However, due to the subterranean behavior of the larvae and the recent appearance of this pest in cassava, little is known about the main behavioral characteristics and damage caused to this crop. The main aim of this study is to demonstrate the variation of starch production in the roots of M. esculenta as a result of the intensity of damage caused by M. fryanus. The study was carried out in a commercial cassava farm in Paraná, Brazil. The proposed scale for damage was: (1) No apparent root damage; (2) roots with scrapings; (3) roots with scraping across the cortex; (4) damaged roots and galleries; (5) roots with galleries and presentation of rot. The parameters evaluated were the damage caused by M. fryanus in roots and starch content, estimated by using a hydrostatic scale, starch extracted by cassava processing, and the starch reduction percentage in damaged roots, assessed by using the hydrostatic scale (SC) and processing methods (SCP). It was observed that there was manifestation of damage in approximately 60% of the roots collected directly from the ground, with levels representing loss of starch produced by the plant. Decreases in the productive parameters, such as starch content, were measured according to the increase of the proposed damage levels in the two cassava cultivation cycles, with a starch reduction rate higher than 20% when the roots suffered the most severe damage.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.894
Threshold uncertainty score0.492

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.049
GPT teacher head0.266
Teacher spread0.217 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

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