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Record W2885654543 · doi:10.5539/jas.v10n9p364

Resistance of Saccharine Sorghum Cultivars to Sugarcane Borer Diatraea saccharalis

2018· article· en· W2885654543 on OpenAlexvenueno aff
Lauren Medina Barcelos, A. P. S. A. da Rosa, Beatriz Marti Emygdio, Ricardo Alexandre Valgas, Indyra F. Carvalho

Bibliographic record

VenueJournal of Agricultural Science · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect-Plant Interactions and Control
Canadian institutionsnot available
Fundersnot available
KeywordsDiatraea saccharalisCultivarSorghumBiologyAntibiosisAgronomyPupaCrambidaeSugarLarvaHorticultureBotanyFood science

Abstract

fetched live from OpenAlex

The saccharine sorghum has been investigated as a complementary source of raw material for ethanol production, especially during the sugarcane off-season, however, it has been susceptible to the attack of the sugarcane borer Diatraea saccharalis. The objective of this work was to verify the effect of sorghum cultivars on D. saccharalis’ biological parameters. Cultivars, BRS 506, BRS 509 and BRS 511 were used to determine duration and survival rates of eggs, larvae, pre-pupae and pupa phases, along with larval weight and adult longevity. D. saccharalis completed its biological cycle in all treatments, however, when fed with dry extracts of BRS 509 cultivar, the net reproduction rate, the intrinsic rate of increase and the finite rate of increase was superior from the others. BRS 506 was the cultivar that negatively affected D. saccharalis’ biological parameters, with possible antibiosis effect. Based on this study, the sorghum cultivars evaluated are not recommended for a grain production system, since D. saccharalis’ larvae presented good development when fed with its dry extract incorporated into the diet.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.010
GPT teacher head0.230
Teacher spread0.220 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

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