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Record W3084067913 · doi:10.5539/jas.v12n10p16

Performance of Spodoptera frugiperda (Lepidoptera: Noctuidae) Fed on Six Host Plants: Potential Risks to Mid-high Latitude Crops in China

2020· article· en· W3084067913 on OpenAlexvenueno aff
Yu Chen, Jingfei Guo, Zupeng Gao, Kanglai He, Shuxiong Bai, Tiantao Zhang, Zhenying Wang

Bibliographic record

VenueJournal of Agricultural Science · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect Resistance and Genetics
Canadian institutionsnot available
FundersAgricultural Science and Technology Innovation ProgramChinese Academy of Agricultural Sciences
KeywordsNoctuidaeLepidoptera genitaliaBiologyFall armywormSpodopteraPEST analysisAgronomySorghumPupaLarvaFecundityHost (biology)HorticultureBotanyEcology

Abstract

fetched live from OpenAlex

The fall armyworm, Spodoptera frugiperda (J. E. Smith) (Lepidoptera: Noctuidae), is a polyphggous and widespread insect pest. In the study, the biological characteristics and nutritional indices of S. frugiperda fed on six crops, namely corn, sorghum, wheat, soybean, peanut, and cotton, were investigated under laboratory conditions. These crops are cultivated mainly in the mid-high latitude of China. Results showed that S. frugiperda was able to develop and reproduce on all six tested plants. Larvae reared on corn exhibited a significant shorter larval and pupal duration, higher pupal weight, and higher fecundity, which were 16.2 d, 8.9 d, 0.248 g, and 979.4 eggs per female, respectively. The host plant significantly affected relative growth, consumption, and metabolic rates, as well as other nutritional indices. Biology and nutritional indexes suggested that corn was the most suitable host. Besides, peanut, sorghum, and wheat have also been shown to be the suitable hosts for S. frugiperda. Although cotton and soybean were found to be less adequate, high larval and pupal survivors recorded on cotton and soybean leaves have indicated that damage may occur in these plants. This work reveals the damage risk of potential hosts of S. frugiperda, lays the foundation for the design of pest management strategies.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.603
Threshold uncertainty score0.360

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 head0.008
GPT teacher head0.234
Teacher spread0.225 · 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

Citations24
Published2020
Admission routes1
Has abstractyes

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