ArticleFrontiers in plant science2020
Machine Learning Techniques for Soybean Charcoal Rot Disease Prediction.
Article in Frontiers in plant science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed, 45 citations in OpenAlex.
- Integrating temporal morphophysiological and genomic markers for precise classification of flowering time in cannabis.Scientific reports · 2026Article
- Feature extraction in sensor plant disease datasets using reformed membership functions independent of class variables.Scientific reports · 2026Article
- Achieving agricultural sustainability through soybean production in Iran: Potential and challenges.Heliyon · 2024Review
- Breeding for disease resistance in soybean: a global perspective.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2022Review
- Soybean cyst nematode detection and management: a review.Plant methods · 2022Review
- A review on antimicrobial peptides databases and the computational tools.Database : the journal of biological databases and curation · 2022Review
- Soybean images dataset for caterpillar andData in brief · 2022Article
- Machine Learning in Agriculture: A Comprehensive Updated Review.Sensors (Basel, Switzerland) · 2021Review
- Posttranslational modifications in proteins: resources, tools and prediction methods.Database : the journal of biological databases and curation · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Early prediction of pathogen infestation is a key factor to reduce the disease spread in plants.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.