ArticleSensors (Basel, Switzerland)2020
Detection of
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed.
- Black Oat (Current pharmaceutical design · 2026Article
- UV reflectance in crop remote sensing: Assessing the current state of knowledge and extending research with strawberry cultivars.PloS one · 2024Review
- Fungal identification in peanuts seeds through multispectral images: Technological advances to enhance sanitary quality.Frontiers in plant science · 2023Article
- Vigour testing for the rice seed with computer vision-based techniques.Frontiers in plant science · 2023Article
- Integrating optical imaging techniques for a novel approach to evaluate Siberian wild rye seed maturity.Frontiers in plant science · 2023Article
- Fungal Pathogens and Seed Storage in the Dry State.Plants (Basel, Switzerland) · 2022Review
- Review
- Single Seed Identification in ThreeSensors (Basel, Switzerland) · 2022Article
- Anemochore Seeds Harbor Distinct Fungal and Bacterial Abundance, Composition, and Functional Profiles.Journal of fungi (Basel, Switzerland) · 2022Article
- An Approach Using Emerging Optical Technologies and Artificial Intelligence Brings New Markers to Evaluate Peanut Seed Quality.Frontiers in plant science · 2022Article
- Autofluorescence-spectral imaging as an innovative method for rapid, non-destructive and reliable assessing of soybean seed quality.Scientific reports · 2021Article
- Non-Destructive Identification of Naturally Aged Alfalfa Seeds via Multispectral Imaging Analysis.Sensors (Basel, Switzerland) · 2021Article
- Multispectral and X-ray images for characterization of Jatropha curcas L. seed quality.Plant methods · 2021Article
- Integrating Optical Imaging Tools for Rapid and Non-invasive Characterization of Seed Quality: Tomato (Frontiers in plant science · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Conventional methods for detecting seed-borne fungi are laborious and time-consuming, requiring specialized analysts for characterization of pathogenic fungi on seed. Multispectral imaging (MSI) combined with machine vision was used as an alternative method to detect
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.