ArticlePlants (Basel, Switzerland)2023
Evaluation of Soybean Wildfire Prediction via Hyperspectral Imaging.
Article in Plants (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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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.
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Who cites it
10 citing papers in PubMed, 24 citations in OpenAlex.
- Early Detection of Postharvest Potato Tuber Dry Rot Based on Hyperspectral Imaging and a Dual-Branch ResNet12-SE Spatial-Spectral Fusion Network.Journal of fungi (Basel, Switzerland) · 2026Article
- Holistic IoT and cloud-based telemetry architecture for proactive fire monitoring in smart agriculture.Scientific reports · 2026Article
- Visible-near infrared spectral analysis for identification of physiological and genetic features in rice.Breeding science · 2025Article
- Prediction of soybean yellow mottle mosaic virus in soybean using hyperspectral imaging.Plant methods · 2025Article
- Python algorithm package for automated Estimation of major legume root traits using two dimensional images.Scientific reports · 2025Article
- Automatic optimization of regions of interest in hyperspectral images for detecting vegetative indices in soybeans.Frontiers in plant science · 2025Article
- Study on the Determination of Flavor Value of Rice Based on Grid Iterative Search Swarm Optimization Support Vector Machine Model and Hyperspectral Imaging.Sensors (Basel, Switzerland) · 2024Article
- Automatic Evaluation of Soybean Seed Traits Using RGB Image Data and a Python Algorithm.Plants (Basel, Switzerland) · 2023Article
- RDA-Genebank and Digital Phenotyping for Next-Generation Research on Plant Genetic Resources.Plants (Basel, Switzerland) · 2023Article
- Development of a longevity prediction model for cut roses using hyperspectral imaging and a convolutional neural network.Frontiers in plant science · 2023Article
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
Abstract
Plant diseases that affect crop production and productivity harm both crop quality and quantity. To minimize loss due to disease, early detection is a prerequisite. Recently, different technologies have been developed for plant disease detection. Hyperspectral imaging (HSI) is a nondestructive method for the early detection of crop disease and is based on the spatial and spectral information of images. Regarding plant disease detection, HSI can predict disease-induced biochemical and physical changes in plants. Bacterial infections, such as
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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.