SynthesisSensors (Basel, Switzerland)2023
Plant Disease Detection and Classification: A Systematic Literature Review.
Synthesis in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed, 60 citations in OpenAlex.
- Fungal infections: Classification performance and detectability with machine learning models.Scientific reports · 2026Article
- MambaSeed: A lightweight Mamba-based hybrid vision network for tomato leaf disease recognition.PloS one · 2026Article
- Optimised hybrid late fusion deep learning model for cashew disease classification.Frontiers in plant science · 2026Article
- Explainable AI for Cotton Leaf Disease Classification: A Metaheuristic-Optimized Deep Learning Approach.Food science & nutrition · 2025Article
- InsightNet: A Deep Learning Framework for Enhanced Plant Disease Detection and Explainable Insights.Plant direct · 2025Article
- Evaluation of Different Few-Shot Learning Methods in the Plant Disease Classification Domain.Biology · 2025Article
- A robust hydroponic system for horticulture farming using deep learning, IoT, and mobile application.PloS one · 2025Article
- Deep learning networks-based tomato disease and pest detection: a first review of research studies using real field datasets.Frontiers in plant science · 2024Review
- Advancements in Imaging Sensors and AI for Plant Stress Detection: A Systematic Literature Review.Plant phenomics (Washington, D.C.) · 2024Article
- A Smartphone-Based Detection System for Tomato Leaf Disease Using EfficientNetV2B2 and Its Explainability with Artificial Intelligence (AI).Sensors (Basel, Switzerland) · 2023Article
- Detection of citrus diseases in complex backgrounds based on image-text multimodal fusion and knowledge assistance.Frontiers in plant science · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 4 institutions in 3 countries.
Funding
Abstract
A significant majority of the population in India makes their living through agriculture. Different illnesses that develop due to changing weather patterns and are caused by pathogenic organisms impact the yields of diverse plant species. The present article analyzed some of the existing techniques in terms of data sources, pre-processing techniques, feature extraction techniques, data augmentation techniques, models utilized for detecting and classifying diseases that affect the plant, how the quality of images was enhanced, how overfitting of the model was reduced, and accuracy. The research papers for this study were selected using various keywords from peer-reviewed publications from various databases published between 2010 and 2022. A total of 182 papers were identified and reviewed for their direct relevance to plant disease detection and classification, of which 75 papers were selected for this review after exclusion based on the title, abstract, conclusion, and full text. Researchers will find this work to be a useful resource in recognizing the potential of various existing techniques through data-driven approaches while identifying plant diseases by enhancing system performance and accuracy.
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.