ArticleSensors (Basel, Switzerland)2020
Machine Learning for Seed Quality Classification: An Advanced Approach Using Merger Data from FT-NIR Spectroscopy and X-ray Imaging.
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 23 papers, 1 of them a synthesis that pooled it.
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.
The trial behind it
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Who cites it
23 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Harnessing large vision and language models in agriculture: a review.Frontiers in plant science · 2025Pooled it
- Progeny Differentiation in Faba Bean Using Hyperspectral Images and Machine Learning.Plant direct · 2026Article
- Integrating AI in seed science: Toward an intelligent design paradigm.Plant communications · 2026Review
- An AI-Driven Dual-Spectral Vision-Language Sensing Framework for Intelligent Agricultural Phenotyping.Sensors (Basel, Switzerland) · 2026Article
- Deep learning-based seed germination prediction using morphological traits and RGB images.BMC plant biology · 2026Article
- Understanding seed germination responses to low-dose X-rays: the role of seed quality, variety, and density.Plant methods · 2025Article
- Current State of the Art and Potential for Construction and Demolition Waste Processing: A Scoping Review of Sensor-Based Quality Monitoring and Control for In- and Online Implementation in Production Processes.Sensors (Basel, Switzerland) · 2025Review
- Predicting Perennial Ryegrass Cultivars and the Presence of anSensors (Basel, Switzerland) · 2025Article
- Digital techniques and trends for seed phenotyping using optical sensors.Journal of advanced research · 2024Review
- RT-DETR-SoilCuc: detection method for cucumber germinationinsoil based environment.Frontiers in plant science · 2024Article
- Evaluation of cucumber seed germination vigor under salt stress environment based on improved YOLOv8.Frontiers in plant science · 2024Article
- Molecular dynamics of seed priming at the crossroads between basic and applied research.Plant cell reports · 2023Review
- Near-infrared spectroscopy for early selection of waxy cassava clones via seed analysis.Frontiers in plant science · 2023Article
- POMONA: a multiplatform software for modeling seed physiology.Frontiers in plant science · 2023Article
- Fungal identification in peanuts seeds through multispectral images: Technological advances to enhance sanitary quality.Frontiers in plant science · 2023Article
- YOLOv8-Peas: a lightweight drought tolerance method for peas based on seed germination vigor.Frontiers in plant science · 2023Article
- A Review of Machine Learning for Near-Infrared Spectroscopy.Sensors (Basel, Switzerland) · 2022Review
- Radiographic Imaging as a Quality Index Proxy forPlants (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
- Review
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Optical sensors combined with machine learning algorithms have led to significant advances in seed science. These advances have facilitated the development of robust approaches, providing decision-making support in the seed industry related to the marketing of seed lots. In this study, a novel approach for seed quality classification is presented. We developed classifier models using Fourier transform near-infrared (FT-NIR) spectroscopy and X-ray imaging techniques to predict seed germination and vigor. A forage grass (
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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.