ArticleFrontiers in plant science2023
Satellite imagery for high-throughput phenotyping in breeding plots.
Article in Frontiers in plant science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Deciphering the genetic basis of yield components in wheat by integrating hyperspectral-based phenomes.Plant phenomics (Washington, D.C.) · 2026Article
- Image-based high-throughput phenotyping enables genetic analyses of pod morphological traits in mungbean (Vigna radiata (L.) R. Wilczek).G3 (Bethesda, Md.) · 2026Article
- Beyond high-throughput: leveraging plant phenotyping to improve understanding and prediction of plant growth through process-based models.The New phytologist · 2026Review
- UAV image-derived canopy traits for predicting alfalfa fall dormancy and forage yield in Mediterranean environments.Frontiers in plant science · 2026Article
- Beyond the genome: the role of functional markers in contemporary plant breeding.Frontiers in plant science · 2025Review
- Current methods and future needs for visible and non-visible detection of plant stress responses.Frontiers in plant science · 2025Review
- Pixel to practice: multi-scale image data for calibrating remote-sensing-based winter wheat monitoring methods.Scientific data · 2024Article
- Integrating Hyperspectral Reflectance-Based Phenotyping and SSR Marker-Based Genotyping for Assessing the Salt Tolerance of Wheat Genotypes under Real Field Conditions.Plants (Basel, Switzerland) · 2024Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Advances in breeding efforts to increase the rate of genetic gains and enhance crop resilience to climate change have been limited by the procedure and costs of phenotyping methods. The recent rapid development of sensors, image-processing technology, and data-analysis has provided opportunities for multiple scales phenotyping methods and systems, including satellite imagery. Among these platforms, satellite imagery may represent one of the ultimate approaches to remotely monitor trials and nurseries planted in multiple locations while standardizing protocols and reducing costs. However, the deployment of satellite-based phenotyping in breeding trials has largely been limited by low spatial resolution of satellite images. The advent of a new generation of high-resolution satellites may finally overcome these limitations. The SkySat constellation started offering multispectral images at a 0.5 m resolution since 2020. In this communication we present a case study on the use of time series SkySat images to estimate NDVI from wheat and maize breeding plots encompassing different sizes and spacing. We evaluated the reliability of the calculated NDVI and tested its capacity to detect seasonal changes and genotypic differences. We discuss the advantages, limitations, and perspectives of this approach for high-throughput phenotyping in breeding programs.
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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.