ArticleFrontiers in plant science2017
Comparative Performance of Ground vs. Aerially Assessed RGB and Multispectral Indices for Early-Growth Evaluation of Maize Performance under Phosphorus Fertilization.
Article in Frontiers in plant science, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.
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25 citing papers in PubMed, 1 synthesis or guideline pooled it, 126 citations in OpenAlex.
- Establishing a knowledge structure for yield prediction in cereal crops using unmanned aerial vehicles.Frontiers in plant science · 2024Pooled it
- Methodology for Selecting Stable UAV-Based Vegetation Indices for Prediction of Agronomic Variables in Maize Using a Multispectral Sensor.Plants (Basel, Switzerland) · 2026Article
- Impact of Land use on soil quality: Insights from the forest-savannah transition zone of Ghana.Heliyon · 2025Article
- A combined model of shoot phosphorus uptake based on sparse data and active learning algorithm.Frontiers in plant science · 2024Article
- Advancements in Imaging Sensors and AI for Plant Stress Detection: A Systematic Literature Review.Plant phenomics (Washington, D.C.) · 2024Article
- Spectral indices with different spatial resolutions in recognizing soybean phenology.PloS one · 2024Article
- Field Plant Monitoring from Macro to Micro Scale: Feasibility and Validation of Combined Field Monitoring Approaches from Remote to in Vivo to Cope with Drought Stress in Tomato.Plants (Basel, Switzerland) · 2023Article
- CropQuant-Air: an AI-powered system to enable phenotypic analysis of yield- and performance-related traits using wheat canopy imagery collected by low-cost drones.Frontiers in plant science · 2023Article
- Remote sensing continuity: a comparison of HTP platforms and potential challenges with field applications.Frontiers in plant science · 2023Article
- AirMeasurer: open-source software to quantify static and dynamic traits derived from multiseason aerial phenotyping to empower genetic mapping studies in rice.The New phytologist · 2022Article
- LED color gradient as a new screening tool for rapid phenotyping of plant responses to light quality.GigaScience · 2022Article
- Integrated diagnosis and time-series sensitivity evaluation of nutrient deficiencies in medicinal plant (Frontiers in plant science · 2022Article
- Performance comparison of RGB and multispectral vegetation indices based on machine learning for estimatingFrontiers in plant science · 2022Article
- Haplotype analysis from unmanned aerial vehicle imagery of rice MAGIC population for the trait dissection of biomass and plant architecture.Journal of experimental botany · 2021Article
- Remote-Sensing-Combined Haplotype Analysis Using Multi-Parental Advanced Generation Inter-Cross Lines Reveals Phenology QTLs for Canopy Height in Rice.Frontiers in plant science · 2021Article
- Peanut Leaf Wilting Estimation From RGB Color Indices and Logistic Models.Frontiers in plant science · 2021Article
- Identification of Quantitative Trait Loci Hotspots Affecting Agronomic Traits and High-Throughput Vegetation Indices in Rainfed Wheat.Frontiers in plant science · 2021Article
- Leaf versus whole-canopy remote sensing methodologies for crop monitoring under conservation agriculture: a case of study with maize in Zimbabwe.Scientific reports · 2020Article
- Evaluating Maize Genotype Performance under Low Nitrogen Conditions Using RGB UAV Phenotyping Techniques.Sensors (Basel, Switzerland) · 2019Article
- Opportunities and Limitations of Crop Phenotyping in Southern European Countries.Frontiers in plant science · 2019Review
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Low soil fertility is one of the factors most limiting agricultural production, with phosphorus deficiency being among the main factors, particularly in developing countries. To deal with such environmental constraints, remote sensing measurements can be used to rapidly assess crop performance and to phenotype a large number of plots in a rapid and cost-effective way. We evaluated the performance of a set of remote sensing indices derived from Red-Green-Blue (RGB) images and multispectral (visible and infrared) data as phenotypic traits and crop monitoring tools for early assessment of maize performance under phosphorus fertilization. Thus, a set of 26 maize hybrids grown under field conditions in Zimbabwe was assayed under contrasting phosphorus fertilization conditions. Remote sensing measurements were conducted in seedlings at two different levels: at the ground and from an aerial platform. Within a particular phosphorus level, some of the RGB indices strongly correlated with grain yield. In general, RGB indices assessed at both ground and aerial levels correlated in a comparable way with grain yield except for indices a
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