ArticleFrontiers in plant science2017
Comparative UAV and Field Phenotyping to Assess Yield and Nitrogen Use Efficiency in Hybrid and Conventional Barley.
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 38 papers, 1 of them a synthesis that pooled it.
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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
38 citing papers in PubMed, 1 synthesis or guideline pooled it, 150 citations in OpenAlex.
- Establishing a knowledge structure for yield prediction in cereal crops using unmanned aerial vehicles.Frontiers in plant science · 2024Pooled it
- Current methods and future needs for visible and non-visible detection of plant stress responses.Frontiers in plant science · 2025Review
- Visualizing Plant Responses: Novel Insights Possible Through Affordable Imaging Techniques in the Greenhouse.Sensors (Basel, Switzerland) · 2024Article
- A global dataset for assessing nitrogen-related plant traits using drone imagery in major field crop species.Scientific data · 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
- Remotely Sensed Phenotypic Traits for Heritability Estimates and Grain Yield Prediction of Barley Using Multispectral Imaging from UAVs.Sensors (Basel, Switzerland) · 2023Article
- Liposomal Formulation of Botanical Extracts may Enhance Yield Triggering PR Genes and Phenylpropanoid Pathway in Barley (Plants (Basel, Switzerland) · 2022Article
- Capturing crop adaptation to abiotic stress using image-based technologies.Open biology · 2022Review
- Sugarcane Nitrogen Concentration and Irrigation Level Prediction Based on UAV Multispectral Imagery.Sensors (Basel, Switzerland) · 2022Article
- Comprehensive assessment of intelligent unmanned vehicle techniques in pesticide application: A case study in pear orchard.Frontiers in plant science · 2022Article
- Rapid prediction of winter wheat yield and nitrogen use efficiency using consumer-grade unmanned aerial vehicles multispectral imagery.Frontiers in plant science · 2022Article
- Source-Sink Dynamics in Field-Grown Durum Wheat Under Contrasting Nitrogen Supplies: Key Role of Non-Foliar Organs During Grain Filling.Frontiers in plant science · 2022Article
- Statistical Methods for the Quantitative Genetic Analysis of High-Throughput Phenotyping Data.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Performance comparison of RGB and multispectral vegetation indices based on machine learning for estimatingFrontiers in plant science · 2022Article
- Sustainability Trait Modeling of Field-Grown Switchgrass (Plants (Basel, Switzerland) · 2021Article
- Omics for the Improvement of Abiotic, Biotic, and Agronomic Traits in Major Cereal Crops: Applications, Challenges, and Prospects.Plants (Basel, Switzerland) · 2021Review
- Peanut Leaf Wilting Estimation From RGB Color Indices and Logistic Models.Frontiers in plant science · 2021Article
- Genetic Yield Gains and Changes in Morphophysiological-Related Traits of Winter Wheat in Southern Chilean High-Yielding Environments.Frontiers in plant science · 2021Article
- Comparative Performance of High-Yielding European Wheat Cultivars Under Contrasting Mediterranean Conditions.Frontiers in plant science · 2021Article
- Phenotyping Flowering in Canola (Frontiers in plant science · 2021Article
Corrections and comments
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Authors and funding
9 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the commercialization and increasing availability of Unmanned Aerial Vehicles (UAVs) multiple rotor copters have expanded rapidly in plant phenotyping studies with their ability to provide clear, high resolution images. As such, the traditional bottleneck of plant phenotyping has shifted from data collection to data processing. Fortunately, the necessarily controlled and repetitive design of plant phenotyping allows for the development of semi-automatic computer processing tools that may sufficiently reduce the time spent in data extraction. Here we present a comparison of UAV and field based high throughput plant phenotyping (HTPP) using the free, open-source image analysis software FIJI (Fiji is just ImageJ) using RGB (conventional digital cameras), multispectral and thermal aerial imagery in combination with a matching suite of ground sensors in a study of two hybrids and one conventional barely variety with ten different nitrogen treatments, combining different fertilization levels and application schedules. A detailed correlation network for physiological traits and exploration of the data comparing between treatments and varieties provided insights into crop performance under different management scenarios. Multivariate regression models explained 77.8, 71.6, and 82.7% of the variance in yield from aerial, ground, and combined data sets, respectively.
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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.