Unmanned aerial platform-based multi-spectral imaging for field phenotyping of maize.
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A Direct Comparison of Remote Sensing Approaches for High-Throughput Phenotyping in Plant BreedingLatin America: A Development Pole for PhenomicsHyperspectral Monitoring of Green Roof Vegetation Health State in Sub-Mediterranean Climate: Preliminary ResultsIntercomparison of Unmanned Aerial Vehicle and Ground-Based Narrow Band Spectrometers Applied to Crop Trait Monitoring in Organic Potato Production.Unmanned Aerial Vehicle Remote Sensing for Field-Based Crop Phenotyping: Current Status and Perspectives.A Novel Remote Sensing Approach for Prediction of Maize Yield Under Different Conditions of Nitrogen Fertilization.From promise to application: root traits for enhanced nutrient capture in rice breeding.Quantitative, Image-Based Phenotyping Methods Provide Insight into Spatial and Temporal Dimensions of Plant Disease.Assessment of Vegetation Indices Derived by UAV Imagery for Durum Wheat Phenotyping under a Water Limited and Heat Stressed Mediterranean Environment.Comparative UAV and Field Phenotyping to Assess Yield and Nitrogen Use Efficiency in Hybrid and Conventional Barley.Uncooled Thermal Camera Calibration and Optimization of the Photogrammetry Process for UAV Applications in Agriculture.Comparative Performance of Ground vs. Aerially Assessed RGB and Multispectral Indices for Early-Growth Evaluation of Maize Performance under Phosphorus Fertilization.A method for automatic segmentation and splitting of hyperspectral images of raspberry plants collected in field conditions.Artificial Neural Network to Predict Vine Water Status Spatial Variability Using Multispectral Information Obtained from an Unmanned Aerial Vehicle (UAV).Conventional and hyperspectral time-series imaging of maize lines widely used in field trials.Genomics-Enabled Next-Generation Breeding Approaches for Developing System-Specific Drought Tolerant Hybrids in Maize.Estimation of vegetation indices for high-throughput phenotyping of wheat using aerial imaging.Translating High-Throughput Phenotyping into Genetic Gain.Comparative Aerial and Ground Based High Throughput Phenotyping for the Genetic Dissection of NDVI as a Proxy for Drought Adaptive Traits in Durum WheatUAV-based high-throughput phenotyping to discriminate barley vigour with visible and near-infrared vegetation indices
P2860
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P2860
Unmanned aerial platform-based multi-spectral imaging for field phenotyping of maize.
description
2015 nî lūn-bûn
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2015年の論文
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2015年学术文章
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name
Unmanned aerial platform-based multi-spectral imaging for field phenotyping of maize.
@en
type
label
Unmanned aerial platform-based multi-spectral imaging for field phenotyping of maize.
@en
prefLabel
Unmanned aerial platform-based multi-spectral imaging for field phenotyping of maize.
@en
P2093
P2860
P50
P1433
P1476
Unmanned aerial platform-based multi-spectral imaging for field phenotyping of maize.
@en
P2093
A Hernández Albà
A Tarekegne
B M Prasanna
C Magorokosho
P Craufurd
P J Zarco-Tejada
P2860
P2888
P356
10.1186/S13007-015-0078-2
P577
2015-06-24T00:00:00Z
P5875
P6179
1006551588