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Agronomy 2014, 4(3), 322-336; doi:10.3390/agronomy4030322

Development of a Mobile Multispectral Imaging Platform for Precise Field Phenotyping

Department of Plant and Environmental Sciences, University of Copenhagen, Thorvaldsensvej 40, Frederiksberg C DK-1871, Denmark
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Received: 19 February 2014 / Revised: 12 June 2014 / Accepted: 13 June 2014 / Published: 1 July 2014
(This article belongs to the Special Issue New Phenotyping Platforms for Field Trials)
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Abstract

Phenotyping in field experiments is challenging due to interactions between plants and effects from biotic and abiotic factors which increase complexity in plant development. In such environments, visual or destructive measurements are considered the limiting factor and novel approaches are necessary. Remote multispectral imaging is a powerful method that has shown significant potential to estimate crop physiology. However, precise measurements of phenotypic differences between crop varieties in field experiments require exclusion of the disturbances caused by wind and varying sunlight. A mobile and closed multispectral imaging system was developed to study canopies in field experiments. This system shuts out wind and sunlight to ensure the highest possible precision and accuracy. Multispectral images were acquired in an experiment with four different wheat varieties, two different nitrogen levels, replicated on two different soil types at four different dates from 15 May (BBCH 13) to 18 June (BBCH 41 to 57). The images were analyzed and derived vegetation coverage and Normalized Difference Vegetation index (NDVI) were used to assess varietal differences. The results showed potentials for differentiating between the varieties using both vegetation coverage and NDVI, especially at the early growth stages. The perspectives of high-precision and high-throughput imaging for field phenotyping are discussed including the potentials of measuring varietal differences via spectral imaging in comparison to other simpler technologies such as spectral reflectance and RGB imaging. View Full-Text
Keywords: field phenotyping; multispectral imaging; supervised classification; canonical discriminant analysis; vegetation coverage; NDVI field phenotyping; multispectral imaging; supervised classification; canonical discriminant analysis; vegetation coverage; NDVI
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MDPI and ACS Style

Svensgaard, J.; Roitsch, T.; Christensen, S. Development of a Mobile Multispectral Imaging Platform for Precise Field Phenotyping. Agronomy 2014, 4, 322-336.

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