Special Issue "New Phenotyping Platforms for Field Trials"
A special issue of Agronomy (ISSN 2073-4395).
Deadline for manuscript submissions: closed (15 February 2014)
Prof. Dr. Adrian C. Newton
The James Hutton Institute, Invergowrie, Dundee DD2 5DA, Scotland, UK; Visiting Professor of Cereal Pathology, SRUC, Edinburgh
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Interests: analysing epidemic spatial trends and local competition effects in heterogeneous vegetation; the effects of climate change particularly on plant disease; Mechanisms of foliar blight pathogen resistance in barley; developing resistance elicitors as crop protectants; Integrated Pest Management (IPM)
The ever increasing amount of DNA sequence information for crop species coupled with the developments in methods to assess sequence polymorphisms and the decrease in assay costs mean that detailed genotypic data can be rapidly and efficiently generated for most populations of most species. Such information has little value unless sequence variation in specific genomic regions of a crop can be interpreted as leading to measureable differences in characteristics or phenotype. Large effects on plant phenotypes can be detected in small populations but most of these have at least been well characterised if not assigned to cloned genes. Plant researchers and breeders are now working on more quantitative characters of smaller effect that require much larger populations to assign phenotypic differences to specific genomic regions. This has resulted in the so-called ‘phenotypic bottleneck’ where traditional assessments of field trials, e.g. recording visual symptoms of biotic and abiotic stress, major crop developmental stage recording, yield estimates from bags of harvested grain and post-harvest quantitative measurements limit the size of population that can be grown, as well as the accuracy and efficiency of measurement. Recent developments in imaging, data handling and remote sensing hold particular promise for high throughput screening of plant structural, developmental or physiological characters. For example 3D imaging and laser scanning can provide information on plant structure, while thermal imaging provides rapid diagnosis of plant responses to water stress, and hyperspectral sensing can provide information on biochemical and physiological responses of plants. It is important that such data is gathered in proper field environments where the ultimate target is to improve crop production that can be realised in agricultural situations.
Prof. Dr. Ulrich Schurr
Prof. Dr. Hamlyn G. Jones
Prof. Dr. Adrian C. Newton
Dr. William Thomas
Manuscript Submission Information
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- remote sensing
- biotic and abiotic stress
- image analysis
- thermal imaging
- hyperspectral sensing
- 3-D structure