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
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are refereed through a peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agronomy is an international peer-reviewed Open Access quarterly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 550 CHF (Swiss Francs). English correction and/or formatting fees of 250 CHF (Swiss Francs) will be charged in certain cases for those articles accepted for publication that require extensive additional formatting and/or English corrections.
- remote sensing
- biotic and abiotic stress
- image analysis
- thermal imaging
- hyperspectral sensing
- 3-D structure