New Phenotyping Platforms for Field Trials

A special issue of Agronomy (ISSN 2073-4395).

Deadline for manuscript submissions: closed (15 February 2014) | Viewed by 116908

Special Issue Editors


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Guest Editor
Forschungszentrum Jülich, IBG-2: Plant Sciences, 52425 Jülich, Germany

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Guest Editor
Plant Research Group, Division of Environmental and Applied Biology, University of Dundee at SCRI, Invergowrie, Dundee DD2 5DA, Scotland, UK

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Guest Editor
1. The James Hutton Institute, Invergowrie, Dundee DD2 5DA, Scotland, UK
2. Visiting Professor of Cereal Pathology, SRUC, Edinburgh, UK
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)

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Guest Editor
The James Hutton Institute, Invergowrie, Dundee DD2 5DA, Scotland, UK

Special Issue Information

Dear Colleagues,

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
Guest Editors

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Keywords

  • remote sensing
  • yield
  • infection
  • biotic and abiotic stress
  • quality
  • image analysis
  • thermal imaging
  • hyperspectral sensing
  • 3-D structure

Published Papers (10 papers)

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Research

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1311 KiB  
Article
Development of a Mobile Multispectral Imaging Platform for Precise Field Phenotyping
by Jesper Svensgaard, Thomas Roitsch and Svend Christensen
Agronomy 2014, 4(3), 322-336; https://doi.org/10.3390/agronomy4030322 - 01 Jul 2014
Cited by 49 | Viewed by 10589
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue New Phenotyping Platforms for Field Trials)
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2088 KiB  
Article
Pheno-Copter: A Low-Altitude, Autonomous Remote-Sensing Robotic Helicopter for High-Throughput Field-Based Phenotyping
by Scott C. Chapman, Torsten Merz, Amy Chan, Paul Jackway, Stefan Hrabar, M. Fernanda Dreccer, Edward Holland, Bangyou Zheng, T. Jun Ling and Jose Jimenez-Berni
Agronomy 2014, 4(2), 279-301; https://doi.org/10.3390/agronomy4020279 - 17 Jun 2014
Cited by 226 | Viewed by 19028
Abstract
Plant breeding trials are extensive (100s to 1000s of plots) and are difficult and expensive to monitor by conventional means, especially where measurements are time-sensitive. For example, in a land-based measure of canopy temperature (hand-held infrared thermometer at two to 10 plots per [...] Read more.
Plant breeding trials are extensive (100s to 1000s of plots) and are difficult and expensive to monitor by conventional means, especially where measurements are time-sensitive. For example, in a land-based measure of canopy temperature (hand-held infrared thermometer at two to 10 plots per minute), the atmospheric conditions may change greatly during the time of measurement. Such sensors measure small spot samples (2 to 50 cm2), whereas image-based methods allow the sampling of entire plots (2 to 30 m2). A higher aerial position allows the rapid measurement of large numbers of plots if the altitude is low (10 to 40 m) and the flight control is sufficiently precise to collect high-resolution images. This paper outlines the implementation of a customized robotic helicopter (gas-powered, 1.78-m rotor diameter) with autonomous flight control and software to plan flights over experiments that were 0.5 to 3 ha in area and, then, to extract, straighten and characterize multiple experimental field plots from images taken by three cameras. With a capacity to carry 1.5 kg for 30 min or 1.1 kg for 60 min, the system successfully completed >150 flights for a total duration of 40 h. Example applications presented here are estimations of the variation in: ground cover in sorghum (early season); canopy temperature in sugarcane (mid-season); and three-dimensional measures of crop lodging in wheat (late season). Together with this hardware platform, improved software to automate the production of ortho-mosaics and digital elevation models and to extract plot data would further benefit the development of high-throughput field-based phenotyping systems. Full article
(This article belongs to the Special Issue New Phenotyping Platforms for Field Trials)
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915 KiB  
Article
Scale-Dependent Assessment of Relative Disease Resistance to Plant Pathogens
by Peter Skelsey and Adrian C. Newton
Agronomy 2014, 4(2), 178-190; https://doi.org/10.3390/agronomy4020178 - 27 Mar 2014
Cited by 4 | Viewed by 7416
Abstract
Phenotyping trials may not take into account sufficient spatial context to infer quantitative disease resistance of recommended varieties in commercial production settings. Recent ecological theory—the dispersal scaling hypothesis—provides evidence that host heterogeneity and scale of host heterogeneity interact in a predictable and straightforward [...] Read more.
Phenotyping trials may not take into account sufficient spatial context to infer quantitative disease resistance of recommended varieties in commercial production settings. Recent ecological theory—the dispersal scaling hypothesis—provides evidence that host heterogeneity and scale of host heterogeneity interact in a predictable and straightforward manner to produce a unimodal (“humpbacked”) distribution of epidemic outcomes. This suggests that the intrinsic artificiality (scale and design) of experimental set-ups may lead to spurious conclusions regarding the resistance of selected elite cultivars, due to the failure of experimental efforts to accurately represent disease pressure in real agricultural situations. In this model-based study we investigate the interaction of host heterogeneity and scale as a confounding factor in the inference from ex-situ assessment of quantitative disease resistance to commercial production settings. We use standard modelling approaches in plant disease epidemiology and a number of different agronomic scenarios. Model results revealed that the interaction of heterogeneity and scale is a determinant of relative varietal performance under epidemic conditions. This is a previously unreported phenomenon that could provide a new basis for informing the design of future phenotyping platforms, and optimising the scale at which quantitative disease resistance is assessed. Full article
(This article belongs to the Special Issue New Phenotyping Platforms for Field Trials)
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1259 KiB  
Article
Effects of Field Plot Size on Variation in White Flower Anther Injury by Tarnished Plant Bug for Host Plant Resistance Evaluations in Arkansas Cotton
by Jeffrey Willers, Tina Gray Teague, George Milliken and Fred Bourland
Agronomy 2014, 4(1), 144-164; https://doi.org/10.3390/agronomy4010144 - 27 Feb 2014
Viewed by 6676
Abstract
Field trials conducted in 2008 and 2009 investigated whether plot size affects incidence of white flower anther injury by tarnished plant bug (Lygus lineolaris (Palisot de Beauvois)) in host plant resistance (HPR) evaluations. The three cotton lines evaluated in the trial included [...] Read more.
Field trials conducted in 2008 and 2009 investigated whether plot size affects incidence of white flower anther injury by tarnished plant bug (Lygus lineolaris (Palisot de Beauvois)) in host plant resistance (HPR) evaluations. The three cotton lines evaluated in the trial included a susceptible frego bract line (RBCDHGPIQH-197) and 2 standards, SureGrow (SG) 105 and Deltapine (DP) 393. Samplers monitored white flower anther injury between single row mini-plots embedded within multiple row max-plots. A sub-section of the max-plots was sprayed with insecticides to evaluate these tactics on altering the incidence of white flower anther injury. Plant bug numbers were very low in 2008, while infestation levels were higher in 2009. Significantly higher numbers of flowers with anther injury were observed in both years in the susceptible frego bract line compared to SG 105 and DP 393 lines. In both years, anther injury levels were similar in the max- and mini-plots, with lower levels observed in max-sprayed plots. The white flower monitoring procedure is a consistent indicator of adult plant bug preferences and is not influenced by plot size or interspersions of cultivar lines among plots. Full article
(This article belongs to the Special Issue New Phenotyping Platforms for Field Trials)
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2371 KiB  
Article
Elements of an Integrated Phenotyping System for Monitoring Crop Status at Canopy Level
by Donald Rundquist, Anatoly Gitelson, Bryan Leavitt, Arthur Zygielbaum, Richard Perk and Galina Keydan
Agronomy 2014, 4(1), 108-123; https://doi.org/10.3390/agronomy4010108 - 17 Feb 2014
Cited by 28 | Viewed by 7096
Abstract
Great care is needed to obtain spectral data appropriate for phenotyping in a scientifically rigorous manner. This paper discusses the procedures and considerations necessary and also suggests important pre-processing and analytical steps leading to real-time, non-destructive assessment of crop biophysical characteristics. The system [...] Read more.
Great care is needed to obtain spectral data appropriate for phenotyping in a scientifically rigorous manner. This paper discusses the procedures and considerations necessary and also suggests important pre-processing and analytical steps leading to real-time, non-destructive assessment of crop biophysical characteristics. The system has three major components: (1) data-collection platforms (with a focus on backpack and tractor-mounted units) including specific instruments and their configurations; (2) data-collection and display software; and (3) standard products depicting crop-biophysical characteristics derived using a suite of models to transform the spectral data into accurate, reliable biophysical characteristics of crops, such as fraction of green vegetation, absorbed photosynthetically active radiation, leaf area index, biomass, chlorophyll content and gross primary production. This system streamlines systematic data acquisition, facilitates research, and provides useful products for agriculture. Full article
(This article belongs to the Special Issue New Phenotyping Platforms for Field Trials)
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Review

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6070 KiB  
Review
Infra-Red Thermography as a High-Throughput Tool for Field Phenotyping
by Ankush Prashar and Hamlyn G. Jones
Agronomy 2014, 4(3), 397-417; https://doi.org/10.3390/agronomy4030397 - 31 Jul 2014
Cited by 89 | Viewed by 13851
Abstract
The improvements in crop production needed to meet the increasing food demand in the 21st Century will rely on improved crop management and better crop varieties. In the last decade our ability to use genetics and genomics in crop science has been revolutionised, [...] Read more.
The improvements in crop production needed to meet the increasing food demand in the 21st Century will rely on improved crop management and better crop varieties. In the last decade our ability to use genetics and genomics in crop science has been revolutionised, but these advances have not been matched by our ability to phenotype crops. As rapid and effective phenotyping is the basis of any large genetic study, there is an urgent need to utilise the recent advances in crop scale imaging to develop robust high-throughput phenotyping. This review discusses the use and adaptation of infra-red thermography (IRT) on crops as a phenotyping resource for both biotic and abiotic stresses. In particular, it addresses the complications caused by external factors such as environmental fluctuations and the difficulties caused by mixed pixels in the interpretation of IRT data and their effects on sensitivity and reproducibility for the detection of different stresses. Further, it highlights the improvements needed in using this technique for quantification of genetic variation and its integration with multiple sensor technology for development as a high-throughput and precise phenotyping approach for future crop breeding. Full article
(This article belongs to the Special Issue New Phenotyping Platforms for Field Trials)
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45972 KiB  
Review
Scaling of Thermal Images at Different Spatial Resolution: The Mixed Pixel Problem
by Hamlyn G. Jones and Xavier R. R. Sirault
Agronomy 2014, 4(3), 380-396; https://doi.org/10.3390/agronomy4030380 - 23 Jul 2014
Cited by 69 | Viewed by 15810
Abstract
The consequences of changes in spatial resolution for application of thermal imagery in plant phenotyping in the field are discussed. Where image pixels are significantly smaller than the objects of interest (e.g., leaves), accurate estimates of leaf temperature are possible, but when pixels [...] Read more.
The consequences of changes in spatial resolution for application of thermal imagery in plant phenotyping in the field are discussed. Where image pixels are significantly smaller than the objects of interest (e.g., leaves), accurate estimates of leaf temperature are possible, but when pixels reach the same scale or larger than the objects of interest, the observed temperatures become significantly biased by the background temperature as a result of the presence of mixed pixels. Approaches to the estimation of the true leaf temperature that apply both at the whole-pixel level and at the sub-pixel level are reviewed and discussed. Full article
(This article belongs to the Special Issue New Phenotyping Platforms for Field Trials)
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4941 KiB  
Review
Proximal Remote Sensing Buggies and Potential Applications for Field-Based Phenotyping
by David Deery, Jose Jimenez-Berni, Hamlyn Jones, Xavier Sirault and Robert Furbank
Agronomy 2014, 4(3), 349-379; https://doi.org/10.3390/agronomy4030349 - 10 Jul 2014
Cited by 302 | Viewed by 20279
Abstract
The achievements made in genomic technology in recent decades are yet to be matched by fast and accurate crop phenotyping methods. Such crop phenotyping methods are required for crop improvement efforts to meet expected demand for food and fibre in the future. This [...] Read more.
The achievements made in genomic technology in recent decades are yet to be matched by fast and accurate crop phenotyping methods. Such crop phenotyping methods are required for crop improvement efforts to meet expected demand for food and fibre in the future. This review evaluates the role of proximal remote sensing buggies for field-based phenotyping with a particular focus on the application of currently available sensor technology for large-scale field phenotyping. To illustrate the potential for the development of high throughput phenotyping techniques, a case study is presented with sample data sets obtained from a ground-based proximal remote sensing buggy mounted with the following sensors: LiDAR, RGB camera, thermal infra-red camera and imaging spectroradiometer. The development of such techniques for routine deployment in commercial-scale breeding and pre-breeding operations will require a multidisciplinary approach to leverage the recent technological advances realised in computer science, image analysis, proximal remote sensing and robotics. Full article
(This article belongs to the Special Issue New Phenotyping Platforms for Field Trials)
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398 KiB  
Review
Assessing the Consequences of Microbial Infection in Field Trials: Seen, Unseen, Beneficial, Parasitic and Pathogenic
by Mark E. Looseley and Adrian C. Newton
Agronomy 2014, 4(2), 302-321; https://doi.org/10.3390/agronomy4020302 - 24 Jun 2014
Cited by 5 | Viewed by 6455
Abstract
Microbial infections of crop plants present an ongoing threat to agricultural production. However, in recent years, we have developed a more nuanced understanding of the ecological role of microbes and how they interact with plants. This includes an appreciation of the influence of [...] Read more.
Microbial infections of crop plants present an ongoing threat to agricultural production. However, in recent years, we have developed a more nuanced understanding of the ecological role of microbes and how they interact with plants. This includes an appreciation of the influence of crop physiology and environmental conditions on the expression of disease symptoms, the importance of non-pathogenic microbes on host plants and pathogens, and the capacity for plants to act as hosts for human pathogens. Alongside this we now have a variety of tools available for the identification and quantification of microbial infections on crops grown under field conditions. This review summarises some of the consequences of microbial infections in crop plants, and discusses how new and established assessment tools can be used to understand these processes. It challenges our current assumptions in yield loss relationships and offers understanding of the potential for more resilient crops. Full article
(This article belongs to the Special Issue New Phenotyping Platforms for Field Trials)
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1148 KiB  
Review
Field Phenotyping and Long-Term Platforms to Characterise How Crop Genotypes Interact with Soil Processes and the Environment
by Timothy S. George, Cathy Hawes, Adrian C. Newton, Blair M. McKenzie, Paul D. Hallett and Tracy A. Valentine
Agronomy 2014, 4(2), 242-278; https://doi.org/10.3390/agronomy4020242 - 22 May 2014
Cited by 17 | Viewed by 8851
Abstract
Unsustainable agronomic practices and environmental change necessitate a revolution in agricultural production to ensure food security. A new generation of crops that yield more with fewer inputs and are adapted to more variable environments is needed. However, major changes in breeding programmes may [...] Read more.
Unsustainable agronomic practices and environmental change necessitate a revolution in agricultural production to ensure food security. A new generation of crops that yield more with fewer inputs and are adapted to more variable environments is needed. However, major changes in breeding programmes may be required to achieve this goal. By using the genetic variation in crop yield in specific target environments that vary in soil type, soil management, nutrient inputs and environmental stresses, robust traits suited to specific conditions can be identified. It is here that long-term experimental platforms and field phenotyping have an important role to play. In this review, we will provide information about some of the field-based platforms available and the cutting edge phenotyping systems at our disposal. We will also identify gaps in our field phenotyping resources that should be filled. We will go on to review the challenges in producing crop ideotypes for the dominant management systems for which we need sustainable solutions, and we discuss the potential impact of three-way interactions between genetics, environment and management. Finally, we will discuss the role that modelling can play in allowing us to fast-track some of these processes to allow us to make rapid gains in agricultural sustainability. Full article
(This article belongs to the Special Issue New Phenotyping Platforms for Field Trials)
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