Cell to whole-plant phenotyping: the best is yet to come.
TL;DR: Overall, attention is focused on spatial and temporal resolution because these are crucial aspects of imaging procedures in plant phenotyping systems.
About: This article is published in Trends in Plant Science.The article was published on 2013-08-01. It has received 278 citations till now.
Citations
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TL;DR: Several genomic selection (GS) models are reviewed with respect to both the prediction accuracy and genetic gain from selection.
479 citations
TL;DR: The potential of using aerial imaging to evaluate resistance/susceptibility to biotic and abiotic stress for crop breeding and precision production management has been discussed along with future perspectives and developments as mentioned in this paper.
365 citations
Cites background from "Cell to whole-plant phenotyping: th..."
...In the last 20 years, advances in DNA sequencing and molecular technologies has significantly improved knowledge of plant genomes; however, current methods to phenotype crops remain slow, expensive, labor-intensive, and often destructive (Furbank and Tester, 2011; Walter et al., 2012; White et al., 2012; Cobb et al., 2013; Dhondt et al., 2013; Fiorani and Schurr, 2013; Araus and Cairns, 2014)....
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...…knowledge of plant genomes; however, current methods to phenotype crops remain slow, expensive, labor-intensive, and often destructive (Furbank and Tester, 2011; Walter et al., 2012; White et al., 2012; Cobb et al., 2013; Dhondt et al., 2013; Fiorani and Schurr, 2013; Araus and Cairns, 2014)....
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...…improve phenotyping efforts for plant breeding (Furbank and Tester, 2011; Walter et al., 2012; White et al., 2012; Cabrera-Bosquet et al., 2012; Dhondt et al., 2013; Fiorani and Schurr, 2013; Yang et al., 2013; Cobb et al., 2013; Araus and Cairns, 2014; Prashar and Jones, 2014; Deery et al.,…...
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...Since 2010, rapid high-throughput crop phenotyping methods or ‘phenomics’ have been discussed as an approach that could significantly improve phenotyping efforts for plant breeding (Furbank and Tester, 2011; Walter et al., 2012; White et al., 2012; Cabrera-Bosquet et al., 2012; Dhondt et al., 2013; Fiorani and Schurr, 2013; Yang et al., 2013; Cobb et al., 2013; Araus and Cairns, 2014; Prashar and Jones, 2014; Deery et al., 2014)....
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TL;DR: A comprehensive framework for high-throughput phenotype data analysis in plants is developed, which enables the extraction of an extensive list of phenotypic traits from nondestructive plant imaging over time and is promising for subsequent genetic mapping to uncover the genetic basis of complex agronomic traits.
Abstract: Significantly improved crop varieties are urgently needed to feed the rapidly growing human population under changing climates. While genome sequence information and excellent genomic tools are in place for major crop species, the systematic quantification of phenotypic traits or components thereof in a high-throughput fashion remains an enormous challenge. In order to help bridge the genotype to phenotype gap, we developed a comprehensive framework for high-throughput phenotype data analysis in plants, which enables the extraction of an extensive list of phenotypic traits from nondestructive plant imaging over time. As a proof of concept, we investigated the phenotypic components of the drought responses of 18 different barley (Hordeum vulgare) cultivars during vegetative growth. We analyzed dynamic properties of trait expression over growth time based on 54 representative phenotypic features. The data are highly valuable to understand plant development and to further quantify growth and crop performance features. We tested various growth models to predict plant biomass accumulation and identified several relevant parameters that support biological interpretation of plant growth and stress tolerance. These image-based traits and model-derived parameters are promising for subsequent genetic mapping to uncover the genetic basis of complex agronomic traits. Taken together, we anticipate that the analytical framework and analysis results presented here will be useful to advance our views of phenotypic trait components underlying plant development and their responses to environmental cues.
280 citations
Cites background from "Cell to whole-plant phenotyping: th..."
...Plants reveal complex phenotypic traits that are expected to be extremely highly dimensional (Houle et al., 2010; Dhondt et al., 2013)....
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TL;DR: In this article, a field-imaging protocol and an algorithmic approach are combined to analyze mature root systems grown in the field. But the results of the analysis were limited to maize (Zea mays) genotypes.
Abstract: Current plant phenotyping technologies to characterize agriculturally relevant traits have been primarily developed for use in laboratory and/or greenhouse conditions. In the case of root architectural traits, this limits phenotyping efforts, largely, to young plants grown in specialized containers and growth media. Hence, novel approaches are required to characterize mature root systems of older plants grown under actual soil conditions in the field. Imaging methods able to address the challenges associated with characterizing mature root systems are rare due, in part, to the greater complexity of mature root systems, including the larger size, overlap, and diversity of root components. Our imaging solution combines a field-imaging protocol and algorithmic approach to analyze mature root systems grown in the field. Via two case studies, we demonstrate how image analysis can be utilized to estimate localized root traits that reliably capture heritable architectural diversity as well as environmentally induced architectural variation of both monocot and dicot plants. In the first study, we show that our algorithms and traits (including 13 novel traits inaccessible to manual estimation) can differentiate nine maize (Zea mays) genotypes 8 weeks after planting. The second study focuses on a diversity panel of 188 cowpea (Vigna unguiculata) genotypes to identify which traits are sufficient to differentiate genotypes even when comparing plants whose harvesting date differs up to 14 d. Overall, we find that automatically derived traits can increase both the speed and reproducibility of the trait estimation pipeline under field conditions.
223 citations
TL;DR: The HyperART system offers the possibility for non-invasive and accurate mapping of leaf transmittance and absorption, significantly expanding the applicability of reflectance, based on mapping spectroscopy, in plant sciences.
Abstract: Background
Combined assessment of leaf reflectance and transmittance is currently limited to spot (point) measurements. This study introduces a tailor-made hyperspectral absorption-reflectance-transmittance imaging (HyperART) system, yielding a non-invasive determination of both reflectance and transmittance of the whole leaf. We addressed its applicability for analysing plant traits, i.e. assessing Cercospora beticola disease severity or leaf chlorophyll content. To test the accuracy of the obtained data, these were compared with reflectance and transmittance measurements of selected leaves acquired by the point spectroradiometer ASD FieldSpec, equipped with the FluoWat device.
219 citations
References
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TL;DR: The origins, challenges and solutions of NIH Image and ImageJ software are discussed, and how their history can serve to advise and inform other software projects.
Abstract: For the past 25 years NIH Image and ImageJ software have been pioneers as open tools for the analysis of scientific images. We discuss the origins, challenges and solutions of these two programs, and how their history can serve to advise and inform other software projects.
44,587 citations
TL;DR: This review examines how fluorescence parameters can be used to evaluate changes in photosystem II (PSII) photochemistry, linear electron flux, and CO(2) assimilation in vivo, and outlines the theoretical bases for the use of specificfluorescence parameters.
Abstract: The use of chlorophyll fluorescence to monitor photosynthetic performance in algae and plants is now widespread. This review examines how fluorescence parameters can be used to evaluate changes in photosystem II (PSII) photochemistry, linear electron flux, and CO(2) assimilation in vivo, and outlines the theoretical bases for the use of specific fluorescence parameters. Although fluorescence parameters can be measured easily, many potential problems may arise when they are applied to predict changes in photosynthetic performance. In particular, consideration is given to problems associated with accurate estimation of the PSII operating efficiency measured by fluorescence and its relationship with the rates of linear electron flux and CO(2) assimilation. The roles of photochemical and nonphotochemical quenching in the determination of changes in PSII operating efficiency are examined. Finally, applications of fluorescence imaging to studies of photosynthetic heterogeneity and the rapid screening of large numbers of plants for perturbations in photosynthesis and associated metabolism are considered.
3,434 citations
TL;DR: New technologies must be developed to accelerate breeding through improving genotyping and phenotyping methods and by increasing the available genetic diversity in breeding germplasm.
Abstract: To feed the several billion people living on this planet, the production of high-quality food must increase with reduced inputs, but this accomplishment will be particularly challenging in the face of global environmental change. Plant breeders need to focus on traits with the greatest potential to increase yield. Hence, new technologies must be developed to accelerate breeding through improving genotyping and phenotyping methods and by increasing the available genetic diversity in breeding germplasm. The most gain will come from delivering these technologies in developing countries, but the technologies will have to be economically accessible and readily disseminated. Crop improvement through breeding brings immense value relative to investment and offers an effective approach to improving food security.
1,777 citations
TL;DR: In this paper, a crop water stress index (CWSI) was calculated using infrared thermometry, along with wet and dry-bulb air temperatures and an estimate of net radiation.
Abstract: Canopy temperatures, obtained by infrared thermometry, along with wet- and dry-bulb air temperatures and an estimate of net radiation were used in equations derived from energy balance considerations to calculate a crop water stress index (CWSI). Theoretical limits were developed for the canopy air temperature difference as related to the air vapor pressure deficit. The CWSI was shown to be equal to 1 - E/Ep, the ratio of actual to potential evapotranspiration obtained from the Penman-Monteith equation. Four experimental plots, planted to wheat, received postemergence irrigations at different times to create different degrees of water stress. Pertinent variables were measured between 1340 and 1400 each day (except some weekends). The CWSI, plotted as a function of time, closely paralleled a plot of the extractable soil water in the 0- to 1.1-m zone. The usefulness and limitations of the index are discussed.
1,642 citations
TL;DR: This review presents plant physiology in an 'omics' perspective, some of the new high-throughput and high-resolution phenotyping tools are reviewed and their application to plant biology, functional genomics and crop breeding is discussed.
1,280 citations