Linking Genes to Shape in Plants Using Morphometrics

2020 ◽  
Vol 54 (1) ◽  
pp. 417-437
Author(s):  
Hao Xu ◽  
George W. Bassel
Keyword(s):  
Multiple Scales ◽  
Computational Simulation ◽  
Plant Phenotyping ◽  
Biological Complexity ◽  
Phenotypic Analysis ◽  
Mechanical Signals ◽  
Whole Plant ◽  
Plant Form ◽  
Morphological Phenotype ◽  
Quantitative Approaches

A transition from qualitative to quantitative descriptors of morphology has been facilitated through the growing field of morphometrics, representing the conversion of shapes and patterns into numbers. The analysis of plant form at the macromorphological scale using morphometric approaches quantifies what is commonly referred to as a phenotype. Quantitative phenotypic analysis of individuals with contrasting genotypes in turn provides a means to establish links between genes and shapes. The path from a gene to a morphological phenotype is, however, not direct, with instructive information progressing both across multiple scales of biological complexity and through nonintuitive feedback, such as mechanical signals. In this review, we explore morphometric approaches used to perform whole-plant phenotyping and quantitative approaches in capture processes in the mesoscales, which bridge the gaps between genes and shapes in plants. Quantitative frameworks involving both the computational simulation and the discretization of data into networks provide a putative path to predicting emergent shape from underlying genetic programs.

scholarly journals Plant phenotyping: increasing throughput and precision at multiple scales

2017 ◽  
Vol 44 (1) ◽  
pp. v ◽  
Author(s):  
Malcolm J. Hawkesford ◽  
Argelia Lorence
Keyword(s):  
Multiple Scales ◽  
Field Trials ◽  
Plant Biology ◽  
Plant Phenotyping ◽  
Form And Function ◽  
Technological Advances ◽  
Basic Plant ◽  
Plant Form ◽  
And Function ◽  
Invasive Techniques

In this special issue of Functional Plant Biology, we present a perspective of the current state of the art in plant phenotyping. The applications of automated and detailed recording of plant characteristics using a range of mostly non-invasive techniques are described. Papers range from tissue scale analysis through to aerial surveying of field trials and include model plant species such as Arabidopsis as well as commercial crops such as sugar beet and cereals. The common denominators are high throughput measurements, data rich analyses often utilising image based data capture, requirements for validation when proxy measurement are employed and in many instances a need to fuse datasets. The outputs are detailed descriptions of plant form and function. The papers represent technological advances and important contributions to basic plant biology, and these studies are commonly multidisciplinary, involving engineers, software specialists and plant physiologists. This is a fast moving area producing large datasets and analytical requirements are often common between very diverse platforms.

scholarly journals Phenotypic Analysis of Germination Time of Individual Seeds Affected by Microenvironment and Management Factors for Cohort Research in Plant Factory

Agronomy ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 1680
Author(s):  
Eri Hayashi ◽  
Yumiko Amagai ◽  
Toru Maruo ◽  
Toyoki Kozai
Keyword(s):  
Plant Growth ◽  
Growth Process ◽  
Germination Percentage ◽  
Plant Phenotyping ◽  
Phenotypic Analysis ◽  
Germination Time ◽  
Commercial Cultivation ◽  
Whole Plant ◽  
Plant Factory ◽  
Management Factors

Plant phenotyping plays a crucial role in understanding variations in the phenotype of individual plants affected by environment, management, and genotype. Measurement of seed germination is an important phenotyping stage as germination impacts on the whole plant growth process. However, germination measurement has been limited to germination percentage of a seed population. Understanding of the germination time, from sowing to outbreak of the radicle from seed coat, at a single seed level is essential. How individual germination time and further plant growth are affected by its microenvironment and management factors remains elusive. Plant phenotype measurement system was developed to assess individual germination time of romaine lettuce (Lactuca sativa L. var. longifolia), using time-series two-dimensional camera images, and to analyze how microenvironment (volumetric water percent in seed tray, individual seed surface temperature and air temperature) and management factors (coated/uncoated seeds) affect the germination time for plant cohort research, emphasizing practicality in commercial cultivation. Germination experiments were conducted to demonstrate the performance of the system and its applicability for a whole plant growth process in a plant factory for commercial production and/or breeding. The developed phenotyping platform revealed the effects of microenvironment and management factors on germination time of individual seeds.

Herbaceous monocot plant form and function along a tropical rain-forest light gradient: a reversal of dicot strategy

2009 ◽  
Vol 25 (1) ◽  
pp. 103-106 ◽  
Author(s):  
Nathan G. Swenson
Keyword(s):  
Tropical Forests ◽  
Environmental Gradients ◽  
Plant Performance ◽  
Seed Plants ◽  
Form And Function ◽  
Light Gradient ◽  
Whole Plant ◽  
Plant Form ◽  
And Function ◽  
High Degree

Whole plant form and function vary spectacularly across the seed plants. In recent years, plant evolutionary ecologists have begun to document this diversity on large geographic scales by analysing ‘functional traits’ that are indicative of whole plant performance across environmental gradients (Swenson & Enquist 2007, Wright et al. 2004). Despite the high degree of functional diversity in tropical forests, convergence in function does occur locally along successional or light gradients (Bazzaz & Pickett 1980, Swaine & Whitmore 1988).

Calcium and the generation of plant form

1995 ◽  
Vol 350 (1331) ◽  
pp. 83-86 ◽  
Keyword(s):  
Plant Development ◽  
Calcium Concentration ◽  
Cytosolic Calcium ◽  
Hypocotyl Growth ◽  
Mechanical Signals ◽  
Tension And Compression ◽  
Plant Form ◽  
Living Organisms ◽  
Exciting Possibility

The involvement of mechanical signals (tension and compression) in the determination of the form of living organisms has been speculated upon for many years. These mechanical signals (both environmental and those generated within the plant itself) have significant effects on plant development and thus morphology. Plants respond to externally applied mechanical signals (touch and wind) by an immediate elevation of cytosolic calcium concentration ([Ca 2+ ] eyt ) in stimulated cells. This response requires the movement of plant tissues to cause tension and compression. Some of the more longer-term responses to mechanical signals, e.g. TCH gene expression and reduction in hypocotyl growth, show a calcium-dependency. It seems likely, therefore, that the effects of mechanical signals on plant development are mediated by the second messenger, calcium. This raises the exciting possibility that this simple ion plays a central role in the determination of plant form itself.

Cell to whole-plant phenotyping: the best is yet to come

2013 ◽  
Vol 18 (8) ◽  
pp. 428-439 ◽  
Author(s):  
Stijn Dhondt ◽  
Nathalie Wuyts ◽  
Dirk Inzé
Keyword(s):  
Plant Phenotyping ◽  
Whole Plant ◽  
To Come

Computational Simulation Modeling in Population Health Research and Policy

2020 ◽  
pp. 171-184
Author(s):  
Nathaniel Osgood
Keyword(s):  
Dynamic Modeling ◽  
Multiple Scales ◽  
Computational Simulation ◽  
Discrete Event ◽  
Intervention Strategies ◽  
Agent Based ◽  
Event Simulation ◽  
Modeling Process ◽  
Trade Offs ◽  
Model Dynamics

Dynamic modeling provides a powerful tool for enabling faster learning in a complex and uncertain world. Within this contribution, we briefly survey three prominent dynamic modeling traditions—agent-based modeling, system dynamics, and discrete event simulation. Each such tradition offers unique combinations of strengths and limitations and is further distinguished by emphasis of different sets of modeling goals and norms. This chapter discusses such trade-offs between such methods, with a particular emphasis on the key distinction between aggregate and individual-based approaches, which has widespread practical ramifications. The authors further note the advent of hybrid dynamic modeling approaches, which provide unique levels of flexibility in addressing diverse intervention strategies and generative pathways at multiple scales and the capacity for the model representation to adapt with the learning and evolving understanding of key elements of model dynamics that constitute a key outcome of the modeling process.

scholarly journals Fluxomics links cellular functional analyses to whole-plant phenotyping

2017 ◽  
Vol 68 (9) ◽  
pp. 2083-2098 ◽  
Author(s):  
Christophe Salon ◽  
Jean-Christophe Avice ◽  
Sophie Colombié ◽  
Martine Dieuaide-Noubhani ◽  
Karine Gallardo ◽  
...  
Keyword(s):  
Plant Phenotyping ◽  
Whole Plant ◽  
Functional Analyses

scholarly journals PocketMaize: An Android-Smartphone Application for Maize Plant Phenotyping

2021 ◽  
Vol 12 ◽  
Author(s):  
Lingbo Liu ◽  
Lejun Yu ◽  
Dan Wu ◽  
Junli Ye ◽  
Hui Feng ◽  
...  
Keyword(s):  
Plant Traits ◽  
Low Cost ◽  
Leaf Traits ◽  
Smartphone Application ◽  
Plant Phenotyping ◽  
Phenotypic Characterization ◽  
Whole Plant ◽  
Outdoor Environments ◽  
Calibration Algorithm ◽  
Trait Measurement

A low-cost portable wild phenotyping system is useful for breeders to obtain detailed phenotypic characterization to identify promising wild species. However, compared with the larger, faster, and more advanced in-laboratory phenotyping systems developed in recent years, the progress for smaller phenotyping systems, which provide fast deployment and potential for wide usage in rural and wild areas, is quite limited. In this study, we developed a portable whole-plant on-device phenotyping smartphone application running on Android that can measure up to 45 traits, including 15 plant traits, 25 leaf traits and 5 stem traits, based on images. To avoid the influence of outdoor environments, we trained a DeepLabV3+ model for segmentation. In addition, an angle calibration algorithm was also designed to reduce the error introduced by the different imaging angles. The average execution time for the analysis of a 20-million-pixel image is within 2,500 ms. The application is a portable on-device fast phenotyping platform providing methods for real-time trait measurement, which will facilitate maize phenotyping in field and benefit crop breeding in future.

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