Literature DB >> 30380107

Functional phenomics: an emerging field integrating high-throughput phenotyping, physiology, and bioinformatics.

Larry M York1.   

Abstract

The emergence of functional phenomics signifies the rebirth of physiology as a 21st century science through the use of advanced sensing technologies and big data analytics. Functional phenomics seeks to fill the significant knowledge gaps that still exist in the relationship of plant phenotype to function. Here, a general approach for the theory and practice of functional phenomics is outlined. The functional phenomics pipeline is proposed as a general method for conceptualizing, measuring, and validating utility of plant phenes, or elemental units of phenotype. The functional phenomics pipeline begins with ideotype development. Second, a phenotyping platform is developed to maximize the throughput of phene measurements. Target phenes and indicators of plant function, or performance, are measured in a mapping population. Forward genetics allows genetic mapping, while functional phenomics links phenes to plant performance. Based on these data, genotypes with contrasting phenotypes can be selected for smaller yet more intensive experiments to understand phene-environment interactions in depth. Simulation modeling is used to further understand the phenotypes, and all stages of the pipeline feed back to ideotype and phenotyping platform development. In total, functional phenomics represents an evolution of pre-existing disciplines, but the goals and unique methodologies constitute a novel research program.

Entities:  

Mesh:

Year:  2019        PMID: 30380107     DOI: 10.1093/jxb/ery379

Source DB:  PubMed          Journal:  J Exp Bot        ISSN: 0022-0957            Impact factor:   6.992


  15 in total

1.  Functional Principal Component Analysis: A Robust Method for Time-Series Phenotypic Data.

Authors:  Yunqing Yu
Journal:  Plant Physiol       Date:  2020-08       Impact factor: 8.340

Review 2.  Targeting Root Ion Uptake Kinetics to Increase Plant Productivity and Nutrient Use Efficiency.

Authors:  Marcus Griffiths; Larry M York
Journal:  Plant Physiol       Date:  2020-02-06       Impact factor: 8.340

3.  Key Traits and Genes Associate with Salinity Tolerance Independent from Vigor in Cultivated Sunflower.

Authors:  Andries A Temme; Kelly L Kerr; Rishi R Masalia; John M Burke; Lisa A Donovan
Journal:  Plant Physiol       Date:  2020-08-11       Impact factor: 8.340

4.  Baseline cell proliferation rates and response to UV differ in lymphoblastoid cell lines derived from healthy individuals of extreme constitution types.

Authors:  Sumita Chakraborty; Sunanda Singhmar; Dayanidhi Singh; Mahua Maulik; Rutuja Patil; Satyam Kumar Agrawal; Anushree Mishra; Madeeha Ghazi; Archana Vats; Vivek T Natarajan; Sanjay Juvekar; Bhavana Prasher; Mitali Mukerji
Journal:  Cell Cycle       Date:  2021-04-18       Impact factor: 4.534

5.  Maize with fewer nodal roots allocates mass to more lateral and deep roots that improve nitrogen uptake and shoot growth.

Authors:  Haichao Guo; Larry M York
Journal:  J Exp Bot       Date:  2019-10-15       Impact factor: 6.992

6.  A 'nodemap' to sustainable maize roots: linking nitrogen and water uptake improvements.

Authors:  Beatriz Lagunas; Ian C Dodd; Miriam L Gifford
Journal:  J Exp Bot       Date:  2019-10-15       Impact factor: 6.992

Review 7.  Morphophysiology of Potato (Solanum tuberosum) in Response to Drought Stress: Paving the Way Forward.

Authors:  Dominic Hill; David Nelson; John Hammond; Luke Bell
Journal:  Front Plant Sci       Date:  2021-01-15       Impact factor: 5.753

8.  Detection of Potassium Deficiency and Momentary Transpiration Rate Estimation at Early Growth Stages Using Proximal Hyperspectral Imaging and Extreme Gradient Boosting.

Authors:  Shahar Weksler; Offer Rozenstein; Nadav Haish; Menachem Moshelion; Rony Wallach; Eyal Ben-Dor
Journal:  Sensors (Basel)       Date:  2021-02-01       Impact factor: 3.576

Review 9.  Targeting Nitrogen Metabolism and Transport Processes to Improve Plant Nitrogen Use Efficiency.

Authors:  Samantha Vivia The; Rachel Snyder; Mechthild Tegeder
Journal:  Front Plant Sci       Date:  2021-03-01       Impact factor: 5.753

10.  Genome-Wide Association Study of Topsoil Root System Architecture in Field-Grown Soybean [Glycine max (L.) Merr.].

Authors:  Arun Prabhu Dhanapal; Larry M York; Kasey A Hames; Felix B Fritschi
Journal:  Front Plant Sci       Date:  2021-02-10       Impact factor: 5.753

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