High-throughput phenotyping for crop improvement in the genomics era. (May 2019)
- Record Type:
- Journal Article
- Title:
- High-throughput phenotyping for crop improvement in the genomics era. (May 2019)
- Main Title:
- High-throughput phenotyping for crop improvement in the genomics era
- Authors:
- Mir, Reyazul Rouf
Reynolds, Mathew
Pinto, Francisco
Khan, Mohd Anwar
Bhat, Mohd Ashraf - Abstract:
- Highlights: Importance of phenomics in view of the genomics revolution and ways to alleviate the phenomics bottleneck. Summary of phenomics initiatives and platforms developed world-wide. Use of phenomics platforms in genetic dissection of targeted traits for crop improvement. Root phenomics to alleviate the root phenotyping bottleneck. Phenomics databases and the need for data sharing for crop improvement. Abstract: Tremendous progress has been made with continually expanding genomics technologies to unravel and understand crop genomes. However, the impact of genomics data on crop improvement is still far from satisfactory, in large part due to a lack of effective phenotypic data; our capacity to collect useful high quality phenotypic data lags behind the current capacity to generate high-throughput genomics data. Thus, the research bottleneck in plant sciences is shifting from genotyping to phenotyping. This article review the current status of efforts made in the last decade to systematically collect phenotypic data to alleviate this 'phenomics bottlenecks' by recording trait data through sophisticated non-invasive imaging, spectroscopy, image analysis, robotics, high-performance computing facilities and phenomics databases. These modern phenomics platforms and tools aim to record data on traits like plant development, architecture, plant photosynthesis, growth or biomass productivity, on hundreds to thousands of plants in a single day, as a phenomics revolution. It isHighlights: Importance of phenomics in view of the genomics revolution and ways to alleviate the phenomics bottleneck. Summary of phenomics initiatives and platforms developed world-wide. Use of phenomics platforms in genetic dissection of targeted traits for crop improvement. Root phenomics to alleviate the root phenotyping bottleneck. Phenomics databases and the need for data sharing for crop improvement. Abstract: Tremendous progress has been made with continually expanding genomics technologies to unravel and understand crop genomes. However, the impact of genomics data on crop improvement is still far from satisfactory, in large part due to a lack of effective phenotypic data; our capacity to collect useful high quality phenotypic data lags behind the current capacity to generate high-throughput genomics data. Thus, the research bottleneck in plant sciences is shifting from genotyping to phenotyping. This article review the current status of efforts made in the last decade to systematically collect phenotypic data to alleviate this 'phenomics bottlenecks' by recording trait data through sophisticated non-invasive imaging, spectroscopy, image analysis, robotics, high-performance computing facilities and phenomics databases. These modern phenomics platforms and tools aim to record data on traits like plant development, architecture, plant photosynthesis, growth or biomass productivity, on hundreds to thousands of plants in a single day, as a phenomics revolution. It is believed that this revolution will provide plant scientists with the knowledge and tools necessary for unlocking information coded in plant genomes. Efforts have been also made to present the advances made in the last 10 years in phenomics platforms and their use in generating phenotypic data on different traits in several major crops including rice, wheat, barley, and maize. The article also highlights the need for phenomics databases and phenotypic data sharing for crop improvement. The phenomics data generated has been used to identify genes/QTL through QTL mapping, association mapping and genome-wide association studies (GWAS) for genomics-assisted breeding (GAB) for crop improvement. … (more)
- Is Part Of:
- Plant science. Volume 282(2019)
- Journal:
- Plant science
- Issue:
- Volume 282(2019)
- Issue Display:
- Volume 282, Issue 2019 (2019)
- Year:
- 2019
- Volume:
- 282
- Issue:
- 2019
- Issue Sort Value:
- 2019-0282-2019-0000
- Page Start:
- 60
- Page End:
- 72
- Publication Date:
- 2019-05
- Subjects:
- RAP rice automatic phenotyping platform -- GWAS genome-wide association studies -- GAB genomics-assisted breeding -- QTL quantitative trait loci -- CE controlled environment -- LIDAR light detection and ranging -- HyperART hyperspectral absorption-reflectance-transmittance imaging -- TLS terrestrial 3D laser scanning -- HSI hyperspectral imaging -- CT X-ray computed tomography -- MRI magnetic resonance imaging -- QTLseq QTL sequencing -- RIL recombinant inbred line -- PheWAS phenome-wide association studies
Phenomics -- Phenomics platforms -- Trait phenotyping -- Association studies -- QTLs/genes -- Phenomics databases -- Crop improvement
Botany -- Periodicals
Botanique -- Périodiques
580 - Journal URLs:
- http://www.sciencedirect.com/science/journal/01689452 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.plantsci.2019.01.007 ↗
- Languages:
- English
- ISSNs:
- 0168-9452
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6523.390000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 9855.xml