SlideShare a Scribd company logo
1 of 27
Download to read offline
Integrated Breeding Platform
Breeding Management System
(BMS)
IBP Management Team
Presenter – Graham McLaren
January 2014
Rationale for the IBP




Large private seed companies have successfully
implemented extensive suites of integrated informatics
tools to turbocharge their breeding programs
Implementation of this integrated informatics in public
programs lags behind, especially in developing countries






Some tools have been developed at various CG centers, but
implementation has been uneven and they are not integrated into
a comprehensive system
Most NARS programs still rely on rudimentary tools, from pen
and paper to Excel spreadsheets
Small SMEs in developing countries typically do not have the
resources to acquire available commercial software or to
implement breeding IT systems on their own
https://www.integratedbreeding.net/
Breeding Management System
(BMS) – Product Concept







Simple and easy-to-use application containing all
informatics tools needed by a breeder
Seamless flow of data between applications
Accumulation, sharing and re-use of breeding data
Targets routine breeding activities and will not replace
research tools
Will allow integration of users own tools into the system
Implementable as a standalone system




Access central and local DB, as well as the BMS on a local PC

Will also be implementable as a cloud-based system via
iPlant cyber-infrastructure


For computationally intensive analyses or large data storage
needs
List Manager Functionality
The List Manager is at the center of all activities in the Breeding
Management System:






First screen you arrive at after opening your Breeding Program
New left navigation menu provides direct access to all tools
Easily build and work with the lists that are used in each stage of
the breeding cycle

Key List Manager Features:






Ability to browse and modify existing lists
Ability to search for lists and germplasm entries
Ability to create a new list dynamically by pulling from existing
lists or germplasm search results
Expanded ability to modify list contents
Ability to export lists for use outside of the Breeding Management
System
Breeding Logistics
Once the strategy and parental material have
been identified, the breeder wants to:


make crosses,



develop populations,



track pedigrees,



track inventory,



characterize lines
Nursery and Trial Management


Breeding Manager configured for different crops






IB Fieldbook





Crossing manager, nursery manager, pedigree recording
Focuses on population development and line selection
Nursery advance and seed inventory tracking
Focuses on field trial management for germplasm evaluation
Trait selection, field design, labels and sample tracking

Android-based hand-held device




Optimized for use with Samsung Galaxy tablet for field data
collection
Other Android devices can be used if preferred

Breeding manager and Field books fully integrated into
BMS workbench
Field Testing
Once populations are developed, the breeder
wants to:


select traits,



make lists of germplasm,



generate designs,



produce fieldbooks,



collect data,



check and store data.
Breeding Management
Trait Dictionaries

Reporting
units or scale
Measurement
method

Trait property

Measurement
Variate
Breeding Management
Trait Selector
Breeding Management
Germplasm List Manager
Breeding Management
IBP Fieldbook
Breeding Management
Bar Code labels
Breeding Management
Tablet Devices

Fieldbook
connects to
Androidbased tablet
devises for
data
collection in
the field and
laboratory
Integrated Breeding Database



Genealogy Management System (GMS)





Phenotypeing Data Management System (DMS)





Germplasm nomenclature, chronology, IP and passport data
Pedigrees and breeding history
Germplasm characterization and evaluation data
Annotated with Crop Research and Crop Trait Ontologies

Genotypic Data Management System (GDMS)




Medium density fingerprinting data
Genotyping data for MAS and MABC
Genotyping data for Marker-trait association analysis

Databases fully integrated into BMS workbench
Query Tools
At the outset of a breeding cycle users want to:


browse all germplasm information



review existing characterization and evaluation



search for adapted germplasm



perform head to head comparisons
Statistical Analysis of Phenotyping Data









Breeding View provides easy access to the high
throughput analyses routinely required by breeders
The same interface can be used to access procedures in
Genstat or R-scripts and allows analyses to be configured
Single site analysis is available for complete and
incomplete block designs as well as row-column designs
and spatial analysis. New designs are being added at
each update,
Analyses can be run in batches over environments and
traits,
Two-stage multi-site analysis is available for GxE and
stability analysis with or without grouping of
environments,
Single pass meta analysis of unbalanced site by season
data is being incorporated.
Tools to be fully integrated into the BMS by June 2014
Genotyping
To use molecular technologies, the breeder
wants to:


select population,



select markers,



genotype population,



check and store genotyping data.
Genotyping Data Management
Breeding View - QTL analysis



Single trait linkage analysis (QTL)












Quality control phenotypes (summary
statistics)
Quality control marker data
QTL detection – genome wide scan
using single and composite IM
Output includes profile plots and tables
Results available for automatic viewing
in Flapjack
HTML report of QTL results

Multiple trait sequential analysis



QTL results for each trait combined
Single Flapjack view for all traits
Decision support for
Marker implementation




OptiMAS
Developed at INRA, Le
Moulon
Implementation of
markers in a MARS
breeding scheme
Identify and track
favorable alleles through
cycles of recombination
and selection
Molecular Breeding
Decision Tool (MBDT)
Developed by team at
ICRISAT
Implementation of
markers in a MAS and
MABC context
Future Directions







Continuous improvement of UI based on user
feedback
Additional analysis methods for expanded
experimental designs and genetic analysis
Seed inventory management system
LAN based deployment available in January, cloud
based deployment available in June
Data will be stored in a single shareable database
with user access roles
Off-line capability will be supported by a data cache
which will synchronize when a connection is
available

More Related Content

Viewers also liked (7)

Breeding systems
Breeding systemsBreeding systems
Breeding systems
 
Building management system (bms)
Building management system (bms)Building management system (bms)
Building management system (bms)
 
Bms system basic
Bms system  basicBms system  basic
Bms system basic
 
Art Nouveau
Art Nouveau  Art Nouveau
Art Nouveau
 
Automatic control of street light using LDR
Automatic control of street light using LDRAutomatic control of street light using LDR
Automatic control of street light using LDR
 
Animal breeding and selection
Animal breeding and selectionAnimal breeding and selection
Animal breeding and selection
 
Slideshare ppt
Slideshare pptSlideshare ppt
Slideshare ppt
 

Similar to PAG XXII 2014 – The Breeding Management System (BMS) of the Integrated Breeding Platform (IBP) – G McLaren

GRM 2014: Mark Sawkins on BMS functionalities and users
GRM 2014: Mark Sawkins on BMS functionalities and usersGRM 2014: Mark Sawkins on BMS functionalities and users
GRM 2014: Mark Sawkins on BMS functionalities and usersIntegrated Breeding Platform
 
GRM 2013: The Integrated Breeding Platform: Overview -- G McLaren and M Sawkins
GRM 2013: The Integrated Breeding Platform: Overview -- G McLaren and M SawkinsGRM 2013: The Integrated Breeding Platform: Overview -- G McLaren and M Sawkins
GRM 2013: The Integrated Breeding Platform: Overview -- G McLaren and M SawkinsCGIAR Generation Challenge Programme
 
Integrated Breeding Platform (IBP): A user-friendly platform to implement the...
Integrated Breeding Platform (IBP): A user-friendly platform to implement the...Integrated Breeding Platform (IBP): A user-friendly platform to implement the...
Integrated Breeding Platform (IBP): A user-friendly platform to implement the...CGIAR Generation Challenge Programme
 
PAG 2015 - Breeding View: Statistical analyses in the Breeding Management Sys...
PAG 2015 - Breeding View: Statistical analyses in the Breeding Management Sys...PAG 2015 - Breeding View: Statistical analyses in the Breeding Management Sys...
PAG 2015 - Breeding View: Statistical analyses in the Breeding Management Sys...Integrated Breeding Platform
 
Integrated Breeding Platform (IBP): A user-friendly platform to implement the...
Integrated Breeding Platform (IBP): A user-friendly platform to implement the...Integrated Breeding Platform (IBP): A user-friendly platform to implement the...
Integrated Breeding Platform (IBP): A user-friendly platform to implement the...CGIAR Generation Challenge Programme
 
Mark Sawkins' presentation at the Symposium on Crop Breeding Databases - Nove...
Mark Sawkins' presentation at the Symposium on Crop Breeding Databases - Nove...Mark Sawkins' presentation at the Symposium on Crop Breeding Databases - Nove...
Mark Sawkins' presentation at the Symposium on Crop Breeding Databases - Nove...Integrated Breeding Platform
 
Genome voyager-beta-brochure
Genome voyager-beta-brochureGenome voyager-beta-brochure
Genome voyager-beta-brochureXing Xu
 
Ramil Mauleon: Galaxy: bioinformatics for rice scientists
Ramil Mauleon: Galaxy: bioinformatics for rice scientistsRamil Mauleon: Galaxy: bioinformatics for rice scientists
Ramil Mauleon: Galaxy: bioinformatics for rice scientistsGigaScience, BGI Hong Kong
 
Self Service BI for Healthcare
Self Service BI for HealthcareSelf Service BI for Healthcare
Self Service BI for HealthcareVeerendra Raju
 
Building Knowledge Graphs for the Agri-Food sector
Building Knowledge Graphs for the Agri-Food sectorBuilding Knowledge Graphs for the Agri-Food sector
Building Knowledge Graphs for the Agri-Food sectorRaul Palma
 
PlantScreen™ Modular Systems | QubitPhenomics.com.pdf
PlantScreen™ Modular Systems | QubitPhenomics.com.pdfPlantScreen™ Modular Systems | QubitPhenomics.com.pdf
PlantScreen™ Modular Systems | QubitPhenomics.com.pdftachet
 
QuahogLife | Solutions and Services
QuahogLife | Solutions and ServicesQuahogLife | Solutions and Services
QuahogLife | Solutions and ServicesVeerendra Raju
 
Advancing life sciences with IBM reference architecture for genomics
Advancing life sciences with IBM reference architecture for genomicsAdvancing life sciences with IBM reference architecture for genomics
Advancing life sciences with IBM reference architecture for genomicsPatrick Berghaeger
 
Legacy Analysis: How Hadoop Streaming Enables Software Reuse – A Genomics Cas...
Legacy Analysis: How Hadoop Streaming Enables Software Reuse – A Genomics Cas...Legacy Analysis: How Hadoop Streaming Enables Software Reuse – A Genomics Cas...
Legacy Analysis: How Hadoop Streaming Enables Software Reuse – A Genomics Cas...StampedeCon
 
App for Physiological Seed quality Parameters
App for Physiological Seed quality ParametersApp for Physiological Seed quality Parameters
App for Physiological Seed quality ParametersEswar Publications
 
An Efficient Online Offline Data Collection Software Solution for Creating Re...
An Efficient Online Offline Data Collection Software Solution for Creating Re...An Efficient Online Offline Data Collection Software Solution for Creating Re...
An Efficient Online Offline Data Collection Software Solution for Creating Re...ijcseit
 

Similar to PAG XXII 2014 – The Breeding Management System (BMS) of the Integrated Breeding Platform (IBP) – G McLaren (20)

GRM 2014: Mark Sawkins on BMS functionalities and users
GRM 2014: Mark Sawkins on BMS functionalities and usersGRM 2014: Mark Sawkins on BMS functionalities and users
GRM 2014: Mark Sawkins on BMS functionalities and users
 
GRM 2013: The Integrated Breeding Platform: Overview -- G McLaren and M Sawkins
GRM 2013: The Integrated Breeding Platform: Overview -- G McLaren and M SawkinsGRM 2013: The Integrated Breeding Platform: Overview -- G McLaren and M Sawkins
GRM 2013: The Integrated Breeding Platform: Overview -- G McLaren and M Sawkins
 
Integrated Breeding Platform (IBP): A user-friendly platform to implement the...
Integrated Breeding Platform (IBP): A user-friendly platform to implement the...Integrated Breeding Platform (IBP): A user-friendly platform to implement the...
Integrated Breeding Platform (IBP): A user-friendly platform to implement the...
 
PAG 2015 - Breeding View: Statistical analyses in the Breeding Management Sys...
PAG 2015 - Breeding View: Statistical analyses in the Breeding Management Sys...PAG 2015 - Breeding View: Statistical analyses in the Breeding Management Sys...
PAG 2015 - Breeding View: Statistical analyses in the Breeding Management Sys...
 
Integrated Breeding Platform (IBP): A user-friendly platform to implement the...
Integrated Breeding Platform (IBP): A user-friendly platform to implement the...Integrated Breeding Platform (IBP): A user-friendly platform to implement the...
Integrated Breeding Platform (IBP): A user-friendly platform to implement the...
 
GRM 2011: The Integrated Breeding Platform tools and services
GRM 2011: The Integrated Breeding Platform tools and servicesGRM 2011: The Integrated Breeding Platform tools and services
GRM 2011: The Integrated Breeding Platform tools and services
 
Mark Sawkins' presentation at the Symposium on Crop Breeding Databases - Nove...
Mark Sawkins' presentation at the Symposium on Crop Breeding Databases - Nove...Mark Sawkins' presentation at the Symposium on Crop Breeding Databases - Nove...
Mark Sawkins' presentation at the Symposium on Crop Breeding Databases - Nove...
 
Genome voyager-beta-brochure
Genome voyager-beta-brochureGenome voyager-beta-brochure
Genome voyager-beta-brochure
 
Ramil Mauleon: Galaxy: bioinformatics for rice scientists
Ramil Mauleon: Galaxy: bioinformatics for rice scientistsRamil Mauleon: Galaxy: bioinformatics for rice scientists
Ramil Mauleon: Galaxy: bioinformatics for rice scientists
 
Self Service BI for Healthcare
Self Service BI for HealthcareSelf Service BI for Healthcare
Self Service BI for Healthcare
 
Self Service BI for Healthcare
Self Service BI for HealthcareSelf Service BI for Healthcare
Self Service BI for Healthcare
 
GRM 2013: Integrated Breeding Workflow System update -- M Sawkins
GRM 2013: Integrated Breeding Workflow System update -- M SawkinsGRM 2013: Integrated Breeding Workflow System update -- M Sawkins
GRM 2013: Integrated Breeding Workflow System update -- M Sawkins
 
Building Knowledge Graphs for the Agri-Food sector
Building Knowledge Graphs for the Agri-Food sectorBuilding Knowledge Graphs for the Agri-Food sector
Building Knowledge Graphs for the Agri-Food sector
 
PlantScreen™ Modular Systems | QubitPhenomics.com.pdf
PlantScreen™ Modular Systems | QubitPhenomics.com.pdfPlantScreen™ Modular Systems | QubitPhenomics.com.pdf
PlantScreen™ Modular Systems | QubitPhenomics.com.pdf
 
Capabilities
CapabilitiesCapabilities
Capabilities
 
QuahogLife | Solutions and Services
QuahogLife | Solutions and ServicesQuahogLife | Solutions and Services
QuahogLife | Solutions and Services
 
Advancing life sciences with IBM reference architecture for genomics
Advancing life sciences with IBM reference architecture for genomicsAdvancing life sciences with IBM reference architecture for genomics
Advancing life sciences with IBM reference architecture for genomics
 
Legacy Analysis: How Hadoop Streaming Enables Software Reuse – A Genomics Cas...
Legacy Analysis: How Hadoop Streaming Enables Software Reuse – A Genomics Cas...Legacy Analysis: How Hadoop Streaming Enables Software Reuse – A Genomics Cas...
Legacy Analysis: How Hadoop Streaming Enables Software Reuse – A Genomics Cas...
 
App for Physiological Seed quality Parameters
App for Physiological Seed quality ParametersApp for Physiological Seed quality Parameters
App for Physiological Seed quality Parameters
 
An Efficient Online Offline Data Collection Software Solution for Creating Re...
An Efficient Online Offline Data Collection Software Solution for Creating Re...An Efficient Online Offline Data Collection Software Solution for Creating Re...
An Efficient Online Offline Data Collection Software Solution for Creating Re...
 

More from CGIAR Generation Challenge Programme

ARM 2008: Dissection, characterisation and utilisation of disease QTL -- R Ne...
ARM 2008: Dissection, characterisation and utilisation of disease QTL -- R Ne...ARM 2008: Dissection, characterisation and utilisation of disease QTL -- R Ne...
ARM 2008: Dissection, characterisation and utilisation of disease QTL -- R Ne...CGIAR Generation Challenge Programme
 
ARM 2007: Dissection, characterisation and utilisation of disease QTL -- R Ne...
ARM 2007: Dissection, characterisation and utilisation of disease QTL -- R Ne...ARM 2007: Dissection, characterisation and utilisation of disease QTL -- R Ne...
ARM 2007: Dissection, characterisation and utilisation of disease QTL -- R Ne...CGIAR Generation Challenge Programme
 
The Generation Challenge Programme: Lessons learnt relevant to CRPs, and the ...
The Generation Challenge Programme: Lessons learnt relevant to CRPs, and the ...The Generation Challenge Programme: Lessons learnt relevant to CRPs, and the ...
The Generation Challenge Programme: Lessons learnt relevant to CRPs, and the ...CGIAR Generation Challenge Programme
 
TLM III: : Improve common bean productivity for marginal environments in su...
TLM III: :   Improve common bean productivity for marginal environments in su...TLM III: :   Improve common bean productivity for marginal environments in su...
TLM III: : Improve common bean productivity for marginal environments in su...CGIAR Generation Challenge Programme
 
TLM III: Improve groundnut productivity for marginal environments from sub-Sa...
TLM III: Improve groundnut productivity for marginal environments from sub-Sa...TLM III: Improve groundnut productivity for marginal environments from sub-Sa...
TLM III: Improve groundnut productivity for marginal environments from sub-Sa...CGIAR Generation Challenge Programme
 
TLM III: Improve cowpea productivity for marginal environments in sub-Sahara...
TLM III: Improve cowpea productivity for marginal  environments in sub-Sahara...TLM III: Improve cowpea productivity for marginal  environments in sub-Sahara...
TLM III: Improve cowpea productivity for marginal environments in sub-Sahara...CGIAR Generation Challenge Programme
 
TLIII: Overview of TLII achievements, lessons and challenges for Phase III – ...
TLIII: Overview of TLII achievements, lessons and challenges for Phase III – ...TLIII: Overview of TLII achievements, lessons and challenges for Phase III – ...
TLIII: Overview of TLII achievements, lessons and challenges for Phase III – ...CGIAR Generation Challenge Programme
 
TLIII: Tropical Legumes I – Improving Tropical Legume Productivity for Margin...
TLIII: Tropical Legumes I – Improving Tropical Legume Productivity for Margin...TLIII: Tropical Legumes I – Improving Tropical Legume Productivity for Margin...
TLIII: Tropical Legumes I – Improving Tropical Legume Productivity for Margin...CGIAR Generation Challenge Programme
 
Adoption of modern breeding tools in developing countries: challenges and opp...
Adoption of modern breeding tools in developing countries: challenges and opp...Adoption of modern breeding tools in developing countries: challenges and opp...
Adoption of modern breeding tools in developing countries: challenges and opp...CGIAR Generation Challenge Programme
 
PAG XXII 2014 – The Crop Ontology: A resource for enabling access to breeders...
PAG XXII 2014 – The Crop Ontology: A resource for enabling access to breeders...PAG XXII 2014 – The Crop Ontology: A resource for enabling access to breeders...
PAG XXII 2014 – The Crop Ontology: A resource for enabling access to breeders...CGIAR Generation Challenge Programme
 
PAG XXII 2014 – Genomic resources applied to marker-assisted breeding in cowp...
PAG XXII 2014 – Genomic resources applied to marker-assisted breeding in cowp...PAG XXII 2014 – Genomic resources applied to marker-assisted breeding in cowp...
PAG XXII 2014 – Genomic resources applied to marker-assisted breeding in cowp...CGIAR Generation Challenge Programme
 
2011: Introduction to the CGIAR Generation Challenge Programme (GCP)
2011: Introduction to the CGIAR Generation Challenge Programme (GCP)2011: Introduction to the CGIAR Generation Challenge Programme (GCP)
2011: Introduction to the CGIAR Generation Challenge Programme (GCP)CGIAR Generation Challenge Programme
 
Working with diversity in international partnerships -- The GCP experience --...
Working with diversity in international partnerships -- The GCP experience --...Working with diversity in international partnerships -- The GCP experience --...
Working with diversity in international partnerships -- The GCP experience --...CGIAR Generation Challenge Programme
 
GRM 2013: Improving rice productivity in lowland ecosystems of Burkina Faso, ...
GRM 2013: Improving rice productivity in lowland ecosystems of Burkina Faso, ...GRM 2013: Improving rice productivity in lowland ecosystems of Burkina Faso, ...
GRM 2013: Improving rice productivity in lowland ecosystems of Burkina Faso, ...CGIAR Generation Challenge Programme
 
GRM 2013: Improving sorghum productivity in semi-arid environments of Mali th...
GRM 2013: Improving sorghum productivity in semi-arid environments of Mali th...GRM 2013: Improving sorghum productivity in semi-arid environments of Mali th...
GRM 2013: Improving sorghum productivity in semi-arid environments of Mali th...CGIAR Generation Challenge Programme
 
GRM 2013: Wheat product catalogue and project status -- Projects ongoing, com...
GRM 2013: Wheat product catalogue and project status -- Projects ongoing, com...GRM 2013: Wheat product catalogue and project status -- Projects ongoing, com...
GRM 2013: Wheat product catalogue and project status -- Projects ongoing, com...CGIAR Generation Challenge Programme
 
GRM 2013: Sorghum product catalogue and project status -- Projects ongoing, c...
GRM 2013: Sorghum product catalogue and project status -- Projects ongoing, c...GRM 2013: Sorghum product catalogue and project status -- Projects ongoing, c...
GRM 2013: Sorghum product catalogue and project status -- Projects ongoing, c...CGIAR Generation Challenge Programme
 
GRM 2013: Rice product catalogue and project status -- Projects ongoing, comp...
GRM 2013: Rice product catalogue and project status -- Projects ongoing, comp...GRM 2013: Rice product catalogue and project status -- Projects ongoing, comp...
GRM 2013: Rice product catalogue and project status -- Projects ongoing, comp...CGIAR Generation Challenge Programme
 

More from CGIAR Generation Challenge Programme (20)

Capacity Building: Gain or Drain? J-M Ribaut, F Okono and NN Diop
Capacity Building: Gain or Drain? J-M Ribaut, F Okono and NN DiopCapacity Building: Gain or Drain? J-M Ribaut, F Okono and NN Diop
Capacity Building: Gain or Drain? J-M Ribaut, F Okono and NN Diop
 
ARM 2008: Dissection, characterisation and utilisation of disease QTL -- R Ne...
ARM 2008: Dissection, characterisation and utilisation of disease QTL -- R Ne...ARM 2008: Dissection, characterisation and utilisation of disease QTL -- R Ne...
ARM 2008: Dissection, characterisation and utilisation of disease QTL -- R Ne...
 
ARM 2007: Dissection, characterisation and utilisation of disease QTL -- R Ne...
ARM 2007: Dissection, characterisation and utilisation of disease QTL -- R Ne...ARM 2007: Dissection, characterisation and utilisation of disease QTL -- R Ne...
ARM 2007: Dissection, characterisation and utilisation of disease QTL -- R Ne...
 
The Generation Challenge Programme: Lessons learnt relevant to CRPs, and the ...
The Generation Challenge Programme: Lessons learnt relevant to CRPs, and the ...The Generation Challenge Programme: Lessons learnt relevant to CRPs, and the ...
The Generation Challenge Programme: Lessons learnt relevant to CRPs, and the ...
 
Lessons learnt from the GCP experience – J-M Ribaut
Lessons learnt from the GCP experience – J-M RibautLessons learnt from the GCP experience – J-M Ribaut
Lessons learnt from the GCP experience – J-M Ribaut
 
TLM III: : Improve common bean productivity for marginal environments in su...
TLM III: :   Improve common bean productivity for marginal environments in su...TLM III: :   Improve common bean productivity for marginal environments in su...
TLM III: : Improve common bean productivity for marginal environments in su...
 
TLM III: Improve groundnut productivity for marginal environments from sub-Sa...
TLM III: Improve groundnut productivity for marginal environments from sub-Sa...TLM III: Improve groundnut productivity for marginal environments from sub-Sa...
TLM III: Improve groundnut productivity for marginal environments from sub-Sa...
 
TLM III: Improve cowpea productivity for marginal environments in sub-Sahara...
TLM III: Improve cowpea productivity for marginal  environments in sub-Sahara...TLM III: Improve cowpea productivity for marginal  environments in sub-Sahara...
TLM III: Improve cowpea productivity for marginal environments in sub-Sahara...
 
TLIII: Overview of TLII achievements, lessons and challenges for Phase III – ...
TLIII: Overview of TLII achievements, lessons and challenges for Phase III – ...TLIII: Overview of TLII achievements, lessons and challenges for Phase III – ...
TLIII: Overview of TLII achievements, lessons and challenges for Phase III – ...
 
TLIII: Tropical Legumes I – Improving Tropical Legume Productivity for Margin...
TLIII: Tropical Legumes I – Improving Tropical Legume Productivity for Margin...TLIII: Tropical Legumes I – Improving Tropical Legume Productivity for Margin...
TLIII: Tropical Legumes I – Improving Tropical Legume Productivity for Margin...
 
Adoption of modern breeding tools in developing countries: challenges and opp...
Adoption of modern breeding tools in developing countries: challenges and opp...Adoption of modern breeding tools in developing countries: challenges and opp...
Adoption of modern breeding tools in developing countries: challenges and opp...
 
PAG XXII 2014 – The Crop Ontology: A resource for enabling access to breeders...
PAG XXII 2014 – The Crop Ontology: A resource for enabling access to breeders...PAG XXII 2014 – The Crop Ontology: A resource for enabling access to breeders...
PAG XXII 2014 – The Crop Ontology: A resource for enabling access to breeders...
 
PAG XXII 2014 – Genomic resources applied to marker-assisted breeding in cowp...
PAG XXII 2014 – Genomic resources applied to marker-assisted breeding in cowp...PAG XXII 2014 – Genomic resources applied to marker-assisted breeding in cowp...
PAG XXII 2014 – Genomic resources applied to marker-assisted breeding in cowp...
 
2011: Introduction to the CGIAR Generation Challenge Programme (GCP)
2011: Introduction to the CGIAR Generation Challenge Programme (GCP)2011: Introduction to the CGIAR Generation Challenge Programme (GCP)
2011: Introduction to the CGIAR Generation Challenge Programme (GCP)
 
Working with diversity in international partnerships -- The GCP experience --...
Working with diversity in international partnerships -- The GCP experience --...Working with diversity in international partnerships -- The GCP experience --...
Working with diversity in international partnerships -- The GCP experience --...
 
GRM 2013: Improving rice productivity in lowland ecosystems of Burkina Faso, ...
GRM 2013: Improving rice productivity in lowland ecosystems of Burkina Faso, ...GRM 2013: Improving rice productivity in lowland ecosystems of Burkina Faso, ...
GRM 2013: Improving rice productivity in lowland ecosystems of Burkina Faso, ...
 
GRM 2013: Improving sorghum productivity in semi-arid environments of Mali th...
GRM 2013: Improving sorghum productivity in semi-arid environments of Mali th...GRM 2013: Improving sorghum productivity in semi-arid environments of Mali th...
GRM 2013: Improving sorghum productivity in semi-arid environments of Mali th...
 
GRM 2013: Wheat product catalogue and project status -- Projects ongoing, com...
GRM 2013: Wheat product catalogue and project status -- Projects ongoing, com...GRM 2013: Wheat product catalogue and project status -- Projects ongoing, com...
GRM 2013: Wheat product catalogue and project status -- Projects ongoing, com...
 
GRM 2013: Sorghum product catalogue and project status -- Projects ongoing, c...
GRM 2013: Sorghum product catalogue and project status -- Projects ongoing, c...GRM 2013: Sorghum product catalogue and project status -- Projects ongoing, c...
GRM 2013: Sorghum product catalogue and project status -- Projects ongoing, c...
 
GRM 2013: Rice product catalogue and project status -- Projects ongoing, comp...
GRM 2013: Rice product catalogue and project status -- Projects ongoing, comp...GRM 2013: Rice product catalogue and project status -- Projects ongoing, comp...
GRM 2013: Rice product catalogue and project status -- Projects ongoing, comp...
 

Recently uploaded

IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsEnterprise Knowledge
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonetsnaman860154
 
Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...Alan Dix
 
Azure Monitor & Application Insight to monitor Infrastructure & Application
Azure Monitor & Application Insight to monitor Infrastructure & ApplicationAzure Monitor & Application Insight to monitor Infrastructure & Application
Azure Monitor & Application Insight to monitor Infrastructure & ApplicationAndikSusilo4
 
My Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationMy Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationRidwan Fadjar
 
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxFactors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxKatpro Technologies
 
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j
 
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdfhans926745
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024Rafal Los
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationMichael W. Hawkins
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerThousandEyes
 
How to Remove Document Management Hurdles with X-Docs?
How to Remove Document Management Hurdles with X-Docs?How to Remove Document Management Hurdles with X-Docs?
How to Remove Document Management Hurdles with X-Docs?XfilesPro
 
Human Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsHuman Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsMark Billinghurst
 
SIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge GraphSIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge GraphNeo4j
 
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsMaria Levchenko
 
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticsKotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticscarlostorres15106
 
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...shyamraj55
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationSafe Software
 
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure serviceWhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure servicePooja Nehwal
 
Install Stable Diffusion in windows machine
Install Stable Diffusion in windows machineInstall Stable Diffusion in windows machine
Install Stable Diffusion in windows machinePadma Pradeep
 

Recently uploaded (20)

IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI Solutions
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonets
 
Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...
 
Azure Monitor & Application Insight to monitor Infrastructure & Application
Azure Monitor & Application Insight to monitor Infrastructure & ApplicationAzure Monitor & Application Insight to monitor Infrastructure & Application
Azure Monitor & Application Insight to monitor Infrastructure & Application
 
My Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationMy Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 Presentation
 
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxFactors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
 
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
 
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day Presentation
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
How to Remove Document Management Hurdles with X-Docs?
How to Remove Document Management Hurdles with X-Docs?How to Remove Document Management Hurdles with X-Docs?
How to Remove Document Management Hurdles with X-Docs?
 
Human Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsHuman Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR Systems
 
SIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge GraphSIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge Graph
 
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed texts
 
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticsKotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
 
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
 
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure serviceWhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
 
Install Stable Diffusion in windows machine
Install Stable Diffusion in windows machineInstall Stable Diffusion in windows machine
Install Stable Diffusion in windows machine
 

PAG XXII 2014 – The Breeding Management System (BMS) of the Integrated Breeding Platform (IBP) – G McLaren

  • 1. Integrated Breeding Platform Breeding Management System (BMS) IBP Management Team Presenter – Graham McLaren January 2014
  • 2. Rationale for the IBP   Large private seed companies have successfully implemented extensive suites of integrated informatics tools to turbocharge their breeding programs Implementation of this integrated informatics in public programs lags behind, especially in developing countries    Some tools have been developed at various CG centers, but implementation has been uneven and they are not integrated into a comprehensive system Most NARS programs still rely on rudimentary tools, from pen and paper to Excel spreadsheets Small SMEs in developing countries typically do not have the resources to acquire available commercial software or to implement breeding IT systems on their own
  • 4. Breeding Management System (BMS) – Product Concept       Simple and easy-to-use application containing all informatics tools needed by a breeder Seamless flow of data between applications Accumulation, sharing and re-use of breeding data Targets routine breeding activities and will not replace research tools Will allow integration of users own tools into the system Implementable as a standalone system   Access central and local DB, as well as the BMS on a local PC Will also be implementable as a cloud-based system via iPlant cyber-infrastructure  For computationally intensive analyses or large data storage needs
  • 5.
  • 6. List Manager Functionality The List Manager is at the center of all activities in the Breeding Management System:     First screen you arrive at after opening your Breeding Program New left navigation menu provides direct access to all tools Easily build and work with the lists that are used in each stage of the breeding cycle Key List Manager Features:      Ability to browse and modify existing lists Ability to search for lists and germplasm entries Ability to create a new list dynamically by pulling from existing lists or germplasm search results Expanded ability to modify list contents Ability to export lists for use outside of the Breeding Management System
  • 7.
  • 8. Breeding Logistics Once the strategy and parental material have been identified, the breeder wants to:  make crosses,  develop populations,  track pedigrees,  track inventory,  characterize lines
  • 9. Nursery and Trial Management  Breeding Manager configured for different crops     IB Fieldbook    Crossing manager, nursery manager, pedigree recording Focuses on population development and line selection Nursery advance and seed inventory tracking Focuses on field trial management for germplasm evaluation Trait selection, field design, labels and sample tracking Android-based hand-held device   Optimized for use with Samsung Galaxy tablet for field data collection Other Android devices can be used if preferred Breeding manager and Field books fully integrated into BMS workbench
  • 10.
  • 11. Field Testing Once populations are developed, the breeder wants to:  select traits,  make lists of germplasm,  generate designs,  produce fieldbooks,  collect data,  check and store data.
  • 12. Breeding Management Trait Dictionaries Reporting units or scale Measurement method Trait property Measurement Variate
  • 17. Breeding Management Tablet Devices Fieldbook connects to Androidbased tablet devises for data collection in the field and laboratory
  • 18. Integrated Breeding Database  Genealogy Management System (GMS)    Phenotypeing Data Management System (DMS)    Germplasm nomenclature, chronology, IP and passport data Pedigrees and breeding history Germplasm characterization and evaluation data Annotated with Crop Research and Crop Trait Ontologies Genotypic Data Management System (GDMS)    Medium density fingerprinting data Genotyping data for MAS and MABC Genotyping data for Marker-trait association analysis Databases fully integrated into BMS workbench
  • 19. Query Tools At the outset of a breeding cycle users want to:  browse all germplasm information  review existing characterization and evaluation  search for adapted germplasm  perform head to head comparisons
  • 20. Statistical Analysis of Phenotyping Data       Breeding View provides easy access to the high throughput analyses routinely required by breeders The same interface can be used to access procedures in Genstat or R-scripts and allows analyses to be configured Single site analysis is available for complete and incomplete block designs as well as row-column designs and spatial analysis. New designs are being added at each update, Analyses can be run in batches over environments and traits, Two-stage multi-site analysis is available for GxE and stability analysis with or without grouping of environments, Single pass meta analysis of unbalanced site by season data is being incorporated. Tools to be fully integrated into the BMS by June 2014
  • 21.
  • 22. Genotyping To use molecular technologies, the breeder wants to:  select population,  select markers,  genotype population,  check and store genotyping data.
  • 24. Breeding View - QTL analysis  Single trait linkage analysis (QTL)        Quality control phenotypes (summary statistics) Quality control marker data QTL detection – genome wide scan using single and composite IM Output includes profile plots and tables Results available for automatic viewing in Flapjack HTML report of QTL results Multiple trait sequential analysis   QTL results for each trait combined Single Flapjack view for all traits
  • 25.
  • 26. Decision support for Marker implementation   OptiMAS Developed at INRA, Le Moulon Implementation of markers in a MARS breeding scheme Identify and track favorable alleles through cycles of recombination and selection Molecular Breeding Decision Tool (MBDT) Developed by team at ICRISAT Implementation of markers in a MAS and MABC context
  • 27. Future Directions       Continuous improvement of UI based on user feedback Additional analysis methods for expanded experimental designs and genetic analysis Seed inventory management system LAN based deployment available in January, cloud based deployment available in June Data will be stored in a single shareable database with user access roles Off-line capability will be supported by a data cache which will synchronize when a connection is available