PAG-ASIA2015_Phosphorus efficiency breeding_V3Ian Paul Navea
This document discusses developing rice varieties that are adapted to temperate regions, climate change, and low-input conditions. Researchers have introduced the Pup1 gene to enhance phosphorus efficiency in temperate rice under low P input and rainfed conditions. They identified 5 QTLs for panicle length on chromosomes 1, 2, 9, and 11 using indica-japonica RILs under low P and rainfed conditions in the tropics. Introgression lines with Pup1 had higher yield than parents, except for one variety. The study aims to develop climate-ready rice using QTL pyramiding.
Division seminar august 1,2012 prashant vikramPrashant Vikram
The document summarizes research on identifying consistent quantitative trait loci (QTLs) for grain yield under drought stress in rice. It describes phenotyping populations of rice under reproductive stage drought stress and genotyping them to identify QTLs. A major QTL, qDTY1.1, was found to increase grain yield by 16-29% in multiple genetic backgrounds. Further research eliminated linkage drag at this QTL locus to develop introgression lines with improved drought tolerance but limited yield penalties under non-stress conditions. Background analysis found that qDTY1.1 alleles from drought tolerant varieties N22 and Dhagaddeshi were similar and distinct from susceptible varieties. Overall, the research aimed to identify stable Q
Drought molecular breeding in rice, 19 november, 2012 swamyarjunmanju
This document discusses mapping and transferring QTLs for drought tolerance in rice. It begins by providing context on rice production, noting that 45% of rice is grown in rainfed areas with lower productivity. It then discusses strategies for developing drought tolerant rice varieties through conventional breeding and molecular approaches. Key points include using improved lines as donors, direct selection for grain yield under drought, identifying major drought yield QTLs, and introgressing QTLs into improved varieties. Several major effect QTLs for grain yield under drought are identified, including DTY1.1, DTY3.1, and DTY12.1. The consistency of these QTLs across backgrounds, ecosystems, and environments is discussed. The document
Marker assisted breeding of biotic stress resistance in Rice Senthil Natesan
A marker is a DNA sequence which serves as a signpost/flag post
linked to the trait/gene of interest and is co-inherited along with
the trait
Presence of specific allele of marker = Presence of specific allele of target gene based on the concept the MAS practiced -R.M. Sundaram
Directorate Rice of Research, Hydrabad , July 3rd 2009, CPMB&B, TNAU presentation
The document discusses marker-assisted selection (MAS), which uses genetic markers linked to genes of interest to make selection decisions for genetic improvement. MAS can be applied to traits that are difficult to measure, late-life traits, or those measured on only one sex. The accuracy of MAS depends on the linkage between the marker and gene. Successful MAS requires gene mapping, genotyping, QTL detection, and integrating phenotypic and genotypic data in evaluations. MAS response is limited long-term but benefits of favorable variants continue. Marker-assisted introgression can also be used to transfer genes between breeds faster.
Marker-assisted selection (MAS) is a plant breeding method that uses DNA markers to select for desirable traits. It allows breeders to select plants earlier in development compared to phenotypic selection. MAS has advantages like being unaffected by environment and ability to select for recessive traits, but may be more expensive initially than conventional methods. Careful analysis of costs and benefits is needed to determine if MAS is advantageous for a particular program over traditional breeding. MAS requires tightly linked markers, knowledge of marker-trait associations, and data management to be effective. A variety of MAS approaches exist like backcrossing, pyramiding, and combined MAS and phenotypic selection.
PAG-ASIA2015_Phosphorus efficiency breeding_V3Ian Paul Navea
This document discusses developing rice varieties that are adapted to temperate regions, climate change, and low-input conditions. Researchers have introduced the Pup1 gene to enhance phosphorus efficiency in temperate rice under low P input and rainfed conditions. They identified 5 QTLs for panicle length on chromosomes 1, 2, 9, and 11 using indica-japonica RILs under low P and rainfed conditions in the tropics. Introgression lines with Pup1 had higher yield than parents, except for one variety. The study aims to develop climate-ready rice using QTL pyramiding.
Division seminar august 1,2012 prashant vikramPrashant Vikram
The document summarizes research on identifying consistent quantitative trait loci (QTLs) for grain yield under drought stress in rice. It describes phenotyping populations of rice under reproductive stage drought stress and genotyping them to identify QTLs. A major QTL, qDTY1.1, was found to increase grain yield by 16-29% in multiple genetic backgrounds. Further research eliminated linkage drag at this QTL locus to develop introgression lines with improved drought tolerance but limited yield penalties under non-stress conditions. Background analysis found that qDTY1.1 alleles from drought tolerant varieties N22 and Dhagaddeshi were similar and distinct from susceptible varieties. Overall, the research aimed to identify stable Q
Drought molecular breeding in rice, 19 november, 2012 swamyarjunmanju
This document discusses mapping and transferring QTLs for drought tolerance in rice. It begins by providing context on rice production, noting that 45% of rice is grown in rainfed areas with lower productivity. It then discusses strategies for developing drought tolerant rice varieties through conventional breeding and molecular approaches. Key points include using improved lines as donors, direct selection for grain yield under drought, identifying major drought yield QTLs, and introgressing QTLs into improved varieties. Several major effect QTLs for grain yield under drought are identified, including DTY1.1, DTY3.1, and DTY12.1. The consistency of these QTLs across backgrounds, ecosystems, and environments is discussed. The document
Marker assisted breeding of biotic stress resistance in Rice Senthil Natesan
A marker is a DNA sequence which serves as a signpost/flag post
linked to the trait/gene of interest and is co-inherited along with
the trait
Presence of specific allele of marker = Presence of specific allele of target gene based on the concept the MAS practiced -R.M. Sundaram
Directorate Rice of Research, Hydrabad , July 3rd 2009, CPMB&B, TNAU presentation
The document discusses marker-assisted selection (MAS), which uses genetic markers linked to genes of interest to make selection decisions for genetic improvement. MAS can be applied to traits that are difficult to measure, late-life traits, or those measured on only one sex. The accuracy of MAS depends on the linkage between the marker and gene. Successful MAS requires gene mapping, genotyping, QTL detection, and integrating phenotypic and genotypic data in evaluations. MAS response is limited long-term but benefits of favorable variants continue. Marker-assisted introgression can also be used to transfer genes between breeds faster.
Marker-assisted selection (MAS) is a plant breeding method that uses DNA markers to select for desirable traits. It allows breeders to select plants earlier in development compared to phenotypic selection. MAS has advantages like being unaffected by environment and ability to select for recessive traits, but may be more expensive initially than conventional methods. Careful analysis of costs and benefits is needed to determine if MAS is advantageous for a particular program over traditional breeding. MAS requires tightly linked markers, knowledge of marker-trait associations, and data management to be effective. A variety of MAS approaches exist like backcrossing, pyramiding, and combined MAS and phenotypic selection.
Presented at the High-Level Ministerial (HLM) Conference on Rice Development in Sub-Saharan Africa 25 September 2018
Dakar, Senegal
Abebe Haile-Gabriel
FAO Regional Programme Leader for Africa, RAF
Rice production, area, and consumption have increased substantially in sub-Saharan Africa between 2008-2018, however self-sufficiency levels have decreased. While rice area and production grew by 40% and 55% respectively, consumption rose even faster at 81%, leading to a widening gap. Yield growth also slowed after initial increases following the 2008 food crisis. To achieve rice self-sufficiency by 2025, production would need to increase at over 16% annually through increased investments estimated at $2.7 billion under a new investment plan for 10 pilot countries in sub-Saharan Africa. Additional policy measures are also needed such as reducing rice imports and supporting improved technologies, organization of value chains, and market access for producers.
Presented at the High-Level Ministerial (HLM) Conference on Rice Development in Sub-Saharan Africa 25 September 2018
Dakar, Senegal
Presented by Dr Amadou Beye, Seed Specialist,
Africa Rice Center (AfricaRice)
Recensement électronique et géo-référence des acteurs de la chaine de valeur riz: cas des pays TAAT
Aminou A. et Aboudou Rachidi
TAAT Rice Compact Launch and Knowledge Sharing Workshop
6 - 7 September 2018
M’be, Bouake
Cote d’Ivoire
The document discusses Good Agricultural Practices (GAP) for rice production in Sub-Saharan Africa and their impact on yields. It provides a list of common GAP components introduced in various countries. Trial results found yield increases of 1-1.2 tonnes/hectare on average when adopting 3-4 GAP components. Larger yield gains were seen under rainfed lowland systems. Outscaling efforts reached over 1500 farmers by 2018. However, adoption faces constraints like limited knowledge and access to improved technologies. The document proposes an impact pathway and budget to train farmers on GAP.
Partnerships for efficient quality seed production and variety dissemination
Saidu Bah
Seed & Seed Systems Expert
The Africa Rice Center
TAAT Rice Compact Launch and Knowledge Sharing Workshop
6 - 7 September 2018
M’be, Bouake
Cote d’Ivoire
- The Africa Rice Center (AfricaRice) is the only CGIAR Research Center owned by African countries. It works to increase rice production and self-sufficiency in Sub-Saharan Africa through research and partnerships.
- AfricaRice has developed over 200 improved rice varieties, good agricultural practices, and innovations along the rice value chain to boost yields and incomes for farmers.
- It aims to increase rice self-sufficiency in Sub-Saharan Africa to 90% by 2020 through implementation of its 2011-2020 strategic plan which focuses on strengthening rice production, processing, and marketing.
AfricaRice Director General Dr Harold Roy-Macauley made a presentation on “Achieving rice self-sufficiency in Africa,” which served as a basis for an in-depth discussion by a panel of speakers consisting of Mr Ade Adefeko, Vice President and Head of Corporate and Government Relations at Olam-Nigeria; Mr Pieter Grobler, Head of Land Development at Dangote Rice Limited; and Mr Busuyi Okeowo, Deputy Team Leader at Growth & Employment in States (GEMS 4), Nigeria.
The panel discussion was organized as part of the Third Edition of the Agra Innovate West Africa Conference, on 23 November 2016 in Lagos, Nigeria, with support from the Federal Ministry of Agriculture and Rural Development (FMARD) and the Nigeria Agribusiness Group (NABG).
L’autosuffisance de l’Afrique en riz : opportunités et défis à l’échelledu continent africain by Dr Harold Roy-Macauley, Directeur général, AfricaRice. -- Table ronde, Montpellier, France, 28 septembre 2016 Organisée en marge de la 14ème symposium international sur la génomique fonctionnelle du riz
"Autosuffisance du riz en Côte d‘Ivoire Contribution d’AfricaRice" -- Harold Roy-Macauley's presentation the Ivorian dignitaries who met with the members of the AfricaRice Board of Trustees on 8 Sep 2016 during the 40th Board meeting at AfricaRice headquarters in Abidjan, Côte d’Ivoire.
CGIAR is a global research partnership addressing agricultural challenges related to poverty, food insecurity, and environmental degradation through research conducted by 15 centers and hundreds of partners. Research products from CGIAR have transformed lives in sub-Saharan Africa, including new rice varieties that have lifted 8 million people out of poverty, drought-resistant sorghum and millet varieties that have increased yields and incomes, and provitamin A maize that provides key nutrients to households. Looking ahead, the second generation CGIAR strategy will focus research on food security, nutrition, health, and climate change through its portfolio of research programs.
Harold Roy-Macauley's presentation on "Africa Rice Center (AfricaRice): A CGIAR research center and pan-African association of member countries" to the World Bank delegation from Côte d'Ivoire led by Mr Pierre Laporte, World Bank Country Director for Côte d'Ivoire, Benin, Burkina Faso, Guinea, and Togo based in Abidjan, visited AfricaRice headquarters on 15 July 2016. The other members of the delegation were Mr Abdoulaye Touré, Lead Agricultural Economist and Task Team Leader of WAAPP-World Bank (Africa Bureau); and Mr Taleb Ould Sid Ahmed, Senior Communications Officer. Mr Hiroshi Hiraoka, Senior Agriculture Economist, AFTA2, World Bank and member of the Coalition for African Rice Development (CARD) Steering Committee also accompanied the delegation.
AfricaRice Director General Dr Harold Roy-Macauley leading the panel discussion on "Africa Riceing : Mobilizing and applying science and complementary resources to achieve self–sufficiency in rice in Africa." at the 7th Africa Agriculture Science Week and FARA General Assembly, Kigali, Rwanda, on 14 June 2016
The document summarizes the achievements and perspectives of the SARD-SC rice value chain project in Africa. The project has:
1) Tested over 50 agricultural innovations to address rice production constraints and close yield gaps across Africa. This includes weeders, seeders, decision support tools, and improved rice processing technologies.
2) Disseminated improved technologies and best practices through rice sector hubs, reaching over 250,000 farmers. This has increased yields, incomes, and market access for smallholders.
3) Built the capacity of over 450 African researchers and stakeholders through training programs. This has strengthened national agricultural research and innovation systems.
4) Effectively managed project implementation through monitoring and evaluation
The document discusses increasing genetic gains in farmers' fields in Africa through public sector crop breeding programs. It notes that current rates of genetic gain achieved by these programs are suboptimal. The key points are:
1. Genetic gain is measured as the annual increase in productivity due to breeding, but is difficult to measure directly in farmers' fields. Estimates suggest average genetic gains of around 0.3% per year for maize in Africa.
2. Higher genetic gains over the long term can transform agriculture by providing steady improvements, effective climate adaptation, and reduced environmental impacts. However, rates of 1-2% per year are needed to have significant impacts.
3. To increase genetic gains, public breeding
Emerging models to drive rice intensification in West Africa
1) Rice demand is exploding in West Africa due to population growth, but current smallholder systems lack efficiency in production and market access.
2) The Syngenta Foundation aims to integrate smallholders into functioning rice value chains through projects providing access to inputs, equipment, and markets.
3) Example projects in Ghana, Cote d'Ivoire, Burkina Faso, Mali, and Senegal involve thousands of smallholders in contract farming and warrantage models with a focus on improved production, post-harvest handling, and market linkages.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Presented at the High-Level Ministerial (HLM) Conference on Rice Development in Sub-Saharan Africa 25 September 2018
Dakar, Senegal
Abebe Haile-Gabriel
FAO Regional Programme Leader for Africa, RAF
Rice production, area, and consumption have increased substantially in sub-Saharan Africa between 2008-2018, however self-sufficiency levels have decreased. While rice area and production grew by 40% and 55% respectively, consumption rose even faster at 81%, leading to a widening gap. Yield growth also slowed after initial increases following the 2008 food crisis. To achieve rice self-sufficiency by 2025, production would need to increase at over 16% annually through increased investments estimated at $2.7 billion under a new investment plan for 10 pilot countries in sub-Saharan Africa. Additional policy measures are also needed such as reducing rice imports and supporting improved technologies, organization of value chains, and market access for producers.
Presented at the High-Level Ministerial (HLM) Conference on Rice Development in Sub-Saharan Africa 25 September 2018
Dakar, Senegal
Presented by Dr Amadou Beye, Seed Specialist,
Africa Rice Center (AfricaRice)
Recensement électronique et géo-référence des acteurs de la chaine de valeur riz: cas des pays TAAT
Aminou A. et Aboudou Rachidi
TAAT Rice Compact Launch and Knowledge Sharing Workshop
6 - 7 September 2018
M’be, Bouake
Cote d’Ivoire
The document discusses Good Agricultural Practices (GAP) for rice production in Sub-Saharan Africa and their impact on yields. It provides a list of common GAP components introduced in various countries. Trial results found yield increases of 1-1.2 tonnes/hectare on average when adopting 3-4 GAP components. Larger yield gains were seen under rainfed lowland systems. Outscaling efforts reached over 1500 farmers by 2018. However, adoption faces constraints like limited knowledge and access to improved technologies. The document proposes an impact pathway and budget to train farmers on GAP.
Partnerships for efficient quality seed production and variety dissemination
Saidu Bah
Seed & Seed Systems Expert
The Africa Rice Center
TAAT Rice Compact Launch and Knowledge Sharing Workshop
6 - 7 September 2018
M’be, Bouake
Cote d’Ivoire
- The Africa Rice Center (AfricaRice) is the only CGIAR Research Center owned by African countries. It works to increase rice production and self-sufficiency in Sub-Saharan Africa through research and partnerships.
- AfricaRice has developed over 200 improved rice varieties, good agricultural practices, and innovations along the rice value chain to boost yields and incomes for farmers.
- It aims to increase rice self-sufficiency in Sub-Saharan Africa to 90% by 2020 through implementation of its 2011-2020 strategic plan which focuses on strengthening rice production, processing, and marketing.
AfricaRice Director General Dr Harold Roy-Macauley made a presentation on “Achieving rice self-sufficiency in Africa,” which served as a basis for an in-depth discussion by a panel of speakers consisting of Mr Ade Adefeko, Vice President and Head of Corporate and Government Relations at Olam-Nigeria; Mr Pieter Grobler, Head of Land Development at Dangote Rice Limited; and Mr Busuyi Okeowo, Deputy Team Leader at Growth & Employment in States (GEMS 4), Nigeria.
The panel discussion was organized as part of the Third Edition of the Agra Innovate West Africa Conference, on 23 November 2016 in Lagos, Nigeria, with support from the Federal Ministry of Agriculture and Rural Development (FMARD) and the Nigeria Agribusiness Group (NABG).
L’autosuffisance de l’Afrique en riz : opportunités et défis à l’échelledu continent africain by Dr Harold Roy-Macauley, Directeur général, AfricaRice. -- Table ronde, Montpellier, France, 28 septembre 2016 Organisée en marge de la 14ème symposium international sur la génomique fonctionnelle du riz
"Autosuffisance du riz en Côte d‘Ivoire Contribution d’AfricaRice" -- Harold Roy-Macauley's presentation the Ivorian dignitaries who met with the members of the AfricaRice Board of Trustees on 8 Sep 2016 during the 40th Board meeting at AfricaRice headquarters in Abidjan, Côte d’Ivoire.
CGIAR is a global research partnership addressing agricultural challenges related to poverty, food insecurity, and environmental degradation through research conducted by 15 centers and hundreds of partners. Research products from CGIAR have transformed lives in sub-Saharan Africa, including new rice varieties that have lifted 8 million people out of poverty, drought-resistant sorghum and millet varieties that have increased yields and incomes, and provitamin A maize that provides key nutrients to households. Looking ahead, the second generation CGIAR strategy will focus research on food security, nutrition, health, and climate change through its portfolio of research programs.
Harold Roy-Macauley's presentation on "Africa Rice Center (AfricaRice): A CGIAR research center and pan-African association of member countries" to the World Bank delegation from Côte d'Ivoire led by Mr Pierre Laporte, World Bank Country Director for Côte d'Ivoire, Benin, Burkina Faso, Guinea, and Togo based in Abidjan, visited AfricaRice headquarters on 15 July 2016. The other members of the delegation were Mr Abdoulaye Touré, Lead Agricultural Economist and Task Team Leader of WAAPP-World Bank (Africa Bureau); and Mr Taleb Ould Sid Ahmed, Senior Communications Officer. Mr Hiroshi Hiraoka, Senior Agriculture Economist, AFTA2, World Bank and member of the Coalition for African Rice Development (CARD) Steering Committee also accompanied the delegation.
AfricaRice Director General Dr Harold Roy-Macauley leading the panel discussion on "Africa Riceing : Mobilizing and applying science and complementary resources to achieve self–sufficiency in rice in Africa." at the 7th Africa Agriculture Science Week and FARA General Assembly, Kigali, Rwanda, on 14 June 2016
The document summarizes the achievements and perspectives of the SARD-SC rice value chain project in Africa. The project has:
1) Tested over 50 agricultural innovations to address rice production constraints and close yield gaps across Africa. This includes weeders, seeders, decision support tools, and improved rice processing technologies.
2) Disseminated improved technologies and best practices through rice sector hubs, reaching over 250,000 farmers. This has increased yields, incomes, and market access for smallholders.
3) Built the capacity of over 450 African researchers and stakeholders through training programs. This has strengthened national agricultural research and innovation systems.
4) Effectively managed project implementation through monitoring and evaluation
The document discusses increasing genetic gains in farmers' fields in Africa through public sector crop breeding programs. It notes that current rates of genetic gain achieved by these programs are suboptimal. The key points are:
1. Genetic gain is measured as the annual increase in productivity due to breeding, but is difficult to measure directly in farmers' fields. Estimates suggest average genetic gains of around 0.3% per year for maize in Africa.
2. Higher genetic gains over the long term can transform agriculture by providing steady improvements, effective climate adaptation, and reduced environmental impacts. However, rates of 1-2% per year are needed to have significant impacts.
3. To increase genetic gains, public breeding
Emerging models to drive rice intensification in West Africa
1) Rice demand is exploding in West Africa due to population growth, but current smallholder systems lack efficiency in production and market access.
2) The Syngenta Foundation aims to integrate smallholders into functioning rice value chains through projects providing access to inputs, equipment, and markets.
3) Example projects in Ghana, Cote d'Ivoire, Burkina Faso, Mali, and Senegal involve thousands of smallholders in contract farming and warrantage models with a focus on improved production, post-harvest handling, and market linkages.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Speck&Tech
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
Ocean lotus Threat actors project by John Sitima 2024 (1).pptxSitimaJohn
Ocean Lotus cyber threat actors represent a sophisticated, persistent, and politically motivated group that poses a significant risk to organizations and individuals in the Southeast Asian region. Their continuous evolution and adaptability underscore the need for robust cybersecurity measures and international cooperation to identify and mitigate the threats posed by such advanced persistent threat groups.
Fueling AI with Great Data with Airbyte WebinarZilliz
This talk will focus on how to collect data from a variety of sources, leveraging this data for RAG and other GenAI use cases, and finally charting your course to productionalization.
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
Digital Marketing Trends in 2024 | Guide for Staying AheadWask
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Th1_Introgression of phosphorus uptake 1 (Pup1) QTL into rice varieties locally adapted in sub-Saharan Africa
1. Introgression of phosphorus
uptake 1 (Pup1) QTL into rice
varieties locally adapted in
sub-Saharan Africa
Khady Nani Dramé et al.
Africa Rice Center – ESA regional office, Tanzania
k.drame@cgiar.org
2. Outline
1. Introduction - Phosphorus (P) deficiency in sub-Saharan Africa
2. Distribution of Pup1 QTL in African germplasm
3. Status of Pup1 introgression into selected rice varieties
4. Genomic organization of Pup1 locus in O. glaberrima species
5. Conclusion - The way forward
3. P-deficiency in SSA
• Plant-available P deficient in many soils
- low levels of P (inherent or depleted),
- high P-sorption capacity (530 million ha, ~25% of land area)
• Annual fertilizer consumption in Africa = 0.8% (1.29 Mt) of global
fertilizer consumption (IFDC, 2013)
• P-fertilizer price is peaking and it is a finite resource
unaffordable for smallholders
Development of cultivars with enhanced tolerance to P-deficiency to
improve rice yield in a cost effective and sustainable way
4. Genetic approach to mitigate P-deficiency
One of the most successful to date: identification and characterization of Pup1 QTL
Pup1 identified in
Kasalath on chr. 12
Pup1 explained close to 80%
of the variation observed
Pup1 locus includes an INDEL
absent from Nipponbare genome
15
YEARS
LATER
Pup1 major determinant is a
kinase gene located in the INDEL
root growth and development
5. Pup1 gene-based markers
Pup1 locus on Chr. 12 aligned
in Nipponbare and Kasalath
Chin et al. (2010)
•
K1 and K20-1: for both markers, we
could not separate the N and K alleles
which differ by only 3 bp
•
K20-2 digested with Bsp1286I: reliable
marker
•
K46-1, K46-2 and K52 amplified as
expected
Profile of K20-2 amplicons digested with Bsp1286I
K
K
K
K
N
K
K
Profile of K46-1 amplicons (dominant marker)
N
K
N
N
K
N
K
K20-2, K46-1 and K52 were selected
as diagnostic markers of Pup1
6. Distribution of Pup1 in African germplasm
Species
Number
Ecology of adaptation
O. sativa japonica
19
Upland
O. sativa indica
17
Lowland (rainfed and irrigated)
Interspecific O. sativa x O. glaberrima (NERICA)
18
Upland
Interspecific O. sativa x O. glaberrima (NERICA-L)
60
Lowland
O. glaberrima
31
Lowland, Upland and Floating
O. barthii
3
Upland
90
80
Average frequency of Kasalath
(K), Nipponbare (N) and unknown
(other) alleles across loci targeted
by K20-2, K46-1 and K52 markers
70
60
50
Mean K
40
Mean N
30
Mean other
20
10
0
O. sativa
japonica
O. sativa
indica
NERICA
NERICA-L
O.
O. barthii
glaberrima
7. Pup1 transfer into selected upland varieties
Donor
Recipients lacking PSTOL1
(targeted by K46-1)
2011
2012
2013
Kasalath
NERICA 1, 4, 10
Dourado-Precoce
WAB 96-1-1
WAB 189-B-B-B-8-HB
WAB 515-B-16-A2-2
Pup1 survey
Genotype
selection
Genotype
selection
BC1F1 from
7 crosses
BC2F1 from
4 crosses
F1 lines
1. Foreground selection (chr. 12), Pup1-gene based markers
8. … Genotype selection
2. Recombinant selection (chr. 12) flanking Pup1
8 markers tested
8 markers tested
16.05 Mb
15.63 Mb
15.47 Mb
15,31 Mb
15.28 Mb
14.93 Mb
Pup1
Two polymorphic makers
selected at 5’ end and one
marker at 3’ end
3. Background selection (chr. 1 to 12)
281 SSR markers tested and 104 to 112 polymorphic markers identified
384 SNP markers tested and 246 to 277 polymorphic markers identified
9. Current status – Pup1 MABC
Combination for
F1 generation
No. of No. of seeds No. of lines No. lines No. of “true” No of lines
No. of BC1F1
crosses obtained genotyped with Pup1
F1
backcrossed seeds obtained
NERICA 1/Kasalath
4
54
31
27
26
17
1048
NERICA 4/Kasalath
1
19
4
3
3
2
487
NERICA 10/Kasalath
2
41
15
10
10
9
547
DOURADO/Kasalath
1
90
27
14
14
12
930
WAB 96-1-1/Kasalath
1
16
2
1
1
1
586
WAB 189-/Kasalath
2
155
22
10
7
7
1084
WAB 515-/Kasalath
5
111
24
14
13
9
1590
Combination for BC1F1
generation
NERICA 1/Kasalath
NERICA 4/Kasalath
NERICA 10/Kasalath
WAB 515-/Kasalath
No. of lines
sown
No. of lines
genotyped
No. of lines
with Pup1
477
472
477
477
360
321
283
405
128
177
85
196
No. of
No of BC2F1
recombinants seeds obtained
34
24
35
24
1004
1412
829
2178
10. The hidden allele
African germplasm genotyped with K46-1 (PSTOL1 marker)
Pariasca-Tanaka et al. (2013)
L
N
1
N
2
N
3
N
4
N
5
N
6
N
7
N N N N N N N
Amplicons sequenced
8 9 1 1 1 1 1
0 1 2 3 4
N
1
5
N
1
6
N
1
8
N
1
7
W
5
0
C
G
W W
1 1
0 8
4
A new story starts…
N
b
K
a
s
11. Distribution of Pup1 alleles at OsPSTOL1
• New Pup1 allele found in CG14 – different from Kasalath Pup1 by 35 nt and new
primers specific of each allele designed (JIRCAS)
• Allele specific primers used to genotype 145 samples from AfricaRice
Pup 1a –Kasalath allele
K46-1fw
Total
K
C
N
U
O. glaberrima
31
1
29
1
0
O. barthii
3
0
3
0
0
O. sativa indica*
14
5
1
9
0
O. sativa japonica
19
3
14
2
0
Ksp-3rv
Duplexed
CGsp-2fw primer pairs
Upland NERICA
18
3
15
0
0
K46-1rv
Lowland NERICA*
60
13
5
43
0
Ksp-3rv
342bp
Pup 1b – CG14 allele
CGsp-2fw
Single
primers
pairs
K46-1rv
258bp
K46-1fw
C
C
K
C
C
C
C
K
K
K
K
N
K
N
K = Kasalath allele at PSTOL1
C = CG14 allele;
N = Nipponbare allele
U = unknown
* = in these groups, one sample has both K and C allele at OsPSTOL1
12. What about the other Pup1 genes?
First survey in O. glaberrima (32) showed:
K20-2 locus is absent
K46-1 revealed a different allele
K52 locus is largely present
Chin et al. (2010)
13. What about the other Pup1 genes?
First survey in O. glaberrima showed:
K20-2 locus is absent
K46-1 revealed a different allele
K52 locus is largely present
Chin et al. (2010)
???
Different sequences?
Missing genes?
14. Comparison of Pup1 genes between Kasalath and CG14
BLAST search against O. glaberrima genomic sequence for each Pup1 gene
Nipponbare
OsPupK01
OsPupK05
OsPupK20
OsPupK66
OsPupK29
INDEL
Kasalath
OsPupK01
OsPupK05
OsPupK20
OsPupK29
OsPupK43
OsPSTOL1
OsPupK59
OsPupK52
OsPupK45
OsPupK66
INDEL
CG14
OsPupK01
OsPupK05
OsPupK43
OsPSTOL1
OsPupK59
OsPupK52
OsPupK45
OsPupK66
Some of the genes present in Pup1 region (Kasalath) are missing from CG14
genome either partially or completely but the INDEL is present contrary to
Nipponbare where the INDEL is missing
15. The way forward
• Evaluation of Pup1-introgression lines developed (BC2F3) even
though Pup1 is present in the targeted varieties (except WAB515)
• Assessment of the efficiency of CG14-allele at OsPSTOL1 vs
Kasalath allele
• Development of new Pup1-introgression lines (K or C allele) in the
background of lowland rice varieties
• Use of new Pup1 donors more adapted and with better grain quality
than Kasalath in next Pup1 MABC.
upland - IAC165, IR12979, N15, N16, N18
lowland - BW348-1, Saro5, Gambiaka, NL15, NL43 (and 10 other NL)
• Search for new sources of P-deficiency tolerance (mainly PUE)
16. Acknowledgements
“A single finger can not lift a stone”
Acknowledgements to all contributors
Donor – Japan (Japan Rice Breeding Project, 2010-2014)
Collaborators – AfricaRice, JIRCAS, IRRI
Support staff
Phosphorus (P) is limiting for crop yield on > 30% of the world’s arable land World resources of inexpensive P may be depleted by 2050annual average P loss in SSA = 2.5 kg /ha (Sachez, 2012) nutrient loss cost 4 bilion USD
PSTOL1 was confirmed as a novel serine/threonine kinase gene whose overexpression in transgenic IR64 and Nipponbare significantly enhanced root growth and yield (60%)PSTOL1 regulates early crown root development and root growth, thereby enabling plants to acquire more phosphorus and other nutrients.Successfully transferred in Nipponbare, IR64, IR74 and 3 Indonesian varieties through MABC
Upland NERICAs and parents Field trials - Japan (2009, 2010) / JIRCAS - Togo (2009, 2010) / AfricaRice - Cotonou (2011) / AfricaRiceHydroponics - Cotonou (2011) / AfricaRicePopular upland varieties Field trials - Japan (2011) / JIRCAS - Ghana at SARI and Kumasi (2011) / JIRCAS - Cotonou (2011) / AfricaRice