The document reports on results from work package 4 of a project exploring genetic diversity in European apple and peach germplasm collections. Phenotypic variability was described for over 1,000 apple and peach accessions with traits related to disease susceptibility, flowering, fruit characteristics, and tree architecture. Genetic analysis of over 1,200 peach accessions identified population structure, levels of diversity, and linkage disequilibrium. Future work will analyze genetic variability and population structure in the apple collection to identify genomic regions associated with horticultural traits.
The document summarizes trends in apple varieties grown in Italy over the last decade. It finds that the main apple growing regions are South Tyrol, Trentino, Veneto, Emilia R., and Piemonte, which together account for over 60,000 hectares and 2.2 million tons of apples. The most common varieties grown are Golden Delicious, Gala, Red Delicious, and Granny Smith, though new varieties like Pink Lady, Kanzi, and Modì are increasingly being planted. Specifically in South Tyrol, where managed plantings prioritize varieties like Pink Lady, Kanzi, Modì, and Jazz, while organic orchards have a higher proportion of Golden Delicious, Gala
FruitBreedomics 1st Annual meeting 20120208 WP7 Overview of state of progressfruitbreedomics
The document provides a status update on tasks in WP7. It discusses progress made on structuring the consensus database (Task 7.1), constructing a relational database for phenotypic data on targeted traits in peach and apple (Task 7.2), and developing pipelines for genomic variation analysis and storage (Task 7.3). Expected delays involve some Tripal modules still being developed and risks that most data will be added later. Tasks to be completed at the annual meeting involve further defining the database structure and tools.
FruitBreedomics KOM 303-2011 2 intellectual property issuesfruitbreedomics
This document summarizes the governance structure and intellectual property rights for a fruit breeding consortium. It outlines the key bodies that govern the consortium including the General Assembly, Executive Committee, and Coordinator. It describes how foreground and background intellectual property is owned and managed. Access rights to intellectual property are granted for implementing the project work or using results, either freely or on fair terms. Publication of results also requires approval from intellectual property owners.
This document summarizes research from two datasets on the environmental effects and genotype-environment interaction in apple. It finds a very high site effect on traits like firmness, texture, and flavor compared to the family/genotype effect. Phenotypic correlations between sites within pairs ranged from non-significant to highly significant depending on the trait. Analysis of a subset of families found significant selection differences between sites for the same individuals. The study concludes that apple selection is highly dependent on environmental and tester effects, with rankings of cultivars differing between sites.
FruitBreedomics KOM Stakeholders meeting 31-03-2011 9 WP7 presentation and fe...fruitbreedomics
This document outlines the objectives and approach of Work Package 7 (WP7) in the Fruitbreedomics project. The goals of WP7 are to:
1) Store and manage phenotypic and genotypic data from Fruitbreedomics and other projects to facilitate studies on plant breeding, linkage disequilibrium, and marker-based analysis.
2) Develop and use tools for structural and functional genomic analysis of traits in apple and peach to help explain genotype-phenotype associations.
3) Build an integrated Fruitbreedomics database through integrating existing databases and developing additional interfaces and analysis tools.
This document summarizes research exploring phenotypic and genetic diversity in peach. Over 1580 accessions were studied across multiple locations in Europe and China. Phenotypic data was collected over several years and correlated between locations. Genetic analysis using a 9K SNP chip identified 473 clones and grouped accessions into occidental breeding, occidental non-breeding, oriental, and admixed categories. Genome-wide association studies identified major genes and QTLs associated with traits like acidity, melting behavior, and fruit flesh color.
FruitBreedomics KOM Stakeholders meeting 31-03-2011 11 WP1 breeders workshopfruitbreedomics
The document summarizes the agenda and organization of the WP1 workshop. It introduces the 5 tasks of WP1 and their leaders, including task 1.2 on developing SNP markers linked to selected traits/loci in apple and peach, led by Andrea Patocchi and Thierry Pascal. It provides an overview of the approaches and methodologies that will be used in tasks 1.1 on breeding strategies, 1.2 on SNP development, 1.3 on pilot studies, 1.4 on genotyping pipelines, and 1.5 on specifying a breeder interface. The partners involved in each task and their responsibilities are also outlined.
The document summarizes trends in apple varieties grown in Italy over the last decade. It finds that the main apple growing regions are South Tyrol, Trentino, Veneto, Emilia R., and Piemonte, which together account for over 60,000 hectares and 2.2 million tons of apples. The most common varieties grown are Golden Delicious, Gala, Red Delicious, and Granny Smith, though new varieties like Pink Lady, Kanzi, and Modì are increasingly being planted. Specifically in South Tyrol, where managed plantings prioritize varieties like Pink Lady, Kanzi, Modì, and Jazz, while organic orchards have a higher proportion of Golden Delicious, Gala
FruitBreedomics 1st Annual meeting 20120208 WP7 Overview of state of progressfruitbreedomics
The document provides a status update on tasks in WP7. It discusses progress made on structuring the consensus database (Task 7.1), constructing a relational database for phenotypic data on targeted traits in peach and apple (Task 7.2), and developing pipelines for genomic variation analysis and storage (Task 7.3). Expected delays involve some Tripal modules still being developed and risks that most data will be added later. Tasks to be completed at the annual meeting involve further defining the database structure and tools.
FruitBreedomics KOM 303-2011 2 intellectual property issuesfruitbreedomics
This document summarizes the governance structure and intellectual property rights for a fruit breeding consortium. It outlines the key bodies that govern the consortium including the General Assembly, Executive Committee, and Coordinator. It describes how foreground and background intellectual property is owned and managed. Access rights to intellectual property are granted for implementing the project work or using results, either freely or on fair terms. Publication of results also requires approval from intellectual property owners.
This document summarizes research from two datasets on the environmental effects and genotype-environment interaction in apple. It finds a very high site effect on traits like firmness, texture, and flavor compared to the family/genotype effect. Phenotypic correlations between sites within pairs ranged from non-significant to highly significant depending on the trait. Analysis of a subset of families found significant selection differences between sites for the same individuals. The study concludes that apple selection is highly dependent on environmental and tester effects, with rankings of cultivars differing between sites.
FruitBreedomics KOM Stakeholders meeting 31-03-2011 9 WP7 presentation and fe...fruitbreedomics
This document outlines the objectives and approach of Work Package 7 (WP7) in the Fruitbreedomics project. The goals of WP7 are to:
1) Store and manage phenotypic and genotypic data from Fruitbreedomics and other projects to facilitate studies on plant breeding, linkage disequilibrium, and marker-based analysis.
2) Develop and use tools for structural and functional genomic analysis of traits in apple and peach to help explain genotype-phenotype associations.
3) Build an integrated Fruitbreedomics database through integrating existing databases and developing additional interfaces and analysis tools.
This document summarizes research exploring phenotypic and genetic diversity in peach. Over 1580 accessions were studied across multiple locations in Europe and China. Phenotypic data was collected over several years and correlated between locations. Genetic analysis using a 9K SNP chip identified 473 clones and grouped accessions into occidental breeding, occidental non-breeding, oriental, and admixed categories. Genome-wide association studies identified major genes and QTLs associated with traits like acidity, melting behavior, and fruit flesh color.
FruitBreedomics KOM Stakeholders meeting 31-03-2011 11 WP1 breeders workshopfruitbreedomics
The document summarizes the agenda and organization of the WP1 workshop. It introduces the 5 tasks of WP1 and their leaders, including task 1.2 on developing SNP markers linked to selected traits/loci in apple and peach, led by Andrea Patocchi and Thierry Pascal. It provides an overview of the approaches and methodologies that will be used in tasks 1.1 on breeding strategies, 1.2 on SNP development, 1.3 on pilot studies, 1.4 on genotyping pipelines, and 1.5 on specifying a breeder interface. The partners involved in each task and their responsibilities are also outlined.
This document summarizes pilot studies on peach conducted for the FruitBreedomics project. The objective was to verify the efficiency of MAS selection by screening 1500 trees from public and private partners for quality and resistance traits using SNP markers. Traits like flesh color, shape, acidity level, and resistance to aphids and powdery mildew were studied. Genotyping was performed using KASP technology. Results showed good prediction efficiency for resistance to green peach aphid and several quality traits, demonstrating the effectiveness of MAS. Further analysis of data and development of additional markers is needed to finalize the approach.
Harvesting practices for special market purposePawan Nagar
1. Harvesting is the act of gathering a ripe crop from the fields using various manual and mechanical methods depending on the crop.
2. Maturity indices help determine the optimal time to harvest crops to ensure acceptable quality for consumers. Indices include factors like color, firmness, sugar and acid content, and days after flowering.
3. The presentation discusses various maturity indices for fruits like mango, banana, citrus and vegetables and the importance of harvesting at the proper maturity stage.
METABOLIC PROFILING OF RIPENING STRAWBERRY (Fragaria x ananassa)Ashlyn Wedde
Strawberries were analyzed to understand how metabolite profiles differ between cultivars and tissue types during ripening. Four strawberry cultivars (Festival, Sensation, Winterstar, Radiance) had receptacle and achene tissue separated at six ripening stages, from small green to ripe. Metabolites were investigated using GC-MS and UPLC-qTOF-MS profiling. Correlation analysis showed cluster patterns between metabolite profiles in cultivars and tissues. Certain metabolites, like ellagic acid, differed significantly between cultivars and tissues throughout ripening. Understanding these metabolic differences provides insights into fruit quality traits and health benefits between strawberry cultivars.
1) The study analyzed the morphological and molecular characteristics of 10 Iranian olive cultivars to clarify inconsistencies in their classification.
2) Morphological analysis revealed homonyms and mislabeling among 5 cultivars and led to reclassifying the 10 cultivars into 27 new groups.
3) Genetic analysis using RAPD markers on a subset of samples supported some aspects of the new morphological classification, helping to validate it.
This study characterized 19 pomegranate genotypes from the Coruh Valley in Turkey using AFLP molecular markers. Four AFLP primer combinations generated a total of 297 fragments, of which 213 (73%) were polymorphic. Cluster analysis grouped the genotypes into two major clusters. Most fruit characteristics varied within clusters, indicating that molecular characterization is needed to accurately assess relationships among pomegranate genotypes. The study found that AFLP markers can effectively characterize genetic diversity in pomegranate.
The document summarizes the results and plans of Work Package 3 (WP3) on pedigree-based analyses (PBA) in peach and apple breeding programs. Key achievements include improving the FlexQTL software to handle high densities of SNP markers, developing scripts to prepare input files, and adding visualization tools. WP3 discovered QTL for traits like flowering time and fruit quality in peach and plans to extend analyses to additional populations. For apple, WP3 constructed a dense SNP map and plans an integrated map using multiple families to identify QTL for disease resistance and other traits. Main challenges are normalizing phenotypic data across locations and constructing SNP haplotypes in peach, and developing an integrated genetic map for apple QTL analyses.
Lecture 3: Fruits and Vegetables HarvestingKarl Obispo
This document discusses harvesting of fruits and vegetables. It begins with learning objectives related to postharvest procedures, maturity indices, and harvesting practices. It then outlines topics to be covered including postharvest handling procedures, defining maturity indices, importance of maturity indices, differences between physiological and horticultural maturity, and harvesting practices for common fruits and vegetables. The document discusses factors that determine optimum maturity for harvesting, different types of maturity, maturity indices used for various fruits and vegetables, and methods for manual and mechanical harvesting. It stresses the importance of harvesting at proper maturity to ensure quality and storage life.
This document provides an acknowledgement and thanks to various individuals who provided support and guidance during the completion of an assignment. It expresses gratitude to professors for their mentorship and support. Thanks are also given to friends for their assistance. Finally, the document acknowledges the support of family members, especially parents, who provided motivation, encouragement, patience and served as the backbone throughout the work.
This document discusses breeding for quality traits in chilli. Quality in chilli is determined by pungency, colour, dry matter content, and vitamin C content. Breeding objectives for quality vary depending on the intended market type. Conventional breeding methods are ineffective for complex traits like quality. Recurrent selection is recommended to improve quality while avoiding negative effects on yield. Quality traits have various modes of inheritance, with some traits like colour controlled by several genes. Breeding objectives aim to develop varieties suited for different markets based on their quality trait requirements.
This document summarizes a project to improve sorghum productivity in Mali through an integrated Marker-Assisted Recurrent Selection (MARS) approach. The project phenotyped multiple traits across multiple environments to identify favorable alleles and define ideal genotypes. It conducted several breeding cycles and genotyped populations to detect QTLs. The main products were improved sorghum material and capacity building activities. Key lessons included validating MARS for African sorghum breeding and considering different trait combinations for varying environments.
The document discusses factors that contribute to grape quality and maturity, including climate, soil type, and vineyard management practices. It notes that seasonal variability can limit efforts to manage quality, and that soil variability within vineyards also inhibits uniform quality. The key is to understand sources of variability and determine which factors can be effectively managed to improve fruit quality through long-term planning and short-term practices. New technologies in soil mapping can help vineyards proactively assess spatial variability and develop targeted management strategies.
The Crop Ontology is a controlled vocabulary for plant breeding data that aims to standardize terminology across crops and languages. It provides definitions and relationships between trait terms to improve data sharing and analysis. The ontology is being developed collaboratively by crop experts and is mapped to other related ontologies. It is powering various crop databases and tools to allow interoperability of phenotypic and genetic data.
14 Barbara Laddomada - Genetic Variability and association mapping for phenol...CNR - Ispa
1. The document summarizes research on phenolic acids in tetraploid wheat. It finds significant genetic variability and heritability for phenolic acid content among 112 wheat accessions.
2. Association mapping identified 29 SNPs associated with individual phenolic acids and total content that can be used for wheat breeding.
3. Pasta supplemented with aqueous extracts from wheat bran containing phenolic acids had higher phenolic content and antioxidant activity than control pasta.
Advances in breeding of Apple and pear.pptxTajamul Wani
1. The document summarizes breeding methods for apple and pear, including conventional methods like plant introduction, clonal selection, and hybridization, as well as newer non-conventional methods like mutation breeding, genetic transformation, marker-assisted selection, and CRISPR/Cas9 technology.
2. Important breeding objectives for apple include early and regular bearing, good fruit quality and storage, dwarfness, and disease/pest resistance. Important pear breeding objectives are high and regular bearing, excellent fruit quality, disease resistance, and dwarfness.
3. Newer transgenic technologies like CRISPR/Cas9 hold promise for quickly introducing economically important traits to improve existing cultivars for apple and pear breeding.
Phenotyping texture and aroma wp5 unravel the complexity of apple aroma by pt...fruitbreedomics
The document discusses research using PTR-ToF-MS (Proton Transfer Reaction-Time of Flight-Mass Spectrometry) to analyze the volatile organic compound (VOC) profiles of apples. Key points include:
- PTR-ToF-MS provides a non-invasive way to monitor VOCs, which are important for sensory qualities like aroma and flavor.
- Research aims to understand the genetic, physiological and metabolic traits related to apple quality, ripening, and storage through VOC fingerprinting and analysis.
- Studies found 1-MCP post-harvest treatment reduces certain VOCs and may help prevent superficial scald disorder by altering VOC profiles in the skin versus flesh.
- A genome-
The document summarizes the development of new apple rootstocks through a breeding program. It discusses:
- The program was initiated in 1967 by Drs. Cummins and Aldwinckle at Cornell University to develop disease resistant and high yielding rootstocks.
- Over 2,500 new rootstocks are currently in development through breeding and selection. Traits of focus include disease resistance, drought tolerance, cold tolerance and yield efficiency.
- Rootstock development involves multiple stages from parent selection and crossing, to disease screening, field trials and commercial production. Molecular tools are now used to aid selection.
- International collaboration has expanded apple rootstock breeding programs globally. Over 100 new rootstocks have been developed and distributed
Here is a summary of the key points from the introduction:
- Genetic diversity in germplasm resources is essential for future crop improvement through breeding.
- Maintaining a wide range of genetic diversity is important for present and future breeding programs, as well as for research, teaching and public outreach.
- Effective conservation strategies are required to ensure diverse germplasm resources remain available over time.
- Many major apple breeding programs have been based on a relatively small number of successful cultivars.
Msc. synopsis OAT Genetic diversity and molecular markersArushi Arora
This document outlines a proposed study on genetic diversity analysis in oat (Avena sativa) varieties using agro-morphological and molecular markers. The study will characterize 56 indigenous and exotic oat genotypes, along with 4 checks, using agro-morphological traits like flowering time, plant height, and yield components. Molecular characterization will be done using SSR markers to analyze diversity. Statistical analysis will include ANOVA, variability parameters, correlation, path analysis, genetic divergence, and principal component analysis. The research aims to assess genetic diversity in oat genotypes and identify varieties suitable for forage, seed yield, and related traits.
tomato fruit show wide phenotypic diversity but fruit developmental gene show...Kamal Tyagi
- Researchers analyzed 127 tomato accessions from 20 countries and found extensive diversity in fruit traits, clustering them into 9 classes based on traits like soluble solids, carotenoids, ripening index, weight, and shape.
- They screened 10 genes involved in plant development for SNPs using EcoTILLING and found 36 non-synonymous and 18 synonymous changes, identifying 28 haplotypes. However, genetic diversity in the fruit development genes was low compared to the wide phenotypic diversity observed.
- While fruit shape was found to be a complex trait influenced by multiple factors, 100% variance between round and flat fruits was explained by one discriminant function. The study indicates potential to further exploit the morphological and genetic diversity in the
FQ-haplotyper is an R script that analyzes haplotype data from FlexQTL and assigns haplotype alleles. It considers each haploblock separately in half-sibling families, imputing missing SNP data or removing conflicting data based on Mendelian inheritance. The output includes files for further analysis and visualization of original and imputed haplotype alleles in pedigrees.
This document summarizes pilot studies on peach conducted for the FruitBreedomics project. The objective was to verify the efficiency of MAS selection by screening 1500 trees from public and private partners for quality and resistance traits using SNP markers. Traits like flesh color, shape, acidity level, and resistance to aphids and powdery mildew were studied. Genotyping was performed using KASP technology. Results showed good prediction efficiency for resistance to green peach aphid and several quality traits, demonstrating the effectiveness of MAS. Further analysis of data and development of additional markers is needed to finalize the approach.
Harvesting practices for special market purposePawan Nagar
1. Harvesting is the act of gathering a ripe crop from the fields using various manual and mechanical methods depending on the crop.
2. Maturity indices help determine the optimal time to harvest crops to ensure acceptable quality for consumers. Indices include factors like color, firmness, sugar and acid content, and days after flowering.
3. The presentation discusses various maturity indices for fruits like mango, banana, citrus and vegetables and the importance of harvesting at the proper maturity stage.
METABOLIC PROFILING OF RIPENING STRAWBERRY (Fragaria x ananassa)Ashlyn Wedde
Strawberries were analyzed to understand how metabolite profiles differ between cultivars and tissue types during ripening. Four strawberry cultivars (Festival, Sensation, Winterstar, Radiance) had receptacle and achene tissue separated at six ripening stages, from small green to ripe. Metabolites were investigated using GC-MS and UPLC-qTOF-MS profiling. Correlation analysis showed cluster patterns between metabolite profiles in cultivars and tissues. Certain metabolites, like ellagic acid, differed significantly between cultivars and tissues throughout ripening. Understanding these metabolic differences provides insights into fruit quality traits and health benefits between strawberry cultivars.
1) The study analyzed the morphological and molecular characteristics of 10 Iranian olive cultivars to clarify inconsistencies in their classification.
2) Morphological analysis revealed homonyms and mislabeling among 5 cultivars and led to reclassifying the 10 cultivars into 27 new groups.
3) Genetic analysis using RAPD markers on a subset of samples supported some aspects of the new morphological classification, helping to validate it.
This study characterized 19 pomegranate genotypes from the Coruh Valley in Turkey using AFLP molecular markers. Four AFLP primer combinations generated a total of 297 fragments, of which 213 (73%) were polymorphic. Cluster analysis grouped the genotypes into two major clusters. Most fruit characteristics varied within clusters, indicating that molecular characterization is needed to accurately assess relationships among pomegranate genotypes. The study found that AFLP markers can effectively characterize genetic diversity in pomegranate.
The document summarizes the results and plans of Work Package 3 (WP3) on pedigree-based analyses (PBA) in peach and apple breeding programs. Key achievements include improving the FlexQTL software to handle high densities of SNP markers, developing scripts to prepare input files, and adding visualization tools. WP3 discovered QTL for traits like flowering time and fruit quality in peach and plans to extend analyses to additional populations. For apple, WP3 constructed a dense SNP map and plans an integrated map using multiple families to identify QTL for disease resistance and other traits. Main challenges are normalizing phenotypic data across locations and constructing SNP haplotypes in peach, and developing an integrated genetic map for apple QTL analyses.
Lecture 3: Fruits and Vegetables HarvestingKarl Obispo
This document discusses harvesting of fruits and vegetables. It begins with learning objectives related to postharvest procedures, maturity indices, and harvesting practices. It then outlines topics to be covered including postharvest handling procedures, defining maturity indices, importance of maturity indices, differences between physiological and horticultural maturity, and harvesting practices for common fruits and vegetables. The document discusses factors that determine optimum maturity for harvesting, different types of maturity, maturity indices used for various fruits and vegetables, and methods for manual and mechanical harvesting. It stresses the importance of harvesting at proper maturity to ensure quality and storage life.
This document provides an acknowledgement and thanks to various individuals who provided support and guidance during the completion of an assignment. It expresses gratitude to professors for their mentorship and support. Thanks are also given to friends for their assistance. Finally, the document acknowledges the support of family members, especially parents, who provided motivation, encouragement, patience and served as the backbone throughout the work.
This document discusses breeding for quality traits in chilli. Quality in chilli is determined by pungency, colour, dry matter content, and vitamin C content. Breeding objectives for quality vary depending on the intended market type. Conventional breeding methods are ineffective for complex traits like quality. Recurrent selection is recommended to improve quality while avoiding negative effects on yield. Quality traits have various modes of inheritance, with some traits like colour controlled by several genes. Breeding objectives aim to develop varieties suited for different markets based on their quality trait requirements.
This document summarizes a project to improve sorghum productivity in Mali through an integrated Marker-Assisted Recurrent Selection (MARS) approach. The project phenotyped multiple traits across multiple environments to identify favorable alleles and define ideal genotypes. It conducted several breeding cycles and genotyped populations to detect QTLs. The main products were improved sorghum material and capacity building activities. Key lessons included validating MARS for African sorghum breeding and considering different trait combinations for varying environments.
The document discusses factors that contribute to grape quality and maturity, including climate, soil type, and vineyard management practices. It notes that seasonal variability can limit efforts to manage quality, and that soil variability within vineyards also inhibits uniform quality. The key is to understand sources of variability and determine which factors can be effectively managed to improve fruit quality through long-term planning and short-term practices. New technologies in soil mapping can help vineyards proactively assess spatial variability and develop targeted management strategies.
The Crop Ontology is a controlled vocabulary for plant breeding data that aims to standardize terminology across crops and languages. It provides definitions and relationships between trait terms to improve data sharing and analysis. The ontology is being developed collaboratively by crop experts and is mapped to other related ontologies. It is powering various crop databases and tools to allow interoperability of phenotypic and genetic data.
14 Barbara Laddomada - Genetic Variability and association mapping for phenol...CNR - Ispa
1. The document summarizes research on phenolic acids in tetraploid wheat. It finds significant genetic variability and heritability for phenolic acid content among 112 wheat accessions.
2. Association mapping identified 29 SNPs associated with individual phenolic acids and total content that can be used for wheat breeding.
3. Pasta supplemented with aqueous extracts from wheat bran containing phenolic acids had higher phenolic content and antioxidant activity than control pasta.
Advances in breeding of Apple and pear.pptxTajamul Wani
1. The document summarizes breeding methods for apple and pear, including conventional methods like plant introduction, clonal selection, and hybridization, as well as newer non-conventional methods like mutation breeding, genetic transformation, marker-assisted selection, and CRISPR/Cas9 technology.
2. Important breeding objectives for apple include early and regular bearing, good fruit quality and storage, dwarfness, and disease/pest resistance. Important pear breeding objectives are high and regular bearing, excellent fruit quality, disease resistance, and dwarfness.
3. Newer transgenic technologies like CRISPR/Cas9 hold promise for quickly introducing economically important traits to improve existing cultivars for apple and pear breeding.
Phenotyping texture and aroma wp5 unravel the complexity of apple aroma by pt...fruitbreedomics
The document discusses research using PTR-ToF-MS (Proton Transfer Reaction-Time of Flight-Mass Spectrometry) to analyze the volatile organic compound (VOC) profiles of apples. Key points include:
- PTR-ToF-MS provides a non-invasive way to monitor VOCs, which are important for sensory qualities like aroma and flavor.
- Research aims to understand the genetic, physiological and metabolic traits related to apple quality, ripening, and storage through VOC fingerprinting and analysis.
- Studies found 1-MCP post-harvest treatment reduces certain VOCs and may help prevent superficial scald disorder by altering VOC profiles in the skin versus flesh.
- A genome-
The document summarizes the development of new apple rootstocks through a breeding program. It discusses:
- The program was initiated in 1967 by Drs. Cummins and Aldwinckle at Cornell University to develop disease resistant and high yielding rootstocks.
- Over 2,500 new rootstocks are currently in development through breeding and selection. Traits of focus include disease resistance, drought tolerance, cold tolerance and yield efficiency.
- Rootstock development involves multiple stages from parent selection and crossing, to disease screening, field trials and commercial production. Molecular tools are now used to aid selection.
- International collaboration has expanded apple rootstock breeding programs globally. Over 100 new rootstocks have been developed and distributed
Here is a summary of the key points from the introduction:
- Genetic diversity in germplasm resources is essential for future crop improvement through breeding.
- Maintaining a wide range of genetic diversity is important for present and future breeding programs, as well as for research, teaching and public outreach.
- Effective conservation strategies are required to ensure diverse germplasm resources remain available over time.
- Many major apple breeding programs have been based on a relatively small number of successful cultivars.
Msc. synopsis OAT Genetic diversity and molecular markersArushi Arora
This document outlines a proposed study on genetic diversity analysis in oat (Avena sativa) varieties using agro-morphological and molecular markers. The study will characterize 56 indigenous and exotic oat genotypes, along with 4 checks, using agro-morphological traits like flowering time, plant height, and yield components. Molecular characterization will be done using SSR markers to analyze diversity. Statistical analysis will include ANOVA, variability parameters, correlation, path analysis, genetic divergence, and principal component analysis. The research aims to assess genetic diversity in oat genotypes and identify varieties suitable for forage, seed yield, and related traits.
tomato fruit show wide phenotypic diversity but fruit developmental gene show...Kamal Tyagi
- Researchers analyzed 127 tomato accessions from 20 countries and found extensive diversity in fruit traits, clustering them into 9 classes based on traits like soluble solids, carotenoids, ripening index, weight, and shape.
- They screened 10 genes involved in plant development for SNPs using EcoTILLING and found 36 non-synonymous and 18 synonymous changes, identifying 28 haplotypes. However, genetic diversity in the fruit development genes was low compared to the wide phenotypic diversity observed.
- While fruit shape was found to be a complex trait influenced by multiple factors, 100% variance between round and flat fruits was explained by one discriminant function. The study indicates potential to further exploit the morphological and genetic diversity in the
Similar to 05 wp4 progresses&results-20130221 (20)
FQ-haplotyper is an R script that analyzes haplotype data from FlexQTL and assigns haplotype alleles. It considers each haploblock separately in half-sibling families, imputing missing SNP data or removing conflicting data based on Mendelian inheritance. The output includes files for further analysis and visualization of original and imputed haplotype alleles in pedigrees.
This document discusses the costs of using marker-assisted selection (MAS) in a peach breeding program run by IRTA-FruitFutur-ASF. It notes that MAS has been used routinely since 2012 to select for traits like flat fruit shape and acidity. The costs of MAS are about 3.5 euros per tree for DNA extraction, marker genotyping, and analysis. In comparison, traditional phenotypic selection costs about 6.7 euros per tree when considering costs of planting, maintaining trees in the orchard, evaluation, and elimination of trees from the orchard. An example is provided showing that for genotyping 1,000 trees using MAS, the total cost is around 7,272 euros, lower than the
FruitBreedomics MAB Services offers integrated consulting services to small fruit breeding companies to help overcome limitations in genetics expertise and laboratory facilities. The initial strategy of pilot studies and training was deemed insufficient, so FruitBreedomics now provides commercial consultancy services using their own data and expertise, with an approach that includes on-site visits to help clients.
This document summarizes apple and peach traits that have genetic markers available or in development for marker-assisted breeding. For apples, markers are available for resistances to scab, mildew, fire blight, and woolly apple aphid. Markers are also available or being developed for traits like fruit texture, acidity, sweetness, and color. For peaches, markers have been applied for resistance to green peach aphid and powdery mildew, as well as traits like flesh color, pubescence, and melting/non-melting flesh. Additional traits are still in development for both crops.
The document discusses selection for sub-acid taste and flat shape in peaches. It identifies single nucleotide polymorphisms (SNPs) associated with these traits: sub-acid taste is associated with one SNP; flat shape is associated with a haplotype of three highly linked SNPs. The SNPs could be used for marker-assisted breeding to more efficiently select for sub-acid taste and flat fruit shape, which are desirable traits for consumers.
The document discusses marker-assisted breeding and the services provided by the Sequencing and Genotyping Platform. It outlines the steps in marker-assisted selection, from laying out seedlings and collecting samples to running analyses. It also lists the facilities and equipment available, including robotic platforms for liquid handling and DNA/RNA extraction, real-time PCR systems, capillary sequencers, and Illumina platforms for high-throughput genotyping. The platform provides support for marker-assisted breeding programs through services like whole genome sequencing, targeted resequencing, and protocol development for next-generation sequencing applications.
This document summarizes a technical session on pyramiding scab and mildew resistance genes in apple breeding at Agroscope. The objective is to cross parent lines with different resistance genes to combine two or more genes against the same pathogen. Two crosses were made between parent lines containing different resistance genes for apple scab (Rvi6 and Rvi2) and powdery mildew (Pl2). SNP markers were used to analyze the crosses and determine which resistance genes were passed to the progeny. The document demonstrates using Excel to interpret the results of the marker analysis and determine which resistance genes were combined in the progeny for future disease resistance.
This document discusses the use of markers for parent selection in peach breeding and production. It covers 1) using markers to characterize relationships between parents and for cross planning to maximize genetic distance and heterozygosity, 2) using markers for seedling selection, and 3) using markers to assist in introgressing traits. It also discusses using markers for breeder's rights protection by creating molecular fingerprints of varieties.
The document summarizes a technical session on fruit tree sampling procedures for genomic analysis. It describes using a 96-well format for efficiency and two coding systems for identifying individual plants without labeling - positional coding using the layout of pots in plates and a combination number system. The demonstration showed efficient procedures for puncturing leaves and expediting plates for analysis, though the whole process took more time than expected. Costs are relatively low compared to DNA extraction and analysis, requiring close work with partner companies.
This document provides information about Centro Innovazione Varietale (CIV), including:
- CIV is an Italian company founded in 1983 aiming to develop new plant varieties through breeding and produce certified propagation materials.
- CIV operates on 52 hectares of land for variety trials, production of certified buds and seedlings, and strawberry nurseries.
- In addition to its own breeding programs, CIV participates in variety development programs with organizations around the world.
- CIV's portfolio includes over 30 strawberry, 12 apple, and 6 peach/nectarine varieties it has developed and licensed in over 27 countries.
This document provides a summary of a training seminar on the use of molecular markers in apple and peach breeding. The one-day seminar will cover topics including sampling procedures, utilizing markers for parental selection and hybrid selection in various breeding programs, markers available for different traits, and cost comparisons. Speakers will discuss examples from breeding programs at IRTA, Agroscope, FEM, and INRA. The afternoon will focus on the FruitBreedomics molecular breeding services and interface. The seminar aims to demonstrate how molecular markers can help breeders in tasks such as selecting for disease resistance, fruit quality traits, and verifying pedigrees.
The document describes Fruitbreedomics, a project that developed a database and breeding interface to improve fruit breeding programs. It collected large amounts of phenotype and genotype data from apple and peach varieties, including traits, markers, and resequencing data. It provides online tools for users to explore the data, including a JBrowse genome browser, breeder's interface to design crosses, and LDExplorer for linkage disequilibrium analysis. The goal is to bridge the gap between genetic research and breeding applications.
The document describes Pedimap software, which is a tool for visually presenting pedigree relationships. It can be used to clarify genetic structures in breeding germplasm and inheritance patterns. The software allows input of pedigree data along with optional phenotypic trait or marker genotype data. It provides different view types, including overviews, names only, names with phenotypic values, and names with marker genotypes. Pedimap is freely available and helps breeding programs validate parentage, true-to-type status of germplasm, and understand the origin and introgression of chromosome segments.
This document summarizes the work of the FruitBreedomics project WP2 on developing apple and peach pre-breeding material. For apples, the objectives were to introduce resistance to scab, mildew and fire blight through marker-assisted breeding in Switzerland and Germany. Selected progenies combined multiple resistance genes. For peaches, the focus was on resistance to powdery mildew and brown rot through conventional breeding in Italy, with some progenies combining both resistances. Marker-assisted breeding in France targeted resistance to multiple pests and diseases. The availability of pre-breeding material from different populations was also outlined.
This document summarizes initial results from modeling genome-wide predictions in peach. Eleven peach populations from four sites were genotyped and phenotyped for traits like fruit weight, sugar content, and acidity. Genotypes were imputed and a repeatability model was used to estimate heritability and predict trait values based on genomic relationships. Preliminary results showed variable predictive ability across populations and traits. Next steps include standardizing the data analysis and interpreting the results to draft a paper on genomic predictions in peach breeding.
This document summarizes a two-year pilot study on genomic selection in apple breeding. The study involved genotyping and phenotyping a training population of 20 full-sib families and 5 application families. Genomic prediction models were developed and used to calculate genomic estimated breeding values (GEBV) for traits like fruit quality, size, and disease resistance. The accuracy of genomic prediction varied among traits from poor to moderate, and selection differentials based on GEBV were significant for several traits. The study provides a proof of concept for genomic selection in apple breeding but highlights the need for further research on prediction accuracy across multiple years and environments.
This document summarizes pilot studies on using molecular markers to assist breeding of new apple cultivars with improved disease resistance and fruit quality traits. Two crosses were made in 2011 and progeny were screened using SNP markers for scab, mildew resistance and fruit quality. Over 1000 seedlings were analyzed, and the best 176 for cross 1 and 100 for cross 2 were selected for further evaluation based on their molecular profiles. The studies demonstrated both benefits and challenges of marker-assisted breeding in apple.
This document summarizes a genome wide association study (GWAS) of two phenology traits, flowering period and picking date, in apple. The study used 1168 apple cultivars genotyped with an Affymetrix Axiom_Apple480k SNP array. Heritability estimates for the phenology traits were moderate to high. GWAS models accounting for population structure and kinship identified several significant SNPs associated with flowering period on chromosomes 9, 11, and 12. For picking date, significant SNPs were identified on chromosome 3. Some of the identified genomic regions overlapped with previous QTL mapping studies of the same traits, validating the GWAS approach. The study provides new markers that can be used for apple breeding
This document summarizes research that used pedigree-based analysis (PBA) to identify quantitative trait loci (QTLs) in peach using data from multiple research centers. PBA was applied to 1,472 offspring from 18 crossing populations genotyped with 9K SNP markers and phenotyped for 24 traits. Several significant QTLs were detected for ripening date, sugar content, blush percentage, and acidity. The QTLs identified new alleles and genomic regions associated with these economically important traits. Integrating data from diverse populations allowed for discovery of more QTLs than previous studies using single progenies.
5th LF Energy Power Grid Model Meet-up SlidesDanBrown980551
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
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
How information systems are built or acquired puts information, which is what they should be about, in a secondary place. Our language adapted accordingly, and we no longer talk about information systems but applications. Applications evolved in a way to break data into diverse fragments, tightly coupled with applications and expensive to integrate. The result is technical debt, which is re-paid by taking even bigger "loans", resulting in an ever-increasing technical debt. Software engineering and procurement practices work in sync with market forces to maintain this trend. This talk demonstrates how natural this situation is. The question is: can something be done to reverse the trend?
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
AppSec PNW: Android and iOS Application Security with MobSFAjin Abraham
Mobile Security Framework - MobSF is a free and open source automated mobile application security testing environment designed to help security engineers, researchers, developers, and penetration testers to identify security vulnerabilities, malicious behaviours and privacy concerns in mobile applications using static and dynamic analysis. It supports all the popular mobile application binaries and source code formats built for Android and iOS devices. In addition to automated security assessment, it also offers an interactive testing environment to build and execute scenario based test/fuzz cases against the application.
This talk covers:
Using MobSF for static analysis of mobile applications.
Interactive dynamic security assessment of Android and iOS applications.
Solving Mobile app CTF challenges.
Reverse engineering and runtime analysis of Mobile malware.
How to shift left and integrate MobSF/mobsfscan SAST and DAST in your build pipeline.
Introduction of Cybersecurity with OSS at Code Europe 2024Hiroshi SHIBATA
I develop the Ruby programming language, RubyGems, and Bundler, which are package managers for Ruby. Today, I will introduce how to enhance the security of your application using open-source software (OSS) examples from Ruby and RubyGems.
The first topic is CVE (Common Vulnerabilities and Exposures). I have published CVEs many times. But what exactly is a CVE? I'll provide a basic understanding of CVEs and explain how to detect and handle vulnerabilities in OSS.
Next, let's discuss package managers. Package managers play a critical role in the OSS ecosystem. I'll explain how to manage library dependencies in your application.
I'll share insights into how the Ruby and RubyGems core team works to keep our ecosystem safe. By the end of this talk, you'll have a better understanding of how to safeguard your code.
"Frontline Battles with DDoS: Best practices and Lessons Learned", Igor IvaniukFwdays
At this talk we will discuss DDoS protection tools and best practices, discuss network architectures and what AWS has to offer. Also, we will look into one of the largest DDoS attacks on Ukrainian infrastructure that happened in February 2022. We'll see, what techniques helped to keep the web resources available for Ukrainians and how AWS improved DDoS protection for all customers based on Ukraine experience
Conversational agents, or chatbots, are increasingly used to access all sorts of services using natural language. While open-domain chatbots - like ChatGPT - can converse on any topic, task-oriented chatbots - the focus of this paper - are designed for specific tasks, like booking a flight, obtaining customer support, or setting an appointment. Like any other software, task-oriented chatbots need to be properly tested, usually by defining and executing test scenarios (i.e., sequences of user-chatbot interactions). However, there is currently a lack of methods to quantify the completeness and strength of such test scenarios, which can lead to low-quality tests, and hence to buggy chatbots.
To fill this gap, we propose adapting mutation testing (MuT) for task-oriented chatbots. To this end, we introduce a set of mutation operators that emulate faults in chatbot designs, an architecture that enables MuT on chatbots built using heterogeneous technologies, and a practical realisation as an Eclipse plugin. Moreover, we evaluate the applicability, effectiveness and efficiency of our approach on open-source chatbots, with promising results.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/how-axelera-ai-uses-digital-compute-in-memory-to-deliver-fast-and-energy-efficient-computer-vision-a-presentation-from-axelera-ai/
Bram Verhoef, Head of Machine Learning at Axelera AI, presents the “How Axelera AI Uses Digital Compute-in-memory to Deliver Fast and Energy-efficient Computer Vision” tutorial at the May 2024 Embedded Vision Summit.
As artificial intelligence inference transitions from cloud environments to edge locations, computer vision applications achieve heightened responsiveness, reliability and privacy. This migration, however, introduces the challenge of operating within the stringent confines of resource constraints typical at the edge, including small form factors, low energy budgets and diminished memory and computational capacities. Axelera AI addresses these challenges through an innovative approach of performing digital computations within memory itself. This technique facilitates the realization of high-performance, energy-efficient and cost-effective computer vision capabilities at the thin and thick edge, extending the frontier of what is achievable with current technologies.
In this presentation, Verhoef unveils his company’s pioneering chip technology and demonstrates its capacity to deliver exceptional frames-per-second performance across a range of standard computer vision networks typical of applications in security, surveillance and the industrial sector. This shows that advanced computer vision can be accessible and efficient, even at the very edge of our technological ecosystem.
[OReilly Superstream] Occupy the Space: A grassroots guide to engineering (an...Jason Yip
The typical problem in product engineering is not bad strategy, so much as “no strategy”. This leads to confusion, lack of motivation, and incoherent action. The next time you look for a strategy and find an empty space, instead of waiting for it to be filled, I will show you how to fill it in yourself. If you’re wrong, it forces a correction. If you’re right, it helps create focus. I’ll share how I’ve approached this in the past, both what works and lessons for what didn’t work so well.
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
Skybuffer SAM4U tool for SAP license adoptionTatiana Kojar
Manage and optimize your license adoption and consumption with SAM4U, an SAP free customer software asset management tool.
SAM4U, an SAP complimentary software asset management tool for customers, delivers a detailed and well-structured overview of license inventory and usage with a user-friendly interface. We offer a hosted, cost-effective, and performance-optimized SAM4U setup in the Skybuffer Cloud environment. You retain ownership of the system and data, while we manage the ABAP 7.58 infrastructure, ensuring fixed Total Cost of Ownership (TCO) and exceptional services through the SAP Fiori interface.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/temporal-event-neural-networks-a-more-efficient-alternative-to-the-transformer-a-presentation-from-brainchip/
Chris Jones, Director of Product Management at BrainChip , presents the “Temporal Event Neural Networks: A More Efficient Alternative to the Transformer” tutorial at the May 2024 Embedded Vision Summit.
The expansion of AI services necessitates enhanced computational capabilities on edge devices. Temporal Event Neural Networks (TENNs), developed by BrainChip, represent a novel and highly efficient state-space network. TENNs demonstrate exceptional proficiency in handling multi-dimensional streaming data, facilitating advancements in object detection, action recognition, speech enhancement and language model/sequence generation. Through the utilization of polynomial-based continuous convolutions, TENNs streamline models, expedite training processes and significantly diminish memory requirements, achieving notable reductions of up to 50x in parameters and 5,000x in energy consumption compared to prevailing methodologies like transformers.
Integration with BrainChip’s Akida neuromorphic hardware IP further enhances TENNs’ capabilities, enabling the realization of highly capable, portable and passively cooled edge devices. This presentation delves into the technical innovations underlying TENNs, presents real-world benchmarks, and elucidates how this cutting-edge approach is positioned to revolutionize edge AI across diverse applications.
“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...
05 wp4 progresses&results-20130221
1. WP4: Exploring the phenotypic and genetic diversity in European
apple and peach germplasm collections and its exploitation by
association genetics approach
Results achieved since the beginning
of the project and plans for 2013
Maria José Aranzana + all WP4 partners
2. Main objectives of WP 4
Improve the knowledge of genetic and phenotypic variability in
apple and peach European collections
Identify genomic regions contributing to the genetic control of
major horticultural traits through genome-wide association
genetics (LD mapping)
In combination with WP3, supply WP1 with tightly linked
molecular markers for implementation into the MAB pipeline
3. Results achieved since the beginning
of the project
Description of phenotypic variability in apple
and peach germplasm collections
• Peach genetic variability, population
structure and LD analysis
• Apple genetic variability and population
structure
4. UK; 2237
FR; 1054
BE; 1314
CZ; 256
IT; 421 SWE;195
Selection of accessions in
germplasm collections
UK
310
FR
274
BE
296
CZ
253
IT
232
SWE
195
5,477 accessions in
germplasm collections
1,560
accessions with
phenotypic
observations
APPLE
Removing synonyms and triploids
IT-RO; 943
IT-MI; 575
FR; 764
ISP; 303
CH; 300
2,885 accessions in
germplasm collections
1,296 accessions
with phenotypic
observations
Removing synonyms and selecting
diversity
PEACH
IT-RO
178
IT-MI
140
FR
343
SP
353
CH
282
5. GROUP LABEL DESCRIPTOR PRIORITY
DI1Canker
Tree-twigs - Susceptibility to NECTRIA
CANKER (1-9)
Partial
DI1Mildew
Leave & twigs - Global Susceptibility to
POWDERY MILDEW (1-9)
Partial
DI1ScabFruit Fruit – Global Susceptibility to SCAB (1-9) Partial
DI1 = FUNGI
DISEASE
DI1ScabLeaf Leaf – Global Susceptibility to SCAB (1-9) Partial
FL1Class Flowering Period (1-9) Common
FL1Intensity Flowering Intensity (1-9) PartialFL1 = FLOWERING
PHENOLOGY
FL1Regularity
Relative regularity of flowering - Biennal
Habit (1-9)
Add
FR1OverColorAmount Fruit Global amount of over colour (1-9) Common
FR1Size Fruit Size (1-9) Common
FR1RibApex Fruit Crowning apex (1-9) Partial
FR1RussetAmount Fruit Global Amount russet (1-9) New
FR1Shape Fruit Basic Global shape (1-4) Common
FR1ShapeRatio Fruit Global shape (RATIO Heigt / Width) Partial
FR1 = FRUIT
CHARACTERISATION
FR1StalkLength Fruit Stalk Length (1-9) Partial
FR2Acid Fruit Sensory Acidity (1-9) Partial
FR2AcidSugarRatio Fruit Sensory Flesh Balance Sweet/acid New
FR2Bitter Fruit Sensory Flesh Bitterness (1#9) Partial
FR2Crunch Fruit Crispness (1-9) New
FR2Firm Fruit Sensory flesh Firmness (1-9) New
FR2Granular Fruit Sensory flesh Texture (1-9) Common
FR2Juice Fruit Sensory Juiciness (1-9) New
FR2Mealy Flesh mealiness Add
FR2Sugar Fruit Sensory Sweetness (1-9) Partial
FR2TasteGlobal Fruit – Sensory Global eating quality (1-9) Common
FR2 = FRUIT TASTE
FR2TasteMaturity
Assessment of the optimal ripening stage of
the fruits when picked and/or tasted
New
FR3PeriodKeeping Global Period of Fruit Keeping ability (1-9) PartialFR3 = FRUIT
KEEPING & PICKING
PERIODS
FR3PeriodPicking Fruit Harvest Maturity (1-9) New
FR4Size Fruit Size (Diameter mm) CommonFR4 = FRUIT
INSTRUMENTAL
CHARACTERISATION
FR4Weight Fruit Weight Average (g) Common
TR1Architecture Tree – Global Architecture PartialTR1 = TREE
CHARACTERISATION TR1BearingHabit Tree Type of fruiting (1-4) (Lespinasse) Partial
TR2 = FRUIT
CROPPING
TR2Prod1year Relative Fruit setting (1-9) – Year by year Add
Results: phenotypic variability in apple
and peach germplasm collections
0
5000
10000
15000
20000
25000
READING INRA CRA-W RBIPH UNIBO
Fruit & Tree
Period of flowering
Disease susceptibility
APPLE
• 1,264 accessions with observations
• 81,206 informative data entries in the
phenotypic database
7. Results: phenotypic variability in apple
and peach germplasm collections
• 998 accessions with observations
• 37,818 informative data entries in the
phenotypic database
PEACH
CRA-Rome UMIL IRTA INRA ZJU
vigor x x - - x
tree habit x x - - x
gland type x x - - x
flower type x x - - x
male sterility - x - x x
beginning of flowering date x - x x x
beginning of flowering description - - - - x
full blossom date - x x x x
full blossom description - - x - x
flower density x x x x x
beginning of ripening date x x x - x
beginning of ripening description - - x - x
yield x x - - x
fruit size x x - x x
fruit size weight x - x x -
fruit pubescence x x x x x
fruit shape x x x x x
fruit flesh color x x x x x
fruit hue of overcolor x x - - x
fruit extent of overcolor x x - x x
sugar content brix - - x x x
sugar content taste data - x - - -
acidity - - x x -
acidity taste description - x - - x
acidity taste scale - x - - -
flesh firmness x x - x x
texture x x - - x
stony hard - x - - x
adherence of stone to flesh x x - x x
PRODUCTION
FRUIT QUALITY
VEGETATIVE TRAITS
FLOWER TRAITS
FRUIT MORPHOLOGY
FLOWERING
MATURITY
0
1000
2000
3000
4000
5000
6000
CRA-Rome UNIMI INRA IRTA ZJU
Vegetative traits
Flower Traits
Flowering period
Maturity
Production
Fruit Morphology
Fruit Quality
.
8. Results: phenotypic variability in apple
and peach germplasm collections
PEACH
Data entries per partner
0
500
1000
1500
2000
2500
3000
3500
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
Years with phenotypic observations
Numberofdataentries
CRA-Rome
UNIMI
INRA
IRTA
ZJU
9. • Analysis of the distribution of traits variability per collection
Results: phenotypic variability in apple
and peach germplasm collections
Days to full blossom Days to ripen
Sugar content Acidity
10. Results achieved since the beginning
of the project
Description of phenotypic variability in apple
and peach germplasm collections
Peach genetic variability, population
structure and LD analysis
• Apple genetic variability and population
structure
11. Results: peach variability, population
structure and LD analysis
1,296 peach
accessions
CRA-Rome
178
UNIMI
140
INRA
343
IRTA
353
ZJU
282
Genotyped with the 9K IPSC SNPs chip:
8,144 SNPs identified through the re-
sequencing of ca. 50 prunus
accessions
SNP genotyping
Good
4379
54%
Nullallele
242
3%
Lack of one
homozygous
827
10%
To check
20
0%
Monomorphic
778
10%
Failed
1898
23%
12. Results: peach variability, population
structure and LD analysis
- ~20% of accessions were clones (98% of identical genotype)
- Average observed heterozygosity 30% (Min 0.3% and Max 68%)
- Average inbreeding coefficient (F): 0.27 (first cousin)
13. Results: peach variability, population
structure and LD analysis
Most representative K is 3:
• Occidental breeding material (352 accessions)
• Chinese / oriental material (58 accessions)
• Occidental old / non breeding material (165 accessions)
• Admixed accessions [Q < 0.8] (665 accessions)
14. Results: peach variability, population
structure and LD analysis
Occidental breeding material Occidental old / non breeding material
Chinese / oriental material Admixed accessions [Q < 0.8]
LD 1Mbp
15. Results achieved since the beginning
of the project
Description of phenotypic variability in apple
and peach germplasm collections
Peach genetic variability, population
structure and LD analysis
Apple genetic variability and population
structure
17. Results: apple genetic variability and
population structure
Nb of
genotypes
Nb of
accessions
Belgium 190 209
CZ 120 132
France 225 225
Italy 167 184
Sweden 158 160
UK 271 271
2 countries 78 171
3 countries 20 72
4 countries 12 58
1241 1482
0
1
2
3
4
5
6
7
8
1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70 73 76 79 82 85 88 91 94 97 100103106109
Duplicates - diploids Belgium Czech_Republic France Italy Sweden United_Kingdom
Diploids
18. Results: apple genetic variability and
population structure Diversity –
Geographic origin
19. Results: apple genetic variability and
population structure Diversity –
Partner’s collection
20. Position of WP3 parents in the overall diversity
WP3 parents cover well the most frequent variability
WP4 based on large genetic diversity while WP3 in breeding material
24. Publications
• Meeting presentations
– Application of high throughput genotyping techniques in peach germplasm and breeding lines
within the FruitBreedomics project (Micheletti D., Arús P., Barreneche T., Bassi D., Dirlewanger E.,
Gao Z., Lambert P., Laurens F., Pascal T., Quilot B., Rossini L., Troggio M., Van de Weg E., Verde I. and
Aranzana MJ). Poster. PAG 2012
– Genetic variability in a wide germplasm of domesticated peach through high throughput
genotyping. Diego Micheletti, Valeria Aramini, Pere Arus, Elisa Banchi, Teresa Barreneche, Daniele
Bassi , Elisabeth Dirlewanger, Zhongshan Gao, Laura Gazza, Patrick Lambert, François Laurens,
Xiongwei, Thierry Pascal, Bénédicte Quilot-Turion, Laura Rossini, Michela Troggio, Ignazio Verde,
Maria Jose Aranzana. Oral presentation. PAG 2013
– Genetic variability description in a wide germplasm of Peach through High Throughput
Genotyping within Fruitbreedomics. Diego Micheletti,Valeria Aramini, Pere Arús, Elisa Banchi, Teresa
Barreneche,Daniele Bassi, Elisabeth Dirlewanger, Zhongshan Gao, Laura Gazza , Patrick Lambert,
François Laurens, Xiongwei Li, Thierry Pascal, Bénédicte Quilot-TurionLaura Rossini, Michela Troggio,
Ignazio Verde, Maria José Aranzana . Oral presentation. RGC6 2012
25. Publications plan for 2013
Genetic variability in a wide germplasm of
domesticated peach through high throughput
genotyping. (D.4.2).
26. Main challenges for 2013
Task 4.1.- Description of phenotypic variability
Phenotypic data already in a web database
Search queries and statistical analysis tools in
the database to be defined (jointly with WP1 and
WP3 and done by WP7)
27. Main challenges for 2013
Task 4.2.- apple and peach core collections
peach cc set and analyzed with 9K SNPs
apple cc set and analyzed with SSRs
Apple SNP genotyping:
• LD decays fast in apple thousands of NSPs needed
• Which genotyping method???
•SNP chip
•Genotyping by sequence
28. Main challenges for 2013: chose
genotyping strategy in apple
• Test of SNP genotyping, 48 old apple accessions
with Illumina SNP Chip
Good
10363
57%
Null allele
110
1%
Lack of one
homozygous;
low frequency;
missing data
5870
33%
Monomorphic
1491
8%
Failed
185
1%
20K apple SNP Chip
14 apple accessions re-sequenced
2.6 million SNPs found 750 K valid
18,019 SNPs selected (16.3K new and
3.7K from previous chip)
Genetic interval 1cM
LD decay at 55 Kb!!
29. Task 4.3.- Acquiring new phenotypic data
Collect second year of phenotypic data
Main challenges for 2013: chose
genotyping strategy in apple
31. Deliverables and milestones for the
next 12 months
D4.2.- Database uploaded with already available phenotypic data (M24)
D4.3.- Submit a manuscript of: (M30)
• Allelic diversity, population structure and LD in peach
• Construction of apple CC
MS15.- SNP SSR data available in the database for apple cultivars (M18)
MS16.- Peach SNP data available in the database (M24)
MS17.- Apple SNP data available in the database (M33)
MS18.- One year of phenotypic and genome-wide data in the database (M36)
32. Interactions between your WP and the
rest of the project
• Interactions planned with other WPs of the project:
– From your WP:
• WP1: provide SNPs linked to monogenic traits
• WP3: share QTLs information for comparison
• WP7: genetic information needs to be included in the
database; search toolbox and statistics of phenotypic
information
– To your WP:
• WP3: share QTLs information for comparison
• WP7: release of
33. Agenda for WP4 session: EDIFICI
POLIVALENT 2.03 room
• Acquiring new phenotypic data (2013) (20´)
– Feedback of 2012 phenotyping
– Problems to solve?
• Apple core collection. Prospects for the paper (15´)
• Draft of variability and LD paper on peach (15´)
• Discussion on the best strategy for apple SNP genotyping
(30´)
• Action plan (10´)