header sections updated

content/03.01.--.HEADER.Phenotyping.md

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 ### Phenotyping
 
-Phenotyping is the basis for all breeding efforts. All the downstream analysis and decision making procedures rely on a foundation of accurate, high-quality, phenotypic data. The BrAPI specification supports phenotypic data as it passes through the entire breeding pipeline, as it is published, and as it is archived. The community has developed tools that use BrAPI during the data collection process, to get the data into a standard format as soon as possible. There are BrAPI compatible systems to store and curate phenotypic data, and tools to manage trait meta data. The community has also begun developing BrAPI compatible tools for managing images and other high throughput phenotyping techniques. 
+<!-- Ajay -->
+Phenotyping is fundamental to plant breeding, providing the accurate, high-quality data needed for downstream analyses and decisions. It goes beyond simple data collection, requiring a thorough understanding of research questions and strategic data gathering to ensure successful outcomes. Effective phenotyping can make or break a research project, underscoring the importance of mastering its techniques. The BrAPI specification supports phenotypic data throughout the entire breeding pipeline, from initial collection and standardization to publication and archiving. The community has developed BrAPI-compatible tools to facilitate early data standardization, efficient storage, and curation of phenotypic data and trait metadata. Additionally, there are ongoing efforts to create tools for managing images and other high-throughput phenotyping techniques, further enhancing the precision and efficiency of plant breeding research.

content/03.01.05.PHIS.md

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 <!-- Isabelle -->
 The Hybrid Phenotyping Information System ([PHIS](http://www.phis.inrae.fr/) [@doi:10.1111/nph.15385]), based on the [OpenSILEX](https://github.com/OpenSILEX/) framework, is an ontology-driven information system based on semantic web technologies. PHIS is deployed in several field and greenhouse platforms of the French national [PHENOME](https://www.phenome-emphasis.fr/) and European [EMPHASIS](https://emphasis.plant-phenotyping.eu/) infrastructures. It manages and collects data from Phenotyping and High Throughput Phenotyping experiments on a day to day basis. PHIS unambiguously identifies all the objects and traits in an experiment, and establishes their types and relationships via ontologies and semantics.
 
-PHIS has been designed to be BrAPI-compliant. PHIS adheres to the standards and protocols specified by BrAPI and implements various services aligning with the BrAPI standards, encompassing the Core, Phenotyping, and Germplasm modules. This enables integration and compatibility with BrAPI-compliant systems and platforms. This prerequisite served as the basis for formalizing the data model, while also facilitating compatibility with other standards, such as the Minimal Information About a Plant Phenotyping Experiment ([MIAPPE](https://www.miappe.org/) [@doi:10.1111/nph.16544]). By integrating BrAPI requirements into its structure, PHIS not only meets the standards of the phenotyping field, but also strengthens its capacity for interoperability and effective collaboration in the wider context of plant breeding and related fields. The fact that data within a PHIS instance can be queried through BrAPI services makes the indexing of PHIS in [FAIDARE](https://urgi.versailles.inrae.fr/faidare/) [@https://urgi.versailles.inrae.fr/faidare/] very easy to implement.
+PHIS has been designed to be BrAPI-compliant. PHIS adheres to the standards and protocols specified by BrAPI and implements various services aligning with the BrAPI standards, encompassing the Core, Phenotyping, and Germplasm modules. This enables integration and compatibility with BrAPI-compliant systems and platforms. This prerequisite served as the basis for formalizing the data model, while also facilitating compatibility with other standards, such as the Minimal Information About a Plant Phenotyping Experiment ([MIAPPE](https://www.miappe.org/) [@doi:10.1111/nph.16544]). By integrating BrAPI requirements into its structure, PHIS not only meets the standards of the phenotyping field, but also strengthens its capacity for interoperability and effective collaboration in the wider context of plant breeding and related fields. The fact that data within a PHIS instance can be queried through BrAPI services makes the indexing of PHIS in [FAIDARE](https://urgi.versailles.inrae.fr/faidare/) [@https://urgi.versailles.inrae.fr/faidare] very easy to implement.
 
 Furthermore, as PHIS offers BrAPI-compliant Web Services, it simplifies the integration and data exchange with other European information systems that handle phenotyping data. The adherence to BrAPI standards ensures a common interface and compatibility, facilitating communication and collaboration between PHIS and other systems in the European context. This interoperability not only eases data sharing, but also promotes a more coherent and efficient approach to the management and use of phenotyping data on various platforms and research initiatives within the European scientific community.

content/03.01.06.PIPPA.md

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 <!-- Rafael -->
 [PIPPA](https://pippa.psb.ugent.be) [@https://pippa.psb.ugent.be] is a data management system used for collecting data from the [WIWAM](https://www.wiwam.be/) [@https://www.wiwam.be/] range of automated high throughput phenotyping platforms. These platforms have been deployed at different research institutes and commercial breeders across Europe. They can be setup in a variety of configurations with different types of equipment including weighing scales, cameras, and environment sensors. The software features a web interface with functionality for setting up new experiments, planning imaging and irrigation treatments, linking metadata to pots (genotype, growth media, manual treatments), importing data, exporting data, and visualizing data. It also supports the integration of image analysis scripts and connections to a compute cluster for job submission.
 
-To share the phenotype data of the experiments linked to publications, an implementation of BrAPI v1.3 was developed which allowed read only access to the data in the BrAPI standardized format. This server was registered on [FAIDARE](https://urgi.versailles.inrae.fr/faidare/) [@https://urgi.versailles.inrae.fr/faidare/] which allows the data to be found alongside data from other BrAPI compatible repositories.
+To share the phenotype data of the experiments linked to publications, an implementation of BrAPI v1.3 was developed which allowed read only access to the data in the BrAPI standardized format. This server was registered on [FAIDARE](https://urgi.versailles.inrae.fr/faidare/) [@https://urgi.versailles.inrae.fr/faidare] which allows the data to be found alongside data from other BrAPI compatible repositories.
 
 As the BrAPI ecosystem has matured, it has created a clear path for the further development of PIPPA. THe BrAPI specification demonstrates how to share data in a manner consistent with the FAIR principles, [@doi:10.1038/sdata.2016.18] which are becoming best practices in plant research data management. The BrAPI technical standard, in combination with the [MIAPPE](https://www.miappe.org/) [@doi:10.1111/nph.16544] scientific standard, have served as guidelines in the current development effort of the PIPPA project. This development is focused on delivering a public BrAPI v2.1 endpoint and making more high throughput datasets publicly available via BrAPI.

content/03.02.--.HEADER.Genotyping.md

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 ### Genotyping
 
-Genotyping has become a cornerstone of most breeding processes, but the data can be difficult to manage. BrAPI supports genotypic data, relying on some existing standards including VCF and the GA4GH Variants standards. The BrAPI Community has built BrAPI compatible tools for storing, searching, visualizing, and analyzing genotypic data. 
+<!-- Ajay -->
+Genotyping has become a cornerstone of most breeding processes, but managing the data can be challenging. Understanding different genotyping protocols for various crops is crucial due to the unique genetic structures of each species. Techniques such as SNP genotyping, Genotyping-by-Sequencing (GBS), SSRs, Whole Genome Sequencing (WGS), and array-based genotyping each offer specific advantages depending on the crop and research objectives. BrAPI supports genotypic data by utilizing existing standards such as VCF [@doi:10.1093/bioinformatics/btr330] and the GA4GH Variants schema [@https://github.com/ga4gh-metadata/SchemaBlocks]. The BrAPI community has developed compatible tools for storing, searching, visualizing, and analyzing genotypic data, making it easier to integrate and utilize this information in breeding programs. Mastery of the various genotyping protocols ensures efficient and effective breeding, while BrAPI compliant tools streamline data management and analysis, enhancing the ability to make data-driven decisions in developing superior crop varieties.

content/03.03.--.HEADER.Germplasm_Management.md

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 ### Germplasm Management
 
-The vast quantity of new accessions, variants, and lines being created each year means germplasm data management is critical to keeping things organized. This is true at the level of a single breeding program, on a national scale, and on the international scale. BrAPI supports the transmission of germplasm passport data, as well as pedigree trees and crossing metadata. The BrAPI community has developed BrAPI compliant tools for storing, searching, and visualizing this metadata. There are even some plans in place to build federated networks of genebank data, connected via BrAPI. 
+<!-- Ajay -->
+Germplasm data management is crucial due to the vast quantity of new accessions, variants, and lines created yearly. Germplasm is the basis of variation on which plant breeders rely to upgrade and optimize their breeding programs. This is essential at the levels of individual breeding programs, national initiatives, and international collaborations. BrAPI supports the transmission of germplasm passport data, pedigree trees, and crossing metadata. The BrAPI community has developed compliant tools for storing, searching, and visualizing this metadata, facilitating efficient management. Additionally, there are plans to establish federated networks of genebank data connected via BrAPI, enhancing global accessibility and collaboration in germplasm management.

content/03.03.06.FAIDARE.md

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 #### FAIDARE
 
 <!-- Cyril P, first draft-->
-[FAIDARE](https://urgi.versailles.inrae.fr/faidare/) [@https://urgi.versailles.inrae.fr/faidare/] is a data discovery portal providing a biologist friendly search system over a global federation of 33 plant research databases. It allows a user to identify data resources using a full text search approach combined with domain specific filters. Each search result contains a link back to the original database for visualization, analysis, and download. The indexed data types are very broad and include genomic features, selected bibliography, QTL, markers, genetic variation studies, phenomic studies, and plant genetic resources. This inclusiveness is achieved thanks to a two stage indexation data model. The first, most generic, index provides basic search functionalities and relies on five fields: name, link back URL, data type, species, and exhaustive description. To provide more advanced filtering, the second stage indexation mechanism takes advantage of BrAPI endpoints to get more detailed metadata on genotyping and phenotyping studies. 
+[FAIDARE](https://urgi.versailles.inrae.fr/faidare/) [@https://urgi.versailles.inrae.fr/faidare] is a data discovery portal providing a biologist friendly search system over a global federation of 33 plant research databases. It allows a user to identify data resources using a full text search approach combined with domain specific filters. Each search result contains a link back to the original database for visualization, analysis, and download. The indexed data types are very broad and include genomic features, selected bibliography, QTL, markers, genetic variation studies, phenomic studies, and plant genetic resources. This inclusiveness is achieved thanks to a two stage indexation data model. The first, most generic, index provides basic search functionalities and relies on five fields: name, link back URL, data type, species, and exhaustive description. To provide more advanced filtering, the second stage indexation mechanism takes advantage of BrAPI endpoints to get more detailed metadata on genotyping and phenotyping studies. 
 
 The indexation mechanism relies on a [public software package](https://github.com/elixir-europe/plant-brapi-etl-faidare) that allows data resource managers to request the indexation of their database. This BrAPI client is able to extract data from any BrAPI 1.3 and 1.2 endpoint. The development of BrAPI 2.x indexation will be initiated in 2025. Since not all databases are willing to implement BrAPI endpoints, we also provide the possibility to generate metadata as BrAPI compliant json files, using the standard as a file exchange format.
 

content/03.04.--.HEADER.Data_Management.md

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 ### Breeding Data Management
 
-While specialty data management is important for some use cases, often breeders want a central repository of critical data. General breeding data management systems support some level of phenotypic, genotypic, and germplasm data, as well as trial, equipment, and people management. By enabling BrAPI support, these larger systems can connect with smaller tools and specialty systems to provide more functionality under the same user interface. There are several breeding data management systems developed in the BrAPI community, each with their own pros and cons. 
+While specialty data management is important for some use cases, often breeders want a central repository of critical data. General breeding data management systems support some level of phenotypic, genotypic, and germplasm data, as well as trial, equipment, and people management. By enabling BrAPI support, these larger systems can connect with smaller tools and specialty systems to provide more functionality under the same user interface. There are several breeding data management systems developed in the BrAPI community, each with their own strengths.