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   <meta name="author" content="Grzegorz Uszynski" />
   <meta name="author" content="Puthick Hok" />
   <meta name="author" content="Andrzej Kilian" />
-  <meta name="dcterms.date" content="2024-05-15" />
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@@ -282,10 +282,10 @@ <h1 class="title">BrAPI Success Stories</h1>
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 <p><small><em>
 This manuscript
-(<a href="https://plantbreeding.github.io/BrAPI-Manuscript2/v/2af458a098c88054eb565e6c06399ed43b7cc752/">permalink</a>)
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-on May 15, 2024.
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+on May 21, 2024.
 </em></small></p>
 <h2 id="authors">Authors</h2>
 <ul>
@@ -763,8 +763,8 @@ <h4 id="gridscore">GridScore</h4>
 <p>Phenotypic data collection underpins scientific crop research and plant breeding. Knowledge gained from collected data and its analysis alongside data visualizations inform further phenotypic trials and ideally support research hypotheses. The importance of accuracy and efficiency in the collection of this data as well as the infrastructure to facilitate the flow of data from the field to a knowledge base cannot be underestimated. <a href="https://ics.hutton.ac.uk/get-gridscore/">GridScore</a> <span class="citation" data-cites="Ne0E9HbC">[<a href="#ref-Ne0E9HbC" role="doc-biblioref">3</a>]</span> is a modern mobile application for phenotypic observations that harnesses technological advancements in the area of mobile devices to enrich the data collection process.</p>
 <p>BrAPI has further increased the value of GridScore by integrating it into the overarching workflow from trial creation, data collection, and its ultimate data storage for further processing. Specifically, trial designs as well as trait definitions can be imported into GridScore using BrAPI and a finalized trial can ultimately be exported via BrAPI to any compatible database.</p>
 <h4 id="climmob">ClimMob</h4>
-<p>ClimMob <span class="citation" data-cites="LCpCba21">[<a href="#ref-LCpCba21" role="doc-biblioref">4</a>]</span> is a software suite that turns the research paradigm in experimental agriculture. Instead of a few researchers designing complicated trials to compare several agricultural technologies in search of the best solutions for the target environment, ClimMob enables many participants to carry out reasonably simple experiments that taken together can offer even more information. It applies the priciples of citizen science and choice experiments to scale the data collection process, mostly in the format of rankings. Although this data may not be as detailed as from a centralized experiment, it can be very useful to inform decisions to a wide range of locations and environments with increased external validity.</p>
-<p>When it comes to BrAPI compatibility, ClimMob follows the same patterns established by Field Book. During a survey, all the farmer collected data is stored in a central ClimMob node. When the survey is complete, all the data is uploaded automatically via BrAPI to a central breeding database for long term storage and analysis. This automated process greatly simplifies the data management requirements for ClimMob, with data ready for analysis almost as soon as its done being collected.</p>
+<p>ClimMob <span class="citation" data-cites="LCpCba21">[<a href="#ref-LCpCba21" role="doc-biblioref">4</a>]</span> is a software suite that turns the research paradigm in experimental agriculture. The platform supports experiment design, data collection through mobile apps, and data analysis to provide actionable insights. Instead of a few researchers designing complicated trials to compare several agricultural technologies in search of the best solutions for the target environment, ClimMob enables many participants to carry out reasonably simple experiments that taken together can offer even more information. It applies the priciples of citizen science and choice experiments to scale the data collection process, mostly in the format of rankings. Although this data may not be as detailed as from a centralized experiment, it can be very useful to inform decisions to a wide range of locations and environments with increased external validity. ClimMob applications include testing crop varieties, evaluating agronomic practices, and investigating climate resilience strategies.</p>
+<p>During a crop varieties trial, all farmer-collected data is stored in ClimMob. Upon data collectection completion, the raw data is automatically uploaded via BrAPI to a central breeding database for long-term storage. To facilitate this synchronization, ClimMob uses BrAPI to retrieve curated germplasm information from breeding databases when designing a trial, significantly enhancing data quality. Additionally, a process has been developed to push analyzed data from ClimMob to the breeding databases, providing breeders with insights into the potential adoption of the tested crop varieties.</p>
 <h4 id="imagebreed">ImageBreed</h4>
 <p>High-throughput phenotyping has been gaining significant traction lately as a way to collect lots of data very quickly. Image collection from unmanned aerial and ground vehicles (UAVs and UGVs) are a great way to collect a lot of raw data all at once, then analyze it later. ImageBreed <span class="citation" data-cites="Dhlmsxng">[<a href="#ref-Dhlmsxng" role="doc-biblioref">5</a>]</span> is an image collection pipeline tool to support regular use of UAVs and UGVs.</p>
 <p>When the raw images have been processed through the standardization pipelines in ImageBreed, useful phenotypes can be extracted from the images. The BrAPI standard is used to push these phenotypes back to a central breeding database where they can be analyzed with other data. In addition to this, ImageBreed has the ability to use BrAPI to upload the raw images to the central breeding database, or any other BrAPI compatible long term storage service. In the current version of the standard (V2.1), the BrAPI data models for images are rudimentary, but effective. The ImageBreed team has put in some work into enhancing the BrAPI image data standards, collaborating with others in the community.</p>
diff --git a/manuscript.md b/manuscript.md
index dffadae..81ef969 100644
--- a/manuscript.md
+++ b/manuscript.md
@@ -7,7 +7,7 @@ keywords:
 - standards
 - community
 lang: en-US
-date-meta: '2024-05-15'
+date-meta: '2024-05-21'
 author-meta:
 - Peter Selby
 - Trevor Rife
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 <small><em>
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-([permalink](https://plantbreeding.github.io/BrAPI-Manuscript2/v/2af458a098c88054eb565e6c06399ed43b7cc752/))
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 was automatically generated
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-on May 15, 2024.
+from [plantbreeding/BrAPI-Manuscript2@b3b3856](https://github.com/plantbreeding/BrAPI-Manuscript2/tree/b3b38564edbd3d2575017ab78c63084176a6c5b2)
+on May 21, 2024.
 </em></small>
 
 
@@ -832,9 +832,9 @@ BrAPI has further increased the value of GridScore by integrating it into the ov
 
 #### ClimMob
 
-ClimMob [@doi:10.1016/j.compag.2023.108539] is a software suite that turns the research paradigm in experimental agriculture. Instead of a few researchers designing complicated trials to compare several agricultural technologies in search of the best solutions for the target environment, ClimMob enables many participants to carry out reasonably simple experiments that taken together can offer even more information. It applies the priciples of citizen science and choice experiments to scale the data collection process, mostly in the format of rankings. Although this data may not be as detailed as from a centralized experiment, it can be very useful to inform decisions to a wide range of locations and environments with increased external validity.
+ClimMob [@doi:10.1016/j.compag.2023.108539] is a software suite that turns the research paradigm in experimental agriculture. The platform supports experiment design, data collection through mobile apps, and data analysis to provide actionable insights. Instead of a few researchers designing complicated trials to compare several agricultural technologies in search of the best solutions for the target environment, ClimMob enables many participants to carry out reasonably simple experiments that taken together can offer even more information. It applies the priciples of citizen science and choice experiments to scale the data collection process, mostly in the format of rankings. Although this data may not be as detailed as from a centralized experiment, it can be very useful to inform decisions to a wide range of locations and environments with increased external validity. ClimMob applications include testing crop varieties, evaluating agronomic practices, and investigating climate resilience strategies.
 
-When it comes to BrAPI compatibility, ClimMob follows the same patterns established by Field Book. During a survey, all the farmer collected data is stored in a central ClimMob node. When the survey is complete, all the data is uploaded automatically via BrAPI to a central breeding database for long term storage and analysis. This automated process greatly simplifies the data management requirements for ClimMob, with data ready for analysis almost as soon as its done being collected. 
+During a crop varieties trial, all farmer-collected data is stored in ClimMob. Upon data collectection completion, the raw data is automatically uploaded via BrAPI to a central breeding database for long-term storage. To facilitate this synchronization, ClimMob uses BrAPI to retrieve curated germplasm information from breeding databases when designing a trial, significantly enhancing data quality. Additionally, a process has been developed to push analyzed data from ClimMob to the breeding databases, providing breeders with insights into the potential adoption of the tested crop varieties.
 
 
 #### ImageBreed
diff --git a/manuscript.pdf b/manuscript.pdf
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Binary files a/manuscript.pdf and b/manuscript.pdf differ
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@@ -1,4 +1,5 @@
 content/03.01.03.ClimMob.md:3:priciples
+content/03.01.03.ClimMob.md:5:collectection
 content/03.02.04.GIGWA.md:4:EE
 content/03.02.04.GIGWA.md:6:Gigwa's
 content/03.02.06.DArT.md:3:Grzegorz
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@@ -19,7 +20,7 @@ López
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 situ
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diff --git a/variables.json b/variables.json
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