Cloverfield v2.16.0 – June 26th, 2024
New features have been added to Cloverfield™, your plant phenotyping online platform. With these additions, we continue to make your digital phenotyping journey frictionless and to allow you to optimize your breeding schemes with always more advanced and efficient analytical capabilities.
New features include:
Declare your control varieties (check plots) within your trial and identify them clearly in the Analytics section in Cloverfield for better trait analysis.
User value: This functionality helps to enhance your analytics.
Use case: Very efficiently benchmark your plots or genotypes against your control varieties (check plots) within your trial.
This new feature has been added to allow you to select a random sample of plot or genotypes in a few clicks. Simply select the sample size of interest and analyze your selection or use it to score visually your plots and genotypes via the Plot Rating tool.
User value: This feature paves the way for phenomic prediction use cases and more advanced analytical projects.
Use Cases: Select a random sample of plots or genotypes and visually score them (e.g., disease score, or lodging score). Then let us extrapolate your visual scores to the rest of the trial.
You can visually score your plots and genotypes directly via the Analytics section in Cloverfield. With this update, you can autonomously declare your scoring range and scales, whether you want a disease score ranging from 1 to 9 or categorical values such as "low", "medium", high". You can cumulate different scales during your visual assessment through Cloverfield™.
User value: Accelerate objective and consistent team-based visual scoring efforts from the confort of your office.
Use Cases: Visually score your plots and let us analyze how they stack up against drone metrics or let us extrapolate your visual scores to the rest of the trial. You can pick and choose the plots to rate via a quick graph selection or use the random plot selector.
Quality checking new drone imagery you upload via Cloverfield is the first thing we do before processing your data. This new functionality allows you to see the quality control status of your flight directly from the Monitoring tool in Cloverfield. Your flight will be marked as "validated" if all is OK, or as "warning" or "rejected" if quality is not adequate. You can consult the report left by your Campaign Manager from this new foldable section.
User value: Get imagery quality feedback within 24 hours of your data being uploaded and do not miss the opportunity to fly again if the quality of your first flight is not as expected.
Use Cases: Manage your drone pilots and access quality control reporting directly from Cloverfield.
For more information, reach out to your Hiphen Campaign Manager. Stay tuned for the next Cloverfield™ features release update next month.
Sincerely, Your Hiphen Success Team.
In the rapidly evolving field of agricultural research, high-throughput plant phenotyping stands out as a critical component for advancing plant breeding by optimizing breeding schemes and by improving the desirable trait heritability & genetic gain of your field trials.
Our latest paper delves into the transformative potential of Real-Time Kinematic (RTK) technology, specifically in the realm of drone acquisitions, to elevate the precision and efficiency of phenotypic data collection and processing.
This comprehensive guide provides a meticulous "recipe for success," offering a detailed checklist to ensure RTK-precision in drone operations. We explore the manifold benefits of RTK technology, elucidating its operational mechanics with both base stations, such as EMLID, and various network solutions like Orpheon, Point One, and SmartNet. The paper walks you through step-by-step procedures, distinguishing between RTK FIX and FLOAT modes, and explains the implications of operating without RTK activation.
Furthermore, we discuss advanced options like Post-Processing Kinematic (PPK) to push the boundaries of precision even further. Whether you are a researcher, agronomist, or technology enthusiast, this paper equips you with the knowledge to harness RTK technology for groundbreaking advancements in plant phenotyping.
The full content of this technical guide is available as a downloadable PDF: https://hiphen-rtk-white-paper-2024.grwebsite.fr/
New features have been added to Cloverfield™, your plant phenotyping online platform. Embark on a smoother plant breeding adventure with Hiphen's latest addition: Dynamic Filtering.
Optimize your breeding scheme by effortlessly filtering your genetic material in a few clicks within Cloverfield™.
Interactively combine traits and set thresholds to filter out under-performing genotypes, or pinpoint the top-performing material you want to advance to the next stage.
Define more precisely your analytics profile. Specify more precisely the experiments, modalities and layers that you which to study and/or compare. You can create multiple profiles for the same trial site.
One step further in making your digital phenotyping experience frictionless with Hiphen, you're now able to make a detailed analysis of your data directly in Cloverfield™. You can easily combine traits and set for each one thresholding boundaries outside of which you wish to eliminate genetic material. For instance, one could set independent min-max thresholds for traits like plant biovolume, flower cover, stay green and lodging and see dynamically what share of the trial genetic material he/she is eliminating. This functionality will take you ever closer to reaching your ideotypes more efficiently than ever before!
User value: Apply multiple criteria filtering on your genetic material and dynamically eliminate under-performing genotypes based on your ideotype recipe.
Use Cases:
We invite you to explore the new dynamic filtering feature with the online INTERACTIVE TOUR. And please reach out to your Hiphen Campaign Manager should you have any question.
Stay tuned for the next Cloverfield™ features release update next month.
Sincerely,
Your Hiphen Success Team.
Welcome to our comprehensive technical guide on plant height trait assessment, a crucial aspect in unlocking plant biomass estimations to speed up breeding cycles. Within these pages, you'll discover the recipe for success in assessing plant height traits, essential for informed decision-making in breeding programs. We delve into the significance of Ground Control Points (GCPs) and why they are pivotal in ensuring accurate and reliable data collection, essential for robust analyses and interpretation.
Drawing from real-world experiences, this guide presents compelling use cases that showcase the practical application of plant height assessments in various agricultural contexts. Moreover, gain invaluable insights from expert agronomists who offer nuanced perspectives and practical advice honed through years of experience in the field.
In addition to presenting established methodologies, we explore alternative approaches and options for those looking to further optimize their plant height trait assessment processes. Whether you're a seasoned professional seeking to refine your techniques or a newcomer eager to grasp the fundamentals, this guide equips you with the knowledge and tools necessary to elevate your breeding programs to new heights.
The full content of this technical guide is available as a downloadable PDF: https://white-paper-hiphen-plant-height.grwebsite.fr/
SIMONE will identify, deliver, and evaluate innovations that involve technical, environmental, and economic dimensions. By fostering cooperation among diverse actors, SIMONE seeks to enhance rural linkages and bolster agricultural sustainability across North-West Europe.
Total project budget: €5.4 million Financial support from Interreg NWE: €2.8 million
Arvalis (FR), Inagro (BE), Hiphen (FR), MTU (IE), Agroscope (CH), VIVES (BE), VanDenBorne (NL), CRA-W (BE), SPNA (NL), ABC (FR) and BIONALES (DE).
View the website
We are committed to meeting the evolving needs of crop researchers, and reimagined the way we articulate our Cloverfield™ Glossary with this this purpose in mind. This new intuitive format helps to parse the 70+ phenotypic traits we process routinely every year. Traits are grouped in explicit agronomic themes, with definitions and visuals to be transparent with regards to methodology. The new version places a strong emphasis on five distinct trait categories:
These categories have been carefully curated to cater to the unique needs of agronomic researchers, providing you with a more precise and comprehensive understanding of phenotypic measures available off-the-shelf for your crops.
With this new version, we are also unveiling our revamped interface for an enhanced user experience. Dive into an enriched journey of knowledge with our detailed visualizations and graphs, providing transparency into our advanced traits processing methodology.
Additionally, a powerful search functionality is now at your disposal to easily navigate the content of the glossary. Try it now!
Feel free to share this open online resource, establishing the new standards in digital phenotyping methodology for Ag research, with your fellow researchers to foster discussions within the scientific community. Moreover, we invite you to regularly check out this resource to keep up to date with the latest traits available. We eagerly anticipate collecting your feedback on this new traits' glossary. Your insights are valuable as we continue to advance in the field of agricultural research.
Cloverfield's Glossary is designed to offer definitions for the traits computed by HIPHEN. Alexis Comar, PhD describes a phenotypic trait as: "A measurable characteristic of the plant or canopy. It is the result of combining raw data obtained from sensors such as cameras, lidar, spectrometers, etc., with an analytical method for interpretation. This process serves as the means to transform raw sensor data into meaningful metrics for agronomists."
We've shared previouosly on our blog a post about what is a phenotypic trait – Read it now.
Hiphen's roots are deep into crop science, which truly sets us apart in the digital phenotyping realm. We gather a decade of experience and an unwavering commitment to agricultural research to ensure that our solutions align with your objectives.
The new and improved Cloverfield Glossary is a testament to our dedication to empowering you with the tools you need to make informed decisions and optimize your agricultural practices.
We invite you to explore the new traits' glossary and ask your Hiphen Campaign Manager should you have any question.
Stay tuned for the next Cloverfield™ features release update next April.
Sincerely,
Your Hiphen Success Team.
As you are aware, Slantrange was acquired by Hiphen last May, and since then, our primary focus has been on ensuring a seamless transition for Slantrange clients to Hiphen, providing the best possible experience throughout the process.
With this transition in mind, we would like to inform you that the Slantview data platform will be discontinued. Instead, all data processing action and results will now be delivered through Cloverfield™, Hiphen's homegrown data platform. This decision has been made in the interest of practicality and to offer our clients the best user experience.**
The merging of Slantrange and Hiphen platforms has been a comprehensive process, allowing us to draw on the strengths of both. The insights gained from this integration have been instrumental in enhancing Cloverfield, making it an all-in-one online platform that you can trust for your phenotyping needs.
We understand that change can be challenging, but we believe that this transition will bring the best of both worlds to our clients. The improvements made to Cloverfield™, based on the lessons learned from the comparison of both platforms, will undoubtedly elevate your phenotyping experience.
This decision also aligns with our upcoming strategic developments at Hiphen. We are committed to maximizing your phenotyping experience by implementing improvements in internal tools, enhancing interconnectivity, ensuring transparency, and prioritizing data security. These developments are part of our broader strategy to provide you with a cutting-edge platform that meets and exceeds your expectations.
We appreciate your understanding and cooperation during this transition. If you have any questions or concerns, please do not hesitate to reach out to our Success Team using the button below.
We are dedicated to making this transition as smooth as possible for you. Thank you for your trust in Hiphen.
Your Hiphen Success Team.
Contact Success Team
API integrations, Plot Scoring tool & new Analytics functionalities are now available in Cloverfield™, your plant phenotyping data platform.
We are thrilled to announce a significant upgrade to our Cloverfield™ online phenotyping data platform. With the release of the latest version, we are introducing new game-changing features that will enhance your experience and streamline your data management processes:
Screenshot of the Plot Scoring Tool interface in Cloverfield™.
The Plot Scoring tool is a game-changer in digital phenotyping and genotype assessment. Now, you can define your own scoring scales (numerical or categorical) and annotate plot images at the phenological stage of interest. The scores will then appear next to the digital traits allowing you to boost and scale your genotype assessments. Directly from Cloverfield, you can now deploy ground-truth annotations at scale for various applications such as plant lodging, disease resilience, plot quality and much more. The Plot Scoring Tool empowers you to augment your phenotypic information with precision and efficiency.
Rate your plots with your own rules directly in Cloverfield™ using the Plot Scoring Tool.
This new functionality allows you to select the agronomic variables you would like to compare on a scatter plot. It is designed to assist breeders in comparing digital traits, facilitating the identification of outliers and trends within your nurseries or field trials. It actually nicely complements the Plot Scoring Tool. Imagine scoring your images, saving this ground-truth as a new trait, and then inspecting how it stacks up against digital traits such as vigor, flowering, and biomass proxies directly from the Genotype Analyzer. This dynamic combination enhances your ability to glean valuable insights from your phenomics data.
Compare Plots using the Genotype Analyzer graph in Cloverfield™.
This box plot was added at the request of crop protection specialists to efficiently assess the impact of their products per experiment. It is now very simple and quick to check how your crop responded to the various treatments applied, which we refer to as modalities. It marks the first step into analytical features designed specifically for crop protection use cases and you can expect more to follow in the next year.
Identify outliers in product development trials using the Modality Profiler graph in Cloverfield™.
APIs, or Application Programming Interfaces, are a set of protocols and tools that allow different software applications to communicate and exchange data with one another. In the context of Cloverfield™, our APIs enable you to seamlessly connect your management or proprietary software to our platform, facilitating automated data transfer, including both uploads and downloads.
Global breeding companies are already using Cloverfield™ APIs to seamlessly connect their information system to ours. Newly acquired data is programmatically pushed to Cloverfield™ and results are automatically retrieved and published into their data lakes. Security is of the essence here as well, with Hiphen's security compliance reaching high standards to guarantee safe data transactions. Our documentation will guide your team of IT experts to connect and we are at your disposal to accompany you should you need any assistance from our software team.
At Hiphen, the team is committed to using our software expertise to help you achieve more season after season. We believe that the addition of Cloverfield™ APIs is a significant step towards making your data management smoother, more efficient, and more powerful.
Read the public documentation online by clicking the image link
Green area index (GAI), leaf chlorophyll content (LCC) and canopy chlorophyll content (CCC) are key variables that are closely related to crop growth. Concurrent and continuous monitoring of GAI, LCC and CCC is critical to keep consistency among variables and make decisions for field precision managements. Previous studies have developed several instruments and algorithms to monitor continuous GAI, while the autonomous monitoring of three variables simultaneously has been lacking. This study presents a novel algorithm to retrieve daily GAI, LCC and CCC from continuous directional observations acquired by a fixed and economic affordable multi-band spectrometer (6 bands covering red, red-edge and near infrared domains) and a photosynthetically active radiation (PAR) sensor in the field. It is composed of three main steps, corresponding to three crucial questions when retrieving variables under natural environments using multi-band spectrometer installed on a near-surface platform: diffuse fraction in each spectral band, radiometric calibration and diurnal sun variation of daily acquisitions. First, we estimated diffuse fraction in each spectral band from the relationship with PAR diffuse fraction based on simulations of the 6S atmospheric radiative transfer model. Second, we computed the relative value of each band to the reference of mean of measurements on all six bands from near-surface measurements, in place of absolute radiometric calibration to limit the influence of changing illumination conditions. In the third step, we combined PROSAIL canopy radiative transfer model and kernel-driven models to retrieved GAI, LCC and CCC from artificial neural network using above spectral diffuse fraction and diurnal multi-angle relative observations. The algorithm was evaluated over 43 IoTA (Internet of things for Agriculture) systems that were installed in 29 wheat fields in France from March to May 2019. Results showed that our method provides good estimates of GAI with root mean square error (RMSE) of 0.54, relative RMSE (RRMSE) of 26.95%, R2 of 0.86, LCC (RMSE = 12.06 μg/cm2, RRMSE = 33.34%, R2 = 0.52) and CCC (RMSE = 0.23 g/m2, RRMSE = 24.58%, R2 = 0.93). This study shows great potentials for concurrent estimates of GAI, LCC and CCC from continuous ground measurements. It will be useful over other vegetations or other near-surface platforms for simultaneous estimations of biophysical variables.
Advancements in plant phenotyping have brought about a remarkable transformation in the way we study and comprehend plant growth, development, and their responses to environmental influences.
With the rapid evolution of web technologies, such as cloud computing, data analytics, and real-time monitoring, Hiphen has harnessed these tools to revolutionize plant phenotyping endeavors with digital technology.
In this blog post, we will explore the significant benefits of utilizing web technologies and how they empower researchers and scientists in their plant phenotyping efforts.
Web technologies have opened exciting new possibilities in understanding plant growth and development. By integrating web-based applications with sensor data, researchers can continuously track key phenotypic traits such as plant height, leaf area, and chlorophyll content in real-time. This level of monitoring enables timely observations, early anomaly detection, and the ability to make necessary adjustments to experimental conditions, leading to more accurate and insightful findings.
One of the most impactful advantages of web technologies in plant phenotyping is the accessibility of data and collaboration opportunities it offers. Through web-based platforms, researchers can access their plant phenotyping data from anywhere with an internet connection. This fosters seamless collaboration among colleagues, allowing for easy sharing of data, methodologies, and discoveries. The ability to collaborate remotely accelerates scientific progress and promotes knowledge exchange within the scientific community.
Monitoring Tab in Hiphen's Cloverfield™ That Enable Optimal Team Collaboration
The sheer volume of data generated in plant phenotyping experiments necessitates scalable solutions. Web technologies, such as cloud infrastructure and web-based databases, provide the necessary capacity to handle large datasets efficiently. Researchers can store, process, and retrieve plant phenotyping data with ease, ensuring valuable information is readily available for analysis. Scalability also allows researchers to scale up their experiments, accommodating more plants, treatments, and replications, leading to more robust and reliable results.
Web technologies empower researchers to visualize plant phenotypic data in innovative and interactive ways. Web-based applications enable the development of visually appealing and informative data visualizations, facilitating the interpretation and communication of research findings. Interactive interfaces allow researchers to explore data, zoom in on specific time points, and extract valuable insights, thereby enhancing their understanding of plant phenotypic traits and effectively communicating their discoveries to a broader audience.
View of Hiphen's Cloverfield™ Data Platform.
Efficiency is paramount in plant phenotyping research, and web technologies offer automation capabilities that streamline workflows. Automated data collection systems integrated with web applications eliminate the need for manual data entry and recording, reducing human errors and saving time. Additionally, web-based tools can automate data analysis and reporting processes, enabling researchers to focus on data interpretation, hypothesis testing, and driving further research advancements.
The integration of web technologies with other cutting-edge technologies amplifies the capabilities of plant phenotyping research. By combining web technologies with remote sensing, image analysis, and machine learning, researchers can unlock new insights and gain a deeper understanding of plant phenotypic traits. This integration allows for the utilization of diverse data sources, advanced analytical techniques, and the development of predictive models for plant growth and responses, ultimately enhancing decision-making in agriculture and breeding applications.
In conclusion, the power of web technologies in advanced plant phenotyping cannot be overstated. The accessibility, real-time monitoring, scalability, advanced visualization, automation, and integration capabilities offered by web technologies empower researchers to make groundbreaking strides in their research. By embracing these cutting-edge tools, researchers can drive innovation, advance scientific understanding, and contribute significantly to sustainable agriculture. Embrace the power of web technologies and revolutionize your plant phenotyping research today.
Grab a time from one of our experts' Calendar below to discover more.
Sincerely,
Your Hiphen Team.