Literal® – agile field imaging
Literal® is Hiphen’s portable phenotyping tool for high-resolution plant imaging in the field, ideal for cocoa. Easy to use, it captures pod counts, flowers, diseases, and height.
Hiphen is a French agtech company specializing in digital plant phenotyping. We have strong expertise in drone data processing for agricultural fields—ranging from crop trials for breeders and biostimulant companies to orchard monitoring for various tree species.
Our capabilities focus on crop monitoring, stress detection, and yield forecasting using drone imagery.
To support this expertise, we offer PhenoScale® (www.hiphen-phenoscale.com), an end-to-end service that combines drone image capture, automated trait extraction, and cloud-based analytics. All processed outputs are centralized and accessible through Cloverfield™, our online phenotyping platform designed to support in-depth analysis, project management, and long-term data tracking.
This solution is optimized for speed, scalability, and ease of use. It transforms raw drone imagery into actionable plant data through a streamlined “capture → upload → analyze” workflow—empowering researchers, breeders, and agronomists to make informed decisions quickly and efficiently.
With proven experience in crops such as coffee, banana, peach, apple, and other tree species, we believe this provides a strong foundation to support your work in cocoa as well.
Hiphen has strong expertise in drone-based plant analysis, enabling rapid, accurate, and high-throughput field phenotyping. In previous projects, we have developed a wide range of agronomic traits to assess yield potential and characterize tree resilience against diseases. These include fruit count, disease symptom detection, flowering, vigor, plant height, and trunk volume. These traits have been validated on multiple fruit tree species—such as apple, prune, and pear—and can be adapted to cocoa through a Proof of Concept (PoC).
We are drone-agnostic, meaning we can work with a variety of drone hardware. Depending on Mondelez’s operational constraints, data capture can be either internalized or outsourced to local service providers—a common approach in tropical crops like coffee and banana.
We propose an initial phase focused on training drone pilots to capture high-quality imagery specific to cocoa. This phase will involve close collaboration to design and refine the data acquisition protocols. We foresee two primary protocol categories:
In both cases, adjustments to data acquisition protocols may be required. Hiphen will provide technical support to address any challenges and help establish reliable, repeatable workflows.
Once the protocols are validated and meet Mondelez’s expectations, Hiphen brings strong expertise in scaling data processing to deliver fast, cost-efficient, and actionable analytics. We believe timely access to data—both for field trials and data analysts—is essential for real-time decision-making and long-term analysis.
With a proven track record in custom crop analytics and collaborative R&D, Hiphen offers both scientific rigor and practical field adaptability.
Below are some of our relevant references:
- INRAE: Bertrand Muller ([email protected] – Phenet project, orchards), Evelyne Costes ([email protected] – Apple trees)
- University of Queensland: Scott Chapman ([email protected])
- Moët & Chandon: Felix Boquet ([email protected])
- Phenet project: https://www.phenet.eu/