The objective of the LITERAL project is to develop, implement and evaluate the performance of a light, portable and affordable phenotyping system. It uses a set of imaging sensors, controlled by a user-friendly interface. The data will be automatically referenced and processed on a cloud platform. Radiative transfer and deep learning algorithms will be implemented to transform the acquired images into agronomic variables of interest. A small series of LITERAL systems will be produced and taken in hand by the partners to evaluate it on different cases of studies and to prepare its industrialization…
The PHENOME project aims to equip the French scientific community with an infrastructure able to measure the agronomic characteristics of plants subjected to various climate scenarios and technical itineraries associated with global change, using precise and high throughput methods.Phenome develops an infrastructure and a suite of methods for characterising hundreds of genotypes under environmental scenarios of climate changes…
In the framework of the IOF2020 European project, ARVALIS and Orange are in charge of a use case dedicated to wheat crop management. Experiments have been set in the Beauce region and in the South East to demonstrate the feasibility of such service and evaluate the added value in comparison with more classical practices…
IOTA (Internet of Things in Agriculture) is a collaborative project that was launched in November 2017 by Hiphen, Bosch, Agrial and INRA EMMAH. It has the ambition to develop a complete crop management system composed of a set of plot-level sensors, grouped together in a network, transmitting their measurements continuously to a data management platform. The crops of interest are wheat and lettuce.
One of the innovations of the project lies in the transformation of data and measurements into agronomic values and their spatialization. The information collected will be analyzed and will feed in real-time the decision-making tools, thus improving the performance of the crop management system.
In the context of agriculture digitalization, the Colza* Digital project was launched to construct a pilot real-time monitoring system for rapeseed crops throughout the growth cycle, using satellite sensors and connected objects in plots. On this project led by Terres Inovia, with the financial support of Sofiproteol, organizations specialized in agronomy, remote sensing and digital technology have come together to take on the challenge. Hiphen’s contribution consists in implementing Field Sensor data acquisition and processing throughout this project.
“Farmers will thus be able to monitor their plots more closely, agricultural advisers will be able to perform a spatialized inventory of crops in their area of activity, and cooperatives will be able to develop a territorial vision of production” Terres Inovia.
Launched in 2011, the AKER research program involves 11 public and private partners with the goal of improving the competitiveness of French sugar beet in a global market largely dominated by sugar cane. The goal is to double the annual increase in sugar yield per hectare (4% vs 2%) by 2020 by carrying research on the most advanced beet genome sequencing, genotyping and phenotyping technologies.
In this ambitious program, CAPTE members designed a methodology assessing sugar beet resistance to Cercospora Leaf Spot disease under field conditions using an UAV-embedded multispectral camera.
The rising adoption of high and medium rate phenotyping systems is generating an increasing amount of data, and therefore an increasing need for data processing. CAPTE members decided to join efforts in order to develop a platform for operation management and analysis of high-throughput phenotyping data.
This project was carried by INRA, ARVALIS and HIPHEN in 2018, through services provided by the companies SOGILIS (via the project Plant2Pro PROCROP) and EPHESIA (via the project PHENOME).
The goal of P2S2 – Products for Sentinel2- is to build a large database that serves as a validation set of SENTINEL2 image processing algorithms. The variables of interest are: LAI, chlorophyll content, and green cover fraction.
The objective of the project is to explore the genetic variability that exists in the varieties of three species of straw cereals: soft wheat, durum wheat and barley. The focus of the study is to analyze the ability of straw cereals to compensate the reduction in tillering (and therefore the number of ears per square meter) by an increase of ears fertility (number of grains per ear).
Our goal is to propose an analysis method of the varietal trials to explicitly identify the varietal differences for the phenotypic plasticity of this trait. CAPTE contributes to the project through the development of an ears counting technique from image acquisition systems and processing algorithms.
In the Western European context, the genetic or cultural parades against the biotic or abiotic stresses suffered by straw cereals are essentially aimed at preventing the appearance of symptoms. However, at equivalent symptoms, tolerant crops will show lower yield losses, a behavior of interest to breeders and producers.
The aim of the project is to provide breeders with answers and methods to integrate the concept of tolerance into their work: physiological explanations, screening methodology. CAPTE contributes by processing phenotyping data acquired at PhenoField.
This project aims at developing phenotyping technologies for monitoring field vegetables, and in particular the potato crop. This project is carried out by ARVALIS and uses the ALPHI® system, an integrated tool that allows crop characterization from acquisition made by imaging or non-imaging sensors.
The objective is to improve the effectiveness of varietal assessment (DHS, VATE) and the information available to stakeholders on the performance of varieties under various production conditions. ARVALIS provides its phenotyping facilities to contribute to the development of new phenotyping methods for varietal evaluation.
SmartAgriHub is a project that brings together 164 partners in the agri-food sector. Its objective is to contribute to the digitalization of European agriculture by structuring an ecosystem of excellence for innovation that brings sustainability and performance. For this purpose, ARVALIS uses remote sensing models and solutions for the observation of cultures for which CAPTE is associated.
The aim of SolACE – Solutions for Improving Agroecosystem and Crop Efficiency for Water and Nutrient Use – is to help European agriculture to cope with the changes in the industry. This includes the increased variability of rainfall and the reduced availability of nitrogen and phosphorus. CAPTE contributes via the processing of phenotyping data acquired on the platforms (PhenoField, Phénomobile)