Baret Frederic

Baret Frederic
French National Institute for Agriculture, Food, and Environment (INRAE) | INRAE · Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes (EMMAH)

PhD

About

545
Publications
183,644
Reads
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33,074
Citations
Additional affiliations
July 1986 - present
French National Institute for Agriculture, Food, and Environment (INRAE)
Position
  • Directeur de recherches
Description
  • Devloment of methods for crop characterization. Application to plant phenotyping, environmental monitoring and decision making in agriculture
January 1985 - May 2014
French National Institute for Agriculture, Food, and Environment (INRAE)
Position
  • Directeur de Recherches
May 1981 - December 1984
ARVALIS Institut du végétal
Position
  • Ingenieur régional
Education
June 1986
Université Paris-Sud 11
Field of study
  • Remote sensing of crops

Publications

Publications (545)
Article
The objective of this study is to evaluate the performances of a semi-empirical approach based on the Bayesian theory to retrieve Green Area Index (GAI) from multiple decametric satellites. It is designed to overcome some limitations in existing Radiative Transfer Model (RTM) inversion methods, including the high dimensionality of the inverse probl...
Article
The definition of LAI (Leaf Area Index) is important when deriving it from reflectance observation for model application and validation. Canopy reflectance and the corresponding quantities of LAI, PAI (Plant Area Index), GAI (Green Area Index) and effective GAI (GAIeff) are first calculated using a 3D radiative transfer model (RTM) applied to 3D wh...
Preprint
The pixels segmentation of high resolution RGB images into background, green vegetation and senescent vegetation classes is a first step often required before estimating key traits of interest including the vegetation fraction, the green area index, or to characterize the sanitary state of the crop. We developed the SegVeg model for semantic segmen...
Article
Full-text available
With the widespread use of high-throughput phenotyping systems, growth process data are expected to become more easily available. By applying genomic prediction to growth data, it will be possible to predict the growth of untested genotypes. Predicting the growth process will be useful for crop breeding, as variability in the growth process has a s...
Article
Full-text available
There is currently a strong societal demand for sustainability, quality, and safety in bread wheat production. To address these challenges, new and innovative knowledge, resources, tools, and methods to facilitate breeding are needed. This starts with the development of high throughput genomic tools including single nucleotide polymorphism (SNP) ar...
Article
Full-text available
Multispectral observations from unmanned aerial vehicles (UAVs) are currently used for precision agriculture and crop phenotyping applications to monitor a series of traits allowing the characterization of the vegetation status. However, the limited autonomy of UAVs makes the completion of flights difficult when sampling large areas. Increasing the...
Preprint
Full-text available
With the widespread use of high-throughput phenotyping systems, growth process data are expected to become more easily available. By applying genomic prediction to growth data, it will be possible to predict the growth of untested genotypes. Predicting the growth process will be useful for crop breeding, as variability in the growth process has a s...
Article
Full-text available
The Global Wheat Head Detection (GWHD) dataset was created in 2020 and has assembled 193,634 labelled wheat heads from 4700 RGB images acquired from various acquisition platforms and 7 countries/institutions. With an associated competition hosted in Kaggle, GWHD_2020 has successfully attracted attention from both the computer vision and agricultura...
Article
Full-text available
Plant growth rhythm in structural traits is important for better understanding plant response to the ever-changing environment. Terrestrial laser scanning (TLS) is a well-suited tool to study structural rhythm under field conditions. Recent studies have used TLS to describe the structural rhythm of trees, but no consistent patterns have been drawn....
Article
Full-text available
Early-stage plant density is an essential trait that determines the fate of a genotype under given environmental conditions and management practices. The use of RGB images taken from UAVs may replace the traditional visual counting in fields with improved throughput, accuracy, and access to plant localization. However, high-resolution images are re...
Article
Several crops bear reproductive organs (RO) at the top of the canopy after the flowering stage, such as ears for wheat, tassels for maize, and heads for sunflowers. RO present specific architecture and optical properties as compared to leaves and stems, which may impact canopy reflectance. This study aims to understand and quantify the influence of...
Article
Full-text available
The canopy bidirectional reflectance distribution function (BRDF) plays a pivotal role in estimating the biophysical parameters of plants, whereas soil background anisotropy creates challenges for their retrieval. Soil optical properties affect canopy anisotropic characteristics, especially in open-canopy areas. However, the remote sensing of backg...
Preprint
Full-text available
Early-stage plant density is an essential trait that determines the fate of a genotype under given environmental conditions and management practices. The use of RGB images taken from UAVs may replace traditional visual counting in fields with improved throughput, accuracy and access to plant localization. However, high-resolution (HR) images are re...
Preprint
Full-text available
The Global Wheat Head Detection (GWHD) dataset was created in 2020 and has assembled 193,634 labelled wheat heads from 4,700 RGB images acquired from various acquisition platforms and 7 countries/institutions. With an associated competition hosted in Kaggle, GWHD has successfully attracted attention from both the computer vision and agricultural sc...
Preprint
Full-text available
Data competitions have become a popular approach to crowdsource new data analysis methods for general and specialized data science problems. In plant phenotyping, data competitions have a rich history, and new outdoor field datasets have potential for new data competitions. We developed the Global Wheat Challenge as a generalization competition to...
Preprint
Full-text available
Plants density is a key information on crop growth. Usually done manually, this task can beneficiate from advances in image analysis technics. Automated detection of individual plants in images is a key step to estimate this density. To develop and evaluate dedicated processing technics, high resolution RGB images were acquired from UAVs during sev...
Article
Full-text available
Canopy light interception determines the amount of energy captured by a crop, and is thus critical to modelling crop growth and yield, and may substantially contribute to the prediction uncertainty of crop growth models (CGMs). We thus analyzed the canopy light interception models of the 26 wheat (Triticum aestivum) CGMs used by the Agricultural Mo...
Article
Continuous and accurate ground measurements of the fraction of absorbed (fAPAR) or intercepted (fIPAR) photosynthetically active radiation by green canopy components is important to monitor canopy functioning. fAPAR and fIPAR are sensitive to illumination conditions and non-green components during the senescence stage. While several methods have be...
Article
Full-text available
Plant phenomics is a new avenue for linking plant genomics and environmental studies, thereby improving plant breeding and management. Remote sensing techniques have improved high-throughput plant phenotyping. However, the accuracy, efficiency, and applicability of three-dimensional (3D) phenotyping are still challenging, especially in field enviro...
Article
Many plant species have distinct optical properties between upper and lower leaf faces. These differences between faces are mainly attributed to the non-homogeneous distribution of absorbing and scattering materials within the leaf depth as well as particular surface features of both epidermises. We proposed the FASPECT model which is an evolution...
Article
Full-text available
The detection of wheat heads in plant images is an important task for estimating pertinent wheat traits including head population density and head characteristics such as health, size, maturity stage, and the presence of awns. Several studies have developed methods for wheat head detection from high-resolution RGB imagery based on machine learning...
Article
Full-text available
Selection of sugar beet (Beta vulgaris L.) cultivars that are resistant to Cercospora Leaf Spot (CLS) disease is critical to increase yield. Such selection requires an automatic, fast, and objective method to assess CLS severity on thousands of cultivars in the field. For this purpose, we compare the use of submillimeter scale RGB imagery acquired...
Preprint
Full-text available
Detection of wheat heads is an important task allowing to estimate pertinent traits including head population density and head characteristics such as sanitary state, size, maturity stage and the presence of awns. Several studies developed methods for wheat head detection from high-resolution RGB imagery. They are based on computer vision and machi...
Data
Data connected to this study can be found at the 4TU Centre for Research Data: https://doi.org/10.4121/uuid:c12affd8-779c-47e4-a93c-ea0afb939237
Article
Full-text available
The Copernicus Global Land Service (CGLS) provides global time series of leaf area index (LAI), fraction of absorbed photosynthetically active radiation (fAPAR) and fraction of vegetation cover (fCOVER) data at a resolution of 300 m and a frequency of 10 days. We performed a quality assessment and validation of Version 1 Collection 300 m products t...
Article
Full-text available
The capacity of canopy light interception is a key functional trait to distinguish the phenotypic variation over genotypes. High-throughput phenotyping canopy light interception in the field, therefore, would be of high interests for breeders to increase the efficiency of crop improvement. In this research, the Digital Plant Phenotyping Platform(D3...
Article
A physically based metamodel is proposed to describe the dependency of canopy reflectance on the wavelength, leaf and soil optical properties. The four-stream solution is first applied to describe the interaction between the soil background and the vegetation layers. This leads to the calibration of four terms for a given canopy structure, observat...
Article
Full-text available
Accurate and timely observations of wheat phenology and, particularly, of heading date are instrumental for many scientific and technical domains such as wheat ecophysiology, crop breeding, crop management or precision agriculture. Visual annotation of the heading date in situ is a labour-intensive task that may become prohibitive in scientific and...
Article
Full-text available
Leaf area index (LAI) is a critical vegetation structural variable and is essential in the feedback of vegetation to the climate system. The advancement of the global Earth Observation has enabled the development of global LAI products and boosted global Earth system modeling studies. This overview provides a comprehensive analysis of LAI field mea...
Article
Full-text available
The extraction of desirable heritable traits for crop improvement from high-throughput phenotyping (HTP) observations remains challenging. We developed a modeling workflow named "Digital Plant Phenotyping Platform" (D3P), to access crop architectural traits from HTP observations. D3P couples the Architectural model of DEvelopment based on L-systems...
Article
Full-text available
The dynamics of the Green Leaf Area Index (GLAI) is of great interest for numerous applications such as yield prediction and plant breeding. We present a high-throughput model-assisted method for characterizing GLAI dynamics in maize (Zea mays subsp. mays) using multispectral imagery acquired from an Unmanned Aerial Vehicle (UAV). Two trials were c...
Article
Full-text available
Total above-ground biomass at harvest and ear density are two important traits that characterize wheat genotypes. Two experiments were carried out in two different sites where several genotypes were grown under contrasted irrigation and nitrogen treatments. A high spatial resolution RGB camera was used to capture the residual stems standing straigh...
Poster
Full-text available
Hardware Software Structural traits Leaf traits Dynamics of traits Conclusion High resolution RGB camera + 6000 x 4000 pixels + Pixel size: 3.93 µm + Focal length: 30-60 mm + Weight: 500 g with lens Footprint 4,2mm Footprint 8mm AIRPHEN multispectral camera + 1080 x 960 pixels + 6 configurable bands + Pixel size: 3.04 µm + Focal length: 4.2-8 mm +...
Presentation
Forests cover about one third on the Earth’s land surface and provide a number of ecosystem services. Among these, forest ecosystems play an essential role within the global carbon dynamics due to their continuous exchange of CO2 with the atmosphere through photosynthesis. For this reason, understanding and quantifying their imprint on the global c...
Data
VALERI : a network of sites and methodology for the validation of medium spatial resolution land products
Article
Full-text available
Wheat ear density estimation is an appealing trait for plant breeders. Current manual counting is tedious and inefficient. In this study we investigated the potential of convolutional neural networks (CNNs) to provide accurate ear density using nadir high spatial resolution RGB images. Two different approaches were investigated, either using the Fa...
Presentation
Terrestrial ecosystems play an essential role in the carbon cycle as they exchange CO2 with the atmosphere through photosynthesis and respiration, but the exact magnitude of these processes is still largely unknown. The uncertainties in the carbon cycle modeling are related to the inadequate representation of terrestrial photosynthesis, due to an i...
Chapter
Phenotyping in breeding trials is the basis for the selection of new varieties of food, feed and fibre crops that support the continued growth of world population. In addition to economic yield, breeders measure many phenotypes (also called traits) associated with the adaptation of these crops, such as the time of flowering, the height of the crop...
Article
Surface soil moisture content (SMC) is known to impact soil reflectance at all wavelengths of the solar spectrum. As a consequence, many semi-empirical methods aim at inferring SMC from soil reflectance, but very few rely on physically-based models. This article presents a multilayer radiative transfer model of soil reflectance called MARMIT (multi...
Article
Full-text available
The recent emergence of unmanned aerial vehicles (UAV) has opened a new horizon in vegetation remote sensing, especially for agricultural applications. However, the benefits of UAV centimeter-scale imagery are still unclear compared to coarser resolution data acquired from satellites or aircrafts. This study aims (i) to propose novel methods for re...
Article
Progress in remote sensing and robotic technologies decreases the hardware costs of phenotyping. Here, we first review cost-effective imaging devices and environmental sensors, and present a trade-off between investment and manpower costs. We then discuss the structure of costs in various real-world scenarios. Hand-held low-cost sensors are suitabl...
Article
Full-text available
Land Surface Phenology (LSP) and Leaf Area Index (LAI) are important variables that describe the photosynthetically active phase and capacity of vegetation. Both are derived on the global scale from optical satellite sensors and require robust validation based on in situ sensors at high temporal resolution. This study assesses the PAI Autonomous Sy...
Article
Full-text available
Leaf rolling in maize crops is one of the main plant reactions to water stress that can be visually scored in the field. However, leaf-scoring techniques do not meet the high-throughput requirements needed by breeders for efficient phenotyping. Consequently, this study investigated the relationship between leaf-rolling scores and changes in canopy...
Article
Full-text available
Background: Leaf biochemical composition corresponds to traits related to the plant state and its functioning. This study puts the emphasis on the main leaf absorbers: chlorophyll a and b ([Formula: see text]), carotenoids ([Formula: see text]), water ([Formula: see text]) and dry mater ([Formula: see text]) contents. Two main approaches were used...
Article
Full-text available
Ce numéro comprend les articles correspondant aux présentations du Colloque Casdar 2018.
Article
Full-text available
The capacity of LiDAR and Unmanned Aerial Vehicles (UAVs) to provide plant height estimates as a high-throughput plant phenotyping trait was explored. An experiment over wheat genotypes conducted under well watered and water stress modalities was conducted. Frequent LiDAR measurements were performed along the growth cycle using a phénomobile unmann...
Preprint
Leaf rolling in maize crops is one of the main plant reactions to water stress that may be visually scored in the field. However, the leaf scoring did not reach the high-throughput desired by breeders for efficient phenotyping. This study investigates the relationship between leaf rolling score and the induced canopy structure changes that may be a...
Presentation
Full-text available
The objective of this study is to assess the performance of physically-based and empirically-based methods to retrieve biophysical variables over either generic crops or specific crop types using Landsat-8 imagery. The following methods are considered: inversion of PROSPECT+SAIL using machine learning algorithms and several empirical machine learni...