Global Wheat Head Detection 2021: an improved dataset for benchmarking wheat head detection methods

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 agricultural science communities. From this first experience, a few avenues for improvements have been identified regarding data size, head diversity, and label reliability. To address these issues, the 2020 dataset has been reexamined, relabeled, and complemented by adding 1722 images from 5 additional countries, allowing for 81,553 additional wheat heads. We now release in 2021 a new version of the Global Wheat Head Detection dataset, which is bigger, more diverse, and less noisy than the GWHD_2020 version

Architectural response of wheat cultivars to row spacing reveals altered perception of plant density

Achieving novel improvements in crop management may require changing interrow distance in cultivated fields. Such changes would benefit from a better understanding of plant responses to the spatial heterogeneity in their environment. Our work investigates the architectural plasticity of wheat plants in response to increasing row spacing and evaluates the hypothesis of a foraging behavior in response to neighboring plants. A field experiment was conducted with five commercial winter wheat cultivars possessing unique architectures, grown under narrow (NI, 17.5 cm) or wide interrows (WI, 35 cm) at the same population density (170 seeds/m2). We characterized the development (leaf emergence, tillering), the morphology (dimension of organs, leaf area index), and the geometry (ground cover, leaf angle, organ spreading, and orientation). All cultivars showed a lower number of emerged tillers in WI compared to NI, which was later compensated by lower tiller mortality and by shoots producing larger blades. The rate of leaf emergence and the final leaf number were higher in WI compared to NI, except for one cultivar. Around the start of stem elongation, pseudo-stems were more erect in WI, while around the time of flowering, stems were more inclined and leaves were more planophile. Cultivars differed in their degrees of responses, with one appearing to prospect more specifically within the interrow space in WI treatment. Altogether, our results suggest that altering interrow distance leads to changes in the perceived extent of competition by plants, with responses first mimicking the effect of a higher plant density and later the effect of a lower plant density. Only one cultivar showed responses that suggested a perception of the heterogeneity of the environment. These findings improve our understanding of plant responses to spatial heterogeneity and provide novel information to simulate light capture in plant 3D models, depending on cultivar behavior

CAN-EYE, logiciel de traitement d'images pour l'estimation de l'indice foliaire.

Nous présentons le freeware CAN-EYE, logiciel de traitement d’images pourl’estimation des variables de structure des couverts végétaux comme la fraction de trou, le LAIou le FAPAR à partir de la prise de photographies numériques dans la végétation. Dans unpremier temps, nous décrivons le fonctionnement du logiciel et nous définissons lesdifférentes variables estimées à partir de la fraction de trou, puis nous terminons par deuxexemples de résultats qui montrent l’aptitude et l’intérêt de la photographie numérique et deCAN-EYE pour la mesure de ces variables

Geometric models for plant leaf area estimation from 3D point clouds: a comparative study

National audienceMeasuring leaf areas is a critical task in plant biology. Automatic leaf area estimation from a 3D point cloud is usually done via meshing techniques or parametric surface modeling. However, there is currently no consensus on the best method because of little comparative evaluation of the techniques. In this paper, we provide evidence about the performance of each approach through a comparative study of four meshing methods and two parametric model fitting techniques applied in the plant sciences. We identified six criteria on either the leaf shape (length/width ratio, curviness, concavity) or the acquisition process (sampling density, noise, holes) which can affect the robustness of the six selected methods. We generated synthetic point clouds covering each criterion and used them to qualitatively and quantitatively evaluate the six approaches. This study allows us to highlight the benefits and drawbacks of each method and evaluate its appropriateness in a given scenario

Phenotypage en plein champ : apports des techniques basées sur les propriétés spectrales du couvert

AGAP : GE2popNational audienceAccéder plus facilement à des traits phénotypiques plus nombreux et suivre leur dynamique via des approches non destructives s’avère indispensable pour le développement de disciplines telles que l’agronomie, la génétique ou l’écophysiologie. Le couplage entre les progrès générés par ces connaissances disciplinaires (connaissance du génome, biologie de la plante entière, capacités adaptatives de la diversité génétique en interaction avec l’environnement), est essentiel pour contribuer à la définition des systèmes de culture de demain les plus appropriés. Le développement de nouvelles techniques de phénotypage s’inscrit dans ce cadre. Dans cette présentation nous étudierons les potentialités des méthodes de phénotypage basées sur l’utilisation des propriétés spectrales du couvert

Parameterising wheat leaf and tiller dynamics for faithful reconstruction of wheat plants by structural plant models

International audienceStructural 3D plant models aim at mimicking the dynamics of plant and crop structure based on experimental data. Such models can be interfaced with physical models to investigate plant-environment interactions. This work aimed at defining functions that represent the leaf and tiller development of individual wheat plants, and that could be fitted to the specific traits produced in a broad range of situations.A dataset of the dynamics of wheat plant (Triticum aestivum) architecture was collected for 55 experimental situations, including 11 growing seasons, three sowing densities, three sowing dates, and 13 commercial cultivars. Data were analysed to identify conserved patterns in the dynamics of leaf emergence and of tiller emergence and senescence.The broad range of conditions tested allowed us to evaluate the robustness of relationships proposed in previous studies and to identify novel patterns. Amongst them, we observed: (i) that leaf emergence dynamics may follow either a linear or a bilinear pattern for the same genotype. When a change in phyllochron occurred, it coincided with the initiation of the flag leaf; (ii) the delay between leaf and tiller emergence was not constant, but increased very regularly for successive phytomers; (iii) the number of leaves emerged at tillering cessation decreased with plant density but depended also on the final number of leaves on the main stem (MS) and marked differences existed between cultivars. Finally, we defined functions representing leaf and tiller dynamics with parameters that have a simple botanical interpretation and are easy to derive from field measurements. Assessing plant density, crop leaf stage at 5–6 dates and tiller population at 2 dates during the cycle provide the required data.This study defines a rationale to analyse and represent the dynamics of the architecture of individual wheat plants. The method can be used to determine the dynamics of architecture in 3D models and should be transposable to a wide range of cereal species

Modeling the spatial distribution of plants on the row for wheat crops: Consequences on the green fraction at the canopy level

This work investigates the spatial distribution of wheat plants and its consequences on the canopy structure.A set of RGB images were taken from nadir on a total 14 plots showing a range of sowing densities,cultivars and environmental conditions. The coordinates of the plants were extracted from RGB images.Results show that the distance between-plants along the row follows a gamma distribution law, with nodependency between the distances. Conversely, the positions of the plants across rows follow a Gaussiandistribution, with strongly interdependent. A statistical model was thus proposed to simulate the possibleplant distribution pattern. Through coupling the statistical model with 3D Adel-Wheat model, theimpact of the plant distribution pattern on canopy structure was evaluated using emerging propertiessuch as the green fraction (GF) that drives the light interception efficiency. Simulations showed thatthe effects varied over different development stages but were generally small. For the intermediate developmentstages, large zenithal angles and directions parallel to the row, the deviations across the row ofplant position increased the GF by more than 0.1. These results were obtained with a wheat functionalstructuralmodel that does not account for the capacity of plants to adapt to their local environment.Nevertheless, our work will extend the potential of functional-structural plant models to estimate theoptimal distribution pattern for given conditions and subsequently guide the field management practices

Valoriser les tolérances variétales pour faire face aux carences azotées

Valoriser les tolérances variétales pour faire face aux carences azotées. Azote et innovation : Quels leviers pour concilier productivité, qualité et autonomie des systèmes céréaliers

High-Throughput Phenotyping of Plant Height: Comparing Unmanned Aerial Vehicles and Ground LiDAR Estimates

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 unmanned ground vehicle. UAV equipped with a high resolution RGB camera was flying the experiment several times to retrieve the digital surface model from structure from motion techniques. Both techniques provide a 3D dense point cloud from which the plant height can be estimated. Plant height first defined as the z-value for which 99.5% of the points of the dense cloud are below. This provides good consistency with manual measurements of plant height (RMSE D 3.5 cm) while minimizing the variability along each microplot. Results show that LiDAR and structure from motion plant height values are always consistent. However, a slight underestimation is observed for structure from motion techniques, in relation with the coarser spatial resolution of UAV imagery and the limited penetration capacity of structure from motion as compared to LiDAR. Very high heritability values (H2 > 0.90) were found for both techniques when lodging was not present. The dynamics of plant height shows that it carries pertinent information regarding the period and magnitude of the plant stress. Further, the date when the maximum plant height is reached was found to be very heritable (H2 > 0.88) and a good proxy of the flowering stage. Finally, the capacity of plant height as a proxy for total above ground biomass and yield is discussed

Use of geostationary satellite thermal infrared data to monitor surface exchanges at local scale over heterogeneous landscape: Application to Meteosat 8 data

International audienceA SVAT calibration methodology based on the optimization of surface brightness temperature has been developed (Coudert et al., 2006a; 2006b, 2007) and validated at field scale in the framework of the Alpilles-ReSeDA ([1]; http://www.avignon.inra.fr/reseda/base/) experiment. This methodology has been extended at regional scale and applied to MSG/Meteosat8 thermal infrared data. MSG/SEVIRI instrument provides the Land Surface Temperature (LST) every 15mn with a spatial resolution of about 3kmx5km over France. A model spatialization is proposed, based on a Geographic Information System in order to estimate the surface temperature at the MSG pixel scale from local SVAT simulation. The estimation of the surface water and energy fluxes and of the soil water content at a finer resolution are provided from the calibration methodology applied at the MSG pixel scale to the the spatialized model. These methods have been applied in the framework of the CITRAM experimental program in order to monitor soil water content and irrigation in agricultural zones. A comparison between methodologies is presented. The validation is done with local soil moisture measurements acquired in different instrumented fields over the region and with high spatial resolution surface temperature estimation from ASTER/TERRA satellite dat