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High-Throughput Measurements of Stem Characteristics to Estimate Ear density and Above-Ground Biomass

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Plant Phenomics 2019年第1期1卷 80-89页

作者： Xiuliang Jin Simon Madec Dan Dutartre benoit de solan Alexis Comar Frédéric Baret INRA EMMAH UMR 1114228 route de l’A′erodrome84914 AvignonFrance Institute of Crop Sciences Chinese Academy of Agricultural Sciences/Key Laboratory of Crop Physiology and EcologyMinistry of AgricultureBeijing 100081China HIPHEN Rue Charrue84000 AvignonFrance ARVALIS-Institut du V′eg′etal Station Exp′erimentale91720 BoignevilleFrance

Total above-ground biomass at harvest and ear density are two important traits that characterize wheat *** 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 straight after the cutting by the combine machine during *** provided a ground spatial resolution better than 0.2 mm.A Faster Regional Convolutional Neural Network(Faster-RCNN)deep-learning model was first trained to identify the stems cross *** showed that the identification provided precision and recall close to 95%.Further,the balance between precision and recall allowed getting accurate estimates of the stem density with a relative RMSE close to 7%and robustness across the two experimental *** estimated stem density was also compared with the ear density measured in the field with traditional methods.A very high correlation was found with almost no bias,indicating that the stem density could be a good proxy of the ear *** heritability/repeatability evaluated over 16 genotypes in one of the two experiments was slightly higher(80%)than that of the ear density(78%).The diameter of each stem was computed from the profile of gray values in the extracts of the stem cross *** show that the stem diameters follow a gamma distribution over eachmicroplot with an average diameter close to ***,the biovolume computed as the product of the average stem diameter,the stem density,and plant height is closely related to the above-ground biomass at harvest with a relative RMSE of 6%.Possible limitations of the findings and future applications are finally discussed.

关键词： Biomass straight finally

Analyzing Changes in Maize Leaves Orientation due to GxExM Using an Automatic Method from RGB Images

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Plant Phenomics 2023年第2期5卷 239-252页

作者： Mario Serouart Raul Lopez-Lozano Gaëtan Daubige Maëva Baumont Brigitte Escale benoit de solan Frédéric Baret Arvalis Institut du végétal228route de l’aérodrome-CS 4050984914 Avignon Cedex 9France INRAE Avignon UniversitéUMR EMMAHUMT CAPTE228route de l’aérodrome-CS 4050984914 Avignon Cedex 9France Arvalis Ecophysiology21 Chemin de Pau64121 MontardonFrance

The sowing pattern has an important impact on light interception efficiency in maize by determining the spatial distribution of leaves within the *** orientation is an important architectural trait determining maize canopies light *** studies have indicated how maize genotypes may adapt leaves orientation to avoid mutual shading with neighboring plants as a plastic response to intraspecific *** goal of the present study is 2-fold:firstly,to propose and validate an automatic algorithm(Automatic Leaf Azimuth Estimation from Midrib detection[ALAEM])based on leaves midrib detection in vertical red green blue(RGB)images to describe leaves orientation at the canopy level;and secondly,to describe genotypic and environmental differences in leaves orientation in a panel of 5 maize hybrids sowing at 2 densities(6 and 12 plants.m^(−2))and 2 row spacing(0.4 and 0.8 m)over 2 different sites in southern *** ALAEM algorithm was validated against in situ annotations of leaves orientation,showing a satisfactory agreement(root mean square[RMSE]error=0.1,R^(2)=0.35)in the proportion of leaves oriented perpendicular to rows direction across sowing patterns,genotypes,and *** results from ALAEM permitted to identify significant differences in leaves orientation associated to leaves intraspecific *** both experiments,a progressive increase in the proportion of leaves oriented perpendicular to the row is observed when the rectangularity of the sowing pattern increases from 1(6 plants.m^(−2),0.4 m row spacing)towards 8(12 plants.m^(−2),0.8 m row spacing).Significant differences among the 5 cultivars were found,with 2 hybrids exhibiting,systematically,a more plastic behavior with a significantly higher proportion of leaves oriented perpendicularly to avoid overlapping with neighbor plants at high *** in leaves orientation were also found between experiments in a squared sowing pattern(6 plants.m^(−2),0.4 m

关键词： cultivar spacing pattern

Self-Supervised Plant Phenotyping by Combining Domain Adaptation with 3D Plant Model Simulations: Application to Wheat Leaf Counting at Seedling Stage

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Plant Phenomics 2023年第2期5卷 226-238页

作者： Yinglun Li Xiaohai Zhan Shouyang Liu Hao Lu Ruibo Jiang Wei Guo Scott Chapman Yufeng Ge benoit de solan Yanfeng Ding Frédéric Baret Plant Phenomics Research Centre Academy for Advanced Interdisciplinary StudiesJiangsu Collaborative Innovation Center for Modern Crop ProductionNanjing Agricultural UniversityNanjingChina Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhanChina Graduate School of Agricultural and Life Sciences The University of Tokyo1-1-1 Midori-choNishitokyo CityTokyoJapan School of Agriculture and Food Sciences The University of QueenslandSt.LuciaQueensland 4072Australia department of Biological Systems Engineering University of Nebraska-LincolnLincolnNebraska 68583United States INRAE Avignon UniversitéUMR EMMAHUMT CAPTE228route de l’aérodrome-CS 4050984914 Avignon Cedex 9France ARVALIS Institut du Végétal 3 Rue Joseph et Marie Hackin75116 ParisFrance

The number of leaves at a given time is important to characterize plant growth and *** this work,we developed a high-throughput method to count the number of leaves by detecting leaf tips in RGB *** digital plant phenotyping platform was used to simulate a large and diverse dataset of RGB images and corresponding leaf tip labels of wheat plants at seedling stages(150,000 images with over 2 million labels).The realism of the images was then improved using domain adaptation methods before training deep learning *** results demonstrate the efficiency of the proposed method evaluated on a diverse test dataset,collecting measurements from 5 countries obtained under different environments,growth stages,and lighting conditions with different cameras(450 images with over 2,162 labels).Among the 6 combinations of deep learning models and domain adaptation techniques,the Faster-RCNN model with cycle-consistent generative adversarial network adaptation technique provided the best performance(R^(2)=0.94,root mean square error=8.7).Complementary studies show that it is essential to simulate images with sufficient realism(background,leaf texture,and lighting conditions)before applying domain adaptation ***,the spatial resolution should be better than 0.6 mm per pixel to identify leaf *** method is claimed to be self-supervised since no manual labeling is required for model *** self-supervised phenotyping approach developed here offers great potential for addressing a wide range of plant phenotyping *** trained networks are available at https://***/YinglunLi/Wheat-leaf-tip-detection.

关键词： Wheat seedling Plant

Global Wheat Head detection(GWHD)Dataset:A Large and Diverse Dataset of High-Resolution RGB-Labelled Images to develop and Benchmark Wheat Head detection Methods

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Plant Phenomics 2020年第1期2卷 243-254页

作者： Etienne David Simon Madec Pouria Sadeghi-Tehran Helge Aasen Bangyou Zheng Shouyang Liu Norbert Kirchgessner Goro Ishikawa Koichi Nagasawa Minhajul A.Badhon Curtis Pozniak benoit de solan Andreas Hund Scott C.Chapman Frédéric Baret Ian Stavness Wei Guo Arvalis Institut du végétal3 Rue Joseph et Marie Hackin75116 ParisFrance UMR1114 EMMAH INRAECentre PACABâtiment ClimatDomaine Saint-Paul228 Route de l’AérodromeCS 4050984914 Avignon CedexFrance Plant Sciences department Rothamsted ResearchHarpendenUK Institute of Agricultural Sciences ETH ZurichUniversitätstrasse 28092 ZurichSwitzerland CSIRO Agriculture and Food Queensland Biosciences Precinct306 Carmody RoadSt Lucia4067 QLDAustralia Plant Phenomics Research Center Nanjing Agricultural UniversityNanjingChina Institute of Crop Science National Agriculture and Food Research OrganizationJapan Hokkaido Agricultural Research Center National Agriculture and Food Research OrganizationJapan department of Computer Science University of SaskatchewanCanada department of Plant Sciences University of SaskatchewanCanada School of Food and Agricultural Sciences The University of QueenslandGatton4343 QLDAustralia Graduate School of Agricultural and Life Sciences The University of Tokyo1-1-1 Midori-choNishitokyo CityTokyoJapan

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 *** studies have developed methods for wheat head detection from high-resolution RGB imagery based on machine learning ***,these methods have generally been calibrated and validated on limited *** variability in observational conditions,genotypic differences,development stages,and head orientation makes wheat head detection a challenge for computer ***,possible blurring due to motion or wind and overlap between heads for dense populations make this task even more *** a joint international collaborative effort,we have built a large,diverse,and well-labelled dataset of wheat images,called the Global Wheat Head detection(GWHD)*** contains 4700 high-resolution RGB images and 190000 labelled wheat heads collected from several countries around the world at different growth stages with a wide range of *** for image acquisition,associating minimum metadata to respect FAIR principles,and consistent head labelling methods are proposed when developing new head detection *** GWHD dataset is publicly available at http://***/and aimed at developing and benchmarking methods for wheat head detection.

关键词： Wheat wheat maturity

Global Wheat Head detection 2021:An Improved Dataset for Benchmarking Wheat Head detection Methods

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Plant Phenomics 2021年第1期3卷 277-285页

作者： Etienne David Mario Serouart Daniel Smith Simon Madec Kaaviya Velumani Shouyang Liu Xu Wang Francisco Pinto Shahameh Shafiee Izzat SATahir Hisashi Tsujimoto Shuhei Nasuda Bangyou Zheng Norbert Kirchgessner Helge Aasen Andreas Hund Pouria Sadhegi-Tehran Koichi Nagasawa Goro Ishikawa Sébastien Dandrifosse Alexis Carlier Benjamin Dumont benoit Mercatoris Byron Evers Ken Kuroki Haozhou Wang Masanori Ishii Minhajul ABadhon Curtis Pozniak David Shaner LeBauer Morten Lillemo Jesse Poland Scott Chapman benoit de solan Frédéric Baret Ian Stavness Wei Guo Arvalis Institut du Végétal3 Rue Joseph et Marie Hackin75116 ParisFrance UMR1114 EMMAH INRAECentre PACABâtiment ClimatDomaine Saint-Paul228 Route de l’AérodromeCS 4050984914 Avignon CedexFrance School of Food and Agricultural Sciences The University of QueenslandGatton4343 QLDAustralia Hiphen SAS 120 Rue Jean DaussetAgroparcBâtiment Technicité84140 AvignonFrance Plant Phenomics Research Center Nanjing Agricultural UniversityNanjingChina Wheat Genetics Resource Center Dep.of Plant PathologyKansas State Univ.4024 Throckmorton Plant Sciences CenterManhattanKansasUSA Global Wheat Program International Maize and Wheat Improvement Centre(CIMMYT)MexicoD.F.Mexico Faculty of Biosciences Norwegian University of Life SciencesP.O.Box 5003NO-1432ÅsNorway Agricultural Research Corporation Wheat Research ProgramP.O.Box 126Wad MedaniSudan Arid Land Research Center Tottori UniversityTottori 680-0001Japan Laboratories of Plant Genetics and Plant Breeding Graduate School of AgricultureKyoto UniversityJapan CSIRO Agriculture and Food Queensland Biosciences Precinct306 Carmody RoadSt Lucia4067 QLDAustralia Institute of Agricultural Sciences ETH ZurichUniversitätstrasse 28092 ZurichSwitzerland Plant Sciences department Rothamsted ResearchHarpendenUK Institute of Crop Science National Agriculture and Food Research OrganizationJapan Hokkaido Agricultural Research Center National Agriculture and Food Research OrganizationJapan Biosystems Dynamics and Exchanges TERRA Teaching and Research CenterGembloux Agro-Bio TechUniversity of Liège5030 GemblouxBelgium Plant Sciences TERRA Teaching and Research CenterGembloux Agro-Bio TechUniversity of Liège5030 GemblouxBelgium Graduate School of Agricultural and Life Sciences The University of Tokyo1-1-1 Midori-choNishitokyo CityTokyoJapan department of Computer Science University of SaskatchewanCanada department of Plant Sciences University of SaskatchewanCanada College of Agriculture and Life Sciences University of ArizonaTucsonArizona

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/*** an associated competition hosted in Kaggle,GWHD_2020 has successfully attracted attention from both the computer vision and agricultural science *** this first experience,a few avenues for improvements have been identified regarding data size,head diversity,and label *** 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 *** 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.

关键词： Wheat adding release

Oxidative stress favours herpes virus infection in vertebrates： a meta-analysis

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Current Zoology 2016年第4期62卷 325-332页

作者： Manrico SEBASTIANO Olivier CHASTEL benoit de THOBY Marcel EENS David COSTANTINI Behavioural Ecology and Ecophysiology Group Department of Biology University of Antwerp Universiteitsplein 1 2610 Wilrijk Belgium Centre d'Etudes Biologiques de Chize (CEBC) UMR7372 - Centre National de la Recherche Scientifique/Universit La Rochelle Laboratory of Virus-Host Interactions. Institut Pasteur de la Guyane French Guiana France Institute of Biodiversity Animal Health & Comparative Medicine (IBAHCM) University of Glasgow Glasgow UK

Herpes viruses are responsible for a variety of pathological effects in humans and in both wild and domestic animals. One mechanism that has been proposed to facilitate replication and activity of herpes viruses is oxidative stress （OS）. We used meta-analytical techniques to test the hypotheses that （1） herpes virus infection causes OS and （2） supplementation of antioxidants reduces virus load, indicating that replication is favoured by a state of OS. Results based on studies on mammals, including humans, and birds show that （1） OS is indeed increased by herpes virus infection across multiple tissues and species, （2） biomarkers of OS may change differently between tissues, and （3） the effect size does not differ among different virus strains. In addition, the increase of oxidative damage in blood （tissue commonly available in ecological studies） was similar to that in the tissues most sensitive to the herpes virus. Our results also show that administration of antioxidants re- duces virus yield, indicating that a condition of OS is favorable for the viral replication. In addition, some antioxidants may be more efficient than others in reducing herpes virus yield. Our results point to a potential mechanism linking herpes virus infection to individual health status.

关键词： antioxidants herpes virus infection immune response interaction host-pathogen oxidative stress.

Event analysis in social multimedia： a survey

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Frontiers of Computer Science 2016年第3期10卷 433-446页

作者： Xueliang LIU Meng WANG benoit HUET School of Computer and Information Hefei University of Technology Hefei 230009 China department of Multimedia EURECOM sophia-antipolis Nice 06560 France

Recent years have witnessed the rapid growth of social multimedia data available over the Internet. The age of huge amount of media collection provides users facihties to share and access data, while it also demands the revolution of data management techniques, since the exponential growth of social multimedia requires more scalable, effective and ro- bust technologies to manage and index them. The event is one of the most important cues to recall people＇s past memory. The reminder value of an event makes it extremely helpful in organizing data. The study of event based analysis on so- cial multimedia data has drawn intensive attention in research community. In this article, we provide a comprehensive sur- vey on event based analysis over social multimedia data, in- cluding event enrichment, detection, and categorization. We introduce each paradigm and summarize related research ef- forts. In addition, we also suggest the emerging trends in this research area.

关键词： event enrichment event detection event categorization

Formation building and collision avoidance for a fleet of NAOs based on optical sensor with local positions and minimum communication

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Science China(Information Sciences) 2019年第5期62卷 214-236页

作者： Xiaomin WANG Lorenzo BENOZZI benoit ZERR Zexiao XIE Hélène THOMAS benoit CLEMENT Engineering college Ocean University of China

Multi-robot system has become a research hotspot because of low demand on the sensors’ accuracy, high reliability, and high efficiency. To put all the robots together, formation control is a crucial problem. In this paper, we propose a local position-based method to plan trajectories and build a pyramid pattern for a fleet of NAOs in the obstacle-free environment by refering to the position-based method and giving an O(n log n) collision avoidance strategy inspired from one graph theory, where the local positions are estimated from optical sensors. To get the local positions, an integrated image processing method is developped. Firstly a mask-base is generated to store the features of NAOs, and a cross-correlation method is introduced to recognize the NAO. Subsequently, the distance and angle models are proposed to get the local information from a single image. Then, a visual compass is introduced to obtain the orientation of one NAO. After the local information exchange by the WiFi communication, a neighbor-check method is put foward to distinguish the homogeneous NAOs(all the NAOs look like the same). Further, a common frame is constructed as an artificial global frame, and straight non-intercrossing trajectories are planned according to the O(n log n) collision avoidance strategy. At last, the performance of our proposed local position-based method is verified by the simulations with up to 15 robots and the indoor experiments with 3 NAOs in a real environment. The convergence of the method has been demonstrated in both obstacle-free and static obstacle environments.

关键词： formation building a fleet of NAOs optical sensor visual compass local positions

Biomarkers of resistance to immune checkpoint inhibitors in non-small-cell lung cancer:myth or reality?

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Cancer Drug Resistance 2020年第3期3卷 276-286页

作者： Ivan Pourmir benoit Gazeau Hortense de Saint Basile Elizabeth Fabre department of Thoracic oncology Hôpital européen Georges PompidouParis 75015France. INSERM U970 UniversitéParis Descartes Sorbonne Paris-CitéParis 75015France.

Immune checkpoint inhibitors represent a major therapeutic advance in non-small-cell lung cancer with several approved anti-programmed death-1 and anti-programmed death-L1 immunotherapies.A majority of patients however,will not respond to immune checkpoint inhibitors and display primary resistance while a subset of initially responsive patients will present secondary ***,there is a crucial need for biomarkers to enable better prediction and diagnosis,and to overcome such *** with improvement in the understanding of immune escape,new biomarkers are being developed,including large scale proteomic,genomic and transcriptomic approaches in tumor and blood *** review the novel biomarkers that have been investigated in non-small-cell lung cancer and discuss how they can rationalize therapeutic strategies.

关键词： Non-small-cell lung cancer immune checkpoint inhibitors resistance predictive biomarkers diagnostic biomarkers programmed death ligand-1 tumor mutational burden circulating tumor DNA