Liste complète des publications du projet par an


  1. Affortit P, Effa-Effa B, Ndoye MS, Moukouanga D, Luchaire N, Cabrera-Bosquet L, et al. (2022). Physiological and genetic control of transpiration efficiency in African rice, Oryza glaberrima Steud. Journal Exp Bot. 2022; 73(15):5279-93. DOI: 10.1093/jxb/erac156
  2. Barrit, T., Campion, C., Aligon, S., Bourbeillon, J., Rousseau, D., Planchet, E., & Teulat, B. (2022). A new in vitro monitoring system reveals a specific influence of Arabidopsis nitrogen nutrition on its susceptibility to Alternaria brassicicola at the seedling stage. Plant Methods, 18(1), 131. DOI: 10.1186/s13007-022-00962-3
  3. Béral A, Girousse C, Le Gouis J, Allard V, Slafer G. (2022). Physiological bases of cultivar differences in average grain weight in wheat: scaling down from plot to individual grain in elite material. Field Crop Res 289 :108713. DOI: 10.1016/j.fcr.2022.108713
  4. Bonnin E., Joseph-Aimé M., Fillaudeau L., Durand S., Falourd X., Le Gall S., & Saulnier L. (2022) Structure of heteroxylans from vitreous and floury endosperms of maize grain and impact on the enzymatic degradation. Carbohydrate Polymers, 278, 118942.  
  5. Campos NA, Colombie S, Moing A, Cassan C, Amah D, Swennen R, Gibon Y, Carpentier SC. (2022). From fruit growth to ripening in plantain: a careful balance between carbohydrate synthesis and breakdown. Journal of Experimental Botany 73: 4832-4849. DOI: 10.1093/jxb/erac187.
  6. Chenais J., Marion L.; Larocque R.; Jam M.; Jouanneau D.; Cladiere L.; Le Gall S.; Fanuel M.; Desban N.; Rogniaux H.; Ropartz D.; Ficko-Blean E.; Michel G. (2022) Systematic Comparison of Eight Methods for Preparation of High Purity Sulfated Fucans Extracted from the Brown Alga Pelvetia Canaliculata. International Journal of Biological Macromolecules 2022, 201, 143–157.
  7. Colombo M, Roumet P, Salon C, Christian J, Lamboeuf M, Lafarge S, Dumas A-V, Dubreuil P, Ngo W, Derepas B, Beauchene K, BreedWheat Consortium T, Allard V, Le Gouis J, Rincent R. (2022). Genetic analysis of platform-phenotyped root system architecture of bread and durum wheat in relation to agronomic traits. Frontiers in Plant Science 13:853601. DOI10.3389/fpls.2022.853601
  8. Coupel-Ledru A., Pallas B., Delalande M., Segura V., Guitton B., Muranty H., Durel CE., Regnard J.L., Costes E. (2022). Tree architecture, light interception and water use related traits are controlled by different genomic regions in an apple tree core collection. New Phytologist 234 : 209-226. DOI : 10.1111/nph.17960
  9. Daviet B, Fernandez R, Cabrera-Bosquet L, Pradal C, Fournier C. (2022). PhenoTrack3D: an automatic high-throughput phenotyping pipeline to track maize organs over time. Plant Methods 18, 130. DOI: 10.1186/s13007-022-00961-4
  10. Ding, L, Milhiet T, Parent B, Meziane A, Tardieu F, Chaumont F. (2022). The plasma membrane aquaporin ZmPIP2;5 enhances the sensitivity of stomatal closure to water deficit. Plant Cell and environment, 45,4 : 1146-1156.
  11. Dussarrat T, Prigent S, Latorre C, Bernillon S, Flandin A, Diaz FP, Cassan C, Van Delft P, Jacob D, Varala K, Joubes J, Gibon Y, Rolin D, Gutierrez RA, Petriacq P. (2022). Predictive metabolomics of multiple Atacama plant species unveils a core set of generic metabolites for extreme climate resilience. New Phytologist 234: 1614-1628. DOI: 10.1111/nph.18095
  12. ElMasry G.,  Mandour N., Ejeez  Y.,  Demilly D., Al-Rejaie  S., Verdier J., Belin  E. &  Rousseau D.  (2022). Multichannel imaging for monitoring chemical composition and germination capacity of cowpea (Vigna unguiculata) seeds during development and maturation. The Crop Journal. Vol. 10, pp. 1399-1411.
  13. Eyland D, Luchaire N, Cabrera-Bosquet L, Parent B, Janssens SB, Swennen R, et al. (2022). High-throughput phenotyping reveals differential transpiration behaviour within the banana wild relatives highlighting diversity in drought tolerance. Plant Cell Environ. 2022, 45,6:1647-63. DOI: 10.1111/pce.14310
  14. Gautreau M, Durand S, Paturel A, Le Gall S, Foucat L, Falourd X, Novales B , Ralet M-C, Chevalier S, Kervoelen A, Bourmaud A, Guillon F and Beaugrand J. (2022) Impact of cell wall non-cellulosic and cellulosic polymers on the mechanical properties of flax fibre bundles 2022, Carbohydrate Polymers, 291, 119599.
  15. Hénault C., Barbier E., Hartmann A., Revellin C. (2022). New insights in the use of rhizobia to mitigate soil N2O emissions. Agriculture. 12:art. 271 .
  16. Jacquiod S., Spor A., Wei S., Munkager V., Bru D., Sorensen S. J., Salon C., Philippot L., Blouin M. (2022). Artificial selection of stable rhizosphere microbiota leads to heritable plant phenotype changes. Ecology Letters, 25 (1), 189-201,
  17. Joram P, Dauzat M, Bédiée A, Vile D. (2022). Relamping PHENOPSIS – a high throughput phenotyping platform – with LEDs. Acta Horticulturae. 1337: 125-135. 
  18. K Turgut, H Dutagaci, G Galopin, D Rousseau. (2022). Segmentation of structural parts of rosebush plants with 3D point-based deep learning methods, Plant Methods 18: 20. DOI: 10.1186/s13007-022-00857-3
  19. Lamichhane Jr., Wojciechowski A., Bourgeois C., Debaeke P. (2022). Genetic variability for early growth traits in second season sunflower. Frontiers in Agronomy 4, 822456. /10.3389/fagro.2022.822456 
  20. Lan, W., Baeten V., Jaillais B., Renard C.M.G.C., Arnould Q., Chen S., Leca A., Bureau S (2022) Comparison of near-infrared, mid-infrared, Raman spectroscopy and near-infrared hyperspectral imaging to determine chemical, structural and rheological properties of apple purees, J. Food Eng, 323, DOI: 10.1016/j.jfoodeng.2022.111002
  21. Lee J.S., Jahani M., Huang K., Mandel J.R., Marek L.F., Burke J.M., Langlade N.B., Owens G.L., Rieseberg L.H. (2022). Expression complementation of gene presence/absence polymorphisms in hybrids contributes importantly to heterosis in sunflower. Journal of Advanced Research.
  22. Montazeaud G., Flutre T., Ballini E., Morel J.B., David J., Girodolle J., Rocher A., Ducasse A., Violle C., Fort F., Freville H. (2022). From cultivar mixtures to allelic mixtures : opposite effects of allelic richness between genotypes and genotype richness in wheat. New Phytologist 233 : 2573-2584. DOI : 10.1111/nph.17915 - Cite l’UE Diascope
  23. Moreau D., Busset H., Matejicek A., Prudent M. & Colbach N. (2022) Water limitation affects weed competitive ability for light. A demonstration using a model-based approach combined with an automated watering platform. Weed Research, 62, 381-392, 
  24. Oury V., Leroux T., Turc O., Chapuis R., Palaffre C., Tardieu F., Alvarez Prado S., Welcker C., Lacube S. (2022). Earbox, an open tool for high-throughput measurement of the spatial organization of maize ears and inference of novel traits. Plant Methods 18 :96. Https:// - Cite Phenome
  25. Panozzo A., Huang H-Y., Bernazeau B., Meunier F., Turc O., Duponnois R., Prin Y., Vamerali T., Desclaux D. (2022). Impact of Olive Trees on the Microclimatic and Edaphic Environment of the Understorey Durum Wheat in an Alley Orchard of the Mediterranean Area. Agronomy 2022, 12(2), 527; - Cite l’UE DiaScope et utilise les capteurs environnementaux de la PF
  26. Paux E, The Breedwheat Consortium, Lafarge S, Balfourier F, Derory J, Charmet G, Alaux M, Perchet G, Bondoux M, Baret F, Barillot R, Ravel C, Sourdille P, Le Gouis J. (2022). Breeding for economically and environmentally sustainable wheat varieties: an integrated approach from genomics to selection. Biology 11:149. DOI: 10.3390/biology11010149
  27. Perez-Valencia DM, Rodriguez-Alvarez MX, Boer MP, Kronenberg L, Hund A, Cabrera-Bosquet L, Millet EJ, van Eeuwijk FA. (2022). A two-stage approach for the spatio-temporal analysis of high-throughput phenotyping data. Scientific Reports 12: 3177. DOI: 10.1038/s41598-022-06935-9
  28. Perthame L., Colbach N., Busset H., Matejicek A. & Moreau D. (2022) Morphological response of weed and crop species to nitrogen stress in interaction with shading. Weed Research 62, 160-171,
  29. Poorter H, Yin XY, Alyami N, Gibon Y, Pons TL. (2022). MetaPhenomics: quantifying the many ways plants respond to their abiotic environment, using light intensity as an example. Plant and Soil 476: 421-454. DOI: 10.1007/s11104-022-05391-8
  30. Poucet T, Beauvoit B, Gonzalez-Moro MB, Cabasson C, Petriacq P, Flandin A, Gibon Y, Marino D, Dieuaide-Noubhani M (2022) Impaired cell growth under ammonium stress explained by modeling the energy cost of vacuole expansion in tomato leaves. The Plant Journal 112: 1014-1028. DOI: 10.1111/tpj.15991.
  31. Reyre JL., Grisel S., Haon M., Navarro D., Ropartz D., Le Gall S., Record E., Sciara G., Tranquet O., Berrin JG., Bissaro B. (2022) The maize pathogen Ustilago maydis secretes glycoside hydrolases and carbohydrate oxidases directed toward components of the fungal cell wall. Applied and Environmental Microbiology, DOI: 10.1128/aem.01581-22
  32. Saint Cast C, Lobet G, Cabrera-Bosquet L, Couvreur V, Pradal C, Tardieu F, et al. (2022). Connecting plant phenotyping and modelling communities: lessons from science mapping and operational perspectives. in silico Plants, 4: 1. DOI: 10.1093/insilicoplants/diac005.
  33. Sapoukhina N., Boureau T. , Rousseau D.  (2022). Plant disease symptom segmentation in chlorophyll fluorescence imaging with a synthetic dataset. Front Plant Sci. 13:969205 doi: 10.3389/fpls.2022.969205.
  34. Serouart, M., Madec, S., David, E., Velumani, K., Lopez Lozano, R., Weiss, M., & Baret, F. (2022). SegVeg: Segmenting RGB images into green and senescent vegetation by combining deep and shallow methods. Plant Phenomics, 2022, 9803570, DOI: 10.34133/2022/9803570
  35. Taugourdeau S., Dionisi M., Lascoste M., Lesnoff M., Capron J-M., Borne F., Borianne P., Julien L. (2022). A first attempt to combine NIRS and plenoptic cameras for the assessment of grasslands functional diversity and species composition. Agriculture, 12, 704. - Cite l’UE DiaScope
  36. Vaitkeviciute G, Aleliunas A, Gibon Y, Armoniene R (2022) Comparative Analysis of Antioxidant Accumulation under Cold Acclimation, Deacclimation and Reacclimation in Winter Wheat. Plants 11: 2818. DOI: 10.3390/plants11212818.
  37. Vaitkeviciute G, Aleliunas A, Gibon Y, Armoniene R. (2022). The effect of cold acclimation, deacclimation and reacclimation on metabolite profiles and freezing tolerance in winter wheat. Frontiers in Plant Science 13: 959118. DOI: 10.3389/fpls.2022.959118.
  38. Vancostenoble B., Blanchet N., Langlade N.B., Bailly, C. (2022). Maternal drought stress induces abiotic stress tolerance to the progeny at the germination stage in sunflower. Environmental and Experimental Botany 201, 104939.
  39. Vasseur F, D Cornet, G Beurier, J Messier, L Rouan, J Bresson, M Ecarnot, M Stahl, S Heumos, M Gérard, H Reijnen, P Tillard, B Lacombe, A Emanuel, J Floret, A Estarague, S Przybylska, K Sartori, LM Gillespie, E Baron, E Kazakou, D Vile and C Violle. (2022). A perspective on plant phenomics: coupling deep learning and near-infrared spectroscopy. Frontiers in Plant Science.
  40. Welcker C., Abusamra Spencer N., Turc O., Granato I., Chapuis R., Madur D., Beauchene K., Gouesnard B., Draye X., Palaffre C., Lorgeou J., Melkior S., Guillaume C., Presterl T., Murigneux A., Wisser R.J., Millet E.J., Van Eeuwijk F., Charcosset A., Tardieu F. (2022). Physiological adaptive traits are a potential allele reservoir for maize genetic progress under challenging conditions. Nature Communications 13:3225. Https:// - Cite Phenome
  41. Zhour H, Bray F, Dandache I, Marti G, Flament S, Perez A, Lis M, Cabrera-Bosquet L, Perez T, Fizames C, Baudoin E, Madani I, El Zein L, Véry A-A, Rolando C, Sentenac H, Chokr A, Peltier J-B. (2022). Wild Wheat Rhizosphere-Associated Plant Growth-Promoting Bacteria Exudates: Effect on Root Development in Modern Wheat and Composition. International Journal of Molecular Sciences 23, 15248. DOI:10.3390/ijms232315248


Autres publications scientifiques

  1. Morcillo A., Grau A. (2022). Évaluation d’un pool génétique de Blé Dur en conditions de stress
     hydrique et thermique. [Stage] UM2 Université Montpellier II Sciences et techniques ; INRAE / Montpellier supagro, 2 place Pierre Viala, 34090 Montpellier; INRAE UE diascope. 2022, pp.1- 45. Ffhal-03811102. - Cite l’infrastructure Phenome
  2. Collet C., (2022). A novel phenotyping pipeline for root system architecture. Evaluation with diversity panels of bread and durum wheat. Thèse présentée en vue de l’obtention du grade de Docteur en sciences agronomiques et ingénierie biologique - Résultats utilisant des données champ du projet SolAce de la PF
  3. Gibon Y., Prigent S., Dussarrat T., Moing A., Tardieu F., and Pétriacq P. (2022). Le métabolome et son utilisation en amélioration des plantes. Le Sélectionneur Français 72: 65-74. Acte de la conférence « Quoi de neuf sur le phénotypage des plantes ? ».
  4. Langlade, N.B., (2022). Phénomique du tournesol - Cas d’usage en génétique et perspectives. Le Sélectionneur Français 72, 47–55.


  1. Affortit et al. High-throughput phenotyping reveals a link between transpiration efficiency and transpiration restriction under high evaporative demand and new loci controlling water use-related traits in African rice, Oryza glaberrima Steud. BioArXiv
  2. Ancín M, Larraya L, Florez-Sarasa I, Bénard C, Fernández-San Millán A, Veramendi J, Gibon Y, Fernie AR, Aranjuelo I, Farran I (2021) Overexpression of thioredoxin m in chloroplasts alters carbon and nitrogen partitioning in tobacco. J. Exp. Bot 72: 4949-4964. doi:10.1093/jxb/erab193
  3. Balliau T, Durufle H, Blanchet N, Blein-Nicolas M, Langlade NB, Zivy M: Proteomic data from leaves of twenty-four sunflower genotypes under water deficit. Ocl-Oilseeds and Fats Crops and Lipids 2021, 28.
  4. Bengoa Luoni SA, Cenci A, Moschen S, Nicosia S, Radonic LM, Sabio y Garcia J, Carrère S, Langlade NB, Vile D, Vazquez Rovere C and Fernandez P. 2021. Genome-Wide analysis of NAC Transcription Factors in Sunflower (Helianthus annuus), their comparative phylogenetic analysis and association with leaf senescence. BMC Genomics 22:893
  5. Bergès SE, M Yvon, D Masclef, M Dauzat, D Vile, M van Munster. Water deficit changes the relationships between epidemiological traits of the Cauliflower mosaic virus across diverse Arabidopsis thaliana accessions. 2021. Scientific Reports 11:24103.
  6. Berton T, Bernillon S, Fernandez O, Duruflé H, Flandin A, Cassan C, Jacob D, Langlade NB, Gibon Y, Moing A (2021) Leaf metabolomic data of eight sunflower lines and their sixteen hybrids under water deficit. OCL 28: #42. Doi: 10.1051/ocl/2021029
  7. Chen J, Beauvoit B, Génard M, Colombie S, Moing A, Vercambre G, Gomes E, Gibon Y, Dai Z (2021) Modelling predicts tomatoes can be bigger and sweeter if biophysical factors and transmembrane transports are fine‐tuned during fruit development. New Phytologist 230: 1489-1502. doi: 10.1111/nph.17260
  8. David, E., Serouart, M., Smith, D., Madec, S., Velumani, K., Liu, S., Wang, X., Pinto, F., Shafiee, S., Tahir, I.S.A., Tsujimoto, H., Nasuda, S., Zheng, B., Kirchgessner, N., Aasen, H., Hund, A., Sadhegi-Tehran, P., Nagasawa, K., Ishikawa, G., Dandrifosse, S., Carlier, A., Dumont, B., Mercatoris, B., Evers, B., Kuroki, K., Wang, H., Ishii, M., Badhon, M.A., Pozniak, C., LeBauer, D.S., Lillemo, M., Poland, J., Chapman, S., de Solan, B., Baret, F., Stavness, I., Guo, W., 2021. Global Wheat Head Detection 2021: An Improved Dataset for Benchmarking Wheat Head Detection Methods. Plant Phenomics 2021, 1–9.
  9. Debaeke P, Casadebaig P, Langlade NB: New challenges for sunflower ideotyping in changing environments and more ecological cropping systems. Ocl-Oilseeds and Fats Crops and Lipids 2021, 28.
  10. Destailleur A, Poucet T, Cabasson C, Alonso AP, Cocuron J-C, Larbat R, Vercambre G, Colombié S, Petriacq P, Andrieu M-H, Beauvoit B, Gibon Y, Dieuaide-Noubhani M (2021) The evolution of leaf function during development is reflected in profound changes in the metabolic composition of the vacuole. Metabolites 11: #848. doi: 10.3390/metabo11120848
  11. Eyland D, Breton C, Sardos J, Kallow S, Panis B, Swennen R, Paofa J, Tardieu F, Welcker C, Janssens SB, Carpentier SC. 2021. Filling the gaps in gene banks: Collecting, characterizing, and phenotyping wild banana relatives of Papua New Guinea. Crop Science 61, 137-149.
  12. Eyland et al. High-throughput phenotyping reveals differential transpiration behavior within the banana wild relatives highlighting diversity in drought tolerance. Authorea. August 02, 2021.
  13. Fagny, M; Kuijjer, ML; Stam, M; Joets, J; Turc, O; Roziere, J; Pateyron, S; Venon, A; Vitte, C (2021) Identification of Key Tissue-Specific, Biological Processes by Integrating Enhancer Information in Maize Gene Regulatory Networks. Frontiers in Genetics DOI 10.3389/fgene.2020.606285
  14. G. ElMasry, N. Mandour, Y. Ejeez, D. Demilly, S. Al-Rejaie, J. Verdier, E. Belin & D. Rousseau. Multichannel imaging for monitoring chemical composition and germination capacity of cowpea (Vigna unguiculata) seeds during development and maturation. The Crop Journal, 2021.
  15. Garbouge, H., Rasti, P., & Rousseau, D. (2021). Enhancing the Tracking of Seedling Growth Using RGB-Depth Fusion and Deep  Learning. Sensors, 21(24), 8425.
  16. Grégoire Bianchetti, Cécile Baron, Aurélien Carrillo, Solenne Berardocco, Nathalie Marnet, Marie-Hélène Wagner, Didier Demilly, Sylvie Ducournau, Maria Manzanares-Dauleux, Françoise Le Cahérec, Julia Buitink, Nathalie Nesi, 2021. Dataset for the metabolic and physiological characterization of seeds from oilseed rape ( Brassica napus L.) plants grown under single or combined effects of drought and clubroot pathogen Plasmodiophora brassicae. Data in Brief, Volume 38, 2021
  17. Jacques C., Forest M., Durey V., Salon C., Ourry A., Prudent M. (2021). Transient nutrient deficiencies in pea: consequences on nutrient uptake, remobilization and seed quality. Front. Plant Sci. 12:art.785221 (14p.).
  18. Jacques C., Salon C., Barnard R.L., Vernoud V., Prudent M. (2021). Drought stress memory at the plant cycle level: a review. Plants. 10:art.1873 (13.). 10.3390/plants10091873
  19. Jiang, J.Y., Comar, A., Weiss, M. and Baret, F., 2021. FASPECT: A model of leaf optical properties accounting for the differences between upper and lower faces. Remote Sensing of Environment, 253.
  20. Jin, S.C., Su, Y.J., Zhang, Y.G., Song, S.L., Li, Q., Liu, Z.H., Ma, Q., Ge, Y., Liu, L.L., Ding, Y.F., Baret, F. and Guo, Q.H., 2021. Exploring Seasonal and Circadian Rhythms in Structural Traits of Field Maize from LiDAR Time Series. Plant Phenomics, 2021.
  21. Jin, S.C., Sun, X.L., Wu, F.F., Su, Y.J., Li, Y.M., Song, S.L., Xu, K.X., Ma, Q., Baret, F., Jiang, D., Ding, Y.F. and Guo, Q.H., 2021. Lidar sheds new light on plant phenomics for plant breeding and management: Recent advances and future prospects. ISPRS Journal of Photogrammetry and Remote Sensing, 171: 202-223.
  22. Krzyzaniak Y., Cointault F., Loupiac C., Bernaud E., Ott F., Salon C., Laybros A., Han S., Héloir M.-C., Adrian M., Trouvelot S. (2021). In situ phenotyping of grapevine root system architecture by 2D or 3D imaging: advantages and limits of three cultivation methods. Front. Plant Sci. 12:art.638688 (15p.).
  23. Laborde, A., Puig-Castellví, F., Jouan-Rimbaud Bouveresse, D., Eveleigh, L., Cordella, C. & Jaillais, B. (2021) Detection of chocolate powder adulteration with peanut using near-infrared hyperspectral imaging and Multivariate Curve Resolution. Food Control, 119, 107454
  24. Laue, C. Stevens. Y, van Erp, M., Papazova, E., Soeth, E., Pannenbeckers, A., Stolte, E., Böhm, R., Le Gall, S., Falourd, X., Ballance, S., Knutsen, S.H., Pinheiro, I., Possemiers, S., Ryan, P.M., Ross,R.P., Stanton, C., Wells, J.M., van der Werf, S., Mes,J.J., Schrezenmeir, J. Adjuvant Effect of Orally Applied Preparations Containing Non-Digestible Polysaccharides on Influenza Vaccination in the Healthy Elderly: A Double-Blind, Randomised, Controlled Pilot Trial. Nutrients 2021, 13, 2683.
  25. Le Gall, S., Sole-Jamault, V., Nars-Chasseray, M., Le Goff, A., Le Bot, L., Guinet, T., Renaud, C., Gervais, J., Bansard, S., Ohleyer, L., Jeandroz, S. Data on agronomic traits, biochemical composition of lipids, proteins and polysaccharides and rheological measurement in a brown mustard seed collection. Data In Brief. 2021.
  26. Li, W., A. Comar, M. Weiss, S. Jay, G. Colombeau, R. Lopez-Lozano, S. Madec and F. Baret (2021). "A Double Swath Configuration for Improving Throughput and Accuracy of Trait Estimate from UAV Images." Plant Phenomics 2021.
  27. Li, W., J. Jiang, M. Weiss, S. Madec, F. Tison, B. Philippe, A. Comar and F. Baret (2021). "Impact of the reproductive organs on crop BRDF as observed from a UAV." Remote Sensing of Environment 259: 112433.
  28. Li, W.J., Fang, H.L., Wei, S.S., Weiss, M. and Baret, F., 2021. Critical analysis of methods to estimate the fraction of absorbed or intercepted photosynthetically active radiation from ground measurements: Application to rice crops. Agricultural and Forest Meteorology, 297.
  29. Liu, S., F. Baret, M. Abichou, L. Manceau, B. Andrieu, M. Weiss and P. Martre (2021). "Importance of the description of light interception in crop growth models." Plant Physiology 186(2): 977-997.
  30. Luoni SAB, Cenci A, Moschen S, Nicosia S, Radonic LM, Sabio GJ, Langlade NB, Vile D, Rovere CV, Fernandez P: Genome-wide and comparative phylogenetic analysis of senescence-associated NAC transcription factors in sunflower (Helianthus annuus). Bmc Genomics 2021, 22.
  31. Machwitz, M., R. Pieruschka, K. Berger, M. Schlerf, H. Aasen, S. Fahrner, J. Jiménez-Berni, F. Baret and U. Rascher (2021). "Bridging the Gap Between Remote Sensing and Plant Phenotyping—Challenges and Opportunities for the Next Generation of Sustainable Agriculture." Frontiers in Plant Science 12(2334).
  32. Maslard C., Arkoun M., Salon C., Prudent M. (2021). Root architecture characterization in relation to biomass allocation and biological nitrogen fixation in a collection of european soybean genotypes. OCL-Ol. Corps Gras Lipides. 28:art. 48 (12p.).
  33. Nikolić Chenais J, Marion L, Larocque R, Jam M, Jouanneau D, Cladiere L, Le Gall S, Fanuel M, Desban N, Rogniaux H, Ropartz D, Ficko-Blean E, Michel G. Systematic comparison of eight methods for preparation of high purity sulfated fucans extracted from the brown alga Pelvetia canaliculata. Int J Biol Macromol. 2021 Dec 27:S0141-8130(21)02752-5. https://doi: 10.1016/j.ijbiomac.2021.12.122
  34. Perez-Valencia et al. A two-stage approach for the spatio-temporal analysis of high-throughput phenotyping data. BioRXiv
  35. Poucet T, González-Moro MB, Cabasson C, Beauvoit B, Gibon Y, Dieuaide-Noubhani M, Marino D (2021) Ammonium supply induces differential metabolic adaptive responses in tomato according to leaf phenological stage. J. Exp. Bot. 72: 3185–3199. doi:10.1093/jxb/erab057
  36. Rubio B, Fernandez O, Cosson P, Berton T, Caballero M, Lion R, Roux F, Bergelson J, Gibon Y, Schurdi-Levraud V (2021) Metabolic Profile Discriminates and Predicts Arabidopsis Susceptibility to Virus under Field Conditions. Metabolites 11: #230. doi: 10.3390/metabo11040230
  37. Shichao, J., S. Xiliang, F. Wu, Y. Su, Y. Li, S. Song, K. Xu, Q. Ma, F. Baret, D. Jiang, Y. Ding and Q. Guo (2021). "Lidar sheds new light on plant phenomics for plant breeding and management: Recent advances and future prospects." ISPRS Journal of Photogrammetry and Remote Sensing Accepted (Novembre 2020).
  38. Shinohara T., Ducournau S., Matthews S., Wagner M.-H., and Powell A.A., 2021. Early counts of radicle emergence, counted manually and by image analysis, can reveal differences in the production of normal seedlings and the vigour of seed lots of cauliflower. Seed Science and Technology 49, 3, 219-235.
  39. Sichert, A.; Le Gall, S.; Klau, L. J.; Laillet, B.; Rogniaux, H.; Aachmann, F. L.; Hehemann, J.-H. Ion-Exchange Purification and Structural Characterization of Five Sulfated Fucoidans from Brown Algae. Glycobiology 2021, 31 (4), 352–357.
  40. Tardieu F (2021) Different avenues for progress apply to drought tolerance, water use efficiency and yield in dry areas. Current opinion in biotechnology;
  41. Tristan Lurthy, Cécile Cantat, Christian Jeudy, Philippe Declerck, Karine Gallardo, et al.. Impact of Bacterial Siderophores on Iron Status and Ionome in Pea. Frontiers in Plant Science, Frontiers, 2020, 11.
  42. Urrutia M, Blein-Nicolas M, Prigent S, Bernillon S, Deborde C, Balliau T, Maucourt M, Jacob D, Ballias P, Bénard C, Sellier H, Gibon Y, Giauffret C, Zivy M, Moing A (2021) Maize metabolome and proteome responses to controlled cold stress partly mimic early-sowing effects in the field and differ from those of Arabidopsis. Plant Cell Environ. 44:1504-1521. doi: 10.1111/pce.13993
  43. Vargas-Rojas, F. (2021). Ontological Formalisation of Mathematical Equations for Phenomic Data Exploitation.  European Semantic Web Conference.
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Autres articles de vulgarisation scientifique

  1. Perspectives Agricoles (projet DUROSTRESS) Stratégies d’adaptation du blé dur au nouveau climat Delphine Hourcade, Paloma Cabeza-Orcel, Décembre 2021 – N°494 Projet accueilli sur la plateforme DiaPhen mais oubli de citation dans l’article
  2. Joram P, Dauzat M, Bédiée A, Vile D. 2022. Relamping PHENOPSIS – a high throughput phenotyping platform – with LEDs. Acta Horticulturae.
  3. Leger J-B, Kuhn E, Parent B, Tardieu F, Welcker C (2021) Estimation des paramètres d'un modèle de culture à partir de données de plein champ et de données de plateforme de phénotypage. 52èmes Journées de Statistique de la Société Française de Statistique, Nice, France (Actes de congrès)
  4.  « Enjeux et outils du phénotypage : UNE STRATÉGIE NUMÉRIQUE sur le long terme » Katia BEAUCHENE Katia Beauchêne, Benoît de Solan, Stéphane Jezequel, Jean Pierre Cohan et Xavier Pinochet, Publication Agricole 485-31-36- de Février 2021.
  5. Redon M. 2021. Imagerie pour le phénotypage du végétal. Application au robot Phenobean. Rapport de projet M2 PSI, Université d’Angers. 09/02/2021.
  6. Redon M. 2021. Imagerie pour le phénotypage du végétal. Application au robot Phenobean. Rapport d’alternance M2 PSI, Université d’Angers. 26/08/2021.


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Date de modification : 31 août 2023 | Date de création : 08 avril 2019 | Rédaction : Pamela Lucas