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24, chemin de Borde Rouge –Auzeville – CS52627
31326 Castanet Tolosan CEDEX - France

Dernière mise à jour : Mai 2018

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Project Publications

Whole list of publications


  1. Artzet S, Chen TW, Chopard J, Brichet N, Mielewczik M, Cohen-Boulakia S, Cabrera Bosquet L, Tardieu F, Fournier C, Pradal C (2020) Phenomenal: An automatic open source library for 3D shoot architecture reconstruction and analysis for image-based plant phenotyping.
  2. Béral A, Le Gouis J, Rincent R, Girousse C, Allard V (2020) Wheat individual grain-size variance originates from crop development and from specific genetic determinism. PLos One 15:e0230689
  3. Bergès SE, Vasseur F, Bediée A, Rolland G, Masclef D, Dauzat M, van Munster M, Vile D (2020) Natural variation of Arabidopsis thaliana responses to Cauliflower mosaic virus infection upon water deficit. PLOS Pathogens 16: e1008557. doi:10.1371/journal.ppat.1008557.
  4. Bernard, A., Hamdy, S., Le Corre, L. et al. 3D characterization of walnut morphological traits using X-ray computed tomography. Plant Methods 16, 115 (2020).
  5. Blein-Nicolas M, Negro SS, Balliau T, Welcker C, Cabrera-Bosquet L, Nicolas SD, Charcosset A, Zivy M (2020) A systems genetics approach reveals environment-dependent associations between SNPs, protein coexpression, and drought-related traits in maize. Genome research 30: 1593-1604. doi:10.1101/gr.255224.119.
  6. Cakpo CB, Vercambre G, Baldazzi V, Roch L, Valsesia P, Memah M-M, Colombié S, Moing A, Gibon Y, Génard M (2020) Model-assisted comparison of sugar accumulation patterns in ten fleshy fruits highlights differences between annual and perennial species. Annals of Botany, in press. DOI: 10.1093/aob/mcaa082
  7. Castelletti S, Coupel-Ledru A, Granato I, Palaffre C, Cabrera-Bosquet L, Tonelli C, Nicolas SD, Tardieu F, Welcker C, Conti L (2020) Maize adaptation across temperate climates was obtained via expression of two florigen genes. Plos Genetics 16: e1008882. doi:10.1371/journal.pgen.1008882.
  8. Couchoud M., Salon C., Girodet S., Jeudy C., Vernoud V., Marion Prudent (2020). Pea efficiency of post drought recovery relies on the strategy to fine-tune nitrogen nutrition. Frontiers in Plant Science, 11, 204.
  9. David, E., S. Madec, P. Sadeghi-Tehran, H. Aasen, B. Zheng, S. Liu, N. Kirchgessner, G. Ishikawa, K. Nagasawa, M. A. Badhon, C. Pozniak, B. de Solan, A. Hund, S. C. Chapman, F. Baret, I. Stavness and W. Guo (2020). "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." Plant Phenomics 2020: 3521852.
  10. Ding L, Milhiet T, Couvreur V, Nelissen H, Meziane A, Parent B, Aesaert S, Van Lijsebettens M, Inzé D, Tardieu F, Draye X, Chaumont F (2020) Modification of the expression of the aquaporin ZmPIP2;5 affects water relations and plant growth. Plant Physiology 182: 2154-2165. doi:10.1104/pp.19.01183.
  11. Dingkuhn M, Luquet D, Fabre D, Muller B, Yin X, Paul M (2020) The case for improving crop carbon sink strength or plasticity for a CO2-rich future. Current Opinion in Plant Biology 56: 259-272. doi:10.1016/j.pbi.2020.05.012.
  12. Ducournau, S., Charrier, A., Demilly, D., Wagner, M. H., Trigui, G., Dupont, A., ... & Dürr, C. (2020). High throughput phenotyping dataset related to seed and seedling traits of sugar beet genotypes. Data in brief, 29, 105201.
  13. Duran Garzon C, Lequart M, Rautengarten C, Bassard S, Sellier-Richard H, Baldet P, Heazlewood JL, Gibon Y, Domon J-M, Giauffret C, Rayon C (2020) Regulation of carbon metabolism in two maize sister lines contrasted for chilling tolerance. Journal of Experimental Botany 71 : 356–369. doi:10.1093/jxb/erz421
  14. ElMasry, G., ElGamal, R., Mandour, N., Gou, P., Al-Rejaie, S., Belin, E., & Rousseau, D. (2020). Emerging thermal imaging techniques for seed quality evaluation: Principles and applications. Food Research International, 131, 109025.
  15. Garbez, M., Belin, E., Chéné, Y. et al. A new approach to predict the visual appearance of rose bush from image analysis of 3D videos. Eur. J. Hortic. Sci, 2020, vol. 85, p. 182-190.
  16. Gody, L., Duruflé, H., Blanchet, N., Carré, C., Legrand, L., Mayjonade, B., Muños, S., Pomiès, L., de Givry, S., Langlade, N.B., others, 2020. Transcriptomic data of leaves from eight sunflower lines and their sixteen hybrids under water deficit. OCL 27, 48.
  17. Heidsieck G, De Oliveira D, Pacitti E, Pradal C, Tardieu F, Valduriez P (2020) Efficient Execution of Scientific Workflows in the Cloud Through Adaptive Caching. In A Hameurlain, AM Tjoa, P Lamarre, K Zeitouni, eds, Transactions on Large-Scale Data-and Knowledge-Centered Systems XLIV, Vol 12380. Springer, Berlin, Germany, pp 41-66.
  18. Hennet L., Berger A., Trabanco N., Ricciuti E., Dufayard J-F., Bocs S., Bastianelli D., Bonnal L., Roques S., Rossini L., Luquet D., Terrier N., Pot D. 2020 Transcriptional regulation of sorghum stem composition: key players identified through co-expression gene network and comparative genomics analyses. Frontiers in Plant Science. Frontiers Media S.A., 11, p. 224. doi: 10.3389/fpls.2020.00224.
  19. Jacob D, David R, Aubin S, Gibon Y (2020). Making experimental data tables in the life sciences more FAIR: a pragmatic approach. GigaScience 9 : giaa144. Doi : 10.1093/gigascience/giaa144
  20. Jay, S., Comar, A., Benicio, R., Beauvois, J., Dutartre, D., Daubige, G., ... & Baret, F. (2020). Scoring cercospora leaf spot on sugar beet: comparison of UGV and UAV phenotyping systems. Plant Phenomics, 2020.
  21. Jiang, J., A. Comar, M. Weiss and F. Baret (2020). "FASPECT: a model of leaf optical properties accounting for the differences between upper and lower faces." Remote Sensing of Environment Accepté (Novembre 2020).
  22. Laborde, A., Jaillais, B., Roger, JM., Metz, M., Jouan-Rimbaud Bouveresse, D., Eveleigh, L., Cordella, C. (2020) Subpixel detection of peanut in wheat flour using a matched subspace detector algorithm and near-infrared hyperspectral imaging. Talanta, 337.
  23. Lacube S, Manceau L, Welcker C, Millet E, Gouesnard B, Palaffre C, Ribaut JM, Hammer G, Parent B, Tardieu F (2020) Simulating the effect of flowering time on maize individual leaf area in contrasting environmental scenarios. Journal of Experimental Botany 71: 5577-5588. doi:10.1093/jxb/eraa278.
  24. Lahaye M., Falourd, X., Laillet, B., Le Gall., S. (2020) Cellulose, pectin and water in cell walls determine apple flesh viscoelastic mechanical properties. Carbohydrate Polymers, 232, 115768.
  25. Lancelot, E., Courcoux, P., Chevallier, S., Le-Bail, A. & Jaillais, B. (2020) Prediction of water content in biscuit using Near-Infrared hyperspectral imaging spectroscopy and chemometric. Journal of Near Infrared Spectroscopy, 28(3), 140-147.
  26. Luna E, Flandin A, Cassan C, Prigent S, Chevanne C, Kadiri CF, Gibon Y, Pétriacq P (2020) Metabolomics to exploit the primed immune system of tomato fruit. Metabolites 11: 146. doi: 10.3390/metabo10030096.
  27. Méline V, Brin C, Lebreton G, Ledroit L, Sochard D, Hunault G, Boureau T, Belin E. « A Computation Method Based on the Combination of Chlorophyll Fluorescence Parameters to Improve the Discrimination of Visually Similar Phenotypes Induced by Bacterial Virulence Factors. ». Frontiers in Plant Science. 2020 Vol 26;11:213. doi: 10.3389/fpls.2020.00213. eCollection 2020.
  28. Montazeaud G, Violle C, Roumet P, Rocher A, Ecarnot M, Compan F, Maillet G, Fort F, Fréville H. 2020. Multifaceted functional diversity for multifaceted crop yield: towards ecological assembly rules for varietal mixtures. Journal of Applied Ecology. doi:10.1111/1365-2664.13735
  29. Papoutsoglou EA, Faria D, Arend D, Arnaud E, Athanasiadis IN, Chaves I, Coppens F, Cornut G, Costa BV, Cwiek-Kupczynska H, Droesbeke B, Finkers R, Gruden K, Junker A, King GJ, Krajewski P, Lange M, Laporte M-A, Michotey C, Oppermann M, Ostler R, Poorter H, Rami Rez-Gonzalez R, Ramsak Z, Reif JC, Rocca-Serra P, Sansone S-A, Scholz U, Tardieu F, Uauy C, Usadel B, Visser RGF, Weise S, Kersey PJ, Miguel CM, Adam-Blondon A-F, Pommier C (2020) Enabling reusability of plant phenomic datasets with MIAPPE 1.1. New Phytologist 227: 260-273. doi:10.1111/nph.16544
  30. Paux E, Derory J, Lafarge S, Charmet G, Le Gouis J (2020) Des variétés de blé tendre pour aujourd'hui et demain. Persp Agric 480:39-44
  31. Penouilh-Suzette, C., Pomiès, L., Duruflé, H., Blanchet, N., Bonnafous, F., Dinis, R., Brouard, C., Gody, L., Grassa, C., Heudelot, X., others, 2020. RNA expression dataset of 384 sunflower hybrids in field condition. OCL 27, 36.
  32. Pinochet, X., Debaeke, P., Casadebaig, P., Mestries, E., Langlade, N., 2020. Un modèle au service de l’amélioration des tournesols. Perspectives agricoles 55–57.
  33. Prudent M., Dequiedt S., Sorin C., Girodet S., Nowak V., Duc G., Salon C. and Maron P.M. (2020) The diversity of soil microbial communities matters when legumes face drought. Plant Cell Environ.2020;43:1023–1035 DOI: 10.1111/pce.13
  34. Robert P, Le Gouis J, The BreedWheat Consortium, Rincent R (2020) Combining crop growth modelling with trait-assisted prediction to predict genotype by environment interactions. Frontiers in Plant Science 11:827
  35. Roch L, Prigent P, Klose H, Cakpo C-B, Beauvoit B, Deborde C, Fouillen L, van Delft P, Jacob D, Usadel B, Dai Z, Génard M, Vercambre G, Colombié S, Moing A, Gibon Y (2020) Biomass composition explains fruit relative growth rate and discriminates climacteric from non-climacteric species. Journal of Experimental Botany 71: 5823–5836.
  36. Shinozaki Y, Beauvoit BP, Takahara M, Hao S, Ezura K, Andrieu M-H, Nishida K, Mori K, Suzuki Y, Kuhara S, Enomoto H, Kusano M, Fukushima A, Mori T, Kojima M, Kobayashi M, Sakakibara H, Saito K, Ohtani Y, Bénard C, Prodhomme D, Gibon Y, Ezura H, Ariizumi T (2020) Fruit setting rewires central metabolism via gibberellin cascades. Proceedings of the National Academy of Sciences 117: 23970-23981. doi: 10.1073/pnas.2011859117
  37. Sichert, A., Le Gall, S., Klau, L-J., Laillet, B., Rogniaux, H., Aachmann, F-L., Hehemann, J-H. (2020) Ion-exchange purification and structural characterization of five sulfated fucoidans from brown algae. Glycobiology, cwaa064,
  38. Spor A, Roucou A, Mounier A, Bru D, Breuil M-C, Fort F, Vile D, Roumet P, Philippot L, Violle C (2020) Domestication-driven changes in plant traits associated with changes in the assembly of the rhizosphere microbiota in tetraploid wheat. Scientific reports 10: 12234. doi:10.1038/s41598-020-69175-9.
  39. Steinemann S, Westermeier P (2020) Assessing genetic variation of maize (Zea mays) root DNA density under contrasting water supply. Plant Breeding 139: 241-250. doi:10.1111/pbr.12777.
  40. Talantikite, M., Stimpson, T. C., Gourlay, A., Le Gall, S., Moreau, C., Cranston, E. D., Moran-Mirabal, J., Cathala, B. (2020) Bioinspired Thermo-Responsive Xyloglucan-Cellulose Nanocrystal Hydrogels. ChemRxiv.
  41. Tardieu F (2020) Educated big data to study sensitivity to drought. Nature Food 1: 669-670. doi:10.1038/s43016-020-00187-4.
  42. Tardieu F, I S C Granato, E J Van Oosterom, B Parent, G L Hammer (2020) Are crop and detailed physiological models equally ‘mechanistic’ for predicting the genetic variability of whole-plant behaviour? The nexus between mechanisms and adaptive strategies. in silico Plants, Volume 2, Issue 1, 2020, diaa011,
  43. Terzić, S., Boniface, M.-C., Marek, L., Alvarez, D., Baumann, K., Gavrilova, V., Joita-Pacureanu, M., Sujatha, M., Valkova, D., Velasco, L., Hulke, B.S., Jocić, S., Langlade, N., Muños, S., Rieseberg, L., Seiler, G., Vear, F., 2020. Gene banks for wild and cultivated sunflower genetic resources. OCL 27, 9.
  44. Velumani, K., S. Madec, B. de Solan, R. Lopez-Lozano, J. Gillet, J. Labrosse, S. Jezequel, A. Comar and F. Baret (2020). "An automatic method based on daily in situ images and deep learning to date wheat heading stage." Field Crops Research 252: 107793.
  45. Zhang Y, Krahnert I, Bolze A, Gibon Y, Fernie AR (2020). Adenine nucleotide and nicotinamide adenine dinucleotide measurements in plants. Current Protocols in Plant Biology 5: e20115. doi: 10.1002/cppb.20115



  1. Artzet S, Chen T-W, Chopard J, Brichet N, Mielewczik M, Cohen-Boulakia S, Cabrera-Bosquet L, Tardieu F, Fournier C, Pradal C. 2019. “Phenomenal”: An automatic open source library for 3D shoot architecture reconstruction and analysis for image-based plant phenotyping. bioRxiv, 805739.
  2. Blein-Nicolas M, Negro SS, Balliau T, Welcker C, Bosquet LC, Nicolas SD, Charcosset A, Zivy M. 2019. A proteomics-based systems genetics approach reveals environment-specific loci modulating protein co-expression and drought-related traits in maize. bioRxiv, 636514.
  3. Decros, G., Baldet, P., Beauvoit, B., Stevens, R., Flandin, A., Colombié, S., Gibon, Y., Pétriacq, P. (2019). Get the Balance Right: ROS Homeostasis and Redox Signalling in Fruit. Frontiers in Plant Science, 10, 1-16. DOI: 10.3389/fpls.2019.01091
  4. Decros, G., Beauvoit, B., Colombié, S., Cabasson, C., Bernillon, S., Arrivault, S., Guenther, M., Belouah, I., Prigent, S., Baldet, P., Gibon, Y., Pétriacq, P. (2019). Regulation of Pyridine Nucleotide Metabolism During Tomato Fruit Development Through Transcript and Protein Profiling. Frontiers in Plant Science, 10, 1201. DOI: 10.3389/fpls.2019.01201
  5. van Eeuwijk F, Bustos-Korts D, Millet EJ, Boer M, Kruijer W, Thompson A, Malosetti M, Iwata H, Quiroz R, Kuppe C, Muller O, Blazakis KN, Yu K, Tardieu F, Chapman S (2019) Modelling strategies for assessing and increasing the effectiveness of new phenotyping techniques in plant breeding. Plant Science doi:10.1016/j.plantsci.2018.06.018
  6. Henriet C., Aimé D., Terezol M., Kilandamoko A., Rossin N., Combes-Soia L., Labas V., Serre R.-F., Prudent M., Kreplak J., Vernoud V., Gallardo K. (2019). Water stress combined with Sulfur deficiency in pea affects yield components but mitigates the effect of deficiency on seed globulin composition. J. Exp. Bot. 70:4287-4303.
  7. Jaafar, Z., Mazeau, K., Boissière, A., Le Gall S., Villares A., Vigouroux J., Beury N., Moreau C., Lahaye M., Cathala B. (2019) Meaning of xylan acetylation on xylan-cellulose interactions: a quartz crystal microbalance with dissipation (QCM-D) and molecular dynamic study. Carbohydrate Polymers 226, 115315.
  8. Jay, S., F. Baret, D. Dutartre, G. Malatesta, S. Héno, A. Comar, M. Weiss and F. Maupas (2019). Exploiting the centimeter resolution of UAV multispectral imagery to improve remote-sensing estimates of canopy structure and biochemistry in sugar beet crops. Remote Sensing of Environment 231: 110898.
  9. Jin, X., S. Madec, D. Dutartre, B. de Solan, A. Comar and F. Baret (2019). High-throughput measurements of stem characteristics to estimate ear density and above-ground biomass. Plant Phenomics 2019: 4820305.
  10. Koch G, Rolland G, Dauzat M, Bediee A, Baldazzi V, Bertin N, Guédon Y, Granier C (2019) Leaf Production and Expansion: A Generalized Response to Drought Stresses from Cells to Whole Leaf Biomass—A Case Study in the Tomato Compound Leaf. Plants 8: 409. doi:10.3390/plants8100409.
  11. Larue F., Fumey D., Rouan L., Soulié J-C, Roques S., Beurier G., Luquet D. 2019. Modelling tiller growth and mortality as a sink-driven process using Ecomeristem: implications for biomass sorghum ideotyping. Annals of Botany 124: 675-690, doi: 10.1093/aob/mcz038.
  12. Liu, S., P. Martre, S. Buis, M. Abichou, B. Andrieu and F. Baret (2019). "Estimation of Plant and Canopy Architectural Traits Using the Digital Plant Phenotyping Platform." Plant physiology 181(3): 881-890.
  13. Madec, S., X. Jin, H. Lu, B. De Solan, S. Liu, F. Duyme, E. Heritier and F. Baret (2019). "Ear density estimation from high resolution RGB imagery using deep learning technique." Agricultural and Forest Meteorology 264: 225-234
  14. Mori, K., Beauvoit, B., Biais, B., Chabane, M., Allwood, J. W., Deborde, C., Maucourt, M., Goodacre, R., Cabasson, C., Moing, A., Rolin, D., Gibon, Y. (2019). Central Metabolism Is Tuned to the Availability of Oxygen in Developing Melon Fruit. Frontiers in Plant Science, 10, 594. DOI: 10.3389/fpls.2019.00594
  15. Parent B, Millet EJ, Tardieu F (2019) The use of thermal time in plant studies has a sound theoretical basis provided that confounding effects are avoided. Journal of Experimental Botany 70: 2359-2370. doi:10.1093/jxb/ery402.
  16. Perez RPA, Fournier C, Cabrera-Bosquet L, Artzet S, Pradal C, Brichet N, Chen TW, Chapuis R, Welcker C, Tardieu F. 2019. Changes in the vertical distribution of leaf area enhanced light interception efficiency in maize over generations of selection. Plant, Cell & Environment.
  17. Pommier, C., Michotey, C., Cornut, G., Roumet, P., Duchêne, E., Flores, R., Lebreton, A., Alaux, M., Durand, S., Kimmel, E., Letellier, T., Merceron, G., Laine, M., Guerche, C., Loaec, M., Steinbach, D., Laporte, M. A., Arnaud, E., Quesneville, H., & Adam-Blondon, A. F. (2019). Applying FAIR Principles to Plant Phenotypic Data Management in GnpIS. Plant Phenomics, 2019, 1–15.
  18. Prudent M., Dequiedt S., Sorin C., Girodet S., Nowak V., Duc G., Salon C., Maron P.A. (2020). The diversity of soil microbial communities matters when legumes face drought. Plant Cell Environ. 43:1023-1035.
  19. Reynolds D, Baret F, Welcker C, Bostrom A, Ball J, Cellini F, Lorence A, Chawade A, Khafif M, Noshita K, Mueller-Linow M, Zhou J, Tardieu F (2019) What is cost-efficient phenotyping? Optimizing costs for different scenarios. Plant Science 282: 14-22. doi:10.1016/j.plantsci.2018.06.015.
  20. Rincent R, Malosetti M, Ababaei B, Touzy G, Mini A, Bogard M, Martre P, Le Gouis J, van Eeuwijk F (2019) Using crop growth model stress covariates and AMMI decomposition to better predict genotype by environment interactions. Theoretical and Applied Genetics 132:3399-3411
  21. Roch, L., Dai, Z., Gomes, E., Bernillon, S., Wang, J., Gibon, Y., Moing, A. (2019). Fruit salad in the lab: comparing botanical species to help deciphering fruit primary metabolism. Frontiers in Plant Science, 10, 836. DOI: 10.3389/fpls.2019.00836
  22. Salon, C., Baussart, C., Bernard, C., Bourion, V., Jeudy, C., Lamboeuf, M., Martinet, J., Moreau, D., Prudent, M., Voisin, A.-S. (2019). Phénotypage racinaire haut débit et ses applications à l'étude des interactions plante x microorganisme. Sélectionneur Français, 70, 65-75.
  23. Sartori K, Vasseur F, Violle C, Baron E, Gerard M, Rowe N, Ayala-Garay OJ, Christophe A, Jalón LGd, Masclef D, Harscouet E, Granado MdR, Chassagneux A, Kazakou E, Vile D (2019) Leaf economics and slow-fast adaptation across the geographic range of Arabidopsis thaliana. Scientific Reports 9: 10758. doi:10.1038/s41598-019-46878-2.
  24. Selby, P., Abbeloos, R., Backlund, J. E., Basterrechea Salido, M., Bauchet, G., … Benites-Alfaro, O. E. (2019). BrAPI—an application programming interface for plant breeding applications. Bioinformatics, 35(20), 4147–4155.
  25. Touzy G, Rincent R, Bogard M, Lafarge S, Dubreuil P, Mini A, Deswarte J-C, Beauchene K, Le Gouis J, Praud S (2019). Using environmental clustering to identify specific drought tolerance QTLs in bread wheat (T. aestivum L.). Theoretical and Applied Genetics 132:2859-2880.
  26. Verhertbruggen, Y., Falourd, X., Sterner, M., Guillon, F., Girousse, C., Foucat, L., Le Gall, S., Chateigner-Boutin, A-L., Saulnier, L., Challenging the putative structure of mannan in wheat (Triticum aestivum) endosperm, Carbohydrate Polymers 224: 115063.
  27. Alvarez Prado S, Sanchez I, Cabrera-Bosquet Ll, Grau A, Welcker C,Tardieu F and Hilgert N. 2019. Cleaning or not cleaning phenotypic datasets for outlier plants in genetic analyses? Journal of Experimental Botany, Vol. 70 n°15: 3693-3698. doi:10.1093/jxb/erz191
  28. Avramova V, Meziane A, Bauer E, Blankenagel S, Eggels S, Gresset S, Grill E, Niculaes C, Ouzunova M, Poppenberger B, Presterl T, Rozhon W, Welcker C, Yang Z, Tardieu F, Schön C-C (2019) Carbon isotope composition, water use efficiency, and drought sensitivity are controlled by a common genomic segment in maize. Theoretical and Applied Genetics 132: 53-63.
  29. Beauchêne K, Leroy F, Fournier A, Huet C, Bonnefoy M, Lorgeou J, de Solan B, Piquemal B, Thomas and Cohan J-P (2019) Management and Characterization of Abiotic Stress via PhénoField®, a High-Throughput Field Phenotyping Platform. Front. Plant Sci. 10:904. doi: 10.3389/fpls.2019.00904
  30. Chen TW, Cabrera Bosquet L, Alvarez Prado S, Perez R, Artzet S, Pradal C, Coupel-Ledru A, Fournier C, Tardieu F (2019) Genetic and environmental dissection of biomass accumulation in multi-genotype maize canopies. Journal of Experimental Botany 70: 2523–2534. doi:10.1093/jxb/ery309
  31. Guérin C, Roche J, Allard V, Ravel C, Bouzidi MF, Mouzeyar S (2019) Genome-wide analysis, expansion and expression of the NAC family under abiotic stresses in bread wheat (T. aestivum L.). PLos ONE 14: e0213390
  32. Millet EJ, Kruijer W,  Coupel-Ledru A, Alvarez Prado S, Cabrera-Bosquet L, Lacube S, Charcosset A, Welcker C, van Eeuwijk F, Tardieu F (2019) Genomic prediction of maize yield across European environmental conditions. Nature Genetics 51, 952-956.
  33. Neveu, P., A. Tireau, N. Hilgert, V. Nègre, J. Mineau-Cesari, N. Brichet, R. Chapuis, I. Sanchez, C. Pommier, B. Charnomordic, F. Tardieu and L. Cabrera-Bosquet. 2019. Dealing with multi-source and multi-scale information in plant phenomics: the ontology-driven Phenotyping Hybrid Information System. New Phytologist 221: 588-601.
  34. Roitsch T, Cabrera-Bosquet L, Fournier A, Ghamkhar K, Jiménez-Berni J, Pinto F, Ober ES (2019) Review: New sensors and data-driven approaches—A path to next generation phenomics. Plant Science 282: 2-10. doi:10.1016/j.plantsci.2019.01.011


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