Debaeke P., Attia F., Champolivier L., Dejoux J.-F., Micheneau A., Bitar A. Al, Trépos R., (2023). Forecasting sunflower grain yield using remote sensing data and statistical models. European Journal of Agronomy, 142, 126677.doi: https://doi.org/10.1016/j.eja.2022.126677.

Nicol S., Cros M.-J., Peyrard N., Sabbadin R., Trépos R., Fuller R. A., Woodworth B. K., (2023). FlywayNet: A hidden semi-markov model for inferring the structure of migratory bird networks from count data. Methods in Ecology and Evolution, 14(1), 265–279.doi: https://doi.org/10.1111/2041-210X.14011.

Casadebaig P., Gauffreteau A., Landré A., Langlade N., Mestries E., Sarron J., Trépos R., Vincourt P., Debaeke P., (2022). Optimized cultivar deployment improves the efficiency and stability of sunflower crop production at national scale. Theoretical and Applied Genetics,.doi: 10.1007/s00122-022-04072-5.

Ravier C., Sabatier R., Beillouin D., Meynard J.-M., Trépos R, Jeuffroy M.-H., (2021). Decision rules for managing n fertilization based on model simulations and viability assessment. European Journal of Agronomy, 125, 126247.doi: 10.1016/j.eja.2021.126247.

Graux A.-I., Resmond R., Casellas E., Delaby L., Faverdin P., Bas C. Le, Ripoche D., Ruget F., Thérond O., Vertès F., Peyraud J.-L., (2020). High-resolution assessment of French grassland dry matter and nitrogen yields. European Journal of Agronomy, 112, 125952.doi: 10.1016/j.eja.2019.125952.

Trépos R., Champolivier L., Dejoux J.-F., Al Bitar A., Casadebaig P., Debaeke P., (2020). Forecasting sunflower grain yield by assimilating leaf area index into a crop model. Remote Sensing, 12(22).doi: 10.3390/rs12223816.

Constantin J., Raynal H., Casellas E., Hoffmann H., Bindi M., Doro L., Eckersten H., Gaiser T., Grosz B., Haas E., Kersebaum K.-C., Klatt S., Kuhnert M., Lewan E., Maharjan G. R., Moriondo M., Nendel C., Roggero P. P., Specka X., Trombi G., Villa A., Wang E., Weihermüller L., Yeluripati J., Zhao Z., Ewert F., Bergez J.-E., (2019). Management and spatial resolution effects on yield and water balance at regional scale in crop models. Agricultural and Forest Meteorology, 275, 184–195.doi: 10.1016/j.agrformet.2019.05.013.

Robert M., Thomas A., Sekhar M., Raynal H., Casellas E., Casel P., Chabrier P., Joannon A., Bergez J.-E., (2018). A dynamic model for water management at the farm level integrating strategic, tactical and operational decisions. Environmental Modelling & Software, 100, 123–135.doi: 10.1016/j.envsoft.2017.11.013.

Beillouin D., Leclère M., Barbu C. M., Bénézit M., Trépos R., Gauffreteau A., Jeuffroy M.-H., (2018). Azodyn-barley, a winter-barley crop model for predicting and ranking genotypic yield, grain protein and grain size in contrasting pedoclimatic conditions. Agricultural and Forest Meteorology, 262, 237–248.doi: 10.1016/j.agrformet.2018.06.002.

Picheny V., Trépos R., Casadebaig P., (2017). Optimization of black-box models with uncertain climatic inputs. Application to sunflower ideotype design.. PLoS ONE, 12(5).doi: 10.1371/journal.pone.0176815.

Picheny V., Casadebaig P., Trépos R., Faivre R., Da Silva D., Vincourt P., Costes E., (2017). Using numerical plant models and phenotypic correlation space to design achievable ideotypes. Plant, Cell and Environment, 40(9), 1926 – 1939.doi: 10.1111/pce.13001.