@article{fdi:010088848,
  title = {{C}alibrating the {STICS} soil-crop model to explore the impact of agroforestry parklands on millet growth},
  author = {{S}ow, {S}. and {S}enghor, {Y}. and {S}adio, {K}. and {V}ezy, {R}. and {R}oupsard, {O}. and {A}ffholder, {F}. and {N}'{D}ienor, {M}. and {C}lermont {D}auphin, {C}athy and {G}aglo, {E}. {K}. and {B}a, {S}. {Y}. {A}. and {T}ounkara, {A}. and {B}alde, {A}. {B}. and {A}gbohessou, {Y}. and {S}eghieri, {J}osiane and {S}all, {S}. {N}. and {C}ouedel, {A}. and {L}eroux, {L}. and {J}ourdan, {C}. and {D}iaite, {D}. {S}. and {F}alconnier, {G}. {N}.},
  editor = {},
  language = {{ENG}},
  abstract = {{C}ontext: {A}groforestry systems provide critical benefits for food security and climate change mitigation. {Y}et, they are complex and heteregoneous sytems hard to optimize. {T}he use of process-based crop models provides an opportunity to understand better the interactions between soil, crop, tree and climate and explore the impact of agroforestry on crop growth, for contrasting crop management. {O}bjective: {T}he objectives of this study were to i) calibrate the soil-crop {STICS} model for pearl millet ({P}ennisetum glaucum) in order to simulate millet potential growth and impact of water and nitrogen limitations on millet growth in open fields and ii) explore the impacts of the parkland tree {F}aidherbia albida on millet performance for contrasting {N} fertilizer inputs. {M}ethods: {W}e gathered a comprehensive database of 28 agronomically contrasting situations, ranging from nearpotential growth to drought- and {N}-stress, either on-station or in a farmer's home- or bush-fields. {P}arameters governing relevant plant and soil processes for grain yield were calibrated in a stepwise procedure. {T}he calibrated model was used to explore the impact on millet growth of the widely reported benefits of {F}aidherbia albida, namely a minimum reduction in radiation thanks to the peculiar reverse phenology of this tree, improvement of soil water content at the beginning of the growing season and of organic nitrogen in the topsoil. {R}esults: {M}odel simulations with the calibration dataset were reasonably accurate for aboveground biomass and grain yield. {N}ormalized {R}oot {M}ean {S}quare {E}rrors (n{RMSE}) for these variables were 29% and 26%, respectively;},
  keywords = {{C}rop model ; {S}ustainable intensification ; {C}alibration ; {V}alidation ; {V}irtual experiment ; {S}enegal ; {SENEGAL}},
  booktitle = {},
  journal = {{F}ield {C}rops {R}esearch},
  volume = {306},
  numero = {},
  pages = {109206 [15 p.]},
  ISSN = {0378-4290},
  year = {2024},
  DOI = {10.1016/j.fcr.2023.109206},
  URL = {https://www.documentation.ird.fr/hor/fdi:010088848},
}