@article{fdi:010079824,
  title = {{L}everaging genome-enabled growth models to study shoot growth responses to water deficit in rice},
  author = {{C}ampbell, {M}. {T}. and {G}rondin, {A}lexandre and {W}alia, {H}. and {M}orota, {G}.},
  editor = {},
  language = {{ENG}},
  abstract = {{E}lucidating genotype-by-environment interactions and partitioning its contribution to phenotypic variation remains a challenge for plant scientists. {W}e propose a framework that utilizes genome-wide markers to model genotype-specific shoot growth trajectories as a function of time and soil water availability. {A} rice diversity panel was phenotyped daily for 21 d using an automated, high-throughput image-based, phenotyping platform that enabled estimation of daily shoot biomass and soil water content. {U}sing these data, we modeled shoot growth as a function of time and soil water content, and were able to determine the time point where an inflection in the growth trajectory occurred. {W}e found that larger, more vigorous plants exhibited an earlier repression in growth compared with smaller, slow-growing plants, indicating a trade-off between early vigor and tolerance to prolonged water deficits. {G}enomic inference for model parameters and time of inflection ({TOI}) identified several candidate genes. {T}his study is the first to utilize a genome-enabled growth model to study drought responses in rice, and presents a new approach to jointly model dynamic morpho-physiological responses and environmental covariates.},
  keywords = {{A}quaporin ; drought ; genome-wide association study ; genomics ; growth ; model ; phenomics ; rice},
  booktitle = {},
  journal = {{J}ournal of {E}xperimental {B}otany},
  volume = {71},
  numero = {18},
  pages = {5669--5679},
  ISSN = {0022-0957},
  year = {2020},
  DOI = {10.1093/jxb/eraa280},
  URL = {https://www.documentation.ird.fr/hor/fdi:010079824},
}