BibTeX
@INCOLLECTION{
         Lauvernet2012UAD,
       title = "Using Automatic Differentiation to Study the Sensitivity of a Crop Model",
       doi = "10.1007/978-3-642-30023-3_6",
       author = "Claire Lauvernet and Laurent Hasco{\"e}t and Fran\c{c}ois-Xavier Le
         Dimet and Fr{\'e}d{\'e}ric Baret",
       abstract = "Automatic Differentiation (AD) is often applied to codes that solve partial
         differential equations, e.g. in geophysical sciences or Computational Fluid Dynamics. In agronomy,
         the differentiation of crop models has never been performed since these models are more empirical
         than fully mecanistic, derived from equations. This study shows the feasibility of constructing the
         adjoint model of a crop model referent in the agronomic community (STICS) with the TAPENADE tool,
         and the use of this accurate adjoint to perform some sensitivity analysis. This paper reports on the
         experience from AD users of the environmental domain, in which AD usage is not very widespread.",
       pages = "59--69",
       crossref = "Forth2012RAi",
       booktitle = "Recent Advances in Algorithmic Differentiation",
       series = "Lecture Notes in Computational Science and Engineering",
       publisher = "Springer",
       address = "Berlin",
       volume = "87",
       editor = "Shaun Forth and Paul Hovland and Eric Phipps and Jean Utke and Andrea Walther",
       isbn = "978-3-540-68935-5",
       issn = "1439-7358",
       year = "2012",
       ad_tools = "TAPENADE"
}