  This work proposes a framework using temporal data and domain knowledge in
order to analyze complex agronomical features. The expertise is first
formalized in an ontology, under the form of concepts and relationships between
them, and then used in conjunction with raw data and mathematical models to
design a software sensor. Next the software sensor outputs are put in relation
to product quality, assessed by quantitative measurements. This requires the
use of advanced data analysis methods, such as functional regression. The
methodology is applied to a case study involving an experimental design in
French vineyards. The temporal data consist of sap flow measurements, and the
goal is to explain fruit quality (sugar concentration and weight), using vine's
water courses through the various vine phenological stages. The results are
discussed, as well as the method genericity and robustness.
