Recent advances in high-throughput technologies have resulted in tremendous increase in the amount of data in the agronomic domain. This data explosion in conjunction with its heterogeneity presents a major challenge in adopting an integrative approach towards research. There is an urgent need to effectively integrate and assimilate complementary information to understand the biological system in its entirety. To this end, the Semantic Web offers a stack of powerful technologies for the integration of information from diverse sources and make knowledge explicit thanks to ontologies. We have developed AgroLD (www.agrold.org), a knowledge based system that exploits the Semantic Web technology and some of the relevant standard domain ontologies, to integrate genome to phenome information on plant species widely studied by the plant science community. We present some integration results of the project, which initially focused on genomics, proteomics and phonemics. Currently, AgroLD contains hundreds millions of triples created by annotating more than 50 datasets coming from major rice databases with some relevant ontologies. Our objective is to offer a domain specific knowledge platform to solve complex biological and agronomical questions related to the implication of genes or proteins in, for instances, plant disease resistance or high yield traits. We expect the resolution of these questions to facilitate the formulation of new scientific hypotheses to be validated with a knowledge-oriented approach.