R. Boll, A. Bout, S. Doise, X. Bernardet , C. Poncet
Acquisition of accurate statistics regarding pest outbreak factors on cultivated crops leads to invaluable experimental data. Abundant information is generally recorded in a warehouse database, left to be analyzed at a later date or to be quickly communicated to the users in a structured way. The OLAP (Online Analytical Processing) concept mines the warehouse database to report answers to specific questions asked by researchers, technicians or advisors. This is in line with the spirit of a data market. For our scientific purposes, the database contains biotic or abiotic measures carried out on spatial and temporal scales. Any available administrative, descriptive or factual information is also recorded as reference data for modeling applications. The database is web-hosted and uses MySQL and phpMyAdmin languages. Software linked to the database has been developed according to the most recurring needs. The different modules of the Sophi@data_market are (1) a data entry form creator to minimize the recording steps and mistakes; (2) a monitoring board displaying chronologic maps and statistics; (3) a climatic reporting application for the corresponding data; (4) a genetic of population toolbox to record and to search among genotyping sequences of individuals (5) a set of statistical models to quantify and forecast the dynamics of population trends and (6) a hands-on module for practical pest and disease identification. An on-going trial evaluates to decrease the use of pesticides on cut rose crops in greenhouse. This challenge depends mainly on estimation and risk taking. A global scouting (sampling) for bio-agressors is performed weekly and the data are immediately exploited for decision-making purposes. The crop manager makes his decision based on his own experience and with help of the data marketing.
Boll, R., Bout, A., Doise, S., Bernardet , X. and Poncet, C. (2011). "DATA_MARKET" AS A REALISTIC TOOL FOR DECISION-MAKING IN THE INTEGRATED PEST MANAGEMENT CHALLENGE . Acta Hortic. 919, 163-170
DOI: 10.17660/ActaHortic.2011.919.20
pest monitoring, quick sampling, database, data reporting, data mining

Acta Horticulturae