Building sustainable cropping systems by combining scientific and empirical knowledge. The example of soil-born disease control on vegetable sheltered crops
| Autor: | Tchamitchian, Marc, Navarrete, Mireille, Bressoud, Frederique, Fauriel, Joel, Pares, Laure |
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| Přispěvatelé: | Unité de recherche d'Écodéveloppement (ECODEVELOPPEMENT), Institut National de la Recherche Agronomique (INRA), Domaine expérimental horticole du Mas Blanc (MAS BLANC) |
| Jazyk: | angličtina |
| Rok vydání: | 2008 |
| Předmět: |
résistance aux maladies
solarisation [SDV]Life Sciences [q-bio] durabilité CROPPING SYSTEMS INTELLIGENCE ARTIFICIELLE MARKET-GARDENING SCIENTIFIC KNOWLEDGE BASE DE DONNEES culture protegée rotation culturale maraîchage [SHS]Humanities and Social Sciences ALTERNATIVE TECHNIQUE matière organique intrant technique culturale EXPERT KNOWLEDGE système de culture pesticide |
| Zdroj: | Book of Abstracts (Symposium on Horticulture in Europe) 1. Symposium on Horticulture in Europe (SHE) 1. Symposium on Horticulture in Europe (SHE), Feb 2008, Vienna, Austria Symposium on Horticulture in Europe. Book of Abstracts. 2008; 1. Symposium on Horticulture in Europe (SHE), Vienna, AUT, 2008-02-17-2008-02-20, 141-142 |
| Popis: | Les cultures maraîchères sous abris doivent faire face à de nouveaux enjeux sur la réduction des produits phytosanitaires tout en maintenant une qualité visuelle satisfaisante. L’objectif de ce projet est de construire des systèmes de culture durables en utilisant des techniques alternatives comme les successions de culture diversifiées, la solarisation ou l’utilisation d’amendements organiques, et en optimisant leur combinaison. Comme les connaissances scientifiques sont très partielles dans ce domaine, le projet s’appuie également sur les savoirs des agriculteurs et de conseillers agricoles. Après avoir construit une base de données qui permet de comparer avec le même formalisme les connaissances scientifiques issues de la littérature et les connaissances expertes nous identifions les complémentarités et les contradictions entre ces connaissances et cherchons à les analyser. Les méthodes d’Intelligence Artificielle comme la théorie de l’évidence ou la théorie de l’argumentation seront testées sur ces données. L’objectif, une fois que ce jeu de connaissance aura été validé, est de construire un modèle des interactions entre techniques culturales, processus biologiques et état du milieu pour simuler l’évolution des attaques de pathogènes. Ce modèle sera utilisé avec des agriculteurs et des conseillers agricoles pour concevoir et évaluer de nouveaux systèmes de culture alternatifs. Protected vegetable crops are facing new stakes as regards the limiting use of chemical products to avoid pesticide residues in the food products and in ground water, while avoiding any visual symptom of pests and diseases to agree with marketing-firm requirements. The aim of this project is to build sustainable cropping systems by using alternative techniques such as diversified crop sequences, thermal disinfection or organic manure and optimizing their combination. This goal cannot be reached using the sole scientific knowledge since systemic knowledge on that subject is very poor. However, a wealth of information and knowledge is available from local practitioners (farmers and technical advisors), especially on the interactions betweens techniques, environment and the expression of pathogens’ activity on the plants. The first step of the project has been to build a database which enables to use a uniform representation frame for scientific literature and empirical knowledge extracted in on-farm surveys. This enables to analyse the effects of each cropping technique on the evolution of soil-born pathogens, taking into account the pedoclimatic conditions in which the technique has been applied and the whole cropping system at hand. The second step is to use this framework to determine the effects of a particular technique or combination of techniques on a specific pathogen, and identify the contracdisction between various knowledge. Methods of AI, like evidence theory or argumentation framework shall be tested on these data. The third step will be triggered when no conclusion can be drawn on the effect of one practice on the development of pathogens, because there are too many contradictions between growers and/or with scientific current knowledge. Then, group discussion between growers and advisers will be conducted to get a more experienced insight and to attempt to identify the roots of the contradiction. If necessary, experimental plots will be designed with the growers to conduct a focussed study of the problem. The last step is to build a dynamic model of the interactions between cropping techniques, biological processes and environmental conditions to simulate the evolution of soil born pathogens in given cropping systems. This model will be used, with growers and advisors, in an iterative process of design, evaluation by the model and improvement of new cropping systems |
| Databáze: | OpenAIRE |
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