L'engagement dans des collectifs de production de connaissance en ligne. Le cas GeoRezo

National audienceNous discutons, à partir d'une étude de cas, GeoRezo, l'implication des participants à des collectifs ou projets qui produisent de la connaissance ou des biens (type logiciels) ou des services en ligne. Cette " carrière " est vue sous deux angles : les facteurs favorisant des prises de rôles ; les raisons de l'engagement

Utilisation de l'indicateur I-PHY comme outil d'aide à la décision en verger d'agrumes à la Réunion. Le cas de la lambda-cyhalothrine

I-PHY de la méthode INDIGO® est un indicateur qui permet d'évaluer les impacts des pesticides sur l'environnement à l'échelle de la parcelle. Basé sur un système expert, il prend en compte les caractéristiques des substances actives (sa), de la parcelle et les conditions d'application. Il renvoie un score I-PHYsa sous la forme d'une note sur 10. Dans ces conditions, I-PHY est un indicateur robuste dont les résultats permettent d'identifier des pratiques à risque pour l'environnement. Cependant, le simple résultat sous la forme d'un score ne fait pas pour autant d'I-PHY un outil d'aide à la décision en l'état. Nous proposons dans cet article d'utiliser les marges de progrès entre les différents scores (IPHY min et max) pour construire des arbres de régression permettant d'identifier les variables à l'origine du score et d'utiliser I-PHY comme outil d'aide à la décision. A titre d'illustration de notre méthode, nous avons étudié les risques environnementaux liés à l'usage de la lambda-cyhalothrine chez trois producteurs d'agrumes à la Réunion. Cette analyse nous a permis d'identifier les leviers techniques mobilisables par ces producteurs. (Résumé d'auteur

L'engagement dans des collectifs de production de connaissance en ligne. Le cas GeoRezo

National audienc

Helping farmers to reduce herbicide environmental impacts

International audienceWhile pesticides help to effectively control crop pests,their collateral effects often harm the environment. On the French island of Reunion in the Indian Ocean, over 75% of the pesticides used are herbicides and they are regularly detected in water. Agri-environmental models and pesticide risk indicators can be used to predict and to help pesticide users to reduce environmental impacts. However, while the complexity of models often limits their use to the field of research, pesticide risk indicators, which are easier to implement, do not explicitly identify the technical levers that farmers can act upon to limit such transfers on their scale of action (the field). The aim of this article is to contribute to developing a decision support tool to guide farmers in implementing relevant practices regarding the reduction of pesticide transfers. In this article, we propose a methodology based on classification and regression trees. We applied our methodology to a pesticide risk indicator (I-PHY indicator) for identifying the importance of the variables, their interactions and relative weight in contributing to the score of the indicator. We applied our methodology to the assessment of transfer risks linked to the use of 20 herbicides applied to all soils in Reunion and according to different climate, plot management and product application scenarios (4096 scenarios tested). We constructed regression trees which identified, for each herbicide on each soil type, the contribution made by each input variable to the construction of the indicator score. The tree is represented graphically, and this aids exploration and understanding. The 20 herbicides were divided into 3 groups that differed through the main contributing variable to the indicator score. These variables were all technical levers available to farmers to limit transfer risks. These trees then become decision support tools specific to each pesticide user, enabling them to take appropriate decisions with a view to reducing pesticide environmental impacts

In silico QTL mapping in an oil palm breeding program reveals a quantitative and complex genetic resistance to Ganoderma boninense

International audienceBasal stem rot caused by Ganoderma boninense is the major threat to oil palm cultivation in Southeast Asia, which accounts for 80% of palm oil production worldwide, and this disease is increasing in Africa. The use of resistant planting material as part of an integrated pest management of this disease is one sustainable solution. However, breeding for Ganoderma resistance requires long-term and costly research, which could greatly benefit from marker-assisted selection (MAS). In this study, we evaluated the effectiveness of an in silico genetic mapping approach that took advantage of extensive data recorded in an ongoing breeding program. A pedigree-based QTL mapping approach applied to more than 10 years' worth of data collected during pre-nursery tests revealed the quantitative nature of Ganoderma resistance and identified underlying loci segregating in genetic diversity that is directly relevant for the breeding program supporting the study. To assess the consistency of QTL effects between pre-nursery and field environments, information was collected on the disease status of the genitors planted in genealogical gardens and modeled with pre-nursery-based QTL genotypes. In the field, individuals were less likely to be infected with Ganoderma when they carried more favorable alleles at the pre-nursery QTL. Our results pave the way for a MAS of Ganoderma resistant and high yielding planting material, and the provided proof-of-concept of this efficient and cost-effective approach could motivate similar studies based on diverse breeding programs