Titlebook: Decision Support Systems for Weed Management; Guillermo R. Chantre,José L. González-Andújar Book 2020 Springer Nature Switzerland AG 2020

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Weed Emergence Models perspectives: a reductionist/mechanistic approach and an empirical modelling viewpoint. While the former provides a close description of the basic ecophysiological processes underlying weed emergence (i.e. seed dormancy, germination and pre-emergence growth), they usually require a large amount of

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Site-Specific Based Models-DSS), recent advances in the use of remote and ground platforms and sensors for information gathering and processing, and initial experiences translating this information into chemical and physical weed control actuations through decision algorithms and models.

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Theory and Practice for Environmental Risk Assessment: Understanding the Trade-Off Between the Benefowever, they have also jeopardized agroecosystem sustainability by causing negative alterations of social and environmental subsystems. The physicochemical properties of herbicides (volatility, adsorption, or water solubility) can make them persist in the soil, air, and water, changing the structure

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Environmental Risk Indicators for Weed Management: A Case Study of Ecotoxicity Assessment Using Fuzzr, development of theoretical frameworks and tools is necessary to allow for environmental assessment of herbicides. In this chapter, we present a series of elements that should be considered for designing these types of tools. In addition, we describe the structure of RIPEST, a simple model based o

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Ryegrass Integrated Management (RIM)–Based Decision Support Systemto manage herbicide resistance (HR). Its success as a DSS for HR management is proven by the various adaptations of RIM to a range of weed species and/or cropping systems: Multispecies RIM for . and . in Australia, Wild Radish RIM for . in Australia, PIM for . in Spain, RIMPhil for . in the Philippi

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