Decision Support Systems for Weed Management

Editors: Guillermo R. Chantre, José L. González-Andújar.Weed management Decision Support Systems (DSS) are increasingly important computer-based tools for modern agriculture. Nowadays, extensive agriculture has become highly dependent on external inputs and both economic costs, as well the negative environmental impact of agricultural activities, demands knowledge-based technology for the optimization and protection of non-renewable resources. In this context, weed management strategies should aim to maximize economic profit by preserving and enhancing agricultural systems. Although previous contributions focusing on weed biology and weed management provide valuable insight on many aspects of weed species ecology and practical guides for weed control, no attempts have been made to highlight the forthcoming importance of DSS in weed management. This book is a first attempt to integrate 'concepts and practice' providing a novel guide to the state-of-art of DSS and the future prospects which hopefully would be of interest to higher-level students, academics and professionals in related areas

An ecological future for weed science to sustain crop production and the environment. A review

Sustainable strategies for managing weeds are critical to meeting agriculture's potential to feed the world's population while conserving the ecosystems and biodiversity on which we depend. The dominant paradigm of weed management in developed countries is currently founded on the two principal tools of herbicides and tillage to remove weeds. However, evidence of negative environmental impacts from both tools is growing, and herbicide resistance is increasingly prevalent. These challenges emerge from a lack of attention to how weeds interact with and are regulated by the agroecosystem as a whole. Novel technological tools proposed for weed control, such as new herbicides, gene editing, and seed destructors, do not address these systemic challenges and thus are unlikely to provide truly sustainable solutions. Combining multiple tools and techniques in an Integrated Weed Management strategy is a step forward, but many integrated strategies still remain overly reliant on too few tools. In contrast, advances in weed ecology are revealing a wealth of options to manage weedsat the agroecosystem levelthat, rather than aiming to eradicate weeds, act to regulate populations to limit their negative impacts while conserving diversity. Here, we review the current state of knowledge in weed ecology and identify how this can be translated into practical weed management. The major points are the following: (1) the diversity and type of crops, management actions and limiting resources can be manipulated to limit weed competitiveness while promoting weed diversity; (2) in contrast to technological tools, ecological approaches to weed management tend to be synergistic with other agroecosystem functions; and (3) there are many existing practices compatible with this approach that could be integrated into current systems, alongside new options to explore. Overall, this review demonstrates that integrating systems-level ecological thinking into agronomic decision-making offers the best route to achieving sustainable weed management

A TaqMan real-time PCR assay for Rhizoctonia cerealis and its use in wheat and soil

Rhizoctonia cerealis causes sharp eyespot in cereals and the pathogen survives as mycelia or sclerotia in soil. Real-time Polymerase Chain Reaction (qPCR) assays based on TaqMan chemistry are highly suitable for use on DNA extracted from soil. We report here the first qPCR assay for R. cerealis using TaqMan primers and a probe based on a unique Sequence Characterised Amplified Region (SCAR). The assay is highly specific and did not amplify DNA from a range of other binucleate Rhizoctonia species or isolates of anastomosis groups of Rhizoctonia solani. The high sensitivity of the assay was demonstrated in soils using a bulk DNA extraction method where 200 μg sclerotia in 50 g of soil were detected. DNA of the pathogen could also be amplified from asymptomatic wheat plants. Using the assay on soil samples from fields under different crop rotations, R. cerealis was most frequently detected in soils where wheat was grown or soil under pasture. It was detected least frequently in fields where potatoes were grown. This study demonstrates that assays derived from SCAR sequences can produce specific and sensitive qPCR assays

Towards an optimal management regime to facilitate the coexistence of GM herbicide tolerant and non-GM oilseed rape

Although a national strategy for the coexistence of GM and conventional/organic crops in Ireland has been published (McGill et al 2005) measures pertaining to the coexistence of GM and non-GM oilseed rape (OSR) crops was omitted pending the completion o

How to manage the impact of gene flow on oilseed rape grain quality? Simulation case studies of three contrasted landscapes

International audienceGrain admixture due to gene flow of oilseed rape (OSR) could be economically damaging. Different strategies are currently used or proposed to anage grain quality, ranging from homogenisation at the silo level to tactical decision rules at the field level. The relevance of these general trategies was appraised in the case of genetically modified (GM) OSR in three contrasted regions in Europe: Beauce Blésoise (France), Schleswig-Flensburg (Germany), and Fife (UK). Field patterns, crop allocation and agricultural practices were derived from existing datasets and complementary field surveys. Then a gene flow simulator was used to assess how the local contexts influenced the grain admixture between GM and non-GM OSR (without separation measures). The simulations showed that grain admixtures in fields followed a leptokurtic curve. While, however, the worst case was similar in the three regions, the median differed greatly depending on contextual factors such as the size and arrangement of fields. Grain admixture very rarely exceeded the 0.9% threshold for non-GM products if assessed at the level of the silo, at which the grains from all non-GM crops were combined, while maintaining crops below the threshold at the field level required management of a few high risk situations. Analysing grain admixtures and commercial risks at different decision levels (field, silo) demonstrated the efficiency of “flexible” as opposed to “rigid” measures, but this technical analysis did not take other criteria like regulatory issues into account