Mette Sønderskov

Decision Support System for Optimized Herbicide Dose in Spring Barley

Abstract Crop Protection Online (CPO) is a decision support system, which integrates decision algorithms quantifying the requirement for weed control and a herbicide dose model. CPO was designed to be used by advisors and farmers to optimize the choice of herbicide and dose. The recommendations from CPO for herbicide application in spring barley in Denmark were validated through field experiments targeting three levels of weed control requirement. Satisfactory weed control levels at harvest were achieved by a medium control level requirement generating substantial herbicide reductions (∼ 60% measured as the Treatment Frequency Index (TFI)) compared to a high level of required weed control. The observations indicated that the current level of weed control required is robust for a range of weed scenarios. Weed plant numbers 3 wk after spraying indicated that the growth of the weed species were inhibited by the applied doses, but not necessarily killed, and that an adequate level of control was reached later in the season through crop competition. Nomenclature: Spring barley; Hordeum vulgare L. Resumen Crop Protection Online (CPO, Protección de Cultivos en Línea) es un sistema de ayuda para la toma de decisión, el cual integra algoritmos que cuantifican el requerimiento de control de malezas y un modelo de dosis de herbicidas. CPO fue diseñado para ser usado por asesores y productores para optimizar la selección de herbicidas y dosis. Las recomendaciones de CPO para la aplicación de herbicidas en cebada de primavera en Dinamarca fueron validadas mediante experimentos de campo enfocados a tres niveles de requerimientos de control de malezas. Niveles satisfactorios de control de malezas al momento de la cosecha se alcanzaron con un nivel de requerimiento de control medio, lo que generó reducciones sustanciales de herbicidas (∼60% medido como el índice de frecuencia de tratamiento (TFI)) al compararse con el nivel de requerimiento de control de malezas alto. Las observaciones indicaron que el nivel actual de requerimientos de control de malezas es robusto para un rango amplio de escenarios de malezas. Los números de plantas de malezas, 3 semanas después de la aplicación, indicaron que el crecimiento de las especies de malezas fue inhibido por las dosis aplicadas, pero estas no necesariamente murieron, y que un nivel adecuado de control fue alcanzado después en la temporada debido a la competencia del cultivo.

Combining a weed traits database with a population dynamics model predicts shifts in weed communities

A functional approach to predicting shifts in weed floras in response to management or environmental change requires the combination of data on weed traits with analytical frameworks that capture the filtering effect of selection pressures on traits. A weed traits database (WTDB) was designed, populated and analysed, initially using data for 19 common European weeds, to begin to consolidate trait data in a single repository. The initial choice of traits was driven by the requirements of empirical models of weed population dynamics to identify correlations between traits and model parameters. These relationships were used to build a generic model, operating at the level of functional traits, to simulate the impact of increasing herbicide and fertiliser use on virtual weeds along gradients of seed weight and maximum height. The model generated ‘fitness contours’ (defined as population growth rates) within this trait space in different scenarios, onto which two sets of weed species, defined as common or declining in the UK, were mapped. The effect of increasing inputs on the weed flora was successfully simulated; 77% of common species were predicted to have stable or increasing populations under high fertiliser and herbicide use, in contrast with only 29% of the species that have declined. Future development of the WTDB will aim to increase the number of species covered, incorporate a wider range of traits and analyse intraspecific variability under contrasting management and environments.

Reviewing research priorities in weed ecology, evolution and management : a horizon scan

Summary Weedy plants pose a major threat to food security, biodiversity, ecosystem services and consequently to human health and wellbeing. However, many currently used weed management approaches are increasingly unsustainable. To address this knowledge and practice gap, in June 2014, 35 weed and invasion ecologists, weed scientists, evolutionary biologists and social scientists convened a workshop to explore current and future perspectives and approaches in weed ecology and management. A horizon scanning exercise ranked a list of 124 pre‐submitted questions to identify a priority list of 30 questions. These questions are discussed under seven themed headings that represent areas for renewed and emerging focus for the disciplines of weed research and practice. The themed areas considered the need for transdisciplinarity, increased adoption of integrated weed management and agroecological approaches, better understanding of weed evolution, climate change, weed invasiveness and finally, disciplinary challenges for weed science. Almost all the challenges identified rested on the need for continued efforts to diversify and integrate agroecological, socio‐economic and technological approaches in weed management. These challenges are not newly conceived, though their continued prominence as research priorities highlights an ongoing intransigence that must be addressed through a more system‐oriented and transdisciplinary research agenda that seeks an embedded integration of public and private research approaches. This horizon scanning exercise thus set out the building blocks needed for future weed management research and practice; however, the challenge ahead is to identify effective ways in which sufficient research and implementation efforts can be directed towards these needs.

Crop Protection Online—Weeds: A Case Study for Agricultural Decision Support Systems

Crop Protection Online—Weeds (CPO-Weeds) is a decision support system for weed control developed in Denmark and later adjusted to conditions in several other countries. In Denmark, the DSS includes all major crops and available herbicides. The background for developing CPO-Weeds was a political motivation for reducing pesticide use and the concept of factor-adjusted doses. It was never the intention to build a sophisticated scientific model, but rather to design a simple user-friendly system. It is a knowledge-driven DSS, which offers herbicide dose suggestions based on a large database of the existing knowledge of herbicides and herbicide efficacies. The required weed control level in CPO-Weeds is based on expert evaluations, a herbicides dose-response model and an additive dose model to calculate possible mixtures of herbicides targeted a specific weed population. The herbicide dose model is a two parameter dose-response model, which is modified to include the effects of temperature, weed growth stage and influence of drought. The development has been driven by an ambition of offering a robust system with relatively low amounts of input variables and limited need for experimental parameter generation. CPO-Weeds offers overview and guidance for field specific spraying solutions, and the system has proved able to recommend herbicide doses with considerable reductions compared to label rates. Furthermore, CPO-Weeds offers a variety of tools that summarises knowledge of herbicides for a wide range of questions asked by practical weed managers, e.g. efficacy profiles of each herbicide, efficacy of users own herbicide mixtures, weed identification key and guidance for spraying strategy. The experiences have shown that even though CPO-Weeds are considered robust and trustworthy by both farmers and advisors there is a relatively low number of farmers subscribing to the system. A survey revealed that the DSS falls in between the strategies of many farmers; either the farmers relies completely on own experiences or advisory services or they considers the full crop rotation in their weed management. The latter is not supported by CPO-Weeds, which focus on a single season. The long term consequences of herbicide recommendations is only included in the need to limit input to soil seed bank. Another limiting factor for an increased practical use of CPO-Weeds is the need for field monitoring of weed populations, which can be a time consuming task and requires extensive weed recognising abilities of the farmer at the very early growth stages of weeds. The intention of CPO-Weeds was to provide recommendations for the full spraying season of a field, but experiences have shown that the system has several uses. Many farmers spray with a standard solution in the autumn in winter crops and then use the DSS for spring sprayings. The relatively simple input requirements also make the DSS suitable for teaching purposes and for farmers starting to grow new crops in their rotation as a learning tool.