Defining Integrated Weed Management: A Novel Conceptual Framework for Models

Weed population dynamics models are an important tool for predicting the outcome of alternative Integrated Weed Management (IWM) scenarios. The growing problem of herbicide resistance has increased the urgency for these tools in the design of sustainable IWM solutions. We developed a conceptual framework for defining IWM as a standardised input template to allow output from different models to be compared and to design IWM scenarios. The framework could also be used as a quantitative metric to determine whether more diverse systems are more sustainable and less vulnerable to herbicide resistance using empirical data. Using the logic of object-oriented programming, we defined four classes of weed management options based on the stage in the weed life cycle that they impact and processes that mediate their effects. Objects in the same class share a common set of properties that determine their behaviour in weed population dynamics models. Any weed control “event” in a system is associated with an object, meaning alternative management scenarios can be built by systematically adding events to a model either to compare existing systems or design novel approaches. Our framework is designed to be generic, allowing IWM systems from different cropping systems and countries to be compared.

Drone and sensor technology for sustainable weed management: a review

Weeds are amongst the most impacting abiotic factors in agriculture, causing important yield loss worldwide. Integrated Weed Management coupled with the use of Unmanned Aerial Vehicles (drones), allows for Site-Specific Weed Management, which is a highly efficient methodology as well as beneficial to the environment. The identification of weed patches in a cultivated field can be achieved by combining image acquisition by drones and further processing by machine learning techniques. Specific algorithms can be trained to manage weeds removal by Autonomous Weeding Robot systems via herbicide spray or mechanical procedures. However, scientific and technical understanding of the specific goals and available technology is necessary to rapidly advance in this field. In this review, we provide an overview of precision weed control with a focus on the potential and practical use of the most advanced sensors available in the market. Much effort is needed to fully understand weed population dynamics and their competition with crops so as to implement this approach in real agricultural contexts.

The R Package PROSPER: An Environment for Modeling Weed Population Dynamics and the Evolution of Herbicide Resistance

Weed management is a challenge for farmers worldwide, and the problem is exacerbated by the spread of weed herbicide resistance. Simulation models that combine population dynamics and genetics are valuable tools for predicting the impact of competing management options on weed density, allele frequency, and phenotypic resistance levels. The new R package PROSPER provides functions for the forward simulation of weed population dynamics on a field scale, the selection of individuals according to their sensitivity to herbicides, and the recombination of alleles during reproduction. Objects are provided to enter and save model parameters in a clear structure, and to save output data for further processing in R. The basic functions are extensible with R code. PROSPER combines individual-based population dynamics with monogenic or polygenic diploid inheritance and flexible selection pressure. Stochasticity can be included at all model steps. Two examples of the population dynamics of two annual weed species with herbicide resistance are presented. All parameters and the models are available in PROSPER. In addition to simulation, PROSPER is intended for sharing and publishing population dynamic parameters and models, which is easily done thanks to R.

CORRELATION BETWEEN SOWING AND FERTILIZER APPLICATION SYSTEMS AND WEEDS IN SOYBEAN CROPS

ABSTRACT The objective of this study was to evaluate the effects sowing systems and fertilizer application systems on the incidence of weeds and on yield components in soybean crops. Two experiments were conducted in soils with different fertility levels. An experimental design in split-plot was used; the plots consisted of four sowing systems: crossed sowing (0.45×0.45 m), and spacings between rows of 0.35 m, 0.175 m, and 0.45 m; and the subplots consisted of fertilizer application systems: application in the sowing row, broadcast fertilizer application at sowing, and no fertilizer application. The variables evaluated were: grain yield, 1000-grain weight, and weed incidence at 30 and 50 days after sowing (DAS). The weed incidence at 30 DAS was lower when using spacing between rows of 0.45 m, which was correlated with the lower turning of the soil surface layer. The plant spacing between rows of 0.175 m resulted in a lower competition with weeds at 50 DAS and in a higher shading, generating higher grain yields. The fertilizer application in the sowing row resulted in a higher grain yield and 1000-grain weight. The sowing system affects the weed population dynamics, which directly affects the grain yield of soybean crops.

Does seed mass drive interspecies variation in the effect of management practices on weed demography?

Optimizing the effect of management practices on weed population dynamics is challenging due to the difficulties in inferring demographic parameters in seed banks and their response to disturbance. Here, we used a long-term plant survey between 2006 and 2012 in 46 French vineyards and quantified the effects of management practices (tillage, mowing and herbicide) on colonization, germination and seed survival of 30 weed species in relation to their seed mass. To do so, we used a recent statistical approach to reliably estimate demographic parameters for plant populations with a seed bank using time series of presence–absence data, which we extended to account for interspecies variation in the effects of management practices on demographic parameters. Our main finding was that when the level of disturbance increased (i.e., in plots with a higher number of herbicide, tillage or mowing treatments), colonization and survival in large-seeded species increased faster than in small-seeded species. High disturbance through tillage increased survival in the seed bank of species with high seed mass. The application of herbicides, considered as an intermediate disturbance, increased germination, survival and colonization probabilities of species with high seed mass. Mowing, representing habitats more competitive for light, increased the survival of species with high seed mass. Overall, the strong relationships between the effects of management practices and seed mass provides an indicator for predicting the dynamics of weed communities under disturbance.