Influence of Spatial Processes on the Population Dynamics of Insect Pests in Minnesota 

Principal Investigator: Ian Macrae

Project Description: 

Most insects pests are not uniformly distributed within fields, but application of pesticides are typically applied in a uniform manner across fields. This discontinuity results in application of crop inputs to areas where they are not needed. Unnecessary inputs increase production costs and adversely affect the environmental and economic sustainability of production. Precision agriculture is the use of site-specific knowledge to target crop inputs (pesticides, fertilizer, etc.) to specific areas of need. This more effectively utilizes inputs, reduces costs, and decreases environmental impacts and exposure risk to producers and consumers. The basis of Precision Agriculture is applying agrochemicals only where necessary. The goal of Integrated Pest Management is to apply pesticide only when it is necessary. By combining Precision Agriculture and IPM, we can implement "site-specific IPM", only applying pesticides where and when it is necessary. For this to work, it is necessary to have detailed information on the spatial and temporal distribution of insect pests within fields. Unfortunately, it is very time consuming to develop detailed maps of insect populations using standard scouting techniques. The effort required to develop such maps is onerous and not economically sustainable and the resulting map when compiled may well be too late to guide targeted application of inputs. Remote sensing may provide a solution to this problem. Remote sensing is the collection of information about an object from a distance and has long been used to assess plant health. Both insects and disease cause responses that affect a plant's spectral reflectance (the ratio of reflected radiation to the amount of incident radiation from the sun). The affected wavelengths can be measured using a variety of instruments, thereby facilitating the evaluation of plant stress. Spectral reflectance can be measured with both multispectral or hyperspectral sensors. Multispectral sensors measure reflectance at a few selected bandwidths or a broad grouping of light wavelengths (most cameras used in remote sensing tend to be multi-spectral). Hyperspectral sensors, conversely, measure a continuous range of very narrow bands or even individual wavelengths. While hyperspectral cameras are available, they are expensive and unlikely to be used by individual producers. Hyperspectral ground-based instruments, however, are both more affordable and available. Recent advancements in the technology, affordability and size efficiency of visible, ultraviolet and near-infrared (NIR) sensors have increased the potential of using remote sensing to economically and accurately assess insect populations. When combined with the rapidly developing abilities and functionality of small unmanned aerial systems (UAS), there are now very feasible systems to rapidly and accurately define the distributions of insect and disease pests in agricultural fields in near real time. This project will assess remote sensing as a technique for scouting insect populations. Objectives will include investigating and comparing methods of remotely scouting for soybean aphid (a photosynthate feeder) in soybean, Colorado potato beetle (a defoliator) in potato, wild rice worm (a direct feeder on grain) in wild rice, and sugarbeet root maggot (a root feeder) in sugarbeet. These 4 insects are indicative of the 4 major methods whereby insects damage plant hosts and cause yield loss. We will use hyperspectral spectroradiometers and a variety of multispectral imaging systems in a variety of field trials using both ground and aerially obtained data. Sensors will be flown using a variety of multi-rotor small UAS.

​​​​​​Project Years: 2016-2021

Funding Source: State Agricultural Experiment Station