Infestation of new and established insect pests in soybean is an on-going concern for farmers in Kansas. Easy and cost effective decision-making tools are needed to help farmers with pest management strategies. In order to accomplish this, we propose a project that has 3 components, all designed to better increase our knowledge of insect pests in KS soybean fields, provide tools for famers to better manage pests, and increase access to new knowledge. It is imperative that sampling and education of various stakeholders (farmers, agents, industry, etc.) continue so that we can have an effective communication strategy in place to respond to infestations in a timely manner.

Our first objective is to continue monitoring of soybean fields within KS to assess the distribution of insect pests and the intensity of pest pressure on soybean production. Scouting for insect pests is particularly important for new pests such as soybean gall midge, that has been found in neighboring states, including NE, MO, and IA. We will using sweep net sampling and traps that target persistent pests, including Dectes stem borer, soybean podworms, stink bugs, Japanese beetles, and new pests such as soybean gall midge. We will also test the efficacy of various sampling methods such as lures to better estimate insect densities in the field.

Using new and existing pest distribution data, our second objective is to develop a tool using landscape models to predict soybean fields with the highest likelihood of pest infestation based on landscape-level features and past management strategies. We will focus on 3 perennial and occasional pests (Dectes stem borer, stink bugs, Japanese beetles, and soybean podworm). This spatial modeling tool with help farmers assess whether their fields have greater likelihood of infestation by pests and therefore help them prepare for earlier scouting and preventative management strategies.

Finally, in order to reach out to famers, our last objective is to continue communicating with farmers through test-based maps, tables, and discussions. We will update the KSRE Soybean Insect Management Guide (https://bookstore.ksre.ksu.edu/pubs/MF743.pdf) and data within the web-based decision management tool myFields (www.myfields.info). We will continue reaching out to the general public and farmers through distributing newsletters and in-person and virtual discussions at field days, radio programs, and social media.

Objective 1. Document the distribution of established and/or new pests in Kansas and adapt existing monitoring technologies to manage Dectes stem borer, soybean podworms, stink bugs, Japanese beetles, and new pests such as soybean gall midge. Because we would like to expand our surveillance efforts, this field-based objective will be the most time-consuming and require most of the resources.

Objective 2. Create tools using landscape models to predict pest densities and damage to soybean plants using existing and new pest distribution data. Using data from Objective 1 and working with collaborators in other states, this modeling objective is computer based and utilizes map-making software in ArcGIS pro and EDDMaps, and plugged into MyFields for KS farmers to use.

Objective 3: Expand web pages and other educational materials associated with soybean insects. Using information from Objectives 1 and 2, we will continue to reach out to farmers and the general public using text-based discussions, maps, tables, and graphs posted to the KSRE Soybean Insect Management Guide and our soybean pest management web-based decision tool in myFields.info. We will continue discussions during field days, radio programs, newsletters, and via other educational opportunities as appropriate and the support of the Kansas Soybean Commission will continue to be highlighted in all of these endeavors.

For Objective 1, project deliverables including collecting pest density data on the distribution of insect pests in soybean across central and eastern KS. We will continue to samples fields from past years to assess long-term population trends but we will expand our surveillance to include new fields and areas, particularly for soybean gall midge. These data will be used to inform spatial distribution models (see Objective 2 below) and understand how changes in climate might affect insect distribution.

For Objective 2, we will use new and existing data from Objective 1 to develop a tool based on landscape models to assess the likelihood of pest infestation. This tool will be freely available for soybean farmers and available on myFields, a web-based extension management tool.

For Objective 3, we will continue to update and add new information and update newsletters, KSRE Soybean Insect Management Guide, myFields, an extension-based management tool (https://www.myfields.info/).

Update:
The proposed project will build off the work previously funded by KSC support. To date, for Obj. 1, we have extensively sampled counties across much of northeast Kansas for the presence of soybean gall midge. Sixty sites were sampled in 2022 and no records have been found so far. However, this new pest continues to expand its range across southern Nebraska and southwestern Iowa (15 new counties were added in 2022). It is imperative that sampling continue and education of various stakeholders (farmers, agents, industry, etc.) continue so that we can have an effective communication strategy in place to respond to infestations in a timely manner; see website for upcoming webinars (https://soybeangallmidge.org/). Consequently, the new alert and notification module within myFields.info (Obj. 3) allows us to send alerts to specific counties and users can sign up for a free account to receive notifications via email.

For Obj. 1, we also tested the efficacy of new pest monitoring strategies and management practices. For improved monitoring strategies, we tested the efficacy of various stink bug pheromones across 6 fields in central Kansas. Our samples were processed in early fall and data are currently being analyzed. Preliminary results show that the lures are effective in attracting several species of economically important stink bugs to the traps. More information will be provided as sticky cards and sweep samples are processed and analyzed this winter. For improved management, we conducted an insecticide efficacy trial this year examining the effectiveness of two new insecticides in comparison to five older general use synthetic organic products. These two new insecticides are more specific to pests (mostly lepidopterans) and less harmful to non-target organisms such as beneficials. We are in the process of analyzing the data and will share pertinent information to Kansas stakeholders through as many venues as possible (Obj. 3).

Furthermore, we have hired a PhD student and several undergraduates in Aug 2022 to lead and carry out Objectives 1 and 2. The PhD student coordinates with undergraduates on field sampling efforts and manages the progress of insect identification of collected samples. They are currently using existing data collected in soybean either from prior years, publicly available data, and data from neighboring states, to understand how landscape features of the environment impact the densities of occasional pests within KS landscapes. They are currently focusing on Japanese beetles since this invasive species is expanding in their ranges and becoming more persistent in soybean fields. They plan to expand modeling efforts to other important pest insects (e.g., Dectes, soybean podworm, and stinkbugs) and will incorporate to results to myFields (Obj. 3).

Update:
The proposed project will build off the work previously funded by KSC support. To date, for Obj. 1, we have extensively sampled counties across much of northeast Kansas for the presence of soybean gall midge (SGM). Sixty sites were sampled in 2022 and no records have been found then. However, recently SGM was found in two counties (Nemaha and Marshall). This new pest continues to expand its range across southern Nebraska and southwestern Iowa (15 new counties were added in 2022). It is imperative that sampling continue and education of various stakeholders (farmers, agents, industry, etc.) continue so that we can have an effective communication strategy in place to respond to infestations in a timely manner; see website for upcoming webinars (https://soybeangallmidge.org/). Consequently, the new alert and notification on module within myFields.info (Obj. 3) allows us to send alerts to specific counties and users can sign up for a free account to receive notifications via email. For Obj. 1, we also tested the efficacy of new pest monitoring strategies and management practices. For improved monitoring strategies, we tested the efficacy of various stink bug pheromones across 6 fields in central Kansas. Preliminary results show that the lures are effective in attracting several species of economically important stink bugs to the traps. More information will be provided as sticky cards and sweep samples were processed this past winter and are currently being analyzed. For improved management, we started an insecticide efficacy trial this summer examining the effectiveness of two new insecticides in comparison to five older general use synthetic organic products. These two new insecticides are more specific to pests (mostly lepidopterans) and less harmful to non-target organisms such as beneficials. We are in the process of collecting data and we will share results and pertinent information to Kansas stakeholders through as many venues as possible (Obj. 3). Furthermore, the PhD student currently funded on this grant and several undergraduates are carrying out Objectives 1 and 2. The PhD student and undergraduate are currently sampling 60 fields across eastern KS. They will use collected data along with previously data collected in soybean either from prior years, publicly available data, and data from neighboring states, to understand how landscape features of the environment impact the densities of occasional pests within KS landscapes. They are currently focusing on Japanese beetles since this invasive species is expanding in their ranges and becoming more persistent in soybean fields. They plan to expand modelling eff orts to other important pest insects (e.g., Dectes, soybean podworm, and stinkbugs) and will incorporate to results to myFields (Obj. 3).

We currently received a 3-month no-cost extension. Results from this summer will be posted on the final report.

Understanding the distribution of insects is critical for management and developing tools to predict and prevent future pest infestation and damage. Continued monitoring is essential to understand where insects occur, particularly for new pests such as the soybean gall midge. Using these data, we can create a model based on landscape features, management practices, and history to predict where pest infestation is likely to occur. This model can be used as a management tool by soybean farmers and crop consultants for determining pest treatment and increased scouting efforts. This model will allow farmers to prepare for the correct action to be taken to prevent or minimize infestation levels and yield loss.