Research and Projects

The Flickner Innovation Farm relies on external partners who bring their experience and expertise to each growing season. Some strategies have been wildly successful, while others haven't been a good fit for the Flickner Farm. It is always our goal to share what we have learned with our community, and we host regular meetings and field days.

The Flickner Innovation Farm team at AGU 2025

Field Days at the Farm

Hosted on-site at the Flickner Innovation Farm in Moundridge, these events are open to the public. Field days often feature faculty from Kansas State University, industry leaders, community representatives, and members of the Flickner family. When possible, field days include live demonstrations of technologies in use at the farm, and participants are invited to get up close and see everything working for themselves. Many of our partners provide displays and are happy to answer questions about their products or services. Let us know if you are interested in receiving information about our next field day.

Current Projects

Paired Watersheds & Biologicals Research
This long-term study at Flickner Innovation Farm examines how water, nutrients, and management decisions interact under real-world conditions. Using a paired watershed design with automated runoff monitoring, researchers are building baseline water quality data before testing management changes. The project also evaluates biological and biostimulant products—many widely marketed but rarely validated—to determine their impact on yield and nutrient efficiency. By combining multi-year monitoring with replicated trials, this research provides credible, field-scale evidence to guide farmers, agencies, and policymakers in protecting water resources while maintaining profitable crop production.

Evaluating Targeted Herbicide Applications at Field Scale
This research tests “See & Spray” targeted herbicide technology in commercial soybean fields to determine if it reduces inputs without sacrificing performance. Kansas State University researchers compared broadcast spraying, single-tank targeted spraying, and a dual-tank approach across two locations. First-year results show targeted spraying treated only 30–50% of the field while maintaining over 90% weed control, reducing crop injury, and preserving yield. These findings confirm small-plot research and highlight the potential for targeted spraying to lower herbicide use. Future work will expand economic analysis to assess return on investment for producers and retailers.

Long-Term Soil Health Outcomes in Kansas Cropping Systems
This project evaluates how cover crops influence soil health in Kansas no-till cropping systems. Research takes place on producer-managed farms across diverse soils and climates. Findings from multi-year data show that cover crops improve soil health over time without reducing yields, with noticeable benefits emerging after five years. These results help producers and advisors set realistic expectations for soil health improvements and inform carbon measurement and verification efforts.

Precision Water Management Research
This project ievaluates advanced irrigation technologies. Researchers compare autonomous center pivot systems equipped with radar-based sensors to subsurface drip irrigation, measuring crop water stress, evapotranspiration, and water use efficiency. Using satellite imagery, drone data, and ground-based measurements, the team develops spatial evapotranspiration maps and scalable water management tools. Findings show dynamic, moving systems can better detect variability and reduce crop stress during critical growth stages. The goal is to validate practical technologies and open-access tools like OpenET to support producers facing declining groundwater supplies.

Whole-Season Drone and Satellite Data for Crop Monitoring and Yield Prediction
This project combines high-resolution drone imagery with satellite, radar (SAR), LiDAR, soil tests, and yield monitor data to track crop performance across more than 2,000 acres from snowmelt through harvest. Researchers assess weather impacts while improving yield prediction by integrating canopy-level and soil-level data. Preliminary results show that adding radar and optical satellite data significantly enhances prediction accuracy compared to terrain data alone. This work supports Extension education and on-farm decision-making by demonstrating how remote sensing can reduce manual scouting, improve damage assessment, and guide management strategies for Kansas producers.

Winter Meetings

The freezing temperatures don't bother us - especially when we have the chance to get together for one of our winter meetings. These gatherings are open to the public, and these are the times when our researchers share data and other results from their on-farm projects. The next winter meeting will take place in Inman, Kansas on January 27, 2026.

a group of people are seated in a large room, listening to a presentation

January 2020

Topics included a farm overview, soil moisture probe placement study, water use efficiency, and nutrient studies.

January 2023

The agenda included a long term irrigation study, mapping soybean protein in-field, using NASA imagery, and groundwater nitrate dynamics.

Research Publications

Changes in soybean seed composition

In past decades, breeding increased soybean yield potential. This KSRE publication explains that, unfortunately, yield improvement has been linked to a reduction of seed protein concentration. Because amino acids are the building blocks of protein, this study's experiments were designed to evaluate how amino acids decreased over time, and if a high-nitrogen environment could alter protein or amino acid changes with yield improvement.

Soybean management for seed composition: the perspective of U.S. farmers

In this study, published in Agronomy Journal, evaluated farmers' perspectives and knowledge on soybean quality and their propensity to adopt quality improvement technologies.

Current status and future opportunities for grain protein prediction using on- and off-combine sensors

In this study, published in Remote Sensing, researchers discussed sensor choice in regard to previously identified uses of a GPC (crop grain protein concentration) layer in GIS mapping systems, and further proposed new uses with remote sensors including same season fertilizer management for increased GPC, and in advance segregated harvest planning related to field prioritization and farm infrastructure.

Interactive soybean variable-rate seeding simulator for farmers

This article in Agronomy Journal introduces the soybean variable-rate seeding (VRS) simulator, an interactive web-tool designed to facilitate VRS decisions. The simulator generates variable rate seeding recommendations by aggregating and classifying historical soybean yield maps using either yield level (low, medium, or high) or temporal yield stability (stable or unstable) classes, and estimating the difference between the farmers current uniform seeding rate and the optimal seeding rates calibrated for different yield environments of the U.S. Midwest region.

Historical trend on seed amino acid concentration does not follow protein changes in soybeans

The aim of this research, published in Scientific Reports, was to determine the genetic shifts of seed composition for 18 amino acids in 13 soybean genotypes released between 1980 and 2014. Additionally, the effect of nitrogen (N) fertilization on protein and amino acids trends were tested.

Winter wheat light interception measured with a quantum sensor and images

This study was published in the Agronomy Journal and used a linear quantom sensor and a camera to collect on-farm observations. These were used to evaluate the use of the fration of green canopy cover as a surrogate for LI in wither wheat canopies.

Calibration and validation of soil water reflectometers

Published in the Vadose Zone Journal, this study tested soil water reflectometers to quantify the sensing volume of specific sensors, evaluate common univariate and multivariate calibration modeals, and assess the implications of using uncalibrated sensors.

Predicting rootzone soil moisture from surface observations in cropland using an exponential filter

Published in the Soil Science Society of America Journal, this study tested the skill of an exponential filter to estimate rootzone soil moisture conditions from a time series of near-surface soil moisture observations.

A soil moisture-based framework for guiding the number and location of soil moisture sensors in agricultural fields

This article, published in the Vadose Zone Journal, evaluates a quantitative framework based on soil moisture-based management zones (MZs) to determine the minimum number and tentative deployment location of soil moisture sensors (SMS).

Evaluation of soil parameters after long-term subsurface drip irrigation under minimum tillage system

This research study, published as a Kansas Agricultural Station Research Report, evaluates soil perameters after the long-term use of sub-surface drip irrigation under no-till, with the use of high pH irrigation water.

On-farm assessment of AquaSpy soil moisture sensors for irrigation scheduling

This Kansas Agruciltural Experiment Station Research Report aimed to compare a commercially-available radio-frequency spectroscopy soil moisture sensor with an array of calibrated research-grade soil water reflectometers in a no-till irrigated corn field.