Progress 03/01/23 to 02/29/24
Outputs
Target Audience:The primary audiencesare public stakeholders, specifically growers, that require data to make on-farm decisions. The goal of the project is to develop a web-based platform that can connect them with researchers that investigate agronomic practices and technology that improves crop production. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?Three graduate students on the project have been trained on various aspects including soil sensor types, installation, python scripting for digital agriculture, hydrologic modeling, remote sensing processing and Microsoft vibes project development. In addition, over the past year, three visiting scholars have helped maintain the sensors (cleaning and calibration) at the Piatt County Illinois on-farm site. The scholars were two graduates of Zamorano University in Honduras. The third was a current Zamorano students fulfilling her Professional Practice Program requirement. This assistance is a valuable learning experience as remote, real-time sensing and communication is becoming more prevalent in environmental research. How have the results been disseminated to communities of interest?The DIRECT4AG platform and the 4 water quality stations were briefly discussed during the Illinois Fertilizer and Chemical Association 4R Field Day held September 7, 2023 at the Piatt County farm. The main topic of the event was various demonstrations of how cover crops can be seeded. Lowell Gentry gave a presentation on all of the research that has been conducted at the farm to date including the installation of the 4 stations. Field Day: Using Cover Crops to Reduce Tile Nitrate Loss Also, see dissemination activities conducted as part of Objective 4. What do you plan to do during the next reporting period to accomplish the goals? Finish parsing all drought-resistant field soil moisture data and make it available through Geostreams and the DIRECT4AG web applications. Create Geostreams parser for Tuskegee research site soil moisture sensor data stored in Zentra cloud system and ingest data into DIRECT4AG platform. Add gridMET weather data for research fields. Continue to build out the platform for storing and exploring field data provided by the research team that will demonstrate the capabilities of DIRECT4AG for communicating research on crop improvement and technology to both researchers and producers. This includes continuing to implement the initial prototype for visualizing drought-resistant seed trials research and nutrient management research through the DIRECT4AG website and gathering feedback that can be incorporated into the website Continue to develop the web service API for serving research data through the DIRECT4AG website Maintain any deployed software with the latest security fixes and keep dependencies up to date. Collect a third year of multi-location trial data for the conventional and drought tolerant lines of hybrid corn. Collect remote sensing data and process for agriculturally based biophysical products including soil moisture, soil temperature, plant moisture stress, evapotranspiration, crop health and green biomass. The data will be analyzed together with field sensor measurements. Revisit all Tuskegee sensor unit in the field and remove/move sensors into different or critical locations. Tuskegee University will provide precision and digital agriculture training in conjunction with TUCEP county agents, to small-scale and socially disadvantaged farmers within the Alabama Black Belt Counties. Increase stakeholder interaction with the DIRECT4AG platform and researchers.
Impacts
What was accomplished under these goals?
Advances in technology are driving innovations in agriculture but also creating uncertainty for growers about which technologies they should adopt. There is also a need to supply large-scale and small-scale farms with relevant information for data driven decisions. In the second year of the project, we completed a second year of data collection for DIRECT4AG field trials and increased the amount of sensor data collected for input into the platform. Feedback from stakeholders was used to guide development of the website prototype and visualizations for decision support tools. Objective 1: Develop and implement the DIRECT4AG digital platform to enhance communication and data sharing with producers. · Used feedback from a Farmer Focus group on the cover crop analyzer tool to inform the design of the Nutrient management research area of the DIRECT4AG site. · Worked through a Strength, Weakness, Opportunities, and Threats (SWOT) analysis with the project team so the data can be used to inform DIRECT4AG website design and areas that should be focused on now versus later in future development of the platform. · Created Figma design for drought-resistant seed visualization to help users gain knowledge from past and future trials. · Created Figma design for cover crop visualization for learning about cover cropping and applying it. · Created python parsers by using Geostreams python library for parsing hydromet sensor data and setup a daily job to fetch and parse nitrate and water level data for the Miller farm so it can be served through the Geostreams Data Framework. · Created a python script to post-process soil moisture sensor data provided by the research team and parsed the soil moisture data for the drought-resistant seed trials for one field site so it can be served through the Geostreams Data Framework. This parser can be used for other field sites with the same data format. · Designed web service RESTful Application Programming Interface (API) and started implementation of the API for storing and retrieving farm research information based on the design for each research area including associating sensor data, yield data, etc with each field for exploration through the web application. · Started implementation of the DIRECT4AG web application landing page based on the Figma design and the visualizations to support exploring the different research areas and the data being collected by the research team. · Provided farm of the future cover crop DSSAT model results to the team to investigate ground truth data versus model outputs and provide data for calibrating the DSSAT crop model and Cover Crop Analyzer tool. Objective 2: Assess marketed water-use efficient hybrid maize lines and provide producers data through the DIRECT4AG platform. The comparison between two Pioneer Hi-Bred lines of corn (1197 and 1151-AquaMax) were again grown at Variety Testing sites across Illinois to evaluate the growing environments that benefit from drought tolerance materials. Due to some problems with on-farm trial locations (premature harvest, incorrect fertilizer application, extreme weather) and decreased sites offered through University of Illinois Variety Testing, we have only have two years of data for five sites. However, with this data, patterns are emerging as to locations that consistently benefit from drought tolerant materials. Soil moisture sensor data was again collected from a subset of locations and is being used both within the DIRECT4AG project and for outside projects. In addition to the soil moisture sensors deployed in Illinois in corn yield trials, twenty-four S TEROS 12 VWC & Temp & EC sensors and six ZL6 Cellular Data Loggers, with ZENTRA Cloud Standard subscription Plan from METER GROUP, Inc. were installed in five specialty crop farmers' fields in Dallas, Perry and Macon counties of the Alabama Black Belt Regions. An additional six sensor array was installed at the Tuskegee University Organic farm in the summer of 2023. Soil samples were also collected from participating farmer fields in Perry, Macon and Dallas counties to provide additional field level insights to crop water management. The soil moisture and composition data are being shared with the farmers as we work with them to see how additional data can inform decisions about crop management. We also have processed Landsat 8 and 9 data for agriculturally based biophysical products including soil moisture soil moisture products/indices and assessed their correlation with the field sensor readings. Research is ongoing to utilize the sensor readings to produce spatial based soil moisture data for the research counties. Although it is important to collect data across different growing environments (fields), it is also vital to understand soil moisture variability at subfield level. However, systematic investigation of subfield scale soil moisture variability over cropland is still lacking from both measurement and satellite remote sensing. We conducted soil moisture field experiments in three typical commercial agricultural fields (∼85 acres per field) in central Illinois, representing typical commercial farmlands in the US Midwest, and compared the soil moisture measurements with satellite remote sensing data from optical and active microwave sensors. We found prominent time-invariant spatial structures of soil moisture at within-field scales both during the dry down period and over longer time scales, and the stability is minimally affected by plant water use during the growing season. Comparing the field campaign measurements with satellite remote sensing data, we found that surface reflectance of shortwave infrared bands, such as SWIR1 (1610 nm) from Sentinel-2, can capture relative surface soil moisture patterns at within-field scales, but their relationships with soil moisture are field specific. These findings and the improved understanding of within-field soil moisture dynamics could potentially help future research on high-resolution soil moisture estimation with multi-source remote sensing data. Objective 3: Evaluate and disseminate maize production management strategies for environmental and economic sustainability using the DIRECT4AG platform. The four water quality stations installed at an on-farm trial location in Piatt County, Illinois collected data for an entire season. With more data we were able to robustly assess the correlation between grab samples and ecoN sensor nitrate concentrations, which remains very good. Data importation from the water quality stations to the DIRECT4AG platform has begun and prior years data (prior to the water quality stations with real-time nitrate concentrations) will be added so that users have access to more information about the cropping systems over a longer period than the one and one-half years we have currently. In the next year we will build out the data visualizations on the DIRECT4AG platform. Objective 4: Deliver Extension education to large-scale and small-scale producers on data access and uses through the DIRECT4AG platform. Tuskegee University investigators had zoom meetings with several limited resources, small scale specialty crop farmers from multiple Alabama Black Belt Counties. The meetings were on precision and digital agriculture, climate smart agriculture and the use of field sensors to collect data on soil and water dynamics to help in making informed decisions for optimizing agricultural management. The University of Illinois team hosted a farmer focus group to introduced new users to the Cover Crop Analyzer tool. Growers that currently use cover crops on their farms were targeted to provide feedback on the Cover Crop Analyzer decision support tool and inform data visualizations.
Publications
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Progress 03/01/22 to 02/28/23
Outputs
Target Audience:The primary audiencesare public stakeholders, specifically growers, that require data to make on-farm decisions. The goal of the project is to develop a web-based platform that can connect them with researchers that investigate agronomic practices and technology that improves crop production. Changes/Problems: As with many projects, project initiation was slow and recruiting graduate students for the project was delayed. These issues are not expected to continue in year 2. Sensor price increases has limited the number of locations where sensors can be installed and some sites have only the capacity for manual data downloads rather than cloud connectivity. We are exploring options to maximize sensor distribution and near real-time data streaming to the cloud across all sites. Some initial software development staff left the project leaving a gap in the software development that was recently restarted on January 1, 2023 with a new software developer and bringing on a UI/UX person to help with requirements gathering and some planned focus groups and SWOT analysis. Co-PIGentry retired from the University of Illinois during year one of the project. However, we were able to add Co-PI Yu to the project to take over deliverables from Co-PI Gentry. What opportunities for training and professional development has the project provided?Three graduate students funded by the project have received various training including soil sensor types, installation, python scripting for digital agriculture, hydrologic modeling, remote sensing processing, and Microsoft vibes project development. How have the results been disseminated to communities of interest?Tuskegee University investigators conducted a virtual meeting with several limited resources, small scale specialty crop farmers from several Alabama Black Belt Counties in February 2023. The meeting was focused on precision and digital agriculture, and the use of field sensors to collect data on soil and water dynamics to help in making informed decisions for optimizing agricultural management. Several farmers expressed interest in having soil sensors installed in the fields to assist them better improve irrigation and nutrient management. The project has been introduced to stakeholders at several Illinois Extension events, including a presentation on Objective 2 by PD Studer at a Certified Crop Advisor Conference with over a hundred participants. A farmer focus group is planned for the cover crop analyzer tool, but will happen in the beginning of the next reporting period, which will introduce producers to the cover crop analyzer tool https://covercrop.ncsa.illinois.edu. What do you plan to do during the next reporting period to accomplish the goals? An internal strengths, weaknesses, opportunities, and threats (SWOT) analysis is planned to help drive the project requirements and determine what can be done for the pilot. Continue working with the UI/UX and project team to use information from the planned focus group and SWOT analysis to drive the platform design for the demonstration pilot and visualizations we can create from their research data and create Figma or similar designs to guide development. Continue to build out the platform for storing sensor data, aerial images and other data and start building parts of the platform identified by the research team that will demonstrate the capabilities of Direct4Ag for communicating research on crop improvement and technology to both researchers and producers. Maintain any deployed software with the latest security fixes and keep dependencies up to date. Provide more agricultural datasets through the DIRECT4AG digital platforms according to the producers' needs. Collect a second year of multi-location trial data for the conventional and drought tolerant lines of hybrid corn. Collect weekly sampling of a cereal rye cover crop field to parameterize the Cover Crop Tool. Install and collect soil sensor data in participating farmer fields in Perry, Macon and Dallas counties in Alabama. Train farmers on the interpretation of soil sensor data and for precision agriculture/use of the sensor output. Collect remote sensing data and process for agriculturally based biophysical products including soil moisture, soil temperature, plant moisture stress, evapotranspiration, crop health and green biomass. The data will be analyzed together with field sensor measurements. Tuskegee University will also provide precision and digital agriculture training in conjunction with TUCEP county agents, to small-scale and socially disadvantaged farmers within the Alabama Black Belt Counties. Training will cover principles of crop water use efficiency, soil fertility and nutrient management, water resources and irrigation. Farmer focus groups are planned to continue requirements gathering for the platform and understand the needs of producers and how research being conducted can be disseminated through the platform. Increase stakeholder interaction with the DIRECT4AG platform and researchers.
Impacts
What was accomplished under these goals?
Advances in technology are driving innovations in agriculture but also creating uncertainty for growers about which technologies they should adopt. There is also a need to supply large-scale and small-scale farms with relevant information for data driven decisions. In the first year of the project, we brought together an extremely diverse team of scientists who are committed to rapidly delivering data to growers to help them make on farm decisions. Data collected from on-farm and on-campus trials were used to drive the development of decision support tools for growers and test data for the design of the DIRECT4AG platform. Objective 1: Develop and implement the DIRECT4AG digital platform to enhance communication and data sharing with producers. The goal of this objective is to design and build a functional platform that will enable interdisciplinary research and rapidly disseminating data and results to stakeholders. Started requirements gathering from the research team to identify technology needs of the DIRECT4AG platform to support all project objectives. Investigated technologies to provide the infrastructure for data collected by the team such as sensor data, aerial images and other research data. For data management and visualization, setup NCSA Clowder and NCSA Geostreams on NCSA Radiant cloud computing and tested with sample data provided by the team. Setup geoserver on NCSA Radiant cloud computing for visualizing Geospatial data. Documented Geostreams setup process. Setup landing page using Geodashboard for initial visualization of sensor data while investigating long term plan based on requirements gathering. Investigated technologies such as React/Typescript for the frontend, mapping libraries such as OpenLayers and MapLibre, and Python FastAPI for the web service. Setup Github repository for source code management, project management including issue tracking, source control, and continuous integration at https://github.com/direct4ag Setup/configured Github source code repositories for building the Frontend, Web service, and data parsers for the sensors. Dockerized the initial frontend application and web service for easy deployment. Setup an on-campus field site using the Cover Crop Tool (https://covercrop.ncsa.illinois.edu) and created a script to run the DSSAT model daily. Using the latitude/longitude of both the on-campus and on-farm field trials sites, added daily gridMET weather downloads for these sites and made the data available in the Cover Crop Tool. Created python parsers by using Geostreams python library for soil moisture sensor and nitrate sensor sample data provided by the team and visualized with the Geodashboard. Objective 2: Assess marketed water-use efficient hybrid maize lines and provide producers data through the DIRECT4AG platform. The goal of this objective is to collect data on a multi-location field trial of drought-tolerant and conventional commercial maize lines and use the DIRECT4AG platform to disseminate the agronomic performance along with sensor data that will add context for interpretation. Overall, this example will allow us to optimize the delivery of data through the DIRECT4AG platform and test a system for providing growers with information that they can use to make decisions about technology adoption. Based on grower feedback, a comparison of two Pioneer Hi-Bred lines of corn (1197 and 1151-AquaMax) were selected to test the need for drought tolerance material in Illinois. In collaboration with Variety Testing at the University of Illinois, these two lines were grown at 12 locations around the state in a replicated trial. Soil moisture sensors were included at three of the locations and an additional site was added on-campus that had irrigation. Although dry June conditions contributed to water deficits at some locations, end-of-season yield data showed that the drought-tolerant line (1151) did not confer a performance advantage over the conventional line (1197). However, this single year of data needs replicated before conclusions can be drawn about the weather and soil properties that buffer Illinois growers from the effects of variable rainfall. Objective 3: Evaluate and disseminate maize production management strategies for environmental and economic sustainability using the DIRECT4AG platform. The goal of this objective is to use suites of sensors and modeling approaches to provide growers with data and examples of the impacts management practices have on productivity and sustainability. In the project period, we have worked on collecting, integrating, and disseminating data such as cover crop aboveground biomass through the DIRECT4AG digital platform. These data were generated by using satellite remote sensing data with field measurements to develop process-guided machine learning models. These data can bring benefits for both large-scale and small-scale producers for timely cover crop management, such as termination, to achieve the co-benefits of maximizing main crop yield and environmental sustainability. Researchers collecting the data are working with programmers and platform developers to optimize data visualizations for stakeholders. In addition, efforts that require fields with cover crops are being coordinated between DIRECT4AG and other relevant USDA-funded projects on campus. Four water quality stations were installed at the on-farm trial location in Piatt County, Illinois. Four tile systems were intercepted leaving the fields with Agri Drain structures equipped with V-notch weirs. The four tiles monitored are each from fields with different management systems including two systems with cover crops. Each station is equipped with an OTT Hydromet ecoN UV nitrate sensor and an OTT PLS (pressure level sensor). The readings are transmitted via cellular communication from a Sutron XLink 100 datalogger once an hour and the data are currently accessible from the Hydromet Cloud. Nitrate losses will be calculated by multiplying the nitrate concentration with the calculated flows. Grab samples are taken weekly from each of the monitored tiles and analyzed for nitrate concentration on a Dionex ICS-1600 ion chromatograph. When compared with the ecoN readings, we have had a very good correlation (R2 = 0.99, n=25). Now that we have established these sensors, we are working to have the data imported for visualization and analysis through the DIRECT4AG platform. These tile readings will provide near real-time comparisons of crop rotation and the effect on nitrogen loss through the tile in on-farm production fields. These data will also allow us to quantify the costs and benefits of rotation practices. Objective 4: Deliver Extension education to large-scale and small-scale producers on data access and uses through the DIRECT4AG platform. The goal of this objective is to establish a feedback loop with stakeholders so that we can collect grower comments on information displayed through the DIRECT4AG platform. These comments can be used to improve the platform and guide the research. Specialty crop farmers have been identified and selected in Dallas, Perry and Macon counties in Alabama where soil moisture sensors will be installed in the fields. These sensors will also be installed in Tuskegee University Organic farm and Greenhouse during the 2023 summer. Additionally, in collaboration with Microsoft, Tuskegee University is developing a Microsoft Vibes farm of the future project. The Microsoft Vibes projects allows the assimilation of different sentinel and other satellite data biophysical modeling product to help in developing data and information-based precision agriculture. Much of it the work in year 1 has been in the design and development stage with less to communicate or disseminate to target audiences. This stage of development does not offer much for professional development or training efforts, but will be an integral component in the coming years.
Publications
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