2017
Cropping systems modeling tools to improve soybean management and yield in Iowa
Contributor/Checkoff:
Category:
Sustainable Production
Keywords:
Field management Nutrient managementSoil healthTillageYield trials
Lead Principal Investigator:
Sotirios Archontoulis, Iowa State University
Co-Principal Investigators:
Michael Castellano, Iowa State University
Ranae Dietzel, Iowa State University
Mark Licht, Iowa State University
Andy VanLoocke, Iowa State University
+3 More
Project Code:
450-47-03
Contributing Organization (Checkoff):
Institution Funded:
Brief Project Summary:

Has soybean yield potential been reached or has it been limited by a confluence of factors such as genotypes, soil, climate and management? The answer is complex and requires comprehensive science-based tools that integrate many factors. The project goal is to improve soybean yields by using science-based mechanistic tools that measure N fixation and relevant crop/soil data during the growing season to better understand N uptake dynamics and develop robust pre-season decision support tools to provide insights into factors limiting soybean yields. The tool also forecasts soybean yields, crop growth and water/nitrogen requirements in real-time. Once the tool is fully calibrated, it can be applied to support both pre- and in-season decision making.

Key Benefactors:
farmers, agronomists, Extension agents

Information And Results
Final Project Results

Update:
We performed a series of field experiments and crop model simulations to increase knowledge on soybean growth in Iowa and support decision making process towards increasing soybean yields and profitability. Field experiments from two sites in 2015 increased to ten sites in 2017. In total, we performed 26 site-years trials. The amount, quality and type of data collected from each trial is unique and provided valuable insights into soybean crop growth, nitrogen and yield dynamics. Below we provide a list of measurements and the main findings:

1. Soil temperature, water at two depths and depth to groundwater table every hour in every trial. Main finding: the depth to groundwater table (range from 2 to 8 feet in all trials) had a substantial impact on crop yields (up to 15 bu/ac contribution to the final yield).
2. Soil nitrate at two depths, every second week. Main finding: by July, soil nitrate levels in soybean plots are very low levels (near 5-10 lbs/ac) because plant roots are very efficient in taken up and using the nitrate derived from the soil organic matter mineralization. We did not measure any N limitation in our plots (note yield levels up to 70 bu/ac).
3. Biological N fixation at two sites, two planting date treatments, and two years (n=8 trials). Main findings: a) on average across all datasets N-fixation contributed about half of the total N uptake, b) high soil nitrate levels suppressed the amount of biological N fixation but not the yield levels, c) the rate of N-fixation varied over the season and in most of the cases we measured high N-fixation rates towards the end of the growing season (grain fill period).
4. Soybean roots in all sites in 2016 and 2017 years, every 10 days. Main findings: a) soybean maximum root depth up to 6 feet depth; b) soybean roots increase initially slow by 0.4 in/d until 3rd node and fast thereafter at a rate of 1.3 in/day; c) the deeper the depth to groundwater the deeper the root depth in Iowa in the absence of other soil constraints. Root mass measurements indicated that 81% of the soybean root mass in concentrated in the top two feet.
5. Leaf area index, node number per plant, leaf mass, every 15-days. Main finding: it takes about 30 to 45 days for soybean to reach a leaf area index of about 3 that means 90% of the light is intercepted. Herbicide application in June delays evolution of leaf area index by a few days (site-management specific). Soybean starts dropping leaves very fast once the day-length is 12 hours (around Sept 20). Under common practices soybean plants produce up to 24 nodes at a rate of about 0.16 nodes per day. Once soybeans have 12 nodes then more than 90% of the incoming radiation is intercepted.
6. Pods per plant, every 15-days. Main finding: very variable plant trait, depending on the plant population. Our measurements indicated that it can vary from 25 to 80 pods/plant.
7. Crop growth, biomass production and partitioning, every 15-days. Main findings: Crop growth rates during the season averaged about 175 kg/ha/day which are below the theoretical limit of C3 plants that is 300 kg/ha/day. The high protein content of leaves and seeds is a reason for the low rates of increase compared to other C3 species. Until 40–60 days after planting, the produced biomass is distributed among leaves, stems and roots. After that time seed becomes the stronger sink and receives much of carbohydrates produced from photosynthesis as well as carbohydrates and nutrients from other plant tissues (re-translocation).
8. Tissue N concentrations, every 15-days. Main finding: Seed protein content at harvest maturity ranged from 30.6 to 39.7% across multiple trials with an average value of 34%.

All of the above measurements were used to calibrate and validate the APSIM cropping systems model. We used the model to perform three types of analyses and develop web-tools to provide more data to the farmers to support decision making:

1. Pre-season scenario analysis. We developed a decision web-tool that calculates optimum combinations of planting date and maturity groups per location to maximize yields. It does also calculate frost risk. The tool is called Soybean Planting Decision Tool and is publically available: http://agron.iastate.edu/CroppingSystemsTools/soybean-decisions.html
2. In-season crop yield, crop staging, soil water and nitrogen forecasting. We developed a second publically available web-tool (called FACTS: https://crops.extension.iastate.edu/facts/ ) that provides real-time information about soybean growth and soil water and nitrogen reserves as well as forecast for the next two weeks and predictions of the end of season yields. That is the only tool in the USA that simultaneously provides simulations and ground-truth data. The FACTS-tool received more than 10,000 web views over the last two years, with the months of June and July to be the months with maximum usage.
3. End-of season benchmarking analysis. At the end of each growing season we performed WHAT-IF model scenario analyses per location to identify yield gaps, learn what went well and what went wrong in the previous growing season and finally we explored combinations of practices that lead to high soybean yields. Most of these results delivered to the farmers via newsletters and extension presentations.

List of deliverables over the last three years:
1. Two publically available web-tools for decision support
2. Two published journal publication (+4 in preparation)
3. Twenty five proceedings and newsletters
4. Twenty research and extension presentations

View uploaded report PDF file

View uploaded report 2 Word file

The United Soybean Research Retention policy will display final reports with the project once completed but working files will be purged after three years. And financial information after seven years. All pertinent information is in the final report or if you want more information, please contact the project lead at your state soybean organization or principal investigator listed on the project.