2020
Determining the Optimum Soil Moisture Sensor Threshold in Soybean
Contributor/Checkoff:
Category:
Sustainable Production
Keywords:
SustainabilityWater resistanceWater supply
Parent Project:
This is the first year of this project.
Lead Principal Investigator:
Michael Plumblee, Clemson University
Co-Principal Investigators:
Project Code:
Contributing Organization (Checkoff):
Institution Funded:
Brief Project Summary:

Irrigated row crop acres in South Carolina have steadily increased over the last 10 years. Groundwater regulation also increased with regard to well permitting. By determining appropriate soil moisture sensor thresholds specific to Coastal Plain soil textures and soybean, growers can maximize profit by maximizing yield and improving irrigation water use efficiency. This project plans to determine the optimum soil moisture sensor threshold value using soil tension (Watermark) soil moisture sensors, evaluate season-long irrigation schedules and determine the return on investment and payback period for soil moisture sensor technologies and irrigation schedules used in soybean production in South Carolina.

Key Beneficiaries:
#agronomists, #extension agents, #farmers
Unique Keywords:
#irrigation, #irrigation, #soil moisture sensors, #threshold kpa, #water use efficiency
Information And Results
Project Deliverables

The expected output/deliverables of this research will be shared with soybean growers in South Carolina and throughout the southeast. Information exchange will be through the use of the bi-monthly Clemson Precision Ag Newsletter, social media (Twitter and Facebook), extension publications, Clemson Precision Ag Seminar Series, field days, and grower meetings.

Final Project Results

Updated January 4, 2021:
SCSB Final Report

General Information
Principal Investigator(s) Name(s): Michael Plumblee
Organization: Clemson University – Edisto REC
Date: January 4, 2020
Quarter: Final

Proposal Information
Title: Determining the Optimum Soil Moisture Sensor Threshold in Soybean
Amount Expended to Date: $6,000 ~ 100%

Progress Assessment
Wendy Buchanan, the M.S. graduate student has been working on this project and started in January 2020. Overall, this trial went well and as expected. Unfortunately, due to timely rainfall events no significant differences were observed between irrigation treatments where rain-fed, non-irrigated, plots made similar yields. Continued research on defining soil moisture sensor thresholds for irrigated soybean in South Carolina is needed.

On-Station Location
Soybean plots were harvested on November 3, 2020. In Blackville, SC during the 2020 growing season annual rainfall resulted in 26.5 inches from May through October. Above average rainfall occurred in August during late bloom and pod fill resulting in good yields even in rain-fed plots. During the growing season approximately 4.5 inches of irrigation were applied to the -15 kPa threshold plots, 3.2 inches of irrigation were applied to the -30 kPa threshold plots, and 1.65 inches of irrigation were applied to the -60 kPa threshold plots. Overall, soybean yields were very good regardless of irrigation treatment and no significant differences were observed between irrigation threshold treatments in 2020. No differences in test weight were observed in 2020.


Figure 1. Soybean Yield (bu/ac) corrected to 13% by irrigation threshold/treatment.

Plant heights and total nodes were collected mid-season and at harvest. No significant differences were observed among irrigation treatments for total plant height or total plant nodes at either measurement timing.

Figure 2. Plant Height Measurements by Treatment


Figure 3. Total Plant Nodes by Treatment

With agricultural water and irrigation becoming a hot topic throughout the Southeast improving our irrigation water use efficiency using soil moisture sensors is imperative. Irrigation water use efficiency is defined as yield produced for every given amount of irrigation water applied. Irrigation water use efficiency was significantly different among treatments even though grain yields were similar. This is in part due to no additional yield being produced even though additional irrigation was applied based on sensor readings for some treatments.

Figure 4. Irrigation Water Use Efficiency by Irrigation Treatment.

Based on these results and the rainfall that we had during the 2020 growing season, our best option would have been to utilize a threshold of -60 kPa (least aggressive) where 47 bushels were produced for every inch of irrigation applied compared to the -30 and -15 kPa threshold at 23 and 17 bushels per inch, respectively. In order to fully understand the best irrigation threshold recommendation evaluating IWUE and net returns above irrigation cost is beneficial. This comparison will provide the most profitable and water efficient threshold value. Based on the 2020 trial, the best irrigation threshold for soybean would have been the -60 kPa threshold. Ideally, before making a recommendation however, additional site-years of data would be obtained to account for year-to-year weather variability before doing so. With this being said, Watermark 200SS soil moisture sensors appeared to have accurately and simply scheduled irrigation in soybean in South Carolina coastal plain soils. Further investigation of sensor thresholds among different weather years is needed to determine the optimum threshold for irrigated soybean production in SC.


Figure 5. IWUE by Net Return Above Irrigation Costs based on $10/bu Soybean Price.


Key Performance Indicators
Key performance indicators for this study were determined at harvest (to determine if irrigation treatment and threshold value had any direct yield benefit). The water use efficiency data and yield data from this trial helps determine if there is an optimum soil moisture threshold that can be utilized for irrigated soybean. This research will help develop irrigation scheduling recommendations where soil moistures sensors are incorporated. Furthermore, this research allows for a threshold to be selected that maximizes yield and water use efficiency. As of now key circumstances impacting this research are rainfall or lack thereof.

Next Steps
Continue irrigation research in additional years to develop a robust dataset that can be used to base soil moisture sensor threshold recommendations for irrigation soybean in South Carolina that maximize IWUE and net returns. Continued work on analyzing data and sharing results with stakeholders will take place over the next few months at regional, local, and national meetings.



View uploaded report Word file

Soybean was irrigated in South Carolina with Watermark 200SS soil moisture sensors at thresholds consisting of -15, -30, and -60 kPa. Non-irrigated plots were included for comparison purposes. In 2020, due to timely rainfall events throughout the growing season, no significant differences in grain yield, plant height, or total plant nodes were observed across sensor threshold treatments. Significant differences in irrigation water use efficiency were observed however, where a threshold of -60 kPa produced the greatest IWUE followed by -30 kPa. A sensor threshold of -15 kPa resulted in the lowest IWUE. When comparing IWUE to net return above irrigation cost a sensor threshold of -60 kPa resulted in the most profitable and water efficient threshold in 2020 for soybean. In order to continue the development of soil moisture sensor thresholds for soybean in South Carolina additional site-years of data is needed to account for year-to-year variability in weather and rainfall. Based on this data it appears that Watermark 200SS soil moisture sensors respond and provide adequate soil moisture readings for soybean grown in the coastal plain of South Carolina.

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.