Development and Application of Cell-Phone-Based Internet of Things (IoT) Systems for Soil Moisture Monitoring

Active soil moisture monitoring is an important consideration in irrigation water management. A permanent and readily accessible record of changes in soil moisture can be used to improve future water management decision-making. Similarly, accessing stored soil moisture data in near-real-time is also essential for making timely farming and management decisions, such as where, when, and how much irrigation to apply. Access to reliable communication systems and delivery of real-time data can be affected by its availability near production fields. Therefore, soil moisture monitoring systems with real-time data functionality that can meet the needs of farmers at an affordable cost are currently needed. The objective of the study was to develop and fieldtest affordable cell-phone-based Internet of things (IoT) systems for soil moisture monitoring. These IoT systems were designed using low-cost hardware components and open-source software to transmit soil moisture data from the Watermark 200SS or ECH2O EC-5 sensors. These monitoring systems utilized either Particle Electron or Particle Proton Arduino-compatible devices for data communication. The IoT soil moisture monitoring systems have been deployed and operated successfully over the last three years in South Carolina.

Effects of Tillage and Planting Methods on Narrow and Wide Row Cotton Production

Cotton (Gossypium hirsutum L.) is an economically important crop for the Southern United States. The southern US also has a long growing season suitable for double cropping a second crop after small grains;however, the harvest date for the small grains typically occurs after the optimum planting window for cotton which reduces yield potential. A relay intercropping system was developed at Clemson University that allows interseeding of cotton into standing wheat 2 to 3 weeks before harvest with interseeded cotton yields similar to the conventional mono-cropped cotton. Therefore, the objectives of this study were 1) to determine the optimum tillage and planting methods for narrow row (76-cm) and wide row (97-cm) cotton, and 2) to compare narrow and wide row systems for conventional tillage cotton, cotton interseeded into standing wheat, and cotton planted into a terminated wheat cover crop on coastal plain soil. Two replicated tests were conducted to accomplish these objectives. In Study 1, conventional narrow row cotton combined with a deep tillage operation using Paratill yielded 23% more than conventional wide row cotton which had a deep tillage operation with a subsoiler just before planting. There were no differences between the conventional (97-cm row spacing) mono-crop and interseeded cotton yields. In Study 2, there was no significant difference in yield between narrow-row and wide-row cotton for each cropping system during the two years study. Both wide and narrow-row full season cotton had significantly higher yields than interseeded and cover crop planting systems in year two of the study. The two conservation cropping practices, wheat used as a cover crop and interseeding, showed considerable promise for reducing energy requirements, soil erosion, and wind-borne cotton damage associated with bare soil in conventional tillage. This research demonstrates the benefits of interseeding and narrow row spacing for sustainable cotton production in coastal plain soils of the Southern United States.

Development of an Internet of Things (IoT) System for Measuring Agricultural Runoff Quantity and Quality

Runoff is an important component of the water balance of agricultural fields. Accurate measurement or estimation of agricultural runoff is important due to its potential impact on water quantity and quality. Since runoff from agricultural fields is sporadic and is often associated with irrigation and/or intense rainfall events, manually measuring runoff and collecting water samples for water quality analysis during runoff events is inconvenient and impractical. In the fall of 2017, a field site was selected at the Clemson University Edisto Research and Education Center with the objective of developing, constructing, and testing an Internet of things (IoT) flume system to automatically measure runoff and collect water samples. In 2018, an automatic IoT system was developed and installed consisting of six stainless steel H-flumes (22.9-cm), which measured runoff from six adjacent research plots under two different cultural regimes (cover crop and no cover crop). An electronic eTape sensor was installed in the flume and used to measure the water level or the flume’s head. Open-source electronic (Arduino) devices and a cloud-based platform were then used to create a wireless sensor network and IoT system to automatically record the amount of runoff (hydrograph) coming from each section, collect water samples and transmit the data to a Cloud server (Thingspeak.com) where the data can be viewed remotely in real-time. The IoT flume system has been operating successfully and reliably for more than two years.

County-Specific Chill Hours Accumulation in South Carolina

Winter chilling is critical for most temperate fruits and perennial plants during the winter season. Most fruit and nut trees require a prolonged period of chilling to break their dormant stage and bloom when spring arrives. This research’s primary objective was to calculate the chill hour’s accumulation in each county in South Carolina based on the historical hourly air temperature data for the last ten years (2010-2020). The chilling hours model used to calculate the daily chill hours was based on the number of hours when the air temperature was between 32°F to 45°F (0 to 7.2°C). The total chill hours for each county were then determined by accumulating the daily chill hours from October to June. Our results showed that among the different counties in South Carolina, on average Laurens County had the most prolonged chill hours (1419 hrs). The chill hours were higher between November to March, and counties near the coastal regions had fewer chill hours than the counties in the inland areas. For example, Beaufort, Charleston, Berkeley, Horry, and Dorchester counties that are located near the coastal region had fewer chill hours. In contrast, counties located in the inland areas like Laurens, Chester, Lancaster, and York recorded the most prolonged chill hours. Our results suggest that selecting high chilling requirement crops for the inland areas and low chilling requirement crops for coastal areas would be appropriate. Farmers in South Carolina can use this information to plan their crop selection and management.