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County-Specific Chill Hours Accumulation in South Carolina  [PDF]
José O. Payero, Udayakumar Sekaran
Atmospheric and Climate Sciences (ACS) , 2021, DOI: 10.4236/acs.2021.113030
Abstract: 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.
Field Evaluation of Soil Water Extraction of Cotton  [PDF]
José O. Payero, Graham Harris, Geoff Robinson
Open Journal of Soil Science (OJSS) , 2017, DOI: 10.4236/ojss.2017.712027
Abstract: Water scarcity is often a major limiting factor in cotton (Gossypium hirsutum L.) production, and sustaining productivity and profitability with limited water is a major challenge for the cotton industry. A good understanding of the magnitude, timing and spatial distribution of cotton soil water extraction is important for proper irrigation management, and for development of accurate crop models and decision support systems. The overall objective of this study was to evaluate the water extraction distribution of cotton under different irrigation regimes. Specific objectives were to quantify: 1) the depth of soil water extraction as a function of time, 2) the percent of seasonal water extraction from each soil depth, and 3) the relationship between depth of soil water extraction and canopy height. To meet these specific objectives, daily and seasonal cotton soil water extraction were determined from continuous records of water content in the soil profile measured from four irrigation treatments during a field experiment. We found that cotton extracted soil water from as deep as 150 cm, but the percent of seasonal extraction sharply decreased with soil depth. The top 50 cm soil layer accounted for 75% of the seasonal extraction and the top 80 cm, for 90%. We also found that from 32 days after sowing (DAS) to 100 DAS, the depth of soil water extraction increased linearly at a rate of 1.89 cm·day-1 or 2.36 times the increase in crop canopy height. These findings suggest that cotton producers should manage irrigations to maintain adequate moisture in the top 80 cm of the soil profile rather than relying on moisture stored deeper in the profile.
Temperature Trends and Accumulation of Chill Hours, Chill Units, and Chill Portions in South Carolina  [PDF]
José O. Payero
Atmospheric and Climate Sciences (ACS) , 2024, DOI: 10.4236/acs.2024.142011
Abstract: There is considerable concern about the potential impact of climate change on agriculture, such as the accumulation of chilling hours needed to break the dormancy of many perennial plants, like fruit trees. Therefore, this study aimed to determine if there had been a significant change in air temperatures and chill hours, chill units, and chill portion accumulation in South Carolina over the last two decades. Two decades of daily maximum (Tmax) and minimum (Tmin) air temperature records were obtained from weather stations in thirty-one counties in South Carolina. Hourly temperature data, reconstructed from the daily data, were used to calculate the daily and annual chill hours, chill units, and chill portions accumulation using four different chill models for each location and year. The chill models included the T(t) < 7.2°C model, the 0°C < T(t) < 7.2°C model, the Utah model, and the Dynamic model. For each county, regression analyses were conducted to evaluate the historical trends. Despite year-to-year variability, the tendency was a statistically significant (α = 0.05) increase in air temperature, averaging 0.089°C per year for 20 out of 31 counties in South Carolina. The other 11 counties had no significant change in temperature. The average temperature increase in the 31 counties was 0.072°C per year. The temperature increase resulted in a decrease in annual chill accumulation during the fall to spring, averaging 17.7 chill hours, 8.6 chill hours, 17.0 chill units, and 0.40 chill portions per year calculated with the T(t) < 7.2°C, 0°C < T(t) < 7.2°C, Utah, and Dynamic models, respectively. However, whether this decrease in chill values was statistically significant or not depended on the chill model used. This study did not investigate the cause of the observed historical trends in temperature and chill accumulation. Still, if the trends continue, they could significantly impact the future of the temperate fruit tree
An Arduino-Based Wireless Sensor Network for Soil Moisture Monitoring Using Decagon EC-5 Sensors  [PDF]
José O. Payero, Ali Mirzakhani Nafchi, Rebecca Davis, Ahmad Khalilian
Open Journal of Soil Science (OJSS) , 2017, DOI: 10.4236/ojss.2017.710021
Abstract: It is undeniable that wireless communication technology has become a very important component of modern society. One aspect of modern society in which application of wireless communication technologies has tremendous potential is in agricultural production. This is especially true in the area of sensing and transmission of relevant farming information such as weather, crop development, water quantity and quality, among others, which would allow farmers to make more accurate and timely farming decisions. A good example would be the application of wireless communication technology to transmit soil moisture data in real time to help farmers make irrigation scheduling decisions. Although many systems are commercially available for soil moisture monitoring, there are still many important factors, such as cost, limiting widespread adoption of this technology among growers. Our objective in this study was, therefore, to develop and test an affordable wireless communication system for monitoring soil moisture using Decagon EC-5 sensors. The new system uses Arduino-compatible microcontrollers and communication systems to sample and transmit values from four Decagon EC-5 soil moisture sensors. Developing the system required conducting lab calibrations for the EC-5 sensors for the microcontroller operating in either 10-bit or 12-bit analog-to-digital converter (ADC) resolution. The system was successfully tested in the field and reliably collected and transmitted data from a wheat field for more than two months.
Evaluating the Effect of Soil Texture on the Response of Three Types of Sensors Used to Monitor Soil Water Status  [PDF]
José O. Payero, Xin Qiao, Ahmad Khalilian, Ali Mirzakhani-Nafchi, Rebecca Davis
Journal of Water Resource and Protection (JWARP) , 2017, DOI: 10.4236/jwarp.2017.96037
Abstract: Accurate monitoring of soil water status can be an important component of precision irrigation water management. A variety of commercial sensors measure soil water status by relating sensor electrical output to soil water content or soil water potential. However, sensor electrical output can also be affected by soil characteristics other than water content, such as soil texture, salinity, and temperature. This makes it difficult to accurately measure and interpret soil water status without prior on-site calibration. In this study, we investigated the impact of soil texture on the response of three types of sensors commonly used to monitor soil water status, including the Decagon EC-5, the Vegetronix VH400, and the Watermark 200ss granular matrix sensor. A replicated laboratory experiment was conducted to evaluate the response of these types of sensors using four major soil textural classes commonly found in South Carolina. We found that the three types of sensors had a significant response to changes in soil water content, but while the EC-5 and VH400 sensors had a linear response, the Watermark 200ss had a curvilinear response that was explained by an exponential decay function. The response of the three sensor types, however, was significantly affected by soil texture, which will significantly affect the trigger point used to initiate irrigation based on the output from these sensors. Therefore, it is suggested that guidelines on how to use these sensors for local soils need to be developed and made available to farmers, so that they can make better irrigation scheduling decisions.
Development of a Low-Cost Internet-of-Things (IoT) System for Monitoring Soil Water Potential Using Watermark 200SS Sensors  [PDF]
José O. Payero, Ali Mirzakhani-Nafchi, Ahmad Khalilian, Xin Qiao, Rebecca Davis
Advances in Internet of Things (AIT) , 2017, DOI: 10.4236/ait.2017.73005
Abstract: Soil moisture monitoring is one of the methods that farmers can use for irrigation scheduling. Many sensor types and data logging systems have been developed for this purpose over the years, but their widespread adoption in practical irrigation scheduling is still limited due to a variety of factors. Important factors limiting adoption of soil moisture sensing technology by farmers include high cost and difficulties in timely data collection and interpretation. Recent developments in open source microcontrollers (such as Arduino), wireless communication, and Internet-of-Things (IoT) technologies offer opportunities for reducing cost and facilitating timely data collection, visualization, and interpretation for farmers. Therefore, the objective of this study was to develop and test a low-cost IoT system for soil moisture monitoring using Watermark 200SS sensors. The system uses Arduino-based microcontrollers and data from the field sensors (End Nodes) are communicated wirelessly using LoRa radios to a receiver (Coordinator), which connects to the Internet via WiFi and sends the data to an open-source website (ThingSpeak.com) where the data can be visualized and further analyzed using Matlab. The system was successfully tested under field conditions by installing Watermark sensors at four depths in a wheat field. The system described here could contribute to widespread adoption of easy-to-use and affordable moisture sensing technologies among farmers.
Effect of Rye and Mix Cover Crops on Soil Water and Cotton Yield in a Humid Environment  [PDF]
José O. Payero, Michael W. Marshall, Rebecca H. Davis, Joe Bible, Nathaniel Nemire
Open Journal of Soil Science (OJSS) , 2021, DOI: 10.4236/ojss.2021.115015
Abstract: In recent years, the use of cover crops is becoming a popular technology among growers in many regions of the United States, which is expected to deliver various benefits such as improving soil health, increasing soil organic matter, controlling weeds, and helping conserve soil water and nutrients. Although expecting these benefits seems reasonable, it is challenging to know how much of these benefits to expect under specific situations. The potential effect of cover crops on soil water conservation is especially significant because of the documented impact of soil water on crop yield, especially for dryland cropping systems. Some researchers have found that planting a cover crop tended to increase soil water, while others have reported the opposite effect. Information on the impact of cover crops on soil water in cotton (Gossypium hirsutum L.) production systems in South Carolina is currently lacking. Therefore, the objective of this study was to quantify the effect of cover crops on soil water and cotton yield. A field experiment was conducted in South Carolina during winter, spring, and summer of 2015, with three cover crop treatments. The treatments included: 1) rye (Secale cereale L.), planted alone; 2) a mix of six cover crop species; and 3) a control treatment with no-cover. The cover crop was established in the winter, terminated in the spring, and cotton was grown during the summer. Soil water was measured at different depths using capacitance probes and a neutron probe. Our results showed no significant differences in soil water and cotton yield among the cover crop treatments. These results suggest that under the humid conditions of this study, any short-term effect of the cover crop on soil water was masked by timely rain.
Development and Application of Cell-Phone-Based Internet of Things (IoT) Systems for Soil Moisture Monitoring  [PDF]
José O. Payero, Michael W. Marshall, Bhupinder S. Farmaha, Rebecca Hitchcock Davis, Ali Mirzakhani Nafchi
Agricultural Sciences (AS) , 2021, DOI: 10.4236/as.2021.125035
Abstract: 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.
Development of an Internet of Things (IoT) System for Measuring Agricultural Runoff Quantity and Quality  [PDF]
José O. Payero, Michael W. Marshall, Ali Mirzakhani Nafchi, Ahmad Khalilian, Bhupinder S. Farmaha, Rebecca Davis, Wesley Porter, George Vellidis
Agricultural Sciences (AS) , 2021, DOI: 10.4236/as.2021.125038
Abstract: 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.
Evaluating Reflected GPS Signal as a Potential Tool for Cotton Irrigation Scheduling  [PDF]
Xin Qiao, Ahmad Khalilian, Jose O. Payero, Joe Mari Maja, Charles V. Privette, Young J. Han
Advances in Remote Sensing (ARS) , 2016, DOI: 10.4236/ars.2016.53013
Abstract: Accurate soil moisture content measurements are vital to precision irrigation management. Remote sensing using the microwave spectrum (such as GPS signals) has been used for measuring large area soil moisture contents. In our previous work, we estimated surface soil moisture contents for bare soil using a GPS Delay Mapping Receiver (DMR) developed by NASA. However, the effect of vegetation was not considered in these studies. Hence the objectives of this study were to: 1) investigate the feasibility of using DMR to determine soil moisture content in cotton production fields; 2) evaluate the attenuation effect of vegetation (cotton) on reflected GPS signal. Field experiments were conducted during the 2013 and 2014 growing seasons in South Carolina. GPS antennas were mounted at three heights (1.6, 2.7, and 4.2 m) over cotton fields to measure reflected GPS signals (DMR readings). DMR readings, soil core samples, and plant measurements were collected about once a week and attenuation effect of plant canopy was calculated. Results showed that DMR was able to detect soil moisture changes within one week after precipitation events that were larger than 25 mm per day. However, the DMR readings were poorly correlated with soil volumetric water content during dry periods. Attenuation effect of plant canopy was not significant. For irrigation purpose, the results suggested that the sensitivity of reflected GPS signals to soil moisture changes needed to be further studied before this technology could be utilized for irrigation scheduling in cotton production. Refinement of this technology will expand the use of advanced remote sensing technology for site-specific and timely irrigation scheduling. This would eliminate the need to install moisture sensors in production fields, which can interfere with farming operations and increase production costs.
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