Considerations with using unmanned aircraft systems in turfgrass

In recent years, small unmanned aircraft systems (sUAS) and advancements in remote sensing technology have provided alternative and more affordable means for monitoring crop health and stress than ground-based (hand-held or vehicle-mounted) or other aerial-based platforms (manned aircraft or satellites). However, few scientific studies have evaluated the application of sUAS in turfgrass systems. The use of sUAS in monitoring turfgrass requires an understanding of basic remote sensing principles; identifying the target of interest and the various sUAS platforms and sensors that provide the necessary resolution and frequencies to measure and monitor that target; calibration of sensors in the field; and data processing considerations. Those topics are discussed, followed by reviews of recent turfgrass field studies conducted to predict and manage drought stress and pest outbreaks, and improve phenotyping capabilities in turfgrass breeding programs. The use of sUAS remote sensing in turfgrass offers unique possibilities and challenges, which are addressed herein

RGB Vegetation Indices, NDVI, and Biomass as Indicators to Evaluate C-3 and C-4 Turfgrass under Different Water Conditions

[EN] Grasslands have a natural capacity to decrease air pollution and a positive impact on human life. However, their maintenance requires adequate irrigation, which is difficult to apply in many regions where drought and high temperatures are frequent. Therefore, the selection of grass species more tolerant to a lack of irrigation is a fundamental criterion for green space planification. This study compared responses to deficit irrigation of different turfgrass mixtures: a C-4 turfgrass mixture, Cynodon dactylon-Brachypodium distachyon (A), a C-4 turfgrass mixture, Buchloe dactyloides-Brachypodium distachyon (B), and a standard C-3 mixture formed by Lolium perenne-Festuca arundinacea-Poa pratensis (C). Three different irrigation regimes were assayed, full irrigated to 100% (FI-100), deficit irrigated to 75% (DI-75), and deficit irrigated to 50% (DI-50) of container capacity. Biomass, normalized difference vegetation index (NDVI), green area (GA), and greener area (GGA) vegetation indices were measured. Irrigation significantly affected the NDVI, biomass, GA, and GGA. The most severe condition in terms of decreasing biomass and vegetation indices was DI-50. Both mixtures (A) and (B) exhibited higher biomass, NDVI, GA, and GGA than the standard under deficit irrigation. This study highlights the superiority of (A) mixture under deficit irrigation, which showed similar values of biomass and vegetation indices under full irrigated and deficit irrigated (DI-75) container capacities.This research was funded by AREA VERDE-MG projects and Projects GO-PDR18-XEROCESPED funded by the European Agricultural Fund for Rural Development (EAFRD) and IMIDRA.Marín, J.; Yousfi, S.; Mauri, PV.; Parra, L.; Lloret, J.; Masaguer, A. (2020). RGB Vegetation Indices, NDVI, and Biomass as Indicators to Evaluate C-3 and C-4 Turfgrass under Different Water Conditions. Sustainability. 12(6):1-16. https://doi.org/10.3390/su1206216011612

Evapotranspiration and Energy Balance of Irrigated Urban Turfgrass

Water usage for irrigation is a big consumer of water resources in urban areas in Utah and other parts of the Intermountain Region of the Western United States. As populations continue to increase in these states, it is important to understand how much water is being used by urban landscapes in order to plan and manage future water resources. Evapotranspiration (ET), or the amount of water leaving a surface over a certain timeframe due to both transpiration from plants and evaporation from the soil, is a key variable in understanding how much water urban landscapes are really using to grow and survive. There are ways to estimate it using nearby weather station data, but this method has shown to not always be accurate for one of the more prominent urban landscapes: turfgrass. There are more rigorous ways of measuring ET, but they are much more expensive and require maintenance and processing time. Satellite remote sensing models are becoming an increasingly popular way to estimate ET as well, but they are difficult to employ in urban areas due to the dense spacing of different landscapes and man-made structures. In this thesis, measurements of high-frequency three-dimensional wind, temperature, and humidity are collected and processed to calculate how much water was used at a golf course in a suburban area. This data is then used to validate a simple yet tested and published remote sensing model. ET measurements during the 2017 and 2018 growing season showed that in general more water was being used by the turfgrass than the recommended amount, although this changed throughout the growing season and the turfgrass was actually using less than the recommended amount during the fall months. The validation of the remote sensing model did provide a fair estimate of the average measured values, but the performance of the model was not as good as those found in other studies, likely due to properties of urban landscapes violating some of the assumptions in the model. Combining the model and its validation provide important information on how much water urban landscapes consume, along with steps forward in modeling this water use from a remote sensing perspective

Spectral analysis of hybrid bermudagrass placed under various combinations of nitrogen and water availability

Remote sensing technology that uses a movable ground-based system has promise for rapid, accurate and objective evaluation of turfgrass quality for instantaneous nitrogen and water application correction. Such a test has been made on hybrid bermudagrass \u27Tifway\u27 [ Cynodon dactylon (L.) Pers. x C. transvaalensis Burtt-Davy] through a 2-year field study at the Center for Urban Water Conservation in the city of North Las Vegas. Ten combinations of water and nitrogen treatments including cyclic and steady conditions were imposed on twenty experimental plots, with two replications per treatment. Treatments consisted of five N treatments: High Steady Nitrogen (HSN), Low Steady Nitrogen (LSN), High Pulse Nitrogen (HPN), Low Pulse Nitrogen (LPN), High Incremental Nitrogen (HIN), Low Incremental Nitrogen (LIN); and three water treatments based on leaching fractions: Low Leaching Fraction (LLF = -0.15), High Leaching Fraction (HLF = +0.15), Low to High Leaching Fraction (LHLF ranging from -0.25 to +0.25) all combined with N treatments in ten different combinations. Canopy spectral reflectance measurements were acquired on a biweekly basis. (Abstract shortened by UMI.)

Using Thermal Imaging to Measure Water Stress in Creeping Bentgrass Putting Greens

Thermal imaging is a developing tool that can help turf managers reduce water consumption and improve irrigation scheduling, but in-depth studies are needed to maximize this potential. This study evaluated the ability of thermal imaging to identify water stress in a creeping bentgrass (Agrostis stolonifera ‘007’) putting green. Water use and canopy temperature (Tc) were measured for plots subjected to three levels of measured water replacement (full, half, and none) to evaluate changes over a range of soil water potentials (SWP). Water use was consistent across the irrigation treatments up to several days before observed wilt with crop coefficients (Kc) between 0.83-1.01. As drought conditions progressed (SWP c decreased. Segmented linear regression was used to quantify the trends and identify the critical value of -1501 kPa. Various metrics utilizing Tc were evaluated for a response to water stress. Two metrics, standard deviation of Tc and Tc relative to non-water stressed turf, show potential to indicate periods of stress prior to visible wilt. A strong diurnal pattern was observed in all Tc metrics confirming the need to normalize Tc for current weather conditions. Multiple regression using 2018 data was used to develop a model using weather parameters of air temperature, solar radiation, relative humidity, and wind speed to estimate Tc values of a non-water stressed baseline. A two parameter model using air temperature and solar radiation input provided a strong fit (adjusted R2=0.955) and when applied to unpublished dataset from a 2016 study measuring Tcon a creeping bentgrass putting green. This study shows water use remained consistent until SWP reached a wilting point, followed by a sharp decrease in water use approaching Kc of zero. We show that metrics utilizing Tc can be early indicators of water stress in turfgrass. However, further research with different microclimates and plot sizes would be needed to identify specific values of these metrics that quantify water stress. We also describe a multiple regression model to predict Tc of non-water stressed baseline under various weather conditions. Understanding how Tc of turf with no water stress behaves in different weather can improve identification of water stress. Advisor: William C. Kreuse

A Decade of Unmanned Aerial Systems in Irrigated Agriculture in the Western U.S.

Several research institutes, laboratories, academic programs, and service companies around the United States have been developing programs to utilize small unmanned aerial systems (sUAS) as an instrument to improve the efficiency of in-field water and agronomical management. This article describes a decade of efforts on research and development efforts focused on UAS technologies and methodologies developed for irrigation management, including the evolution of aircraft and sensors in contrast to data from satellites. Federal Aviation Administration (FAA) regulations for UAS operation in agriculture have been synthesized along with proposed modifications to enhance UAS contributions to irrigated agriculture. Although it is feasible to use sUAS technology to produce maps of actual crop coefficients, actual crop evapotranspiration, and soil water deficits, for irrigation management, the technology and regulations need to evolve further to facilitate a successful wide adoption and application. Improvements and standards are needed in terms of cameras’ spectral (bands) ranges, radiometric resolutions and associated calibrations, fuel/power technology for longer missions, better imagery processing software, and easier FAA approval of higher altitudes flight missions among other issues. Furthermore, the sUAS technology would play a larger role in irrigated agriculture when integrating multi-scale data (sUAS, groundbased or proximal, satellite) and soil water sensors is addressed, including the need for advances on processing large amounts of data from multiple and different sources, and integration into scientific irrigation scheduling (SIS) systems for convenience of decision making. Desirable technological innovations, and features of the next generation of UAS platforms, sensors, software, and methods for irrigated agriculture, are discussed

Agricultural Water Conservation: Tools, Strategies, and Practices

Water scarcity is a critical issue for agriculture, and, hence, efficient management and conservation practices for agricultural water use are essential for adapting to and mitigating the impacts of current and future discrepancy between water supplies and water demands. This Special Issue focuses on “Agricultural Water Conservation: Tools, Strategies, and Practices”, which aims to bring together a collection of recent cutting-edge research and advancements in agricultural water conservation. The Special Issue intends to give a broad overview focusing on on-farm water conservation practices, advanced irrigation tools and water technologies, and the best management practices and strategies for efficient water use in agriculture

Applicability of Pigment Compounds for Reducing Light Stress in Bentgrass

Chlorinated copper phthalocyanine (Signature) and pulverized cells of Chlorella vulgaris (Chlorella) were evaluated in a controlled environment for their ability to act as photoprotectants under supraoptimal levels of ultraviolet (UV) and photosynthetically active radiation (PAR) when applied to plant leaves. Plant pigment changes were documented using High Performance Liquid Chromatography following 1 week of exposure to supraoptimal light in two separate experiments incorporating UV (106.6 μmol m-2 s-1) and PAR (760.6 μmol m-2 s-1) over a 12h photoperiod. Supraoptimal levels of UV and PAR light were found to cause significant reductions in Agrostis palustris chlorophyll and carotenoid leaf pigment levels. In both experiments, high light coincided with increases in zeaxanthin and antheraxanthin and decreases in violaxanthin across all treatments, suggesting that plants experienced a stress response regardless of pigment application. Under high PAR light, the levels of total carotenoid pigment degradation were significantly higher in untreated Agrostis palustris controls than in Chlorella and Signature treated plants. However, only Chlorella demonstrated the ability to significantly reduce instances of chlorophyll degradation in bentgrass plants under high UV light. Spectral imaging of light following transmission through treatments demonstrated how Chlorella was successful in limiting the absorbance of wavelengths in regions of UV (300 to 400 nm) and PAR (480 and 580 nm). Photon flux measurements of transmitted light showed a significant decrease in both treatments when compared to controls; the greatest reduction in light levels occurred with Chlorella applications under both UV and PAR light. Results of these experiments demonstrate how this interception of light may limit chlorophyll and carotenoid degradation under these conditions, suggesting that they may be used to successfully act as photoprotectants. This holds particular value in golf course maintenance, where bentgrasses are cultivated at low mowing heights in regions where supraoptimal light conditions persist throughout the growing season