Improving Accuracy of Unmanned Aerial System Thermal Infrared Remote Sensing for Use in Energy Balance Models in Agriculture Applications

Unmanned aerial system (UAS) remote sensing has rapidly expanded in recent years, leading to the development of several multispectral and thermal infrared sensors suitable for UAS integration. Remotely sensed thermal infrared imagery has been used to detect crop water stress and manage irrigation by leveraging the increased thermal signatures of water stressed plants. Thermal infrared cameras suitable for UAS remote sensing are often uncooled microbolometers. This type of thermal camera is subject to inaccuracies not typically present in cooled thermal cameras. In addition, atmospheric interference also may present inaccuracies in measuring surface temperature. In this study, a UAS with integrated FLIR Duo Pro R (FDPR) thermal camera was used to collect thermal imagery over a maize and soybean field that contained twelve infrared thermometers (IRT) that measured surface temperature. Surface temperature measurements from the UAS FDPR thermal imagery and field IRTs corrected for emissivity and atmospheric interference were compared to determine accuracy of the FDPR thermal imagery. The comparison of the atmospheric interference corrected UAS FDPR and IRT surface temperature measurements yielded a RMSE of 2.24 degree Celsius and a R2 of 0.85. Additional approaches for correcting UAS FDPR thermal imagery explored linear, second order polynomial and artificial neural network models. These models simplified the process of correcting UAS FDPR thermal imagery. All three models performed well, with the linear model yielding a RMSE of 1.27 degree Celsius and a R2 of 0.93. Laboratory experiments also were completed to test the measurement stability of the FDPR thermal camera over time. These experiments found that the thermal camera required a warm-up period to achieve stability in thermal measurements, with increased warm-up duration likely improving accuracy of thermal measurements

SOLID WASTE DISPOSAL SITE CHARACTERIZATION USING NON-INTRUSIVE ELECTROMAGNETIC SURVEY TECHNIQUES AND GEOSTATISTICS

Prior to the research reported in this paper, a site-specific hydrogeologic investigation was developed for a closed solid waste facility in Eastern Nebraska using phased subsurface characterizations. Based on the findings of this prior investigation, a surface based geoelectric survey using electromagnetic induction to measure subsurface conductivity was implemented to delineate the vertical and horizontal extent of buffed waste and subsurface contamination. This technique proved to be a key non-intrusive, cost-effective element in the refinement of the second phase of the hydrogeologic investigation. Three-dimensional ordinary kriging was used to estimate conductivity values at unsampled locations. These estimates were utilized to prepare a contaminant plume map and a cross section depicting interpreted subsurface features. Pertinent subsurface features were identified by associating a unique range of conductivity values to that of solid waste, saturated and unsaturated soils and possible leachate migrating from the identified disposal areas

SOLID WASTE DISPOSAL SITE CHARACTERIZATION USING NON-INTRUSIVE ELECTROMAGNETIC SURVEY TECHNIQUES AND GEOSTATISTICS

Prior to the research reported in this paper, a site-specific hydrogeologic investigation was developed for a closed solid waste facility in Eastern Nebraska using phased subsurface characterizations. Based on the findings of this prior investigation, a surface based geoelectric survey using electromagnetic induction to measure subsurface conductivity was implemented to delineate the vertical and horizontal extent of buffed waste and subsurface contamination. This technique proved to be a key non-intrusive, cost-effective element in the refinement of the second phase of the hydrogeologic investigation. Three-dimensional ordinary kriging was used to estimate conductivity values at unsampled locations. These estimates were utilized to prepare a contaminant plume map and a cross section depicting interpreted subsurface features. Pertinent subsurface features were identified by associating a unique range of conductivity values to that of solid waste, saturated and unsaturated soils and possible leachate migrating from the identified disposal areas

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

Rev-erb-alpha modulates skeletal muscle oxidative capacity by regulating mitochondrial biogenesis and autophagy

The nuclear receptor Rev-erb-α modulates hepatic lipid and glucose metabolism, adipogenesis and the inflammatory response in macrophages. We show here that Rev-erb-α is highly expressed in oxidative skeletal muscle and plays a role in mitochondrial biogenesis and oxidative function, in gain- and loss-of function studies. Rev-erb-α-deficiency in skeletal muscle leads to reduced mitochondrial content and oxidative function, resulting in compromised exercise capacity. This phenotype was recapitulated in isolated fibers and in muscle cells upon Rev-erbα knock-down, while Rev-erb-α over-expression increased the number of mitochondria with improved respiratory capacity. Rev-erb-α-deficiency resulted in deactivation of the Stk11–Ampk–Sirt1–Ppargc1-α signaling pathway, whereas autophagy was up-regulated, resulting in both impaired mitochondrial biogenesis and increased clearance. Muscle over-expression or pharmacological activation of Rev-erb-α increased respiration and exercise capacity. This study identifies Rev-erb-α as a pharmacological target which improves muscle oxidative function by modulating gene networks controlling mitochondrial number and function

Systematic review of metrics used to characterise dietary nutrient supply from household consumption and expenditure surveys.

OBJECTIVE: To review existing publications using Household Consumption and Expenditure Survey (HCES) data to estimate household dietary nutrient supply to (1) describe scope of available literature, (2) identify the metrics reported and parameters used to construct these metrics, (3) summarise comparisons between estimates derived from HCES and individual dietary assessment data and (4) explore the demographic and socio-economic sub-groups used to characterise risks of nutrient inadequacy. DESIGN: This study is a systematic review of publications identified from online databases published between 2000 to 2019 that used HCES food consumption data to estimate household dietary nutrient supply. Further publications were identified by 'snowballing' the references of included database-identified publications. SETTING: Publications using data from low- and lower-middle income countries. RESULTS: In total, fifty-eight publications were included. Three metrics were reported that characterised household dietary nutrient supply: apparent nutrient intake per adult-male equivalent per day (n 35), apparent nutrient intake per capita per day (n 24) and nutrient density (n 5). Nutrient intakes were generally overestimated using HCES food consumption data, with several studies finding sizeable discrepancies compared with intake estimates based on individual dietary assessment methods. Sub-group analyses predominantly focused on measuring variation in household dietary nutrient supply according to socio-economic position and geography. CONCLUSION: HCES data are increasingly being used to assess diets across populations. More research is needed to inform the development of a framework to guide the use of and qualified interpretation of dietary assessments based on these data

Modeling food fortification contributions to micronutrient requirements in Malawi using Household Consumption and Expenditure Surveys.

Large-scale food fortification may be a cost-effective intervention to increase micronutrient supplies in the food system when implemented under appropriate conditions, yet it is unclear if current strategies can equitably benefit populations with the greatest micronutrient needs. This study developed a mathematical modeling framework for comparing fortification scenarios across different contexts. It was applied to model the potential contributions of three fortification vehicles (oil, sugar, and wheat flour) toward meeting dietary micronutrient requirements in Malawi through secondary data analyses of a Household Consumption and Expenditure Survey. We estimated fortification vehicle coverage, micronutrient density of the diet, and apparent intake of nonpregnant, nonlactating women for nine different micronutrients, under three food fortification scenarios and stratified by subpopulations across seasons. Oil and sugar had high coverage and apparent consumption that, when combined, were predicted to improve the vitamin A adequacy of the diet. Wheat flour contributed little to estimated dietary micronutrient supplies due to low apparent consumption. Potential contributions of all fortification vehicles were low in rural populations of the lowest socioeconomic position. While the model predicted large-scale food fortification would contribute to reducing vitamin A inadequacies, other interventions are necessary to meet other micronutrient requirements, especially for the rural poor