In over two decades of agricultural research, I've worked on many different projects. As a result of this experience, there are some areas of research that I am particularly comfortable in pursuing. These are listed below.
Micrometeorology. My Master's Thesis involved computing the vertical fluxes of heat and momentum in the atmospheric boundary layer. Since most of my career has been spent in semi-arid agricultural regions, I have been keenly interested in the energy balance of crop canopies and its effects on evapotranspiration and, in particular, methods of measuring these quatities. The figure below shows a Conditional Sampling system that I and John Baker (USDA-ARS, St. Paul, MN) put together at the Shafter USDA lab. It is capable of providing continuous simulataneous measurements of the vertical fluxes of sensible heat, water vapor, and carbon dioxide. I've also used DynaMax stemflow gages and microlysimeters to quantify the components of evapotranspiration from agricultural fields. At Texas Tech, I now have two of the new Campbell Scientific CS-7500 Eddy Correlation systems that can measure the 3-dimensional fluxes of sensible heat, water vapor, and carbon dioxide. This and other instrumentation will greatly enhance our ability to quantify the microenvironment and biophysics of agricultural crops in the semi-arid Texas High Plains.
Plant Growth Modeling. My Dissertation involved modeling the competition between individual plants in a stand and its effect on the growth of the plant community. During the 1970's, I helped develop the SORGF grain sorghum growth model at the Texas Agricultural Experiment Station at Temple, TX. There I also developed a completely new growth model for winter and spring wheat, TAMW. During the 1980's, I pioneered the development of "within-season calibration", a technique for incorporating infrequent remote sensing observations into crop growth model simulations. This technique was used in a model for the grain crops called GRAMI, and later in a model of regional biomass and evaporation called ProBE. This calibration technique has been adopted by modelers around the world. In more recent years, I have been involved in modeling the interaction of light with the crop leaf canopy, and building submodels that will allow crop growth models to directly simulate the scene reflectance observed by remote sensing systems.
Remote Sensing. I began working in remote sensing when I joined the USDA-ARS laboratory at Weslaco, TX, in 1984. There, I was primarily interested in quantifying plant characteristics such as leaf area index using remote sensing, and developing methods of incorporating remote sensing information into crop growth models. After joining the USDA-ARS lab at Shafter, CA, I became more involved in detecting water stress and insect-related damage in crops using high-resolution airborne imagery. While at Shafter, I led the development of the Shafter Airborne Multispectral Remote Sensing System (SAMRSS, see the picture below), a system for obtaining high-resolution multispectral (visible, near-infrared, and thermal) remote sensing imagery from a light aircraft. This system has been used in many of the precision agriculture studies that I conducted in the Shafter area prior to coming to Texas Tech. More recently, I have been involved in modeling the interaction of light with the plant canopy to allow correction of remote sensing imagery for features such as bi-directional reflectance. Work has been completed on TTAMRSS, a multispectral airborne remote sensing system similar to SAMRSS for use in precision agriculture studies in the Texas High Plains.
Crop Yield Estimation. For most of my professional career, I have been involved in various aspects of crop yield estimation. The crop models that I have worked on, including SORGF, TAMW, and GRAMI, have been aimed at simulating crop growth and yield on the field and regional level. During the early 1980's, I spent time at the Statistical Reporting Service of USDA in Washington, DC, investigating the application of weather data and crop models to regional yield prediction. As a result of my work in developing the "within-season calibration" procedure described above, I developed specialized versions of the GRAMI model for the Foreign Agricultural Service of USDA for use in estimating foreign crop production. At Texas Tech, I am currently leading a cooperative research effort to use this crop yield estimation technology in an Internet-based system ("YieldTracker") to deliver within-season yield predictions to farmers based on weather and remote sensing data.
Precision Farming. Many of my efforts since the mid-1990's have been involved in applications of remote sensing or crop models to precision farming. At the USDA-ARS lab at Shafter, CA, I concentrated on the two crop management topics most important to cotton farmers in the Central Valley of California: irrigation and pest management. I served as a site leader for a large cooperative project involving USDA-ARS and a private company (Resource21 of Englewood, CO) aimed at developing remote sensing products for precision farming applications. Prior to joining Texas Tech, I served as the USDA coordinator for a large project on a farm in Central California, as part of the joint USDA-NASA Ag20/20 program. The objective of this program is to develop and test new technologies (remote sensing, GPS, and GIS) for farm management. At Texas Tech, I currently cooperate with colleagues from the Texas Agricultural Experiment Station in the Texas High Plains Precision Agriculture Project. With Supprt fron Cotton Inc, the National Cotton Council, and the International Cotton Research Center, I have been cooperating with farmers in the Lubbock area in collecting field data and developing procedures for precision agriculture. A good example is the development and adoption of a remote sensing-based method of variable-rate application of plant growth regulator to cotton.
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