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PRECISION AGRICULTURE INITIATIVE FOR TEXAS HIGH PLAINS
2001 ANNUAL COMPREHENSIVE REPORT
Texas Agricultural Experiment Station and Texas Agricultural Extension Service
Principal Investigator:
Eduardo Segarra, Agricultural and Applied Economist, TAES-Lubbock, Texas A&M University and Department of Agricultural and Applied Economics, Texas Tech University. E-mail address: eduardo.segarra@ttu.edu. Physical address: Texas A&M University Research and Extension Center, Route 3, Box 219, Lubbock, Texas 79403.
Cooperators:
Robert Lascano, Tom Archer, Steve Searcy, James Bordovsky, Kevin F. Bronson, Terry Wheeler, L. Ted Wilson, and Michael Shubert – Texas Agricultural Experiment Station, Texas A&M University.
Project Title:
Precision Farming - Site Specific Production Systems: Economics of Precision Farming Practices in the Texas High Plains (cotton, grain sorghum, corn, and peanuts).
Project Objective:
The overall objective of this project is to derive precision farming optimal decision rules of input use and evaluate the economic impacts of precision farming practices in cotton, grain sorghum, corn, and peanut production in the Texas High Plains.
Reporting Period: January 1, 2001 - December, 2001.
A. Summary of Progress:
Widespread utilization of fertilizers, pesticides, and other chemicals have significantly contributed to the enhancement of agriculture’s productivity in recent decades. Currently, production agriculture is facing many challenges such as increasing cost of production, shortage of irrigation water, and increased public concern on the impacts of agricultural production on the environment. To survive in the highly competitive world market of agricultural commodities, agricultural producers must produce high quality products at low prices while using environmentally sound practices. A way to address these issues is to adopt precision farming technology. Traditionally, input use in crop production has assumed field homogeneity with respect to soil fertility, soil moisture, pest populations, and crop characteristics. That is, optimal decision rules of input use do not account for differences of those characteristics within fields. Precision farming, precision agriculture, or site-specific management recognizes the variability of such factors within fields and seeks to optimize variable input use under these conditions. Precision farming is an advanced information-technology-based management system designed to identify, analyze and manage site-soil spatial and temporal variability within fields for optimum profitability, sustainability, and/or protection of the environment. The development of precision farming practices is closely related to the many new technologies that have been utilized in agricultural production in recent years. These new technologies involve microcomputers, microprocessor based control systems, satellite positioning technologies, and many kinds of sensors. With the help of these technologies, variable rate application of fertilizers and spraying of weeds, spatial soil testing, and yield mapping are becoming available. The overall objective of this project is to derive precision farming optimal decision rules of input use (irrigation water, fertilizers, herbicides and insecticides) and evaluate the economic impacts of precision farming practices in cotton, grain sorghum, corn, and peanut production in the Texas High Plains.
The general approach followed in the derivation of precision farming economically optimal decision rules of input use of all the crops analyzed has been as follows. First, statistical estimation of site specific production functions are derived to evaluate spatial crop responses across a specific field. In some cases equations of motion related to the dynamics associated with the spatial nature of soil fertility and residual levels of nitrate have also been estimated. Once these functions are estimated, either static of dynamic mathematical optimization models are formulated to derive site-specific precision farming optimal decision rules of input use under alternative input and output price scenarios. Then, these decision rules and their associated levels of economic profitability are compared to those that would have been obtained under conventional (i.e., “average”) production practices. Sophisticated mapping computer software such as MapInfo and Vertical Mapper are then used to graphically depict the results obtained. These mapping procedures facilitate the visualization of results and clearly convey the spatial details of what, within the field being analyzed, specific locations are the most or least profitable.
Precision farming optimal decision rules of input use have been derived for cotton, grain sorghum, peanuts, and corn production. Overall, these results indicate that: (1) precision farming practices have the potential to be economically beneficial as compared to conventional practices, but widespread use of these practices will critically dependent on their adoption cost; (2) the economic benefits of precision farming practices are not evenly distributed across fields - in fact, we have found that spatial variability of both yields and profits across fields are magnified under precision farming practices as compared to conventional production practices; and (3) precision farming can effectively be used to identify “management zones” within fields where the potential for significant improvements in profits are possible. This research could have significant impacts on well over 5.0 million acres of cropland in the production of corn, grain sorghum, peanuts and cotton in the Texas High Plains.
B. Educational/technology transfer:
Several presentations addressing the economics of precision farming production practices have been made to varied audiences. The overall message conveyed has been: precision farming can be economically enhancing for producers in the Texas High Plains, if adoption costs are reasonably low. Depending on the specific location, the crop being analyzed, and input and output price scenarios, net increases of profits of 2 to 5 percent per acre could be expected from the adoption of precision farming practices. However, there could be specific zones within crop fields where net increases in profits could be significantly higher. Also, precision farming practices could contribute to the “improved placement” of chemicals on fields, and thus reduce the potential for environmental degradation from chemical use in agriculture.
C. Milestones achieved:
The most significant milestone achieved to date has been the establishment of a sound methodology to derive optimal decision rules of input use under precision farming practices.
D. Publications:
Machado, S., E. D. Bynum, Jr., T. L. Archer, R. J. Lascano, L. T. Wilson, J. Bordovsky, E. Segarra, K. Bronson, D. M. Smith,and W. Xu. 2001. Spatial and Temporal Variability of Corn Growth and Grain Yield: Implications for Site Specific Farming. Crop Science, in press.
Li, H., R. J. Lascano, J. Booker, L. T. Wilson, and E. Segarra. 2001. State-Space Description of Underlying Field Heterogeneity on Water and Nitrogen Use in Cotton. Soil Science Society of America Journal, in press.
Machado, S., E. D. Bynum, Jr., T. L. Archer, R. J. Lascano, L. T. Wilson, J. Bordovsky, E. Segarra, K. Bronson, D. M. Nesmith, and W. Xu. 2001. Spatial and Temporal Variability of Sorghum Grain Yield: Influence of Soil, Water, Pests, and Diseases Relationships. Precision Agriculture, in press.
Li, H., R. J. Lascano, E. M. Barnes, J. Booker, L. T. Wilson, K. F. Bronson, and E. Segarra. 2001. Multispectral Reflectance of Cotton Related to Plant Growth, Soil Water and Texture, and Site Elevation. Agronomy Journal, 93(6): 1327-1337.
Arabiyat, T. S., E. Segarra, and J. L. Johnson. 2001. Technology Adoption in Agriculture: Implications for Ground Water Conservation in the Texas High Plains. Resources, Conservation and Recycling, 32(2001): 147-156.
Li, H., R. J. Lascano, L. T. Wilson, and E. Segarra. 2001. Semivariance and Crosscorrelation of Sand, Water, Cotton Canopy Temperature, and Plant Reflectance in the Landscape. Proceedings of the 3rd European Conference in Precision Agriculture, pp. 241-245, Vol. 1.
Yu, M., E. Segarra, S. Watson, H. Li, and R. J. Lascano. 2001. Precision Farming Practices in Irrigated Cotton Production in the Texas High Plains. Proceedings of the 2001 Beltwide Cotton Conferences, pp. 201-208.
Li, H., R. J. Lascano, J. Booker, L. T. Wilson, E. Segarra, and K. F. Bronson. 2001. Using a Topographic Factor to Explain Soil and Cotton Lint Variability in the Landscape. Proceedings of the 2001 Beltwide Cotton Conferences, pp. 585-588.
Li, H., R. J. Lascano, E. M. Barnes, J. Booker, L. T. Wilson, K. F. Bronson, and E. Segarra. 2001. Temporal Patterns of Cotton Reflectance and NDVI-Days Lint Yield Modeling. Proceedings of the 2001 Beltwide Cotton Conferences, pp. 590-594.
Li, H., R. J. Lascano, J. Booker, L. T. Wilson, K. F. Bronson, and E. Segarra. 2001. Identification of Factors Affecting Cotton Spectral Reflectance Variability Using Principal Component Analysis. Abstract in Proceedings of the 2001 ASA, CSSA, and SSSA Annual Meetings, S01-li203926-O - CD-Rom.
Li, H., R. J. Lascano, J. Booker, L. T. Wilson, K. F. Bronson, and E. Segarra. 2001. Autoregressive Analysis of Spatial Association of Cotton Nitrogen Uptake with Soil Water and Landscape Position. Abstract in Proceedings of the 2001 ASA, CSSA, and SSSA Annual Meetings, S01-li201429-P - CD-Rom.
Watson, S., E. Segarra, M. Yu, E. Bynum, S. Machado, T. Archer, and L. T. Wilson. 2001. The Economics of Precision Farming in Grain Sorghum. Abstract in Journal of Agricultural and Applied Economics, 33(3): 627.
Yu, M., and E. Segarra. 2001. Economic Impacts of Precision Farming in Cotton Production. Abstract in Journal of Agricultural and Applied Economics, 33(3): 626-627.
E. Precision agriculture proposals:
Principal investigator (this project). Site Specific Production Systems: Economics of Precision Farming Practices in the Texas High Plains (cotton, grain sorghum, corn, and peanuts). Precision Agriculture Initiative - Texas A&M University. September 2001 - August 2002. Amount requested $28,333 - funded.
Cooperator with S. J. Maas, D. R. Krieg, and R. J. Lascano. Precision Agriculture Systems and Strategies for the Semiarid Southern Plains. Submitted to USDA’s NRI - Application of Geospatial and Precision Technologies Program. Amount requested $1,254,670 - not funded.
F. Precision agriculture meetings attended/papers (posters) presented:
Li, H., R. J. Lascano, L. T. Wilson, and E. Segarra. 2001. Semivariance and Crosscorrelation of Sand, Water, Cotton Canopy Temperature, and Plant Reflectance in the Landscape. Selected for presentation at the 3rd European Conference in Precision Agriculture, June 13-21, Montpellier, France.
Yu, M., E. Segarra, S. Watson, H. Li, and R. J. Lascano. 2001. Precision Farming Practices in Irrigated Cotton Production in the Texas High Plains. Selected for presentation, 2001 Beltwide Cotton Conferences. Co-sponsored by the National Cotton Council and the Cotton Foundation, January 9-13, Anaheim, California.
Li, H., R. J. Lascano, J. Booker, L. T. Wilson, E. Segarra, and K. F. Bronson. 2001. Using a Topographic Factor to Explain Soil and Cotton Lint Variability in the Landscape. Selected for presentation, 2001 Beltwide Cotton Conferences. Co-sponsored by the National Cotton Council and the Cotton Foundation, January 9-13, Anaheim, California.
Li, H., R. J. Lascano, E. M. Barnes, J. Booker, L. T. Wilson, K. F. Bronson, and E. Segarra. 2001. Temporal Patterns of Cotton Reflectance and NDVI-Days Lint Yield Modeling. Selected for presentation, 2001 Beltwide Cotton Conferences. Co-sponsored by the National Cotton Council and the Cotton Foundation, January 9-13, Anaheim, California.
Li, H., R. J. Lascano, J. Booker, L. T. Wilson, K. F. Bronson, and E. Segarra. 2001. Identification of Factors Affecting Cotton Spectral Reflectance Variability Using Principal Component Analysis. Selected for presentation at the 2001 ASA, CSSA, and SSSA Annual Meetings, October 21-25, 2001, Charlotte, North Carolina.
Li, H., R. J. Lascano, J. Booker, L. T. Wilson, K. F. Bronson, and E. Segarra. 2001. Autoregressive Analysis of Spatial Association of Cotton Nitrogen Uptake with Soil Water and Landscape Position. Selected for presentation at the 2001 ASA, CSSA, and SSSA Annual Meetings, October 21-25, 2001, Charlotte, North Carolina.
Watson, S., E. Segarra, M. Yu, E. Bynum, S. Machado, T. Archer, and L. T. Wilson. 2001. The Economics of Precision Farming in Grain Sorghum. Selected for presentation at the annual meeting of the Southern Agricultural Economics Association, January 27-31, Fort Worth, Texas.
Yu, M., and E. Segarra. 2001. Economic Impacts of Precision Farming in Cotton Production. Selected for presentation at the annual meeting of the Southern Agricultural Economics Association, January 27-31, Fort Worth, Texas.
G. Other developments: None.