Browsing by Subject "precision agriculture"
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Item Extending the utility of machine based height sensors to spatially monitor cotton growth(Texas A&M University, 2004-09-30) Geiger, David WilliamThe recommended procedures for implementing COTMAN; a cotton management expert system; suggest frequent crop scouting at numerous locations for each field. Machine based height sensors coupled with the ability to spatially record height values make it possible to locate regions of a field that are height representative of the entire field. A machine based height measurement system called HMAP was used to assess plant height in various fields in the 2003 growing season while the same fields were monitored with COTMAN. The plant height data was used to determine an optimal COTMAN sampling scheme for each field consisting of significantly fewer sampling locations than recommended by COTMAN. It was possible to ascertain equivalent information from COTMAN using two sites selected from height data in place of six sites selected per COTMAN recommendations. The HMAP system was extended to monitor rate of growth in real time in addition to plant height by comparing historical plant height data recorded on previous field passes to current height values. The rate of growth capable HMAP system will make it possible to track cotton growth and development with an automated system.Item Factors determining the adoption or non-adoption of precision agriculture by producers across the cotton belt(Texas A&M University, 2006-04-12) Lavergne, Christopher BernardThe purpose of this study was to determine factors influencing cotton producer adoption of Precision Agriculture in the cotton belt according to members of the American Cotton Producers of the National Cotton Council. The National Research Council??s Board on Agriculture defines Precision Agriculture (PA) as ??a management strategy that uses information technologies to bring data from multiple sources to bear on decisions associated with crop production.?? For the purpose of this study, Precision Agriculture technologies included yield monitors, global positioning units, variable rate applicators, and similar components. Many studies have found that adoption of Precision Agriculture can be profitable for agricultural producers. However, the fact that Precision Agriculture is relatively new and unproven hinders rapid adoption by agricultural producers. According to the National Research Council Board of Agriculture widespread adoption relies on economic gains outweighing the costs of the technology. This study attempted to find the factors associated with adoption of these technologies in the cotton belt. The sample population consisted of cotton producer representatives from the leading cotton-producing states. A Delphi approach was utilized to establish a consensus of cotton producer perceptions of the advantages of adopting Precision Agriculture technologies. Advantages included more accurate farming (i.e., row spacing, reduced overlap, and cultivation). Barriers to adoption were also documented, questioning employee capability to operate equipment, learning curve, technology complexity, and uncertain return on investment.Item Site-specific strategies for cotton management(Texas A&M University, 2005-08-29) Stabile, Marcelo de Castro ChavesThe use of site-specific data can enhance management decisions in the field. Three different uses of site-specific data were evaluated and their outcomes are promising. Historical yield data from yield monitors and height data from the HMAP (plant height mapping) system were used to select representative areas within the field, and areas of average conditions were used as sampling sites for COTMAN, a cotton management expert system. This proved to be effective, with predicted cutout dates and date of peak nodal development similar to the standard COTMAN approach. The HMAP system was combined with historical height data for variable rate application of mepiquat chloride, based on the plant growth rate. The system performance was evaluated, but weather conditions in 2004 did not allow a true evaluation of varying mepiquat chloride. A series of multi-spectral images were normalized utilizing the soil line transformation (SLT) technique and normalized difference vegetation index (NDVI) was calculated from the transformed images, from the raw image and for the true reflectance images. The SLT technique was effective in tracking the change in true reflectance NDVI in some images, but not all. Changes to the soil line extraction program are suggested so that it more effectively determines soil lines.