Timing of precision agriculture technology adoption in US cotton production

Precision Agriculture

Volumn 15, Issue 4, 2014, Pages 427-446

  Watcharaanantapong, Pattarawan ^a   Roberts, Roland K ^a   Lambert, Dayton M ^a   Larson, James A ^a   Velandia, Margarita ^a   English, Burton C ^a   Rejesus, Roderick M ^b   Wang, Chenggang ^c  

^a UNIVERSITY OF TENNESSEE   (United States)

^b NORTH CAROLINA STATE UNIVERSITY   (United States)

^c TEXAS TECH UNIVERSITY   (United States)

Author keywords

Grid soil sampling; Multivariate Tobit; Precision agriculture; Remote sensing; Timing of adoption; Yield monitors

Indexed keywords

GOSSYPIUM HIRSUTUM;

EID: 84917741211     PISSN: 13852256     EISSN: 15731618     Source Type: Journal    
DOI: 10.1007/s11119-013-9338-1     Document Type: Article

References (58)

1. Aerospace Corporation. (2013). Aerospace's work. The Aerospace Corporation. http://www.aerospace.org/ about-us/history/aerospaces-work. Accessed June 8, 2013.
2. Amemiya, T. (1974). Multivariate regression and simultaneous equation models when the dependent variables are truncated normal. Econometrica, 42, 999-1012.
3. Anastasopoulos, P., Shankar, V., Haddock, J., & Mannering, F. (2012). A multivariate Tobit analysis of highway accident-injury-severity rates. Accident Analysis and Prevention, 45(1), 110-119.
4. Batte, M. T., Jones, E., & Schnitkey, G. D. (1990). Computer use by Ohio commercial farmers. American Journal of Agricultural Economics, 72, 935-945.
5. Bretches, K. (2001). Uncleaned in three years, UT cotton yield monitor lets the light shine. The Light Touch. http://milan.tennessee.edu/research/cotyield.pdf. Accessed June 6, 2013.
6. Clemson University. (2013). Evaluation of cotton yield monitors. http://www.clemson.edu/precisionag/ cotton%20yield%20monit.htm. Accessed June 6, 2013.
7. Cordell, M. L., Robertson, W. C., & Groves, F. E. (2004). Evaluation of yield monitors for on-farm cotton variety testing. In Summaries of Arkansas cotton research 2004 (pp. 238-240). AAES Research Series 533. http://arkansasagnews.uark.edu/533-45.pdf. Accessed June 6, 2013.
8. Cornick, J., Cox, T. L., & Gould, B. W. (1994). Fluid milk purchases: A multivariate Tobit analysis. American Journal of Agricultural Economics, 76(1), 74-82.
9. Daberkow, S. G., & McBride, W. D. (2003). Farm and operator characteristics affecting the awareness and adoption of precision agriculture technologies in the US. Precision Agriculture, 4, 163-177.
10. DigitalGlobal. (2013). Satellite information. http://www.digitalglobe.com/resources/satellite-information. Accessed October 24, 2013.
11. Durrence, J. S., Thomas, D. L., Perry, C. D., & Vellidis, G. (1999). Preliminary evaluation of commercial cotton yield monitors: The 1998 season in South Georgia. In P. Dugger & D. Richter (Eds.), Proceedings 1999 beltwide cotton conferences (pp. 366-372). Memphis, TN: National Cotton Council of America.
12. Fernandez-Cornejo, J., Beach, E. D., & Huang, W. Y. (1994). The adoption of IPM technologies by vegetable growers in Florida, Michigan, and Texas. Journal of Agricultural and Applied Economics, 26, 158-172.
13. Fountas, S., Blackmore, S., Ess, D., Hawkins, S., Blumhoff, G., Lowenberg-DeBoer, J., et al. (2005). Farmer experience with precision agriculture in Denmark and the US Eastern Corn Belt. Precision Agriculture, 6, 121-141.
14. Gaudry, M. J. I., & Blum, U. (1988). An example of correlation among residuals in directly ordered data. Economic Letters, 26, 335-340.
15. Greene, W. H. (2012). Econometric analysis (7th ed.). Upper Saddle River, NJ: Prentice Hall.
16. Griliches, Z. (1957). Hybrid corn: An exploration of the economics of technological change. Econometrica, 25(4), 501-522.
17. Gujarati, D. (1995). Basic econometrics (3rd ed.). New York: McGraw Hill.
18. Harper, D. (2011). Soil test information in cotton production: Adoption, use, and value in potassium management. M.S. thesis, The University of Tennessee, Knoxville, TN.
19. InTime. (2013). InTime: Making precision pay. http://www.gointime.com/index.jsp. Accessed March 1, 2013.
20. Isgin, T., Bilgic, A. D., Forster, L., & Batte, M. T. (2008). Using count data models to determine the factors affecting farmers' quantity decisions of precision farming technology adoption. Computers and Electronics in Agriculture, 62(2), 231-242.
21. Kaiser, U. (2003). Strategic complementarities between different types of ICT expenditures. The open access publication server of the ZBW-Leibniz Information Centre for Economics, ZEW Discussion Paper No. 03-46. http://hdl.handle.net/10419/23981. Accessed July 12, 2013.
22. Khanna, M. (2001). Sequential adoption of site-specific technologies and its implications for nitrogen productivity: A double selectivity model. American Journal of Agricultural Economics, 83, 35-51.
23. Kuhlgatz, C., Abdulai, A., & Barrett, C. B. (2010). Food aid allocation policies: Coordination and responsiveness to recipient country needs. Agricultural Economics, 41(3-4), 319-327.
24. Larkin, S. L., Perruso, L., Marra, M. C., Roberts, R. K., English, B. C., Larson, J. A., et al. (2005). Factors affecting perceived improvements in environmental quality from precision farming. Journal of Agricultural and Applied Economics, 37, 577-588.
25. Larson, J. A., Roberts, R. K., English, B. C., Cochran, R. L., & Wilson, B. S. (2005). A computer decision aid for the cotton yield monitor investment decision. Computers and Electronics in Agriculture, 48, 216-234.
26. Larson, J. A., Roberts, R. K., English, B. C., Larkin, S. L., Marra, M. C., Martin, S. W., et al. (2008). Factors influencing the adoption of remotely sensed imagery for site specific management in cotton production. Precision Agriculture, 9, 195-208.
27. Larson, J. A., Roberts, R. K., English, B. C., Parker, J., & Sharp, T. (2004). A case study economic analysis of a precision farming system for cotton. In P. Dugger & D. Richter (Eds.), Proceedings 2004 beltwide cotton conferences (pp. 539-542). Memphis, TN: National Cotton Council of America.
28. Leamer, E. E. (1983). Let's take the con out of econometrics. The American Economic Review, 73, 31-43.
29. Li, Z. L. (2007). Digital map generalization at the age of enlightenment: A review of the first forty years. The Cartographic Journal, 44, 80-93.
30. Linsley, C. M., & Bauer, F. C. (1929). Test your soil for acidity. Circular 346. Urbana, IL: University of Illinois, Agricultural Experiment Station.
31. Lowenber-DeBoer, J. (1999). Risk management potential of precision farming technologies. Journal of Agricultural and Applied Economics, 31, 275-285.
32. Maddala, G. S. (1988). Introduction to econometrics. New York: Macmillan.
33. Mansfield, E. R., & Helms, B. P. (1982). Detecting multicollinearity. American Statisticians, 36(3), 158-160.
34. Mooney, D. F., Roberts, R. K., English, B. C., Lambert, D. M., Larson, J. A., Velandia, M., et al. (2010). Precision farming by cotton producers in twelve southern states: Results from the 2009 southern cotton precision farming survey. Research Report 10-02. Department of Agricultural and Resource Economics, The University of Tennessee, Knoxville.
35. Nair, S., Wang, C., Segarra, E., Johnson, J., & Rejesus, R. (2012). Variable rate technology and cotton yield response in Texas. Journal of Agricultural Science and Technology B, 2, 1034-1043.
36. National Research Council. (1997). Precision agriculture in the 21st century: Geospatial and information technologies in crop management. Washington, DC: National Academy Press.
37. Neter, J., Wasserman, W., & Kutner,M. (1985). Applied linear statistical models (2nd ed.). IL: Richard Irwin.
38. Rejesus, R. M., Marra, M. C., Roberts, R. K., English, B. C., Larson, J. A., & Paxton, K. W. (2013). Changes in producers' perceptions of within-filed yield variability after adoption of cotton yield monitors. Journal of Agricultural and Applied Economics, 45, 295-312.
39. Roades, J. P., Beck, A. D., & Searcy, S. W. (2000). Cotton yield mapping: Texas experiences in 1999. In P. Dugger & D. Richter (Eds.), Proceedings 2000 beltwide cotton conferences (pp. 404-407). Memphis, TN: National Cotton Council of America.
40. Roberts, R. K., English, B. C., Larson, J. A., Cochran, R. L., Goodman, W. R., Larkin, S. L., et al. (2004). Adoption of site-specific information and variable rate technologies in cotton precision farming. Journal of Agricultural and Resource Economics, 36, 143-158.
41. Rogers, E. M. (1983). Diffusion of innovations (3rd ed.). New York: Free Press.
42. SAS Institute. (2013). SAS/ETS_ 12.1 user's guide. Cary, NC: SAS Institute.
43. Schimmelpfennig, D., & Ebel, R. (2011). On the doorstep of the information age: Recent adoption of precision agriculture. US Department of Agriculture, Economic Research Service, Economic Information Bulletin No. 80.
44. Soil Conservation Service. (1981). Statutory authorities for the activities of the US Department of Agriculture, Soil Conservation Service. Agricultural handbook no. 588. Washington, DC: US Government Printing Office.
45. Swinton, S. M., & Lowenberg-DeBoer, J. (2001). Global adoption of precision agriculture technologies: Who, when and why? In G. Grenier and S. Blackmore (Eds.), Precision agriculture 2001: Proceedings of the 3rd European conference on precision agriculture (pp. 557-562). Montpellier, France.
46. Tenkorang, F., & Lowenberg-DeBoer, J. (2008). On-farm profitability of remote sensing in agriculture. Journal of Terrestrial Observation, 1(1), 50-59.
47. Tobin, J. (1958). Estimation of relationships for limited dependent variables. Econometrica, 26(1), 24-36.
48. Torbett, J. C., Roberts, R. K., Larson, J. A., & English, B. C. (2007). Perceived importance of precision farming technologies in improving phosphorous and potassium efficiency in cotton production. Precision Agriculture, 8, 127-137.
49. Torbett, J. C., Roberts, R. K., Larson, J. A., & English, B. C. (2008). Perceived improvements in nitrogen fertilizer efficiency from cotton precision farming. Computers and Electronics in Agriculture, 64, 140-148.
50. US Department of Agriculture (USDA). (2007). 2007 census of agriculture. Washington, DC: National Agricultural Statistics Service, US Department of Agriculture.
51. US Department of Agriculture (USDA) Economic Research Service (ERS). (2007). 2010 agricultural resource management survey farm financial and crop production practice. Washington, DC: National Agricultural Statistics Service, US Department of Agriculture. http://www.ers.usda.gov/data-products/ arms-farm-financial-and-crop-production-practices.aspx. Accessed July 12, 2013.
52. US Department of Agriculture (USDA) Economic Research Service (ERS). (2010). 2010 agricultural resource management survey farm financial and crop production practice. Washington, DC: US Department of Agriculture. http://www.ers.usda.gov/data-products/arms-farm-financial-and-cropproduction- practices.aspx. Accessed July 12, 2013.
53. Velandia, M., Lambert, D. M., Jenkins, A., Roberts, R. K., Larson, J. A., English, B. C., et al. (2010). Precision farming information sources used by cotton farmers and implications for extension. Journal of Extension, 48(5), 1-7.
54. Walton, J. C., Lambert, D. M., Roberts, R. K., Larson, J. A., English, B. C., Larkin, S. L., et al. (2008). Adoption and abandonment of precision soil sampling in cotton production. Journal of Agricultural and Resource Economics, 33(3), 428-448.
55. Walton, J. C., Larson, J. A., Roberts, R. K., Lambert, D. M., English, B. C., Larkin, S. L., et al. (2010a). Factors influencing farmer adoption of portable computers for site-specific management: A case study for cotton production. Journal of Agricultural and Applied Economics, 42(2), 192-209.
56. Walton, J. C., Roberts, R. K., Lambert, D. M., Larson, J. A., English, B. C., Larkin, S. L., et al. (2010b). Grid soil sampling adoption and abandonment in cotton production. Precision Agriculture, 11, 135-147.
57. Wolak, F. J., Khalilian, A., Dodd, R. B., Han, Y. J., Keshkin, M., Lippert, R. M., et al. (1999). Cotton yield monitor evaluation, South Carolina-Year 2. In P. Dugger & D. Tichter (Eds.), Proceedings 1999 beltwide cotton conference (pp. 361-364). Memphis, TN: National Cotton Council of America.
58. Wooldridge, J. M. (2003). Introductory econometrics: A modern approach. Cincinnati, OH: South-Western College.