Applying glue for estimating ceres-maize genetic and soil parameters for sweet corn production

Transactions of the ASABE

Volumn 52, Issue 6, 2009, Pages 1907-1921

  He, Jianqiang ^a   Dukes, Michael D ^a   Jones, James W ^a   Graham, Wendy D ^b   Judge, Jasmeet ^a  

^a J Crayton Pruitt Family Department of Biomedical Engineering   (United States)

^b UNIVERSITY OF FLORIDA   (United States)

Author keywords

CERES Maize; Crop model; DSSAT; Generalized likelihood uncertainty estimation; GLUE; Parameter estimation; Sweet corn

Indexed keywords

AGROTECHNOLOGY TRANSFER; AVERAGE RELATIVE ERROR; CORN GENOTYPES; CROP MODEL; CROP SIMULATION MODEL; CV VALUE; DATA SETS; DRY MATTER YIELD; DSSAT; ESTIMATED PARAMETER; FIELD DATA; FLORIDA; GENERALIZED LIKELIHOOD UNCERTAINTY ESTIMATION; GLUE PROCEDURE; GROWTH SEASON; INDEPENDENT MEASUREMENT; MANAGEMENT PRACTICES; MEAN VALUES; MODEL PARAMETERS; MULTIVARIATE NORMAL DISTRIBUTIONS; NITROGEN LEACHING; POSTERIOR DISTRIBUTIONS; PRIOR DISTRIBUTION; RELATIVE ERRORS; SOIL PARAMETERS; SOIL WATER; SOIL WATER CONTENT; SWEET CORNS; TEMPORAL TRENDS; UNIFORM DISTRIBUTION; VEGETABLE CROPS;

ARTIFICIAL INTELLIGENCE; CROPS; DECISION MAKING; DECISION SUPPORT SYSTEMS; DECISION THEORY; GEOLOGIC MODELS; GLUES; GLUING; LEACHING; NITROGEN; NITROGEN FERTILIZERS; NORMAL DISTRIBUTION; PROFITABILITY; SOIL MOISTURE; SOIL SURVEYS; TIME SERIES; UNCERTAINTY ANALYSIS; UNDERWATER SOILS; WATER CONTENT; WOOLEN AND WORSTED YARN;

PARAMETER ESTIMATION;

AGRICULTURAL MODELING; AGRICULTURAL SOIL; AGRICULTURAL TECHNOLOGY; CROP PRODUCTION; DECISION MAKING; DECISION SUPPORT SYSTEM; FERTILIZER APPLICATION; GENETIC ANALYSIS; LEACHING; MAIZE; NITROGEN; SOIL PROFILE; UNCERTAINTY ANALYSIS; VEGETABLE;

FLORIDA [UNITED STATES]; UNITED STATES;

CERES; ZEA MAYS;

EID: 76249128941     PISSN: 21510032     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (53)

1. Asadi, M. E., and R. S. Clemente. 2003. Evaluation of CERES-Maize of DSSAT model to simulate nitrate leaching, yield, and soil moisture content under tropical conditions. Food, Agric. and Environ. 1(3-4): 270-276.
2. Asadi, M. E., R. S. Clemente, A. D. Gupta, R. Loof, and G. K. Hansen. 2002. Impacts of fertigation via sprinkler irrigation on nitrate leaching and corn yield in an acid-sulfate soil in Thailand. Agric. Water Mgmt. 52(3): 197-213.
3. Beven, K. 1993. Prophecy, reality, and uncertainty in distributed hydrological modeling. Advances in Water Resources 16(1): 41-51.
4. Beven, K. 2001. Rainfall-Runoff Modelling: The Primer. New York, N.Y.: Wiley.
5. Beven, K., and A. Binley. 1992. The future of distributed models: Model calibration and uncertainty prediction. Hydrol. Proc. 6(3): 265-277.
6. Candela, A., L. V. Noto, and G. Aronica. 2005. Influence of surface roughness in hydrological response of semiarid catchments. J. Hydrol. 313(3-4): 119-131.
7. Casanova, J. J., J. Judge, and M. Y. Jang. 2006. Vertical distribution of moisture in a growing sweet corn canopy during MicroWEX-4. Circular No. 1492. Gainesville, Fla.: University of Florida, IFAS. Available at: http://edis.ifas.ufl.edu/AE395.
8. Casanova, J., F. Yan, J. Judge, K. J. Tien, L. W. Miller, and O. Lanni. 2007. Field observations during the fifth microwave, water, and energy balance experiment (MicroWEX-5): From March 9 through May 26, 2006. Circular No. 1514. Gainesville, Fla.: University of Florida, IFAS. Available at: http://edis.ifas.ufl.edu/AE407.
9. Conrad, Y., and N. Fohrer. 2009. Modeling of nitrogen leaching under a complex winter wheat and red clover crop rotation in a drained agricultural field. Physics and Chem. of the Earth 34(8-9): 530-540.
10. Florida. 1999. Florida statute 403.067: Establishment and implementation of total maximum daily loads. Tallahassee, Fla.: State of Florida.
11. FASS. 2002. 2000-2001 Vegetable acreage, production, and value. Orlando, Fla.: Florida Agricultural Statistics Service.
12. Gabrielle, B., and L. Kengni. 1996. Analysis and field evaluation of the CERES model's soil components: Nitrogen transfer and transformations. SSSA J. 60(1): 142-149.
13. He, J. 2008. Best management practice development with the CERES-Maize model for sweet corn production in north Florida. PhD diss. Gainesville, Fla.: University of Florida, Department of Agricultural and Biological Engineering.
14. He, J., J. W. Jones, W. D. Graham, and M. D. Dukes. 2009. Influences of different likelihood functions on parameter estimation with the generalized likelihood uncertainty estimation method. Agric. Systems (in review).
15. Hoogenboom, G., J. W. Jones, C. H. Porter, P. W. Wilkens, K. J. Boote, W. D. Batchelor, L. A. Hunt, and G. Y. Tsuji, eds. 2003. Vol.1: Overview. In Decision Support System for Agrotechnology Transfer. Version 4.0. Honolulu, Hawaii: University of Hawaii.
16. Jagtap, S. S., F. J. Abamu, and J. G. Kling. 1999. Long-term assessment of nitrogen and variety technologies on attainable maize yields in Nigeria using CERES-Maize. Agric. Systems 60(2): 77-86.
17. Jones, C. A., and J. R. Kiniry, eds. 1986. CERES-Maize: A Simulation Model of Maize Growth and Development. College Station, Tex.: Texas A&M University Press.
18. Jones, J., G. Hoogenboom, C. Porter, K. Boote, W. Batchelor, L. Hunt, P. Wilkens, U. Singh, A. Gijsman, and J. Ritchie. 2003. The DSSAT model cropping system model. European J. Agron. 18(3-4): 235-265.
19. Judge, G. G., R. C. Hill, W. E. Griffiths, H. Lutkepohl, and T. C. Lee. 1982. Introduction to the Theory and Practice of Economics. New York, N.Y.: Wiley.
20. Katyal, J. C., B. Singh, P. L. G. Vlek, and E. T. Grasweel. 1985. Fate and efficiency of nitrogen fertilizers applied to wetland rice: II. Punjab, India. Fertilizer Res. 6(3): 279-290.
21. Kiniry, J. R. 1991. Plant development: Maize. In Modeling Plant and Soil Systems, 55-70. J. T. Ritchie and R. J. Hanks, eds. ASA Monograph. Madison, Wisc.: ASA.
22. Kiniry, J. R., and R. Bonhomme. 1991. Predicting maize phenology. In Physiological Aspects of Predicting Crop Phenology, 115-131. T. Hodges, ed. Boca Raton, Fla.: CRC Press.
23. Klute, A.1986. Part 1: Physical and mineralogical methods. In Methods of Soil Analysis. 2nd ed. No.9 (Part 1) in the series. Madison, Wisc.: ASA, SSSA.
24. Lizaso, J. I., K. J. Boote, C. M. Cherr, J. J. Casanova, J. Judge, J. M. Scholberg, J. W. Jones, and G. Hoogenboom. 2007. Developing a sweet corn simulation model to predict fresh market yield and quality of ears. J. American Soc. Hort. Sci. 132(3): 415-422.
25. Makowski, D., D. Wallach, and M. Tremblay. 2002. Using a Bayesian approach to parameter estimation, comparison of the GLUE and MCMC methods. Agronomie 22(2): 191-203.
26. Makowski, D., J. Hillier, D. Wallach, and B. Andrieu. 2006. Parameter estimation for crop models. In Working with Dynamic Crop Models: Evaluation, Analysis, Parameterization, and Application, 101-103. D. Wallach, D. Makowski, and J. W. Jones, eds. Amsterdam, The Netherlands: Elsevier.
27. Matlab. 2004. Version 7.0.0. Natick, Mass.: The MathWorks, Inc.
28. Monteith, J. L. 1996. The quest for balance in crop modeling. Agron. J. 88(5): 695-697.
29. Morris, M. D. 1991. Factorial sampling plans for preliminary computational experiments. Technometrics 33(2): 161-174.
30. Page, A. L, E. H. Miller, and D. R. Keeney. 1982. Part 2: Chemical and microbiological properties. In Methods of Soil Analysis, 595 and 673. 2nd ed. Madison, Wisc.: ASA, SSSA.
31. Pang, X. P., J. Letey, and L. Wu. 1997a. Yield and nitrogen uptake prediction by CERES-Maize model under semiarid conditions. SSSA J. 61(1): 254-256.
32. Pang, X. P., J. Letey, and L. Wu. 1997b. Irrigation quantity and uniformity and nitrogen application effects on crop yield and nitrogen leaching. SSSA J. 61(1): 257-261.
33. Pang, X. P., S. C. Gupta, J. F. Moncrief, C. J. Rosen, and H. H. Cheng. 1998. Evaluation of nitrate leaching potential in Minnesota glacial outwash soils using the CERES-Maize model. J. Environ. Qual. 27(1): 75-85.
34. Poss, R., and H. Saragoni. 1992. Leaching of nitrate, calcium, and magnesium under maize cultivation on an oxisol in Togo. Fertil. Res. 33(2): 123-133.
35. Ratliff, L. F., J. T. Ritchie, and D. K. Cassel. 1983. Filed-measured limits of soil water availability as related to laboratory-measured properties. SSSA J. 47(4): 770-775.
36. Rinaldi, M., D. Ventrella, and C. Gagliano. 2007. Comparison of nitrogen and irrigation strategies in tomato using CROPGRO model: A case study from southern Italy. Agric. Water Mgmt. 87(1): 91-105.
37. Ritchie, J. T. 1998. Soil water balance and plant water stress. In Understanding Options for Agricultural Production, 41-54. G. Y. Tsuji, G. Hoogenboom, and P. K. Thornton, eds. Dordrecht, The Netherlands: Kluwer Academic.
38. Ritchie, J. T., and D. C. Godwin. 1989. Description of soil balance. In Modeling the Growth and Development of Sorghum and Pearl Millet, 14-16. S. M. Virnami, H. L. S. Tandon, and G. Alagarswamy, eds. Research bulletin 12. Pradesh, India: ICRISAT.
39. Ritchie, J. T., U. Singh, D. C. Godwin, and W. T. Bowen. 1998. Cereal growth, development, and yield. In Understanding Options for Agricultural Production, 79-98. G. Y. Tsuji, G. Hoogenboom, and P. K. Thornton, eds. Dordrecht. The Netherlands: Kluwer Academic.
40. Stedinger, J. R., R. M. Vogel, S. U. Lee, and R. Batchelder. 2008. Appraisal of the generalized likelihood uncertainty estimation (GLUE) method. Water Resources Res. 44: W00B06, doi:10.1029/2008WR006822.
41. Steele, D. D., E. C. Stegman, and B. L. Gregor. 1994. Field comparison of irrigation scheduling methods for corn. Trans. ASAE 37(4): 1197-1203.
42. Theocharopoulos, S. P., M. Karayianni, P. Gatzogiani, A. Afentaki, and S. Aggelides. 1993. Nitrogen leaching from soils in the Kopais area of Greece. Soil Use Mgmt. 9(2): 76-84.
43. Tsuji, G. Y., J. W. Jones, G. Hoogenboom, L. A. Hunt, and P. K. Thornton. 1994. Introduction. In DSSAT v3, Decision Support System for Agrotechnology Transfer, Vol.1. G. Tsuji, Y. Uehara, and G. S. Balas, eds. Honolulu, Hawaii: University of Hawaii.
44. USDA-ERS. 1993. Agricultural chemical usage: 1992 vegetables summary. Washington, D.C.: USDA Economic Research Service.
45. USDA-NASS. 1995. Agricultural chemical usage: Vegetable crop summary 1994. Washington, D.C.: USDA National Agricultural Statistics Service, Agricultural Statistics Board.
46. USDA-NASS. 1999. Agricultural chemical usage: Vegetables, 1998 summary. Washington, D.C.: USDA National Agricultural Statistics Service, Agricultural Statistics Board.
47. USDA-NASS. 2003. Agricultural chemical usage: Vegetables, 2002 summary. Washington, D.C.: USDA National Agricultural Statistics Service, Agricultural Statistics Board.
48. USDA-NASS. 2007. Agricultural chemical usage: Vegetables, 2006 summary. Washington, D.C.: USDA National Agricultural Statistics Service, Agricultural Statistics Board.
49. Wang, X., X. He, J. R. Williams, R. C. Izaurralde, and J. D. Atwood. 2005. Sensitivity and uncertainty analyses of crop yields and soil organic carbon simulated with EPIC. Trans. ASABE 48(3): 1041-1054.
50. Wolf, J., M. J. D. Hack-ten Broeke, and R. Rötter. 2005. Simulation of nitrogen leaching in sandy soils in The Netherlands with the ANIMO model and the integrated modeling system STONE. Agric. Ecosystems and Environ. 105(3): 523-540.
51. Wu, Y., C. M. Sakamoto, and D. M. Botner. 1989. On the application of the CERES-Maize model to the north China plain. Agric. and Forest Meteorology 49(1): 9-22.
52. Mertens, J., H. Madsen, L. Feyen, D. Jacques, and J. Feyen. 2004. Including prior information in the estimation of effective soil parameters in unsaturated zone modeling. J. Hydrol. 294(4): 251-269.
53. Olson, S. M., and E. Simonne. 2005. Vegetable production guide for Florida 2003-2004. Gainesville, Fla.: University of Florida, IFAS.