Comparison of two simulation-based methods for modeling plant growth

HortScience

Volumn 31, Issue 1, 1996, Pages 25-28

  Hopper, Douglas A ^a   Hammer, P Allen ^b   Wilson, James R ^c  

^a Department of Environmental and Radiological Health Sciences   (United States)

^b PURDUE UNIVERSITY   (United States)

^c North Carolina State University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 0030052302     PISSN: 00185345     EISSN: None     Source Type: Journal    
DOI: 10.21273/hortsci.31.1.25     Document Type: Review

References (10)

1. Avramidis, A.N. and J.R. Wilson. 1994. A flexible method for estimating inverse distribution functions in simulation experiments. ORSA J. Computing 6:342-355.
2. Conte, S.D. and C. de Boor. 1980. Elementary numerical analysis: An algorithmic approach. 3rd ed. McGraw-Hill, New York.
3. de Wit, C.T. and J. Goudriaan. 1978. Simulation of ecological processes. 2nd ed. Wiley, New York.
4. Draper, N.R. and H. Smith. 1981. Applied regression analysis. 2nd ed. Wiley. New York.
5. Hopper, D.A. and P.A. Hammer. 1991. Regression models describing Rosa hybrida L. response to day/night temperature and photosynthetic photon flux. J. Amer. Soc. Hort. Sci. 116:609-617.
6. Hopper, D.A., P.A. Hammer, and J.R. Wilson. 1994. A simulation model of Rosa hybrida growth response to constant irradiance and day and night temperatures. J. Amer. Soc. Hort. Sci. 119:903-914.
7. Hora, S.C. 1983. Estimation of the inverse function for random variate generation. Communications Assn. Computing Machinery 26:590-594.
8. Nelder, J. A. 1961. The fitting of a generalization of the logistic curve. Biometrics 17:89-110.
9. Richards, F.J. 1959. A flexible growth function for empirical use. J. Expt. Bot. 10:290-300.
10. Richards, F.J. 1969. The quantitative analysis of growth, p. 3-76. In: F.C Steward (ed.). Plant physiology: A treatise. vol. VA. An analysis of growth: Behavior of plants and their organs. Academic, New York.