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Integrating Photosynthesis, Respiration, Biomass Partitioning, and Plant Growth: Developing a Microsoft Excel®-based Simulation Model of Wisconsin Fast Plant (Brassica rapa, Brassicaceae) Growth with Undergraduate Students

Published online by Cambridge University Press:  05 October 2011

Y. L. Grossman ,
A. B. Berdanier ,
M. L. Custic ,
L. R. Feeley ,
S. F. Peake ,
A. J. Saenz  and
K. S. Sitton
Y. L. Grossman*
Affiliation:
Department of Biology, Beloit College, Beloit, WI 53511, USA
A. B. Berdanier
Affiliation:
Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO 80523, USA
M. L. Custic
Affiliation:
Department of Biological Sciences, University of Illinois, Chicago, IL 60607, USA
L. R. Feeley
Affiliation:
Veterinary Technology Distance Learning Program, Purdue University, West Lafayette, IN 47907, USA
S. F. Peake
Affiliation:
Freeman School of Business, Tulane University, New Orleans, LA 70118, USA
A. J. Saenz
Affiliation:
Colegio de Educación Infantil y Primaria Doctor López Rosat, Valencia, 46018, SPAIN
K. S. Sitton
Affiliation:
Parker Junior High School, Flossmoor, IL 60422, USA
*
⋆Corresponding author. E-mail: [email protected]
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Abstract

This paper demonstrates the development of a simple model of carbon flow during plant growth. The model was developed by six undergraduate students and their instructor as a project in a plant ecophysiology course. The paper describes the structure of the model including the equations that were used to implement it in Excel®, the plant growth experiments that were conducted to obtain information for parameterizing and testing the model, model performance, student responses to the modeling project, and potential uses of the model by other students.

Keywords

carbon flowpartitioningphotosynthesisplant growthpotential relative growth raterespirationsimulation modelstudent learningWisconsin Fast Plants
Type
Research Article
Information
Mathematical Modelling of Natural Phenomena , Volume 6 , Issue 6: Biomathematics Education , 2011 , pp. 295 - 313
Copyright
© EDP Sciences, 2011

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References

American Association of Medical Colleges/Howard Hughes Medical Institute. Scientific foundations for future physicians. Washington, D.C., 2009.
J. S. Amthor. Respiration and crop productivity. Springer-Verlag, New York, New York, 1989.
Amthor, J. S. Cummings, J. R.. Low levels of ozone increase bean leaf maintenance respiration. Canadian Journal of Botany, 66 (1988), 724–726. CrossRefGoogle Scholar
Beedlow, P. A., Tingey, D. T., Phillips, D. L., Hogsett, W. E., Olszyk, D. M.. Rising atmospheric CO2 and carbon sequestration in forests. Frontiers in Ecology and the Environment, 2 (2004), 315–322. Google Scholar
Bloom, A. J., Chapin III, F. S., Mooney, H. A.. Resource limitation in plants–an economic analogy. Annual Review of Ecology and Systematics, 16 (1985), 363–392. CrossRefGoogle Scholar
Boehmel, C., Lewandowski, I., Claupein, W.. Comparing annual and perennial energy cropping systems with different management intensities. Agricultural Systems, 96 (2008), 224–236. CrossRefGoogle Scholar
Carlsson, B.. Ecological understanding 1: ways of experiencing photosynthesis. International Journal of Science Education, 24 (2002), 681–699. CrossRefGoogle Scholar
Ebert-May, D., Batzli, J., Lim, H.. Disciplinary research strategies for assessment of learning. BioScience, 53 (2003), 1221–1228. CrossRefGoogle Scholar
Gibbons, N. J., Evans, C., Payne, A., Shah, K., Griffin, D. K.. Computer simulations improve university instructional laboratories. Cell Biology Education, 3 (2004), 263–269. CrossRefGoogle ScholarPubMed
J. Goudriaan, H. H. van Laar. Modelling potential crop growth processes: textbook with exercises. Kluwer Academic Publishers, Dordrecht, Netherlands, 1994.
R. Greenler, J. Greenler, D. Lauffer, P. Williams. Spiraling through life with fast plants: an inquiry rich manual. Kendall/Hunt Publishing Company, Dubuque, Iowa, 2001.
Grossman, Y. L., DeJong, T. M.. Maximum fruit growth potential and seasonal patterns of resource dynamics during peach growth. Annals of Botany, 75 (1995), 553–560. CrossRefGoogle Scholar
Grossman, Y. L., DeJong, T. M.. Maximum vegetative growth potential and seasonal patterns of resource dynamics during peach growth. Annals of Botany, 76 (1995), 473–482. CrossRefGoogle Scholar
Grossman, Y. L., DeJong, T. M.. PEACH: A model of reproductive and vegetative growth in peach trees. Tree Physiology, 14 (1994), 329–345. CrossRefGoogle ScholarPubMed
Y. L. Grossman, T. M. DeJong, S. F. Vosburg. PEACH. First review folder. BioQUEST Library, (2002), VI:116–117. Website http://www.bioquest.org/BQLibrary/library_result.php [accessed 16 August 2010].
Haslam, F., Treagust, D. F.. Diagnosing secondary students’ misconceptions of photosynthesis and respiration in plants using a two-tier multiple choice instrument. Journal of Biological Education, 21 (1987), 203–211. CrossRefGoogle Scholar
Jackson, L. J., Trebitz, A. S., Cottingham, K. L.. An introduction to the practice of ecological modeling. BioScience, 50 (2000), 694–706. CrossRefGoogle Scholar
I. R. Johnson. PlantMod: exploring the physiology of plant canopies. IMJ Software, Armidale, NSW, Australia, 2010. Website http://www.imj.com.au/software/plantmod [accessed 16 August 2010].
Khush, G. S.. Green revolution: the way forward. Nature Reviews Genetics, 2 (2001), 815–822. CrossRefGoogle ScholarPubMed
Kishitani, S., Shibles, R.. Respiration rates of soybean cultivars. Crop Science, 26 (1986), 580–583. CrossRefGoogle Scholar
Kleier, C., Farnsworth, B., Winner, W.. Biomass, reproductive output, and physiological responses of rapid-cycling Brassica (Brassica rapa) to ozone and modified root temperature. New Phytologist, 139 (1998), 657–664. CrossRefGoogle Scholar
H. Lambers, F. S. Chapin III, T. L. Pons. Plant physiological ecology. Springer-Verlag, New York, New York, 1998.
Le Roux, X., Lacointe, A., Escobar-Gutiérrez, A., Dizès, S. Le. Carbon-based models of individual tree growth: a critical appraisal. Annals of Forest Science, 58 (2001), 469–506. CrossRefGoogle Scholar
Marcelis, L. F. M.. A simulation model for dry matter partitioning in cucumber. Annals of Botany, 74 (1994), 43–52. CrossRefGoogle Scholar
Marcelis, L. F. M.. Sink strength as a determinant of dry matter partitioning in the whole plant. Journal of Experimental Botany, 47 (1996), 1281–1291. CrossRefGoogle ScholarPubMed
Marcelis, L. F. M., Heuvelink, E., Goudriaan, J.. Modelling biomass production and yield of horticultural crops: a review. Scientia Horticulturae, 74 (1998), 83–111. CrossRefGoogle Scholar
Meir, E., Perry, J., Stal, D., Maruca, S., Klopfer, E.. How effective are simulated molecular-level experiments for teaching diffusion and osmosis? Cell Biology Education, 4 (2005), 235–248. CrossRefGoogle ScholarPubMed
Mooney, H. A.. The carbon balance of plants. Annual Review of Ecology and Systematics, 3 (1972), 315–346. CrossRefGoogle Scholar
National Research Council. A new biology for the 21st century: ensuring the United States leads the coming biology revolution. National Academies Press, Washington, DC., 2009.
E. C. Odum, H. T. Odum, N. Peterson. Environmental decision making. BioQUEST Library, (1995), VI:116–117. Website http://www.bioquest.org/BQLibrary/library_result.php [accessed 16 August 2010].
Piñeiro, G., Perelman, S., Guerschman, J. P., Paruelo, J. M.. How to evaluate models: observed vs. predicted or predicted vs. observed. Ecological Modelling, 216 (2008), 316–322. CrossRefGoogle Scholar
Poorter, H., Remkes, C., Lambers, H.. Carbon and nitrogen economy of 24 wild species differing in relative growth rate. Plant Physiology, 94 (1990), 621–627. CrossRefGoogle ScholarPubMed
F. B. Salisbury, C. W. Ross. Plant Physiology, 4th ed. Wadsworth Publishing Company, Belmont, California, 1992.
Tardieu, F.. Why work and discuss the basic principles of plant modelling 50 years after the first plant models? Editorial. Journal of Experimental Botany, 61 (2010), 2039–2041. CrossRefGoogle ScholarPubMed
J. H. M. Thornley, I. R. Johnson. Plant and crop modelling: a mathematical approach to plant and crop physiology. Clarendon Press, Oxford, 1990.
Vos, J., Evers, J. B., Buck-Sorlin, G. H., Andrieu, B., Chelle, M., de Visser, P. H. B.. Functional-structural plant modelling: a new versatile tool in crop science. Journal of Experimental Botany, 61 (2010), 2101–2115. CrossRefGoogle ScholarPubMed
P. Wareing, J. Patrick. Source-sink relationships and the partition of assimilates in plants. In J. Cooper [ed.], Photosynthesis and productivity in different environments, 481–499. Cambridge University Press, Cambridge, 1975.
Williams, P. H., Hill, C. B.. Rapid-cycling populations of Brassica. Science, 232 (1986), 1385–1389. CrossRefGoogle ScholarPubMed
Wilson, C. D., Anderson, C. W., Heidemann, M., Merrill, J. E., Merritt, B. W., Richmond, G., Sibley, D. F., Parker, J. M.. Assessing students’ ability to trace matter in dynamic systems in cell biology. CBE Life Sciences Education, 5 (2006), 323–331. CrossRefGoogle ScholarPubMed
Wisconsin Fast Plant Program. Exploring with Wisconsin fast plants. University of Wisconsin-Madison, Madison, Wisconsin, 1995.
Zhu, X-G., Long, S. P., Ort, D. R.. Improving photosynthetic efficiency for greater yield. Annual Review of Plant Biology, 61 (2010), 235–261.CrossRefGoogle ScholarPubMed