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United States Department of Agriculture

Agricultural Research Service

Title: Calculation of Rates for Enzyme and Microbial Kinetics Via a Spline Technique

Author
item Klasson, K Thomas

Submitted to: UJNR Food & Agricultural Panel Proceedings
Publication Type: Proceedings
Publication Acceptance Date: August 15, 2005
Publication Date: October 23, 2005
Repository URL: http://hdl.handle.net/10113/45865
Citation: Klasson, K.T. 2005. Calculation of rates for enzyme and microbial kinetics via a spline technique. In: Proceedings of the United States-Japan Cooperative Program in Natural Resources, Food and Agriculture Panel, October 22-29, 2005, Susono Fuji, Japan. p. 223-230.

Interpretive Summary: In enzyme and microorganism research, determination of enzyme reaction speed, microorganism growth, and nutrient reaction speed, product production rate is sometimes required using a method that other researchers can duplicate. In this paper, several methods that have been suggested in the books and magazines are discussed. A spreadsheet methodology was developed to handle the complicated equations. The results show that a smooth curve generating method proved more versatile in its use, even though the spreadsheet programming was challenging. The methods discussed were tested with old experimental results and a recommended technique was determined.

Technical Abstract: In biocatalysis research, determination of enzyme kinetics, microbial growth rates, substrate utilization rates, and product accumulation rates sometime require derivatives to be calculated with a method that can be duplicated and yields consistent results. In this paper, several methods that have been suggested in the literature are discussed and the result is presented graphically. A spreadsheet methodology was developed to handle the complicated equations. The results show that a cubic spline method proved more versatile in its use, even though the spreadsheet programming was challenging. The methods discussed were tested with published literature data for cell growth, and a preferred technique was developed based on smoothing the data and using this smooth data for rate calculations.

Last Modified: 12/21/2014
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