Chromatography and Capillary Electrophoresis in Food Analysis

By Hilmer Sørensen, Susanne Sørensen, Charlotte Bjergegaard, Søren Michaelsen

The Royal Society of Chemistry

Copyright © 1999 The Royal Society of Chemistry
All rights reserved.
ISBN: 978-0-85404-561-7

Contents

Chapter 1 General Aspects of Experimental Biochemistry, 1,
Chapter 2 Buffers and Micelles, 12,
Chapter 3 Binding, Association, Dissociation, and Kinetics, 35,
Chapter 4 Extraction of Native Low-Mr and High-Mr, Biomolecules, 69,
Chapter 5 Spectroscopy and Detection Methods, 92,
Chapter 6 Liquid Chromatography, 120,
Chapter 7 Ion-exchange Chromatography, 152,
Chapter 8 High-performance Liquid Chromatography and Fast Polymer Liquid Chromatography, 168,
Chapter 9 Electrophoresis, 178,
Chapter 10 High-performance Capillary Electrophoresis, 208,
Chapter 11 Analytical Determination of Low-Mr, Compounds, 278,
Chapter 12 Protein Purification and Analysis, 315,
Chapter 13 Immunochemical Techniques, 374,
Chapter 14 Analysis of Dietary Fibre, 394,
Appendix Supercritical Fluid Extraction (SFE) and Supercritical Fluid Chromatography (SFC), 413,
Subject Index, 430,

CHAPTER 1

General Aspects of Experimental Biochemistry

1 Introduction

Experimental work demands a knowledge of some basic areas such as quantities, symbols, and units commonly used in biochemistry, as well as of laboratory safety rules and general working practices, including the registration and evaluation of results, the search for literature, etc. Whereas quantities, symbols, and units are beyond dispute, variations of course exist in how things are done at different laboratories/institutions. Some general aspects can, however, be stated from which one hopefully may get inspiration.

2 Quantities, Symbols, and Units

The following tables and lists are not complete, but are intended as guidelines to frequently used quantities, symbols, and units. A more comprehensive overview can be found in Ref. 1.

A physical quantity is the product of a numerical value (a pure number) and a unit. The base units may be given in the centimetre – gram – seconds (cgs) system or, more often, in SI units (Système International d’Unités; The International System of Units) (Table 1.1).

Units with special names and symbols are derived from these basic units. Examples of commonly used units are listed in Table 1.2 together with some units found in older literature but which are also of current interest.

Some values of selected fundamental constants are:

Faraday (F) 9.6485309 x 104 C
mol-1

Electron volt (eV) 96.6 kJ mol-1 = 23.1
kcal mol-1

Electronic charge (e-) F/N0
= 4.8 x 10-10
electrostatic units (esu)
= 14.4 x 10-8 V = 1.60 x
10-19 C, 1 mol e-
= 6.023 x 1023 e-

Avogadro constant (N0) 6.0221367 x 1023
mol-1

Planck constant (h) 6.6260755 x 10-34 J s
= 1.58 x 10-34 cal s
= 6.62 x 10~27 erg s

Absolute temperature of the ‘ice’ point, 0°C (T0°c) 273.16 K

Gas constant (R) R = PV/nT
(P = pressure = 0, and
T = temperature = 0° C)
= 8.314510 J K-1
mol-1 = 1.987 cal
K-1 mol-1
= 0.0821 atm K-1
mol-1

Pressure-volume product (PV) for 1 mol of a gas at 0°C and zero pressure 22.414 L atm mol-1
= 22414 cm3 atm
mol-1

Boltzmann constant (kB) R/N0
= 1.380658 x 10-23
J K-1
Acceleration due to gravity (g) 9.80665 m s-2

Speed of light in vacuum (c0) 2.99792 x 108
ms-1

An enzyme unit (U) is defined as the amount of enzyme catalysing the conversion of 1 µmol of substrate into product in 1 min under defined conditions (often at 25 or 30 °C and at optimal assay conditions, including pH). The SI unit for enzyme activity is the katal (kat), which is the amount of enzyme converting 1 mol s-1 of substrate into product under optimal/defined conditions; 1 katal = 6 x 107 U; 1 U = 1.67 x 10-8 kat.

Units are often expressed as multiples or sub-multiples by the use of prefixes (Table 1.3). Knowledge of the Greek alphabet may be useful in various connections (Table 1.4). A Periodic Table of the elements is shown in Figure 1.1.

3 Basic Mathematics and Statistics

This section reviews some fundamental concepts within mathematics and statistics relevant for the evaluation of analytical results. For a more comprehensive discussion, the reader is referred to textbooks on these subjects.

Significant figures. The concept of significant figures is most simply illustrated by the use of examples, e.g. 0.0073. This number has two significant figures as the leading zeroes are not regarded as significant, except as a way of showing the magnitude of the number. The number 7.3 x 10-3 also has two significant figures. However, zeroes after the first figure higher than zero are included, e.g. 0.00730 has three significant figures, as it is neither 0.00731 nor 0.00732, etc. An example of a number higher than 1 is 24500, which has five significant figures, whereas 2.45 x 104 has 3 significant figures.

Analyses generally lead to results with a limited number of significant figures compared to, for example, mathematically defined constants such as π = 3.1415 … or e = 2.7182. … The uncertainty of results may be random or systematic. Results of analyses should only be given with the number of reliable figures, often 2–4. This is, however, only for the final results. During calculations, rounded figures should not be used.

Mean value. The mean value [bar.x] of n data (x1, x2, x3, …, xn): [bar.x] = 1/n Σ xi.

Standard deviation. The standard deviation (σ) is the average square root of the squares of the deviations from the mean value: [MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII]. With a restricted number of observations, [MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] should be used.

Standard deviation of the mean value. The standard deviation of the mean value or relative standard deviation (RSD) is defined as σ/[bar.x].

Normal distribution. The normal distribution applies to measurements of continuous values. Normal distribution diagrams have 68.27% of all values within a plus or minus one standard deviation of the mean (Figure 1.2), 95.45% within k [+ or -] 2σ, and 99.73% within [+ or -] 3σ.

Mean deviation. The mean deviation (MD) is defined as MD = 1/n Σ |xi – [bar.x]|. The mean deviation between two results can be given in the same way: MD = 1/2 Σ |x1 – x2|.

Repeatability. The repeatability is the standard deviation for a set of analyses performed in the same laboratory with the same apparatus and by the same analyst within a limited period. The data must have a normal distribution.

Reproducibility. The reproducibility is the standard deviation for a set of analyses performed in different laboratories, and/or with different apparatus, and/or by different analysts, and/or over different periods. The data must have a normal distribution.

Linear regression. The statistical procedure used to find the line of best fit is based on the principle of least squares. The equation describing the best line is y = b + αx where

α = Σ(xi – [bar.x]) (yi – [bar.y])/ Σ(xi – [bar.x])

α is the slope of the best straight line and can be calculated from any two points (x1, y1 and x2, y2) on the line [α = (y2 – y1)/(x2 – x1)] b is the intercept of the line with the y-axis. These figures (α and b) are easily found by the use of most calculation software for PCs or with calculators. This is also true for the correlation coefficient r; r = [+ or -] 1.0 describes a perfectly linear positive/negative correlation, whereas r = 0 means that no linear correlation exists between the x– and y-values. A value of r ≥ 0.998 is normally considered satisfactory for most biochemical analyses.

Hyperbola and power functions. The equation for two parameters following a hyperbolic curvature is y = k1 + k2x-1. If the data follow a power function, the equation is y = kx[bar.n]. Data following such functions are often found in analytical and experimental biochemistry. These equations can be transformed into linear functions: single/double reciprocal and logarithmic functions, respectively (Section 3.4), which then give a better basis for evaluation of the experimental results.

4 Laboratory Safety

Before dealing with analytical work, one should recognize the importance of safe laboratory practice. Most often, a laboratory is a working place for a group of people, meaning that your knowledge of basic safety rules matters for more than yourself. Some very general laboratory safety rules are listed below. Most laboratories have additional rules and specialized laboratories, e.g. laboratories working with micro-organisms, may require further precautions.

• Do not smoke in the laboratory.

• Do not eat or drink in the laboratory.

• Never wear contact lenses in the laboratory.

• Safety glasses should be used when necessary.

• Naked flames should not be used outside the fume cupboard. Always check that no inflammable liquids or other inflammable materials are present in the fume cupboard.

• Be aware of the location of fire exits, emergency showers, and the use and whereabouts of fire-fighting equipment.

• Be aware of the location of eye-wash bottles.

• Never heat plugged flasks and other closed glassware.

• Never pipette by mouth.

• Be careful when attaching or detaching a rubber tube to glassware. Use, for example, a pair of scissors. Broken glass is often involved in laboratory accidents.

• Read and follow specific safety instructions from manufacturers on hazardous chemicals.

• Get a basic knowledge of national legislation as well as company or university ‘rules’ on safety and environmental aspects of laboratory rules.

• Always use a fume cupboard when working with hazardous chemicals.

• Waste chemicals at working places, e.g. in fume cupboards, in or around balances, centrifuges, etc., should be thoroughly cleaned up.

• Always mark samples, chemicals, test tubes, etc. with name, date and type of content.

(Continues…)Excerpted from Chromatography and Capillary Electrophoresis in Food Analysis by Hilmer Sørensen, Susanne Sørensen, Charlotte Bjergegaard, Søren Michaelsen. Copyright © 1999 The Royal Society of Chemistry. Excerpted by permission of The Royal Society of Chemistry.
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