复试包括英语第二份食品分析课件

1、Reporting Results and Reliability of Analyses12Reporting Results3Reliability of Analysesintroduce The basic purpose of an analytical assay is to determine the mass (weight) of a component in a sample. The numerical result of the assay is expressed as a weight percentage or in other units that are eq

2、uivalent to the mass/mass ratio. The mass (weight) of a component in a food sample is calculated from a determination of a parameter whose magnitude is a function of the mass of the specific component in the sample. Some properties are basically mass dependent. Absorption of light or other forms of

3、radiant energy is a function of the number of molecules, atoms, or ions in the absorbing species. Although certain properties, such as specific gravity and refractive index, are not mass dependent, they can be used indirectly for mass determination. Thus, one can determine the concentration of ethan

4、ol in aqueous solutions by a density determination. Refractive index is used routinely to determine soluble solids (mainly sugars) in syrups and jams. Some mass-dependent properties may be characteristic of several or even of a single component and may be used for selective and specific assays. Exam

5、ples are light absorption, polarization, or radioactivity. Some properties have both a Reporting Results and Reliability of Analyses magnitude and a specificity parameter (nuclear magnetic resonance and infrared spectroscopy). Such properties are of great analytical value because they provide select

6、ive determinations of a relatively large number of substances. In this chapter, we describe conventional ways of expressing analytical results and discuss the significance of specificity, accuracy, precision, and sensitivity in assessing the reliability of analyses. In recent years the metric SI sys

7、tem of units has gained worldwide acceptance. It has been mended or required by International Union of Pure and Applied Chemistry (IUPAC), and the International Union of Pure and Applied Physics (IUPAP), as well as by an increasing number of scientific and professional organizations in the United St

8、ates and by the industry and the trade. The SI system contains seven base units, two supplementary units, 15 derived units having special names, and 14 prefixes for multiple and submultiple units. All physical properties can be quantified by 38 names. In reporting analytical results, both the refere

9、nce basis and the units used to express the results must be considered. For example, analyses can be performed and the results reported on the edible portion only or on the whole food as purchased. Results can be reported on an as-is basis, on an air-dry basis, on a dry matter basis, or on an arbitr

10、arily selected moisture basis (e.g., 14% in cereals). To convert contents (%) of component Y from oven-dried (OD) to an as-received (AR) basis, or vice versa, the following formulas are used: Reporting Results To convert contents from an as-received basis to an arbitrary moisture basis, the followin

11、g formula is used: To weight out a sample on an arbitrary moisture (AM) basis, use the following: To obtain % dry matter, subtract percentage of moisture from 100. If the moisture has been determined in two stages, air drying followed by oven drying, compute total moisture contents of sample as foll

12、ows: Where TM is the % total moisture, A the % moisture loss in air drying, and B the % moisture of air-dried sample as determined by oven drying. Tables, nomograms, and calculators are available to simplify calculations in expressing results on a given basis, or for weighing samples on a fixed mois

13、ture basis (e.g., 20% in dried fruit). In view of the very wide range in moisture contents in various foods, analytical results are often meaningless unless the basis of expressing the results is known. Expressing analytical results on an as-is basis is wrought with many difficulties. It is practica

14、lly impossible to eliminate considerable desiccation of fresh plant material. In some instances, even if great pains are taken to reduce such losses, the results may still vary widely. For example, the moisture contents of leafy foods may vary by as much as 10% depending on the time of harvest (from

15、 early morning to late afternoon). Similarly, the moisture contents of bread crust and crumb change from the moment bread is removed from the oven as a result of moisture migration and evaporation. Absorption of water in baked or roasted low-moisture foods (crackers, coffee) is quite substantial. In

16、 most cases, storing air-dried foods in hermetically closed containers is least troublesome. Once the moisture contents of such foods are determined, samples can be used for analyses over a reasonable period. The concentrations of major components are generally expressed on a percentage by weight or

17、 percentage by volume basis. For liquids and beverages, g per 100mL is often reported. Minor components are calculated as mg (or mcg) per kg or L; vitamins in mcg or international units per 100g or 100mL.Amuunts of spray residues are often reported in ppm (parts per million). In calculating the prot

18、ein contents of a food, it is generally assumed the protein contains 16% nitrogen. To convert from organic nitrogen (generally determined by the Kjeldahl method; see Chapter 37) to protein, the factor of 6.25=100/16 is used. In specific foods known to contain different concentrations of nitrogen in

19、the protein, other conversion factors are used (5.7 in cereals, 6.38 in milk). Heidelbaugh et al. (1975) compared three methods for calculating the protein content of 68 foods: (1) multiplication of Kjeldahl nitrogen by 6.25; (2) multiplication of Kjeldahl nitrogen by factors ranging from 5.30 to 6.

20、38 depending on the type of food; and (3) calculation on the basis of amino acid composition, determined by chemical analyses. Up to 40% differences in protein content were found depending on the calculation method. There were, however, only small differences in mixed diets representing typical menu

21、s. If a food contains a mixture of carbohydrates, the sugars and starch are often expressed as dextrose. In lipid analyses (free fatty acids or total lipid contents) calculations are based on the assumption that oleic acid is the predominant component. Organic acids are calculated as citric, malic,

22、lactic, or acetic acid depending on the main acid in the fruit or vegetable. Mineral components can be expressed on an as-is basis or as % of total ash. In either case the results can be calculated as elements or as the highest valency oxide of the element. Amino acid composition can be expressed in

23、 several ways: g amino acid per 100 g of sample, or per 100 g of protein, or per 100 g of amino acids. For the determination of molar distribution of amino acids in protein, g-mol of amino acid residue per 100 g-mol of amino acid are computed. In trade and industry, empirical tests are often used. F

24、or example, fat acidity of cereal grains is often expressed as mg KOH required to neutralize the fatty acids in 100 g of food. Acidity is often expressed for simplicity in milliliters of N/10 or N NaOH. The acidity of acid phosphates in baking powders is reported in industry as the number of parts o

25、f sodium bicarbonate that are required to neutralize 100 parts of the sample.BACK The reliability of an analytical method depends on its (1) specificity, (2) accuracy, (3) precision, and (4) sensitivity (Anastassiadis and Common 1968). Specificity is affected primarily by the presence of interfering

26、 substances that yield a measurement of the same kind as the substance being determined. In many cases, the effects of the interfering substances can be accounted for. In calculating or measuring the contribution of several interfering substances, it is important to establish whether their effects a

27、re additive. Accuracy of an analytical method is defined as the degree to which a mean estimate approaches a true estimate of an analyzed substance, after the effects of other substances have been allowed for by actual determination or calculation. In determining the accuracy of a method, we are bas

28、ically or calculation. In determining the accuracy of a method, we are basically interested in establishing the deviation of an analytical method from an ideal one. That deviation may be due to an inaccuracy inherent in the procedure; the effects of substances other than the analyzed one in the food

29、Reliability of Analyses sample; and alterations in the analyzed substance during the course of the analysis. The accuracy of an analytical assay procedure can be determined in two ways. In the absolute method, a sample containing known amounts of the analyzed components is used. In the comparative m

30、ethod, results are compared with those obtained by other methods that have been established to gibe accurate and meaningful results. The absolute method is often difficult or practically impossible to apply, especially for naturally occurring foods. In some cases, foods can be prepared by processing

31、 mixtures of pure compounds. If the mixtures are truly comparable in composition to natural foods, meaningful information is obtained. Several indirect methods are available to determine the accuracy of analyses. Although these methods are useful in revealing the presence of errors they cannot prove

32、 the absence of errors. When a complete analysis of a sample is made and each component is determined directly, a certain degree of accuracy is indicated if the sum of the components is close to 100. On the other hand, an apparently good summation can result from compensation of unrelated errors in

33、the determination of individual components. A more serious error can result from compensation of errors that are related in such a way that a negative error in one component will cancel a positive error in another component. This may be particularly important in plete fractionations. For example, th

34、e sum of proteins separated according to differences in solubility may be close to 100%, yet the separation of individual components may be plete or of limited accuracy. In the recovery method, known amounts of a pure substance are added to a series of samples of the material to be analyzed and the

35、assay procedure is applied to those samples. The recoveries of the added amounts are then calculated. A satisfactory recovery is most useful in demonstrating absence of negative errors. If the accuracy of an analytical method is affected by interference from substances that cannot be practically eli

36、minated, a suitable correction can sometimes be applied. Such a correction is often quite complicated because the results may be affected by concentration of the interfering or assayed substance, or by their interaction in food processing or during the analyses. Precision of a method is defined as t

37、he degree to which a determination of a substance yields an analytically true measurement of that substance. It is important to distinguish clearly between precision and accuracy. In industrial quality control, it often is unimportant whether analysis of numerous similar samples yields exactly accur

38、ate (i.e., true) information regarding the composition of the sample. The information may be useful provided the difference between the precise and accurate determination is consistent. The analysis that gives the actual composition (or in practice the most probable composition) is said to be the mo

39、st accurate. For instance, direct and accurate determination of the bran content can be estimated directly from the amount of crude fiber in a flour. This estimation is based on the fairly constant ratio between crude fiber (determined by a precise, but not accurate, empirical method) and actual bra

40、n contents. Still simpler is the estimation of bran content from total mineral content or reflectance color assay of a flour. To determine the precision of an analytical procedure and the confidence that can be placed on the results obtained by that procedure, statistical methods are used. The most

41、basic concept in statistical evaluation is that any quantity calculated from a set of data is an estimate of an unknown parameter and that the estimate is sufficiently reliable. It is common to use English letters for estimates and Greek letters for true parameters. If n determinations x1,x2,.xn are

42、 made on a sample, the average is an estimate of the unknown true value . The precision of the assay is given by the standard deviation : If the number of replicate determinations is small (10), an estimate of the standard deviation ( s ) is given by The divisor n-1 used to estimate s is termed the

43、degrees of freedom and indicates that there are only n-1 independent deviations from the mean. The standard deviation is the most useful parameter for measuring the variability of an analytical procedure. If s is independent of x for a given concentration range, s can be computed from results of rep

44、licate analyses on several samples of similar materials. In that case, the sums of the squares of the deviations of the replicates of each material are added, and the resultant total is divided by the number of degrees of freedom (the sum of the total number of determinations, n, minus the number of

45、 series of replicate determinations). A complicating factor in determining the precision arises when the standard deviation varies with the concentration of the element present. Sometimes the range of concentration can be divided into intervals and the standard deviation given for each interval. If

46、the standard deviation is approximately proportional to the amount present, precision can be expressed as a percentage by using the coefficient of variation (CV). If the data show a varying standard deviation, transformation of the data into other units in which the standard deviation is constant is

47、 often useful. Two widely used transformations are square roots and logarithms. Chemical analyses are made for various purposes and the precision required may vary over a wide range. In the determination of atomic weights, an effort is made to keep the error below 1 part in 104-105. in most analytic

48、al work, the allowable error lies in the range 1-10 parts per 1000 for components comprising more than 1% of the sample. As a rule, analyses should not be made with a precision greater than required. Up to a point, precision is a function of time, labor, and overall cost (Youden 1959). The precision

49、 of an analytical result depends on the least exact method used in obtaining the result. In expressing the result, the number of figures given should be such that the next to the last figure is certain and the last figure is highly probable yet not certain. Thus 10% and 10.00% denote widely varying

50、precision (Paech 1956). The following is an example of how an average result computed from several determinations should be expressed. Assume the moisture content of sugar is determined in triplicate, and the following results are obtained: 1.032, 1.046, and 1.036%. The average is 1.038%. However, b

51、ecause the difference between 1.032 and 1.046 is larger than 0.010, the results should not be expressed with more than two figures after the decimal point. Thus, the average result should be reported as 1.04% (not 1.038%), indicating that the first figure after the decimal point is certain, and the

52、second one is probable but uncertain. The results of weighing, buret reading, and instrumental (including automatic) reading have limitations. Replication of analyses eliminates some the errors resulting from sampling, from heterogeneity of sampled material, and from indeterminateaccidental or rando

53、merrors in the assay. Although repetition of an assay generally increases the precision of the analysis, it cannot improve its specificity and accuracy. If, however, reasonable specificity and accuracy have been established, the precision of the assay is an important criterion of its reliability. Se

54、nsitivity can be increased in tow ways: (1) by increasing the response per unit of analyzed substance (e.g., in colorimetric assays by the use of color reagents that have a high specific absorbance; in gravimetric determinations by the use of organic reagents with a high molecular weight) and (2) by

55、 improving the discriminatory power of the instrument or operator (e.g., in gravimetry by using a microbalance; in spectrophotometry by using a photomultiplier with a high magnifying power) (Anastassiadis and Common 1968). According to Horwitz (1982, 1983), the important components of reliability, w

56、hich are listed in their order of importance for most purposes in food analyses, are as follows: 1.Reproducibilitytotal between laboratory precision 2.Repeatabilitywithin-laboratory precision 3.Systematic error or biasdeviation from the “true” value 4.Specificityability to measure what is intended t

57、o be measured 5.Limit of reliable measurementthe smallest increment that can bemeasured with a statistical degree of confidence Typical analytical systematic errors (biases) are plotted in Fig.4.2.Detection and determination of errors were described and discussed in detail by Cardone. Tolerances and

58、 errors are depicted in Fig.4.3, in which the tolerance limits for the measured property are given by Lp and Cm indicates the uncertainty in the measurement. The values of Lp and Cm include estimates of the bounds for systematic errors or biases (B) and estimates of random errors (s, the estimate of

59、 standard deviation). Cm should be less than Lp. The confidence limits for , the mean of replicate measurements, are where is the so-called Student factor. For regulatory purposes, reliability is paramount and reproducibility is the critical component (Horwitz 1982).The between-laboratory coefficien

60、t of variation CV is represented by Where C is the concentration expressed as powers of 10(e.g., 1ppm, or 10-6, C=-6).The value of CV doubles for each decrease in concentration of two orders of magnitude. The between-laboratory coefficient of variation at 1 ppm is 16%(24).The within-laboratory CV sh