Examples colour analysis

Thus, for example, an analysis using coloured solutions can be carried out, where an indicator cannot be used. Moreover, it is not easy to find a redox indicator which will change colour at the right point. Potentiometric methods can fairly readily be made automatic. 

In the MCR framework, there are few cases in which the quantitative analysis is based on the acquisition of a single spectrum per sample, as is the case for classical first-order multivariate calibration methods, such as partial least squares (PLS), seen in other chapters of this book. There are some instances in which quantitation of compounds in a sample by MCR can be based on a single spectrum, that is, a row of the D matrix and the related row of the C matrix. Sometimes, this is feasible when the compounds to be determined provide a very high signal compared with the rest of the substances in the food sample, for example colouring additives in drinks determined by ultraviolet—visible (UV-vis) spectroscopy [26,27]. Recently, these examples have increased due to the incorporation of a new cmistraint in MCR, the so-caUed correlation constraint [27,46,47], which introduces an internal calihratimi step in the calculation of the elements of the concentradmi profiles in the matrix C related to the analytes to be quantified. This calibration step helps to obtain real concentration values and to separate in a more efficient way the information of the analytes to be quantified from that of the interferences. 

The last example of ToF-SIMS analysis of natural fibres is of a structural characterization of wood species for an eventual dendrochronological study [Saito et al. 2008], The aim of this research was to develop a new method to differentiate heartwood and sapwood. In dendrochronology, when bark is not present on the samples, the presence of sapwood is the key to determining felling date. Usually, heartwood and sapwood can easily been differentiated by their colour, with heartwood being much darker. Nevertheless, in the case of... 

With regard to comprehensive LC data elaboration, the acquired data is commonly elaborated with dedicated software that constructs a matrix with rows corresponding to the duration of the second-dimension analysis and data columns covering all successive second-dimension chromatograms. The result is a bidimensional contour plot, where each component is represented as an ellipse-shaped peak, defined by double-axis retention time coordinates. When creating a 3D chromatogram, a third axis by means of relative intensity is added. The colour and dimension of each peak is related to the quantity of each compound present in the sample. Figure 4.9 illustrates an example of data elaboration in comprehensive LC. 

Colour centres are formed if a crystal of NaCl is heated in sodium vapour sodium is taken into the crystal, and the formula becomes Nai+/fl. The sodium atoms occupy cation sites, creating an equivalent number of anion vacancies they subsequently ionize to form a sodium cation with an electron trapped at the anion vacancy. The solid so formed is a non-stoichiometric compound because the ratio of the atomic components is no longer the simple integer that we have come to expect for well-characterized compounds. A careful analysis of many substances, particularly inorganic solids, demonstrates that it is common for the atomic ratios to be non-integral. Uranium dioxide, for instance, can range in composition from UOi 05 to UO2.25, certainly not the perfect UO2 that we might expect Many other examples exist, some of which we discuss in some detail. 

When colours are added to a food system, their characterisation is often more difficult due to interferences from other materials in the food or difficulty with their extraction from the food. This is particularly the case for high-protein foods, which bind colours very tightly and can make their quantitative analysis very difficult. However, analysis for azo-dyes in soft drinks is generally straightforward using modern methods. There is less interference than in other food systems and as the colours are already in solution, and not bound to other materials, this makes the analysis easier. In some cases, the colours can be analysed without prior concentration and in others they have to be concentrated by solid-phase extraction methods, for example, Ci8 cartridges followed by elution with a small volume of methanolic ammonia. 

Chemists use a range of techniques for qualitative analysis. For example, the colour of an aqueous solution can help to identify one of the ions that it contains. Examine Table 9.3. However, the intensity of ion colour varies with its concentration in the solution. Also keep in mind that many ions are colourless in aqueous solution. For example, the cations of elements from Groups 1 (IA) and 2 (IIA), as well as aluminum, zinc, and most anions, are colourless. So there are limits to the inferences you can make if you rely on solution colour alone. 

The formation of complexes in qualitative inorganic analysis is often observed and is used for separation or identification. One of the most common phenomena occurring when complex ions are formed is a change of colour in the solution. Some examples are ... 

If the specimen provided is a trace sample, sufficient material should be recovered to allow an instrumental analysis directly. The nature of the sample will often provide a clue as to the drug(s) involved and direct comparison can be made by using gas chromatography-mass spectrometry (GC-MS), for example. If the specimen is a bulk sample, presumptive (colour) tests are undertaken to determine the class or classes of drugs which the sample contains. Thin layer chromatography (TEC) is used to determine which members of the classes are present and it might also be possible to make a semi-quantitative estimate of the amount(s) of drug(s) present. Standard mixes can then be prepared for use in the confirmatory techniques. 

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