Food instrumental measures

Carrasco, A. and Siebert, K. J. (1999). Human visual perception of haze and relationships with instrumental measurements of turbidity. Thresholds, magnitude estimation and sensory descriptive analysis of haze in model systems. Food Qual. Pref. 10, 421 436. 

Voisey, P. W. Instrumental Measurement of Food Texture, in "Rheology and Texture in Food Quality," J. M. de Man,... 

PROBLEMS ASSOCIATED WITH INSTRUMENTAL MEASUREMENT OF FOOD... 

There would be considerable advantage for both sensory scientists and the food industry in knowing what consumers are measuring in order to assess particular textural properties. Despite many real advances in the instrumental measurement of food texture, we are not significantly closer to understanding the sensory cues used in consumer assessment of texture. The mastication process is adjusted to the consistency of the food bolus in real time. From studies of this process is emerging a novel approach to characterisation of food texture. 

Voisey, P.W. and Larmond, E. (1977). The effect of deformation rate on the relationship between sensory and instrumental measurements of meat tenderness by the Warner- Bratzler method. Canad. Inst. Food Sci. Technol. 10, 307-312. 

Since sensory and mechanical properties of a food depend on its microstructure, the knowledge of microstructure must precede any operation aimed to the attainment of a specific texture (Ding and Gunasekaran, 1998). The instrumental measurements of mechanical and rheological properties represent the food responses to the forces acting on the food structure and, for this reason, are affected by the way in which these analyses are performed. Furthermore, mechanical and rheological tests are always destructive and make impossible the execution of other analyses. 

Ultrasound is one of the more dynamic areas of food quality measurement, as indicated by the rapid rate at which commercial ultrasound instrumentation is entering the market (Mulet et al., 1999 Povey, 2001 Povey and Higgs, 2001). Many reviews of the literature on the subject have also appeared recently (Povey, 1997a Kress-Rogers, 2001). This dynamism is the result of two decades of developmental work (Povey and Wilkinson,... 

Pa.s. Therefore, 1 Pa.s = 10 P = 1000 cP. Some instruments measure kinematic viscosity, which is equal to dynamic viscosity x density and is expressed in units of Stokes. The viscosity of water at room temperature is about 1 cP. Mohsenin (1970) has listed the viscosities of some foods these, as well as their SI equivalents, are given in Table 8-2. 

Houskaet al. (1998) determined the relationships for five sensory methods of oral and non-oral viscosity evaluation between viscosity scores and instrumentally measured dynamic viscosity for Newtonian fluid foods of low and medium viscosities. From those relationships, the effective shear rates for the five the sensory tests were estimated. Highest shear rates were predicted for viscosity perception by compression of samples between tongue and palate, and the lowest for pouring the fluid foods from a teaspoon. Mixing with a teaspoon, slurping and swallowing exhibited nearly... 

An instrument, known as the Food Oil Sensor, has been marketed by the Northern Instrument Company since the late 1970s. The instrument measures the change in the value of the dielectric constant in frying fat. This value increases as the oil is degraded because of the formation of polar material in the oil. The instrument is simple to operate and is used by many researchers to study fryer oil quality in the... 

Methods for the instrumental measurement of food eoloiu by reflectance involve four stages ... 

Zhou, P. and Regenstein, J. M. (2007). Comparison of water gel desserts from fish skin and pork gelatins using instrumental measurements. /. Food Sci. 72(4), C196-C201. 

Have you ever wondered how the energy content of a fuel or food is measured An Instrument called a bomb calorimeter is used to measure energy content. Figure 9-5 shows the major components of a bomb calorimeter. 

The application of nuclear magnetic resonance spectroscopy within the food sector has, imtil recently, focussed primarily on the use of time domain (TD) techniques. These enable the quantitative measurement of bulk properties such as water and fat content in whole foods. The measurement relies on the intrinsic relaxation properties of the proton nucleus when a radio frequency pulse is applied to a sample placed in a magnetic field. The differential between the relaxation properties of major food components allows the proportion of these components to be estimated by reference to a calibration safes. This form of NMR spectroscopy is routinely applied for quality and composition checks and is often undertaken in situ as the instrumentation is both inexpensive and robust... 

Feeding and texture of food (meeting), Vincent J.F.V, Cambridge UP, 1991, 60 Food texture measurement and perception, Rosenthal A.J, Aspen PubL, 1999, 142 Food texture Instrumental and sensory measurement (meeting), Moskowitz H.R,... 

Correlation was established between the colors of food samples measured by the colorimeter color and the color machine vision system. The correlation coefficients between L a b color parameters for beef and carrots obtained from the two instruments can be seen in Table 2. For all the data collected, a high correlation was observed (R > = 0.98). The established correlation makes it possible to verify CMVS s color measurement accuracy of colors that are not available from published color standards. Furthermore, the correlations between the CMVS and colorants in food systems can also be inferenced based on established correlations between colorimeter measurements and colorant contents. 

In-line/on-line feedback control of color of food during processing can improve not only color quality but also color related quality such as texture and appearance. To do this, there are three major aspects development of an in-line/on-line color sensor understanding of color change kinetics and establish correlations between instrumental measured and sensory panel perceived colors of foods. In this research, we have chosen color machine vision technology for the measurement of colors of food due to its superior spatial resolution over conventional instruments such as colorimeter or spectrophotometer. Relationships between measured colors and corresponding principal chemical markers were established for the model food systems. We have also found excellent correlations between the color machine vision system (CMVS) measured and a sensory panel determined colors of food samples (Ling and Tepper, 1995). We believed that a CMVS can be used for food process control to ensure color quality as perceived by consumers. 

However, most of the time, due to the complexity of the food samples and the need to minimize the sample treatment, that is, the chemical separation of the interferences from the compounds of interest, more powerful instrumental measurements, such as 2D spectroscopies, for example EEM fluorescence spectra, or hyphenated separation techniques, for example gas chromatogra-phy/MS (GC/MS), HPLC/DAD or HPLC/MS, are used. As mentioned in previous sections, obtaining a data table per sample is a much more natural scenario for the application of MCR techniques. In these instances, the typical strategy is to perform the simultaneous analysis of data tables related to standards of known concentration together with tables from unknown samples, in which the concentration(s) of the analyte(s) are determined. Either using multiset analysis or multiway analysis, these determinations benefit from the so-called second-order advantage, which means that analytes can be determined in the presence of interferences, even if those are absent from the calibration samples [48]. The reason why this second-order advantage exists is that MCR techniques describe the information of the compounds in separate concentration profiles and spectra, that is, they make a mathematicar separation of the information related to aU compounds in the analysed sample, analytes and interferences. Afterwards, only the information of the profiles related to the analytes is used for quantitation purposes. 

Wardencki, W., Chmiel, T., Dymerski, T., 2013. Gas chromatography-olfactometry (GC-O), electronic noses (e-noses) and electronic tongues (e-tongues) for in vivo food flavor measurement. In Kilcast, D. (Ed.), Instrumental Assessment of Food Sensory Quality. A Practical Guide. Woodhead Publishing Limited, Cambridge (Chapter 7). 

Photoelectric-Colorimetric Method. Although the recording spectrophotometer is, for food work at least, a research tool, another instrument, the Hunter multipurpose reflectometer (4), is available and may prove to be applicable to industrial quality control. (The newer Hunter color and color difference meter which eliminates considerable calculation will probably be even more directly applicable. Another make of reflection meter has recently been made available commercially that uses filters similar to those developed by Hunter and can be used to obtain a similar type of data.) This instrument is not a spectrophotometer, for it does not primarily measure the variation of any property of samples with respect to wave length, but certain colorimetric indexes are calculated from separate readings with amber, blue, and green filters, designated A, B, and G, respectively. The most useful indexes in food color work obtainable with this type of instrument have been G, which gives a... 

In the preceding section, we presented principles of spectroscopy over the entire electromagnetic spectrum. The most important spectroscopic methods are those in the visible spectral region where food colorants can be perceived by the human eye. Human perception and the physical analysis of food colorants operate differently. The human perception with which we shall deal in Section 1.5 is difficult to normalize. However, the intention to standardize human color perception based on the abilities of most individuals led to a variety of protocols that regulate in detail how, with physical methods, human color perception can be simulated. In any case, a sophisticated instrumental set up is required. We present certain details related to optical spectroscopy here. For practical purposes, one must discriminate between measurements in the absorbance mode and those in the reflection mode. The latter mode is more important for direct measurement of colorants in food samples. To characterize pure or extracted food colorants the absorption mode should be used. 

Instrumental color measurements eliminate subjectivity, are more precise, take less time, and are simpler to perform. However, to evaluate instrumental results properly, the physics of the measurement processes must be considered. Three types of color measurement instruments are used for food the monochromatic colorimeter, the tristimulus colorimeter, and the colorimetric spectrophotometer. 

The experimental designs discussed in Chapters 24-26 for optimization can be used also for finding the product composition or processing condition that is optimal in terms of sensory properties. In particular, central composite designs and mixture designs are much used. The analysis of the sensory response is usually in the form of a fully quadratic function of the experimental factors. The sensory response itself may be the mean score of a panel of trained panellists. One may consider such a trained panel as a sensitive instrument to measure the perceived intensity useful in describing the sensory characteristics of a food product. 

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