M. Kent

Dielectric studies of added water in poultry meat and scallops

Abstract Using a Hewlett-Packard dielectric spectrometer and 3.5mm coaxial probe, the dielectric spectra of chicken and scallop samples have been obtained in the frequency range 200 MHz to 12 GHz. The samples were subjected to different treatments involving soaking in water and polyphosphate solutions. Using principal component analysis (PCA), it was possible to distinguish between the controls and the various treatments. The spectra themselves show marked differences. Principal component regression (PCR) was also used to attempt calibrations for added water, nitrogen and ash contents in poultry meat and scallops; however, this appears not to be significantly better than using the permittivity values at a frequency close to 2 GHz.

Hand-held instrument for fat/water determination in whole fish

Abstract The fat content of fish is related to its water content, and measurement of one serves to determine the other. A compact microwave instrument is described which utilizes this fact to measure the fat content of pelagic and other fatty species of fish. The instrument discussed relies on a microstrip sensor. Its use with herring is demonstrated and its further development is considered.

Composition of foods including added water using microwave dielectric spectra

Abstract The added water content of fresh and untreated pork, poultry, fish and prawns was adjusted either by dipping in polyphosphate and salt solutions of known concentrations for controlled periods, or by injection (pork) with polyphosphate and salt solutions. Mixtures were prepared from treated and untreated fish and other foods (milk and flour). Liquid uptake was determined by the weight gain of samples. The proximate composition of the samples was determined: water, fat, protein, NaCl and phosphorus (for polyphosphate content). Complex dielectric spectra of each product were measured at known temperatures and at 31 frequencies in the range 0.2–12 GHz using an automatic network analyser (ANA) and a 3.0 mm open-ended coaxial sensor. The spectra were subjected to various procedures. • Principal component analysis (PCA) using the individual complex components. • Regression of the composition data against the principal components to obtain prediction formulae for composition including liquid uptake (internal cross-validation). • Regression of the composition data against raw spectral data and against other composition variables to obtain similar formulae. In order to design a simpler instrument, the effect on accuracy was studied of reducing the number of frequencies in the spectrum and its range. The slight loss of accuracy engendered by using only five or six frequencies was acceptable. The accuracy of the method in predicting liquid uptake and composition was good. Using one of the compositional variables in the calibration made it equivalent to accuracy obtained by proximate analysis, which was the limiting factor. Measurements on solutions of glycerol, NaCl and water with precisely known composition demonstrated that the intrinsic accuracy of the instrument was far better. A prototype instrument was built and validated using samples of prawns and herring.

Determination of added water in pork products using microwave dielectric spectroscopy

The effects of added water on the microwave dielectric spectra of pork products has been studied. Results are presented for canned pork, bacon, ham, leg meat and commercial samples of ham and bacon bought from UK retailers. The dielectric spectra were transformed by the method of principal components and the added water content and other compositional variables were regressed against the resultant PC scores to obtain calibration equations. The results were validated using both internal cross-validation (ICV) and a number of unknown samples. The main sources of error are discussed with particular reference to the standard method for determining added water.

Optimization of the microwave determination of water in foods using principal component analysis

In this paper a method for determining the composition of foodstuffs from the measured microwave dielectric spectra using an open ended coaxial probe is presented. The dielectric spectra of several kinds of meat were collected in the range of 200 MHz to 12 GHz. The data are used to predict the composition of the materials applying principal component analysis and regression. Effects of the reduction of the used bandwidth on the performance are investigated. Optimal frequency ranges with respect to measurement accuracy and hardware effort for an instrument are defined.

UWB Free-Space Characterization and Shape Recognition of Dielectric Objects Using Statistical Methods

This paper presents a novel method for the free-space characterization and shape recognition of dielectric objects using multivariate calibration methods and linear discriminant analysis. The dimensions of the variously shaped objects are comparable with some of the transmitted wavelengths of the ultra-wideband (UWB) time-domain pulses used. A system illuminating the objects under test by a subnanosecond UWB pulse has been built. An array of receiving antennas receives the scattered pulses that contain information about the shape, the size, and the dielectric or related material properties of the objects. Multivariate analysis is applied to separate geometric effects from those due to the dielectric properties. Results are shown for two measurement series determining the amount of carbon and weight or the dielectric constant of the objects under test, independent of their shape, size, and orientation. Furthermore, a classification algorithm is applied, separating the objects into geometrical classes independent of all other varied parameters.

Multiparameter microwave sensors for determining composition or condition of substances

A multiparameter microwave sensor is introduced that is capable of monitoring the percentage of constituents in composite dielectrics like foodstuffs. Results are demonstrated for so called artificial meat and for fish. The method applies principal component analysis (PCA) and principal component regression (PCR), both known from other disciplines like chemometrics. A prototype instrument operating in the frequency domain is presented showing excellent results. Also time domain measurements are suggested, which prove for the first time the applicability of the PCA and PCR signal processing scheme on short pulses with ps- and ns-risetimes.

Rapid monitoring of selected food properties using microwave dielectric spectra

In this paper, a novel microwave measurement approach is presented, which is capable of determining selected food properties from the dielectric spectrum. Such properties could be the water content, a possible amount of additionally added water, the content of conducting ions or the percentage of other constituents, having a noticeable influence on the effective complex permittivity versus frequency. The approach is based on measured dielectric data across a significant bandwidth of one or two octaves (or more), and on data analysis using the multi-variate statistical method of Principal Component Analysis (PCA) and Principal Component Regression (PCR). The prototype of a dedicated microwave instrument is described and as an experimental example the viability of the new approach is demonstrated by the exact determination of the percentage of deliberately added water in fruit juices.

Non-contacting moisture sensing using a dedicated UWB time domain instrument

Abstract This paper presents a method for the moisture determination of small and irregularly shaped objects independent from their shape and orientation. The objects under test are illuminated by UWB-pulses and the scattered pulses are received by an array of antennas. A dedicated measurement set-up and time domain transmission instrument is proposed. The scattered pulses contain information about the geometric as well as the dielectric properties. In order to separate this information multivariate calibration is applied. The time domain data is therefore subjected to principal component regression, partial least squares regression and an artificial neural network. All calibration methods deliver excellent performance. The moisture content of the objects can be determined with an accuracy of prediction of 0.69% while the range of moisture is within about 5% to 24%.

New UWB free-space method for the classification and characterization of dielectric objects

This paper presents a new approach for the accurate free-space characterization of irregularly shaped and arbitrarily oriented dielectric objects. The objects under test are illuminated by UWB-pulses and the scattered pulses are collected by an array of receiving antennas. The scattered pulses contain information about the geometrical properties as well as the dielectric properties; a multivariate calibration method is supposed to be able to separate these properties. A classification algorithm is applied prior to the multivariate calibration. It provides a classification into two classes, low or high permittivity. The statistical calibration method is then applied separately in each class. This leads to a significant improvement of the accuracy of the determination of the dielectric properties compared to processing without classification.