Jon Tschudi

Non-contact transflectance near infrared imaging for representative on-line sampling of dried salted coalfish (bacalao)

This paper describes a multi-spectral imaging near infrared (NIR) transflectance system developed for on-line determination of crude chemical composition of highly heterogeneous foods and other bio-materials. The system was evaluated for moisture determination in 70 dried salted coalfish (bacalao), an extremely heterogeneous product. A spectral image cube was obtained for each fish and different sub-sampling approaches for spectral extraction and partial least squares calibration were evaluated. The best prediction models obtained correlation R2 values around 0.92 and root mean square error of cross-validation of 0.70%, which is much more accurate than todays traditional manual grading. The combination of non-contact NIR transflectance measurements with spectral imaging allows rather deep penetrating optical sampling as well as large flexibility in spatial sampling patterns and calibration approaches. The technique works well for moisture determination in heterogeneous foods and should, in principle, work for other NIR absorbing compounds such as fat and protein. A part of this study compares the principles of reflectance, contact transflectance and non-contact transflectance with regard to water determination in a set of 20 well-defined dried salted cod samples. Transflectance and non-contact transflectance performed equally well and were superior to reflectance measurements, since the measured light penetrated deeper into the sample.

On-line determination and control of fat content in batches of beef trimmings by NIR imaging spectroscopy

An NIR imaging scanner was calibrated for on-line determination of the fat content of beef trimmings. A good calibration model was obtained for fat in intact beef (R=0.98, RMSECV=3.0%). The developed model could be used on single pixels to get an image of the fat distribution, or on the average spectrum from each trimming/portion of trimmings passing under the scanner. The fat model gave a rather high prediction error (RMSEP=8.7%) and a correlation of 0.84 when applied to 45 single trimmings with average fat content ranging from 1.6 to 49.3% fat. Test measurements on streams of trimmings making up batches varying from 10 to 24 kg gave a much lower prediction error (RMSEP=1.33%). Simulations based on true measurements indicate that the RMSEP decreases with increasing batch size and, for the present case, reached about 0.6% for 100 kg batches. The NIR scanner was tested on six batches of intact trimmings varying from 145 to 210 kg and gave similar fat estimates as an established microwave system obtained on the ground batches. The proven concept should be applicable to on-line estimation of fat in trimmings in order to determine the batch fat content and also to control the production of batches to different target fat levels. A possible requirement for the concept to work properly is that the trimming or layer of trimmings on the belt is not too thick. In this study maximum thickness was about 8 cm. Thicker trimmings might be measured, but careful hardware adjustments are then required.

On-Line Fat Content Classification of Inhomogeneous Pork Trimmings Using Multispectral near Infrared Interactance Imaging

A novel system for on-line measurement of fat content in inhomogeneous pork trimmings is presented. The system allows near infrared (NIR) energy to interact with the meat using non-contact optics while it is travelling in large plastic boxes on a conveyor belt. A comparison was made between the log of the inverse of the interactance NIR spectra [log(1/T)], standard normal variate (SNV) and extended multiplicative signal correction (EMSC) as techniques for the correction of physical light scattering due to colour and textural differences, height variation and temperature fluctuations, depending on whether the meat was warm-cut or cold-cut. EMSC gave the best prediction results; a robust partial least squares regression using two factors resulted in a root mean square error (RMSEP) of 1.9% on 20 kg batches of inhomogeneous meat trimmings. The model was fully tested twice in an on-line environment at a slaughter house and performed with a RMSEP of 3.4% for a fat range of 8–55% in the first industrial trial and 2.82% in the second industrial trial.

Near-Infrared (NIR) Interactance System for Non-Contact Monitoring of the Temperature Profile of Baked Liver Pâté

This article investigates the possibility of using non-contact interactance as a method for profiling the temperature in a processed meat product (liver pâté) as it comes out of the oven. The application was defined by an industrial partner, Nortura SA, Tønsberg, Norway, where more control of the cooking process was desired. The optical system employs low spectral resolution to achieve high enough signal-to-noise ratio (SNR) to depths of 2 cm into the product. The partial least squares (PLS) method was applied to interactance spectra in the region 760–1040 nm and a root mean square error of 1.52 °C was obtained. The model was tested on five different validation sets spread over 18 months and a root mean square error of prediction of 2.66 °C was achieved. The output of this model was based on the weighted average of two temperatures in the first 2 cm of the liver pâté, one of which is the core temperature. A comparison was also made with two other models: a model based on the core temperature alone and a model based again on the weighted temperature but using the shorter wavelength range of 905.5–1047 nm. These two models gave less favorable prediction errors.

Measuring Water Holding Capacity—A Comparison between a Miniature near Infrared System and an Energy Dispersive X-Ray Scattering System

The results presented here describe a comparative study on pork loins with drip loss varying from 0.25% w/w to 10.69% w/w. Thirty samples were measured using both near infrared (NIR) interactance and X-ray scattering. Partial least squares regression was used to build calibration models for each method. Results show that the correlation for the calibration model between NIR interactance and drip loss was R2 = 0.47 (leaving out three outliers) while that for X-ray and drip loss was R2 = 0.72 (leaving out three outliers).

Wireless Infrared Gas Sensor

Infrared hydrocarbon gas detectors are essential for safety, but the requirement for cabled power complicates installation. A new low-power optical design based on a micro-opto-electromechanical system gives several years of reliable battery operation.

Quasi-imaging spectrometer with programmable field of view and field of illumination

8 Introduction t his article details the development of a robust, quasi-imaging spectrometer that reduces the effects of stray light from the background and nearby objects. In an industrial setting, samples are seldom well-ordered, making accurate spectral measurements more challenging than in a controlled, laboratory setting. objects may vary in size, shape and reflectance properties. Furthermore, background levels can fluctuate when, for example, measuring unordered objects in a bin or objects with unknown positions in a scene. thorough analysis of the measurement situation requires knowledge of spatial resolution, spectral resolution, wavelength band of interest and so forth. the solution to such problems may be a scanning point measurement or some kind of imaging spectrometer, often including a dispersive element, a camera and a scanning action; this latter may be achieved by either using a mirror device, such as a Digital Micro-mirror Device (DMD), or by moving the sample itself (the latter being more time-consuming). the system described here includes two digital micro-mirror devices (DMD) to dynamically select both the field of illumination (FoI) and the field of view (FoV) in a scene as shown in Figure 1. A DMD is an array of micro mirrors with two angle positions. the illumination DMD selects the illumination pattern, which can consist of sub-millimetre areas. the detection DMD selects the detector type; here a camera or spectrometer. the system can be programmed to operate in both reflection and remote interactance modes for increased flexibility. In Figure 1, the system is looking at an apple on a reflective surface. the entire image is illuminated in order to locate the region of interest, in this case the apple, and this image is sent to the camera (light path represented by dashed arrows). After this, the field of illumination is reprogrammed to illuminate only the apple (solid arrows), avoiding stray light from both the reflective surface and the apple’s green leaf. the detected light can again be sent to either the camera or spectrometer (in this case the spectrometer). Some preliminary results were conducted in three areas that could be considered advantageous as a result of the use of DMDs in an imaging/spectrometry system: 1) reference banking—to correct for variation across the image; 2) 3-D measurements for improved region-of-interest location and reference-bank selection; and 3) remote interactance measurements—for increased absorption information.

Low Cost “Laserless” FTIR Spectrometer with Resolution Better Than 0.5 cm-1

We have designed a FTIR instrument where the traditional He-Ne reference laser is replaced by a low-cost linear encoder. We achieve an RMS sampling error of less than 50nm by oversampling both the interferogram and the encoder signal and then resampling the interferogram using a correction table for the encoder.