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Schmilovitch, Z., Institute of Agricultural Engineering, Agricultural Research Organization, Volcani Center, PO Box 6, 50520 Bet Dagan, Israel
Shmulevich, I., Technion-Israel Institute of Technology, Faculty of Agricultural Engineering, Haifa, Israel
Notea, A., Technion-Israel Institute of Technology, Faculty of Industrial Engineering and Management, Haifa, Israel
Maltz, E., Institute of Agricultural Engineering, Agricultural Research Organization, Volcani Center, PO Box 6, 50520 Bet Dagan, Israel
Composition analysis by NIR spectrometry usually uses models that assume the sample to be homogeneous. However, agricultural fluid products are naturally heterogeneous, and in some cases of on-line sensing, it is very difficult to fulfill the homogeneity requirement, and some precautions are needed. The flow itself might create a non-uniform distribution of the measured ingredient concentrations across the cross-section of the flow. A modified discrete model was developed, which incorporates the concentration distribution of the ingredients. The effects of model parameters (number of layers and of iterations, valid ranges of absorbency and specular reflectance factors) were studied and evaluated. Samples of fresh raw milk were tested, in order to create a known distribution of the fat content in the sample, and were scanned by a NIR spectrometer. In the case of monotonic variation, along the sample, of the concentration of the measured ingredient (fat), the effect on the measured spectrum was similar to that of changes in the average concentration of a homogeneous sample. Comparison of the errors predicted by the model with the result of NIR measurements in heterogeneous conditions of fresh raw cow's milk gave close correlation in their direction and their relative size. This created the basis for a technique to evaluate other fluids, in which the distribution of the concentration of the measured ingredient could be evaluated and incorporated in the model simulations. (C) 2000 Elsevier Science Ireland Ltd.Composition analysis by NIR spectrometry usually uses models that assume the sample to be homogeneous. However, agricultural fluid products are naturally heterogeneous, and in some cases of on-line sensing, it is very difficult to fulfill the homogeneity requirement, and some precautions are needed. The flow itself might create a non-uniform distribution of the measured ingredient concentrations across the cross-section of the flow. A modified discrete model was developed, which incorporates the concentration distribution of the ingredients. The effects of model parameters (number of layers and of iterations, valid ranges of absorbency and specular reflectance factors) were studied and evaluated. Samples of fresh raw milk were tested, in order to create a known distribution of the fat content in the sample, and were scanned by a NIR spectrometer. In the case of monotonic variation, along the sample, of the concentration of the measured ingredient (fat), the effect on the measured spectrum was similar to that of changes in the average concentration of a homogeneous sample. Comparison of the errors predicted by the model with the result of NIR measurements in heterogeneous conditions of fresh raw cow's milk gave close correlation in their direction and their relative size. This created the basis for a technique to evaluate other fluids, in which the distribution of the concentration of the measured ingredient could be evaluated and incorporated in the model simulations.
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Near infrared spectrometry of milk in its heterogeneous state
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Schmilovitch, Z., Institute of Agricultural Engineering, Agricultural Research Organization, Volcani Center, PO Box 6, 50520 Bet Dagan, Israel
Shmulevich, I., Technion-Israel Institute of Technology, Faculty of Agricultural Engineering, Haifa, Israel
Notea, A., Technion-Israel Institute of Technology, Faculty of Industrial Engineering and Management, Haifa, Israel
Maltz, E., Institute of Agricultural Engineering, Agricultural Research Organization, Volcani Center, PO Box 6, 50520 Bet Dagan, Israel
Near infrared spectrometry of milk in its heterogeneous state
Composition analysis by NIR spectrometry usually uses models that assume the sample to be homogeneous. However, agricultural fluid products are naturally heterogeneous, and in some cases of on-line sensing, it is very difficult to fulfill the homogeneity requirement, and some precautions are needed. The flow itself might create a non-uniform distribution of the measured ingredient concentrations across the cross-section of the flow. A modified discrete model was developed, which incorporates the concentration distribution of the ingredients. The effects of model parameters (number of layers and of iterations, valid ranges of absorbency and specular reflectance factors) were studied and evaluated. Samples of fresh raw milk were tested, in order to create a known distribution of the fat content in the sample, and were scanned by a NIR spectrometer. In the case of monotonic variation, along the sample, of the concentration of the measured ingredient (fat), the effect on the measured spectrum was similar to that of changes in the average concentration of a homogeneous sample. Comparison of the errors predicted by the model with the result of NIR measurements in heterogeneous conditions of fresh raw cow's milk gave close correlation in their direction and their relative size. This created the basis for a technique to evaluate other fluids, in which the distribution of the concentration of the measured ingredient could be evaluated and incorporated in the model simulations. (C) 2000 Elsevier Science Ireland Ltd.Composition analysis by NIR spectrometry usually uses models that assume the sample to be homogeneous. However, agricultural fluid products are naturally heterogeneous, and in some cases of on-line sensing, it is very difficult to fulfill the homogeneity requirement, and some precautions are needed. The flow itself might create a non-uniform distribution of the measured ingredient concentrations across the cross-section of the flow. A modified discrete model was developed, which incorporates the concentration distribution of the ingredients. The effects of model parameters (number of layers and of iterations, valid ranges of absorbency and specular reflectance factors) were studied and evaluated. Samples of fresh raw milk were tested, in order to create a known distribution of the fat content in the sample, and were scanned by a NIR spectrometer. In the case of monotonic variation, along the sample, of the concentration of the measured ingredient (fat), the effect on the measured spectrum was similar to that of changes in the average concentration of a homogeneous sample. Comparison of the errors predicted by the model with the result of NIR measurements in heterogeneous conditions of fresh raw cow's milk gave close correlation in their direction and their relative size. This created the basis for a technique to evaluate other fluids, in which the distribution of the concentration of the measured ingredient could be evaluated and incorporated in the model simulations.
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