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Algorithms have been developed for controlling the calibration and the measurement cycles of hyperspectral equipment. Special calibration and preprocessing methods were necessary to obtain suitable signal level and acceptable repeatability of the measurements. Therefore, the effect of the noise of NIR sensor was decreased, the signal level was enhanced and stability was ensured simultaneously. In order to investigate the properties of the number of objects suitable for statistical analysis, the enormous size of acquired hypercube (gigabytes per object) should be reduced by vector-to-scalar mathematical operators in real-time to extract the desired features. The algorithm developed was able to calculate the score of operators during scanning and the matrices were displayed as pseudo-images to show the distribution of the properties on the surface. The operators had to be determined by analysis of a sample set in preliminary experiments. Stored carrot was chosen as a model sample for investigation of the detection of moisture loss by hyperspectral properties. Determination of the proper operator on different tissues could help to analyze and model drying process and to control storage. Hyperspectral data of different carrot cultivars were tested under different storage conditions. Using improved measurement method the spectral parameter of the suitable operator described quite well the moisture loss of the different carrot tissues.

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The objective of the work reported here was to determine changes in the moisture content, firmness characteristics, color attributes and NIR absorbance of two carrot cultivars during storage. There was a definite loss in the moisture content that caused changes in the firmness. This result shows that carrot firmness is very sensitive to the moisture content. The firmness — especially the cutting force — is a good characteristic for predicting changes in carrot moisture content during storage. The color characteristics — a* and b* — showed a slight change in the function of the moisture content. However, these color characteristics are suitable for distinguishing the phloem and xylem parts of carrot cultivars. There were not found definite changes in the NIR absorbance as the function of the moisture content. Consequently, the specific cutting force and the impact stiffness coefficient are good characteristics of the carrot moisture content and the mass reduction during storage under non-ideal conditions.

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Progress in Agricultural Engineering Sciences
Katalin Badak-Kerti
Szabina Németh
Andreas Zitek
, and
Ferenc Firtha

In our research marzipan samples of different sugar to almond paste ratios (1:1, 2:1, 3:1) were stored at 17 °C. Reducing sugar content was measured by analytical method, texture analysis was done by penetrometry, electric characteristics were measured by conductometry and hyperspectral images were taken 6–8 times during the 16 days of storage. For statistical analyses (discriminant analysis, principal component analysis) SPSS program was used.

According to our findings with the hyperspectral analysis technique, it is possible to identify how long the samples were stored (after production), and to which class (ratio of sugar to almond) the sample belonged. The main wavelengths which gave the best discrimination results among the days of storage were between 960 and 1100 nm. The type of the marzipan was easy to distinguish with the hyperspectral data; the biggest differences were observed at 1200 and 1400 nm, which are connected to the first overtone of C-H bound, therefore correlate with the oil content. The spatial distribution of penetrometric, electric and spectral properties were also characteristic to fructose content.

The fructose content of marzipan is difficult to measure by usual optical ways (polarimetry, spectroscopy), but since fructose is hygroscopic, the spatial distribution of spectral properties can be characteristic.

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