A b s t r a c t . Image analysis is widely used for monitoring seeds during germination, and it is often the final phase of germination that is subjected to the greatest attention. However, the initial phase of germination (the so-called imbibition) also exhibits interesting behaviour. This work shows that image analysis has significant potential in the imbibition. Herein, a total of 120 seeds were analysed during germination tests, and information about seed size and shape was stored and analysed. It was found that the imbibition can be divided into two newly defined parts. The first one ('abrupt imbibition') consists mainly of the swelling of the seed embryo part and lasts approximately one hour. The second one, referred to as 'main imbibition', consists mainly of spatial expansion caused by imbibition in the other parts of the seed. The results presented are supported by the development of seed cross area and shape parameters, and by direct observation.

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Moisture content is one of the most important parameters related to the quality of wood chips that affects both the calorific and economic value of fuel chips. For industrial applications, moisture content needs to be detected quickly. For this purpose, various indirect moisture content measurement methods (e.g., capacitance, NIR, microwave, ECT, X-ray CT, and nuclear MR) have been investigated with different results in the past. Nevertheless, determining wood chip moisture content in real time is still a challenge. The main aim of this article was therefore to analyze the dielectric properties of wood chips at low frequencies (10 kHz–5 MHz) and to examine the possibility of using these properties to predict wood chip moisture content and porosity. A container-type probe was developed for this purpose. The electrical capacitance and dissipation factor of wood chips with different moisture content was measured by an LCR meter at 10 kHz, 50 kHz, 100 kHz, 500 kHz, 1 MHz, and 5 MHz frequencies. Wood chip porosity was also measured using a gas displacement method. Linear models for moisture content and porosity prediction were determined by backward stepwise linear regression. Mathematical model was developed to better understand the physical relationships between moisture content, porosity, and electrical capacitance. These models were able to predict the moisture content of observed quantities of wood chips with the required accuracy (R2 = 0.9−0.99). This finding opens another path to measuring the moisture content and porosity of wood chips in a relatively cheap and fast way and with adequate precision. In addition, principal component analysis showed that it is also possible to distinguish between individual wood chip fraction sizes from the information obtained.

The objective of this paper was to test the suitability of Doppler microwave radar for the detection of wild animals hidden in grassland in front of the harvester. The ability of Doppler radar HB100 sensor to detect a dog or a human person hidden behind different types of crops was tested in laboratory conditions. Relative movement between the radar and the observed object was secured by the assembly acting as mathematical pendulum. The radar always moved in front of different crop samples (arranged in two or one line). The dog or human person was situated behind the crop. In five out of seven cases, the sensor was able to detect the human person. Only in two out of seven cases, the sensor was able to detect the dog. Nevertheless, it can be concluded that microwave radar sensor can be a useful device for detection of wild animals in the crop. Next research is needed in order to better explain the influence of disturbing factors on the measurements.

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