Forest regeneration by means of seedlings grown in container nurseries is usually performed manually with the use of the standard dibble bar or the tube dibble. Manual placement of a large number of seedlings in the soil requires a lot of work. Manual removal of the soil cover and digging the soil in spots with a diameter of 0.4 m requires, under average conditions, about 38 man-hours/ha, while planting with a dibble bar requires about 34 man-hours/ha. Addi-tional work time is needed to carry seedlings over an area that is being afforested. At present, forestry does not have automatic planters that would enable the establishment of forest cul-tures. The aim of the paper is to present the concept of an autonomous robot and an innovative technology of performing forest regeneration and afforestation of former agricultural and re-claimed areas. The paper also presents the design solutions of the key working unit, which is a universal, openable dibble, cooperating with a three-toothed shaft to prepare a planting spot. The solution proposed enables continuous operation of the machine, i.e. without the need to stop the base vehicle.

This research estimates carbon sink and allocation in above- and below-ground biomass of a 12-year-old willow coppice plantation on fluvisol soil near the Vistula River (southern Poland). The plantation showed high C sink potential and sequestration rates. C sequestration by above-ground biomass was estimated at 10.8 Mg C ha −1 a −1 . Accumulation in coarse roots was estimated at 1.5 Mg C ha −1 a −1 and in fine roots at 1.2 Mg C ha −1 a −1 . Total C sequestered (above-ground biomass, coarse roots and fine roots) was estimated at 13.5 Mg C ha −1 a −1 . These results confirm the potential of fast-growing plantations of willow to mitigate, over a short time span, the effects of high CO 2 concentrations.

EU forestry does not currently have automatic planters, hence the project proposes to develop an innovative technology in which the key role will be played by an autonomous planter designed for establishing forest cultures and afforestation of former farmland and reclaimed areas with the use of seedlings with a covered root system (grown in container nurseries). The device will have a self-levelling traction system, a control system with a satellite navigation module to support autonomous navigation and planting site selection, a mechanism of planting spot preparation, a planting unit, an intelligent robotic arm to feed seedlings from containers to the planting unit according to a given algorithm, a container storage unit with an automated feeder, a drive unit with an electro-hydraulic control system, a control module, and a wireless remote control system. The autonomous planter will significantly reduce the cost and machine inputs during establishing forest cultures and afforestation of former farmland and reclaimed areas with the use of seedlings with a covered root system, and thus perfectly fits into the assumptions of agriculture 4.0.

The goal of the research described in the article was to develop the device for the automatic scarification of acorns and computer vision-based assessment of their viability. The color image of the intersection of the tissue of cotyledons was selected as a key feature for separating healthy seeds from the spoiled ones. Because the device is being designed for the diagnosis of high volume of seeds aiming at producing high-quality seedlings, several assessment criteria of the overall design of the automaton are being assessed. The basic one is the overall accuracy of viability recognition. The other refers to particular functions implemented in the model of the device being described.

Abstract The objective of the paper was to determine fuel consumption on elimination of the energy willow plantation with current mechanical methods with the use of the machine research model. The paper covers investigations of four machine units. The lowest fuel consumption (142.6 l∙ha−1) with the use of Meri Crusher MJS-2.0) did not ensure effectiveness of operation of this unit. Efficiency of elimination of the plantation in this case is only 36.4%. On the other hand, the highest consumption of diesel oil (776.4 l∙ha−1) was reported for FAO FAR model FV 4088, and the effectiveness of elimination was not satisfactory and it was 57.0%. The highest effectiveness of elimination of the plantation was reported for the model of a new machine. Fuel consumption in this case was 535.7 l∙ha−1 and the willow plantation elimination effectiveness was the highest and it amounted to 94.8%.

Energy willow plantations are used in cycles of 20–25 years. After such a period of use, or earlier, plantations should be liquidated. In the case of arable land, liquidation of a plantation also means restoration of the original production properties of the soil. In particular, this means: permanent elimination of the possibility of plant regrowth from the above-ground rootstock and root systems and disintegration and mixing of the above-ground rootstock and root systems. The present authors undertook the task of developing a technology for stump removal on energy willow plantations that would have the advantage of lower energy consumption and execution costs than the technologies used so far. The development of a new machine for the disintegration of the above-ground rootstock and root systems requires recognition of the variability of their morphological parameters and their biomass. For that purpose, a head for planting trees was used to sample rootstocks and extract them, and a number of biometric parameters were determined with the division into thickness fractions. The average biomass of the root system of an energy willow shrub with a butt-end of approx. 10 cm in height was 3.1 kg, of which the butt-end and roots with a diameter greater than 30 mm accounted for more than 73%. The vertical and horizontal range of thick roots, which should be ground during plantation liquidation, is small and amounts to approx. 26 and 29 cm, respectively. This justifies the use of machines that work along strips of land during plantation reclamation.

Due to technological progress in forestry, seedlings with covered root systemsespecially those grown in container nurserieshave become increasingly important in forest nursery production. One the trees that is most commonly grown this way is the common oak (Quercus robur L.). For an acorn to be sown in a container, it is necessary to remove its upper part during mechanical scarification, and evaluate its sowing suitability. At present, this is mainly done manually and by visual assessment. The low effectiveness of this method of acorn preparation has encouraged a search for unconventional solutions. One of them is the use of an automated device that consists of a computer vision-based module. For economic reasons related to the cost of growing seedlings in container nurseries, it is beneficial to minimize the contribution of unhealthy seeds. The maximum accuracy, which is understood as the number of correct seed diagnoses relative to the total number of seeds being assessed, was adopted as a criterion for choosing a separation threshold. According to the method proposed, the intensity and red components of the images of scarified acorns facilitated the best results in terms of the materials examined during the experiment. On average, a 10% inaccuracy of separation was observed. A secondary outcome of the presented research is an evaluation of the ergonomic parameters of the user interface that is attached to the unit controlling the device when it is running in its autonomous operation mode.

Old trees fall for various reasons, so planting new oak trees is a must. Meanwhile not all acorns are useful and effective as oak seeds. Many of them will never germinate despite careful nurturing. Since breeding of cuttings is expensive – it is important to plant only the acorns that will grow into oak trees. As methods for mechanical separation of acorns using the classic features of distribution prompts are of low efficiency, we are trying to search for unconventional solutions. We have developed a model of an automaton with a video system for scarification of acorns and assessment of their viability . The article presents the resulting method for automating the process of oak seed scarification and visual analysis of the seed cross section in order to select the most promising acorns.

The basic principle of silviculture is the rational use of natural regeneration. The acceleration and equalisation of seed germination and an increase of the field seed germination ability are affected by seed scarification, which results in the destruction or weakening of the seed cover. Acorn scarification is performed manually, in the standing position, most often in adapted work stations, whose geometry is adjusted by the staff to their own anthropometric dimensions. An added value of acorn scarification consists in the ability to visually assess the health status of the cotyledons visible on the cross-section, making it possible to infer the potential use of a seed for sowing. However, due to the scope and duration of the activities involved, manual scarification is a process that is monotonous and physically as well as psychologically tiring for its performer. Automating of this process allows for effective replacement of human labour. The results obtained from the use of the vision system designed to determine the length and orientation of acorns may be considered satisfactory. The implementation of the seed orientation detection algorithm using the Harris detector was 90% accurate. Studies and analyses have shown that the process of acorn scarification has a positive effect on the later improvement of uniformity and acceleration of seedling emergence. In the case of seeds subjected to scarification, 83% of the acorns germinated within 4 to 6 weeks after sowing.

„Journal of Research and Applications in Agricultural Engineering” 2017, Vol. 62(1) Ryszard TADEUSIEWICZ, Jan SZCZEPANIAK, Józef WALCZYK, Paweł TYLEK 31 Joanna GRABSKA-CHRZĄSTOWSKA, Joanna KWIECIEŃ, Michał DROŻDŻ, Zbigniew BUBLIŃSKI, Ryszard TADEUSIEWICZ, Jan SZCZEPANIAK, Józef WALCZYK, Paweł TYLEK 1 AGH University of Science and Technology, Cracow, Poland e-mail: buba@agh.edu.pl ; drozdzmic@gmail.com ; asior@agh.edu.pl ; kwiecien@agh.edu.pl ; rtad@agh.edu.pl 2 Industrial Institute of Agricultural Engineering, Poznan, Poland e-mail: janek@pimr.poznan.pl 3 University of Agriculture in Cracow, Poland e-mail: rltylek@cyf-kr.edu.pl ; rlwalczy@cyf-kr.edu.pl Received: 2016-11-22 ; Accepted: 2017-01-24