Design of a Planting Module for an Automatic Device for Forest Regeneration

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. Additional 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 cultures. 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 reclaimed 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

Scots Pine Seedlings Growth Dynamics Data Reveals Properties for the Future Proof of Seed Coat Color Grading Conjecture

Seed coat color grading conjecture is also known as Pravdin’s conjecture. To verify the conjecture, we established a long-term field experiment. This data set included unique empirical data of Scots pine (Pinus sylvestris L.) container-grown seedlings produced from different seed color grades, outplanted on a post fire site in the Voronezh region, Russia. Variables were provided for 10 rows of 90 samples in each row. These data contribute to our understanding of seed germination and seedlings growth dynamics from size and color gradings of seeds. This structure is the future basis of the Forest Reproductive Material Library (FRMLib) and will be used for assisted migration and forest seed transfer