Study of the dimensional characteristics of pea seeds for the development and operation of agricultural machinery

The development of agricultural machinery structures occurs with the emergence of new knowledge, technologies for manufacturing machines (parts), structural, operational and materials which working bodies interact with. Grains and seeds of cultivated plants are ones of the most important materials for the development and operation of agricultural machines. Knowledge of their physical and mechanical properties makes it possible to rationally design and operate (adjust operating modes) sowing, harvesting, cleaning, loading and other machines. Significant physical and mechanical properties of seeds are dimensional characteristics. When researching and designing the sowing apparatus as an example, it is necessary to take into account the physical and mechanical properties, as well as the size of the seeds used for sowing. Dimensional characteristics are used to calculate the size and volume of the seed chamber of the sowing apparatus, the dimensions of the pasthrough windows of the hopper and apparatus, the coil or the sowing disc, the dosing element. Due to the increase in the acreage occupied by peas, there is a need to create new designs and improve existing ones of sowing apparatuses used for dosing pea seeds. Currently, the advantage of piece-by-piece dosing of pea seeds is undeniable, as this allows for a more rational placement of seeds over the field area, which ensures an increase in yield. Therefore, there is a need to develop sowing apparatuses for piece-by-piece dosing of pea seeds. In order to make rational decisions when designing devices, it is necessary to know the size of the seeds to be sown. Therefore, the department of «Technologies and means of mechanization of agriculture» conducted a study of the size of pea seeds of four varieties. The length, width and thickness of three hundred and fifty seeds of the Nordman, Lump, Slovan, Aksai Usatyi varieties zoned in the Zernograd district of the Rostov region were studied. Dimensional characteristics of datasets were obtained, processed and analyzed.