Determination of seed sowing quality by dotted-nesting method using video file processing technology

• Published in: E3S web of conferences Vol. 623; p. 4010
• Main Authors: Strygin, Sergei, Konkina, Viktoriya, Korobova, Irina, Rybachok, Maksim, Pustovarov, Nikita
• Format: Journal Article Conference Proceeding
• Language: English
• Published: Les Ulis EDP Sciences 01.01.2025
• Subjects: Coefficient of variation; Crop yield; Information technology; Nesting; Neural networks; Optimization; Planting; Seeding
• ISSN: 2267-1242; 2555-0403; 2267-1242
• DOI: 10.1051/e3sconf/202562304010

The research work presents a method for assessing the qualitative performance of a sowing machine using the dotted-nest sowing method. The analysis of the subject area was carried out, within which the object of optimization was described. The sowing of agricultural crops is considered one of the most important technological operations in crop cultivation, as it directly affects crop yields. The control of the sowing process and the detection of any malfunctions during it are investigated using information technology. An algorithm for determining the accuracy of sowing using the dotted-nest method is presented. Two indicators were considered as optimization criteria: the coefficient of variation of the time intervals between seed emission from the sowing disc and seed placement, which were minimized. Two parameters affecting sowing quality were selected as optimization variables: the rotation frequency of the sowing disc and the position of the seed ejector of the sowing unit. The results of the experiments and research have been processed in the form of video files showing the seeding process using the YOLO v8 neural network.