SOLUÇÃO ELETRÔNICA MICROCONTROLADA PARA A DETERMINAÇÃO DA DISTRIBUIÇÃO LONGITUDINAL DE SEMENTES DE MILHO

Abstract

Actually, the process of determining the longitudinal distance of seeds on the same planting line is manual and prone to failures. In the maize’s case, the distribution of seeds in inadequate distances lowers its productivity, influencing in the plants development, both by the maize’s root system, that doesn’t make up to the variation of the distances, like some other cultures do, and my the lower amount of sun radiation that the plants can absorb when plants are too close to each other. Considering the importance of knowing the longitudinal distance of seeds and that that reading is made manually, this dissertation presents a microcontrolled solution to be used along with a plantability track. The microcontroller used in the solution is an Atmega 328, part of an Arduino. The seed detection was made using an industrial infrared sensor, model DFRobot RB-DFR-49, with adjustable sensing distance, fixed perpendicularly to the track. With the developed solution added to the track, it was possible to obtain a precise reading from the distance between each seed, by counting the time between each seed, plus the known speed of the rolling track. That value is then registered on the developed solution and passed to a computer through an USB connection. By comparing to the manual mattering, the medium error obtained was 0,90cm, less than 0,5% in a 40cm distance, as used in maize. The validation of the developed solution, amount of detected double spacing and fail spacing, was made by comparing the results obtained by the solution with those obtained by manual testing, made by an specialist on those tests. By doing that, it was possible to notice that in tests with low amounts of double and fail spaces (6 and 5 in a test, and 6 and 3 in the second), the results where the same to the manual accounting. In tests with bigger amounts of errors (32 doubles, 50 fails), the result was slightly different (more 7 doubles and 28 fails, when comparing to manual testing), what evidences that the developed solution is more precise than the manual measuring method. Its believed that the solution can help in the selection of planting disks, and to obtain a better plant stand in the field, what brings better productivity. Keywords: Zea Mays, Agricultural Automation, Precision Agriculture.