Detecção precoce e predição da perda de matéria seca e qualidade de grãos de milho em tempo real durante o transporte ; Early detection and prediction of dry matter loss and quality of corn grains in real time during transport

Taking into account that the transport of grains can be carried out over long distances and that the mass of grains during transport, many times, has high contents of water, there may be risks of heat and moisture transfer and heating of the mass of grains, proving quanti-qualitative losses. Thus, this study aimed to validate a probe system for monitoring temperature, relative humidity and diffusion of the concentration of carbon dioxide in the mass of corn grains, in real time, during transport, as a function of different initial water contents (12, 16 and 25% w.b.), to detect early dry matter losses and predict possible changes in the physical quality of the grains. Portable equipment was developed to monitor the grain mass during road transport. The equipment consists of an Arduino Mega 2560 microcontroller as a control core. The system's hardware included three digital sensors to detect air temperature and relative humidity, a non-destructive infrared sensor to detect CO2 concentration, real-time clock modules and a micro-SD card. The output data from the digital sensor, infrared sensor and modules were connected to the I/O communication terminals of the microcontroller which were responsible for physical communication, component integration and data calculation. The temperature and relative humidity sensors were fixed at three ends of a threaded bar and the CO2 sensor was fixed in the central part. The real-time clock module and the micro-SD card were packaged in a plastic back box. The software used on the Arduino board was programmed based on the C++ programming language, with most of the libraries provided by the platform. The Arduino IDE (Integrated Development Environment) was used to develop the embedded firmware for the Atmega 2560 microcontrollers. To monitor the mass of corn grains, simulating a transport condition, a box was experimentally made with plywood material. in the dimensions of (0.2 x 0.2 x 1.8 m). The probe was inserted into the grain mass profile to assess the detection level of ...