Drying and storage methods are fundamental for maintaining the grain quality until processing. Therefore, the aim of this study was to evaluate the associations of the drying temperature with storage systems and conditions as a strategy for preserving the quality of maize grain postharvest on laboratory and field scales. An increase in temperature accelerated the reduction in grain moisture, but increased the deterioration. The wetting during the storage period reduced the grain quality. Hermetic and aerated storage systems maintained the chemical quality of the grains. The control with healthy and whole corn dried at 80 °C and stored in silos with natural aeration provided a satisfactory quality, equivalent to those of controlled drying and storage under airtight conditions and at low temperatures. Different conditions of drying and storage of corn on the laboratory and field scales were evaluated, which provides an appropriate management of these operations to maintain the grain quality.
The use of silo and raffia bags for the temporary grain storage has been increasing in recent years. However, the methods for monitoring a stored product are limited to visual inspections and sampling. Thus, this research aimed to real-time equilibrium moisture content monitoring to predict grain quality of corn stored in different conditions in silo and raffia bags using wireless sensor network prototype, Internet of Things (IoT) platform, and neural network algorithms. Experiments were conducted using corn grain with two initial water contents of 13% and 18% (w.b.), three storage environments with temperatures of 30, 23, and 17 C, and two types of packaging, that is, silo and raffia bags, for a 3-month storage evaluation. During the monitoring
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