Food security is intrinsically linked to maintaining optimal physical health and promoting active lifestyles. Stored Grain Ecosystems (SGEs) are complex systems comprising a range of grains, microorganisms, and environmental elements. To ensure sustainable grain storage and promote food-friendly SGEs, careful regulation and monitoring of these factors are vital. This review traces the evolution of the Eco-concept of stored grain in China, focusing on micro- and macro-structural composition, the Multi-field/Re-coupling structure, and Smart Construction of SGEs, while introducing the four development lines and Wisdom Methodology of SGEs. The current status and challenges of SGEs in China are also discussed. The Eco-concept of stored grain in China has progressed through the initial exploration period, formation and practice periods, and has now entered its fourth stage, marked by a shift to include interactions of multiple biological fields. This evolution extends beyond the traditional binary relationship and offers emerging technologies greater scope for scientific and intelligent theoretical analysis of grain storage practices. The Wisdom Methodology employs a multifaceted, Mechanism and Data-driven approach, incorporating four driving methods, and is now widely recognized as a leading strategy for researching Smart Grain Systems. Digital Twin technology enables precise simulations and mappings of real-world SGEs in a virtual environment, supporting accurate assessments and early warnings for issues concerning grain conditions. Driven by Mechanism and Data, Digital Twin solutions are a pioneering trend and emerging hotspot with vast potential for enhancing the intelligence and wisdom of future grain storage processes. Overall, this review provides valuable guidance to practitioners for advancing high-quality Smart Grain Systems, enhancing sustainable and intelligent grain storage practices.

Grain moisture is one of the key indexes of grain quality, and acquiring an accurate moisture value is critical for grain storage security. However, the sensors used in the traditional methods for testing grain moisture are based on capacitance, microwave, or radio-frequency methods and still exhibit low accuracy and instability because they are susceptible to the temperature, moisture, and micro gas flow of the air in the granary. In this study, we employed a new design for a radio-frequency moisture sensor for grain. The structure of the sensor is based on the difference method and consists of two parallel probe units. These units are at different distances to the tested grain, resulting in different sensitivities in the moisture measurements. Through a phase difference operation on the test signals, the disturbance variable was reduced. The specific size of the two parallel probes was confirmed by calculation and simulation using High Frequency Structure Simulator (HFSS) software. The simulated and measured parameters of a prototype sensor agreed well. The linear relationship yielded a correlation coefficient of 0.9904, and the average error of the moisture testing was within ±0.3% under the conditions where the VSWR (voltage standing wave ratio) value and return losses were 1.5896 and −20 dB, respectively, at a measured central frequency of 100 MHz. The results indicate that the performance of the sensor was excellent.