Progress and Prospective in the Development of Stored Grain Ecosystems in China: From Composition, Structure, and Smart Construction to Wisdom Methodology

Yunshandan Wu, Wenfu Wu, Kai Chen, Ji Zhang, Zhe Liu and Yaqiu Zhang ()
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Yunshandan Wu: College of Biological and Agricultural Engineering, Jilin University, Changchun 130022, China
Wenfu Wu: College of Biological and Agricultural Engineering, Jilin University, Changchun 130022, China
Kai Chen: College of Biological and Agricultural Engineering, Jilin University, Changchun 130022, China
Ji Zhang: College of Biological and Agricultural Engineering, Jilin University, Changchun 130022, China
Zhe Liu: College of Biological and Agricultural Engineering, Jilin University, Changchun 130022, China
Yaqiu Zhang: College of Biological and Agricultural Engineering, Jilin University, Changchun 130022, China

Agriculture, 2023, vol. 13, issue 9, 1-13

Abstract: 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.

Keywords: food security; stored grain ecosystems; Eco-concept; multi-field/re-coupling structure; smart construction; grain storage; wisdom methodology; mechanism and data; smart grain systems; digital twin (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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