Open AccessEvaluation Model of Grain System Based on AAQN Index System
Author(s) -
Ying Ge,
Wen Chen,
Yinxuanye Zhang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2006/1/012024
Subject(s) - food security , food systems , index (typography) , food quality , environmental economics , resilience (materials science) , equity (law) , profitability index , food processing , sustainability , business , environmental resource management , computer science , economics , agriculture , food science , ecology , biology , finance , physics , world wide web , political science , law , thermodynamics
According to UN FAO, global food production in 2019 reached 2.722 billion tons, showing high profitability and efficiency levels [1] . However, while we enjoy fresh and nutritious food, people in Africa and Central Asia are suffering from starvation and nutritional deficiencies. Despite the high profitability and efficiency levels, the existing food systems are challenged by equity and sustainability problems. In order to assess the current food system and propose a rational optimization approach, we propose a linear and hierarchical food system based on the priorities of food flow and distribution. To quantify food security based on food systems, we develop the AAQN Index system to measure the affordability, availability, quality& safety, and natural resources& resilience of a food system based on the Global Food Security Index (GFSI). We select 68 indicators and calculate the indicator weights by combining the entropy weight method (EWM) with GFSI. By systematically clustering the calculated results, we classified the food systems of 113 countries/regions into: excellent, normal, and poor. Then, we adjust the priorities of the Indian food system, a poor food system, to reveal the differences before and after optimization. Finally, by predicting the future AAQN Index of Indian through Grey Relational Analysis.