Prediction on the Farmland Demand of Yunnan Province in 2020 Based on Food Security

According to the cultivated area and grain yield during 1996- 2008 and adopting the prediction method of farmland demand based on food security, five indexes, including the cultivated area, grain sown area, yearly food yield per unit area, total population and per capita grain yield, are selected to analyze and predict the farmland demand in Yunnan Province in 2020. As the prediction results of each index show, the total population of Yunnan Province in 2020 will reach 51 464 000, significantly higher than the upper bound (50 million); the per capita food demand of Yunnan Province in 2020 will be 400kg below the bottom line of the well-off type; food self-sufficient ratio will be respectively given the value of 100%, 95% and 90% in three schemes; the prediction will be conducted with the yearly food yield per unit area at an average annual growth rate of 2.5% and 3.0% in two schemes; the rate of grain sowing in 2010 is determined to be 66%. As the prediction results of farmland demand show, there are totally 6 schemes about farmland demand in Yunnan Province obtained through analysis, among them, schemeⅠis difficult to achieve, the prediction results of scheme Ⅳ, Ⅴ and Ⅵ are relatively low, which do not conform to the state policies and regulations to protect farmland and are also not conductive for ensuring the food security; schemeⅡ and Ⅲ are close to each other, but scheme Ⅲ obtains better prediction results and determines the farmland demand of Yunnan province in 2020 based on food security to be 5.9 million so as to ensure the provincial food security and realize the “red line” of basic provincial food self-sufficiency.


Subject(s):
Issue Date:
2010-03
Publication Type:
Journal Article
Record Identifier:
http://ageconsearch.umn.edu/record/93651
PURL Identifier:
http://purl.umn.edu/93651
Published in:
Asian Agricultural Research, 02, 03
Page range:
58-61
Total Pages:
4




 Record created 2017-04-01, last modified 2018-11-28

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