Potential of NERICA Production in Uganda

Potential of NERICA Production in Uganda
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乌干达 NERICA 生产潜力

DOI:
10.11248/jsta.54.44
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发表时间:
2010
期刊:
Tropical agriculture and development
影响因子:
--
通讯作者:
M. Kikuchi
M. Kikuchi
中科院分区:
--
文献类型:
--
作者:
H. Fujiie;A. Maruyama;M. Fujiie;N. Kurauchi;M. Takagaki;M. Kikuchi

文献摘要

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非洲新稻有望成为撒哈拉以南非洲地区绿色革命的推动力,那里的大多数农民都在从事风险大、不稳定、依赖降雨的高地农业。在这个关键时刻,要问的一个关键问题是,如果在该区域的高地农业中引进非洲新稻,如果不仅考虑到更高的产量,而且考虑到更高的风险,非洲新稻的真实的潜力是什么。本文试图通过研究非洲新稻的引进如何改变农民的最佳种植模式来回答这个问题。我们使用利润优化模型,以确定最佳的土地利用三个主要的主食作物,即非洲新稻,玉米和小米,种植在乌干达,大多数作物种植是在坡地上进行的特点乌干达农业。模拟结果表明,坡上坡下的最佳种植模式存在很大差异,这是因为坡上坡下的非洲新稻产量风险差异很大。在斜坡的较低部分,种植非洲新稻的面积迅速增加是可取的,非洲新稻具有显着的优势。在山坡的上部,在玉米和小米种植面积之外增加非洲新稻种植面积不是最佳选择。迄今为止,非洲新稻的传播政策忽视了关于农田位置的信息,如果考虑到这些信息,就可以使这些政策更加有效。
NERICA (New Rice for Africa) is expected to be a driving force of the green revolution in Sub-Saharan Africa, where most farmers practice risky, unstable upland agriculture that depends on rainfall. At this juncture, a critical question to be asked is what the real potential of NERICA is, if introduced in upland farming in the region, and if not only higher yield but also higher risks are taken into account. In this paper, we try to give an answer to this question through studying how the introduction of NERICA changes farmers’ optimum cropping patterns. We use a profit optimization model to determine optimum land use for three major staple crops, ie, NERICA, maize and millet, planted in Uganda, where most crop cultivation is carried out on sloping fields that characterize Ugandan agriculture. The results of simulations show that the upper and lower parts of slopes have very different optimum cropping patterns because the risk associated with NERICA yield is sharply different between the two parts. A rapid increase in area planted to NERICA is desirable in the lower parts of slopes, where NERICA has significant advantage. In the upper parts of slopes it is not optimal to increase area planted to NERICA beyond the areas planted to maize and millet. NERICA dissemination policies, which have thus far overlooked information about the locations of farm fields, could be made more effective by taking such information into account.