一种可扩展的方法,以改善CSA针对小农的做法
Cyrus Muriithi1, Caroline Mwongera1, Wuletawu Abera1
1The Alliance of Bioversity International and International Center for Tropical Agriculture (CIAT), Duduville Campus Off Kasarani Road P.O. Box 823-00621, Nairobi, Kenya.
Heliyon
|October 9, 2023
概括
气候智能农业 (CSA) 战略可以提高小规模农民的抵御力. 这项研究确定了塞内加尔的不同农民类型,使得CSA干预措施能够精确地针对改善土壤肥力和产量.
科学领域:
- 农业科学 农业科学
- 适应气候变化 适应气候变化
- 发展研究 发展研究 研究
背景情况:
- 气候变化,人口增长和土地退化带来的不断增加的压力对发展中国家的农业系统构成了挑战.
- 气候智能农业 (CSA) 对于提高小农农户的抵御能力至关重要,但准确的目标仍然很困难.
- 五大资本模型为评估农民资产 (人力,社会,物质,自然,金融) 提供了一个框架.
研究的目的:
- 识别和分类塞内加尔小农农业系统的不同类型.
- 分析社会经济和生物物理 (SEBP) 因素和资本资产在塑造这些类型学中的作用.
- 确定CSA采用的概率,并为不同农民群体确定合适的技术.
主要方法:
- 混合数据 (FAMD) 的因子分析,以整合SEBP和资本数据.
- 围绕Medoids (PAM) 划分集群分析以确定农民类型.
- 试点回归模型CSA采用概率,并确定技术需求.
主要成果:
- 根据SEBP因素和位于Tambacounda和Sedhiou地区的地理位置,确定了四种不同的农民类型.
- 在农民的个人资料和可用资本资产之间观察到显著的技术不匹配.
- 类型学在收入水平和气候挑战严重程度上有所不同,这表明对CSA的需求不同.
结论:
- 精确的CSA干预目标对于提高土壤肥力,作物产量和营养质量至关重要.
- 根据特定农民类型和当地农业动态量身定制CSA战略,优化干预的有效性.
- 解决技术不匹配对于成功采用CSA和加强小农的弹性至关重要.
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