布达区阿拉比卡咖啡生产中气候智能型农业实践的采用强度

Abdullahi Faisal Salad, Simon Zziwa, David Talengera, Lydia Nabatanzi, Olivia Makumbi, Vivian Najjuma, Marveen Nafula
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引用次数: 2

摘要

乌干达是世界上最大的咖啡生产国和出口国之一,也是非洲第二大咖啡出口国,但它继续受到气候变化的重大影响,包括不稳定的降雨变化和环境退化。本研究调查了Bududa地区阿拉比卡咖啡生产中气候智能型农业(CSA)实践采用强度的决定因素。采用横断面调查设计收集117名被调查者的数据,其中采用面对面问卷收集研究的定量数据。使用频率计数和百分比等描述性统计来描述咖啡农的特征。采用Tobit回归模型评估CSA实践采用强度的决定因素。结果显示,大多数农民(67.3%)几乎没有获得任何信贷,其中大多数农民(64.5%)从未获得过推广服务。大多数受访者高度采用阴影(71.7%),CBI(76%),覆盖物(61.5%),有机肥(89%),等高线沟(58.9%),覆盖作物(84.6%)和树桩(55.5%)的使用。Tobit回归分析显示,农户受教育程度、推广服务可及性和婚姻状况对农户采用CSA的程度分别有显著正影响(P≤0.01)、显著影响(P≤0.01)和显著影响(P≤0.05)。农业年限、获得信贷的机会、农场规模和农民年龄与CSA实践的采用强度呈负相关。总之,乌干达政府应该在咖啡农中加强推广采用CSA做法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adoption intensity of climate smart agricultural practices in arabica coffee production in Bududa District
Uganda is one of the largest producing and exporting countries of coffee in the world and second in Africa, but it continues to experience significant impacts of climate change, including erratic rainfall variability and environmental degradation. This research investigated the determinants of adoption intensity of Climate Smart Agricultural (CSA) practices in Arabica coffee production in Bududa district. A cross-sectional survey design was adopted to collect data from 117 respondents, where face to face questionnaire were used to collect the quantitative data of the study. Descriptive statistics such as frequency count and percentages were used to characterize coffee farmers. Tobit regression model was used to assess determinants of adoption intensity of CSA practices. Results showed that majority of the farmers (67.3%) hardly obtained any credit and majority of them (64.5%) never had access to extension services. Majority of the respondents highly adopted the use of shades (71.7%), CBI (76%), mulching (61.5), organic fertilizer (89%), contour trenches (58.9), cover crops (84.6), and stumping (55.5). Tobit regression analysis revealed that farmer’s level of education, access to extension services and marital status showed a positive and significant (P≤0.01), (P≤0.01), and (P≤0.05) influence on adoption intensity of CSA practices, respectively. Years of farming, access to credit, farm size, and farmer’s age showed a negative relationship with adoption intensity of CSA practices. In conclusion, the government of Uganda should intensify extension of adoption of CSA practices among coffee farmers.
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