撒哈拉以南非洲地区以每年3％的人口增量在世界人口增长中处于领先地位。此外，大量使用农业土地维持人口导致土壤侵蚀增加，土壤肥力降低，从而大大降低了农业生产率。这就要求促进诸如农林复合经营的可持续农业系统。农林复合经营目标是为小农提供多种选择，以通过改善土壤肥力，增加粮食安全和收入多样化来提高作物生产力。尽管农民在热带地区使用各种创新技术，但尚未广泛采用。本文目标是研究肯尼亚西波科特农林复合经营的采用及其对玉米生产的影响。具体目标是：1.查明影响肯尼亚西波科特小农户采用农林复合经营的决定性因素；2.为了确定农林复合经营对肯尼亚西波科特的玉米生产力的影响。基于抽样家庭的社会经济，人口和农场特征，使用概率模型和K-means算法来分析影响农户采用农林复合经营决策因素。研究发现总产量，农场规模，扩展频率，非农收入，获得培训，获得信贷，获得运输设施，团体成员，进入市场，性别，距最近的贸易中心的距离以及家庭教育水平对农林复合经营的采用产生了重大影响。使用内生转换回归模型对影响进行估算，第二阶段的结果表明，诸如性别，农场规模，交通设施的可及性以及非农收入等变量对收养者和非收养者的产量产生了显着不同的影响。采纳可使小农户的玉米产量从 116公斤增加到 696公斤。因此，这项倡议很重要，因为它可以帮助小农户获得粮食并增加其收入。该项目的研究结果对于政策制定和农林复合经营采用的实施非常重要。

Sub-Saharan Africa leads in population growth in the world with a 3% annual population increment. Furthermore, the intensive use of agricultural land to sustain the population has led to increased soil erosion and reduced soil fertility, thus significantly decreasing agricultural productivity. This calls for the promotion of sustainable agricultural systems such as agroforestry technologies. The goal of agroforestry-based technologies is to provide smallholder farmers with options to increase crop productivity through improvements in soil fertility and increase food security and income diversification. Although farmers are using various innovations in the tropics, widespread adoption has not occurred. The broad objective is to study the adoption and impacts of agroforestry-based technologies on maize production in West Pokot, Kenya. The specific goals are: 1. To identify the determinant factors affecting the adoption of agroforestry-based technology among smallholder farmers in West Pokot, Kenya; 2. To determine the impact of agroforestry-based technology on maize productivity in West Pokot, Kenya. A probit model and K-means algorithm were used to analyze the factors affecting farmers' agroforestry technology adoption decisions based on socio-economic, demographic, and farm characteristics of the sampled households. The study finds that total yields, farm size, extension frequency, off-farm income, access to training, access to credit, access to transport facilities, group membership, access to market, gender, distance to nearest trading center, and household education level had significant effects on the adoption of agroforestry technologies. The estimation of the impacts used endogenous switching regression model, the results of the second stage showed that variables such as gender, farm size, access to transport facilities, and off-farm income significantly affected the yields of both adopters and non-adopters differently. Adoption could increase the smallholder farmers' yield of maize crops from 116kgs to 696kgs.  Hence, this initiative is important because it could help smallholder farmers access food and increase their incomes. The findings of this project are important in informing policy formulation and implementation of agroforestry technologies adoption.

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