A Geospatial Approach to Assessing the Impact of Agroecological Knowledge and Practice on Crop Health in a Smallholder Agricultural Context
A Geospatial Approach to Assessing the Impact of Agroecological Knowledge and Practice on Crop Health in a Smallholder Agricultural Context
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DOI：
10.1080/00330124.2022.2146908
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发表时间：
2023-02
期刊：
影响因子：
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通讯作者：
Daniel Kpienbaareh;Jinfei Wang;I. Luginaah;R. Bezner Kerr;E. Lupafya;L. Dakishoni
中科院分区：
文献类型：
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作者：
Daniel Kpienbaareh;Jinfei Wang;I. Luginaah;R. Bezner Kerr;E. Lupafya;L. Dakishoni
在资源贫乏环境中粮食不安全的背景下，农业生态学（AE）已成为提高作物生产力的重要方法，但很少有研究表明农业生态学方法的组合如何改善作物健康，从而提高作物生产力。使用地理空间的方法，这项研究调查了农业生态实践是否可以改善作物健康的小农环境。我们比较了AE和非AE农场作物的叶面积指数（莱什），并使用植被指数（维斯）前瞻性地预测了AE的影响。我们发现，玉米和木豆（1.28 m2/m2）和玉米和豆类（1.29 m2/m2）农场的AE农场的作物产生较高的平均生长季节莱什分别为0.97 m2/m2和0.80 m2/m2，对于相同的作物在非AE农场。较高的莱什指数表明，农业战略的组合实行的AE农场生产更健康的作物。随机森林回归前瞻性预测产生了统计学显著较高的莱什指数玉米和豆类（R 2 = 0.90，均方根误差[RMSE] = 0.32 m2/m2）和玉米和木豆（R 2 = 0.88 m2/m2，RMSE = 0.42 m2/m2）的AE农场，但非AE农场的预测没有统计学显著性。研究结果表明，结合AE战略可能会提高作物生产力，以提高小农家庭的粮食安全和收入。
In the context of food insecurity in resource-poor settings, agroecology (AE) has emerged as an important approach promoted for improving crop productivity, yet few studies have demonstrated how a combination of agroecological methods can improve crop health and thereby crop productivity. Using a geospatial approach, this study investigated whether agroecological practices can improve crop health in smallholder contexts. We compared leaf area indexes (LAIs) of crops on AE and non-AE farms and prospectively predicted the impact of AE using vegetation indexes (VIs). We found that crops on AE farms produced higher average growing season LAIs for maize and pigeon peas (1.28 m2/m2) and maize and beans (1.29 m2/m2) farms compared to 0.97 m2/m2 and 0.80 m2/m2, respectively, for the same crops on the non-AE farms. The higher LAIs suggest that the combination of farming strategies practiced on the AE farms produced healthier crops on AE farms. Random forest regression prospective predictions generated statistically significant higher LAIs for maize and beans (R 2 = 0.90, root mean square error [RMSE] = 0.32 m2/m2) and maize and pigeon peas (R 2 = 0.88 m2/m2, RMSE = 0.42 m2/m2) on the AE farms, but predictions for the non-AE farms were not statistically significant. The findings demonstrate that combining AE strategies can potentially improve crop productivity to enhance household food security and income in smallholder contexts.