Document Type

Article

Publication Date

2023

Publication Title

The Professional Geographer

Keywords

agroecology, agroecosystems, crop health, Malawi, random forest regression

Abstract

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 (R2 = 0.90, root mean square error [RMSE] = 0.32 m2/m2) and maize and pigeon peas (R2 = 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.

Funding Source

The authors are grateful to the International Development Research Centre (IDRC) for the Doctoral Awards (IDRA 2018, 108838-013) and the Micha and Nancy Pazner Fieldwork Award for their financial support for the doctoral field work of Daniel Kpienbaareh. Funding was also provided by the National Science Foundation, Grant/Award Number: 1852587; Natural Sciences and Engineering Research Council of Canada, Grant/Award Number: 523660-2018; German Federal Ministry of Education and Research; and the Research Council of Norway.

DOI

10.1080/00330124.2022.2146908

Comments

This is an Accepted Manuscript of an article published by Taylor & Francis in The Professional Geographer on 02 February 2023, available at: https://doi.org/10.1080/00330124.2022.2146908.

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