Affiliation:
1. Department of Systems Engineering, Colorado State University, Fort Collins, CO 80523, USA
Abstract
The adoption of agricultural technologies in developing economy countries has the potential to reduce poverty through sustainable intensification. Mechanized farming can also improve perceptions of farming and mitigate rural out-migration. However, many traditional farmers do not have access to machinery and/or machinery is cost prohibitive. The objective of this paper is to quantify how the use of machinery affects costs, revenue, net-profits, and returns on investment for a case study of farmers in Sudan, Africa. A treatment control study (N = 36) was performed across the 2019 (baseline), 2020, and 2021 farming seasons, where the treatment group was provided tractors. ANOVAs and t-tests were used to compare financial values between these groups across the farming seasons, to quantify economic differences associated with farming machinery. We show that all farmers had similar net-profits when farming without machinery, while mechanized farming yielded significantly higher net-profits (USD 16.61/acre more in 2020, USD 27.10/acre more in 2021). Our study also finds that the volatility of the black-market exchange rate and labor shortages have a significant impact on farming net-profits. These results provide a quantified difference between farming with and without machinery, which can provide a financial basis for purchasing and borrowing models, machinery design requirements, and educational value to farmers.
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