Financial performance of strip cropping in the Netherlands under high uncertainty: a Monte Carlo analysis

Abstract

During the XXth century, technological breakthroughs in genetics, machinery, and improved inputs led to dramatic increases in crop yields (Pingali, 2012). This agricultural revolution was a remarkable success in food production, tripling yields while increasing the area devoted to production by only 30% (Pingali, 2012). This increase in crop yields was necessary to avoid famine, as the world population more than doubled during this period (Pingali, 2012).Unfortunately, this form of industrial agriculture, which relies on crop uniformity, heavy machinery and the intensive use of agrochemicals, leads to the loss of soil fertility, and an acceleration in soil degradation (Gomiero et al., 2011). The current system is reaching its limits, with yields either stagnating or growing much slower than needed to meet the projected demand (Hawkesford et al., 2013). In response to this looming crisis, the Dutch Ministry of Agriculture aims to convert the Netherlands to circular agriculture by 2030. This shift requires the need to develop new ways of farming (Ministry of Agriculture & food quality, 2020). Strip cropping is proposed by researchers at Wageningen University and farmers as a potential solution. Strip cropping is a form of agriculture, which is less reliant on agrochemical inputs and promotes biodiversity by planting narrow rows (or strips) of different crops next to each other (Zhang, 2019). Researchers at Wageningen University and farmers in the Noordoostpolder want to investigate the future economic performance of this new type of agriculture compared to traditional intensive farming. This problem is formulated in the following research question: What are the economic opportunities and risks associated to the implementation of strip cropping in the Netherlands? This research is relevant to the MSc Engineering and Policy Analysis as it can guide decisions related to horticulture. Given that agriculture is a complex socio-technical system and food security is a global challenge, this topic is an adequate fit for an EPA master thesis. The EPA master promotes the use of mathematical modeling to gain insight into societal challenges within a context of high uncertainty. The problem at hand is to determine the future economic performance of alternative farming methods, namely strip cropping, through a mathematical model with currently available information. The resulting document should enable farmers and policymakers to make informed economic decisions about the adoption of strip cropping. The detected knowledge gap relates to a lack of understanding of the economics of the strip cropping farming method. Through a study of the literature, the ecological benefits and drawbacks of strip-cropping and monocropping are examined. By gathering information from agricultural specialists, the financial impact of strip cropping is examined. A mathematical model is then used to process and analyze this data. Microsoft Excel is the program of choice because farmers and researchers are familiar with it and it would enable farmers to input their unique parameters and simulate their future financial returns for both monocropping and strip-cropping configurations. Initially, the information provided by the farmers is used to identify the pertinent financial variables. Revenue and Costs are the two groups into which these variables are divided. Yields, price per kilogram, and byproducts are all factors that affect revenue. Seeds, fertilization, crop protection, fuel price, fuel usage, labor cost, labor hours, and miscellaneous costs are variables in the Costs category. More specifically, a Monte Carlo analysis was chosen for the simulation since it has been shown to be effective for assessing the adaptability of various cropping systems to climatic uncertainty (Cary & Frey, 2020). This entails assigning probability distributions to the variables affected by high levels of uncertainty and executing an experiment several times to determine how the investigated farming systems would behave in various scenarios...