Browsing by Person "Pergner, Isabell"

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Profitability and risk efficiency of arable farming without chemical-synthetic plant protection but with optimized use of mineral fertilizers
(2024) Pergner, Isabell; Lippert, Christian
The use of chemical-synthetic plant protection products (pesticides) in conventional agriculture has been repeatedly criticized in recent years for its negative environmental impacts. Their use can lead to contamination of soil, water, and air, endangering not only biodiversity but also decreasing the quality of drinking water. A potential, more environmentally friendly alternative is organic farming, which abstains from both pesticides and mineral fertilizers. Despite the recognized environmental benefits of organic arable farming, there are some criticisms. For instance, organic farming’s production quantity may be lower compared to conventional agriculture, raising concerns about its ability to ensure food security. An arable farming system without pesticides but with the use of mineral fertilizers represents a middle way between conventional and organic farming. This method uses mineral fertilizers to promote plant growth while abstaining from pesticides. Compared to organic farming, this approach may achieve higher production quantities, contributing to food security, while avoiding the adverse environmental effects of pesticides. This type of agriculture can thus offer a more balanced approach. It is important to explore and promote this alternative arable farming system for a healthier long-term way of arable farming. Hence, the first article in this dissertation provides a comprehensive literature review of the social, economic, and ecological impacts of pesticides and the resulting reasons for farmers to use or abstain from them. It identifies obstacles and potential benefits that could be utilized for developing farming without pesticides but with use of mineral fertilizer. In farming without pesticides, but with mineral fertilizer: (1) yields and their temporal stability are expected to be higher than in organic farming but lower than in conventional farming; (2) profitability might suffer due to energy consumption and high costs; (3) soil fertility and biodiversity are expected to increase along with alternative measures for disease and pest control; (4) crop rotations will more diverse compared to conventional agriculture; (5) optimal plant utilization of mineral fertilizers might not be achieved without balanced nitrogen supply. When farmers choose between different cropping systems, they consider not only expected farm income but also income stability. The lower the total contribution margin variance of a farm, the more stable the income. Income variance can be calculated and included in Quadratic Risk Programming models applying the Expected Value-Variance Criterion when temporal (co-)variances of the contribution margins of individual crops are known. Empirically sound approaches to identify these are lacking. In the second article, we outline a way, from an individual farmer’s perspective, to derive temporal (co-)variances of contribution margins for crops. Neglecting producer price variances and variable costs, it is shown how to estimate temporal crop yield (co-)variances based on available yield data from a long-term field trial at the Julius Kühn Institut in Dahnsdorf (Germany). The four studied cropping systems are (b1) without fertilizer and pesticides; (b2) without fertilizer but with pesticides; (b3) with fertilizer but without pesticides; and (b4) with fertilizer and pesticides. Using a mixed-effects model, a covariance matrix is estimated for yield data of winter rye, winter barley, and peas from 1998 to 2021 for each system. Additionally, we computed means, standard deviations, and coefficients of variation for the different yields. The estimated (co-)variances serve as valuable indicators for corresponding orders of magnitude and can be utilized for Quadratic Risk Programming, aiming to optimize a cultivation program while considering preferred risk levels. In the third article, time series data on yields, prices, and variable costs are collected from statistical institutes for several crops grown in conventional agriculture, organic farming, and farming without pesticides, but with mineral fertilizers. Their standard deviations and correlation coefficients are calculated to derive corresponding (co-)variances. These are used for a Monte Carlo simulation providing average contribution margins and their (co-)variances for the considered crops. With this information a hypothetical model farm is constructed. Using Quadratic Risk Programming and considering different risk levels, expected total contribution margins are maximized, resulting in optimal combinations of expected total contribution margin and its variance. Organic farming shows high total contribution margins for optimized crop rotations but also increased variance compared to other cropping systems. The inclusion of cereals in a crop rotation reduces risk, while the inclusion of potatoes and sugar beets raises risk across all systems. The ceteris paribus analysis indicates that implementing conventional crop rotations into other systems leads to unfavorable crop portfolios or even negative total contribution margins. Therefore, optimizing and diversifying the portfolio for each cropping system is crucial. An optimized farming system without pesticides but with mineral fertilizer exhibits lower risk and lower total contribution margin compared to other systems. With rising prices and increased variances, farming without pesticides, but with mineral fertilizers becomes more advantageous, providing a higher total contribution margin while maintaining lower risk compared to optimized conventional crop rotations. In the future, this planning method should be executed using data from farms for an empirically well founded comparison of cropping systems.