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Effect of adoption of sustainable crop production systems on farm economics

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Abstract

This study uses farm models to analyze the effect of farm size on farm-level costs of adoption of reduced soil cultivation systems. In an empirical study in the Kulunda Steppe in Russia, we examine the farm-level economics of three crop cultivation technologies: old Soviet intensive tillage technology (OS), modified Soviet reduced-tillage technology (MS), and modern Canadian no-till technology (MC). We consider economies of size by considering three farm sizes (small = 500 ha, medium = 5000 ha, and large = 15,000 ha). Based on the general approach to cost and activity accounting, we sequentially compute gross cost–benefit measurement to assess the economic performance of the different systems. The study utilizes two data sources: (1) experts’ estimates regarding the input requirements and yield impacts of reduced-tillage systems in the marginal ecosystem of the Kulunda Steppe and (2) market prices in 2014 and 2015. According to the model calculations, OS is inferior to MC and MS tillage systems in all farm sizes if we adopt a medium- to long-term perspective and consider residual income. If we adopt a very short-term perspective and consider only the difference between sales and direct costs, the MC tillage system would rank first across all modeled farm sizes. However, because farms in the Kulunda Steppe are heterogeneous, our results cannot replace management decisions based on farm-specific calculations that consider the conditions of the respective farm.

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Notes

  1. Dr. Meinel has studied soil cultivation in the Altai krai for approximately 15 years.

  2. Prof. Belayev (Professor at the Farm Mechanisation Department at the Agrarian University in Barnaul) has investigated soil cultivation technologies in Altai krai for two decades.

  3. With regard to machinery requirement for follow, it must be noted that the mechanical follow is cultivated six times during the vegetation period: once using a deep cultivation and five times using flat cultivation by harrow.

  4. As mentioned previously, machinery prices have changed significantly due to the depreciation of the Russian ruble. Thus, machinery costs were calculated based on the exchange rates that prevailed before (40 RUB/€ exchange rate) and after the crisis (60 RUB/€ exchange rate). However, only the more current results are presented here. Data regarding the cost of machinery before the exchange rate crisis are available upon request.

  5. The bank interest rate on the purchase of both imported and Russian machines is 12%.

  6. OS is the conventional technology that usually uses Russian machinery. We therefore assume Russian machinery equipment when calculating the costs of OS.

  7. Similar results were also obtained using the pre-crisis exchange rate (40 €/RUB), although residual income with the pre-crisis exchange rate is higher than residual income with the exchange rate that prevailed during the crisis (60 €/RUB). These results are available upon request.

  8. A total of 92 farms were investigated in the Altai Krai between February 2015 and July 2016. We collected the data through quantitative face-to-face questionnaire surveys. When selecting the farms, our aim was to have at least one large and medium or small farm from each rayon in our sample. We closely achieved this aim as we covered 52 rayons from 59.

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Acknowledgements

The authors would like to thank Dr. Tobias Meinel and Lars Grünwald (experts on introduction of no-till system from the agricultural machinery manufacturer Amazon in Kazakhstan and Russia and co-founders of farmers’ extension organization on reduced till introduction in Altai Krai) as well as Prof. Belayev (professor from the Farm Mechanization Department at the Agrarian University in Barnaul and co-founder of farmers’ extension organization on reduced till introduction in Altai Krai) for their valuable estimations. Without their knowledge input, this analysis would not have been possible. The authors acknowledge the KULUNDA Project, part of the BMBF research program ‘Sustainable Land Management’, for completion of this research.

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Authors and Affiliations

  1. Czech University of Life Sciences, Faculty of Tropical AgriScience, Kamýcká 129, 165 00, Prague 6 - Suchdol, Czech Republic

    Miroslava Bavorova

  2. Department of Theoretical Cybernetics and Applied Mathematics, Faculty of Mathematics and Information Technologies, Altai State University, pr. Lenina 61, Barnaul, Russia, 656049

    Elena V. Ponkina

  3. Institute of Agricultural and Nutritional Sciences, Martin-Luther-University-Halle-Wittenberg, Karl-Freiherr-von-Fritsch-Str. 4, 06120, Halle(Saale), Germany

    Nizami Imamverdiyev & Norbert Hirschauer

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  1. Miroslava Bavorova
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Correspondence to Miroslava Bavorova.

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Appendix

Appendix

Table 11 Prices for imported and Russian machines, and number of machines used in the farm models for each tilling technology and farm size
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Bavorova, M., Ponkina, E.V., Imamverdiyev, N. et al. Effect of adoption of sustainable crop production systems on farm economics. Environ Dev Sustain 22, 6961–6984 (2020). https://doi.org/10.1007/s10668-019-00522-1

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