A portfolio theory approach to crop planning under environmental constraints

Bogner

et al. 2016

Agricultural Systems

Temporal fluctuations of crop price and yield can have a strong influence on farmers' revenue. Under uncertainty, farmers' crop selection on -what to cultivate and how much of their land to allocate to different crops-is of crucial importance to secure their revenue as well as related ecosystem services. Multi-crop farming can be seen as a strategy to mitigate uncertainties that farmers face. In this study, we used Singular Spectrum Analysis (SSA) to quantify the fluctuations of crop price and yield for single and multiple crop selections in South Korea. Furthermore, risk adjusted revenue of each crop selection was analysed using the Sharpe ratio. We constructed three empirical crop portfolios containing one, three and five crops. For the single crop farming, six main crops in South Korea were analysed, and household data were used to build empirical crop portfolios. Our results showed that revenue from rice farming was the most stable, whereas it fluctuated strongly for pepper. However, growing rice provided the lowest revenue and farmers who cultivate multiple crops might as much as double their revenue compared to rice farming. Diversified crop farming can be a means of enhancing revenue. The biggest part of fluctuations in portfolios with several crops was seasonal, which might be mitigated by planning in advance. The artificial stability of rice price was due to policy intervention. However, it should be noted that the rice policy has been reformed and a high protection for domestic rice farming would no longer last in the future in South Korea. These results might have practical consequences for farmers' decision making on crop selection as well as for agricultural policy.

Section: Introductionmentioning

confidence: 99%

Crop selection under price and yield fluctuation: Analysis of agro-economic time series from South Korea

Bogner

et al. 2016

Agricultural Systems

European Journal of Operational Research

“…To diversify the sample, the surface area of each plot is drawn in the interval [4,11]. We observe that for all instances, the two exact methods find an optimal solution but BPC is in average 5 times faster than IP solver.…”

Section: Numerical Resultsmentioning

confidence: 97%

“…Another example can be found in [10] where harvested crops can be stocked for a limited period of time, and demands are subject to uncertainty. [11] presents multi-objective crop rotation models that take risk into account, converted into linear programs and solved with standard Linear Programming (LP) methods. A survey on crop rotation decisions exists [12] but does not include most recent papers in optimization.…”

Section: Introductionmentioning

confidence: 99%

A branch-and-price-and-cut approach for sustainable crop rotation planning

Alfandari

Plateau

Schepler

2015

In this paper, we study a multi-periodic production planning problem in agriculture. This problem belongs to the class of crop rotation planning problems, which have received increased attention in the literature in recent years. Crop cultivation and fallow periods must be scheduled on land plots over a given time horizon so as to minimize the total surface area of land used, while satisfying crop demands every period. This problem is proven strongly N P -hard. We propose a 0-1 linear programming compact formulation based on crop-sequence graphs. An extended formulation is then provided with a polynomial-time pricing problem, and a Branch-and-Priceand-Cut (BPC) algorithm is presented with adapted branching rules and cutting planes. The numerical experiments on instances varying the number of crops, periods and plots show the effectiveness of the BPC for the extended formulation compared to solving the compact formulation, even though these two formulations have the same linear relaxation bound.

“…We formulate two minimum financial risk models and two maximum expected net return models. In contrast to the models developed in Radulescu and Radulescu [14] and Radulescu et al [16], which are binary and respectively mixed-binary, the models from the present paper are formulated in continuous variable. Our models can be embedded as modules in a decision support system for crop planning.…”

Section: Introductionmentioning

confidence: 97%

“…The minimum risk model is a QP model. In Hazell For other references regarding applications of portfolio theory to agriculture see Radulescu [13], [14] and [16].…”

Section: Introductionmentioning

confidence: 99%

Crop Planning Models with Symmetric Risk Measures

Rădulescu¹,

Rădulescu²

2014

SIC

Self Cite

Abstract:In this paper the financial risk of crop plans is measured by two symmetric risk measures: variance and mean absolute deviation of the return. Several crop planning models with symmetric risk measures, based on the financial portfolio theory, are formulated. Among them minimum risk and maximum expected return models are of interest. The decision variables are the land areas allocated to crops. The models belong to mathematical programming with continuous variables. Some numerical examples for the minimum financial risk model are studied and efficient frontiers of the models are displayed.