A mathematical programming procedure for selecting crops for mixed-cropping schemes

Jolayemi, Joel K.; Olaomi, JO

doi:10.1016/0304-3800(94)00041-f

Cited by 10 publications

(3 citation statements)

References 4 publications

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“…A large portion of the literature is devoted to developing linear programming or other mathematical programming formulations for specific problems involving farm land allocation, crop rotation, harvesting, etc. (e.g., Audsley 1985, Cocks 1968, Heady 1954, Jolayemi and Olaomi 1978, Rae 1971). The primary focus of the aforementioned studies is to demonstrate the viability of mathematical programming tools in efficiently solving a range of proposed problems, whereas, in comparison, our objective also includes obtaining the structural characterization of the optimization problem.…”

Section: Introductionmentioning

confidence: 99%

Optimal Crop Choice, Irrigation Allocation, and the Impact of Contract Farming

Huh

Lall

2013

Production and Operations Management

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T he changing climate and concerns over food security are prompting a new look at the supply chain reliability of products derived from agriculture, and the potential role of contract farming as a mechanism to address climate and price risk while contributing toward crop diversification and water use efficiency is also emerging. In this study, the decision problem of a farmer associated with allocating his land among different crops with varying water requirements is considered, given that a subset of the crops may be associated with a forward contract that is being offered by a buyer. The problem includes a decision to acquire a certain amount of irrigation water capacity prior to the season and to allocate this capacity as irrigation water to be applied during the season to each of the crops selected. Rainfall in the growing season and the market price of each crop at the end of the season are considered to be random variables. Two stochastic programming models are developed to consider facets of this problem and to understand how contracts that reduce market price uncertainty from the problem may change the farmer's decision. The structural properties of these models are discussed, and selected implications are illustrated through an application to data from the Ganganagar district in Rajasthan, India.

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Section: Introductionmentioning

confidence: 99%

Optimal Crop Choice, Irrigation Allocation, and the Impact of Contract Farming

Huh

Lall

2013

Production and Operations Management

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“…The LP model has been chosen because farm income is linear in output prices and quantities (Buongiorno and Gilless, 2003). The methodology has been used successfully for many years in operations research for both agricultural and forestry production and conservation (Merry et al, 2002;Bernet et al, 2000;Shiferaw and Holden, 2000;Delforce, 1994;Jolayemi and Olaomi, 1995;Nicholson et al, 1994;Howard, 1993;Bezuneh et al, 1988;Ahn et al, 1981), and in the empirical estimation of deforestation at the household and firm level (Kaimowitz and Angelsen, 1998). The LP model is an optimization model that identifies a production plan that maximizes peasant net annual income under various policy instruments.…”

Section: The Modelmentioning

confidence: 99%

Modeling farm households for estimating the efficiency of policy instruments on sustainable land use in Haiti

et al. 2009

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“…Linear programming is also used to make the decision of land allocation among different types of farming alternatives subject to resource constraints. Jolayemi (1990) and Jolayemi et al (1992) developed a linear programming model for selecting crops for mixed cropping schemes.…”

Section: Introductionmentioning

confidence: 99%

Diversification of Farmland use in Bangladesh: Land Allocation Impacts on Farm Profitability

Palash

Bauer

2017

Open Agriculture

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Smallholder farmers in Bangladesh face many difficulties. A trend towards fish farming has opened new opportunities in recent years. This research focuses on the concern, whether smallholders could improve their gross margins by improving the allocation of the available physical and non-physical resources. Combinations of the participatory, qualitative and quantitative methods were used for primary data collection. A linear programming based modelling approach shows that farmers can increase the farm gross margin by reallocating the land in the model solution. Essential requirements, e.g. determined by household consumption requirements, determine parts of the resource allocation. The remaining land is in tendency allocated to fish farming; where one specific fish farming alternative is dominant to others. In the scenario analysis, all farming groups keep the same proportion of land use pattern until a certain level of price change, beyond that crop farming is selected. Scenarios modifying the available fish feed show the significant sensitivity of this resource on the land allocation.

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A mathematical programming procedure for selecting crops for mixed-cropping schemes

Cited by 10 publications

References 4 publications

Optimal Crop Choice, Irrigation Allocation, and the Impact of Contract Farming

Optimal Crop Choice, Irrigation Allocation, and the Impact of Contract Farming

Modeling farm households for estimating the efficiency of policy instruments on sustainable land use in Haiti

Diversification of Farmland use in Bangladesh: Land Allocation Impacts on Farm Profitability

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