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A Linear Programming Approach To Food Crops And Livestock Enterprises Planning In Aba Agricultural Zone Of Abia State, Nigeria

Authors: Igwe, K. C.; Onyenweaku, C. E.;

A Linear Programming Approach To Food Crops And Livestock Enterprises Planning In Aba Agricultural Zone Of Abia State, Nigeria

Abstract

Linear programming technique was applied to farm data obtained from thirty arable crop farmers during 2010 farming season to maximize gross margin from various combination of arable crop and selected livestock enterprises. Optimization and reallocation of available resources were found to bring significant changes in the existing plan. Twenty enterprises were observed in the existing plan made up of one sole crop, fourteen crop mixtures and five livestock enterprises across poultry, fish and piggery which an average farmer would make a gross margin of N232, 317.12. However the LP maximization model recommended that for optimum gross margin of N374, 850.00 which is about 61.35% of the existing gross margin, an average farmer should devote 0.31 hectare to yam/maize/melon, 0.33 hectare to cassava/maize/cocoyam and 1.30 hectares to Cassava/Maize/Yam/Mucuna Floanei while 0.14 of 500 birds of broiler 1 raised usually between January – May and 0.11 of 1000 fish of fish 2 done between July – December and 0.07 of 15 pigs be produced. Given the mean farm size of 0.45 hectares, the farming orientation is still subsistence. It is recommended that crop mixtures be undertaken by farmers in combination with poultry and fish enterprises for improved gross margin. Policies of Government should be geared towards encouraging individual extension services to achieve increased farm advisory services to help deal with the problem of misallocation of farm resources among farmers as well as possibility of achieving stable wage among farm labour.

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Keywords

Linear programming;, livestock;, plan., existing;, arable crops;, optimum;

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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