| dc.description.abstract | The main problem addressed in this thesis is inadequate utilization of farm equipment for conservation tillage in maize production. This problem is manifested in the form of inadequate soil loosening, low application of organic fertilizers, late planting and weeding. These are some of the main causes of low maize yield estimated at one tonne per ha, which is less than half the potential after adoption of available package of recommended practices.
Therefore the purpose of the study was to analyse the effect of tested farm equipment on optimum maize production subject to available labour, land, power and specified crop residue recycle. After selecting and testing available tools and equipment it was found that land breaking, furrow making, timely planting and weeding are possible. It was also found that innovative animal draft power (ADP) tillage equipment could significantly minimise runoff. A single objective linear programming (LP) model was formulated to estimate optimum production with input data drawn from technical test performance. The input parameters used were: available farm labour, land, schedule of maize production tillage operations and expected yield for various levels of timeliness of planting and weeding.
Variables in the objective function were areas of land planted and weeded at various timeliness combinations whereas the corresponding coefficients were the net maize yields. The output production was therefore in kilograms of maize grain dry matter available per farm. The constraint equations included weekly man-hours, ox-hours and tractor hours available for the scheduled operations over the critical time period starting with the period before the rains. Other constraints included available land for cultivation and surplus crop residue after recycling a specified quantity.
Goal programming was carried out to determine optimum energy use subject to specified crop residue recycles. This time the energy consumption for various timeliness combinations was substituted for yield as the coefficient of the objective function to minimize energy use. At the same time the solution of the linear programming objective function formulation with production as the objective function was stated as an additional constraint to ensure that the optimum production achieved under single objective LP formulation was not violated.
Results show that farmers who own ADP equipment do not require tractor powered (TP) mechanization for seasonal operations unless more than 4.0 ha per farmer cultivated land is available.
For farmers who do not own ADP, it is more beneficial to switch to new ADP equipment than to supplement their capacity with hired tractors. The model experiments show that farmers having 3 ha cultivated land and 3 adult labour equivalent can double maize production from 1800 kg to 3740 kg by simply moving from hiring traditional ADP equipment to hiring innovative ADP equipment. Alternatively the farmer can potentially realise 3550 kg by hiring tractors for land preparation. It can therefore be concluded that TP is justified only when the higher quality of work in terms of depth of tillage and land forming are needed once in three to four years.
These results provide the basic information necessary to carry out benefit cost analysis for investment on infrastructure to support sustainable adoption of innovative ADP and supplementary tractor hire service when necessary. The model developed in this thesis provides a mathematically valid methodology for quantifying the effect of innovative equipment on production before major investments on support infrastructure are made. The model is also appropriate for quantifying the effect of combining ADP and TP and showing that they are complimentary and not mutually exclusive. Application of this model for the mechanization of semi arid agriculture in Kenya can have positive effect on food security, incomes and employment and thus contribute to the realization of vision 2030. | en_US |
