Bananas and Food Security - Bioversity International

732 Les productions bananières / Bananas and food security – Session 4
farm size, housing facility, cattle owned, off-farm employment, vehicles owned, food
security, crop processing facility, size of banana and coffee plantations.
Analytical methods
Budgeting techniques were used to measure the comparative advantage of various crops
to the farmer in terms of income earned and return to family labour. Regression analysis
was used to determine the factors affecting banana productivity and profitability in the
study area. Yield of bananas was regressed against variables thought to influence
farmers’decisions to invest in agricultural production.
Thus,
Qy = f (A, Fi, Xi, Yr, Wd, Ext, G, D, Ed, C) ...................(1)
Where:
Qy = Yield of bananas in kg ha-1 by farmer
A = Total farm size in ha
Fi = Total farm income in Uganda Shillings
Xi = Off-farm income in Uganda Shillings
Yr = Age of farmer in years
Wd = % weevil damage
Ext = Interaction with government extension agents
1 = yes, 0 = none
G = Gender of farmer; 1 = male, 0 = female
D = Distance from farm to tarmac road in km
Ed = Years spent in school by farmer
C = Number of cattle owned
Results and discussion
Household characteristics
Household characteristics of respondents are provided in Tables 1 and 2. Age of the
household head averaged 45.6 years. Seventy one percent of the household heads were
males, 64.5% married and 58.3% had at least obtained primary education. Most of the
farmers (64.5%) had part-time off-farm employment suggesting that most of the
responsibilities were left to their spouses who in most cases were female. Part-time
employment put stress on the already less available family labour. On average, two
persons per household were available for work, being shared between farm and off-farm
labour. Off-farm employment contributed 19% to the total household income. Off-farm
income supplemented farm income enabling farmers to meet household needs and buy a
few farm inputs.
Household size averaged 6.52 persons with a male to female ratio of 0.93. Most
children were going to school (76%), reducing the available family labour. The high
enrolment in school might have been a result of government policy of free universal
education combined with moderate household incomes. Annual household income