CHAPTER 3 Farmer perceptions on the availability of feed resources, and extent of
3.2 Materials and methods
3.2.1 Study sites
The survey was conducted in Namaacha, Boane and Marracuene districts of Maputo province.
Naamacha district lies 80 km west of Maputo on the border with Swaziland. It is located in the Lebombo Mountains. The range of the mountains is relatively low with altitude between 450 and 800 m above sea level. The district has a total land area of 2.196 km2 (INE, 2011). The climate is tropical humid. There are predominantly two two seasons: hot and high rainfall between October and April; and the fresh and dry, between April to September. The average annual rainfall is 751.1 mm and the average temperature is 21°C. Main sources of water are the Movene, Mabenga, and Calichane, Impaputo and Umbeluzi rivers as well as the Lebombo dam.
Agriculture is the main economic activity in the district. The main horticultural crops grown are maize, groundnuts, beans (Vigna unguiculata and Phaseolos vulgaris), sweet potatoes, cassava, peanuts, maize, and fruits. The predominant livestock species are cattle, goats, sheep, chickens, ducks, and pigs. Michangulene lies at 26 17' 29'' S and the 32' 11 and 23'' E and at an altitude of 94 m. The annual temperature is approximately 28°C. The annual precipitation varies between 600 and 800 mm. The region is largely semi-arid.
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Boane district (40 km from the city of Maputo) is located at 26°.02'S and 32°17'E. The district has a total land area of 820 km² and population about 102 457 residents, which corresponds to a population density of 124.9 habitants per km² (INE, 2011). The climate is sub- humid with the hot and wet seasons experienced between November and March, while the dry season occurs from April to October. The average annual rainfall is 752 mm and the annual average temperature is 23.7°C with a maximum relative annual humidity of 80.5 %. The water courses of Boane belong to the hydrographic basins of Umbeluzi, Matola and Tembe rivers. The southern area is covered by the rivers, benefits from irrigation and low humidity, being able to grow vegetables, bananas and citrus. The main crops grown are maize, cassava, beans, bananas, and citrus. Livestock such as cattle, sheep, and poultry are produced for household consumption and sale.
Marracuene is located 30 km north of Maputo. The climate of the district is rainy tropical savanna, influenced by the proximity of the sea. It is characterized by warm temperatures with an average annual value of more than 20°C with relative humidity ranging from 55 to 75 %.
The rainfall is moderate, with an annual average of 500 mm. The rainy season lasts from October to April, with 60 % of the rainfall received between December and February.
Agriculture is the economic base of the district. The main crops cultivated are rice, maize, cassava, sweet potato, and bananas. The predominant species of livestock are cattle, sheep, and poultry.
Namaacha district represented households in mountainous locations, while households interviewed in the Boane district were located around a dam that supplies water for both domestic and household use. Marracuene district has a generally flat terrain.
3.2.2 Sampling procedure
Data were collected using diagnostic surveys. For each district, three villages and 10% of households of each village were randomly selected. Pre-tested structured questionnaires were administered to a total of 240 households across the three districts. In each district, 80 individual households were selected randomly.
3.2.3 Data collection
To assess the farmer perceptions, participatory rural appraisal (PRA) and structured questionnaires were used. The questionnaire covered aspects of household demography, the
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chicken breeds used, flock sizes, chicken management, and utilization of non-conventional feed resources. The interviews were conducted in the vernacular language.
To collect primary data of village chicken production, importance, and challenges to rearing village chickens, face-to-face interviews with nine key informants were conducted. The key informants were management from the International Rural Poultry Centre, personnel from the technical department in the National Extension Service, extension officials, district livestock technicians, and community leaders. Transect walks were conducted in the villages. Data were also collected through direct observations. Participatory mapping and seasonal calendars were used to gather data on challenges facing village chicken production.
Using groups of fairly homogenous farmers, in each district, resource maps showing the general conditions of the village and its environment including farming fields, grazing lands, dams, major roads, common market places, schools and other major community resources were prepared. Seasonal calendars were used to gather information on the availability of feed and problems that occur in each season. Data on commonly used non-conventional feed resources and their availability were collected from each group. Feed calendars were produced to illustrate the changes in the scavenging feed resource base.
Focus group discussions were conducted to assess the importance and availability of feed resources. Opportunities for village chicken production were assessed. The major challenges facing village chicken production in each community were ranked.
3.2.4 Statistical analyses
All data were analysed using SAS (2008). The PROC FREQ procedure was used to determine differences among districts, season, type of feed, dietary supplementation; frequency, availability of feed and feed shortages. The general linear models procedure was used to compare productivity of the chicken breeds in each village. An ordinal logistic regression (PROC LOGISTIC) was used to predict the odds of a household, regarding the level of importance of village chickens, to experience chicken feed shortages, to house chickens at night, to use kitchen waste and maize bran. The variables fitted in the logit model included district, age, gender, level of education, number of adults, number of children, feed, lack of market, prevalence of diseases and parasites and the level of predation. The model used was:
Ln [P/1-P] =β0 + β1X1 + β2X2 + β3X3+ βtXt+ ε Where:
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P is the probability of level of importance of village chickens experiencing chicken feed shortages, housing chickens at night, feeding chickens with kitchen waste and maize bran;
[P/1−P] is the odds of (household saying village chickens are important; experiencing chicken feed shortages; housing chickens at night, feeding chickens with kitchen waste and maize bran);
β0 is the intercept;
β1…βt are the regression coefficients of predictors;
X1…Xt are the predictor variables;
ε is the random residual error.