Academic literature on the topic 'Farms, Small – Swaziland'

Mushrooms have been cultivated in Swaziland since 2001 as part of a long-term programme which sought to improve rural livelihoods through commercial production of non-conventional high-value commodities. Despite the mushroom enterprise gaining popularity in a number of Sub-Saharan African (SSA) countries, where production is dominated by rural-based small-scale farmers, limited research has been done to study the technical efficiency of mushroom farmers in Swaziland.The primary objectives of this study were to determine the level of technical efficiency of mushroom farmers in Swaziland and identify factors which influence technical efficiency of mushroom farmers. Measures of technical efficiency were conducted with 62 farmers in the four Agro ecological zones of Swaziland. The list of current mushroom farmers was obtained from the Mushroom Development Unit in Malkerns. The Stochastic frontier production function was used to compute the level of technical efficiency (TE). The results revealed that the mean technical efficiency was 95%. The results suggest that substantial gains in output can be attained by improving present technical practices which includes the increase in the amount of substrate used. A two limit Tobit regression technique was used to examine the relationship between TE and various farm and farmer characteristics. The results showed that household size was significant at 5% level, technical assistance was also significant at 5% and access to credit was significant at 10% level. It was recommended that extension officers equip farmers on technologies that will help boost their efficiency level and policies that will make access to credit from government and NGO’s for mushroom farmers to acquire resources.

More than 60% of the dairy products consumed in Swaziland are imported from South Africa. The Swaziland Dairy Board had established the dairy credit guarantee scheme with Swaziland Finance Development Cooperation to improve local dairy production and boost the livelihoods of smallholder dairy farmers. Unfortunately, the scheme was terminated without its effectiveness being evaluated. Therefore, the study set out to investigate the contribution of the dairy credit guarantee scheme to household food security. A total of 30 beneficiary households participated in the study. The data were collected through a structured questionnaire and analysed using the Statistical Package for Social Sciences (SPSS version 18.0). The households were compared in terms of the mean number of cows, milk production and volume of sales using the Duncan Multiple Range Test (DMRT). The dairy scheme was open to all qualifying smallholder dairy farmers, but most (86.7%) beneficiaries were male. The beneficiary households owned, on average, between one and eight cows between 2006 and 2009, and produced 188079 litres of milk on average per year. The highest income generated from milk sales was R74137.00 per year between 2006 and 2009. The lowest income from milk sales was R1020.00, from a household with the lowest number of dairy cows on average per year between 2006 and 2009. Beneficiaries reported that the increase in income enabled them to accumulate agricultural assets, increased food purchases and the diversification of livelihoods. Over 56.7% of the households were able to diversify their livelihoods by engaging in other income-generating projects such as poultry and pig production, horticulture, selling groceries and block (brick) making. With improved income especially milking households were able to increase food supply and this is indicated by their higher average Food Consumption Scores (75.58) than non-milking households (59.65). However, all the average Food Consumption Scores were above 42 which is a threshold level for acceptable nutrient intake, dietary diversity and this implies that the dairy production scheme led to improved dietary intake. In conclusion, the dairy credit scheme has the potential to improve local milk production and household food security. It is, therefore, recommended that the dairy scheme be revived, with better accessibility. The establishment of dairy development policy should be considered, in order to create a favourable environment for dairying and the promotion of cooperation among dairy development partners. This cooperation would help to avoid duplication of efforts among development partners and create a platform for interaction, sharing of information and exchange of ideas.
Thesis (M.Sc.Agric.)-University of KwaZulu-Natal, Pietermaritzburg, 2011.

Summary: Swaziland has long had a disparity between the supply and demand of milk. Even at present milk production continues to be less than the market demand. The quantitative contribution of smallholder dairy farmers to local milk production remains unknown because of poor record keeping. This study was aimed at attaining a clear understanding of the dynamics of smallholder dairying in Swaziland, including the identification and understanding of the constraints faced by farmers in dairying, with the hope of devising workable solutions to them. A sample of 118 smallholder dairy farms were covered in this study, with a total herd of 306 lactating cows, comprising mainly of Jerseys and Holstein Friesians, with some cross breeds. There were no significant differences in mean milk yield/cow with respect to farmer gender (P > 0.05) and Agro-ecological zone location (P > 0.05) of the farms. Milking frequency had a significant effect on milk yield, since cattle milked once a day had lower (P < 0.05) milk yields than those milked twice a day. The cattle had extensively long calving intervals i.e. 448 ± 166 days, ranging from 292 to 1082 days. Low milk yield and poor reproductive performance of cattle were found to be mainly due to poor nutrition, breeding practices and stock quality. These are primarily a result of insufficient farmer training and inadequate technical assistance, scarce availability of quality stock, lack of investment resources and market support that includes favourable milk prices for farmers to make money. This performance of the Swazi smallholder dairy herd was then evaluated by comparing it to the performance of a larger, well-managed herd of known pedigree. Lactation records from 252 Jersey cows and 108 Holstein Friesian cows were obtained from Cedara Agricultural Research Institute, covering the periods; July, 2002 to July, 2004 and November, 2002 to April, 2004, respectively. Cows were grouped by parity and calving season and the gamma function proposed by Wood (Y = An(b) e(-cn)) was used to fit standard lactation curves on group data. The curve parameters A and b increased with parity, while that of c and s (persistency of lactation at peak) decreased, producing standard lactation curves save for the Holstein Friesian summer calvers, which produced atypical curves. The R(2) values (goodness of fit) increased with parity. Animal parity and calving season were found to influence the peak and shape of the lactation curves and their parameter estimates. The performance of the Swazi smallholder herd showed a mean deviation of the observed daily milk yield of the Holstein Friesian breed from the expected yield to be - 3.47 (SD 6.052) kg and that of the Jersey breed was - 16.92 (SD 5.473) kg. The mean proportional deviation of observed milk yield from the expected yield for the Holstein Friesian breed was - 0.3 (SD 0.37) and that of the Jersey breed to be - 0.6 (SD 0.19). The proportional milk yield deviation of the Holstein Friesian breed can be explained using the equation Y = O.1322(SE = 0.1293) x - 2.3581 (SE = 0.20639), where x = expected milk yield and Y is the proportional deviation of the observed milk yield deviation from the expected milk yield. With respect to the smallholder Jersey breed, no relationship was found that could explain the proportional milk yield deviation. The smallholder herd was shown to be underperforming, considering the potential for higher milk yields of the two breeds. In the quest to gain a greater understanding of the dynamics of smallholder dairying, the sample of 118 farmers was further analysed using multivariate statistics to categorise them based on their herd sizes, herd structures, management and success perceptions in dairying. The analysis produced three clusters (categories): cluster 1 had the largest herd sizes and poor milk production efficiency; cluster 2 had intermediate herd sizes, the highest number of farmers and more efficient milk production per cow. This cluster, however, had the highest proportion of calf mortalities. Cluster 3 had the smallest herd size, the lowest calf to cow ratio and the second highest calf mortality. Record keeping across all clusters was very poor and the average milk yield per cow was generally low. Most of the farmers do not appreciate the importance of annual calving of their cows as an integral part of the success of their dairy projects and winter feed supplementation is very poor across all the clusters. There remains a great need for the enlightenment of the farmers on the importance of good nutrition, breeding, calf rearing and record keeping in successful dairying.
Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2005.