An understanding of factors influencing smallholder farmers’ livestock ownership at the household level is vital in formulating pro-poor livestock production policies and technologies. Hence, this study examined factors that influence livestock ownership of smallholder farmers. The data was collected randomly from three purposively selected study areas in the OR Tambo District (King Sabata Dalindyebo, Port St Johns and Ingquza Hill local municipalities) in the Eastern Cape Province of South Africa using a cross-sectional survey of 650 households. A multivariate probit model (MPM) was used to estimate correlates of livestock species ownership at the household level. Results indicated that education, age, household income, marital status, religion, rainfall, gender, household size and employment status influence livestock species ownership at the household level. Therefore, efforts to promote livestock ownership and production should be guided by these significant explanatory variables in the study area. Interdependence among species was also noted (cattle and sheep; goats and pigs; sheep and pigs; cattle and goats; goats and sheep), suggesting complementarity among the different types of livestock species. This complementarity among the species can possibly be explained by functional diversity generic with multi-species livestock farming which is worth supporting to enhance biodiversity conservation, climate change mitigation, rural resource use efficiency and socio-economic sustainability at the household level.

Maize is an important staple crop for poverty reduction and global food security in Sub Saharan Africa. Food insecurity can be combated through adoption of productivity improving technologies, which include improved maize varieties. In that endeavour, South Africa has promoted various improved maize varieties which include open pollinated varieties (OPVs), hybrids, and genetically modified (GM) varieties. Despite this, the traditional landrace varieties have also been dominating in the country. However, the household food insecurity problem in the Eastern Cape Province of South Africa may signify a mis-match between maize varieties being promoted amongst smallholder farmers’ and their needs. It therefore necessitates a scrutiny of the food security status among users of different maize varieties, and the determinants of such food security. A cross sectional survey was conducted in Port St Johns, Mqanduli and Flagstaff in the Eastern Cape Province, South Africa. Data was purposively collected from a sample of 650 smallholder farmers using a structured questionnaire. Descriptive statistics, Household Food Insecurity Access Score and ordinal logistic regression model were employed to characterize, examine the household food insecurity status and the determinants, respectively. Fifty-six percent of the respondents were utilizing land race maize varieties, whilst 29% GMs, 10% combining GMs and landrace, 4% improved OPVs and 1% convectional hybrids. The average land area under maize was 1.09 hectares with average yields (t/ha) of 1.9, 0.5, 1.7 and 1.6 for GM, landrace, conventional hybrids and improved OPVs respectively. Fifty-five percent of households utilizing GM varieties and 61% of those combining maize varieties were food secure. The regression model showed that maize variety had significant influence on food security. The study found that GM maize, improved OPV, white maize and combination effects of GM maize was associated with reduction of household food insecurity. From the study, it can be put into perspective that use of white and improved maize varieties reduces household food insecurity. Therefore, to address household food insecurity, the study recommended targeting white maize varieties, especially GM white maize varieties which are highly productive and a positive influence on household food security.

Adoption of improved technology tends to recalibrate labour use in agricultural production. The study examined how the adoption of various maize varieties impacted labour use in smallholder production. The study utilised a structured pre-coded questionnaire-based survey of 487 smallholder maize farmers in South Africa. The purposive sample was obtained from Ingquza Hill and Port St John’s Local Municipalities in the Eastern Cape Province. A multinomial regression model and Monte Carlo Simulation were utilised to analyse the data. Statistical Package for Social Scientist (SPSS) version 23 as well as Excel were the statistical tools utilised. Through multinomial regression analysis, the study found that weeding labour was the most significantly affected by a change in maize variety. It was observed that as maize variety transcends in use from Landrace to GMO, improved OPV and conventional hybrid, ploughing and weeding hours tend to decrease. The harvesting, storage and shelling hours tend to increase. Utilising the Monte Carlo Simulation, the study also found an increased impact of maize variety utilisation on harvesting as well as on shelling and storage labour hours.  The study recommends that varieties be promoted taking cognizance of the labour dynamics to tier maximize suitability and labour-based productivity, reducing tedious labour use in ploughing and weeding, whilst promoting employment in harvesting, shelling and storage.