Background Farm productivity on smallholder family-owned crop farms remains low despite several interventions to transform agriculture especially in developing countries. Farmers in rural areas face serious constraints that impede their productive capacities for the principal dietary staple, notably maize. Smallholder farmers have access to unprofitable markets that in turn make their enterprises less profitable. Efforts to commercialise smallholder maize production have not yielded desired results. This study, therefore, estimates profit efficiency and its determinants in the smallholder cropping systems in the Eastern Cape Province of South Africa. Methodology A random sample of 158 smallholder maize farmers was selected. A normalised translog profit function was then fitted by means of a one-step estimation of technical efficiency and its determinants using the STATA software. Results The results indicate that cost of fertiliser and area under cultivation for maize were the positive drivers of profitability. Complementarities among resources were very important determinants of profit. Conclusion The study concludes that family-owned farms have a positive effect on crop production. Farm profits rise with cultivated area in maize farms. Therefore, the study recommends that policy favouring smallholder commercialisation would improve farm profits.

As rural poverty deepens over much of Sub-Saharan Africa, smallholder transformation has become more urgent than ever before. A majority of rural people derive their livelihoods from agriculture, hence the urgent need for transforming the sector. The South African government launched a comprehensive land reform programme at the dawn of democracy in the country on the assumption that constraints on land size would be eliminated to make room for a more inclusive agricultural economy. The present study sought to assess how cultivated area affects food security and the profits of maize and cabbage farmers. The purposive sampling technique was used for the selection of study sites, from which 158 irrigators and homestead gardeners were selected. The data were then subjected to analysis by defining a maximum likelihood estimator that combines the seemingly unrelated regression (SUR) and one-way error correction model, to determine the factors influencing food security and farm profits. The model revealed diverse relationships, suggesting that location, farm type and income were important variables in explaining food security. The area under cultivation was found to influence profits for both crops. Policies in favour of technology adoption, market access and input use would greatly incentivize farmers to cultivate larger plots of land.

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