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The purpose of this paper is to analyse the effects of the determinants of farmer participation in value addition through cassava processing in Nigeria.

This study employs the probit model to analyse the determinants of farmer participation in value addition whereas the Tobit model is used to investigate the determinants of the extent of producer’s involvement in value addition using a data set of 400 cassava farmers drawn from the Oyo State of Nigeria.

The findings further indicate that among other factors, human capital factors including farmer age and location variable tend to reduce farmer participation in value addition through processing whereas experience and record keeping promote farmer participation in cassava processing. Institutional variables, notably membership of farmer association, extension access and credit access, enhance farmer participation in value addition. Finally, ownership of a radio set, a television set and access to electricity strengthen the value-adding capacity of farmers.

This study only considers the determinants of producers’ participation in cassava processing but does not explicitly analyse the impact of value addition on their profit margin. This issue would form a basis for future research to enhance knowledge in the extant literature.

The study suggests that if the value-adding capacity of farmers is strengthened, rural economy is likely to be improved upon through the proliferation of rural food processing enterprises.

Despite the relevance of developing food value chains in Africa and integrating farmers in them, there are limited studies on promoting value addition among farmers. This study contributes to narrowing this knowledge gap.

This study analyses income inequality and distribution patterns among key actors in the cassava value chain. The study also identifies factors that influence profit of key actors in the cassava value chain.

The study was conducted in Oyo State, Nigeria, using primary data from 620 actors, consisting of 400 farmers, 120 processors and 100 traders in the cassava value chain. The Gini coefficient was used to estimate income inequalities within and between actors. Multiple linear regression was applied to identify factors that influence the profit of the actors in the cassava value chain.

The result shows a gender pattern in the participation in the cassava value chain: men dominate in the production, whereas women mostly engage in processing and marketing of processed cassava products. We also find that incomes are unequally distributed among actors, favouring traders and processors more than farmers in the value chain. Women are better off in processing and trading of value-added products than in the raw cassava production. Spatial differences also contribute to income inequality among farmers in the cassava value chain. An increase in farmers and processors’ incomes reduces inequality in the value chain while an increase in traders’ income widens inequality. Age is significantly negatively correlated with actors’ profit at 1%, while educational level significantly increases their profit at 5%. Processors and traders with large households have a higher profit. We also find that farm size, experience and labour input have significant positive effects on farmers’ profit only at 5%. Membership in an association increases farmers and processors’ profit at 1 and 10%, respectively.

The study recommends that agricultural policies that promote agrifood value chains should aim at minimizing income inequality by targeting vulnerable groups, particularly female farmers to achieve sustainable development in rural communities.

Existing studies recognise income inequality in agricultural value chains in sub-Saharan Africa. However, there are few rigorous quantitative studies that address this pressing issue. Our paper fills this knowledge gap and suggests ways to minimise income inequality in the agri-food value chain, using the example of the cassava value chain in Nigeria.

The purpose of this paper is to analyse the impacts of storage losses and market development on the maize-selling behaviours of rural households in China.

Based on the survey data of 543 households from nine major maize production provinces in China, the authors introduce storage losses to a household's maize-selling decision-making model and use fractional logit model and ordered probit model to empirically analyse the impact of maize storage losses and market development on household maize-selling decisions in China. To overcome potential endogeneity problems, the authors select the weather at drying (whether bad weather occurs during the drying process) and harvest loss as instrumental variables and re-estimate the model.

The results show that increased storage losses prompt farmers to increase the proportion of maize sold within three months after harvest and sell maize in advance. Meanwhile, the degree of market development has a significant impact on farmers' maize-selling decisions. Other factors, such as the maize output, non-agricultural employment and awareness of loss control, also affect farmers' maize-selling behaviours.

The government should promote advanced storage facilities, reduce household storage losses, decrease the phenomenon of centralised sales after harvest and help farmers freely choose the suitable time for sales. The government also needs to strengthen market information releases and publicity, reduce transaction costs and help farmers make reasonable sales decisions.

The authors introduce storage losses as a separate variable in a farmer's grain-selling decision model to empirically analyse the impact of storage losses on farmers' grain-selling behaviours. Moreover, the authors analyse the impact of market development on household grain-selling behaviours in China. These findings can help avoid oversupply in the market during the harvest season and alleviate the pressure on the market from the supply and demand imbalance. These results are also beneficial for farmers waiting for a higher price and increasing their income.