The cost of chemical fertilizers is increasing and becoming unaffordable for smallholders in Africa. The present study aimed to assess the impact of combined fertilization strategies using urea and animal manure (beef cattle manure and poultry litter manure) on rice yield and nutrient uptake. For this, a field experiment was carried out on a loam sandy soil in the Chókwè Irrigation Scheme. We set seven treatments in a Randomized Complete Block Design (RCBD), namely: T0: no fertilizer, T1: 100% urea, T2: 100% beef cattle manure, T3: 100% poultry litter, T4: 50% urea + 50% beef cattle manure, T5: 50% urea + 50% poultry litter and T6: 40% urea + 30% beef cattle manure + 30% poultry litter, replicated four times each. All treatments, except T0, received an amount of nitrogen (N) equivalent to 100 kgN·ha−1. Results revealed that the highest yield grain (425 g·m−2), plant height (115 cm), number of tillers (18) and thousand-grain weight (34g) were observed in treatments combining urea with manure (T4, T5 and T6) indicating that N supply in the mixture (urea + manure) is more efficient than in isolated applications of N (T1, T2 and T3). The data obtained in this study suggest that a combination of fertilizers (T6) lead to competitive yields and is thus recommended for best soil management practices.

Rice farming systems (RFSs) in southern Mozambique are very heterogeneous and diversified, which has implications for smallholders’ adoption of each RFS, as well as on rice production and productivity in the region. In this regard, it is important to understand: (i) which RFS typologies can be leveraged to improve rice production and productivity; (ii) the drivers for smallholder farmers’ decisions to adopt an RFS; and (iii) which policies/incentives could enhance existing RFSs. The present study was based on surveys of 341 smallholder rice farmers in the Chókwè Irrigation Scheme (CIS), southern Mozambique. Data on the productivity of rice, size of the herd, and total other crop types were used to frame the RFS typologies. A multinomial logit model (MLM) and multiple linear regression (MLR) were applied to determine the driver for each RFS, and predict the constraints for production and yield. Based on cluster analysis, four typologies of RFSs were identified: the subsistence farming system (FS), specialised rice FS, mixed crops FS, and rice–livestock FS. Farms with longer experience reported applying more fertiliser and seedlings per unit hectare. The availability of labour increased the likelihood of adopting the mixed crops FS and rice–livestock FS. Older households were more likely to adopt the subsistence FS, and live closer to the farming fields. Yield of rice was positively associated with inputs such as fertilisers, pesticides, and seedlings, as well as years of experience of the household. Our results suggest that smallholder farmers need more assistance and technical support to identify and adopt more productive and less costly RFSs in this region.