Small farmers in low-and-middle-income countries are disproportionately affected by uncertainties under which they have to make decisions. However, decision-making may not be purely rational as it could be influenced by affective or emotional states. Compared to integral mood, there are few studies investigating whether incidental mood influences farmers’ monetary decisions under uncertainty. This paper applies the Cumulative prospect theory (CPT) model to determine farmers’ attitudes under uncertainty and examines the association with farmers mood, measured by direct elicitation during an experimental session. Participants (farmers) were mostly uncertainty averse in the gain domain. In contrast, farmers were uncertainty-seeking for losses. A one-way ANOVA was conducted to examine the differences between groups in sad, neutral and happy mood states, followed by posthoc tests to determine which groups differed from each other. The results revealed statistically significant differences in uncertainty aversion, loss aversion, and the parameters representing how probabilities are perceived and weighted, i.e., sad, neutral and happy in the gain domain. However, there was an absence of a relationship between incidental mood and several CPT parameters in the loss domain. The paper highlights how understanding the association between mood and attitudes can be harnessed for a better quality of decision-making in various contexts. This finding has important implications for agricultural contexts where farmers often face uncertain outcomes and must make choices that involve potential gains and losses. Since the transfer of incidental moods to decision making is usually done unconsciously, it is crucial to eliminate or reduce the impact of negative moods on decision-making, especially where the outcome is likely to be suboptimal.