A tool for crop choice integrates gender and farmer's preferences

An inclusive participatory approach to facilitate the inclusion of marginalised individuals and groups, including women and the very poor, in agricultural intensification processes was developed as a part of a project undertaken in West Bengal, India and Bangladesh - ‘Socially Inclusive Agricultural Intensification (SIAGI)’ with Australian, Indian and Bangladesh researchers and NGO and government extension agents during 2016–2020.

The objective of this study was to design a crop-choice model to support extension agronomists in engaging with the farming communities more effectively using a quantitative analysis tool. These groups are typically excluded from development opportunities that can favour farmers with established networks and existing capital.

The paper based on this ‘Integrating gender and farmer's preferences in a discussion support tool for crop choice’ explored how agricultural system models can be inclusive and allow participation and eventual application by NGO and government extension agents, using a process of gender-sensitive contribution.

The study was done in northern West Bengal and southern Bangladesh, where rabi crops, sown in winter and harvested in the spring, are an important source of income and nutrition for the target communities. The model was used to explore the consequences of different crop choices on income, gender-specific labour, use of inputs and markets, and to reveal the trade-offs of pursuing different crop choice pathways in the context of agricultural intensification.

Discussion

The study tried to explore if systems models can be developed that allow user engagement to explore options for crop choice in an attempt to bridge gap between modelling tools and their use, a need that was highlighted by Antle et al. (2017) and consistent with McIntosh et al. (2008) arguing the importance of bridging the gap between design and use by engaging users and other stakeholders.

The study reinforced the fact that for models to be useful discussion tools, they need to incorporate the preferences of the participating farmers so they become realistic to the situation on the ground. The other key learning is that a gender-sensitive approach helped to unpack the variation across gender and is especially critical where female members of the farming community take significant responsibilities in farming activities.

Including extension agents/NGO partners as intermediaries and potential facilitators of the model from the conceptual stage to model, delivery is critical for continued use of these tools post-project life. For farmers, the learnings are that understanding the cost of cultivation is equally important as the focus on revenue, and that models such as this help explicitly to lay out the costs of cultivation.

The male and female farmer preferences were explicitly expressed, resulting in different crop choices and facilitating a structured discussion among themselves on the reasons for the preferences and the pros and cons of these choices. The outcomes of this approach are consistent with Groot et al. (2012) suggestion that the utility of bio-economic modelling tools' role in design of mixed farming system has a strong potential to support learning by farmers, NGO/extension agents and scientists.

A key innovation of the model has been the inclusion of gender in its design so male and female farmers could participate equally in crop choice discussions. This approach helped facilitate the inclusion of often excluded individuals and groups in agricultural development decisions and processes.

Historically, gender inequality remains a deeply entrenched institutional barrier to economic empowerment in development settings (Hansda, 2018). Using the scoring and weight elicitation process, the model facilitated both male and female farmers to input their preferences of crop choice allowing model outputs to be consistent with their individual preferences across the seven variables viz., water, risk, markets, self-consumption, cash flow, labour and price volatility.

Gender-specific preferences helped with highlighting differences in perspectives between male and female farmers. While these discussions are a regular feature in farming families, the scenario development activity enabled a more explicit expression of the choices. Male and female farmers priorities and preferences on which crop to grow differ for a number of reasons including labour, regular cash flow (e.g. chilies) versus one-off income (e.g. potatoes).

The ability of the model to differentiate the crop choices to reflect the preferences and priorities of the male and female farmers is a key contribution of this approach. The engagement with male and female farmers on capturing the preferences and including in the model that eventually reflected in the crop choices provided a basis for objective discussions.

The model scenarios presented are a sample from potentially hundreds of scenarios that can be generated with the model. These scenarios are those that participating farmers indicated during the workshops held with them in the case study villages.

The objective of the workshops was to expose users to the model and ‘validate’ the model results using their preferences of crop choice. Feedback received from farmers made it clear that the choices made via the model interaction corresponded to their preferences. This helped to build confidence of the participating farming community to generate of scenarios to explore options in collaboration with NGO extension partners and researchers.

These scenarios are useful in discussions among farming communities and the eventual decision on which crop to plant in the upcoming season is entirely up to them based on the model generated options and various variables that are not included in the model such for example access to credit, expertise in growing a certain crop, access to timely inputs, family circumstances among many others.

This tool may also be useful in assessing new or emerging agronomic practices (with which farmers are currently unfamiliar) from a socio-economic perspective. The model interface was deliberately designed with ease-of-use as an objective consistent with Rose et al. (2018) suggestion of user-centred design practices.

Feedback on the utility of the model from farmers has clearly indicated an improved understanding of the various components which requires consideration before making crop choice decisions. Participating farmers, NGOs and academic partners commented that an important asset of the modelling was that it provided them with a better appreciation of the various inputs that were applied in growing different crops in the region, and costs and revenues as a result of their crop choices.

As regards the level of interactions between the ‘modellers’, farmers and the ‘NGO extension agents’ that would be required, it is evident from the study that a collaborative learning process between key stakeholders i.e., researchers, extension staff, NGOs and participating farmers is critical.

The study suggests that male farmers were more concerned over market, profit, and the underlying risks, while female farmers were more focused on self-consumption of the produce by their family members, labour requirement, and regular flow of returns.

Decision-making practices in the households is a collective process with the participation of both men and women members where women could freely express their opinions over any crop choice and men listened to their concerns carefully before taking a final call.

The final decisions are often driven by the objectives of farming, which in turn depend on whether the household head is male or female. Male and female farmers came together and worked in a group in this activity where extension officials and practitioners involved themselves in a supportive manner.

This created a space for dialogue and mutual consideration among men and women farmers as well as among all the stakeholders. The extension services officials reflected that this engagement tool will make their future interventions more informative and hence convincing to the farmers.

Conclusion

This study demonstrated that appropriate design and development principles enabled ‘complex’ systems models to be used by NGO partner/extension agents to engage with farming communities as discussion support tools in farming decisions. The value of modelling tools to bring together researchers, extension agents and farmers in farming decision-making helps in the development process bringing in legitimacy and building trust (Cash et a., 2003; Sterk et al., 2011).

In addition to the inclusion of development actors, participatory model development allows for the brokering of diverse knowledge types (between science and community and across multiple disciplinary boundaries (Adelle, 2015). Importantly, the co-development process has had a knowledge validation effect in that it provides some legitimacy to farmers' existing knowledge, which helps to build confidence in farming decisions.

Using the reflective learning process, the researchers highlight that the modelling is not an end in itself but should support a co-learning process among researchers and the farming community (Norstrom et al., 2020). Farming systems models need to consider the gender dimension and its critical role in farm decision making and how this can be included in models to reflect the diversity of the decision process.

While the modelling tool may support informed discussion in making cropping choices, the outcomes of improved financial and food security will be a diffused pathway. The attribution of these outcomes from the tool application needs to be carefully calibrated while emphasising that this tool is not a prescriptive tool but rather a discussion tool.