Agritech 2024

Data – the driving factor Digital public infrastructure (DPI) in agriculture is poised to become the critical enabler of agritech services in emerging economies. From an agritech provider’s perspective, developing innovative and customized services requires a range of current and historical datasets, including those for soil quality and temperature. Ease of access to high- quality, usable data can generate social-economic value for both farmers and industry alike. DPI for agriculture can include three components:23 –Platform: A technology platform allows the exchange of data with the consent of the owner of that data. In many cases the data owner and the data provider can be different entities. One example would be if an individual farmer’s data held by a government body is shared with the private sector once the farmer has given consent. The platform may include components such as identity and access management, a data explorer, application programming interface (API) gateways, consent management and a transaction engine. Data exchange platforms (DXP) open the door to the transformation of agricultural services through real-time access to multiple datasets. –Policy: There are three critical prerequisites for data sharing: to protect the individual; to prevent harm; and to promote innovation.24 These three requirements can form the basis of a data-management policy that can be introduced alongside data-management platforms. Such a policy should focus on creating value for all stakeholders with the aim of accelerating innovation in the agricultural sector while safeguarding data, both personal and otherwise. Any policy should ideally be designed under the data protection legislation of a given country – India’s Digital Personal Data Protection Act 2023 being one example. –Protocols and standards: As a traditional sector that has been around for millennia, agriculture is rooted in the cultural and socioeconomic circumstances of a given locale, as well as its climate, and this has led to varied local names for crops and crop diseases. As DPIs are scaled, there is a need to focus also on the interoperability of platforms and to standardize terminology and schemas. A well-known example of such standardization is the standard botanical Latin names of plant species, while the FAO has come up with a multilingual vocabulary named AGROVOC. More work is needed in the area of developing data standards, however, and the AgriJSON initiative being pursued by the Indian Institute of Science in association with the World Economic Forum is an example of efforts being made to do just that.25 Rwanda faces agricultural challenges, including limited arable land, water scarcity, a predominant smallholder farming system and susceptibility to climate change. The integration of emerging technologies like precision farming, drones, IoT and blockchain in food-supply systems has transformative potential, enhancing efficiency and transparency. Keen to collaborate with the C4IR Network, we look forward to adopting digital agriculture best practices, learning from impactful smallholder farmer case studies and fostering public-private partnerships for sustainable agricultural development. Joris Cyizere, Strategy Lead, Centre for the Fourth Industrial Revolution, Rwanda As DPIs continue to become more sophisticated, questions should be asked about what they might mean for individual farmers and how they might help farmers adapt to or mitigate risks such as those arising from climate change. The propositions for farmers, as well as the wider sector, with respect to emerging challenges, are as follows: –Hyperlocal customized solutions at farm level: DPIs could potentially offer farmers the ability to create a unique identity, providing an understanding of “who I am” (identity), “where I am” (georeferenced farm location) and “what I am growing” (crops sown and the area under cultivation). These three datasets help to establish an individual farmer as a distinct enterprise who can be offered a range of customized solutions at farm level, leading to efficient farm operations and enhanced revenues. –Adaptation of climate-smart agriculture: Climate change is negatively affecting yield, production and the quality of food and causing post-harvest crop losses. Climate-smart agriculture (CSA) can help farmers adapt to changes for the long term while preserving or improving yield and quality. For CSA to scale, it is important that service providers and farmers have access to historical as well as current data in order to generate information on weather patterns and their effects on production in a particular location, to identify vulnerabilities and define adaptation measures. Agritech: Shaping Agriculture in Emerging Economies, Today and Tomorrow 13