Data-driven technologies in the agri-food sector have the potential to enhance agricultural productivity, sustainability, and efficiency.
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This is part of the essay series: World Population Day 2024
The agri-food sector in the past decade has faced tremendous challenges from climate change, population rise, and resource constraints to shifting consumer behaviour. It is thus necessary to transform the agri-food system to make it sustainable and resilient. Food system transformation needs to ‘ensure that food systems elevate and prioritise health, inclusion, sustainability, resilience, climate, and the environment.’ This shift requires the adoption of a data-driven approach to enable informed decision-making and maximise the use of resources to improve productivity. An analysis of the state of food systems worldwide indicates ‘Better data is urgently needed to monitor progress in food safety, off-farm livelihoods tied to agriculture and food systems, food loss and waste, agriculture and food systems’ economic contributions, governance, and agriculture and food system resilience.’
Data-driven technologies in the agri-food sector have the potential to enhance agricultural productivity, sustainability, and efficiency. For example, precision agriculture technology not only improves crop yield but also enables farmers to optimise resource utilisation and reduce the environmental impact. Evidence has shown that data on soil moisture and nutrient levels can inform farmers about the optimal amount and timing to use water and fertiliser, reducing waste and improving crop yields. Data analytics can optimise resource management and supply chain to identify gaps and ensure sustainability. Additionally, it can reduce food waste, enable sustainable sourcing and improve the supply chain efficiency to minimise carbon footprint.
Data-driven technologies in the agri-food sector have the potential to enhance agricultural productivity, sustainability, and efficiency. For example, precision agriculture technology not only improves crop yield but also enables farmers to optimise resource utilisation and reduce the environmental impact.
A sustainable agri-food system is critical for food production to meet the current demand and balances the environmental, social and economic concerns in agriculture. Data science in sustainable agriculture plays a pivotal role in promoting farming efficiency and reducing environmental impact. Data science can help integrate data from all sources to help farmers predict crop yield and optimise inputs and healthier crops.
The use of data to track the journey of food products from the field to consumption enhances traceability, transparency, and accountability. Traceability is essential in ensuring food safety and prevent foodborne outbreak or even recalling contaminated products. Like Walmart’s blockchain technology that does real-time tracking of the produce from farm to store. Also, the data on food quality, nutritive value and packaging are essential for maintaining quality and safety standards along with consumer trust. Big data and machine learning can help to monitor food security in real-time. The World Food Programme uses the Vulnerability Analysis Mapping, to identify the vulnerable population and track food security trends.
Investing in data-driven agriculture has been proven to increase agricultural production and productivity through climate change mitigation and efficient resource utilisation. Data-driven agriculture empowers smallholder farmers through information and innovation to enhance their livelihood and resilience. Mobile applications can provide real-time information to smallholder farmers on weather, crop updates, farming practices, and pest management. Additionally, data-driven platforms can improve efficiency, market access, and financial inclusion for the smallholder. Digital marketing and e-commerce platforms like Agri Marketplace and Farmcrowdy are innovations to build sustainable food solutions through technology. Agri e-commerce platforms are emerging across developing nations, empowering rural agricultural communities.
Investing in data-driven agriculture has been proven to increase agricultural production and productivity through climate change mitigation and efficient resource utilisation. Data-driven agriculture empowers smallholder farmers through information and innovation to enhance their livelihood and resilience.
The integration of data into agri-food systems fuels innovation and research by providing valuable insights and evidence for developing new technologies and practices. Agricultural research institutions and private companies can leverage data to conduct experiments, model scenarios, and evaluate the effectiveness of interventions. Data on crop breeding and resilience can inform farmers on crop diversification and new varieties with improved yield and nutritional value. Moreover, multistakeholder platforms and data-sharing initiatives enable researchers, policymakers, and industry stakeholders to work together and address complex challenges. A 2023 report by FAO on ‘Harvesting change: Harnessing emerging technologies and innovations for agrifood Global foresight synthesis report systems transformation’ calls for ‘bridging the gap between the start of technology and its practical application and need for a conducive environment to maximise benefits across the entire agri-food ecosystem’.
Despite the numerous benefits of data in transforming agri-food systems, several challenges that exist need to be overcome to utilise its potential. The biggest challenge is the quality of data and its standardisation which hinders effective data analysis. A lack of awareness among farmers and stakeholders and expertise to collect, analyse, and interpret data effectively. Also, the cost of collecting and analysing the data is high, thus ensuring a return on investment is challenging. Ensuring the quality, accuracy, and completeness of data is a fundamental challenge. Access to data by the smallholder farmer is a challenge in developing regions, due to poor market linkage and the lack of infrastructure. Bridging the digital divide and addressing disparities in technology adoption is essential for inclusive transformation.
Despite the numerous benefits of data in transforming agri-food systems, several challenges that exist need to be overcome to utilise its potential. The biggest challenge is the quality of data and its standardisation which hinders effective data analysis.
It is clear that data can enable transformation of the agri-food system through improved market access, enhancing food safety, production, and sustainability. Stakeholders can make informed choices and maximise resource utilisation using data analytics. To improve the agri-food system, governments need to invest in data collection and statistical systems at the national and sub-national levels. Further inclusive data governance and equitable data sharing are essential. Better collaboration and coordination among stakeholders—governments, donors, and non-state actors—is crucial to support data governance for addressing agri-food systems.
Shoba Suri is a Senior Fellow at the Observer Research Foundation.
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Dr. Shoba Suri is a Senior Fellow with ORFs Health Initiative. Shoba is a nutritionist with experience in community and clinical research. She has worked on nutrition, ...
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