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Food security: All the way from field to fork

Our first blog in this series discussed climate information and how data can support small island developing states to build resilience in terms of infrastructure and targeted support for people affected by extreme weather events such as tropical cyclones.

With the majority of Small Island Developing States (SIDS) importing over 60% of their food supply, we also need to ensure that data is available for governments and regional organisations to be able to ensure that their food supply chains will be resilient enough to withstand a potential increase in demand and to mitigate against potential economic losses when extreme weather events occur.

Data cannot stop cyclones and floods from happening, but we can use it to build systems that help nations address the resulting logistical challenges by supporting informed decision-making.

IPP CommonSensing partners Sensonomic are focusing on providing data, prediction models, and training to support agricultural productivity for food producers in Fiji, Vanuatu, and the Solomon Islands in the face of climate change.

Fijian farmers
© Sensonomic

How do we support agricultural productivity for food producers?

Any number of elements can affect agricultural productivity. At the very start of the process, crops need harvesting, which means having enough people with appropriate skills and the right machinery in the right place at the right time.

For example, crops need to be stored and transported. They may also need to be processed in mills or factories. Following an extreme weather event, roads can be washed away or blocked. Storage facilities can be damaged and production facilities can be destroyed. The nearest port may be out of action. Even if you can find a way to move the crops from a farm to the nearest mill, for example, what will happen if that mill cannot then be used to process them? Even if you transport them to an alternative site, you may end up with an oversupply of crops at one mill, so that the excess cannot be stored and gets left to rot.

The management system needs to have an overview of the status of all parts of the supply chain at any time, to identify such issues, find alternatives and help smooth out any peaks and troughs. Not only this, but those using it need to be ready and prepared when a disaster occurs. The ability to run simulations to practice responses to various scenarios and take some decisions in advance is extremely valuable.

Ultimately, the goal would be to have a single system that a government or company could use to support production of any relevant crop. But we must start somewhere and, in the case of IPP CommonSensing, we have been looking at sugar cane production in Fiji, primarily because it is the countries second-largest export product after fish and we are able to access a wider range of historical data. Sugar cane production also involves processing and export stages, enabling modelling that can be applied to a wider range of other crops in future.

Sugar cane crops

How does the Covid-19 pandemic affect the project?

When we started this project, nobody could have foreseen that we would be completing it during a global pandemic that would prevent us from travelling to Fiji to complete aspects of the project, including training. Nothing is as effective as face-to-face training, and in some cases even today’s technology can be somewhat unreliable for remote training sessions.

A more important reality check provoked by the pandemic is that when people can’t travel due to sickness or travel restrictions, they are also unable to tend and harvest crops. This type of manual labour is skilled, so there’s a strong possibility that perfectly good food may rot in the fields, particularly in the south Pacific region where migrant skilled workers move between island states and New Zealand to carry out this work. In future, any severe weather events caused by climate change could also impact travel at crucial times in any crop’s lifecycle.

Global needs, local requirements

The most important thing when it comes to designing systems like CommonSensing is engagement from the start with all stakeholders to uncover their requirements and understand the local challenges; not everything is obvious and you can’t apply the requirements of one island nation to every other. The aim is to build systems that can be extended locally and used elsewhere with minimum additional development. For example, different levels of permissions to start this type of work, especially if there is a commercial element involved, as there is with sugar cane in Fiji. 

In our efforts to achieve Sustainable Development Goal 7, Zero Hunger, understanding local needs and requirements means that we can develop effective and relevant systems to support governments and organisations in small island nations through satellite-enabled technology to help them become more agriculturally resilient and efficient for the future, which is vital for every country around the world, no matter what they face due to climate change.



CommonSensing Team

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