Blog

An overview of how CIAT is using data analytics to help farmers make better on-farm decisions.

Vietnam’s technology innovators and farmers convened at a workshop to gain a deeper appreciation of the challenges in the field on the one hand, and existing technology solutions on the other.

The GDPR and data science for agricultural development are at odds when it comes to delivering personalized products for the public good.

Data scientists need to be more serious about standardization, to make data interoperable, says Daniel Jimenez.

‘We need to do ‘preemptive breeding’ if we want to sustain bean production under the more erratic climate of the future’

The Global Biodiversity Informatics Outlook is a new framework to deliver biodiversity knowledge. Find out more about how it will help gather unprecedented evidence about biodiversity and inform better decisions.

Crop Ontology provides scientists and breeders with a common language that describes crop phenotypes and interprets descriptions provided by farmers for the performance of the varieties they prefer.

Daniel Jimenez on how Data-driven agronomy community of practice will advance data-driven agronomy to support the farmers, technicians and researchers committed to meet the Sustainable Development Goals.

Standardizing data is central to the success of the Global Crop Improvement Network to improve global integration of crop research.

A more comprehensive understanding of agricultural soils is needed to support sustainable development decision making – but collecting the necessary data is challenging.

Extension officers, radio, and mobile phones remain crucial for the farmers to access and discover agricultural information.

Transdisciplinary thinking is a fundamental requirement if we are to take meaningful steps towards using big data to solve complex socio-environmental problems.

Farmers are contributing to the huge amounts of information that can be harnessed for global food security solutions. But they need good allies to ensure its full, and ethical, potential is reached.

Does big data raise more questions than answers?

Big data in agriculture is instrumental not just for farmers who produce our food but for various stakeholders and along the agriculture value chain.

Big data can help smallholders can become agriculture’s big players.

As a young data scientist I strongly believe that if we can share the data we hold in our laptops, and take advantage of the daily generated data, we can have more nutritious food in our plates.

Quick disease monitoring and diagnosis of tubers, due to the limited number of experts and resources to cover the entire country, has been a problem for Uganda. How can big data solve this?

To achieve food and nutritional security, for present and future generations, an agricultural transformation is not only required. It is vital.