Closing the Research Gaps in Sustainable Farming

Our approach is grounded in two key principles that form the foundation of our research methodology: bibliometric research and statistically designed trials.

Recognizing the importance of research methods is crucial for the progress of sustainable agriculture. They play a key role in guiding the industry towards more environmentally friendly and efficient practices.

At LoginEKO, we are committed to leading the way in sustainable farming research. Our approach is grounded in two key principles that form the foundation of our research methodology: bibliometric research and statistically designed trials.

Bibliometric Research: Detecting Key Areas for Advancing Organic Practices

Bibliometrics is a powerful research tool that allows us to delve deep into the vast world of agricultural research. By analyzing large datasets of scientific publications, we can uncover the trends, gaps, and opportunities in the field of sustainable farming. This method provides valuable insights into overlapping research topics, and helps us identify the areas where we can make the most significant impact.

Marrying agronomy and AI for a transition to sustainable farming.

At the core of our bibliometric research is now our advanced chatbot, GrainBrain,  which is based on Large Language Models (LLMs). This advanced tool enables us to rapidly scan and comprehend the extensive body of literature in the field of sustainable farming. It also helps us pinpoint areas that require special attention and further investigation. Through this, we can ensure that our research efforts are focused on the most critical and pressing issues within the realm of sustainable agriculture.

To get a glimpse of our bibliometric research in action, you can read our first bibliometric study. This study provides valuable insights into the current state of sustainable farming research and sets the stage for our future endeavors.

Statistically Designed Trials: The Importance of Real-World Validation

While bibliometric research allows us to identify promising areas of study, the scientific method cannot underplay the importance of real-world validation. This is where statistically designed trials come into play. Properly designed trials provide us with the empirical evidence we need to determine what truly works in sustainable farming.

Our in-house teams are a unique blend of agronomists, data scientists, and engineers. This diversity of expertise allows us to plan and execute trials with precision and purpose. We conduct these trials on selected plots of our expansive 3,700-hectare farm, which enables us to validate our findings in real-world farming environments.

We can plan and execute trials on a real large-scale farm, demonstrating that a transition to sustainable farming  is possible.

Putting latest technology at par with hands-on trials

By combining the power of data-driven insights with hands-on experimentation, our Agro R&D team plows its way toward discovering and vetting new sustainable practices in agriculture.

Some of our already implemented trials have yielded fascinating results. For example, we have explored how peas can serve as effective green manure, the benefits of malting barley in crop rotation for sustainability, and the advantages of intercropping wheat with perennial legumes as a nitrogen source. These trials are at the forefront of our mission to transform large-scale agricultural production.

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Assessing green manure impact on wheat productivity through Bayesian analysis of yield monitor data

April 24, 2024

Agronomy research traditionally relies on small, controlled trial plots, which may not accurately represent the complexities and variabilities found in larger, real-world settings.

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Food and Climate Change: The Power of Food Choices

April 22, 2024

The power lies in our hands—or rather, on our plates. With each meal, we wield the ability to shape a more sustainable future.

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Full Traceability & Transparency: Myth or Reality?

April 18, 2024

Our data-driven approach to traceability enables comprehensive data collection at every step of the production process.

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