Sabina Sujecka
Sabina Sujecka

Determining the Water Retention Capacity of Naturally Fertilized Soil Through Machine Learning

The problem

It’s critical to take into account the issue of excess manure produced globally by animals as we work to address the pressing issue of climate catastrophe and adopt regenerative farming techniques. The soil, a non-renewable natural resource, is no longer healthy as a result of human dependence on synthetic fertilizers. We should think about the original fertilizer found in nature instead. It’s important to remember that the bulk of farms—roughly 84%—are modest enterprises with an area of fewer than two hectares. On the other hand, over 50 hectare farms make up just 1% of all farms. Nonetheless, the majority of the greenhouse gas emissions brought on by manure storage and application to the soil are attributable to these larger farms. In actuality, although synthetic fertilizers account for almost 20% of worldwide direct agricultural emissions, manure only accounts for 7% of those emissions. Manure emissions must be decreased through improved management and efficiency in order to counteract this. By promoting the use of manure and organic soil amendments, we can effectively address the issue of excess manure while reducing reliance on synthetic fertilizers and ultimately mitigating greenhouse gas emissions from agriculture. In order to do this, in this Omdena-Nitrolytics project, will be working on this subject using a data-centric approach.

The project goals

We aim to develop a tool to evaluate soil water retention and water-holding capacity when manure, charcoal, and compost are utilized. The main goals of this Omdena-Nitrolytics Challenge are:

  • Relevant data collection through different possible sources.

  • Demonstrate organic fertilizer use and how it improves water retention capacity.

  • Give farmers insights into crop water demands in real or near real-time to maximize water conservation.

  • Demonstrate enhanced capabilities with biochar application, and support intelligent irrigation.

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