Where Should We Apply Biochar? Application of Bayesian Networks.

Over the past few decades, the list of environmental challenges facing the agricultural sector has grown in both size and complexity. While no universal solutions exist with respect to complex ecological problems, one important tool may be biochar. Biochar is one of the main by-products of a thermochemical process called pyrolysis that is used to transform low-density biomass to a higher-energy-density solid material. Researchers across the globe have proposed and verified the benefits of the use of biochar as a strategic tool with respect to soil and water quality issues and carbon sequestration. However, because of the complexity of biochar interactions with soil-crop-atmosphere, the long-term effects and the agronomic implications of biochar application are not well understood. Whereas, prediction models enable us to deal with this complexity and help to refine our understanding of the relationships between factors involved. In this study, we built a predictive model using Bayesian Belief Networks to estimate the biochar response for a wide range of soil and biochar properties. Using our limited dataset, preliminary results from the model showed that it understands the variable response of biochar to different soil properties.