Neural Modelling in the Exploration of the Biomethane Potential from Cattle Manure: A Case Study on Herds Structure from Wielkopolskie, Podlaskie, and Mazowieckie Voivodeships in Poland

Abstract

In the presented study, data on the size and structure of cattle herds in Wielkopolskie, Podlaskie, and Mazowieckie voivodeships in 2019 were analyzed and subjected to modelling with the use of artificial intelligence, namely artificial neural networks (ANNs). The potential amount of biogas (m3) from cattle manure and slurry for the analyzed provinces was as follows: for the Mazowieckie Voivodeship, 800,654,186 m3; for the Podlaskie voivodeship, 662,655,274 m3; and for the Wielkopolskie voivodeship, 657,571,373 m3. Neural modelling was applied to find the relationship between the structure of the herds and the amount of generated slurry and manure (biomethane potential), as well as to indicate the most important animal types participating in biogas production. In each of the analyzed cases, the three-layer MLP perceptron with a single hidden layer proved to be the most optimal network structure. Sensitivity analysis of the generated models concerning herd structure showed a significant contribution of dairy cows to the methanogenic potential for both slurry and manure. The amount of slurry produced in the Mazowieckie and Wielkopolskie voivodeships was influenced in turn by heifers (both 6–12 and 12–18 months old) and bulls 12–24 months old, and in the Podlaskie voivodeship by calves and heifers 6–12 months old. As for manure, in addition to cows, bulls 12–24 months old and heifers 12–18 represented the main factor for Mazowieckie and Wielkopolskie voivodeships, and heifers (both 6–12 and 12–18 months old) for Podlaskie voivodeship.