Forecasting N2O emission and nitrogen loss from swine manure composting based on BP neural network

• Main Authors: Chen Haotian, Sun Shaoze, Zhang Baoli
• Format: Article
• Language: English
• Published: EDP Sciences 2019-01-01
• Series: MATEC Web of Conferences
• Online Access: https://www.matec-conferences.org/articles/matecconf/pdf/2019/26/matecconf_jcmme2018_01010.pdf

Nitrogen loss and greenhouse gas emission during compost will cause secondary pollution and waste nutrients. To address this issue, a predictive model was set up to obtain a clear knowledge of the N2O emission and nitrogen loss from swine manure composting. This paper collected 68 group data from 11 published papers about pig manure composting N2O emission and total nitrogen loss. Select 4 indexes were taken as predicted indexes include aeration rate, moisture content, C/N, and the amount of superphosphate to establish a BP neural network for forecasting the N2O emission and total nitrogen loss from composting. The analyses show that the mean error of N2O emission forecasting model is 1.17; the value of MAPE is 138.85%. As for nitrogen loss, the mean error is 24.72 and the mean absolute percentage error is 11.06%. Compare to the traditional linear regression, the BP neural network model has good accuracy on forecasting N2O emission and TN loss from manure composting. BP neural network has considerable application prospect in forecast nitrogen loss and greenhouse gas emission from composting.