Abstract:Livestock and poultry manure may result in significant environmental challenges. Meanwhile, it is an advantageous raw material for the production of organic fertilizer due to the rich nutrients such as organic matter, nitrogen, phosphorus and potassium. Aerobic composting is an effective way to solve the livestock manure pollution problem and realize utilization of this valuable resource. However, composting is an extremely complex process of physical and chemical changes. Online detection tools of the key parameters are important for both composting process control and organic fertilizer quality assurance. Aiming to investigate the feasibility of online near infrared (NIR) spectrometer to conduct realtime analysis of moisture content (MC), pH value, electrical conductivity (EC), organic matter (OM), total carbon (TC), total nitrogen (TN) and carbon to nitrogen (C/N ratio) ratio in the whole composting process and evaluate its ability to accurately predict these changes. Totally 60 samples in the whole composting process were collected. The NIR quantitative analysis models of MC, pH value, EC, OM, TC, TN and C/N ratio were established by using the online NIR spectrometer combined with partial least square method. The research results showed that the online NIR spectrometer can realize the rapid detection of key parameters in the whole composting process (RSD<10%), with excellent predictions for MC and TN with R2C and RPD value of 0.94 and 3.62, 0.92 and 3.14, respectively, good predictions for pH value, TC and C/N ratio with R2C and RPD value of 0.90 and 1.89, 0.83 and 2.12, 0.82 and 215, respectively, approximate predictions for EC and OM with R2C and RPD value of 0.79 and 1.85, 0.80 and 1.93, respectively; the deviation between the NIRpredicted and measured values of each parameter was small, the NIR predictions were in good agreement with measured values as the composting process progressed. The above research results laid the foundation for realizing the process analysis of organic fertilizer production based on the online NIR spectroscopy.
