Research of copper and zinc passivation prediction model during cattle manure composting based on uniform design-partial least squares method

The wood vinegar was elected the passivation materials and the key factors affecting the quality of compost for moisture content and C/N ratio. Each factor had six levels, uniform design was used for multiple factors level test, the test results were analyzed by using partial least squares regression, and the heavy metal passivation prediction model was established. Results showed that the test combination with 0.50% wood vinegar, 40% water content and 40C/N ratio had the maximum passivation effects for Cu and Zn (13.5% and 30.2%, respectively). Partial least squares regression was also applied to the test results. The prediction model for heavy metal Cu passivation effect was y_Cu=15.4748+0.3524x_A-0.1100x_B+0.0131x_C, where x_A, x_B, and x_C were wood vinegar content, water content, and C/N ratio, respectively. The cross-validation was: Q₂²=-2.0767 < 0.0985. The model reached precision requirement. The prediction model for heavy metal Zn passivation effect was y_Zn=34.3512 +11.0905x_A-0.2561x_B-0.0531x_C. The cross-validation was: Q₂²=-3.0863 < 0.0985. The model reaches precision requirement. In view of the multiple factors level complex composting system, the uniform experimental design combined with partial least squares analysis to effectively solve the experiment many times, and the problems of multiple correlation between factors, so that the precision and practicability of model was improved.