Biochar has been considered as a stable-carbon source for improving soil quality and long-term sequestration of carbon. However, in view of ecological environmental feedback and the tightly coupled system of carbon-nitrogen cycling, further attention has shifted to the effect of biochar on soil net nitrogen mineralization (SNNM). Recently, ecological evaluations of biochar were mostly based on laboratory incubation or pot experiments, ignoring external and uncontrollable natural factors. Therefore, the essential characteristics of local environments were not accurately described.
Materials and methods
In this paper, a nonlinear stochastic model of SNNM based on least squares support vector machine (LS-SVM) was set up to study the effect of biochar on nitrogen cycling in a field experiment. In order to explore this effect in natural conditions, partial derivative (PaD) sensitivity analysis of LS-SVM was firstly proposed, evaluated by the data from a known equation, and then applied to open the “black-box” stochastic model of SNNM.
Results and discussion
Comparing with the sensitivity analysis of artificial neural networks (ANNs), the RD values of LS-SVM PaD1 algorithm were almost the same as those of ANNs PaD1 algorithm. However, the RSD values of LS-SVM PaD2 algorithm were closer to the given equation. In the SNNM model, RD values of LS-SVM PaD1 algorithm of initial nitrogen, time, and precipitation were 21, 15, and 14 %, and the biochar RD value was only 0.51 %, implying that biochar did not influence SNNM directly. However, the cumulative RSD of the PaD2 algorithm of biochar with the other factors was 15.05 %, the maximum of the interactions, implying that it could greatly enhance the tendency for SNNM by interacting with other factors.
Conclusions
PaD sensitivity analysis of LS-SVM was a stable and reliable data mining method. In the SNNM model, initial nitrogen, time, and precipitation were the main controlling factors of the SNNM model. Biochar did not directly influence SNNM; however, it could greatly enhance the tendency for SNNM by interactions with other factors by decreasing the inhibitory effect of initial nitrogen on SNNM and modifying soil condition to change the effect of other factors on SNNM.
An air-injection press, which has holes punched in the heating plates, injects high-pressure air through the holes of one
plate into boards during press heating. The air-injection press can manufacture boards from high-moisture-content particles
by controlling blowouts of the boards. In this study, boards were manufactured from particles that had a moisture content
of 25% by using the air-injection press, which reduced the required pressing time. Boards manufactured by injecting air through
holes of 5 mm in diameter were of poor quality with a low internal bond strength of only 0.31 MPa. When the hole diameter
was reduced to 1 mm, the internal bond strength increased to 0.44 MPa. A high air-injection pressure of 0.55 MPa also resulted
in improved board properties over those for boards manufactured at lower pressures. This was probably because a large amount
of binder was released from boards through the 5-mm holes, together with water vapor, during air injection; the small-diameter
holes reduced the release of binder, resulting in better board properties. 相似文献