Guanghua Yin

Biochar Improves Soil Aggregate Stability and Water Availability in a Mollisol after Three Years of Field Application

A field experiment was carried out to evaluate the effect of organic amendments on soil organic carbon, total nitrogen, bulk density, aggregate stability, field capacity and plant available water in a representative Chinese Mollisol. Four treatments were as follows: no fertilization (CK), application of inorganic fertilizer (NPK), combined application of inorganic fertilizer with maize straw (NPK+S) and addition of biochar with inorganic fertilizer (NPK+B). Our results showed that after three consecutive years of application, the values of soil bulk density were significantly lower in both organic amendment-treated plots than in unamended (CK and NPK) plots. Compared with NPK, NPK+B more effectively increased the contents of soil organic carbon, improved the relative proportion of soil macro-aggregates and mean weight diameter, and enhanced field capacity as well as plant available water. Organic amendments had no obvious effect on soil C/N ratio or wilting coefficient. The results of linear regression indicated that the improvement in soil water retention could be attributed to the increases in soil organic carbon and aggregate stability.

Maize Yield Response to Water Supply and Fertilizer Input in a Semi-Arid Environment of Northeast China

Maize grain yield varies highly with water availability as well as with fertilization and relevant agricultural management practices. With a 311-A optimized saturation design, field experiments were conducted between 2006 and 2009 to examine the yield response of spring maize (Zhengdan 958, Zea mays L) to irrigation (I), nitrogen fertilization (total nitrogen, urea-46% nitrogen,) and phosphorus fertilization (P2O5, calcium superphosphate-13% P2O5) in a semi-arid area environment of Northeast China. According to our estimated yield function, the results showed that N is the dominant factor in determining maize grain yield followed by I, while P plays a relatively minor role. The strength of interaction effects among I, N and P on maize grain yield follows the sequence N+I >P+I>N+P. Individually, the interaction effects of N+I and N+P on maize grain yield are positive, whereas that of P+I is negative. To achieve maximum grain yield (10506.0 kg·ha−1) for spring maize in the study area, the optimum application rates of I, N and P are 930.4 m3·ha−1, 304.9 kg·ha−1 and 133.2 kg·ha−1 respectively that leads to a possible economic profit (EP) of 10548.4 CNY·ha−1 (CNY, Chinese Yuan). Alternately, to obtain the best EP (10827.3 CNY·ha−1), the optimum application rates of I, N and P are 682.4 m3·ha−1, 241.0 kg·ha−1 and 111.7 kg·ha−1 respectively that produces a potential grain yield of 10289.5 kg·ha−1.

Quantifying Spatial Variability of Selected Soil Trace Elements and Their Scaling Relationships Using Multifractal Techniques

Multifractal techniques were utilized to quantify the spatial variability of selected soil trace elements and their scaling relationships in a 10.24-ha agricultural field in northeast China. 1024 soil samples were collected from the field and available Fe, Mn, Cu and Zn were measured in each sample. Descriptive results showed that Mn deficiencies were widespread throughout the field while Fe and Zn deficiencies tended to occur in patches. By estimating single multifractal spectra, we found that available Fe, Cu and Zn in the study soils exhibited high spatial variability and the existence of anomalies ([α(q)max−α(q)min]≥0.54), whereas available Mn had a relatively uniform distribution ([α(q)max−α(q)min]≈0.10). The joint multifractal spectra revealed that the strong positive relationships (r≥0.86, P<0.001) among available Fe, Cu and Zn were all valid across a wider range of scales and over the full range of data values, whereas available Mn was weakly related to available Fe and Zn (r≥0.18, P<0.01) but not related to available Cu (r = −0.03, P = 0.40). These results show that the variability and singularities of selected soil trace elements as well as their scaling relationships can be characterized by single and joint multifractal parameters. The findings presented in this study could be extended to predict selected soil trace elements at larger regional scales with the aid of geographic information systems.

Effects of stubble and mulching on soil erosion by wind in semi-arid China

Soil erosion is a growing challenge for agricultural production in Northern China. To explore the effect of variation in stubble height and mulching biomass on soil erosion caused by wind, we conducted a field experiment using a quadratic rotation combination design. Results showed that the quantity of straw mulch was the dominant factor affecting soil erosion, and stubble height was of secondary importance. The soil water content in stubble and straw mulching treatments was higher than in a control treatment at 0–20 cm soil, and the tendency in the amount of soil water content was opposite to the amount of wind erosion (r = −0.882, n = 10, p < 0.01). The change in soil water content observed in the stubble and mulch treatments at the 15–20 cm depth was higher than the change from 0–5 cm to 5–10 cm. Combined, the influence of a stubble height of 34 cm and mulch quantity of 4260 kg·ha−1 lowered the amount of erosion to 0.42 t·ha−1, and increased the corn yield to 11900 kg·ha−1. We determined that those were the most appropriate levels of stubble height and straw mulch for crop fields in the semi-arid regions of Northern China.

The research and application of liquid membrane

By the serious soil “white pollution”, the research and application of liquid membrane for the prevention of soil pollution caused by plastic mulch is of great significance. The article reviews the development process of the liquid membrane materials, summarizes the application effects of different liquid membranes on soil improvement and water use, points out limitations of liquid membrane and the future development trend. With natural biodegradable materials (especially the industrial and agricultural waste) as raw material to develop new type of multifunctional biodegradable liquid membrane is a hotspot of current research of liquid membrane. Past research is mainly for agricultural water saving and moisture conservation, the future research should strengthen the study of soil degradation, soil and water conservation and the control of degradation rate.

Analysis of Grain Yield Prediction Model in Liaoning Province

Based on agricultural production data of Liaoning Province from 1980a to 2009a, using stepwise regression method, the gray prediction method, BP neural network, the grain yield prediction model was respectively established in Liaoning Province, China. The grain yield was predicted with these models, and models were compared. The results show that the yield forecasts relative error of the stepwise regression model, gray prediction model, BP neural network model are respectively: 3.41%, 6.59%, and 1.16%. Among the three models, the order of best fit is the BP neural network model, the less is the stepwise regression model, the least is the gray model. It was proved that the BP neural network model is optimum one with high correspondence degreed and high accuracy for food production forecast in Liaoning Province.

Prediction of Precipitation Based on Artificial Neural Networks by Free Search

FS-BP model was used to try to predict precipitation. The last six years’ precipitation were selected as input variable and the next year’s precipitation as output variable. The results show that the mean relative error of the prediction is 2.92%. T-test and regression analysis indicates that the predicted value differs just slightly from the observed value and their correlation coefficient was 0.9901.The FS-BP model is quite higher than BP model in accuracy and stability, and serves as useful tool in further research on prediction of precipitation.