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Heavy clay soils are globally widespread but their poor drainage and poor aeration limit their use for agriculture. This study was designed to test the effect of the amendment of biochar (BC) from woody shrubs on drainage/saturated hydraulic conductivity (Ksat), soil aeration/air capacity, available water capacity and biomass and grain yields of maize. In a field experiment, BC from Gliricidia sepium was applied in planting basins or rip lines at 2.5% and 5% w/w in addition to a control without BC. The maize biomass and grain yields were higher in BC treated plots compared to control (p<0.05) during the 2012 and 2013 seasons. There was no significant difference in the yields between 2.5% and 5% BC treatments (e.g. grain yield were 6.6 and 8.1 t ha-1 in 2012 and 9.3 and 10.3 t ha-1 in 2013 compared to control with 4.2 and 6.7 t ha-1 in 2012 and 2013, respectively). Soil from the same field site was also mixed with a similar woody shrub BC from Eupatorium adenophorum in the laboratory at rates of 2.5%, 5% and 10% BC w/w and a control without BC. The mixtures were then incubated and subjected to two wet-dry cycles for two weeks. Core samples were taken from the incubated soil and tested for bulk density, Ksat and pF measurements. Total porosity and moisture at field capacity and wilting point were 72.3%, 43.7% and 23.7%, respectively, and not affected by BC amendment (p>0.05). In contrast, bulk density decreased linearly by 0.011±0.002 g cm-3 per percent BC added (p<0.001). Ksat and air capacity of the soil were 288 cm day-1 and 30.9%, respectively falling within the generally accepted optimal range. Both Ksat and air capacity followed a significant quadratic relation (p<0.05) upon BC addition, decreasing at low BC doses, reaching a minimum at 3–5% BC and increasing at higher doses. Results allowed a partial attribution of the yield increases to changes in soil physical properties such as changes in bulk density and not clearly to Ksat and air capacity. [ABSTRACT FROM AUTHOR]

Effective pretreatment of spectral reflectance is vital to model accuracy in soil parameter estimation. However, the classic integer derivative has some disadvantages, including spectral information loss and the introduction of high-frequency noise. In this paper, the fractional order derivative algorithm was applied to the pretreatment and partial least squares regression (PLSR) was used to assess the clay content of desert soils. Overall, 103 soil samples were collected from the Ebinur Lake basin in the Xinjiang Uighur Autonomous Region of China, and used as data sets for calibration and validation. Following laboratory measurements of spectral reflectance and clay content, the raw spectral reflectance and absorbance data were treated using the fractional derivative order from the 0.0 to the 2.0 order (order interval: 0.2). The ratio of performance to deviation (RPD), determinant coefficients of calibration (), root mean square errors of calibration (RMSEC), determinant coefficients of prediction (), and root mean square errors of prediction (RMSEP) were applied to assess the performance of predicting models. The results showed that models built on the fractional derivative order performed better than when using the classic integer derivative. Comparison of the predictive effects of 22 models for estimating clay content, calibrated by PLSR, showed that those models based on the fractional derivative 1.8 order of spectral reflectance ( = 0.907, RMSEC = 0.425%, = 0.916, RMSEP = 0.364%, and RPD = 2.484 ≥ 2.000) and absorbance ( = 0.888, RMSEC = 0.446%, = 0.918, RMSEP = 0.383% and RPD = 2.511 ≥ 2.000) were most effective. Furthermore, they performed well in quantitative estimations of the clay content of soils in the study area. [ABSTRACT FROM AUTHOR]