【半干旱地区作物覆盖对土壤性质的影响】Humberto Blanco-Canqui John D. Holman Alan J. Schlegel John Tatarko and Tim M. Shaver.Replacing Fallow with Cover Crops in a Semiarid Soil: Effects on Soil Properties. SSSAJ Vol. 77 No. 3 p. 1026-1034
Abstract
Replacement of fallow in crop–fallow systems with cover crops (CCs) may improve soil properties. We assessed whether replacing fallow in no-till winter wheat (Triticum aestivum L.)–fallow with winter and spring CCs for 5 yr reduced wind and water erosion increased soil organic carbon (SOC) and improved soil physical properties on a Ulysses silt loam (fine-silty mixed superactive mesic Aridic Haplustolls) in the semiarid central Great Plains. Winter triticale (×Triticosecale Wittm.) winter lentil (Lens culinaris Medik.) spring lentil spring pea (Pisum sativum L. ssp.) and spring triticale CCs were compared with wheat–fallow and continuous wheat under no-till management. We also studied the effect of triticale haying on soil properties. Results indicate that spring triticale and spring lentil increased soil aggregate size distribution while spring lentil reduced the wind erodible fraction by 1.6 times indicating that CCs reduced the soil’s susceptibility to wind erosion. Cover crops also increased wet aggregate stability and reduced runoff loss of sediment total P and NO3–N. After 5 yr winter and spring triticale increased SOC pool by 2.8 Mg ha–1 and spring lentil increased SOC pool by 2.4 Mg ha–1 in the 0- to 7.5-cm depth compared with fallow. Triticale haying compared with no haying for 5 yr did not affect soil properties. Nine months after termination CCs had however no effects on soil properties suggesting that CC benefits are short lived in this climate. Overall CCs grown in each fallow phase in no-till can reduce soil erosion and improve soil aggregation in this semiarid climate.
【土壤盐度估算校正模型】Xystus N. Amakor Grant E. Cardon Jürgen Symanzik and Astrid R. Jacobson. A New Electromagnetic Induction Calibration Model for Estimating Low Range Salinity in Calcareous Soils. SSSAJ Vol. 77 No. 3 p. 985-1000
Abstract
In arid and semiarid regions calibrating bulk soil salinity sensing technologies such as electromagnetic induction (EMI) relies on the assumption of uniformity of all soil factors influencing the reading except soil salinity to create a calibration model. When potentially perturbing factors are non-homogeneous or interact in a non-systematic way conditional mean calibration models based on the least squares method fail to completely describe the entire salinity distribution due to the violation of model assumptions (i.e. homogeneity of perturbing factors). Therefore a new approach is needed. The main objective of this study is to produce a salinity calibration model capable of reasonably predicting salinity directly from the EMI signal readings irrespective of the heterogeneity of perturbing factors. Toward this e