1986). Strip cropping corn and grain legumes: A review.Abstract. Multiple cropping systems are prevalent in many parts of the world, and alternating strips of corn and soybeans or dry beans have been used by farmers in the temperate region. Strip cropping has the potential to reduce erosion on hilly lands, to allow a crop rotation in the field if strips are changed from one season to the next, and to increase total system yields. Results from several experiments in Eastern and Midwest U.S. show considerable variation in production among years and locations. Corn grown in narrow strips has yielded from 10 to 40 percent over sole cropping, while soybeans or dry beans in narrow strips suffer yield reductions of 10 to 30 percent due to light, water and nutrient competition. There has been no definitive research to quantify the relative importance of these factors in the competitive interface between corn and legume rows. With wider strips there is less increase in corn yields and less reduction in legume yields compared to sole cropping. Changes in component crop yields also depend on rainfall, and may be influenced by the variety of each component crop and by the width of strips. Rarely does total yield in a strip crop system fall below the average monoculture performance. In years of adequate rainfall, production of strip crops may outyield sole crops by 10 to 20 percent. Potential production of strip cropping systems is reviewed, and projected soil conservation is estimated using the Universal Soil Loss Equation.
Five simplified methods of estimating the relationship between hydraulic conductivity K and water content θ were compared in this study. Redistribution of water following constant rate infiltration (steady state) was monitored for a 10‐day period at 100 locations and seven depths at each location within a 5000‐m2 fallow sandy loam field. All the methods assumed a unit hydraulic gradient during redistribution and an exponential relationship between k and θ of the form K(θ) = k0 exp [β(θ − θ0)]. The five methods were the θ, flux, and CGA methods (Libardi et al., 1980) and two methods based on a Lax solution of the Richards’ equation (Sisson et al., 1980). Water content data were used to calculate K0 and β by each method at each depth and location. Soil water flux was estimated for selected depths using appropriate mean and variance values of K0 and β for the field. Relative differences between the methods are briefly discussed.
Slope geometry and the associated variation in soil properties influence runoff, drainage, soil temperature, the extent of soil erosion and deposition, and crop yields. With the current emphasis on prescription farming, approaches are needed to more effectively match inputs to production system needs while accounting for variation in soil and water resources within a field. The objective of the study was to develop simplified regression models to predict soil properties on different landscape positions from observed values on the nearly level upper interfluve. Soil samples were taken from the upper and lower interfluve, shoulder, upper and lower linear, and footslope at each of four sites in eastern Nebraska. Predictive equations were developed for 20 soil properties using multiple linear regression. Independent variables included were observed values of the property being modeled from the upper interfluve, sampling depth, and an irrigation code. Of the 100 models developed, only eight included significant contributions from all three independent variables. Models for pH, organic matter, electrical conductivity, exchangeable K, base saturation percentage, and available P and K consistently had R2 values greater than 0.50. The upper interfluve contributed significantly to the prediction of each of these properties except electrical conductivity. A comparison between average observed and predicted values for each soil property at each sampling depth revealed that the observed values generally fell within a 95% confidence interval about the predicted values. The confidence interval half‐width was generally <10% of the mean for the observed values. Further evaluation with independent data sets could be used to help strengthen and refine such generalized or geographically based models.
Differences in traffic and tillage intensity among positions in ridge tillage create distinctly different environments for microbial activity. This study was conducted to assess the impact of long-term controlled wheel traffic on soil respiration in ridge-till and to use correlation analysis to identify relationships between soil respiration and soil physical and chemical properties. Soil respiration was evaluated from 0 to 30 cm in one row, one tractor-trafficked interrow, and one nontrafficked interrow of continuous corn (Zea mays L.) and continuous soybean [Glycine max (L.) Merr.]. Soil respiration was measured on disturbed samples at three levels of water-filled pore space (WFPS) by gas chromatography for 25 d. Properties assessed included bulk density, soil strength, texture, aggregate-size distribution, saturated hydraulic conductivity (/Cat), water retention characteristics, organic C, and total N. Soil respiration was greatest at 0 to 7.5 cm in each position and decreased significantly below that depth. Correlation analysis indicated microbial activity in-ridge-till varied spatially in relation to changes in the soil physical environment. Soil respiration was negatively correlated with bulk density at each WFPS. The K sn was positively correlated with soil respiration at 0 to 7.5 cm for each WFPS. Under drier soil conditions, as exemplified by 47% WFPS, aggregates <1.0 mm and gravitational water were positively correlated with soil respiration at the 0 to 7.5 cm. Soil environments characterized by bulk density <1.4 Mg m" 3 and £* >10 cm h" 1 were associated with respiration rates >4 and 12 mg COj-C L"' soil d~', respectively.
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