| الوصف: |
Crop growth models can be useful tools in evaluating the impacts of different tillage systems on the growth and final yield of crops. A tillage model was incorporated into CROP-GRO-Soybean and tested for conditions in Ames, IA, USA. Predictions of changes in surface residue, bulk density, hydraulic conductivity, runoff curve number, and surface albedo were consistent with expected behaviors of these parameters as described in the literature. For conditions at Ames, IA, the model gave good predictions of soil temperature at 6 cm depth under moldboard (R2 = 0.81), chisel plow (R2 = 0.72), and no-till (R2 = 0.81) for 1997 and was able to simulate cooler soil temperatures and delayed emergence under no-till in early spring. However, measured differences in soil temperature under the three tillage treatments were not statistically significant. Excellent predictions of soybean phenology and biomass accumulation (e.g. R2 = 0.98, 0.97, and 0.95 for pod weight predictions under moldboard, chisel plow, and no-till, respectively) were obtained in 1997. More importantly, the model satisfactorily predicted relative differences in soybean growth components (canopy height, leaf weight, stem weight, canopy weight, pod weight, and number of nodes) among tillage treatments for critical vegetative and reproductive stages in one season. The tillage model was further tested using weather and soybean yield data from 1995 to 1997 at Nashua, IA. Tillage systems considered were no-till, disk-chisel + field cultivator, and moldboard plow + field cultivator. Predicted yields for the 1996 calibration year were within 1.3% of the measured yields for all three tillage treatments. The model gave adequate yield predictions for the no-till (-0.2-3.9% errors), disk-chisel (5.8-6.9% errors), and moldboard (5.5-6.1% errors) tillage treatments for the two years of validation. A sensitivity analysis showed that predicted soybean yield and canopy weight were only slightly sensitive to the tillage parameters (less than 3% change with 30% change in ... |
