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1. 1989 Agronomic Implications of the 1988 DroughtHistorical Perspective Grain marketing analysts have a rule of thumb that says, "A short crop has a long tail". From the agronomist's point of view, a similar statement could be made for the agronomic implications of the 1988 drought. And coming on the heals of several years of depressed prices, there are some psychological effects that must be considered in working out management plans for farmers for the 1989 growing season. Since the 1988 season broke all previous records for extent and duration... |
2. Variable-Rate Fertilizer Application- Update and EconomicsThe potential for application of computer-controlled, satellite-guided, variable-rate application systems for fertilizer has opened an interesting new area of research and development. While variable-rate application is not new--and does not require the com- puter or satellite systems to be useful--the technology is definitely helping to convince dealers and farmers that this concept has broader potential. Economic pressures and environmental concerns are leading them to take a closer look at how... |
3. Skip-Row Configuration and Plant Density Effects on Sorghum Grain Yield and Yield Component in Southern NebraskaEqual spacing of sorghum rows typically results in the highest grain yield when soil water is adequate throughout the season, but skip-row plan ting may be a means to reduce water deficits during reproductive growth stages. We evaluated the effect of skip-row planting configuration and plant population density on grain yield, yield components and water use efficiency at five locations in a transect across southern Nebras ka where annual mean precipitation ranges from 300 to 900 mm yr -1. Three row... |
4. Improving Digital Soil Maps for Site-specific Soil Fertility Management Using Feature SelectionDigital soil mapping (DSM) has become an attractive option to manage site-specific soil fertility management thanks to its capabilities of creating highly accurate, fine-resolution (e.g., 3 m) soil maps with uncertainty measures associated with soil property predictions. One approach to making soil maps with geospatial technologies is to build statistical models using machine learning (ML) based on the relationships between environmental covariates (e.g., digital terrain attributes, satellite,... C. Ferhatoglu, B.A. Miller |