Proceedings
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1. Nitrogen and Water ManagementIt is difficult to separate N and water management when developing improved management systems for irrigated corn production. This is because adequate supplies of both N and water are critical for crop growth, but excesses of either or both can threaten ground water quality. Several N and water management systems were established at the Nebraska Management Systems Evaluation Area (MSEA) project to evaluate the impact of improved irrigation and N fertilizer management practices on production and/or... |
2. Remote Sensing Techniques to Identify N Deficiency in CornNitrogen management remains a primary concern for corn production. Environmental consciousness has increased the need for diagnostic techniques to identify N deficiencies to guide corrective measures or to provide feedback on management practices. This study was designed to evaluate several techniques that measure reflectance from corn plants to detect N stress. The experiment was located in Central Nebraska and involved four hybrids and five N rates. Leaf reflectance, canopy reflectance, and aerial... |
3. Remote Sensing as a Tool for AgricultureThe tendency for nearlv everything in our society to be bigger, better, faster, easier, cheaper, and safer than in the past has resulted in many challenges. Agriculture is not immune from these trends, and in some cases agriculture even leads the way. Incorporation of remote sensing into site- specific management activities is one area where technologies are being merged to develop a new array of products that are intended to help producers and consultants make better and more timely management decisions.... |
4. Assessing the Variability of Corn Response to NitrogenBecause results of experiments designed to test the response of corn to N rate tend to vary considerably with the environment. repetitions of such studies over time are essential. It is not clear, however, what number of repetitions are needed in order to deduce sound recommendations for application of N fertilizer to succeeding crops. We used the results from 16 years of a crop rotation x N rate study conducted at Monmouth, Illinois to assess the effect of duration of such an experiment on the stability... |
5. Corn Nitrogen Response Across Environments and Crop RotationRecent research on corn has tended to show variability in N response. Brown et al. (1993) reported that economically optimal N rates among 77 sites in Illinois ranged from zero to more than 200 lb N per acre. Results from other studies show similar variability in time and space. Even with such variability, results over environments have been combined and used to develop an N fertilizer rate guideline in Illinois based on anticipated corn yield (Hoeft and Peck, 2002). This guideline suggests providing... |
6. Managing Continuous Corn for High YieldsMany "contest-winning" corn yields have historically been produced in fields where corn is grown continuously, often with extensive tillage, hgh soil test values of P and K, high N rates, and high plant populations. We are conducting a series of research trials at four sites in Illinois, in whlch we are varying tillage, fertilizer rates, and plant population in a factorial experiment at several Illinois locations. Over ten site-years to date, tillage deeper than normal increased yield at two site-years.... |
7. In-Season Nitrogen Recommendations for CornMaking fertilizer N recommendations involves a great deal of guess work and uncertainty because much, essentially all, of the fertilizer N is applied before the crop is planted and the amount is based on estimated crop use from historical data. In addition, producers, consultants, and fertilizer dealers try to anticipate how much N might be lost because of untimely or excess precipitation or how much additional N might be required if the weather conditions are favorable. Sidedress and in-season... |
8. Integrating Management Zones and Canopy Sensing for Improved Nitrogen Recommendation AlgorithmsActive crop canopy sensors have been studied as a tool to direct spatially variable nitrogen (N) fertilizer applications in maize, with the goal of increasing the synchrony between N supply and crop demand and thus improving N use efficiency (NUE). However, N recommendation algorithms have often proven inaccurate in certain subfield regions due to local spatial variability. Modifying these algorithms by integrating soil-based management zones (MZ) may improve their accuracy... J. Crowther, J. Parrish, R. Ferguson, J. Luck, K. Glewen, T. Shaver, D. Krull, L. Thompson, N. Mueller, B. Krienke, T. Mieno, T. Ingram |
9. Comparison of Ground-Based Active Crop Canopy Sensor and Aerial Passive Crop Canopy Sensor for In-Season Nitrogen ManagementCrop canopy sensors represent one tool available to help calculate a reactive in-season nitrogen (N) application rate in corn. When utilizing such systems, corn growers must decide between using active versus passive crop canopy sensors. The objectives of this study was to 1) determine the correlation between N management by remote sensing using a passive sensor and N management using proximal sensing with an active sensors. Treatments were arranged as field length strips in a randomized complete... J. Parrish, R. Ferguson, J. Luck, K. Glewen, L. Thompson, B. Krienke, N. Mueller, T. Ingram, D. Krull, J. Crowther, T. Shaver, T. Mieno |