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1. 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... |
2. 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... |
3. 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.... |
4. Considerations for Development of Optical Sensor Based Nitrogen Recommendation Algorithms for CornOptical sensor technology in Kansas has been used on winter wheat and grain sorghum with great success for predicting N fertilizer needs early in the growing season. However with both crops, there is a required minimum period of growth required before optical sensors can accurately detect N deficiencies. In both cases the target crop needs to have entered a period of vegetative growth where N uptake and utilization is increasing. In the case of wheat that generally corresponds to the Feekes 4 to... |
5. Evaluation of Weed Management Strategies on Grain Sorghum Nitrogen Status and Grain Yield Using Optical SensorsInformation on weed management options and relation to nutrient status is very limited for grain sorghum production. The objectives of this study were: (i) determine the effects of different weed management strategies on grain sorghum yield; and (ii) evaluate the impact on nitrogen (N) status and development of the crop. This study was established at two locations in 2014 (Smith and Reno Co in Kansas). The study used a randomized complete block design with 4 replications. Two main factors evaluated... |
6. Use and Misuse of Aerial ImageryThroughout the 1990’s agricultural researchers were hitting the sky’s collecting untold amounts of spectral data. The majority of that push quieted down in the early 2000’s as scalability was a constant struggle. However, in the past few years the introduction of affordable and easy to use unmanned aerial vehicles (UAV), more cost effective cameras, and significant increase in satellite constellations has reignited the interest in remote sensing that died out a decade... B. Arnall |
7. Implications of Clay Mineral Analysis for Improved Calibration of Corn Potassium Fertilizer RecommendationsEastern South Dakota has seen an increase in soil potassium (K) deficiencies. To correct those deficiencies and avoid yield reductions, corn producers rely on accurate K fertilizer recommendations (KFRs). Among the various parameters used to estimate a KFR, clay mineralogy has significant potential to increase KFR accuracy. The study has two objectives: first, to determine the relationships among clay mineralogy, K uptake by corn, and KFRs, and second, to calibrate KFRs in South Dakota to incorporate... A. Ahlersmeyer, J. Clark, D. Clay, K. Osterloh |
8. What Soil Measurements Relate Best to Corn Economic Optimal N Rate?The use of nitrogen (N) fertilizer is critical for optimizing corn (Zea mays L.) yield. However, improper applications can reduce fertilizer efficiency, create environmental issues, and reduce grower profits. The N cycle is largely affected by biological processes. Therefore, the inclusion of biological soil tests alone or in combination with other soil chemical and physical properties may enable us to improve the accuracy of corn N fertilizer needs to optimize yield. From 2018-2021,... J. Clark, P. Kovacs, A. Bly, A. Ahlersmeyer |
9. Consideration of Clay Mineralogy for Enhanced Prediction of Optimal Corn Potassium Fertilizer RatesProperly calibrated potassium (K) fertilizer recommendations (KFRs) are critical for improving crop yields and maintaining environmental stewardship. Recent innovations in soil and crop management suggest that certain soil factors, including clay mineralogy, can be used to predict optimal K requirements in corn. The objectives of this study include 1) correlate soil K levels to corn yield, 2) calibrate KFRs with clay mineralogy data, and 3) determine the relationships among clay mineralogy, K... A. Ahlersmeyer, J. Clark, K. Osterloh, D. Clay |
10. Does Sensor-based Nitrogen Management Maintain Crop Production and Decrease Nitrate-N Leaching?To improve water quality, nitrogen (N) management in corn production systems should shift from current N decision support system [maximum return to N (MRTN)] which suggests a single rate N addition to sensor-based (GreenSeeker) active N management (variable N rate approach). Single rate N recommendations often result in under- and over-N addition and either increase environmental N losses or cause corn yield penalty. Our objectives were to evaluate corn optimum nitrogen N requirement (EORN) in... A. Sadeghpour, M. Guzel, J. Mcgrath, O. Adeyemi, B. Arnall, O. Guzel |