Proceedings
Authors
| Filter results10 paper(s) found. |
|---|
1. North Dakota Corn Recommendations for Preplant and Sensor Directed Sidedress NNitrogen rates for preplant N application in North Dakota have been drastically revised. The former yield-based strategy may have served when N costs were stable and relatively low and high yields in North Dakota were rarely higher than 100 bushels per acre. Due to improved germplasm developed at North Dakota State University and other northern Land-Grant Universities with favorable adaptation to North Dakota climate and soil conditions corn has become one of the most planted crops in the state.... |
2. Soil and Site Factors Responsible for Yield Variations in Two Southern Illinois Farm FieldsYield variability within a field is largely influenced by the soil physical. chemical. and topographic features of that field. On-farm field research studies were conducted from 1997 through 1999 on two southern Illinois farm fields (one in Jefferson County and the other in Pope County) with varying soil physical, chemical, and topographic features to determine which factors most influenced crop yield variability. Each location was GPS-gridded utilizing a grid cell size of 0.45 acres. Detailed topographic... |
3. Corn and Soybean Response to Potassium Fertilization and PlacementI\ncreased adoption of conservation tillage, evidence of large within-field nutrient variability, and an apparent increase in the Frequency of crop potassium (K) deficiency symptoms in Iowa and other states have prompted questions about the effectiveness of current soil-test K interpretations and fertilizer recommendations. These questions relate to fertilizer placement and management of within-field nutrient variability. Broadcast placements are less costly than banded placements but they seem inefficient... |
4. Site-Specific Management of Iron Deficiency in CornThe addition of FeS04mH20 in the seed row increases corn (Zea mays L.) yield in areas with Fe deficiency-induced chlorosis. Our objectives were to determine the correct application rate of FeS04.H20 for irrigated corn, identi9 the spatial distribution of Fe deficiency, and alleviate deficiency symptoms with targeted FeS04.H20 applications. Eleven site-years were selected for small-plot studies in western Kansas. At these fields, soil CaC03 content in chlorotic or problematic deficient areas of the... |
5. Varying Nitrogen and Seeding Rates of Corn Across Productivity Regions in FieldsA field study was conducted fiom 1999 to 2001 to determine the effects of variable seeding rates and variable nitrogen rates on corn (Zeu muys L.) in southern Ihois. In whole field experiments, variable seeding rates ranging fiom 18,000 to 38,000 seeds ac-' in 4.000 seed increments were planted in randomized strips (in a randomized complete block design) across the field that had soils with varying productivity based upon historical yield maps. From the yield data it was determined that the optimum... |
6. Using Historical Yield Patterns in Fields as a Management Tool to Variably Apply NitrgenIn whole field studies in southem Illinois a uniform rate of N application was compared with variably applied rates of N based upon historical crop yields for each field. The fields used were partitioned in "low". "medium", and "high" zones of productivity depending upon the normalized yield of the preceding 5 to 10 years of crops grown. Two formulas were used to variably apply nitrogen. One formula (VRN-One) calculated a N rate that favored more fertilizer in "high" productivity regions and less... |
7. Use Of Corn Height To Improve The Relationship Between Active Optical Sensor Readings And Yield EstimatesPre-season and early in-season loss of N continues to be a problem in corn (Zea mays, L.). One method to improve nitrogen use efficiency is to fertilize based on in-season crop foliage sensors. The objective of this study was to evaluate two different ground-based, active-optical sensors and explore the use of corn height with sensor readings for improved relationship with corn yield. Two different ground-based active-optical sensors (Greenseeker�, Trimble, Sunnydale, CA; and Holland Crop Circle... |
8. Crop Yield Relationship to Remote Sensing Data Using Intensified Weighted Nonlinear Regression ModelsYield prediction is important for making in-season agronomic input decisions as well as for greater logistical decisions. In predicting the crop yield based on ground-based active optical sensing data, the ordinary statistical unweighted linear or nonlinear regression models are the most popular choices. However, these unweighted models may not be accurate enough for practical use because they are based on the assumption that each data point for regression is obtained with equal precision and that... |
9. Nitrogen Rate Revisions for Corn in North DakotaNitrogen rates in North Dakota have been based on a yield-goal or yield-potential formula for over forty years. The currently published formula (Franzen, 2010) is: Recommended N rate = (Yield Potential, bushels per acre) X 1.2 less N credits from previous crops and soil test nitrate to 2 feet in depth. A yield-based strategy was practical when N costs were relatively low and yields in North Dakota were at most 100 bushels per acre. However, due to improved germplasm developed at North Dakota State... |
10. Correlation Between Mehlich-3 and Haney Extractable Phosphorus and Potassium, and Their Relationship to Soybean (Glycine Max) Yield ResponseNumerous soil tests have been developed for estimating the plant-availability of soil phosphorus (P) and potassium (K). Understanding the relationship between these test’s results and crop response to fertilizer application is essential for developing and improving fertilizer recommendations. Field trials have been initiated at six sites located across the state of Kansas to investigate the response of soybean to broadcast P and K fertilizer application. Plots are... E. Rutter, D. Ruiz Diaz, F. Hansel |