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| Filter results7 paper(s) found. |
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1. Intensive Wheat Managent in the Corn BeltIntensive wheat management (ICX) is based on European cropping systems including narrow row spacing, precise seeding rates, multiple nitrogen (N) fertilizer application, fungicide application for disease control, and plant growth regulator (PGR) application for lodging control. Components of this cropping system were compared to current recommended management (CRM) practices with 12 varieties during 1986-87. The purpose for the experiment was to determine the responsiveness of soft winter wheat varieties... |
2. Perspective on Sustainable Agriculture- Sustaining Agribusiness in a Changing Rural EnvironmentAgriculture is an evolving industry -- it responds to market forces, tc improvements in technology, to government programs. LlJe also see changes as 3 result of new technologies, improved information about how to efficiently raise crops and livestock, and more integration with other sectors of society. In agriculture, as in arty business, to stand still is to fall behind the rest of the industry. !!le nnoed to be ready to adapt to change, to face ned rl-zli- ties, and even to initiate cnange in positive... |
3. Nitrogen and Phosphorus Fertilization of Cool Season GrassStudies were initiated at two locations on cool season grass in central South Dakota to evaluate the effects of nitrogen and phosphorus on forage and seed yields. Nitrogen rates (0,30,60,90,120,1501b Nacre) and phosphorus rates (0,30,60,90,180 Ib P,Odacre) were applied to established crested or intermediate wheatgrass once and harvested for either two or three years depending on location. Nitrogen increased dry matter yield by 48 and 62% at the two locations and seed yield by 166 percent. Phosphorus... |
4. Spatial Response of Corn to Banded Zinc Sulfate Fertilizer in IowaThe solubility of zinc (Zn) decreases as pH increases. There are soil associations that contain high pH spots within fields where the surrounding soils' pHs are slightly acid. It is reasonable to expect that Zn availability, due to a difference in solubility, is different in the two areas. The objectives of this study were to find corn (Zea nlnys L.) grain yield responses to Zn fertilizers within fields and to define the soil characteristics in responsive areas. The study was conducted at twelve... |
5. Can Soil Information Better Inform Canopy Sensor Algorithms for Corn?Corn production is often limited by the loss of nitrogen (N) due to leaching, volatilization and denitrification. The use of canopy sensors for making in-season N fertilizer applications has been proven effective in matching plant N requirements with periods of rapid N uptake (V7-V11), reducing the amount of N lost to these processes. However, N recommendation algorithms used in conjunction with canopy sensor measurements have not proven accurate in many fields of the U.S. Cornbelt, resulting in... , N.R. Kitchen, J. Camberato, P.R. Carter, R.B. Ferguson, F.G. Fernandez, D.W. Franzen, F.G. Fernandez, E.D. Nafziger, C.J. Ransom, , J. Shanahan, G.M. Bean |
6. Fertilizer Placement and Tillage Interaction in Corn and Soybean ProductionDifferent tillage systems can affect the availability of phosphorus (P) in the soil. The objective of this study was to evaluate the effects and interaction of fertilizer placement, tillage, and varieties/hybrids for corn and soybean. The experiment was established at two locations in Kansas in 2014. The experimental design was a factorial in a randomized complete block with four replications. Three fertilizer treatments were combined with two tillage systems and two varieties/hybrids of soybean... |
7. 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 |