Electromagnetic Induction Technology and Precision Agriculture in Iowa

Precision agriculture (PA) is concerned with understanding variability and managing it. Precision agriculture is made possible by the merging of several old and newer technologies, which are listed below

Understanding Iowa Soils for Precision Agriculture Use

The objectives of this presentation are to explain soil surveys and to better understand soils, their properties, and their spatial variability so that this information can contribute to improved decision-making related to precision soil, crop, and water management

Remote sensing in Iowa agriculture

The author has identified the following significant results. Analysis of 1972 single-date coverage indicated that a complete crop classification was not attainable at the test sites. Good multi-date coverage during 1973 indicates that many of the problems encountered in 1972 will be minimized. In addition, the compilation of springtime imagery covering the entire state of Iowa has added a new dimension to interpretation of Iowa's natural resources. ERTS-1 has provided data necessary to achieve the broad synoptic view not attainable through other means. This should provide soils and crop researchers and land use planners a base map of Iowa. Granted and due to the resolution of ERTS-1, not all details are observable for many land use planning needs, but this gives a general and current view of Iowa

Remote sensing in Iowa agriculture: Identification and classification of Iowa's crops, soils and forestry resources using ERTS-1 and complimentary underflight imagery

The author has identified the following significant results. Springtime ERTS-1 imagery covering pre-selected test sites in Iowa showed considerable detail with respect to broad soil and land use patterns. Additional imagery has been incorporated into a state mosaic. The mosaic was used as a base for soil association lines transferred from an existing map. The regions of greatest contrast are between the Clarion-Nicollet-Webster soil association area and adjacent areas. Landscape characteristics in this area result in land use patterns with a high percentage of pasture, hay, and timber. The soil association areas of the state that have patterns interpreted to be associated with intensive row crop production are: Moody, Galva-Primghar-Sac, Clarion-Nicollet-Webter, Tama-Muscatine, Dinsdale-Tama, Cresco-Lourdes, Clyde, Kenyon-Floyd-Clyde, and the Luton-Onawa-Salix area on the Missouri River floodplain. Forestland estimates have been attained for an area in central Iowa using wintertime ERTS-1 imagery. Visual analysis of multispectral, temporal imagery indicates that temporal analysis for cropland identification and acreage analyses procedures may be a very useful tool. Combinations of wintertime, springtime, and summertime ERTS-1 imagery separate most vegetation types. Timing can be critical depending upon crop development and harvesting times because of the dynamic nature of agricultural production

Remote sensing in Iowa agriculture: Identification and classification of Iowa's crops, soils and forestry resources using ERTS-1 and complimentary underflight imagery

There are no author-identified significant results in this report

Missouri River history, floodplain construction, and soil formation in southwestern Iowa

The Platte River has influenced the Missouri River below the mouth of the Platte by contributing sizable suspended and coarser-textured bed loads. Consequently, the Missouri River has been and is a braided stream in a reach about 43 miles long below the mouth of the Platte. In this reach the channel is wider, is less sinuous, has greater low-water slope profile, and contains numerous bars and islands. The Otoe Bend area, in this reach of the Missouri River near the southwestern corner of Iowa, has inherited these channel characteristics. By use of historic maps and aerial photographs, the lateral shifting of the river channel at Otoe Bend may be reconstructed. Adjustments of scale and geographic locations must be made to compare features of all maps and aerial photographs to the present landforms in the area. The older maps usually are not as accurate as present-day cartography with photogrammetric field control. Within the different levels of cartographic accuracy, however, correlation of landforms can be made by similarity of features or similarity of sequences of features

Productivity levels of some Iowa soils

This report presents crop yield estimates for corn, soybeans, oats, and hay on 290 selected soil types and phases. These yield estimates are believed attainable as a 5-year average with the technology available in 1971 and average weather conditions.https://lib.dr.iastate.edu/specialreports/1063/thumbnail.jp

SAIDE: a Semi-Automated interface for Hydrogen/Deuterium Exchange Mass Spectrometry

Comunicaciones a congreso

Iowan Drift Problem, Northeastern Iowa

https://ir.uiowa.edu/igs_ri/1006/thumbnail.jp

Cardiac cell modelling: Observations from the heart of the cardiac physiome project

In this manuscript we review the state of cardiac cell modelling in the context of international initiatives such as the IUPS Physiome and Virtual Physiological Human Projects, which aim to integrate computational models across scales and physics. In particular we focus on the relationship between experimental data and model parameterisation across a range of model types and cellular physiological systems. Finally, in the context of parameter identification and model reuse within the Cardiac Physiome, we suggest some future priority areas for this field