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At least 307 records · Page 17

Invertebrate and Plant Community Diversity of an Illinois Corn–Soybean Field with Integrated Shrub Willow Bioenergy Buffers

Perennial bioenergy crop production within intensively managed agricultural landscapes has the potential to improve the sustainability, resiliency, and diversity of these landscapes. Perennial crops are ideal because of their high production potential on marginal lands relative to grain crops (e.g., corn and soybean) and their ability to provide additional ecosystem service benefits. When agricultural landscapes are designed to target specific services, determining the non-targeted services of perennial bioenergy crops can further promote their adoption. This 3-year study addresses this proposition by evaluating the canopy invertebrates and understory plant (non-target crop) communities using bee bowls and point measurement of ground coverage, respectively, within a grain field integrated with shrub willow buffer systems designed for nutrient loss reduction. Greater plant diversity and richness were observed under willow than under grain, resembling that of the surrounding riparian community with more perennial, native species. However, the same relationship did not hold true for invertebrates, with seasonality having a significant influence resulting in similar communities observed in willow and grain plots. The presence of unique plant and invertebrate species in both willow and grain crops as well as foraging pollinators on both crop and non-target crop species highlights the importance of habitat heterogeneity for supporting biodiversity and the potential benefits of buffer bioenergy landscape designs.

09 BIOMASS FUELS↗

BESS-STAIR: a framework to estimate daily, 30m, and all-weather crop evapotranspiration using multi-source satellite data for the US Corn Belt

Abstract. With increasing crop water demands and drought threats, mapping andmonitoring of cropland evapotranspiration (ET) at high spatial and temporalresolutions become increasingly critical for water management andsustainability. However, estimating ET from satellites for precise waterresource management is still challenging due to the limitations in bothexisting ET models and satellite input data. Specifically, the process of ETis complex and difficult to model, and existing satellite remote-sensing datacould not fulfill high resolutions in both space and time. To address theabove two issues, this study presents a new high spatiotemporal resolution ETmapping framework, i.e., BESS-STAIR, which integrates a satellite-drivenwater–carbon–energy coupled biophysical model, BESS (Breathing Earth SystemSimulator), with a generic and fully automated fusion algorithm, STAIR(SaTallite dAta IntegRation). In this framework, STAIR provides daily 30'mmultispectral surface reflectance by fusing Landsat and MODIS satellite datato derive a fine-resolution leaf area index and visible/near-infrared albedo,all of which, along with coarse-resolution meteorological and CO 2 data, are used to drive BESS to estimate gap-free 30 m resolution daily ET.We applied BESS-STAIR from 2000 through 2017 in six areas across the US CornBelt and validated BESS-STAIR ET estimations using flux-tower measurementsover 12 sites (85 site years). Results showed that BESS-STAIR daily ETachieved an overall R2=0.75, with root mean square error RMSE=0.93 mm d -1 and relative error RE =27.9 % when benchmarkedwith the flux measurements. In addition, BESS-STAIR ET estimations capturedthe spatial patterns, seasonal cycles, and interannual dynamics well indifferent sub-regions. The high performance of the BESS-STAIR frameworkprimarily resulted from (1) the implementation of coupled constraints onwater, carbon, and energy in BESS, (2) high-quality daily 30 m data from theSTAIR fusion algorithm, and (3) BESS's applicability under all-skyconditions. BESS-STAIR is calibration-free and has great potentials to be areliable tool for water resource management and precision agricultureapplications for the US Corn Belt and even worldwide given the globalcoverage of its input data.

54 ENVIRONMENTAL SCIENCES↗

The applications of remote sensing to corn blight detection and crop yield forecasting

Photography revealed the widespread and variable effects of southern corn leaf blight in Indiana. Three levels of severity of the infection could be discerned from good quality color and color infrared photography. As many as five severity levels appeared to be detectable and classifiable with multispectral scanner data and pattern recognition analysis. These conclusions are preliminary in nature, however, having been obtained from a limited amount of good quality scanner data collected over a small geographic area.

Macdonald, R. B.↗

Prediction of directional reflectance of a corn field under stress

A vegetative canopy model concept is developed and used to calculate the directional spectral reflectance of a corn field under stress. The problem has been idealized by assuming that the canopy is represented in several layers of uniform but randomly distributed biological components; horizontal and vertical projection of leaves, for example, replaces the actual leaf. An accumulative horizontal projection leads to a quantitative horizontal leaf area index while accumulated vertical projections provide the vertical leaf index area for each layer. The spectral properties of the projections are obtained from the spectral properties of the biological components. These techniques together with soil reflectance data provide a physical description for the vegetative canopy and adequately interprete multispectral scanning data.

Suits, G. H.↗

The 1971 corn blight watch experiment data processing, analysis, and interpretation

The principle data acquisition centers are listed for the corn blight experiment. A data storage and retrieval system was established. The purpose of the system was to: (1) store data in organized library; (2) maintain a record of all data stored and reduced for future access; (3) report the data in simplest form to users; and (4) record data reduction results from photographic and multispectral scanner sensors. The procedures designed for handling the large amounts of data are also reviewed.

Phillips, T. L.↗

Detection of southern corn leaf blight by remote sensing techniques.

Multispectral photographic and scanner data were collected over western Indiana in August and September 1970, to determine the detectability of southern corn leaf blight by remote sensing. Measurements were made at altitudes of 3000 to 7000 ft. Color, color IR, and multiband black and white photography were collected at altitudes from 3000 to 60,000 ft. Six levels of infection based on the amount of leaf damage were identified in the fields. Three levels of infection were detected with color IR photography by standard photo-interpretive techniques. Up to five levels of infection were distinguished by applying automatic pattern recognition techniques to the multispectral scanner data. The results illustrate the potential of remote sensing techniques in the detection of crop diseases.

Bauer, M. E.↗

Data handling and analysis for the 1971 corn blight watch experiment

The overall corn blight watch experiment data flow is described and the organization of the LARS/Purdue data center is discussed. Data analysis techniques are discussed in general and the use of statistical multispectral pattern recognition methods for automatic computer analysis of aircraft scanner data is described. Some of the results obtained are discussed and the implications of the experiment on future data communication requirements for earth resource survey systems is discussed.

Anuta, P. E.↗

Aerial Photography: Use in Detecting Simulated Insect Defoliation in Corn

Artificial defoliation in corn was used to explore the usefulness of aerial photography in detecting crop insect infestations. Defoliation on the top of plants was easily detected, while that on the base was less so. Aero infrared film with Wratten 89B filter gave the best results, and morning flights at the scale of 1:15840 are recommended. Row direction, plant growth stage, and time elapse since defoliation were not important factors.

Chiang, H. C.↗

Data handling and analysis for the 1971 corn blight watch experiment.

Review of the data handling and analysis methods used in the near-operational test of remote sensing systems provided by the 1971 corn blight watch experiment. The general data analysis techniques and, particularly, the statistical multispectral pattern recognition methods for automatic computer analysis of aircraft scanner data are described. Some of the results obtained are examined, and the implications of the experiment for future data communication requirements of earth resource survey systems are discussed.

Anuta, P. E.↗

Economic Benefits of Improved Information on Worldwide Crop Production: An Optimal Decision Model of Production and Distribution with Application to Wheat, Corn, and Soybeans

An optimal decision model of crop production, trade, and storage was developed for use in estimating the economic consequences of improved forecasts and estimates of worldwide crop production. The model extends earlier distribution benefits models to include production effects as well. Application to improved information systems meeting the goals set in the large area crop inventory experiment (LACIE) indicates annual benefits to the United States of $200 to $250 million for wheat, $50 to $100 million for corn, and $6 to $11 million for soybeans, using conservative assumptions on expected LANDSAT system performance.

Andrews, J.↗

Temporal spectral measurements of corn and soybean crops

A ground-based, hand-held radiometer, configured to measure red and photographic infrared spectral radiances, was successfully used to collect in situ temporal spectral measurements of corn and soybean crops. Significant relationships were found between the radiance data and the biomass, plant height, percentage crop cover, percentage crop chlorosis, and percentage leaf loss. The results of this experiment show conclusively that hand-held radiometers can be used to collect spectral data that are highly correlated to several agronomic variables. These findings suggest approaches for agronomic research, and confirm the value of remote sensing of agricultural targets.

Tucker, C. J.↗

Advances in the Dow Corning process for solar-grade silicon

The Dow Corning process consists of the carbothermic reduction of silica to produce silicon that is then purified by unidirectional solidification. The process has produced silicon of semiconductor quality with respect to all elements except boron and phosphorus at about 10 ppma and aluminum at 0.1 ppma. Solar cells produced from this silicon gave AM0 conversion efficiencies of 11%. A process cost analysis is presented.

Hunt, L. P.↗

Progress on the Dow Corning process for solar-grade silicon

The Dow Corning approach to increasing the resistivity of solar-grade silicon from about 0.04 ohm-cm (40 ppma B) to greater than 0.1 ohm-cm (10 ppma B) involves the use of high-purity raw materials carbothermically reduced in a specially designed electric arc furnace. Final purification occurs during Czochralski crystal growth of a polycrystalline ingot. This small-scale purification technology has resulted in silicon that has been fabricated into solar cells with a maximum AM1 conversion efficiency of 13.4%.

Hunt, L. P.↗

A project to evaluate moisture stress and phenological factors in corn and soybean areas of southwestern and south-central Minnesota

The capability of aerial color infrared photography for identifying and locating soilscapes most susceptible to drought development or those having different soil drainages was evaluated. Although west central and southwestern Minnesota had a significant precipitation deficit during the 1980 crop season, indications of plant stress were not observed either from ground observation or through interpretation of imagery at the selected sampling sites. Well-drained soil was more depleted during the "maximium green peak" period than the poorly drained soil. The recharge was more evident on the poorly drained site in the fall. Measurements of leaf water potential and leaf temperature for corn and soybean leaves were made by multispectral band scanner and recorded for analysis.

Rust, R. H.↗

Recommended data sets, corn segments and spring wheat segments, for use in program development

The sets of Large Area Crop Inventory Experiment sites, crop year 1978, which are recommended for use in the development and evaluation of classification techniques based on LANDSAT spectral data are presented. For each site, the following exists: (1) accuracy assessment digitized ground truth; (2) a minimum of 5 percent of the scene ground truth identified as corn or spring wheat; and (3) at least four acquisitions of acceptable data quality during the growing season of the crop of interest. The recommended data sets consist of 41 corn/soybean sites and 17 spring wheat sites.

Austin, W. W.↗

Effects of nitrogen nutrition on the growth, yield and reflectance characteristics of corn canopies

Spectral and agronomic measurements were collected from corn (Zea mays L.) canopies under four nitrogen treatment levels (0, 67, 134, and 202 kg/ha) on 11 dates during 1978 and 12 dates during 1979. Data were analyzed to determine the relationship between the spectral responses of canopies and their argonomic characteristics as well as the spectral separability of the four treatments. Red reflectance was increased, while the near infrared reflectance was decreased for canopies under nitrogen deprivation. Spectral differences between treatments were seen throughout each growing season. The near infrared/red reflectance ratio increased spectral treatment differences over those shown by single band reflectance measures. Of the spectral variables examined, the near infrared/red reflectance ratio most effectively separated the treatments. Differences in spectral response between treatments were attributed to varying soil cover, leaf area index, and leaf pigmentation values, all of which changed with N treatment.

Bauer, M. E.↗