Crop yield literature review for AgRISTARS crops: Corn, soybeans, wheat, barley, sorghum, rice, cotton, and sunflowers

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Phase transfer catalysis: chemistry and engineering

Phase transfer catalysis (PTC) uses catalytic amounts of phase transfer agents which facilitate interphase transfer of species, making reactions between reagents in two immiscible phases possible. PTC is used widely in the synthesis of various organic chemicals in both liquid-liquid and solid-liquid systems. Existing literature on PTC is chemistry-intensive and a mere handful of recent articles constitute the entire information on engineering analysis. This article reviews the field comprehensively by combining the existing knowledge from chemistry with insights into mechanistic and kinetic analysis and mathematical modeling of soluble and insoluble PTC. By its very nature, PTC involves a series of equilibrium and mass-transfer steps, beside the two main reactions. Neglect of mass-transfer effects can grossly overpredict the conversion of a PTC mediated reaction. A practical way of using PTC, which enables easy separation, is to immobilize the catalyst on a solid support. Mass-transfer limitations and higher costs, however, have precluded its commercial use so far, requiring further analysis of mass-transfer limitations in these complex three-phase systems. The use of PTC, combined with other rate enhancement techniques like sonochemistry, microwaves, electroorganic synthesis, and photochemistry, is being increasingly explored. Applications in this area in the manufacture of organic intermediates and fine chemicals seem almost unlimited

Effect of interaction and mobility on fixed-bed reactor performance

The roles of interaction and mobility in determining surface rates and hence reactor performance, as reflected in the space time values required for achieving a desired conversion or selectivity, are demonstrated. It is shown that localized adsorption models predict larger space times in comparison to the mobile models. Further, repulsive forces lead to higher space times in comparison to attractive forces, and the divergence between models is most marked for localized adsorption

Use of NOAA-N satellites for land/water discrimination and flood monitoring

A tool for monitoring the extent of major floods was developed using data collected by the NOAA-6 advanced very high resolution radiometer (AVHRR). A basic understanding of the spectral returns in AVHRR channels 1 and 2 for water, soil, and vegetation was reached using a large number of NOAA-6 scenes from different seasons and geographic locations. A look-up table classifier was developed based on analysis of the reflective channel relationships for each surface feature. The classifier automatically separated land from water and produced classification maps which were registered for a number of acquisitions, including coverage of a major flood on the Parana River of Argentina

Influence of catalyst deactivation on the nature of the steady state solutions for reactions on catalytic surfaces

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Effectiveness factors in bidispersed catalysts under conditions of catalyst fouling

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Preliminary evaluation of spectral, normal and meteorological crop stage estimation approaches

Several of the projects in the AgRISTARS program require crop phenology information, including classification, acreage and yield estimation, and detection of episodal events. This study evaluates several crop calendar estimation techniques for their potential use in the program. The techniques, although generic in approach, were developed and tested on spring wheat data collected in 1978. There are three basic approaches to crop stage estimation: historical averages for an area (normal crop calendars), agrometeorological modeling of known crop-weather relationships agrometeorological (agromet) crop calendars, and interpretation of spectral signatures (spectral crop calendars). In all, 10 combinations of planting and biostage estimation models were evaluated. Dates of stage occurrence are estimated with biases between -4 and +4 days while root mean square errors range from 10 to 15 days. Results are inconclusive as to the superiority of any of the models and further evaluation of the models with the 1979 data set is recommended