NEXAFS Sensitivity to Bond Lengths in Complex Molecular Materials: A Study of Crystalline Saccharides

Detailed analysis of the C K near-edge X-ray absorption fine structure (NEXAFS) spectra of a series of saccharides (fructose, xylose, glucose, galactose, maltose monohydrate, α-lactose monohydrate, anhydrous β-lactose, cellulose) indicates that the precise determination of IPs and σ* shape resonance energies is sensitive enough to distinguish different crystalline saccharides through the variations in their average C–OH bond lengths. Experimental data as well as FEFF8 calculations confirm that bond length variations in the organic solid state of 10–2 Å can be experimentally detected, opening up the possibility to use NEXAFS for obtaining incisive structural information for molecular materials, including noncrystalline systems without long-range order such as dissolved species in solutions, colloids, melts, and similar amorphous phases. The observed bond length sensitivity is as good as that originally reported for gas-phase and adsorbed molecular species. NEXAFS-derived molecular structure data for the condensed phase may therefore be used to guide molecular modeling as well as to validate computationally derived structure models for such systems. Some results indicate further analytical value in that the σ* shape resonance analysis may distinguish hemiketals from hemiacetals (i.e., derived from ketoses and aldoses) as well as α from β forms of otherwise identical saccharides

Automatic control of farming operations based on spatial web services

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ASSESSMENT OF VARIOUS REMOTE SENSING TECHNOLOGIES IN BIOMASS AND NITROGEN CONTENT ESTIMATION USING AN AGRICULTURAL TEST FIELD

Multispectral and hyperspectral imaging is usually acquired by satellite and aircraft platforms. Recently, miniaturized hyperspectral 2D frame cameras have showed great potential to precise agriculture estimations and they are feasible to combine with lightweight platforms, such as drones. Drone platform is a flexible tool for remote sensing applications with environment and agriculture. The assessment and comparison of different platforms such as satellite, aircraft and drones with different sensors, such as hyperspectral and RGB cameras is an important task in order to understand the potential of the data provided by these equipment and to select the most appropriate according to the user applications and requirements. In this context, open and permanent test fields are very significant and helpful experimental environment, since they provide a comparative data for different platforms, sensors and users, allowing multi-temporal analyses as well. Objective of this work was to investigate the feasibility of an open permanent test field in context of precision agriculture. Satellite (Sentinel-2), aircraft and drones with hyperspectral and RGB cameras were assessed in this study to estimate biomass, using linear regression models and in-situ samples. Spectral data and 3D information were used and compared in different combinations to investigate the quality of the models. The biomass estimation accuracies using linear regression models were better than 90 % for the drone based datasets. The results showed that the use of spectral and 3D features together improved the estimation model. However, estimation of nitrogen content was less accurate with the evaluated remote sensing sensors. The open and permanent test field showed to be suitable to provide an accurate and reliable reference data for the commercial users and farmers

AGRIX-järjestelmä - älyä, automaatiota ja tehokkuutta kasvintuotantoon

Sisältö: CD-ROM sisältää artikkelit Maataloustieteen Päivien 2006 esitelmistä ja postereista kokonaisuudessaan.vo