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The lack of soil data, which are relevant, reliable, affordable, immediately available, and sufficiently detailed, is still a significant challenge in precision agriculture. A promising technology for the spatial assessment of the distribution of chemical elements within fields, without sample preparation is laser-induced breakdown spectroscopy (LIBS). Its advantages are contrasted by a strong matrix dependence of the LIBS signal which necessitates careful data evaluation. In this work, different calibration approaches for soil LIBS data are presented. The data were obtained from 139 soil samples collected on two neighboring agricultural fields in a quaternary landscape of northeast Germany with very variable soils. Reference analysis was carried out by inductively coupled plasma optical emission spectroscopy after wet digestion. The major nutrients Ca and Mg and the minor nutrient Fe were investigated. Three calibration strategies were compared. The first method was based on univariate calibration by standard addition using just one soil sample and applying the derived calibration model to the LIBS data of both fields. The second univariate model derived the calibration from the reference analytics of all samples from one field. The prediction is validated by LIBS data of the second field. The third method is a multivariate calibration approach based on partial least squares regression (PLSR). The LIBS spectra of the first field are used for training. Validation was carried out by 20-fold cross-validation using the LIBS data of the first field and independently on the second field data. The second univariate method yielded better calibration and prediction results compared to the first method, since matrix effects were better accounted for. PLSR did not strongly improve the prediction in comparison to the second univariate method.
A technique has been developed to measure absolute intracellular oxygen concentrations in green plants. Oxygen-sensitive phosphorescent microbeads were injected into the cells and an optical multifrequency phase-modulation technique was used to discriminate the sensor signal from the strong autofluorescence of the plant tissue. The method was established using photosynthesis-competent cells of the giant algae Chara corallina L., and was validated by application to various cell types of other plant species.
The salivary glands of the blowfly were injected with luminescent oxygen-sensitive microbeads. The changes in oxygen content within individual gland tubules during hormone-induced secretory activity were quantified. The measurements are based on an upgraded phase-modulation technique, where the phase shift of the sensor phosphorescence is determined independently from concentration and background signals. We show that the combination of a lock-in amplifier with a fluorescence microscope results in a convenient setup to measure oxygen concentrations within living animal tissues at the cellular level.