@article{ErlerRiebeBeitzetal.2023, author = {Erler, Alexander and Riebe, Daniel and Beitz, Toralf and L{\"o}hmannsr{\"o}ben, Hans-Gerd and Leenen, Mathias and P{\"a}tzold, Stefan and Ostermann, Markus and W{\´o}jcik, Michał}, title = {Mobile laser-induced breakdown spectroscopy for future application in precision agriculture}, series = {Sensors}, volume = {23}, journal = {Sensors}, number = {16}, publisher = {MDPI}, address = {Basel}, issn = {1424-8220}, doi = {10.3390/s23167178}, pages = {17}, year = {2023}, abstract = {In precision agriculture, the estimation of soil parameters via sensors and the creation of nutrient maps are a prerequisite for farmers to take targeted measures such as spatially resolved fertilization. In this work, 68 soil samples uniformly distributed over a field near Bonn are investigated using laser-induced breakdown spectroscopy (LIBS). These investigations include the determination of the total contents of macro- and micronutrients as well as further soil parameters such as soil pH, soil organic matter (SOM) content, and soil texture. The applied LIBS instruments are a handheld and a platform spectrometer, which potentially allows for the single-point measurement and scanning of whole fields, respectively. Their results are compared with a high-resolution lab spectrometer. The prediction of soil parameters was based on multivariate methods. Different feature selection methods and regression methods like PLS, PCR, SVM, Lasso, and Gaussian processes were tested and compared. While good predictions were obtained for Ca, Mg, P, Mn, Cu, and silt content, excellent predictions were obtained for K, Fe, and clay content. The comparison of the three different spectrometers showed that although the lab spectrometer gives the best results, measurements with both field spectrometers also yield good results. This allows for a method transfer to the in-field measurements.}, language = {en} } @article{KimLeifheitMaassetal.2021, author = {Kim, Shin Woong and Leifheit, Eva F. and Maaß, Stefanie and Rillig, Matthias C.}, title = {Time-dependent toxicity of tire particles on soil nematodes}, series = {Frontiers in Environmental Science}, volume = {9}, journal = {Frontiers in Environmental Science}, publisher = {Frontiers Media}, address = {Lausanne}, issn = {2296-665X}, doi = {10.3389/fenvs.2021.744668}, pages = {9}, year = {2021}, abstract = {Tire-wear particles (TWPs) are being released into the environment by wearing down during car driving, and are considered an important microplastic pollution source. The chemical additive leaching from these polymer-based materials and its potential effects are likely temporally dynamic, since amounts of potentially toxic compounds can gradually increase with contact time of plastic particles with surrounding media. In the present study, we conducted soil toxicity tests using the soil nematode Caenorhabditis elegans with different soil pre-incubation (30 and 75 days) and exposure (short-term exposure, 2 days; lifetime exposure, 10 days) times. Soil pre-incubation increased toxicity of TWPs, and the effective concentrations after the pre-incubation were much lower than environmentally relevant concentrations. The lifetime of C. elegans was reduced faster in the TWP treatment groups, and the effective concentration for lifetime exposure tests were 100- to 1,000-fold lower than those of short-term exposure tests. Water-extractable metal concentrations (Cr, Cu, Ni, Pb, and Zn) in the TWP-soils showed no correlation with nominal TWP concentrations or pre-incubation times, and the incorporated metals in the TWPs may be not the main reason of toxicity in this study. Our results show that toxic effects of TWPs can be time-dependent, both in terms of the microplastic particles themselves and their interactions in the soil matrix, but also because of susceptibility of target organisms depending on developmental stage. It is vital that future works consider these aspects, since otherwise effects of microplastics and TWPs could be underestimated.}, language = {en} } @article{ErlerRiebeBeitzetal.2020, author = {Erler, Alexander and Riebe, Daniel and Beitz, Toralf and L{\"o}hmannsr{\"o}ben, Hans-Gerd and Gebbers, Robin}, title = {Soil Nutrient Detection for Precision Agriculture Using Handheld Laser-Induced Breakdown Spectroscopy (LIBS) and Multivariate Regression Methods (PLSR, Lasso and GPR)}, series = {Sensors}, volume = {20}, journal = {Sensors}, number = {2}, publisher = {MDPI}, address = {Basel}, issn = {1424-8220}, doi = {10.3390/s20020418}, pages = {17}, year = {2020}, abstract = {Precision agriculture (PA) strongly relies on spatially differentiated sensor information. Handheld instruments based on laser-induced breakdown spectroscopy (LIBS) are a promising sensor technique for the in-field determination of various soil parameters. In this work, the potential of handheld LIBS for the determination of the total mass fractions of the major nutrients Ca, K, Mg, N, P and the trace nutrients Mn, Fe was evaluated. Additionally, other soil parameters, such as humus content, soil pH value and plant available P content, were determined. Since the quantification of nutrients by LIBS depends strongly on the soil matrix, various multivariate regression methods were used for calibration and prediction. These include partial least squares regression (PLSR), least absolute shrinkage and selection operator regression (Lasso), and Gaussian process regression (GPR). The best prediction results were obtained for Ca, K, Mg and Fe. The coefficients of determination obtained for other nutrients were smaller. This is due to much lower concentrations in the case of Mn, while the low number of lines and very weak intensities are the reason for the deviation of N and P. Soil parameters that are not directly related to one element, such as pH, could also be predicted. Lasso and GPR yielded slightly better results than PLSR. Additionally, several methods of data pretreatment were investigated.}, language = {en} } @article{NeillCoeRiskinetal.2013, author = {Neill, Christopher and Coe, Michael T. and Riskin, Shelby H. and Krusche, Alex V. and Elsenbeer, Helmut and Macedo, Marcia N. and McHorney, Richard and Lefebvre, Paul and Davidson, Eric A. and Scheffler, Raphael and Figueira, Adelaine Michela e Silva and Porder, Stephen and Deegan, Linda A.}, title = {Watershed responses to Amazon soya bean cropland expansion and intensification}, series = {Philosophical transactions of the Royal Society of London : B, Biological sciences}, volume = {368}, journal = {Philosophical transactions of the Royal Society of London : B, Biological sciences}, number = {1619}, publisher = {Royal Society}, address = {London}, issn = {0962-8436}, doi = {10.1098/rstb.2012.0425}, pages = {7}, year = {2013}, abstract = {The expansion and intensification of soya bean agriculture in southeastern Amazonia can alter watershed hydrology and biogeochemistry by changing the land cover, water balance and nutrient inputs. Several new insights on the responses of watershed hydrology and biogeochemistry to deforestation in Mato Grosso have emerged from recent intensive field campaigns in this region. Because of reduced evapotranspiration, total water export increases threefold to fourfold in soya bean watersheds compared with forest. However, the deep and highly permeable soils on the broad plateaus on which much of the soya bean cultivation has expanded buffer small soya bean watersheds against increased stormflows. Concentrations of nitrate and phosphate do not differ between forest or soya bean watersheds because fixation of phosphorus fertilizer by iron and aluminium oxides and anion exchange of nitrate in deep soils restrict nutrient movement. Despite resistance to biogeochemical change, streams in soya bean watersheds have higher temperatures caused by impoundments and reduction of bordering riparian forest. In larger rivers, increased water flow, current velocities and sediment flux following deforestation can reshape stream morphology, suggesting that cumulative impacts of deforestation in small watersheds will occur at larger scales.}, language = {en} }