Electrooxidación del etanol y bioetanol sobre catalizadores de naturaleza amorfa de composición Ni59Nb40Pt1 y Ni59Nb39Pt2

La ecotoxicidad de las disoluciones provenientes de las pilas de combustible de etanol directo (DEFC) disminuyetras el proceso de electrooxidación con electrodos de naturalezaamorfa. Esta disminución es función del potencialaplicado y de la composición del electrodo utilizado.El proceso de electrooxidación del etanol y bioetanol, sucedetras una secuencia de reacciones, donde se formanvarios productos intermedios que pueden afectar al procesogeneral de electrooxidación de los alcoholes.El bioetanol, se está estudiando como combustible alternativoal etanol para las DEFC, pero se comporta de formadiferente, en cuanto a su electrooxidación. Se han obtenidoresultados diferentes al electrooxidar disoluciones deetanol y de bioetanol

Vibrational spectroscopy coupled to a multivariate analysis tiered approach for argentinean honey provenance confirmation

In the present work, the provenance discrimination of Argentinian honeys was used as case study to compare the capabilities of three spectroscopic techniques as fast screening platforms for honey authentication purposes. Multifloral honeys were collected among three main honey-producing regions of Argentina over four harvesting seasons. Each sample was fingerprinted by FT-MIR, NIR and FT-Raman spectroscopy. The spectroscopic platforms were compared on the basis of the classification performance achieved under a supervised chemometric approach. Furthermore, low- mid- and high-level data fusion were attempted in order to enhance the classification results. Finally, the best-performing solution underwent to SIMCA modelling with the purpose of reproducing a food authentication scenario. All the developed classification models underwent to a “year-by-year” validation strategy, enabling a sound assessment of their long-term robustness and excluding any issue of model overfitting. Excellent classification scores were achieved by all the technologies and nearly perfect classification was provided by FT-MIR. All the data fusion strategies provided satisfying outcomes, with the mid- and high-level approaches outperforming the low-level data fusion. However, no significant advantage over the FT-MIR alone was obtained. SIMCA modelling of FT-MIR data produced highly sensitive and specific models and an overall prediction ability improvement was achieved when more harvesting seasons were used for the model calibration (86.7% sensitivity and 91.1% specificity). The results obtained in the present work suggested the major potential of FT-MIR for fingerprinting-based honey authentication and demonstrated that accuracy levels that may be commercially useful can be reached. On the other hand, the combination of multiple vibrational spectroscopic fingerprints represents a choice that should be carefully evaluated from a cost/benefit standpoint within the industrial context

Стратегічне планування як основний інструмент ефективності підприємства

Наук. кер.: А.Ю. Жулавськи

Prediction of key milk biomarkers in dairy cows through milk MIR spectra and international collaborations.

peer reviewedAt the individual cow level, sub-optimum fertility, mastitis, negative energy balance and ketosis are major issues in dairy farming. These problems are widespread on dairy farms and have an important economic impact. The objectives of this study were: 1) to assess the potential of milk Mid Infrared (MIR) spectra to predict key biomarkers of energy deficit (citrate, isocitrate, glucose-6P, free glucose), ketosis (BHB and acetone), mastitis (NAGase and LDH), and fertility (progesterone); 2) to test alternative methodologies to partial least square regression (PLS) to better account for the specific asymmetric distribution of the biomarkers; and 3) to create robust models by merging large data sets from 5 international or national projects. Benefiting from this international collaboration, the data set comprised a total of 9,143 milk samples from 3,758 cows located in 589 herds across 10 countries and represented 7 breeds. The samples were analyzed by reference chemistry for biomarker contents while the MIR analyses were performed on 30 instruments from different models and brands, with spectra harmonized into a common format. Four quantitative methodologies were evaluated to address the strongly skewed distribution of some biomarkers. PLS was used as the reference basis, and compared with a random modification of distribution associated with PLS (Random-downsampling-PLS), an optimized modification of distribution associated with PLS (KennardStone-downsampling-PLS) and Support Vector Machine (SVM). When the ability of MIR to predict biomarkers was too low for quantification, different qualitative methodologies were tested to discriminate low vs high values of biomarkers. For each biomarker, 20% of the herds were randomly removed within all countries to be used as the validation data set. The remaining 80% of herds were used as the calibration data set. In calibration, the 3 alternative methodologies outperform the PLS performances for the majority of biomarkers. However, in the external herd validation, PLS provided the best results for isocitrate, glucose-6P, free glucose and LDH (R2v = 0.48, 0.58, 0.28, and 0.24). For other molecules, PLS-Random-downsampling and PLS-KennardStone-downsampling outperformed PLS in the majority of cases, but the best results were provided by SVM for citrate, BHB, acetone, NAGase and progesterone (R2v = 0.94, 0.58, 0.76, 0.68, and 0.15). Hence, PLS and SVM based on the entire data set provided the best results for normal and skewed distributions, respectively. Complementary to the quantitative methods, the qualitative discriminant models enabled the discrimination of high and low values for BHB, acetone, and NAGase with a global accuracy around 90%, and glucose-6P with an accuracy of 83%. In conclusion, MIR spectra of milk can enable quantitative screening of citrate as a biomarker of energy deficit and discrimination of low and high values of BHB, acetone, and NAGase, as biomarkers of ketosis and mastitis. Finally, progesterone could not be predicted with sufficient accuracy from milk MIR spectra to be further considered. Consequently, MIR spectrometry can bring valuable information regarding the occurrence of energy deficit, ketosis and mastitis in dairy cows, which in turn have major influences on their fertility and survival

A global spectral library to characterize the world's soil

Soil provides ecosystem services, supports human health and habitation, stores carbon and regulates emissions of greenhouse gases. Unprecedented pressures on soil from degradation and urbanization are threatening agro-ecological balances and food security. It is important that we learn more about soil to sustainably manage and preserve it for future generations. To this end, we developed and analyzed a global soil visible-near infrared (vis-NIR) spectral library. It is currently the largest and most diverse database of its kind. We show that the information encoded in the spectra can describe soil composition and be associated to land cover and its global geographic distribution, which acts as a surrogate for global climate variability. We also show the usefulness of the global spectra for predicting soil attributes such as soil organic and inorganic carbon, clay, silt, sand and iron contents, cation exchange capacity, and pH. Using wavelets to treat the spectra, which were recorded in different laboratories using different spectrometers and methods, helped to improve the spectroscopic modelling. We found that modelling a diverse set of spectra with a machine learning algorithm can find the local relationships in the data to produce accurate predictions of soil properties. The spectroscopic models that we derived are parsimonious and robust, and using them we derived a harmonized global soil attribute dataset, which might serve to facilitate research on soil at the global scale. This spectroscopic approach should help to deal with the shortage of data on soil to better understand it and to meet the growing demand for information to assess and monitor soil at scales ranging from regional to global. New contributions to the library are encouraged so that this work and our collaboration might progress to develop a dynamic and easily updatable database with better global coverage. We hope that this work will reinvigorate our community's discussion towards larger, more coordinated collaborations. We also hope that use of the database will deepen our understanding of soil so that we might sustainably manage it and extend the research outcomes of the soil, earth and environmental sciences towards applications that we have not yet dreamed of

Nanocrystallization by current annealing (with and without tensile stress) of Fe73.5−xNixSi13.5B9Nb3Cu1 alloy ribbons (x=5, 10, and 20

Microstructural (crystalline volume fraction and grain size), magnetization (coercive field), and saturation magnetostriction measurements in Fe73.5−xNixSi13.5B9Nb3Cu1 alloy ribbons (x=5, 10, and 20) treated by current annealing and stress-current annealing are presented. Microstructural analysis of the treated ribbons using x-ray diffraction showed a high content of the amorphous phase in the bulk. In addition, substantial changes in the crystalline state such as grain size of the samples annealed at different conditions were observed. The alloy composition also affects greatly the grain size: increase in Ni content leads to higher values of the average grain size. The evolutions of the coercive field with the two kinds of thermal treatment were analyzed, allowing us to conclude that the addition of Ni tends to reduce the magnetic softness of the original material and that the coercivities are higher in the samples treated by stress annealing than in those treated without tensile stress. On the other hand, the saturation magnetostriction decreases with the thermal treatment, which is in agreement with the microstructural behavior (structural relaxation and nanocrystallization process), although some discrepancies are found for samples with x=5.This work has been supported by the Basque Country Government and the Excma Diputación Foral de Gipuzkoa under the project NANOTRON.Peer reviewe

Perspectives offertes par l'imagerie hyperspectrale proche infrarouge dans l'étude de systèmes racinaires de légumineuses

Cet article synthétise les résultats de plusieurs études menées sur des systèmes racinaires de pois protéagineux en utilisant les données fournies par l'imagerie hyperspectrale proche infrarouge, une technique d'analyse combinant l'imagerie et la spectroscopie vibrationnelle. Dans un premier cas d'étude, cette méthode d'analyse a permis de quantifier la masse de racines de pois protéagineux au sein d'échantillons de racines prélevés sous des cultures en association de pois protéagineux et de froment d'hiver. Dans un second cas d'étude, cette méthode d'analyse a permis de quantifier la leghémoglobine au sein de nodosités individuelles de pois. La concentration de cette molécule est liée à l'activité de fixation d'azote des nodosités et sert dès lors d'indicateur pour mesurer cette activité. Sur base des résultats de ces études, cet article propose aussi des pistes de réflexion et de développement en lien avec l'imagerie hyperspectrale dans l'étude des systèmes racinaires de légumineuses. Il vise également à démontrer dans quelle mesure cette technique d'analyse constitue un outil de mesure intéressant dans l'étude des systèmes racinaires en général.This paper summarizes the results of several studies conducted on pea root systems using data provided by near infrared hyperspectral imaging, an analytical technique combining imaging and vibrational spectroscopy. In a first case study, this analytical method was used to quantify the mass of pea roots in root samples collected under pea-wheat intercropping. In a second case study, this analytical method was used to quantify leghaemoglobin in individual pea nodules. The concentration of this molecule is related to the nitrogen fixation activity of nodules and is therefore used as indicator to measure this activity. On the basis of the results of these studies, this article proposes ways of reflection and development related to hyperspectral imaging in the study of legume root systems and aims demonstrating to what extent this analytical technique constitutes an interesting measurement tool in the study of other root systems