Combined use of Vis-NIR and XRF sensors for tropical soil fertility analysis : assessing different data fusion approaches

Visible and near infrared (vis-NIR) diffuse reflectance and X-ray fluorescence (XRF) sensors are promising proximal soil sensing (PSS) tools for predicting soil key fertility attributes. This work aimed at assessing the performance of the individual and combined use of vis-NIR and XRF sensors to predict clay, organic matter (OM), cation exchange capacity (CEC), pH, base saturation (V), and extractable (ex-) nutrients (ex-P, ex-K, ex-Ca, and ex-Mg) in Brazilian tropical soils. Individual models using the data of each sensor alone were calibrated using multiple linear regressions (MLR) for the XRF data, and partial least squares (PLS) regressions for the vis-NIR data. Six data fusion approaches were evaluated and compared against individual models using relative improvement (RI). The data fusion approaches included (i) two spectra fusion approaches, which simply combined the data of both sensors in a merged dataset, followed by support vector machine (SF-SVM) and PLS (SF-PLS) regression analysis; (ii) two model averaging approaches using the Granger and Ramanathan (GR) method; and (iii) two data fusion methods based on least squares (LS) modeling. For the GR and LS approaches, two different combinations of inputs were used for MLR. The GR2 and LS2 used the prediction of individual sensors, whereas the GR3 and LS3 used the individual sensors prediction plus the SF-PLS prediction. The individual vis-NIR models showed the best results for clay and OM prediction (RPD >= 2.61), while the individual XRF models exhibited the best predictive models for CEC, V, ex-K, ex-Ca, and ex-Mg (RPD >= 2.57). For eight out of nine soil attributes studied (clay, CEC, pH, V, ex-P, ex-K, ex-Ca, and ex-Mg), the combined use of vis-NIR and XRF sensors using at least one of the six data fusion approaches improved the accuracy of the predictions (with RI ranging from 1 to 21%). In general, the LS3 model averaging approach stood out as the data fusion method with the greatest number of attributes with positive RI (six attributes; namely, clay, CEC, pH, ex-P, ex-K, and ex-Mg). Meanwhile, no single approach was capable of exploiting the synergism between sensors for all attributes of interest, suggesting that the selection of the best data fusion approach should be attribute-specific. The results presented in this work evidenced the complementarity of XRF and vis-NIR sensors to predict fertility attributes in tropical soils, and encourage further research to find a generalized method of data fusion of both sensors data. Keywords Author Keywords

Análise da construção do conhecimento na perspectiva das teorias de Vygotsky

The present article approaches some aspects of the theories of learning of Vygotsky and argues, from this reference, it disciplines it of boarded chemistry in Right Scholl through the analysis of interactions between mediators and learning. Such analysis is made from Interventions carried through with pupils the third series in the State School Cristiano de Souza in the City of Lavras - MG. the applied methodology is based on questionnaires daily pay and experimental after-lesson and in the assembly of the experiments for the proper learning, this method is called Intervention. The results observed during and after the accomplishment of this work, indicated that the method of teach-learning of chemistry presented and argued here, inside of the of this reference can contribute as factor for the chemistry education.O presente artigo aborda alguns aspectos das teorias de aprendizado de Vygotsky e discute, a partir desse referencial, a disciplina de química abordada no Ensino Médio através da análise de interações entre mediadores e discentes. Tal análise é feita a partir de Intervenções realizadas com alunos e alunas da terceira série do Ensino Médio na Escola Estadual Cristiano de Souza, no Município de Lavras -MG. A metodologia aplicada baseia-se em questionários pré e pós-aula experimental e na montagem dos experimentos pelos próprios discentes, este método é denominado Intervenção. Os resultados observados durante e após a realização deste trabalho, indicou que o método de ensino-aprendizado de química aqui apresentado e discutido, dentro do referencial teórico abordado, pode contribuir como fator motivador para o ensino de química. Palavras-chave: Mediadores. Vygotsky. Metodologia

Cellulose Acetate Microbeads for Controlled Delivery of Essential Micronutrients

The controlled delivery of micronutrients to soil and plants is essential to increase agricultural yields. However, this is today achieved using fossil fuel-derived plastic carriers, posing environmental risks and contributing to global carbon emissions. In this work, a novel and efficient way to prepare biodegradable zinc-impregnated cellulose acetate beads for use as controlled release fertilizers is presented. Cellulose acetate solutions in DMSO were dropped into aqueous antisolvent solutions of different zinc salts. The droplets underwent phase inversion, forming solid cellulose acetate beads containing zinc, as a function of zinc salt type and concentration. Even higher values of zinc uptake (up to 15.5%) were obtained when zinc acetate was added to the cellulose acetate–DMSO solution, prior to dropping in aqueous zinc salt antisolvent solutions. The release profile in water of the beads prepared using the different solvents was linked to the properties of the counter-ions via the Hofmeister series. Studies in soil showed the potential for longer release times, up to 130 days for zinc sulfate beads. These results, together with the efficient bead production method, demonstrate the potential of zinc-impregnated cellulose acetate beads to replace the plastic-based controlled delivery products used today, contributing to the reduction of carbon emissions and potential environmental impacts due to the uptake of plastic in plants and animals

Efficiency of soluble and insoluble sources of manganese for soybean nutrition in the Brazilian Cerrado

O objetivo deste trabalho foi avaliar a eficiência de fontes e doses de magnésio solúvel (MnSO4.H2O) e insolúvel (MnCO3) nos processos de absorção, transporte e redistribuição deste nutriente na soja (Glycine max), bem como na produtividade da cultura, em solo de Cerrado. O delineamento experimental foi em blocos ao acaso, em arranjo fatorial 4×2 – quatro doses (150, 250, 350 e 450 g ha-1) × duas fontes (MnSO4.H2O e MnCO3) de Mn –, com quatro repetições. Nas safras de 2015/2016 e 2016/2017, realizaram-se adubações foliares no terceiro trifólio e avaliaram-se os conteúdos de Mn e a produtividade da soja. Em ambas as safras, a fertilização foliar com Mn aumentou os teores do nutriente nas folhas, nos caules e nos grãos, mas não afetou o rendimento de grãos e a produção de matéria seca. Os teores máximos de Mn nas folhas foram obtidos com doses entre 150 e 450 g ha-1. A aplicação de MnSO4.H2O aumentou a absorção, o transporte e a redistribuição de Mn na planta, com desempenho superior ao de MnCO3. A fertilização foliar com MnSO4.H2O em soja, em solo de Cerrado, aumenta os teores de Mn nas folhas, mas não a produtividade e a produção de matéria seca.The objective of this work was to evaluate the efficiency of sources and rates of soluble (MnSO4.H2O) and insoluble (MnCO3) manganese on the processes of uptake, transport, and redistribution of this nutrient in soybean, as well as on crop yield, in Cerrado soil. The experimental design was randomized complete blocks in a 4×2 factorial arrangement – four rates (150, 250, 350, and 450 g ha-1) × two sources (MnSO4.H2O and MnCO3) of Mn –, with four replicates. In the 2015/2016 and 2016/2017 crop seasons, foliar fertilizations were carried out on the third trifoliate leaflet, and Mn content and soybean yield were evaluated. In both crop seasons, Mn foliar fertilization increased the contents of the nutrient in leaves, stems, and grains, but did not affect grain yield and dry matter production. The maximum Mn contents in leaves were obtained with rates between 150 and 450 g ha-1. The fertilization with MnSO4.H2O increased Mn uptake, transport, and redistribution in the plant, with a performance superior to that of MnCO3. Foliar fertilization with MnSO4.H2O in soybean, in a Cerrado soil, increases Mn contents in the leaves but not yield and dry matter production

Cellulose Acetate Microbeads for Controlled Delivery of Essential Micronutrients

The controlled delivery of micronutrients to soil and plants is essential to increase agricultural yields. However, this is today achieved using fossil fuel-derived plastic carriers, posing environmental risks and contributing to global carbon emissions. In this work, a novel and efficient way to prepare biodegradable zinc-impregnated cellulose acetate beads for use as controlled release fertilizers is presented. Cellulose acetate solutions in DMSO were dropped into aqueous antisolvent solutions of different zinc salts. The droplets underwent phase inversion, forming solid cellulose acetate beads containing zinc, as a function of zinc salt type and concentration. Even higher values of zinc uptake (up to 15.5%) were obtained when zinc acetate was added to the cellulose acetate-DMSO solution, prior to dropping in aqueous zinc salt antisolvent solutions. The release profile in water of the beads prepared using the different solvents was linked to the properties of the counter-ions via the Hofmeister series. Studies in soil showed the potential for longer release times, up to 130 days for zinc sulfate beads. These results, together with the efficient bead production method, demonstrate the potential of zinc-impregnated cellulose acetate beads to replace the plastic-based controlled delivery products used today, contributing to the reduction of carbon emissions and potential environmental impacts due to the uptake of plastic in plants and animals.</p

Effect of X-ray tube configuration on measurement of key soil fertility attributes with XRF

The successful use of energy-dispersive X-ray fluorescence (ED-XRF) sensors for soil analysis requires the selection of an optimal procedure of data acquisition and a simple modelling approach. This work aimed at assessing the performance of a portable XRF (XRF) sensor set up with two different X-ray tube configurations (combinations of voltage and current) to predict nine key soil fertility attributes: (clay, organic matter (OM), cation exchange capacity (CEC), pH, base saturation (V), and extractable nutrients (P, K, Ca, and Mg). An XRF, operated at a voltage of 15 kV (and current of 23 mu A) and 35 kV (and current of 7 mu A), was used for analyzing 102 soil samples collected from two agricultural fields in Brazil. Two different XRF data analysis scenarios were used to build the predictive models: (i) 10 emission lines of 15 keV spectra (EL-15), and (ii) 12 emission lines of 35 keV spectra (EL-35). Multiple linear regressions (MLR) were used for model calibration, and the models' prediction performance was evaluated using different figures of merit. The results show that although X-ray tube configuration affected the intensity of the emission lines of the different elements detected, it did not influence the prediction accuracy of the studied key fertility attributes, suggesting that both X-ray tube configurations tested can be used for future analyses. Satisfactory predictions with residual prediction deviation (RPD) >= 1.54 and coefficient of determination (R-2) >= 0.61 were obtained for eight out of the ten studied soil fertility attributes (clay, OM, CEC, V, and extractable K, Ca, and Mg). In addition, simple MLR models with a limited number of emission lines was effective for practical soil analysis of the key soil fertility attributes (except pH and extractable P) using XRF. The simple and transparent methodology suggested also enables future researches that seek to optimize the XRF scanning time in order to speed up the XRF analysis in soil samples

Assessing soil key fertility attributes using a portable X-ray fluorescence : a simple method to overcome matrix effect

The matrix effect is one of the challenges to be overcome for a successful analysis of soil samples using X-ray fluorescence (XRF) sensors. This work aimed at evaluation of a simple modeling approach consisted of Compton normalization (CN) and multivariate regressions (e.g., multiple linear regressions (MLR) and partial least squares regression (PLSR)) to overcome the soil matrix effect, and subsequently improve the prediction accuracy of key soil fertility attributes. A portable XRF was used for analyzing 102 soil samples collected from two agricultural fields with contrasting soil matrices. Using the intensity of emission lines as input, preprocessing methods included with and without the CN. Univariate regression models for the prediction of clay, cation exchange capacity (CEC), and exchangeable (ex-) K and Ca were compared with the corresponding MLR models to assess matrix effect mitigation. The MLR and PLSR models improved the prediction results of the univariate models for both preprocessing methods, proving to be promising strategies for mitigating the matrix effect. In turn, the CN also mitigated part of the matrix effect for ex-K, ex-Ca, and CEC predictions, by improving the predictive performance of these elements when used in univariate and multivariate models. The CN has not improved the prediction accuracy of clay. The prediction performances obtained using MLR and PLSR were comparable for all evaluated attributes. The combined use of CN with multivariate regressions (MLR or PLSR) achieved excellent prediction results for CEC (R-2= 0.87), ex-K (R-2 >= 0.94), and ex-Ca (R-2 >= 0.96), whereas clay predictions were comparable with and without CN (0.89 <= R-2 <= 0.92). We suggest using multivariate regressions (MLR or PLSR) combined with the CN to remove the soil matrix effects and consequently result in optimal prediction results of the studied key soil fertility attributes. The prediction performance observed for this solution showed comparable results to the approach based on the preprogrammed measurement package tested (Geo Exploration package, Bruker AXS, Madison, WI, USA)

Physiological, biochemical, and ultrastructural characterization of selenium toxicity in cowpea plants

Selenium (Se) is considered a beneficial element for plants; however, in high concentrations, it causes negative effects on plant physiology and development. This study reports the first physiological, nutritional, and ultrastructural description of Se toxicity in cowpea growing under field conditions. Selenium was supplied as a foliar application of sodium selenite at varying concentrations (0, 50, 100, 200, 400, 800, 1200, and 1600 g ha−1). An increased yield was observed with the application of 50 g ha−1 Se. Application of concentrations higher than 50 g ha−1 caused leaf toxicity. Increased lipid peroxidation and hydrogen peroxide concentration and reduced total sugars, sucrose, and carotenoid concentration were observed at highest doses tested (1200 and 1600 g ha−1). Applications of more than 50 g ha−1 Se reduced the phloem diameter, caused chlorosis of the leaf blade with a coalescence of lesions, and caused pink salt deposits to appear. Lesions were observed mainly near the trichomes on the adaxial surface of the leaf blade. An analysis of the element distribution with microprobe X-ray fluorescence spectrometry (μ-XRF) revealed accumulation of Se, calcium (Ca), potassium (K), copper (Cu), and manganese (Mn) near the primary vein and in the necrotic brown areas of the leaf lesions. In contrast, Na was homogeneously distributed in the leaf tissue