Clean and accurate soil quality monitoring in mining areas under environmental rehabilitation in the Eastern Brazilian Amazon.

Soil quality monitoring in mining rehabilitation areas is a crucial step to validate the effectiveness of the adopted recovery strategy, especially in critical areas for environmental conservation, such as the Brazilian Amazon. The use of portable X-ray fluorescence (pXRF) spectrometry allows a rapid quantification of several soil chemical elements, with low cost and without residue generation, being an alternative for clean and accurate environmental monitoring. Thus, this work aimed to assess soil quality in mining areas with different stages of environmental rehabilitation based on predictions of soil fertility properties through pXRF along with four machine learning algorithms (projection pursuit regression, PPR; support vector machine, SVM; cubist regression, CR; and random forest, RF) in the Eastern Brazilian Amazon. Sandstone and iron mines in different chronological stages of rehabilitation (initial, intermediate, and advanced) were evaluated, in addition to non-rehabilitated and native forest areas. A total of 81 soil samples (26 from sandstone mine and 55 from iron mine) were analyzed by both traditional wet-chemistry methods and pXRF. The available/exchangeable contents of K, Ca, B, Fe, and Al, in addition to H+Al, cation exchange capacity at pH = 7, Al saturation, soil organic matter, pH, sum of bases, base saturation, clay, and sand were accurately predicted (R2 > 0.70) using pXRF data, with emphasis on the prediction of Fe (R2 = 0.93), clay content (R2 = 0.81), H+Al (R2 = 0.81), and K+ (R2 = 0.85). The best predictive models were developed by RF and CR (86%) and when considering pXRF data + mining area + stage of rehabilitation (73%). The results highlight the potential of pXRF to accurately assess soil properties in environmental rehabilitation areas in the Amazon region (yet scarcely evaluated under this approach), promoting a more agile and cheaper preliminary diagnosis compared to traditional methods.

Proximal sensing provides clean, fast, and accurate quality control of organic and mineral fertilizers.

Farms use large quantities of fertilizers from many sources, making quality control a challenging task, as the traditional wet-chemistry analyses are expensive, time consuming and not environmentally-friendly. As an alternative, this work proposes the use of portable X-ray fluorescence (pXRF) spectrometry and machine learning algorithms for rapid and low-cost estimation of macro and micronutrient contents in mineral and organic fertilizers. Four machine learning algorithms were tested. Whole (i.e., as delivered by the manufacturer) (CP) and ground (AQ) samples (429 in total) were analyzed to test the effect of fertilizer granulometry in prediction performance. Model validation indicated highly accurate predictions of macro (N: R2 = 0.92; P: 0.97; K: 0.99; Ca: 0.94, Mg: 0.98; S: 0.96) and micronutrients (B: 0.99; Cu: 0.99; Fe: 0.98; Mn: 0.91; Zn: 0.94) for both organic and mineral fertilizers. RPD values ranged from 2.31 to 9.23 for AQ samples, and Random Forest and Cubist Regression were the algorithms with the best performances. Even samples analyzed as they were received from the manufacturer (i.e., no grinding) provided accurate predictions, which accelerate the confirmation of nutrient contents contained in fertilizers. Results demonstrated the potential of pXRF data coupled with machine learning algorithms to assess nutrient composition in both mineral and organic fertilizers with high accuracy, allowing for clean, fast and accurate quality control. Sensor-driven quality assessment of fertilizers improves soil and plant health, crop management efficiency and food security with a reduced environmental footprint.

A Proximal Sensor-Based Approach for Clean, Fast, and Accurate Assessment of the Eucalyptus spp. Nutritional Status and Differentiation of Clones.

Several materials have been characterized using proximal sensors, but still incipient efforts have been driven to plant tissues. Eucalyptus spp. cultivation in Brazil covers approximately 7.47 million hectares, requiring faster methods to assess plant nutritional status. This study applies portable X-ray fluorescence (pXRF) spectrometry to (i) distinguish Eucalyptus clones using pre-processed pXRF data; and (ii) predict the contents of eleven nutrients in the leaves of Eucalyptus (B, Ca, Cu, Fe, K, Mg, Mn, N, P, S, and Zn) aiming to accelerate the diagnosis of nutrient deficiency. Nine hundred and twenty samples of Eucalyptus leaves were collected, oven-dried, ground, and analyzed using acid-digestion (conventional method) and using pXRF. Six machine learning algorithms were trained with 70% of pXRF data to model conventional results and the remaining 30% were used to validate the models using root mean square error (RMSE) and coefficient of determination (R2). The principal component analysis clearly distinguished developmental stages based on pXRF data. Nine nutrients were accurately predicted, including N (not detected using pXRF spectrometry). Results for B and Mg were less satisfactory. This method can substantially accelerate decision-making and reduce costs for Eucalyptus foliar analysis, constituting an ecofriendly approach which should be tested for other crops.

Clean quality control of agricultural and non-agricultural lime by rapid and accurate assessment of calcium and magnesium contents via proximal sensors.

Ca and Mg are the most important chemical elements in lime. Properly measuring Ca and Mg contents is essential to assess the quality of lime products. Quality control guarantees the adequate use of lime in industrial processes, in soils, and helps avoiding adulteration. Proximal sensors can aid in this process by determining Ca and Mg contents easily, rapidly and without producing chemical waste. The objective of this study was to evaluate the use an environmentally-friendly method of analyzing the quality of lime. We studied 1) the use of portable X-ray fluorescence (pXRF) to predict concentrations of Ca and Mg in lime, 2) tested if NixPro™ sensor can improve prediction accuracy and 3) tested if sample preparation methods (grinding) affect analyses. 74 samples of lime were analyzed by two different laboratories (lab. 1 = 38, lab. 2 = 36). All samples submitted to pXRF and NixPro™ analyses. Sensor analyses were done in whole (CP) and ground (AQ) samples to test the effect of sample preparation in prediction performance. High correlation was found between Ca and Mg contents measured via pXRF and laboratory analyses. Mg-CP presented the highest correlation coefficient (r = 0.81); Mg-AQ, the lowest (0.57). Predictions presented good performance (R2 > 0.68); Mg had the best results (0.86). Separating models per laboratory showed that some datasets are harder to model, probably due to variability in the source material (limestone). The addition of NixPro™ data contributed to improve prediction accuracy, although slightly. Predictions using CP samples presented the best results, especially for Mg, indicating that grinding is not necessary. This pioneer study demonstrated that fused proximal sensors can be used to rapidly and easily determine contents of Ca and Mg in soil amendments without producing chemical waste.

Tropical soils characterization at low cost and time using portable X-ray fluorescence spectrometer (pXRF): Effects of different sample preparation methods / Caracterização de solos tropicais a baixo custo e tempo usando espectrômetro portátil de fluorescência de raios-X (pXRF): Efeitos de diferentes métodos de preparo de amostras

ABSTRACT Portable X-ray fluorescence spectrometer (pXRF) has been recently adopted by the Soil Science community for uses in both field and laboratory, obtaining the total content of several chemical elements in a few seconds. Sulfuric acid digestion is an expensive and time-consuming laboratory analysis that provides contents of Fe2O3, Al2O3, SiO2, TiO2 and P2O5, important for soil studies. Due to few pXRF studies in tropical soils, this work aimed to compare contents of Fe2O3, Al2O3, SiO2, TiO2 and P2O5 obtained by pXRF with sulfuric acid digestion results, and to evaluate the effects of varying forms of preparing soil samples and scanning with pXRF on the resulting values in Brazilian soils. Soils were scanned in five conditions in-field (in situ) and in laboratory, evaluating varying sample preparation methods, particle sizes and soil moisture. Four pXRF scanning operational modes were tested. Linear regressions were adjusted between results of pXRF and sulfuric acid digestion. Equations were validated with an independent set of samples. Statistical analyses compared the methods of preparing the samples. Adequate linear models reached R2 of 0.99 and 0.89 for Fe2O3 and TiO2, respectively. Validation promoted R2 greater than 0.97 and RMSE and ME close to zero for both oxides. Statistical differences of pXRF results were found among the methods of preparing samples. pXRF spectrometer has great potential to obtain Fe2O3 and TiO2 content rapidly and economically with high correspondence with laboratory results of sulfuric acid digestion analysis. Varying methods of preparing the samples promote differences in the results of pXRF.

RESUMO O espectrômetro portátil de fluorescência de raios-X (pXRF) foi recentemente adotado pela Ciência do Solo, para uso em campo e laboratório, para obtenção do conteúdo total de vários elementos químicos em poucos segundos. A digestão com ácido sulfúrico é uma análise laboratorial cara e demorada que fornece teores de Fe2O3, Al2O3, SiO2, TiO2 e P2O5, importantes para estudos sobre solos. Devido aos poucos estudos sobre o pXRF em solos tropicais, este trabalho objetivou comparar os teores de Fe2O3, Al2O3, SiO2, TiO2 e P2O5 obtidos pelo pXRF com os resultados de digestão com ácido sulfúrico e avaliar os efeitos de diferentes formas de preparo de amostras de solo e leitura com o pXRF sobre seus resultados para solos brasileiros. Os solos foram submetidos a leituras com o pXRF em cinco condições, em campo (in situ) e em laboratório, avaliando variados métodos de preparo de amostras, tamanhos de partículas e umidade do solo. Quatro modos de operação do pXRF foram testados. Regressões lineares foram ajustadas entre os resultados do pXRF e digestão com ácido sulfúrico. As equações foram validadas com um conjunto independente de amostras. Análises estatísticas compararam os métodos de leitura de amostras. Modelos lineares adequados atingiram R2 de 0,99 e 0,89 para Fe2O3 e TiO2, respectivamente. A validação promoveu R2 maior que 0.97 e RMSE e ME próximos a zero para ambos os óxidos. Foram encontradas diferenças estatísticas dos resultados do pXRF entre os métodos de preparo de amostras. O pXRF possui um grande potencial para obter rápida e economicamente os teores de Fe2O3 e TiO2 com elevada correspondência com os resultados laboratoriais da análise da digestão com ácido sulfúrico. Métodos variáveis ​​de preparo das amostras promovem diferenças nos resultados de pXRF.

Multiple linear regression and random forest to predict and map soil properties using data from portable X-ray fluorescence spectrometer (pXRF) / Regressão linear múltipla e random forest para predição e mapeamento de atributos do solo utilizando dados de espectrômetro portátil de fluorescência de raios-X (pXRF)

ABSTRACT Determination of soil properties ​​helps in the correct management of soil fertility. The portable X-ray fluorescence spectrometer (pXRF) has been recently adopted to determine total chemical element contents in soils, allowing soil property inferences. However, these studies are still scarce in Brazil and other countries. The objectives of this work were to predict soil properties using pXRF data, comparing stepwise multiple linear regression (SMLR) and random forest (RF) methods, as well as mapping and validating soil properties. 120 soil samples were collected at three depths and submitted to laboratory analyses. pXRF was used in the samples and total element contents were determined. From pXRF data, SMLR and RF were used to predict soil laboratory results, reflecting soil properties, and the models were validated. The best method was used to spatialize soil properties. Using SMLR, models had high values of R² (≥0.8), however the highest accuracy was obtained in RF modeling. Exchangeable Ca, Al, Mg, potential and effective cation exchange capacity, soil organic matter, pH, and base saturation had adequate adjustment and accurate predictions with RF. Eight out of the 10 soil properties predicted by RF using pXRF data had CaO as the most important variable helping predictions, followed by P2O5, Zn and Cr. Maps generated using RF from pXRF data had high accuracy for six soil properties, reaching R2 up to 0.83. pXRF in association with RF can be used to predict soil properties with high accuracy at low cost and time, besides providing variables aiding digital soil mapping.

RESUMO A determinação de atributos do solo auxilia no correto manejo da sua fertilidade. O equipamento portátil de fluorescência de raios-X (pXRF) foi recentemente adotado para determinar o teor total de elementos químicos em solos, permitindo inferências sobre atributos do solo. No entanto, esses estudos ainda são escassos no Brasil e em outros países. Os objetivos deste trabalho foram prever atributos do solo a partir de dados do pXRF, comparando-se os métodos de regressão linear múltipla stepwise (SMLR) e de random forest (RF), além de mapear e validar atributos do solo. 120 amostras de solo foram coletadas em três profundidades e submetidas a análises laboratoriais. Utilizou-se o pXRF para leitura das amostras e determinou-se o teor total de elementos. A partir dos dados do pXRF, foram utilizadas SMLR e RF para predizer resultados laboratoriais, que refletem atributos do solo, e os modelos foram validados. O melhor método foi utilizado para espacializar os atributos do solo. Utilizando SMLR, os modelos apresentaram valores elevados de R² (≥0,8), porém maior acurácia foi obtida na modelagem com RF. A capacidade de troca de cátions potencial e efetiva, matéria orgânica do solo, pH, saturação por bases e teores trocáveis de Ca, Al e Mg apresentaram ajustes adequados e predições acuradas com RF. Dos dez atributos do solo preditos por RF a partir de dados do pXRF, sete apresentavam CaO como a variável mais importante para auxiliar as predições, seguido por P2O5, Zn e Cr. Os mapas gerados a partir de dados do pXRF usando RF apresentaram adequados valores de R² para seis atributos do solo, atingindo R2 de até 0,83. O pXRF em associação com RF pode ser usado para prever atributos do solo com elevada acurácia, com rapidez e a baixo custo, além de proporcionar variáveis que auxiliam o mapeamento digital de solos.

Land-use effect on hydropedology in a mountainous region of Southeastern Brazil / Efeito do uso do solo na hidropedologia em uma região montanhosa do sudeste do Brasil

ABSTRACT In Brazil, the Mantiqueira Range, southeastern region, shelters the last remnants of the ecologically important Upper Montane Tropical Forest. since extensive exploration that has been taking place in this biome for decades, the influence of land-use changes on hydropedology in these areas must be investigated once major land-use changes have been observed. This study aims to evaluate the land-use influence on soil drainable porosity (SDP) in a headwater watershed located in the Mantiqueira Range region, and to validate the proposed methods based on micromorphological and hydrological indicators. The native vegetation of the study area is Atlantic forest that occupies 62% of the area, and the remaining 38% has been used for pasture. Thirty nine combinations of environmental variables were tested, each one generating a map for predicting SDP. The performance of the spatial prediction of SDP was assessed using 20% of the data from the total number of samples collected throughout the watershed. The least values of SDP are due to the process of removal of native forest and replacement by pasture. Areas with high to moderate SDP are associated with native forest fragments demonstrating the effects of the Atlantic Forest on the water infiltration and groundwater recharge processes, given by the greater contribution of baseflow in a forested catchment located within the studied watershed. The analysis of soil micromorphological images provided useful supporting information on the soil porosity system and along with hydrological properties of the watershed helped understand the SDP behavior on subsurface and groundwater storage capacity.

RESUMO No Brasil, a Serra da Mantiqueira, abriga um dos últimos remanescentes da Floresta Tropical de Altitude. Devido a grande exploração que vem ocorrendo neste bioma há décadas, a influência na hidropedologia decorrente das mudanças do uso do solo deve ser investigada. O objetivo deste estudo foi avaliar a influência do uso do solo na porosidade drenável do solo (PDS) em uma bacia hidrográfica localizada na região da Serra da Mantiqueira e validar os métodos propostos com base em indicadores micromorfológicos e hidrológicos. A vegetação nativa da área de estudo é a Mata Atlântica que ocupa 62% da área, e com os 38% restantes utilizados para pastagem. Trinta e nove combinações de variáveis ​​ambientais foram testadas, cada uma gerando um mapa para predizer a PDS. O desempenho da predição espacial da PDS foi avaliado utilizando 20% dos dados do número total de amostras coletadas em toda a bacia hidrográfica. Os menores valores de PDS são devidos ao processo de remoção de floresta nativa e substituição por pastagem. Áreas com altos a moderados valores de PDS estão associadas a fragmentos de florestas nativas que demonstram os efeitos da Mata Atlântica nos processos de infiltração de água e de recarga de água subterrânea na região da Mantiqueira, dada a maior contribuição do fluxo base em áreas florestadas. A análise micromorfológica do solo forneceu informações úteis sobre o sistema poroso do solo e as propriedades hidrológicas da bacia hidrográfica, ajudando a entender o comportamento da PDS e a capacidade de armazenamento em subsuperfícíe.

Portable X-ray fluorescence (pXRF) applications in tropical Soil Science / Aplicações da fluorescência de raios-X portátil (pXRF) na Ciência do Solo tropical

ABSTRACT The X-ray fluorescence (XRF) is an analytical technique for determination of elemental composition of different materials. In soils, the XRF has many pedological, environmental and agronomic applications, mainly after the emergence of portable equipments (pXRF). This technique has been recently adopted and successfully used for soil characterization worldwide, but very rare works have been carried out in soils of developing countries. The soil characterization includes the complete elemental composition determination (nutrients, trace and rare-earth elements) and allows estimating some soil physical and chemical properties. In Brazil, this technique is still incipient, mainly the use of pXRF, however, it can greatly contribute to soil characterization in-field or in-lab conditions and also replacing methods of soil analyses considered non-environmentally friendly. This review summarizes the XRF technique including principles and the main applications of pXRF in soils highlighting its potential for tropical Soil Science.

RESUMO Fluorescência de raios-X (FRX) é uma técnica analítica para determinação da composição elementar de diferentes materiais. Em solos, a FRX apresenta muitas aplicações pedológicas, ambientais e agronômicas, principalmente após a emergência de equipamentos portáteis (pXRF). Essa técnica tem sido utilizada com sucessso no mundo todo para caracterização do solo, entretanto, são raros os trabalhos em solos de países em desenvolvimento. A caracterização do solo inclui a determinação completa da composição elementar (nutrientes, elementos-traço e terras-raras) e permite a estimativa de atributos químicos e físicos do solo. No Brasil, a FRX é ainda incipiente, principalmente o uso do pXRF, entretanto, essa técnica pode contribuir grandemente para a caracterização do solo no campo, em condições laboratoriais e, também, substituindo alguns métodos de análise do solo considerados não prejudicial ao ambiente. Esta revisão sumariza a técnica de FRX incluindo princípios e as principais aplicações do pXRF, destacando seu potencial de uso na Ciência do Solo tropical.

Urochloa decumbens growth and P uptake as affected by long-term phosphate fertilization, mycorrhizal inoculation and historical land use in contrasting Oxisols of the Brazilian Cerrado / Crescimento e absorção de P por Urochloa decumbens afetado por longos períodos de adubação fosfatada, inoculação micorrízica e histórico de uso em Latossolos contrastantes do Cerrado brasileiro

ABSTRACT In the fertility management of highly weathered-leached Brazilian Oxisols, P is the most limiting macronutrient. A greenhouse experiment was conducted with the objective to evaluate the influence of the interaction between P doses, mycorrhizal inoculation and historical land use on Urochloa decumbens growth and P uptake in four Oxisols with contrasting chemical, physical and mineralogical properties. The plants were cultivated in plastic pots containing 4 kg of soil in a completely randomized design, four replications and 2x2x2 factorial scheme: with two P doses; with and without mycorrhizal inoculation; soils cultivated for long periods and non-cultivated (under native vegetation). There were two plantings of ten weeks each. Shoot dry mater, concentration and accumulation of P in the shoot were evaluated. In the first planting, the Urochloa response was greater in non-cultivated soils associated with inoculation and P addition. However, in the second planting, the inoculation had a greater effect in all soils compared to the first planting associated with the lowest P dose. As the P concentration in the soil increased, P in the shoot dry matter increases. The inoculation did not affect the P concentration and accumulation in the shoot of Urochloa. The growth of Urochloa decumbens was strongly influenced by the interaction among soil class x history of land use x dose of P x inoculation.

RESUMO No manejo da fertilidade de Latossolos brasileiros altamente intemperizados e lixiviados, o P é o macronutriente mais limitante. Assim, conduziu-se um experimento em casa de vegetação, objetivando-se avaliar a influência da interação entre doses de P, inoculação micorrízica e histórico de uso do solo no crescimento de Urochloa decumbens e absorção de P, em quatro Latossolos com atributos químicos, físicos e mineralógicos contrastantes. As plantas foram cultivadas em vasos contendo 4 kg de solo, dispostos em um delineamento inteiramente casualizado, com quatro repetições e esquema fatorial 2x2x2: duas doses de P; com e sem inoculação micorrízica; solos cultivados por longos períodos e não cultivados (sob vegetação nativa). Realizaram-se dois cultivos com duração de 10 semanas cada. Após cada cultivo avaliaram-se a matéria seca da parte aérea, teor e acúmulo de P na parte aérea. No primeiro cultivo, maior resposta ao P aconteceu nos solos sob vegetação nativa em associação à inoculação e adição de P. No segundo cultivo, a inoculação teve maior efeito em todos os solos, associada à menor dose de P. O aumento do P no solo aumenta a concentração desse nutriente na parte aérea. A inoculação não teve efeito na concentração e no acúmulo de P na parte aérea de Urochloa. O crescimento de Urochloa decumbens foi fortemente influenciado pela interação entre classe de solo x histórico de uso da terra x dose de P x inoculação.