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Abstract The increasing demand for sustainable agricultural practices necessitates innovative solutions for soil fertilization. This study aimed to assess the viability of using limestone mining co-products from the Irati and Corumbataí Formations as multi-nutrient sources for Glycine max cultivation. The experiment utilized a double factorial design (7 × 2) with five replications, randomly arranged and placed in pots within a greenhouse. The factors examined were the type of co-product (sedimentary rocks from the Irati Formation: rhythmite and bituminous shale; and the Corumbataí Formation: clayey siltstone) and the soil type (Haplic Arenosol and Rhodic Ferralsol). Soil ion content was assessed at 21 and 140 days after treatment application. Each pot housed four G. max plants, with leaf harvest occurring after 42 days of growth. Macronutrient content, leaf production, and soil ion availability were determined thereafter. Overall, co-product application led to increased soil pH and availability of essential ions, including K+, Mg2+, Ca2+, P, S-SO4 2−, and Si. At 140 days, rhythmite was notably effective in increasing pH, Ca2+, and Mg2+ in Haplic Arenosol, with respective increases of 22%, 224%, and 696%. Bituminous shale, on the other hand, significantly increased S-SO4 2− content by 67% and 426% in Rhodic Ferralsol and Haplic Arenosol, respectively. Moreover, the application of co-products resulted in enhanced accumulation of K, Ca, Mg, and S in G. max plants, alongside increased leaf production. In conclusion, the utilization of mining co-products positively influenced soil and plant chemical attributes, particularly enhancing leaf production in G. max. These findings highlight the potential of co-products as environmentally friendly solutions for soil fertilization, supporting sustainable agricultural practices. This research highlights a significant step towards sustainable agriculture by recycling mining waste into valuable soil amendments, which can improve crop yields and reduce the environmental impact of both mining and agricultural activities. Graphical Abstract

Some of the problems attributed to traditional laboratory analyses that limit the correct assessment of the nutrient contents in the soil are time requirements and high cost of the soil nutrient determinations. To solve these problems, a study was carried out to evaluate the use of visible, near-infrared, and short-wave infrared (Vis-NIR-SWIR) spectroscopy in the prediction of soil available ions submitted to the application of rock powders. The study was carried out on an Arenosol in Paranavaí City/Brazil. Treatments (rock powders) were arranged within a split-plot system designed in randomized blocks with four repetitions. Sugarcane was cultivated for 14 months after the application of rock powders. Later, 96 soil samples were collected for measuring the pH and available ions P, K+, Ca2+, Mg2+, S-SO42-, Si, Cu2+, Fe2+, Mn2+, and Zn2+ as well as spectral reading through a Vis-NIR-SWIR spectroradiometer to predict the soil chemical attributes through the partial least square regression (PLS) technique. The results showed that the elements K+, Ca2+, Mg2+, Cu2+, and Fe2+ could be predicted with a reasonable rightness degree (R2p > 0.50, RPDp > 1.40) from spectral models. However, for the attributes pH, P, S-SO42-, Si, Mn2+, and Zn2+, there were no satisfactory models (R2p

The quantification of soil organic matter (SOM) has increased over the years, especially in the Brazilian Cerrado region, one of the most important areas for grain production in the country. In this area, SOM content tends to be low, which directly impacts the physical, chemical and biological quality of soils. Thus, the use of spectroradiometry has been widely evaluated to investigate whether it can be used as a faster, more reliable and cheaper solution to meet the SOM estimation. In this context, the objective of the present paper was to evaluate the performance of a local spectral model for SOM prediction generated through the spiking strategy. The research was developed in the municipality of Passos, Minas Gerais State, located in the Brazilian Cerrado. Soil samples (0–0.2 m and 0.2–0.4 m depths) were collected in a zigzag pattern and split in calibration of the local models from a test area (90 soil samples) and recalibration and validation from a target area (46 soil samples). After this stage, the SOM contents were determined in a laboratory, and the spectral responses (350–2500 nm) of each soil sample were collected. From the target area, 10, 25 and 50% of soil spectra were selected for recalibration of the local models generated for the test area. Although median results were observed in the post-recalibration, due to the type of sample selected and the relative similarity among the spectral curves of both areas, improvement was observed for all statistical indices, especially when using 50% (23) of samples for recalibration of the local models, reaching r2 = 0.43, RMSEP = 2.34 gdm−3 and RPIQ = 4.58. These results are important for the SOM estimation in the Brazilian Cerrado considering its importance to the food security and socioeconomic activities. However, considering the lack of similar research in the study area, it is necessary to further investigate the development of spectral models on a local scale and their contribution to improve the identification of SOM spatial variability.

ABSTRACT Spatial variability management of soil chemical attributes is one of the approaches to be employed in the face of the constant challenge of increasing agricultural yield to meet world demand. In this sense, precision agriculture has as one of its tools the application of inputs at varying rates, which seeks to determine the ideal amount of fertilizer at each point of the crop, contrary to the conventional recommendation approach based on average values. In this context, this work studied the fertilizer recommendation methods used in site-specific nutrient management and the calculation methodologies for N, P, and K recommendations. For this purpose, a systematic literature study (SLS), consisting of systematic literature mapping, snowballing, and systematic literature review was performed. The analyzed studies were grouped into five domains (precision agriculture, soil fertility, site-specific nutrient application, fertilizer recommendation methods, and recommendation software for site-specific nutrient application). As a result, the SLS identified 12 methods for recommending N, nine for recommending P, and six for recommending K, in addition to five computer programs for precision agriculture that perform fertilizer recommendations at varying rates.

Photodynamic therapy is a treatment modality that can be used to treat various types of lesions. To produce cell death, reaching a certain threshold dose of reactive oxygen species (ROS) is required. The estimation of ROS production is of paramount importance to predict the depth of necrosis and to ensure that the volume to be treated receives doses higher than the threshold. In this study, we compared a theoretical model for PDT based on Monte Carlo simulations of light irradiance and rate equations with a rat liver model. At the end of the simulation, necrosis depths and volumes were estimated, as well as the photosensitizer (PS), oxygen, and ROS concentrations at each position of the treated area. From the in vivo study, we obtained the ROS concentration threshold of about 1 mM for Photogem in rat liver. This proposed method can be used for any PS or tissue, including tissues with multiple layers. The proposed method can be used to estimate parameters for any PS or tissue, including layered tissues, as long as their parameters are known. In addition, other protocols can be tested, or compared with the standard ones, providing the bases for analyzing a diverse range of photodynamic treatment scenarios.

Thousands of chemical analyses are carried out annually with the aim of recommending soil correction; however, these analyses are expensive, destructive, time-consuming, and can be harmful to the environment. As an alternative to conventional analysis methods, diffuse reflectance spectroscopy has been proposed as an option for evaluating the chemical characteristics of soil. The selection of variables has also emerged as an alternative to improve the performance of PLSR (partial least squares regression), as it decreases the root mean square error (RMSE) and increases the accuracy of the models. However, few studies have used a previous selection of variables for the construction of PLSR models to estimate the chemical characteristics of soil. In this context, the hypothesis in this study was that it is possible to calculate the liming recommendation in Oxisol based on the chemical characteristics estimated by PLSR, with a previous selection of variables using iPLS (Interval PLS). The objective was to calculate the need for liming based on chemical characteristics estimated via iPLS selection and PLSR modeling of specific wavelengths of soil reflectance. The experimental area was treated with different application rates of limestone, with and without incorporation, and phosphogypsum was applied in additional treatments. Soil assessments were carried out 5, 12, 24, and 36 months after the application of the treatments, using six layers: 0.00–0.05, 0.05–0.10, 0.10–0.20, 0.20–0.30, 0.30–0.40 and 0.40–0.60 m. Samples were subjected to conventional laboratory analyses, and spectral readings (400–2500 nm) were obtained with a spectroradiometer. The spectral curves were subjected to the iPLS variable selection method to generate PLSR models of the chemical characteristics used to calculate the liming recommendation. The chemical characteristics of the soil, such as Ca2+, sum of bases (SB), effective cation exchange capacity (CTCe), cation exchange capacity (CTC), and base saturation (BS), could be estimated, with values of R2 ranging from 0.83 to 0.92 in the calibration and validation steps, and from 0.84 to 0.90 for the prediction step (in the fourth assessment). The liming recommendation calculated based on the chemical characteristics predicted from the PLSR models showed a strong correlation (r > 0.86) with the liming recommendation calculated by conventional laboratory techniques. The fourth soil assessment yielded the best correlation coefficient (r = 0.95).

We evaluated the use of airborne hyperspectral imaging and non-imaging sensors in the Vis—NIR—SWIR spectral region to assess particle size and soil organic matter in the surface layer of tropical soils (Oxisols, Ultisols, Entisols). The study area is near Piracicaba municipality, São Paulo state, Brazil, in a sugarcane cultivation area of 135 hectares. The study area, with bare soil, was imaged in April 2016 by the AisaFENIX aerotransported hyperspectral sensor, with spectral resolution of 3.5 nm between 380 and 970 nm, and 12 nm between 970 and 2500 nm. We collected 66 surface soil samples. The samples were analyzed for particle size and soil organic matter content. Laboratory spectral measurements were performed using a non-imaging spectroradiometer (ASD FieldSpec 3 Jr). Partial Least Square Regression (PLSR) was used to predict clay, silt, sand and soil organic matter (SOM). The PLSR functions developed were applied to the hyperspectral image of the study area, allowing development of a prediction map of clay, sand, and SOM. The developed PLSR models demonstrated the relationship between the predictor variables at the cross-validation step, both for the non-imaging and imaging sensors, when the highest r and R2 values were obtained for clay, sand, and SOM, with R2 over 0.67. We did not obtain a satisfactory model for silt content. For the non-imaging sensor at the prediction step, R2 values for clay and SOM were over 0.7 and sand was lower than 0.54. The imaging sensor yielded models for clay, sand, and SOM with R2 values of 0.62, 0.66, and 0.67, respectively. Pearson correlation between sensors was greater than 0.849 for the prediction of clay, sand, and SOM. Our study successfully generated, from the imaging sensor, a large-scale and detailed predicted soil maps for particle size and SOM, which are important in the management of tropical soils.

Visible (V), Near Infrared (NIR) and Short Waves Infrared (SWIR) spectroscopy has been indicated as a promising tool in soil studies, especially in the last decade. However, in order to apply this method, it is necessary to develop prediction models with the capacity to capture the intrinsic differences between agricultural areas and incorporate them in the modeling process. High quality estimates are generally obtained when these models are applied to soil samples displaying characteristics similar to the samples used in their construction. However, low quality predictions are noted when applied to samples from new areas presenting different characteristics. One way to solve this problem is by recalibrating the models using selected samples from the area of interest. Based on this premise, the aim of this study was to use the spiking technique and spiking associated with hybridization to expand prediction models and estimate organic matter content in a target area undergoing different uses and management. A total of 425 soil samples were used for the generation of the state model, as well as 200 samples from a target area to select the subsets (10 samples) used for model recalibration. The spectral readings of the samples were obtained in the laboratory using the ASD FieldSpec 3 Jr. Sensor from 350 to 2500 nm. The spectral curves of the samples were then associated to the soil attributes by means of a partial least squares regression (PLSR). The state model obtained better results when recalibrated with samples selected through a cluster analysis. The use of hybrid spectral curves did not generate significant improvements, presenting estimates, in most cases, lower than the state model applied without recalibration. The use of the isolated spiking technique was more effective in comparison with the spiked and hybridized state models, reaching r2, square root of mean prediction error (RMSEP) and ratio of performance to deviation (RPD) values of 0.43, 4.4 g dm−3, and 1.36, respectively.

Este projeto de pesquisa trata sobre “Tráfico Humano” o qual compreende o tráfico de pessoas como transferência, alojamento ou acolhimento de pessoas, recorrendo ameaça ou ao uso de forças ou outras formas de coação, o rapto, a fraude, o engano e o abuso de autoridade ou a situação de vulnerabilidade da entrega ou aceitação de pagamentos ou benefícios para obter consentimento de uma pessoa ou autoridade sobre outra para fins de exploração. O projeto justifica-se pelo fato de que este tema está frequente na nossa sociedade e muitas pessoas estão vivendo esta realidade vergonhosa, a qual destrói a vida do ser humano e os mesmos perdem a capacidade de viver dignamente. Com este trabalho pretende-se identificar as práticas de tráfico humano em suas formas e alertar sobre a importância da denúncia a fim de evitar a violação da dignidade e da liberdade humana, mobilizando a sociedade para erradicar esse mal, com vista ao resgate da vida das pessoas. Cabe salientar, que este trabalho traz a abordagem de vários segmentos, entre eles: “Prostituição” é a denominação vulgar para designar uma série de práticas sexuais onde há o desvirtuamento de alguns pressupostos necessários para a sua ocorrência, tais como a falta de consentimento, ou uso da violência, física ou moral. “Trabalho escravo” são elementos que caracterizam o trabalho análogo ao de escravo: condições degradantes de trabalho, jornada exaustiva, trabalho forçado. Os elementos podem vir juntos ou isoladamente. “Tráfico de órgãos” entende-se que é a prática ilegal de comércio de órgãos (coração, fígado, rins, etc.) para o transplante de órgãos. “Tráfico de crianças” é uma das formas de tráfico humano, constitui uma prática de sequestro, desaparecimento e ocultação da identidade das crianças, muitas vezes através de partos clandestinos e “adoções ilegais”. A partir do desenvolvimento do mesmo, evidencia-se que este problema está presente nas nossas vidas e que muitos não percebem que estão enfrentando essa situação, talvez em uma proporção menor, porque não tinham esses fatos esclarecidos em suas mentes. Em resumo, “tráfico humano” é qualquer atitude que fere a dignidade humana, portanto, devemos nos prevenir contra esse mal, dando prioridade ao estudo e a leitura, com isso, fortalecerá nossa leitura de mundo, a fim de que não sejamos presas fáceis.

Resumo A implementação de atividades práticas que envolvam cores constitui uma estratégia poderosa para estimular o interesse de crianças e adolescentes para a Ciência. Devido ao seu forte apelo visual e presença no cotidiano, as cores despertam a curiosidade dos estudantes e propiciam o aprendizado de conceitos fundamentais no campo da óptica, tais como reflexão, transmissão e refração. Nesse trabalho, descrevemos um programa de atividades desenvolvido para ensinar conceitos de óptica presentes na formação de cores a partir de materiais simples, baratos e acessíveis. Através de demonstrações abertas e discussões autônomas por parte dos estudantes, elucidamos o processo de formação de cores por reflexão e transmissão, bem como a razão pela qual se pode visualizar objetos incolores. As atividades aqui descritas foram apresentadas num evento de divulgação científica direcionado a crianças e adolescentes com idade entre 8 e 17 anos.