This work developed an effective and eco-friendly analytical method to support quality control for Brazilian Bill proposal No. 5332/2009. The bill advocates the creation of the “Brazilian bread” by mandating the incorporation of cassava byproducts into wheat flour, with the aim of reducing Brazil’s external dependency on wheat imports and promoting domestic cassava family farming. For this, a handheld near-infrared (NIR) spectrophotometer was utilized for on-site determination of cassava starch in commercial wheat flour. The quantitative analysis, which utilized NIR spectra pre-processed with offset correction (OFF) combined with linear baseline correction (LBC), alongside the successive projections algorithm for interval selection in partial least squares (iSPA-PLS), exhibited superior predictive capability, achieving a relative error of prediction below 8%. Furthermore, the classification process, which involved NIR spectra pre-processed with LBC and iSPA-PLS for discriminant analysis (iSPA-PLS-DA), yielded an impressive 94% overall accuracy, with only 3 misclassifications in the test set. ecofriendly eco friendly No 53322009 5332 2009 5332/2009 bread flour Brazils Brazil s farming this nearinfrared near infrared (NIR onsite site preprocessed pre processed OFF (OFF LBC, , (LBC) iSPAPLS, iSPAPLS iSPA PLS (iSPA-PLS) capability 8 8% Furthermore process iSPAPLSDA, iSPAPLSDA DA (iSPA-PLS-DA) 94 accuracy set 5332200 533 200 5332/200 (LBC (iSPA-PLS (iSPA-PLS-DA 9 533220 53 20 5332/20 53322 5 2 5332/2 5332/

The use of materials such as organofunctionalized silica for application in solid phase extraction (SPE) allows the preconcentration of several ions, including Pt, and subsequent detection. This work aims to synthesize and characterize an organofunctionalized silica (Sil-TMSDT) with the silylant N’(trimethoxysilyl)propylethylenetriamine and its application as a solid phase in the preconcentration Pt4+ ions in aqueous media, using detection by flame atomization atomic absorption spectroscopy (FAAS). The Fourier-transform infrared spectroscopy (FTIR) spectra and scanning electron microscopy (SEM) coupled with energy-dispersive spectroscopy (EDS) confirmed the aminofunctionalization of the silica. For the adsorption process, a preconcentration mini-column with 200 mg of Sil-TMSDT, a solution of 0.485 mg L−1 of K2[PtCl6] at pH 10 and HNO3 0.5 mol L−1 as eluent were used, obtaining an enrichment factor of 15-fold with retention efficiency higher than 99%. The Pt4+ ion determined by FAAS showed a linear response between 0.02 and 0.40 mg L−1; a linear coefficient where R = 0.9981; a 16-fold preconcentration factor; a limit of quantification (LOQ) and limit of detection (LOD) of 0.045 and 0.014 mg L−1, respectively. The proposal system showed analytical applicability to determining Pt4+ ion in an aqueous medium and could be used to detect traces of this potentially toxic metal in biological fluids such as urine and blood. SPE (SPE Pt SilTMSDT Sil TMSDT (Sil-TMSDT Ntrimethoxysilylpropylethylenetriamine N trimethoxysilyl propylethylenetriamine Pt4 media FAAS. . (FAAS) Fouriertransform Fourier transform FTIR (FTIR SEM (SEM energydispersive energy dispersive EDS (EDS process minicolumn mini column 20 SilTMSDT, TMSDT, Sil-TMSDT 0485 0 485 0.48 L1 L 1 L− K2PtCl6 KPtCl K2 PtCl6 K PtCl K2[PtCl6 HNO 05 5 0. 15fold fold 15 99 99% 002 02 0.0 040 40 0.4 0.9981 09981 9981 16fold 16 LOQ (LOQ LOD (LOD 0045 045 0.04 0014 014 0.01 respectively blood (FAAS 2 048 48 K2PtCl K2[PtCl 9 00 04 4 0.998 0998 998 004 001 01 0.99 099 0.9 09

RESUMEN Esta investigación analizó la respuesta espectral foliar de tres especies forestales maderables nativas del bosque seco tropical, Diomate (Astronium graveolens Jacq.), Choibá (Dipteryx oleifera Benth.) y Algarrobo (Hymenaea courbaril L.). El estudio se efectuó en el Arboretum y Palmetum León Morales Soto de la Universidad Nacional de Colombia, sede Medellín, Antioquia, Colombia. Los datos espectrales de las hojas se colectaron in situ con el espectrorradiómetro portátil ASD FieldSpec HandHeld-2, que trabaja con una resolución espectral de 1 nm (remuestreada a 10 nm) y un rango espectral entre 325 y 1.075 nm (acotado entre 400 y 900 nm). A partir de las mediciones, se evaluó el comportamiento y la variabilidad espectral de las especies. Se implementó el Análisis de Varianza de un factor y la prueba U de Mann - Whitney - Wilcoxon en los espectros de reflectancia con el fin de seleccionar las bandas estrechas óptimas para discriminar las especies. Se evaluó la capacidad de clasificación de las especies en las bandas estrechas seleccionadas, utilizando el algoritmo de los K vecinos más cercanos. Encontrando que A. graveolens e H. courbaril presentaron firmas espectrales típicas de la vegetación saludable y D. oleifera evidenció cambios espectrales en el período inicial de la senescencia. Respecto a la separabilidad espectral, se encontraron 23 bandas estrechas en la región visible e infrarrojo cercano óptimas para diferenciar las especies vegetales. El algoritmo de clasificación supervisada aplicado en las 23 bandas estrechas, tuvo una precisión general del 95,8%. En conclusión, estos hallazgos proporcionan valiosos conocimientos sobre la respuesta espectral de importantes especies tropicales y contribuyen a sus esfuerzos de conservación al mejorar la comprensión de sus características espectrales únicas en ecosistemas diversos y heterogéneos como el bosque tropical.

ABSTRACT This study analyzed the leaf spectral response of three native timber forest species in the tropical dry forest: Diomate (Astronium graveolens Jacq.), Choibá (Dipteryx oleifera Benth.), and Algarrobo (Hymenaea courbaril L.). The study was conducted at the León Morales Soto Arboretum and Palmetum, at the Universidad Nacional de Colombia in Medellín, Antioquia, Colombia. Spectral data from the leaves were collected in situ using the portable spectroradiometer ASD FieldSpec HandHeld-2, which operates with a spectral resolution of 1 nm (resampled to 10 nm) and covers a spectral range between 325 and 1,075 nm (limited to 400-900 nm). Based on the measurements, the behavior and spectral variability of the species were evaluated. One-factor Analysis of Variance and Mann-Whitney-Wilcoxon U-test were implemented in reflectance spectra to select the optimal narrow bands for species discrimination. The classification capacity of the selected narrow bands was assessed using the K-nearest neighbors' algorithm. It was found that A. graveolens and H. courbaril exhibited spectral signatures typical of healthy vegetation, while D. oleifera showed spectral changes during the early stages of senescence. Regarding spectral separability, 23 narrow bands in the visible region and near-infrared region were identified as optimal for distinguishing the plant species. The supervised classification algorithm applied to these 23 narrow bands achieved an overall accuracy of 95.8%. In conclusion, these findings provide valuable insights into the spectral response of important tropical species and contribute to their conservation efforts by enhancing understanding of their unique spectral characteristics in diverse and heterogeneous ecosystems like tropical forests.

ABSTRACT The aim of this study was to develop visible and near-infrared spectroscopy (Vis-NIRS) calibration models for predicting the content of organic carbon (OC), total nitrogen (N), clay + silt, and pH values in soils from Argentina, employing different mathematical preprocessing techniques for spectral data. A total of 154 soil samples with contrasting physicochemical characteristics was selected, dried, and sieved to 2 mm prior to the analysis of OC, N, pH, and clay + silt using reference methods. Subsequently, the Vis-NIR spectrum (400 to 2500 nm) of each sample was obtained in reflectance mode. The sample set was randomly divided into two groups: one for calibration model development (80%) and the other for model validation (20%). Eight preprocessing techniques for spectral information were employed, and the best one for each parameter studied was selected based on the criteria of achieving the minimum standard error of cross-validation (EECV), maximum coefficient of determination of cross-validation (R2cv), and maximum residual predictive deviation (RPD). Calibration models were obtained using modified partial least squares regression (MPLS) and five-fold cross-validation. The best models for predicting OC and N were obtained with the raw spectra (RPD=4.69 and 3.65 respectively); for pH, the best model was obtained using the standard normal variate preprocessing technique with the second derivative (RPD=2.27), and for clay + silt, the best model was obtained with multiple scattering correction and second derivative (RPD=2.83). The performance of the models applied to the calibration and testing groups was similar. The results indicate that the appropriate choice of spectral data preprocessing technique can optimize calibration for the prediction. Vis-NIRS is a valuable tool for soil monitoring in Argentina, complementing traditional analysis methods.

RESUMEN El objetivo de este estudio fue desarrollar modelos de calibración por espectroscopía visible e infrarrojo cercano (Vis-NIRS) para la predicción del contenido de carbono orgánico (CO), nitrógeno total (N), arcilla+li-mo, y pH en suelos de Argentina, aplicando diferentes técnicas de pretratamiento matemático de los datos espectrales. Se seleccionaron 154 muestras de suelo con características físico químicas contrastantes, se secaron y tamizaron a 2 mm previo al análisis de CO, N, pH y arcilla+limo mediante métodos de referencia. Luego se obtuvo el espectro Vis-NIR (400 a 2500 nm) de cada muestra en modo reflectancia. El conjunto de muestras fue dividido aleatoriamente en dos grupos: uno para obtener el modelo de calibración (80 %) y el otro para la validación del modelo (20 %). Se utilizaron ocho técnicas de pretratamiento de la información espectral y luego se seleccionó la mejor para cada parámetro, con el criterio de obtener el mínimo error estándar de la validación cruzada (EEVC), máximo coeficiente de determinación de la validación cruzada (R2cv) y máxima desviación predictiva residual (RPD). Los modelos de calibración se obtuvieron utilizando regresión de cuadrados mínimos parciales modificada (MPLS) y validación cruzada con cinco etapas. Los mejores modelos para la predicción de CO y N se obtuvieron con los espectros sin procesar (RPD=4,69 y 3,65 respectivamente); para pH se obtuvo con la técnica variación normal estándar con segunda derivada (RPD=2,27) y para arcilla+limo con corrección de dispersión múltiple y segunda derivada (RPD=2,83). El desempeño de los modelos aplicados sobre el grupo de testeo y calibración fue similar. Los resultados indican que la elección apropiada de la técnica de pretratamiento de datos espectrales puede optimizar la calibración. Vis-NIRS es una herramienta valiosa para el monitoreo de suelos en Argentina, como comple-mento de los métodos tradicionales de análisis.

Abstract Maize (Zea mays L.) is of socioeconomic importance as an essential food for human and animal nutrition. However, cereals are susceptible to attack by mycotoxin-producing fungi, which can damage health. The methods most commonly used to detect and quantify mycotoxins are expensive and time-consuming. Therefore, alternative non-destructive methods are required urgently. The present study aimed to use near-infrared spectroscopy with hyperspectral imaging (NIR-HSI) and multivariate image analysis to develop a rapid and accurate method for quantifying fumonisins in whole grains of six naturally contaminated maize cultivars. Fifty-eight samples, each containing 40 grains, were subjected to NIR-HSI. These were subsequently divided into calibration (38 samples) and prediction sets (20 samples) based on the multispectral data obtained. The averaged spectra were subjected to various pre-processing techniques (standard normal variate (SNV), first derivative, or second derivative). The most effective pre-treatment performed on the spectra was SNV. Partial least squares (PLS) models were developed to quantify the fumonisin content. The final model presented a correlation coefficient (R2) of 0.98 and root mean square error of calibration (RMSEC) of 508 µg.kg-1 for the calibration set, an R2 of 0.95 and root mean square error of prediction (RMSEP) of 508 µg.kg-1 for the test validation set and a ratio of performance to deviation of 4.7. It was concluded that NIR-HSI with partial least square regression is a rapid, effective, and non-destructive method to determine the fumonisin content in whole maize grains. Zea L. L nutrition However mycotoxinproducing mycotoxin producing fungi health timeconsuming. timeconsuming time consuming. consuming time-consuming Therefore nondestructive non destructive urgently nearinfrared near infrared NIRHSI NIR HSI (NIR-HSI cultivars Fiftyeight Fifty eight samples 4 NIRHSI. HSI. 38 (3 20 (2 obtained preprocessing pre processing standard SNV, SNV , (SNV) derivative derivative. . derivative) pretreatment treatment PLS (PLS R (R2 098 0 98 0.9 RMSEC (RMSEC 50 µg.kg1 µgkg1 µgkg µg.kg 1 µg kg µg.kg- 095 95 RMSEP (RMSEP 47 7 4.7 3 ( 2 (SNV (R 09 9 0. 5 kg1 4.

Resumo O milho (Zea mays L.) possui importância socioeconômica por constituir um dos alimentos básicos na nutrição humana e animal. Porém, o cereal é suscetível ao ataque de fungos produtores de micotoxinas que podem causar danos à saúde. Os métodos mais utilizados para detectar e quantificar micotoxinas são caros e demorados e métodos alternativos para a detecção das micotoxinas são uma necessidade. O presente trabalho tem como objetivo utilizar espectroscopia no infravermelho próximo com imagem hiperespectral (NIR-HSI) e análise multivariada de imagens para desenvolver um método rápido e preciso para quantificação de fumonisinas em grãos inteiros de seis cultivares de milho naturalmente contaminadas. Cinquenta e oito amostras, cada uma contendo 40 grãos, foram submetidas ao NIR-HSI e posteriormente divididas em um conjunto de calibração (38 amostras) e um conjunto de predição (20 amostras) com base nos dados multiespectrais obtidos. Os espectros médios foram submetidos a diversas técnicas de pré-processamento (variação normal padrão – SNV, primeira derivada ou segunda derivada). O melhor pré-processamento dos espectros foi SNV e um modelo de mínimos quadrados parciais (PLS) foi desenvolvido para quantificar o teor de fumonisinas. O modelo final apresentou coeficiente de correlação (R2) de 0,98 e raiz quadrada do erro médio quadrático de calibração (RMSEC) de 508 µg.kg-1 para o conjunto de calibração, R2 de 0,95 e raiz quadrada do erro médio quadrático de predição (RMSEP) de 508 µg.kg-1 para o conjunto de validação do teste e relação desempenho/desvio de 4,7. Conclui-se que o NIR-HSI com regressão parcial de mínimos quadrados pode ser um método rápido, eficaz e não destrutivo para determinar o teor de fumonisinas em grãos integrais de milho. Zea L. L animal Porém saúde necessidade NIRHSI NIR HSI (NIR-HSI contaminadas amostras 4 38 (3 20 (2 obtidos préprocessamento pré processamento variação derivada. . derivada) PLS (PLS R (R2 098 0 98 0,9 RMSEC (RMSEC 50 µg.kg1 µgkg1 µgkg µg.kg 1 µg kg µg.kg- 095 95 RMSEP (RMSEP desempenhodesvio desempenho desvio 47 7 4,7 Concluise Conclui se 3 ( 2 (R 09 9 0, 5 kg1 4,

This is an initial study using infrared (IR) in silico data as a standard database in preliminary method for new synthetic seized drugs. For this purpose, ten of the most common synthetic illicit seized substances on the Brazilian market were compared and computational chemistry was used as a tool for theoretical standard database. Infrared data from standard electronic library, experimental data from seized samples and data simulated by Density Functional Theory (DFT) were evaluated. The feasibility of the method was based on the degree of correlation of evaluated data. The results suggest that the computational methodology can be a viable way to analyze the structures of new synthetic drugs and obtain preliminary infrared profiles. Correlations data indicated a presumptive identification of the analyzed samples and it was also possible to observe a preliminary identification of drugs in five classes. However, it was observed that some synthetic cathinones and phenylethylamines were confused with amphetamines. Therefore, new studies must be developed to optimize the use of these data, because the simulated IR spectra can be advantageous to evaluate the profile of possible substances that may be synthesized in the future. (IR purpose library DFT (DFT profiles classes However amphetamines Therefore future

ABSTRACT This work aimed at investigating the viability of near infrared spectrometry (NIR), associated with chemometric methods, in order to identify differences at the levels of vigor of naturally and artificially aged soybean seeds. Seeds of six soybean genotypes were analyzed when freshly harvested, after natural aging in storage for eight months, and after artificial aging at the temperature of 41 °C for 96 hours. The seed moisture content, germination potential and vigor were evaluated. Also, there were measured the content of protein, oil and of the fatty acids: palmitic, stearic, oleic, linoleic and linolenic. The NIR spectra were obtained from the freeze-dried and grinded seeds. The natural and artificial aging of the seeds promote deterioration at distinct levels, reflecting in differences in seed vigor. The regions of the electromagnetic spectrum between wavelengths of 1000-1200 nm, 1350-1450 nm, 1800-1900 nm and 2300-2400 nm are important to distinguish the levels of quality of the soybean seeds. The contents of oil and protein have a relationship with the physiological quality of the seeds. Also, the most relevant wavelengths for the classification of seed vigor present a relationship with these compounds. NIR spectroscopy, in combination with chemometric methods, presents potential to be used in the classification of soybean seeds regarding their physiological quality. NIR, , (NIR) methods harvested months 4 C 9 hours evaluated Also acids palmitic stearic oleic linolenic freezedried freeze dried 10001200 1000 1200 1000-120 13501450 1350 1450 1350-145 18001900 1800 1900 1800-190 23002400 2300 2400 2300-240 compounds spectroscopy (NIR 1000120 100 120 1000-12 1350145 135 145 1350-14 1800190 180 190 1800-19 2300240 230 240 2300-24 100012 10 12 1000-1 135014 13 14 1350-1 180019 18 19 1800-1 230024 23 24 2300-2 10001 1 1000- 13501 1350- 18001 1800- 23002 2 2300-

Abstract Bio-high density polyethylene (BHDPE) films with organoclay and antimicrobial additives (zinc pyrithione) were evaluated. The composites were prepared in a single-screw extruder using the melt intercalation technique, and the films were obtained by flat extrusion. The diffractograms indicated the formation of an intercalated nanocomposite (BHDPE/6 wt% of clay). Infrared spectra suggested that the polymer predominates over the antimicrobial agent bands. Thermal stability was slightly reduced by up to 3°C. The clay and antimicrobial agent reduced the melting point and crystallinity of BHDPE by up to 12 °C and 13.3%, respectively. In addition, the presence of clay and antimicrobial agent significantly (p < 0.05) affected all mechanical properties. Proliferation of Staphylococcus aureus demonstrated that both evaluated additives did not significantly (p > 0.05) inhibit microbial growth. The results emphasize a promising application of the films for packaging that does not require antimicrobial control, with films highlighted by 6 wt% of clay. Biohigh Bio high (BHDPE zinc pyrithione singlescrew single screw technique extrusion BHDPE/6 BHDPE6 (BHDPE/ wt . clay) bands 3C C 3 3°C 1 133 13 13.3% respectively addition p 0.05 005 0 05 properties growth control BHDPE/ 13.3 0.0 00 13. 0.

ABSTRACT Hybrid materials formed between polyaniline and layered double hydroxides of Zn and Al (Pani/ZnAlHDL) were obtained by adding previously prepared polyaniline (Pani) to the reaction medium during the synthesis of the HDLs, including HDLs modified with the anionic surfactants sodium dodecyl sulfate and sodium dodecylbenzenesulfonate. The composites exhibited a blue color characteristic of the emeraldine base phase of Pani. X-ray diffraction (XRD) patterns of these compounds showed a shift of the peaks (003) and (006) of ZnAlHDL to lower 2θ values, indicating the presence of both phases in the composites. Additionally, it was observed that the anionic surfactants also influence the structural characteristics of the composites. Fourier-transform infrared (FTIR) spectra support the XRD results. Composites obtained with surfactants were subjected to colorimetric sensor tests for HCl. After only 5 minutes of exposure to HCl vapors, the materials changed their color from blue to green, indicating the formation of the Pani emeraldine salt phase. This indication was confirmed by UV-Vis spectroscopy, as spectra after acid interaction showed new bands in the 400 nm and 820 nm regions, characteristic of the emeraldine salt, the green-colored structural form of Pani. These results demonstrate the feasibility of using these materials in acid sensing, providing a rapid and effective response. Pani/ZnAlHDL PaniZnAlHDL (Pani/ZnAlHDL (Pani dodecylbenzenesulfonate Xray X ray (XRD 003 (003 006 (006 θ values Additionally Fouriertransform Fourier transform FTIR (FTIR vapors green UVVis UV Vis spectroscopy 40 82 regions greencolored colored sensing response 00 (00 4 8 0 (0 (

RESUMO Materiais híbridos formados entre polianilina e hidróxidos duplos lamelares de Zn e Al (Pani/ZnAlHDL) foram obtidos adicionando a Polianilina (Pani) previamente preparada ao meio reacional da síntese dos HDLs e também HDLs modificado com os surfactantes aniônicos dodecilsulfato de sódio e dodecilbenzenosulfato de sódio. Os compósitos apresentaram cor azul que é característica da fase base esmeraldina da Pani. Os difratogramas de raios X destes compostos apresentaram deslocamento dos picos (003) e (006) do ZnAlHDL para menores valores de 2θ, indicando a presença das duas fases nos compósitos. Além disso, foi constatado também que os surfactantes aniônicos também exercem influência nas características estruturais dos compósitos. Os espectros de FTIR corroboram os resultados do DRX. Os compósitos obtidos com os surfactantes foram submetidos à testes de sensor colorimétrico para HCl. Após 5 minutos apenas de exposição aos vapores do HCl, os materiais apresentaram mudança na sua coloração de azul para verde, indicando a formação da fase da Pani, sal esmeraldina. Esse indício foi confirmado por espectroscopia na região do UV-Vis, uma vez que os espectros após interação com ácido, apresentaram novas bandas, nas regiões de 400 nm e 820 nm, que são características do sal esmeraldina, forma estrutural da Pani de coloração verde. Esses resultados mostram a viabilidade da utilização destes materiais no sensoriamento de ambientes ácidos, apresentando resposta rápida e eficaz. Pani/ZnAlHDL PaniZnAlHDL (Pani/ZnAlHDL (Pani 003 (003 006 (006 2θ θ disso DRX HCl verde UVVis, UVVis UV Vis, Vis UV-Vis ácido bandas 40 82 ácidos eficaz 00 (00 4 8 0 (0 (

ABSTRACT: Near-infrared (NIR) spectroscopy is a promising tool for optimizing seed analyses quickly and assertively. The aim of this study was to investigate the viability of NIR in association with chemometric methods in classification of soybean seed lots regarding their physiological potential. We evaluated 372 soybean seed lots for vigor and obtained NIR spectra from seed samples. The original spectra were pre-processed by the following methods: Standard Normal Variate (SNV), SNV + 1st and 2nd derivatives, Gap-segment derivative, and Savitzky-Golay for the first- and second-degree derivatives, as well as combinations of the methods. The lots were divided into Class I (≥ 85% germination after accelerated aging) and Class II (< 85% germination after accelerated aging); and the pre-processed spectra were used to build classification models through the following methods: K-nearest neighbors (KNN), Partial Least Squares - Discriminant Analysis (PLS-DA), Naive Bayes (NB), Random Forest (RF), and Support Vector Machine (SVM). The PLS-DA model showed greater classification accuracy and kappa, followed by SVM. The lowest accuracy values were obtained for the NB and RF models. The regions between the wavelengths 1,000-1,200 nm and 2,200-2,500 nm were the most important for distinguishing the quality levels of soybean seeds. ABSTRACT Nearinfrared Near infrared (NIR assertively potential 37 samples preprocessed pre processed SNV, , (SNV) st nd derivatives Gapsegment Gap segment derivative SavitzkyGolay Savitzky Golay first seconddegree second degree ≥ ( 85 aging < Knearest K nearest KNN, KNN (KNN) PLSDA, PLSDA PLS DA (PLS-DA) NB, (NB) RF, (RF) SVM . (SVM) kappa 1,0001,200 10001200 1,000 1,200 1 000 200 1,000-1,20 2,2002,500 22002500 2,200 2,500 2 500 2,200-2,50 seeds 3 (SNV 8 (KNN (PLS-DA (NB (RF (SVM 0001 1,0001,20 1000120 1000 1,00 1200 1,20 00 20 1,000-1,2 2002 2,2002,50 2200250 2200 2,20 2500 2,50 50 2,200-2,5 1,0001,2 100012 100 1,0 120 1,2 0 1,000-1, 2,2002,5 220025 220 2,2 250 2,5 5 2,200-2, 1,0001, 10001 10 1, 12 1,000-1 2,2002, 22002 22 2, 25 2,200-2 1,0001 1,000- 2,2002 2,200-

RESUMO: A espectroscopia no infravermelho próximo (NIR) consiste em uma ferramenta promissora para otimização das análises de sementes de forma rápida e assertiva. Este trabalho teve como objetivo investigar a viabilidade do NIR, associado a métodos quimiométricos, para classificar lotes de sementes de soja quanto ao potencial fisiológico. Foram utilizados 372 lotes de sementes de soja avaliados quanto ao vigor e obtidos espectros NIR das amostras de sementes. Os espectros originais foram submetidos aos métodos de pré-processamento Standard Normal Variate (SNV), SNV + 1ª e 2ª derivadas; Gap-segment derivative; e Savitzky-Golay, pelas derivadas de primeiro e segundo grau, e a combinação entre os métodos. Os lotes foram divididos em Classe I (≥ 85% de germinação após envelhecimento acelerado), Classe II (< 85% de germinação após envelhecimento acelerado) e os espectros pré-processados foram utilizados para a construção de modelos de classificação por meio dos métodos K-nearest neighbors (KNN), Partial Least Squares - Discriminant Analysis (PLS-DA), Naive Bayes (NB), Random Forest (RF) e Support Vector Machine (SVM). O modelo de classificação PLS-DA apresentou maior acurácia e kappa, seguido pelo SVM. Os menores valores de acurácia foram obtidos para os modelos NB e RF. As regiões entre os comprimentos de ondas 1.000-1.200 nm e 2.200-2.500 nm foram as mais importantes para distinguir os níveis de qualidade das sementes de soja. RESUMO (NIR assertiva quimiométricos fisiológico 37 préprocessamento pré processamento SNV, , (SNV) ª Gapsegment Gap segment derivative SavitzkyGolay, SavitzkyGolay Savitzky Golay, Golay Savitzky-Golay grau ≥ ( 85 acelerado, acelerado < préprocessados processados Knearest K nearest KNN, KNN (KNN) PLSDA, PLSDA PLS DA (PLS-DA) NB, (NB) RF (RF SVM . (SVM) kappa 1.0001.200 10001200 1.000 1.200 1 000 200 1.000-1.20 2.2002.500 22002500 2.200 2.500 2 500 2.200-2.50 3 (SNV 8 (KNN (PLS-DA (NB (SVM 0001 1.0001.20 1000120 1000 1.00 1200 1.20 00 20 1.000-1.2 2002 2.2002.50 2200250 2200 2.20 2500 2.50 50 2.200-2.5 1.0001.2 100012 100 1.0 120 1.2 0 1.000-1. 2.2002.5 220025 220 2.2 250 2.5 5 2.200-2. 1.0001. 10001 10 1. 12 1.000-1 2.2002. 22002 22 2. 25 2.200-2 1.0001 1.000- 2.2002 2.200-

ABSTRACT Background: The determination of seed moisture content is of utmost importance for the evaluation of its quality. Near-infrared (NIR) spectroscopy has been successfully applied to estimate properties of biological materials. However, studies using this technique on forest seeds are still scarce. Thus, the aim of this study was to explore the potential of NIR spectroscopy for estimating the moisture content of E. uniflora seeds. NIR spectra were obtained using optical fiber from 100 individual seeds that were dehydrated in silica gel for 2, 7, 14, and 21 days. Subsequently, the seeds were subjected to the moisture test by the oven method, and had moisture contents of 52.4%, 41.7%, 33.1%, 21.8%, and 18.1%, respectively. Results: Principal component analysis (PCA) of the spectral signatures explained 100% of the data variability. The moisture content was associated with the spectra by partial least squares regression (PLS-R) and the predictive model presented a coefficient of determination in cross-validation (R²cv) of 0.88 and the root mean square error of cross-validation (RMSEcv) was 5.43%. Conclusion: The statistics associated with the models indicate that NIR spectroscopy has potential for estimating the moisture content of E. uniflora seeds. Background quality Nearinfrared Near infrared (NIR materials However scarce Thus E 10 2 7 14 days Subsequently method 524 52 4 52.4% 417 41 41.7% 331 33 1 33.1% 218 8 21.8% 181 18 18.1% respectively Results PCA (PCA variability PLSR PLS R (PLS-R crossvalidation cross validation R²cv Rcv cv (R²cv 088 0 88 0.8 RMSEcv (RMSEcv 543 5 43 5.43% Conclusion 52.4 41.7 3 33.1 21.8 18.1 08 0. 54 5.43 52. 41. 33. 21. 18. 5.4 5.

ABSTRACT Agriculture intensification in Southern Brazil’s subtropical regions combined with the frequent occurrence of erosive rainfall has rendered the area a global water erosion hotspot. In this scenario, understanding and regulating erosion processes at the river catchment scale is critical for mitigating soil and water resource degradation. Traditional methods for tracing sediment sources are expensive and time-consuming and justify the development of alternative approaches. Therefore, in this study, we employed diffuse reflectance spectroscopy analyses in the ultraviolet-visible (UV-VIS), near-infrared (NIR), and mid-infrared (MIR) ranges, combined with multivariate models and spectral pre-processing techniques to estimate sediment source contributions in a homogeneous subtropical catchment (Conceição River, 804 km²). Soil samples (n = 181) were collected to characterize the four potential sediment sources, including: cropland (n = 78), stream bank (n = 36), unpaved road (n = 40) and pasture (n = 27). Moreover, 44 sediment samples were collected, including suspended sediment (n = 8), fine sediment deposited on the riverbed (n = 15), and suspended sediment samples collected in the water column during storm events (n = 21). Vector machine (SVM) model outperformed the others, with better accuracy and reliability. While UV-VIS spectra proved less effective due to soil homogeneity across the catchment, NIR and MIR spectra provided valuable information for discriminating sediment sources. Furthermore, reducing the number of potential sources (from four to three or two) improved model predictions, especially when distinguishing between surface sources (cropland and pasture) and subsurface sources (unpaved roads and stream banks). The study’s findings shed light on the power of efficient and cost-effective alternative methods for assessing sediment sources, which are vital for promoting effective erosion control and sustainable land management in similar regions. Brazils Brazil s hotspot scenario degradation timeconsuming time consuming approaches Therefore study ultravioletvisible ultraviolet visible UVVIS, UVVIS UV VIS , (UV-VIS) nearinfrared near infrared NIR, (NIR) midinfrared mid (MIR ranges preprocessing pre processing Conceição River 80 km². km² km . km²) n 181 78, 78 78) 36, 36 36) 40 27. 27 27) Moreover 4 8, 8 8) 15, 15 15) 21. 21 21) SVM (SVM others reliability Furthermore from two predictions banks. banks banks) studys costeffective cost (UV-VIS (NIR 18 7 3 2 1

We report a quantum chemical study of cryptolepine, an alkaloid that is of considerable pharmacological interest. We focus on solvent effects, spectroscopic properties and on chemical reactivity descriptors, such as electronegativity, hardness, and electrophilicity. On the density functional level, gas phase ¹H and 13C nuclear magnetic resonance chemical shifts and infrared spectra agree well with experiments, although the dipole moment increases significantly with an increasing polarity of the solvent. We characterize normal modes using a potential energy distribution scheme. In the gas phase and in solution, the UV-Vis spectra are computed using time-dependent density functional theory. Here, major discrepancies between experiment and theory can only be observed in the visible range.

Summary: A retrospective-prospective research was carried out to establish a soil quality index (SQI) of Los Rios region (RR), Tabasco, Mexico, and its modeling with the near infrared technology (NIR) and chemometrics. The SQI was determined with the OM / (clay + silt) relationship to evaluate the Cambisol soils of RR. The OM percentage and the SQI were compared to define the best soil quality qualifier. Based on the SQI, 58% of the soils in RR exhibit degradation, while only 14% indicates a low concentration of OM. Therefore, we conclude that the SQI is more sensitive to quantify soil degradation compared to the evaluation based on OM. A sustainable soil management program and soil practices adapted to local environmental, social and economic conditions are recommended to increase OM and improve SQI. With the SQI, a classification model was established using near-infrared spectroscopy and chemometrics. The spectra of each soil sample were recorded and through chemometric interpretation, it was shown that it is possible to conduct a partial least squares discriminant analysis model (PLS-DA) to predict the SQI. The model meets all statistical qualifiers and correctly predicts the SQI in 100% of cases. We conclude that the NIR technology provides sufficient information to predict the SQI with the advantage of eliminating the consumption of reagents, no laboratory waste is generated, the analysis time is reduced to minutes, and the sample under study is not destroyed. In addition, the procedure is simple as it consists of drying, grinding and sieving the soil samples to assess the structural quality of the soil.

Resumen: Se realizó una investigación retrospectiva - prospectiva, para establecer un índice de calidad de los suelos (ICS) de la región de los Ríos (RR) en Tabasco, México y su modelación con la tecnología de infrarrojo cercano (NIR) y la quimiometría. Con la relación MO / (arcilla + limo) se estableció el ICS para evaluar los suelos Cambisoles de la RR. El porcentaje de MO y el ICS fueron comparados para definir el mejor calificador de la calidad de los suelos. Con base en el ICS, el 58% de los suelos de la RR presentan degradación, mientras que, solo el 14% de los suelos indican que presentan baja concentración de MO. Por lo que se concluye que el ICS es más sensible para cuantificar la degradación de los suelos cuando se comparó con la evaluación basada en la MO. Se recomienda un programa de manejo sostenible del suelo y prácticas edafológicas adaptadas a las condiciones locales, ambientales, sociales y económicas, para incrementar la MO y mejorar el ICS. Con el ICS se estableció un modelo de clasificación mediante espectroscopía de infrarrojo cercano y quimiometría. Se registraron los espectros de cada muestra de suelo y mediante interpretación quimiométrica se demostró que es posible establecer un modelo de análisis discriminante por mínimos cuadrados parciales (PLS-DA) para predecir el ICS. El modelo cumple con todos los calificadores estadísticos y predice correctamente el ICS en el 100% de los casos. Se concluye que la tecnología NIR genera información suficiente para predecir el ICS; con la ventaja de, eliminar el consumo de reactivos, no se generan residuos de laboratorio, se reduce el tiempo de análisis a minutos y no se destruye la muestra en estudio. Y solo se necesita secar, moler y tamizar las muestras de suelos para evaluar la calidad estructural de suelos.

Parkinson’s disease is a neurodegenerative disorder characterized by progressive loss of dopaminergic neurons. There is substantial evidence that the endocannabinoid system modulates the dopaminergic activity in the basal ganglia, a forebrain system that integrates cortical information to coordinate motor activity regulating signals. In this article, a fused-silica capillary with a molecularly imprinted polymer was developed for in-tube solid-phase microextraction of the endocannabinoid anandamide in plasma samples from Parkinson’s disease patients and further analysis by ultra-high-performance liquid chromatography with tandem mass spectrometry. The molecularly imprinted polymer capillary presented recognition sites with complementary shape, size, and functionality to anandamide. Scanning electron micrographs and Fourier transform infrared spectra illustrated the physical and chemical modification of the printed and non-printed capillary surface. The in-tube solid-phase microextraction ultra-high-performance liquid chromatography with tandem mass spectrometry method presented a linear range from 0.1 to 20 ng mL-1, precision with coefficient of variation values ranging from 1.2 to 13%, and relative standard deviation accuracy ranging from -3.6 to 7.5%. The method developed herein can adequately determine anandamide in plasma samples from Parkinson’s disease patients. By applying the standard addition approach, the anandamide plasmatic concentration in these samples was found to range from 0.2 to 0.4 ng mL-1. Parkinsons Parkinson s neurons ganglia signals article fusedsilica fused silica intube tube solidphase solid phase ultrahighperformance ultra high performance shape size nonprinted non surface 01 0 1 0. 2 mL1, mL1 mL 1, mL-1 12 1. 13 13% 3.6 36 3 6 -3. 75 7 5 7.5% approach 02 04 4 mL1. mL- 3. -3 7.5 - 7.