Abstract Near infrared spectroscopy (NIRS) combined with various chemometrics methods was tried to identify the fresh tea leaves at different altitudes quickly and nondestructively. Three kinds of samples were collected, then scanning NIRS, conducting spectral preprocessing to remove noise information, using backward interval partial least squares to screen characteristic spectral intervals, going on principal component analysis, respectively. Finally, least squares support vector machine method (LS-SVM) was applied to establish NIRS models, whose robustness was tested by prediction set samples. The best pretreated method was the combination of multivariate scattering correction and the first derivative. Six characteristic spectral intervals were screened, and the corresponding spectral wavenumbers were 4821.2-5091.2 cm-1, 5368.9-5638.8 cm-1, 6190.4-6460.4 cm-1, 7011.9-7281.9 cm-1, 8924.9-9191.1 cm-1 and 9734.9-10000 cm-1. The cumulative contribution rate of the first three principal components was 99.92%. The root mean square error of the cross validation and the determination coefficient of the calibration set model were 0.027 and 0.973, respectively. The root mean square error and the determination coefficient of the prediction set model were 0.034 and 0.968, respectively. The discrimination accuracy in prediction set was 100%. The results showed NIRS combined with LS-SVM can realize fast and nondestructive discrimination of fresh tea leaves at different altitudes.

Abstract The current developmental trend is to evaluate the quality of Yongchuan Xiuya tea rapidly. After spectrum pre-processing, near infrared spectroscopy (NIRS) coupled with synergy interval partial least squares (siPLS), principal component analysis (PCA) and back propagation-artificial neural network (BP-ANN) was applied to rapidly and non-destructively predict the quality of Yongchuan Xiuya tea. External Yongchuan Xiuya tea samples were used for the actual application of the proposed model. The best pre-processing method was multiple scattering correction coupled with second derivative, and the characteristic spectral regions selected by siPLS were 4381.5-4755.6 cm-1, 4759.5-5133.6 cm-1, 6266.6-6637.8 cm-1 and 7389.9-7760.2 cm-1. The cumulative contribution rate was 99.05% for the first three principal components of the characteristic spectra regions. The transfer function, root mean square error and determinant coefficient of the best BP-ANN prediction model were the tanh function, 0.384 and 0.977, respectively. The root mean square error and determinant coefficient of the external 10 Yongchuan Xiuya tea samples were 0.406 and 0.969, respectively. These results showed that NIRS combined with BP-ANN algorithm can be used to evaluate the quality of Yongchuan Xiuya tea rapidly and accurately.

Abstract Near infrared spectroscopy (NIRS) combined with multiple algorithms was used to determinate the tea polyphenols content in Chongzhou new loquat tea lines quickly and nondestructively. Samples of 26 Chongzhou new loquat tea lines were collected, then scanning NIRS, pretreating spectral noise information, screening characteristic spectral intervals by backward interval partial least squares, proceeding principal component analysis. Finally, the artificial neural network (BP-ANN) method with three kinds of transfer functions was applied to establish models. The best pretreated method was the combination of standard normal variation (SNV) and first derivative, and the characteristic spectral regions selected were 4381.5-4755.6 cm–1, 4759.5-5133.6 cm–1, 6266.6-6637.8 cm–1 and 7389.9-7760.2 cm–1, respectively. The cumulative contribution rate of the first three principal components of the selected characteristic spectra was 95.24%. When the BP-ANN calibration set model was established with the logistic function, NIRS model had the best results, whose root mean square error and determination coefficient of the cross validation were 0.975 and 0.372%, respectively. The root mean square error and the determination coefficient of the prediction set model were 0.962 and 0.400%, respectively. The results showed NIRS can predict the tea polyphenols content in Chongzhou new loquat tea lines quickly and accurately.

RESUMO Objetivou-se comparar os teores dos nutrientes do capim Andropogon gayanus obtidos no equipamento NIRS com os valores obtidos por análises de via úmida, para identificar se os modelos globais de calibração do equipamento NIRS são adequados para predizer a composição químico-bromatológica. As análises de via seca no NIRS foram executadas no Laboratório de Bromatologia e Nutrição Animal (Laban), pertencente à Faculdade de Medicina Veterinária (Famev) da Universidade Federal de Uberlândia (UFU), enquanto as análises de via úmida foram realizadas no Laboratório de Química Analítica de Plantas da Embrapa Cerrados, localizado em Brasília-DF. As amostras utilizadas foram de capim Andropogon gayanus, cultivar Planaltina, as quais, após corte de 20cm acima do solo, foram secas e moídas no tamanho de 1mm. Após a moagem, foram analisadas por via úmida para os teores de matéria seca (MS), matéria mineral (MM), proteína bruta (PB), fibra insolúvel em detergente neutro (FDN) e fibra insolúvel em detergente ácido (FDA), segundo metodologias propostas por Detmann et al. (2012). As amostras moídas foram colocadas em cubetas próprias do equipamento e escaneadas em espectrômetro de refletância no infravermelho próximo (NIRS) NIR, modelo Spectra Star 2600 XT series of Near Infrared Analyzers (Unity Scientific®), em duplicata. Para obtenção dos teores de MS, MM, PB, FDN e FDA, empregaram-se modelos de calibração do próprio equipamento NIRS, utilizando-se a curva de calibração própria do equipamento. As médias dos teores de MS, MM, PB, FDN e FDA obtidas pelas análises de bancada (via úmida) e pelo uso do equipamento NIRS foram comparadas pelo teste T (dados pareados), ao nível de 5% de probabilidade, empregando-se o delineamento em blocos ao acaso. Houve diferença significativa nos nutrientes preditos pelo NIRS e analisados por via úmida (P≤0,05). O NIRS superestimou os teores de matéria seca e matéria mineral, mas subestimou os teores de FDN, FDA e PB. Esse resultado mostra que, quando do uso de modelos globais de calibração, esse equipamento não é capaz de predizer corretamente a composição químico-bromatológica de forrageiras de clima tropical.

ABSTRACT Background: Water pollution by nitrate and antibiotics has been growing over the years, so the denitrifying process can be a good alternative for the simultaneous removal of both compounds. Objective: Show the role of denitrification in the elimination of antibiotics, as well as their effects on the physiology and kinetics of the respiratory process, genes, and denitrifying microbial populations. Results: There are studies on the elimination of different antibiotics under denitrifying conditions, however, in most of them, the fate of the carbonated and nitrogenous matter consumed is unknown. Antibiotics such as sulfonamides and tetracyclines cause negative effects on the denitrifying process by decreasing the nitrate removal efficiency, its rate of consumption, and promoting the accumulation of nitrite. Denitrifying genera such as Thauera and Pseudomonas were reported as resistant and/or tolerant to the presence of different antibiotics belonging to fluoroquinolones, macrolides, tetracyclines, and β-lactams, as well as mixtures of antibiotics. Decreased abundance and gene expression of genes involved in denitrification such as nirS and nosZ, was observed in the presence of sulfonamides, this effect could cause nitrite and nitrous oxide accumulation, producing a possible bottleneck in the denitrifying process. Antibiotic resistance genes have been detected in denitrifying microorganisms exposed to antibiotics, which could act as defense mechanisms to the presence of these compounds. Conclusions: The information contained in this review contributes to the knowledge about the denitrifying process and proposes its use to carry out more efficient and stable disposal of nitrate and antibiotics present in contaminated waters.

RESUMEN Antecedentes: La contaminación del agua por nitrato y antibióticos ha ido creciendo a lo largo de los años, por lo que el proceso desnitrificante puede ser una buena alternativa para la eliminación simultánea de ambos compuestos. Objetivo: Mostrar el papel de la desnitrificación en la eliminación de antibióticos, así como los efectos de estos compuestos sobre la fisiología y cinética del proceso respiratorio, los genes y las poblaciones microbianas desnitrificantes. Resultados: Existen estudios sobre la eliminación de diferentes antibióticos bajo condiciones desnitrificantes, sin embargo, en la mayoría de los trabajos, el destino de la materia carbonada y nitrogenada consumida se desconoce. Antibióticos como las sulfonamidas y tetraciclinas provocan efectos negativos sobre el proceso desnitrificante al disminuir la eficiencia de eliminación de nitrato, su velocidad de consumo y propiciar la acumulación de nitrito. Se reportaron géneros desnitrificantes como Thauera y Pseudomonas como resistentes y/o tolerantes ante la presencia de diferentes antibióticos pertenecientes a las fluoroquinolonas, macrólidos, tetraciclinas y β-lactámicos, así como mezclas de éstos. La disminución de la abundancia y expresión génica de genes que participan en la desnitrificación como nirS y nosZ, fue observada en presencia de sulfonamidas, efecto que podría causar la acumulación de nitrito y óxido nitroso, ocasionando un posible cuello de botella en el proceso desnitrificante. En microorganismos desnitrificantes expuestos a antibióticos han sido detectados genes de resistencia a antibióticos, los cuales podrían actuar como mecanismos de defensa ante su presencia. Conclusiones: La información contenida en la presente revisión contribuye al conocimiento sobre el proceso desnitrificante, proponiendo su uso para llevar a cabo una eliminación más eficiente y estable de nitrato y antibióticos presentes en aguas contaminadas.

Abstract Objective/Introduction: Near-infrared spectroscopy (NIRS) is a non-invasive technique to detect cerebral ischemia by monitoring changes in regional cerebral oxygenation (rSO2) in the frontal lobes. However, there are no studies showing the changes in NIRS values in response to hemodynamic variations during stages of carotid endarterectomy (CEA) procedure and clinical implications of these changes. The aim of this study was to determine if hemodynamic changes affect NIRS values during carotid endarterectomy and if our results may help to provide strategies for hemodynamic management in these patients. Methods: A total of 50 consecutive patients undergoing CEA were prospectively included in the study. NIRS was measured at first minute after clamping of carotid artery, and then systolic blood pressure was increased above 150 mmHg. NIRS values from both hemispheres were recorded simultaneously at certain time points and were analyzed to evaluate the changes at different stages of operation and to assess correlations with hemodynamic parameters. Results: NIRS values on the right and left sides were correlated with systolic (right P<0.001, R2:0.24; left P=0.02, R2:0.10) diastolic (right P<0.001, R2:0.36; left P=0.001, R2:0.18) and mean (right P<0.001, R2:0.33; left P=0.003, R2:0.17) blood pressures when the patient was under general anaesthesia. NIRS values were significantly lower than pre-incision values just after clamping of carotid artery in both hemispheres (P=0.005 for the right and P<0.001 for the left side). Conclusion: NIRS values measured in our study show that there is a correlation between hemodynamic changes and cerebral oxygenation. This effect is especially pronounced while the patient is asleep and intubated, which implies the importance of close monitoring of patients with carotid disease during any surgery requiring general anaesthesia.

Abstract: Understanding the drivers of wood density variation both within a tree and between trees is important in predicting the quality of wood logs and improving this quality through adequate forestry management. This study examined the effect of the diameter growth of Acacia auriculiformis on its wood density variation. The study was conducted in the South of Benin in four plantations of Acacia auriculiformis. Near infrared spectroscopy (NIRS) method was used to predict the basic density of 225 tree wood cores of Acacia auriculiformis. A predicting model of the average tree density using the diameter as predictor was established. The relationship between wood density and tree diameter was best described by a linear mixed-effect model. The average wood density of trees increased with the diameter. The study concluded that the quality of the species logs can be improved through regular thinning and genetic selection.

Near-infrared spectroscopy (NIRS) could be a useful continuous, non-invasive technique for monitoring the effect of partial pressure of carbon dioxide (PaCO2) fluctuations in the cerebral circulation during ventilation. The aim of this study was to examine the efficacy of NIRS to detect acute changes in cerebral blood flow following PaCO2 fluctuations after confirming the autoregulation physiology in piglets. Fourteen piglets (<72 h of life) were studied. Mean arterial blood pressure, oxygen saturation, pH, glycemia, hemoglobin, electrolytes, and temperature were monitored. Eight animals were used to evaluate brain autoregulation, assessing superior cava vein Doppler as a proxy of cerebral blood flow changing mean arterial blood pressure. Another 6 animals were used to assess hypercapnia generated by decreasing ventilatory settings and complementary CO2 through the ventilator circuit and hypocapnia due to increasing ventilatory settings. Cerebral blood flow was determined by jugular vein blood flow by Doppler and continuously monitored with NIRS. A decrease in PaCO2 was observed after hyperventilation (47.6±2.4 to 29.0±4.9 mmHg). An increase in PaCO2 was observed after hypoventilation (48.5±5.5 to 90.4±25.1 mmHg). A decrease in cerebral blood flow after hyperventilation (21.8±10.4 to 15.1±11.0 mL/min) and an increase after hypoventilation (23.4±8.4 to 38.3±10.5 mL/min) were detected by Doppler ultrasound. A significant correlation was found between cerebral oxygenation and Doppler-derived parameters of blood flow and PaCO2. Although cerebral NIRS monitoring is mainly used to detect changes in regional brain oxygenation, modifications in cerebral blood flow following experimental PaCO2 changes were detected in newborn piglets when no other important variables were modified.

ABSTRACT Ground bay laurel leaf samples (10–15 g) were scanned using Fourier-transform near-infrared (FT-NIR) spectrometer with reflectance mode in the 1000–2500 nm wavelength range. According to the wet chemical analyses, the essential oil content of the samples from different locations varied between 1.77 and 5.30%. The major component of essential oil was 1-8 cineole with a concentration of 43.4–58.1%. The regression coefficients of calibration (R2CAL) and validation (R2VAL) for essential oil and 1-8 cineol content with partial least square regression (PLSR) actualized as 0.96–0.98 and 0.98–0.98, respectively. The prediction accuracy of the final NIRS model was reasonable, with acceptable root mean standard errors of prediction (RMSEP) of 0.18% and 0.45%. According to the residual predictive deviation (RPD) index (3.58 and 8.41), the accuracy of the NIRS models was regarded as the best. The PLSR model differentiated bay laurel genotypes very well on the first principal component (PC1), based on the related properties.

Resumo O lúpulo é uma das matérias-primas vitais para a fabricação da cerveja e sua forma de armazenamento influencia diretamente nas sensações organolépticas finais das cervejas. Quando os lúpulos são armazenados incorretamente, a degradação de importantes compostos, responsáveis pelo amargor, ocorre de forma rápida. No presente trabalho, são apresentados estudos, nas regiões ultravioleta/visível e infravermelho próximo, maximizados por Cromatográfica Líquida de Ultra Eficiência, para a identificação da melhor forma de armazenamento de lúpulos, através da variação da (i) temperatura de armazenamento, (ii) do contato com o ar atmosférico e (iii) do tempo de armazenamento. Para tanto, três variedades diferentes de lúpulos comerciais foram armazenadas por seis meses (Hersbrucker, Magnum e Zeus). Os resultados quimiométricos com os dados obtidos por UV-Vis e NIRS demonstraram claramente a cinética de degradação dos lúpulos em diferentes condições de armazenamento, enquanto os resultados cromatográficos promoveram a quantificação dessa degradação. Juntos, os resultados indicaram que os lúpulos estocados em sacos plásticos a vácuo em baixas temperaturas (≤ -10 °C) apresentaram a menor taxa de degradação dos α - ácidos durante os meses de estudo.

Abstract Hops (Humulus lupulus L.) are one of the vital raw materials of brewing and their form of storage directly influences the final organoleptic sensations of beers. When hops are incorrectly stored, the degradation of important bitter compounds occurs fast. In the present work, it was used the ultraviolet/visible and near infrared regions, maximized by Ultra-Performance Liquid Chromatographic (UPLC) analyses, to identify the best way to store hops, by varying the (i) storage temperature, (ii) contact with atmospheric air, and (iii) storage time. For that, three different varieties of commercial hops were stored for six months (Hersbrucker, Magnum and Zeus). The chemometric results obtained with the Ultraviolet/ Visible (UV-Vis) and Near Infrared Spectroscopy (NIRS) data demonstrated the hop degradation kinetics under different storage conditions, while the chromatographic results provided the quantification of this degradation. Together, the results indicated that hops stored at low temperatures (≤ -10 °C) under a vacuum plastic bag presented the lower α - acids degradation rates over the months of the study.

RESUMO A espectroscopia no infravermelho próximo (NIR) é uma ferramenta capaz de fornecer resultados eficientes para moléculas orgânicas de diversos materiais. O estudo desenvolveu modelo preditivo com a espectroscopia NIR com Transformada de Fourier, para distinguir taninos em diferentes espécies florestais da Amazônia. Foram obtidas amostras de diferentes regiões do Estado do Amazonas/Brasil, testes para taninos e obtenção de espectros NIRS foram realizados. A montagem de matrizes de dados espectrais, versus analitos de interesse foram cruzados com os resultados das análises tradicionais. Um conjunto de calibração e validação foi construído para taninos condensados, taninos hidrolisáveis e amostras sem taninos. Ao final, avaliou-se o desempenho dos modelos de classificação quanto à sensibilidade, índice de identificação e erros. Em 63% das espécies estudadas, foi detectada a classe de tanino condensado, seguida de 34% para espécies que não continham tanino. A análise discriminante produziu agrupamentos com índice de sensibilidade de acerto >90%. O modelo desenvolvido pode ser aplicado em estudos de ecologia, silvicultura e quimiotaxonomia, com foco em compostos fenólicos como taninos. A metodologia proposta neste trabalho apresenta vantagens sobre os métodos de referência, destacando-se a menor necessidade de preparo das amostras, menor tempo de análise, não utiliza-se reagentes e consequentemente, não gera resíduos.

ABSTRACT Near infrared spectroscopy (NIR) is a tool capable of providing efficient results for organic molecules of different materials. We developed a predictive model using Fourier Transform NIR Spectroscopy to distinguish the types of tannins in different forest species in the Amazon. Samples were obtained from different regions of the State of Amazonas/Brazil, and tests for tannins were performed, including obtaining NIRS spectra. The assembly of spectral data matrices versus analytes of interest was crossed with the results of traditional analyses. In addition, a calibration and validation set was constructed for condensed tannins, hydrolyzable tannins, and samples with no tannins. Finally, the performance of classification models was evaluated for sensitivity, identification index, and errors. The condensed tannin classes were detected in 63% of the species studied, followed by 34% of the species not containing tannin. The discriminant analysis produced groupings of classes, with a hit sensitivity index >90%. The developed model can be applied in studies of ecology, forestry and chemotaxonomy, with a focus on phenolic compounds such as tannins. The proposed methodology has advantages over the reference methods, reflected as a lower need for sample preparation, shorter analysis time, no use of reagents, and, consequently, no generation of waste.

Resumen Introducción. La carne bovina es un alimento de alto valor biológico para la nutrición humana, es fuente de grasa, proteína, vitaminas y minerales. Sin embargo, aspectos asociados al impacto ambiental del sistema productivo y asociación con enfermedades no trasmisibles, han promovido nuevas tendencias en el consumo de proteína (vegetal, insectos, laboratorio), por lo que se hace necesario identificar y ofrecer información sobre los atributos de la carne que favorecen la aceptación de los consumidores, de forma rápida y confiable a través de técnicas no destructivas y amigables al ambiente como el infrarrojo cercano. Objetivo. Revisar las experiencias asociadas a la implementación de la Espectroscopia de Infrarrojo Cercano (NIRS) como alternativa en la determinación de la calidad de la carne bovina. Desarrollo. Los atributos de la carne con mayor relación con los consumidores pueden ser segmentados en apariencia, consumo y confianza. Estas características involucran elementos intrínsecos de la carne como color, grasa y terneza. Dada las limitantes en la aplicación de técnicas de laboratorio para la determinación de atributos cárnicos, se revisa la aplicación del NIRS con experiencias exitosas en características de interés para el consumidor. Además, se estudia la aplicación del NIRS en líneas de producción y otros usuarios de interés en la industria como detección de anomalías en la carne y autenticación de producto. Conclusión. La aplicación del NIRS, permite determinar de forma rápida y confiable atributos de la calidad de la carne que tienen una estrecha relación con el consumidor. Esta herramienta permite obtener resultados que respondan a la velocidad de producción de la industria y discriminar y autenticar aspectos relacionados con la carne y el sistema de producción.

Abstract Introduction. Beef is a food of high biological value for human nutrition; it is a source of fat, protein, vitamins, and minerals. However, aspects associated with the environmental impact of the production system and association with non-communicable diseases have promoted new protein consumption trends (vegetable, insects, lab protein). So, it is necessary to identify and offer information on the attributes of the meat that favor consumer acceptance quickly and reliably through non-destructive and environmentally friendly techniques such as near-infrared. Objective. To review the experiences associated with the implementation of Near-Infrared Spectroscopy (NIRS) as an alternative in the determination of beef quality. Development. Meat attributes with the greatest relationship with consumers can be segmented into appearance, consumption, and confidence. These characteristics involve intrinsic elements of the meat, such as color, fat, and tenderness. Given the limitations in the application of laboratory techniques for the determination of meat attributes, the application of the NIRS is reviewed with successful experiences in characteristics of interest to consumers. Additionally, the application of NIRS in production lines and other applications of interest in the industry, such as detection of meat anomalies and product authentication, is studied. Conclusion. The application of the NIRS allows to determine quickly and reliably attributes of the quality of the meat that have a close relationship with the consumer. This tool allows to obtain results that respond to the production speed of the industry, and to determinate and authenticate aspects related to meat and the production system.

Resumen: El espectro electromagnético provee una serie de diversas herramientas ópticas para probar, manipular e interactuar con los tejidos biológicos. En particular, el tejido blando permite que la luz entre 600 y 900 nm lo penetre algunos centímetros, rango conocido como ventana óptica. Esta característica convierte a la luz en el infrarrojo cercano en una herramienta diagnóstica, con la particularidad de ser no invasiva. Resulta de especial interés para este estudio su aplicación en el diagnóstico mamario. Estos tejidos no permiten la propagación de luz en este rango espectral en forma rectilínea, sino que se presentan como difusivos, deteriorándose así la resolución espacial de las imágenes que pueden obtenerse de ellos. De esta forma es necesario desarrollar técnicas experimentales y estrategias de análisis de datos específicas para poder obtener información óptica de los mismos. El tejido mamario puede sufrir diferentes tipos de lesiones, tales como tumores o quistes. Este trabajo presenta el estudio sobre fantomas, que reproducen sus propiedades ópticas con inclusiones que representan tumores y/o quistes, analizando la influencia de estas últimas, cuyas características ópticas son no difusivas, sobre las imágenes ópticas y el transporte de la luz en estos medios. El principal objetivo de este trabajo se centra en la localización 3D y caracterización óptica de heterogeneidades traslúcidas en medios turbios.

Abstract: Biological tissues have the particularity of allowing light between 600 and 900 nm, within a range called optical window, to penetrate them a few centimeters. This characteristic arouses interest in the near infrared light for its use as a diagnosis tool, with the characteristic of being non-invasive, its application in breast diagnosis is of particular interest for this study. These tissues do not allow the propagation of light in this spectral range in a rectilinear manner, but rather appear as diffusive, thus deteriorating the spatial resolution of the images that can be obtained from them. In this way, it is necessary to develop experimental techniques and specific data analysis strategies in order to obtain optical information from them. Breast tissue can suffer different types of lesions, such as tumors or cysts. This work presents the study of phantoms, which reproduce their optical properties with inclusions that represent tumors and / or cysts, analyzing the influence of the latter, which optical characteristics are non-diffusive, on optical images and the transport of light in these media. The main objective of this work is focused on the 3D localization and optical characterization of translucent heterogeneities in turbid media.

Combining NIRS spectra with the reference data, calibration models to predict non sugar compounds such as phosphates, starch, mannitol, phenols, conductivity ash and color were generated. Validations with new samples independent of the calibration population were carried out to verify the performance of the models. For all the studied parameters the calibration models returned relatively low correlation coefficients (RSQ = 0.60-0.90), with standard errors of prediction (SEP) nevertheless good enough for rapid qualitative analysis.

Combinando los espectros NIRS con los datos de referencia se generaron modelos para predecir compuestos no azúcares: fosfatos, almidón, manitol, fenoles, cenizas conductimétricas y color. Se llevaron a cabo validaciones con muestras independientes de la población de calibración para verificar el desempeño de los modelos. Para todos los parámetros estudiados los modelos de calibración tuvieron coeficientes de correlación (RSQ) relativamente bajos (0,60d"RSQd"0,90), sin embargo los errores de predicción (SEP) fueron suficientemente buenos para un análisis cualitativo rápido.

RESUMEN En girasol, la concentración de aceite (OG) determina el rendimiento industrial de los granos y la concentración de proteína (PG) determina la calidad de los subproductos como pellets y harinas (PM). Existen varias metodologías para cuantificar la concentración de nitrógeno total en grano (NG): a) Kjeldahl (digestión húmeda); b) Dumas (combustión seca); y c) NIRS (análisis del espectro de la luz reflejada por la muestra). NIRS representa un método promisorio para determinar NG porque es simple y rápido. El objetivo de este trabajo fue comparar los métodos de NIRS, Kjeldahl y Dumas para cuantificar NG en granos de girasol y ajustar modelos para estimar PM a partir de NG. Se seleccionaron ochenta y cuatro muestras de granos de girasol que cubren un amplio rango de NG (de 1.75 a 3.80% tomando la referencia del método de Dumas) de una red de experimentos realizados en el sudeste de la provincia de Buenos Aires (2013-2014 y 2014-2015). El NIRS fue el método más preciso para la determinación de NG y presentó un mayor grado de ajuste con Dumas respecto a Kjeldahl. La PM se estimó satisfactoriamente con NG. Por lo tanto, NIRS podría ser una alternativa superadora a las otras técnicas debido a su bajo costo, reducido tiempo de análisis, es no tóxico y puede determinar otros componentes del grano de manera simultánea con la determinación de NG.

ABSTRACT In sunflower, grain oil concentration (OG) determines oil industrial yield and protein concentration (PG) determines the protein of by-products as pellets and meals (PM). There are various methodologies to quantify total grain nitrogen concentration (NG): a) Kjeldahl (wet digestion); b) Dumas (dry combustion); c) NIRS (analysis of the spectrum of the light reflected by the sample). NIRS represents a promissory method for determining NG because it is simple and fast. The objective of this work was to compare the methods of NIRS, Kjeldahl and Dumas to quantify NG in sunflower grains and to adjust models to estimate PM from NG. Eighty-four samples of sunflower grains were selected covering a wide range of NG (from 1.75 to 3.80% taking Dumas reference) from a net of experiments conducted in southeastern Buenos Aires Province (2013-2014 and 2014-2015). NIRS was the most precise method for the determination of NG and presented a greater degree of agreement with Dumas than Kjeldahl. PM was satisfactorily estimated with NG. Therefore, NIRS could be a better alternative to the other techniques because its low cost, quickness, low toxicity, and adaptability to determine other components of the grain simultaneously with the determination of NG.