Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2016-05-03T22:43:01Z No. of bitstreams: 1 MariaSantanaBezerraDeLima_TESE.pdf: 6593085 bytes, checksum: 34afc03a9376435110e739375a8efdd4 (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2016-05-05T00:05:35Z (GMT) No. of bitstreams: 1 MariaSantanaBezerraDeLima_TESE.pdf: 6593085 bytes, checksum: 34afc03a9376435110e739375a8efdd4 (MD5) / Made available in DSpace on 2016-05-05T00:05:35Z (GMT). No. of bitstreams: 1 MariaSantanaBezerraDeLima_TESE.pdf: 6593085 bytes, checksum: 34afc03a9376435110e739375a8efdd4 (MD5) Previous issue date: 2015-05-29 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior (CAPES) / Este trabalho foi desenvolvido com o objetivo de propor uma rotina metodol?gica simples, r?pida e vers?til utilizando espectroscopia de infravermelho pr?ximo (NIR) aliada ? an?lise multivariada para a determina??o dos teores de cinzas, umidade, prote?na e lip?dios totais presentes no camar?o cinza (Litopenaeus vannamei) que convencionalmente ? realizada por gravimetria ap?s redu??o a cinzas a 550 oC por gravimetria ap?s secagem em estufa a 105 ?C para a determina??o de umidade, gravimetria ap?s extra??o utilizando Soxhlet e volumetria ap?s digest?o e destila??o por Kjedhal, respectivamente. Inicialmente, foram coletados os espectros de 63 amostras processadas de camar?o cozidos da esp?cie Litopenaeus vannamei. Em seguida, foram realizadas as determina??es pelos m?todos convencionais de refer?ncia. Os espectros centrados na m?dia foram submetidos ? corre??o de espalhamento multiplicativo da luz, alisamento de Saviztky-Golay em 15 pontos e primeira derivada, eliminada a regi?o ruidosa, a faixa de trabalho foi 1036,15 a 3232,49 nm. Desta forma, os modelos PLS para predi??o de cinzas mostraram R 0,9419, RMSEC 0,1065 e RMSEP 0,1929; para umidade o R foi de 0,7704, RMSEC 4,1407 e RMSEP 4,6948; para prote?na R 0,8510, RMSEC 2,6372 e RMSEP 2,8468; para lip?dios R 0,8078, RMSEC 0,3618 e RMSEP 0,2255 De maneira que, os resultados mostraram que os erros relativos encontrados entre o m?todo de refer?ncia e o NIR foram pequenos e satisfat?rios. Estes resultados s?o um excelente indicativo de que se pode utilizar o NIR para estas an?lises, o que ? bastante vantajoso, j? que as t?cnicas convencionais s?o demoradas, gastam uma grande quantidade de reagentes e envolvem v?rios profissionais, o que demanda um tempo razo?vel de execu??o, enquanto que ap?s a valida??o da metodologia a execu??o utilizando NIR reduz todo esse tempo para alguns minutos, com economia de reagentes, de tempo e sem gera??o de res?duos, al?m de tratar-se de uma t?cnica n?o destrutiva. / This work was developed with the objective of proposing a simple, fast and versatile methodological routine using near-infrared spectroscopy (NIR) combined with multivariate analysis for the determination of ash content, moisture, protein and total lipids present in the gray shrimp (Litopenaeus vannamei ) which is conventionally performed gravimetrically after ashing at 550 ? C gravimetrically after drying at 105 ? C for the determination of moisture gravimetrically after a Soxhlet extraction using volumetric and after digestion and distillation Kjedhal respectively. Was first collected the spectra of 63 samples processed boiled shrimp Litopenaeus vannamei species. Then, the determinations by conventional standard methods were carried out. The spectra centered average underwent multiplicative scattering correction of light, smoothing Saviztky-Golay 15 points and first derivative, eliminated the noisy region, the working range was from 1100,36 to 2502,37 nm. Thus, the PLS models for predicting ash showed R 0,9471; 0,1017 and RMSEP RMSEC 0,1548; Moisture R was 0,9241; 2,5483 and RMSEP RMSEC 4,1979; R protein to 0,9201; 1,9391 and RMSEP RMSEC 2,7066; for lipids R 0,8801; 0,2827 and RMSEP RMSEC 0,2329 So that the results showed that the relative errors found between the reference method and the NIR were small and satisfactory. These results are an excellent indication that you can use the NIR to these analyzes, which is quite advantageous, since conventional techniques are time consuming, they spend a lot of reagents and involve a number of professionals, which requires a reasonable runtime while after the validation of the methodology execution using NIR reduces all this time to a few minutes, saving reagents, time and without waste generation, and that this is a non-destructive technique.

Made available in DSpace on 2014-12-17T15:42:08Z (GMT). No. of bitstreams: 1 RosangelaCC_DISSERT.pdf: 3998203 bytes, checksum: f53c6aa79d4a6709116a504b71acbe98 (MD5) Previous issue date: 2013-05-17 / The aim of this study was to evaluate the potential of near-infrared reflectance spectroscopy (NIRS) as a rapid and non-destructive method to determine the soluble solid content (SSC), pH and titratable acidity of intact plums. Samples of plum with a total solids content ranging from 5.7 to 15%, pH from 2.72 to 3.84 and titratable acidity from 0.88 a 3.6% were collected from supermarkets in Natal-Brazil, and NIR spectra were acquired in the 714 2500 nm range. A comparison of several multivariate calibration techniques with respect to several pre-processing data and variable selection algorithms, such as interval Partial Least Squares (iPLS), genetic algorithm (GA), successive projections algorithm (SPA) and ordered predictors selection (OPS), was performed. Validation models for SSC, pH and titratable acidity had a coefficient of correlation (R) of 0.95 0.90 and 0.80, as well as a root mean square error of prediction (RMSEP) of 0.45?Brix, 0.07 and 0.40%, respectively. From these results, it can be concluded that NIR spectroscopy can be used as a non-destructive alternative for measuring the SSC, pH and titratable acidity in plums / O objetivo deste estudo foi avaliar a potencialidade da espectroscopia no infravermelho pr?ximo (NIRS) como um m?todo r?pido e n?o destrutivo para determina??o do teor de s?lidos sol?veis (TSS), pH e acidez titul?vel em ameixas intactas. Amostras de ameixa com teor de s?lidos sol?veis variando de 5,7 a 15%, pH de 2,72 a 3,84 e acidez de 0,88 a 3,6% foram adquiridas de supermercados em Natal - Brasil, e foram coletados espectros NIR no intervalo de 714-2500 nm. Uma compara??o de v?rias t?cnicas de calibra??o multivariada com rela??o ao pr?-processamento dos dados e algoritmos de sele??o de vari?veis, tais como m?nimos quadrados parciais por intervalos (iPLS), o algoritmo gen?tico (GA), algoritmo das proje??es sucessivas (SPA), e sele??o de previsores ordenados (OPS) foi realizada. Modelos de valida??o para o teor de s?lidos sol?veis, pH e acidez titul?vel tiveram um coeficiente de correla??o (R) de 0,95 a 0,90 e 0,80, bem como um erro m?dio quadr?tico de previs?o (RMSEP) de 0,45? Brix, 0,07 e 0,40%, respectivamente. A partir desses resultados, pode concluir-se que a espectroscopia NIR pode ser utilizada como uma alternativa n?o destrutiva para determina??o do teor de s?lidos sol?veis, pH e acidez em ameixas

Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2016-05-30T22:35:17Z No. of bitstreams: 1 MariaRaquelCavalcantiInacio_TESE.pdf: 2176193 bytes, checksum: 1c0288ef05b8770739a332aeef0364e1 (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2016-06-01T21:19:57Z (GMT) No. of bitstreams: 1 MariaRaquelCavalcantiInacio_TESE.pdf: 2176193 bytes, checksum: 1c0288ef05b8770739a332aeef0364e1 (MD5) / Made available in DSpace on 2016-06-01T21:19:57Z (GMT). No. of bitstreams: 1 MariaRaquelCavalcantiInacio_TESE.pdf: 2176193 bytes, checksum: 1c0288ef05b8770739a332aeef0364e1 (MD5) Previous issue date: 2014-12-12 / Neste estudo, foram avaliadas a espectroscopia de reflect?ncia do infravermelho pr?ximo (NIR) e o potencial da calibra??o multivariada como um m?todo r?pido para determinar o teor total de antocianinas em frutos intactos de a?a? e palmiteiro ju?ara. Diversas t?cnicas de calibra??o multivariadas, incluindo regress?o por m?nimos quadrados parciais (PLS), M?nimos Quadrados Parciais por Intervalo (iPLS), algoritmo gen?tico (AG), algoritmo das proje??es sucessivas (APS),foram comparadas e validadas pelo c?lculo das figuras de m?rito. Resultados adequados foram obtidos com o modelo PLS (4 vari?veis latentes e suaviza??o em janela com 5 pontos) com limite de detec??o de 6,2 g.kg-1, limite de quantifica??o de 20,7 g.kg-1, precis?o estimada como raiz quadrada da m?dia do erro da previs?o (RMSEP) de 4,8 g.kg-1, seletividade de 0,79 g.kg-1, sensibilidade de 5,04 x 10-3 g kg-1, precis?o de 27,8 g.kg-1 e a raz?o sinal-ru?do foi de 1,04 x 10-3 g.kg-1. Estes resultados sugerem que a espectroscopia NIR e a calibra??o multivariada podem ser efetivamente usadas para determinar o teor de antocianinas em frutos intactos de a?a? e palmiteiro ju?ara. / In this study was evaluated near-infrared reflectance spectroscopy (NIR), and multivariate calibration potential as a rapid method to determinate anthocyanin content in intact fruit (a?a? and palmitero-ju?ara). It?s important to develop new methods to determinate quality parameters in foods, mostly the use of quick techniques, non-invasive and which have reliable methods. The NIR spectroscopy fills these requirements and these have shown as an alternative to conventional quality control analysis in several foods, including, fruit. Currently, analytical methods have been reported to determinate anthocyanin in fruits. However, the NIR spectroscopy is cited rarely to determinate anthocyanin content in a?a? and palmitero-ju?ara. This study could contribute to research that already have performed. Several multivariate calibration techniques, including partial least squares (PLS), interval partial least squares (iPLS), genetic algorithm (AG), successive projections algorithm (SPA), were compared and validated by establishing figures of merit. In this job, 139 fruits were used, 69 were acai and 70 were palmiteiro ju?ara. The potential anthocyanin sources has been quantified using differential pH method, as a reference method. Soon after, the near-infrared diffuse reflectance spectra have been measured, and finally the chemometrics models have been built. Suitable results were obtained with the PLS model (four latent variables and 5- point smoothing) with a detection limit of 6.2 g kg-1, limit of quantification of 20.7 g kg-1, accuracy estimated as root mean square error of prediction of 4.8 g kg-1, mean selectivity of 0.79 g kg-1, sensitivity of 5.04 x10-3 g kg-1, precision of 27,8 g kg-1, and signal-to-noise ratio of 1.04 x10-3 g kg-1. These results suggest NIR spectroscopy and multivariate calibration can effectively be used to determine anthocyanin content in intact a?a? and palmitero-ju?ara fruit.

Made available in DSpace on 2014-12-17T15:41:56Z (GMT). No. of bitstreams: 1 AlessandraMC_DISSERT.pdf: 3533058 bytes, checksum: de92ff683335d9aa6c119013acb5b5d0 (MD5) Previous issue date: 2011-08-15 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / In this work calibration models were constructed to determine the content of total lipids and moisture in powdered milk samples. For this, used the near-infrared spectroscopy by diffuse reflectance, combined with multivariate calibration. Initially, the spectral data were submitted to correction of multiplicative light scattering (MSC) and Savitzsky-Golay smoothing. Then, the samples were divided into subgroups by application of hierarchical clustering analysis of the classes (HCA) and Ward Linkage criterion. Thus, it became possible to build regression models by partial least squares (PLS) that allowed the calibration and prediction of the content total lipid and moisture, based on the values obtained by the reference methods of Soxhlet and 105 ? C, respectively . Therefore, conclude that the NIR had a good performance for the quantification of samples of powdered milk, mainly by minimizing the analysis time, not destruction of the samples and not waste. Prediction models for determination of total lipids correlated (R) of 0.9955, RMSEP of 0.8952, therefore the average error between the Soxhlet and NIR was ? 0.70%, while the model prediction to content moisture correlated (R) of 0.9184, RMSEP, 0.3778 and error of ? 0.76% / Neste trabalho foram constru?dos modelos de calibra??o para determinar os teores de lip?dios totais e umidade em amostras de leite em p?. Para isso, utilizou-se a espectroscopia no infravermelho pr?ximo por reflect?ncia difusa, aliado ? calibra??o multivariada. Inicialmente, os dados espectrais foram submetidos ? corre??o multiplicativa do espalhamento da luz (MSC) e alisamento de Savitzsky-Golay. Em seguida, as amostras foram divididas em subgrupos por aplica??o da an?lise por agrupamento hier?rquico das classes (HCA) e crit?rio de Ward Linkage. Desta forma, tornou-se poss?vel construir modelos de regress?o por m?nimos quadrados parciais (PLS) que permitiu a calibra??o e previs?o dos teores de lip?dios e umidade, com base nos valores obtidos por m?todos de refer?ncia de Soxhlet e secagem a 105 ? C, respectivamente. Portanto, conclui-se que o NIR apresentou um bom desempenho para quantifica??o de amostras de leite em p?, principalmente pela minimiza??o do tempo das an?lises, n?o destrui??o das amostras e n?o gera??o de res?duos. Os modelos de previs?o para determina??o de lip?dios totais apresentaram correla??o (R) de 0,9955, RMSEP de 0,8952, por conseguinte, o erro m?dio entre o Soxhlet e o NIR foi ? 0,70%, enquanto o modelo de previs?o para teor de umidade apresentou correla??o (R) de 0,9184, RMSEP, 0,3778 e erro de ? 0,76%

Made available in DSpace on 2014-12-17T15:42:05Z (GMT). No. of bitstreams: 1 AnaCON_DISSERT.pdf: 2560306 bytes, checksum: 01b4c26da4748508add3442c02e1b43b (MD5) Previous issue date: 2013-02-04 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / In this work, the quantitative analysis of glucose, triglycerides and cholesterol (total and HDL) in both rat and human blood plasma was performed without any kind of pretreatment of samples, by using near infrared spectroscopy (NIR) combined with multivariate methods. For this purpose, different techniques and algorithms used to pre-process data, to select variables and to build multivariate regression models were compared between each other, such as partial least squares regression (PLS), non linear regression by artificial neural networks, interval partial least squares regression (iPLS), genetic algorithm (GA), successive projections algorithm (SPA), amongst others. Related to the determinations of rat blood plasma samples, the variables selection algorithms showed satisfactory results both for the correlation coefficients (R?) and for the values of root mean square error of prediction (RMSEP) for the three analytes, especially for triglycerides and cholesterol-HDL. The RMSEP values for glucose, triglycerides and cholesterol-HDL obtained through the best PLS model were 6.08, 16.07 e 2.03 mg dL-1, respectively. In the other case, for the determinations in human blood plasma, the predictions obtained by the PLS models provided unsatisfactory results with non linear tendency and presence of bias. Then, the ANN regression was applied as an alternative to PLS, considering its ability of modeling data from non linear systems. The root mean square error of monitoring (RMSEM) for glucose, triglycerides and total cholesterol, for the best ANN models, were 13.20, 10.31 e 12.35 mg dL-1, respectively. Statistical tests (F and t) suggest that NIR spectroscopy combined with multivariate regression methods (PLS and ANN) are capable to quantify the analytes (glucose, triglycerides and cholesterol) even when they are present in highly complex biological fluids, such as blood plasma / No presente trabalho, a an?lise quantitativa de glicose, triglicer?deos e colesterol (total e HDL) em plasma sangu?neo de ratos e humanos foi realizada sem necessidade de pr?tratamentos de amostras, atrav?s do uso da espectroscopia no infravermelho pr?ximo (NIR), aliada a m?todos multivariados. Para tanto, foram comparadas diferentes t?cnicas e algoritmos utilizados para pr?-processamentos de dados, sele??o de vari?veis e regress?es multivariadas, tais como a regress?o por m?nimos quadrados parciais (PLSR), regress?o n?o linear via redes neurais artificiais (ANN), regress?o por m?nimos quadrados parciais por intervalos (iPLS), algoritmo gen?tico (GA), algoritmo das proje??es sucessivas (SPA), entre outros. Para as determina??es em sangue de ratos, os algoritmos de sele??o de vari?veis apresentaram resultados satisfat?rios tanto em rela??o aos coeficientes de correla??o (R?) quanto para os valores de erro quadr?tico m?dio de previs?o (RMSEP) para os tr?s analitos, especialmente para triglicer?deos e colesterol-HDL. Os valores de RMSEP para glicose, triglicer?deos e colesterol-HDL atrav?s do melhor modelo PLS foram de 6,08, 16,07 e 2,03 mg dL-1, respectivamente. Para as determina??es em sangue de humanos, as previs?es atrav?s de modelos PLS apresentaram resultados insatisfat?rios, com comportamento n?o linear e presen?a de bias. A regress?o ANN foi investigada como uma alternativa ao PLS, por sua habilidade de modelar sistemas n?o lineares. O erro quadr?tico m?dio de monitoramento (RMSEM) para glicose, triglicer?deos e colesterol total, para os melhores modelos ANN, foram de 13,20, 10,31 e 12,35 mg dL-1, respectivamente. Testes estat?sticos (F e t) sugerem que a espectroscopia NIR aliada a m?todos de regress?o multivariados (PLS e ANN) possuem capacidade de quantificar os analitos (glicose, triglicer?deos e colesterol) mesmo quando os mesmos est?o presentes em fluidos biol?gicos altamente complexos, como o plasma sangu?neo