2 research outputs found
Evaluation of quality and potential bioactive of fruit drinks : application of spectroscopy on infrared and chemometric
Orientador: Juliana Azevedo Lima PalloneDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia de AlimentosResumo: O Brasil é o terceiro maior produtor de frutas no mundo. Dentre as frutas produzidas no território nacional, o caju (2 milhões toneladas/ano), goiaba (345 mil toneladas/ano) e uva (1,4 milhões de toneladas/ano), merecem destaque pela grande produção e variedade de produtos gerados a partir deles (sucos, néctares, polpas, doces, refrigerantes, etc). O setor de bebidas, sucos e néctares, tem sido responsável pela movimentação de US 1.9 billion from the sale of 476 million liters/ year, this share of the market has been driven by consumers looking for healthier products. Nectars of cashew apple and guava, present high content of vitamin C found in fruits (average 230 mg/100g and 600 mg/100g, respectively) and grape juice has a significant amount of phenolic compounds, especially anthocyanins. Ascorbic acid, phenolic compounds, including anthocyanins are labile compounds and subject to oxidative degradation, especially in aqueous media, such as drinks. To ensure the quality of nectars Brazilian legislation defined acidity parameters (TA) and total sugars (TS), soluble solids (SS), pH and ascorbic acid (AA) that are commonly performed by traditional analyzes involving the use of toxic substances, danger to the analyst and the environment, and the need for specific equipment. Similar scenario is found to analyze concentration of total phenolics content (TPC) and anthocyanins content (TAC) of grape juice, with the aggravation that these analyzes, in general, are time consuming and therefore impair the stability of the bioactive compounds during the process. As an alternative to these problems, this work proposes to use the spectroscopic analysis NIR and/or MIR along with chemometrics as an alternative to analyze nectars cashew and guava (ACT, AT, SS, pH and AA) and grape juice (TF and TA), to replace the traditional analysis. The spectra obtained by transflectance were preprocessed to reduce multiplicative effects (MSC/SNV), to improve signal/noise ratio (smoothing using Savitzky-Golay), baseline correction (derived by Savitzky-Golay) and mean centered. Among the PLS calibration models constructed for the analyzes in nectars stood out the AA model for cashew¿s nectar (RMSEP= 4.8 mg/100g and RMSEC= 4.6 mg/100g) and AT for guava¿s nectar (RMSEP = 0.315% and RMSEC = 0.297%), the other models presented good values of R² (> 0.7) in addition to low values of RMSEP and RMSEC. Calibration models using NIR and MIR constructed to determine TA and TF in grape juice showed similar performance. MIR and NIR models for TA forecast RMSEP had low values (4,22mg / 100mL and 4,44mg / 100 mL, respectively) and for predicting TF, MIR presented a slightly smaller RMSEP than presented by NIR (2.12 EqAGmg/ml and 3.71 EqAGmg/mL, respectively). The RMSEP values found for all models built in this work show that spectroscopic analysis, NIR and MIR, can act as a substitute for traditional analyzes for quality control nectars and bioactive compounds in grape juice, with the advantages of being chemically green, fast and efficient, and do not require sample preparation, avoiding errors due to instability of the compounds evaluatedMestradoCiência de AlimentosMestra em Ciência de Alimentos145658/2014-72015/15848-0CNPQFAPES
Evaluation of vibrational and image analytical techniques associated with chemometrics for the quality control of high value foods
Orientador: Juliana Azevedo Lima PalloneTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia de AlimentosResumo: Métodos tradicionais (MT) empregados no controle de qualidade (CQ) de alimentos utilizam reagentes químicos, têm elevado custo e tempo de execução. Nesse contexto, a espectroscopia no infravermelho próximo e médio (NIR e MIR) e técnicas de imagem hiperespectral (NIR-HSI) e smartphone (SBI), são alternativas verdes aos MT. Sendo assim, objetivou-se avaliar o potencial de técnicas analíticas verdes associadas a quimiometria para CQ, aspectos nutricionais e bioativos de repolho roxo, polpa de açaí e arroz integral. Inicialmente, 60 amostras de repolho roxo tiveram os parâmetros relacionados aos compostos bioativos (antocianinas e polifenois totais, ORAC, DPPH e TEAC) determinados por MT, os espectros NIR e MIR coletados e os dados foram empregados para a obtenção de modelos de calibração multivariada. Os modelos de calibração construídos, baseados em NIR e MIR, apresentaram performance satisfatória na predição dos paramêtros avaliados. Para polpas de açaí, espectros de NIR e MIR também foram obtidos para verificar a possibilidade de utilização das técnicas para detecção de amostras adulteradas, com farinha de tapioca, mandioca, trigo e emulsificante. Determinou-se cartas de controle multivariada e modelos PLS-DA e KNN. Como resultado, ambas técnicas foram capazes de detectar amostras adulteradas com 100% de precisão através dos modelos PLS-DA. Além disso, 96 amostras de polpa de açaí liofilizadas foram utilizadas para obtenção de modelos PLS, baseados em NIR e SBI, para a determinação dos parâmetros bioativos obtidos através de MT. Os modelos PLS obtidos por NIR e SBI se mostraram satisfatórios para todos os parâmetros avaliados, com exceção do modelo ORAC-SBI. Em adição, verificou-se a possibilidade de utilização de minerais essenciais como marcadores de adulterações. Para essa fase do trabalho, polpa de açaí liofilizada autêntica e adulterada, com beterraba, suco de uva, maltodextrina, farinhas de tapioca e mandioca, tiveram os teores de Ca, Mn, Fe e K determinados por FAAS e baseado nesses valores foram construídos modelos de classificação por PLS-DA, OCPLS e SIMCA, onde obteve-se 90% de precisão na detecção de polpas adulteradas através do modelo OCPLS, demonstrando que a composição mineral pode ser útil para a detecção de fraudes em açaí. Na etapa seguinte, os teores de Ca, Mn, Fe e K, determinados via FAAS, de polpas de açaí liofilizadas e NIR foram utilizados para a construção de modelos PLS para predição indireta do teor desses minerais. Exceto para o Ca, os modelos obtidos por PLS apresentaram desempenho insatisfatório. A seleção de variáveis (iPLS) foi realizada, as porções do espectro selecionadas resultaram em modelos PLS satisfatórios para Mn, Fe e K. Amostras de arroz integral orgânico e convencional foram analisadas por instrumentos NIR-bancada, NIR-portátil e NIR-HSI, para a construção de modelos discriminativos entre os grãos. Todos modelos PLS-DA mostraram-se capazes de discriminar as amostras (85% de precisão), sendo o NIR-bancada a técnica de melhor desempenho. Sendo assim, foi possível concluir que as técnicas analíticas verdes, conhecidas como rápidas e não destrutivas, associadas a quimiometria, foram consideradas adequadas como alternativas para CQ, nutricional, bioativo e detecção de adulteração em alimentos diferentes alimentos de origem vegetal, com alto valor agregadoAbstract: Traditional methods (TM) applied in food quality control (QC) use chemical reagents, present high cost and time consuming. In this context, the near and mid infrared spectroscopy (NIR e MIR), hyperspectral imaging system (NIR-HSI) and smartphones (SBI) are green alternatives for TM. Therefore, it is intended to evaluate the potential of green analytical techniques associated to chemometric for QC, nutritional and bioactive aspects of red cabbage, açai pulp and brown rice. Initially, 60 red cabbage samples had parameters related to bioactive compounds (anthocyanins and phenolics content, ORAC, DPPH and TEAC) determined by TM, the NIR and MIR spectra collected and chemical data were implemented to obtain models of multivariate calibration. The calibration models built, based on NIR and MIR, provided satisfactory performance in the prediction of the evaluated parameters. Regard açaí pulp, NIR and MIR spectra were also obtained to verify the possibility of utilization of techniques that aimed to detect adulterated samples, with tapioca flour, cassava and wheat and emulsifier. It was stablished multivariate control charts and PLS-DA and KNN models. The outcome showed that both techniques were capable to detect adulterated samples with 100% precision through PLS-DA models. Furthermore, 96 freeze-dried açaí pulp samples were employed to obtain PSL models, based on NIR and SBI, in order to determined bioactive parameters acquired through TM. The PLS models collected by NIR and SBI had a satisfactory result to all the evaluated parameters, with an exception of ORAC-SBI model. In addition, it was found the possibility of the utilization of essential minerals as adulterations markers. In this stage, authentic and adulterated freeze-dried açaí pulp, with beet pulp, grape juice, maltodextrin, tapioca flour and cassava presented contents of Ca, Mn, Fe and K determined by FAAS and based on these amounts were built models of classification by PLS-DA, OCPLS and SIMCA, attaining 90% of precision on the detection of adulterated pulps via OCPLS model, revealing that the mineral composition can be useful to expose fraud in açai. In the next stage, the contents of Ca, Mn, Fe and K, determined by FAAS, of freeze-dried açai pulp samples and NIR were used to build PLS models for the indirect prediction of the content of these minerals. Except for Ca, the models acquired by PLS presented unsatisfactory performance. The selection of variables (iPLS) was executed, the portions of spectra selected resulted in satisfactory PLS models for Mn, Fe and K. Samples of organic and conventional brown rice were analyzed by NIR-benchtop, NIR-portable and NIR-HIS instruments, in order to build discriminative models among grains. All the PLS-DA models were able to discriminate the samples (85% of precision) and NIR-benchtop achieved the best performance. Accordingly, it was possible to conclude that green analytical techniques, known as fast and non-destructive, associated with chemometric, were considered suitable as alternatives for QC, nutritional, bioactive and detection of adulterations in different food of plant origin, with high value-addedDoutoradoCiência de AlimentosDoutora em Ciência de Alimentos142414/2016-62018/09759-3CNPQFAPES