Uso da espectroscopia do infravermelho próximo e técnicas multivariadas para diferenciar escherichia coli e salmonella enteritidis inoculadas em polpa de fruta (abacaxi)

Aiming to consumer s safety the presence of pathogenic contaminants in foods must be monitored because they are responsible for foodborne outbreaks that depending on the level of contamination can ultimately cause the death of those who consume them. In industry is necessary that this identification be fast and profitable. This study shows the utility and application of near-infrared (NIR) transflectance spectroscopy as an alternative method for the identification and classification of Escherichia coli and Salmonella Enteritidis in commercial fruit pulp (pineapple). Principal Component Analysis (PCA), Independent Modeling of Class Analogy (SIMCA) and Discriminant Analysis Partial Least Squares (PLS-DA) were used in the analysis. It was not possible to obtain total separation between samples using PCA and SIMCA. The PLS-DA showed good performance in prediction capacity reaching 87.5% for E. coli and 88.3% for S. Enteritides, respectively. The best models were obtained for the PLS-DA with second derivative spectra treated with a sensitivity and specificity of 0.87 and 0.83, respectively. These results suggest that the NIR spectroscopy and PLS-DA can be used to discriminate and detect bacteria in the fruit pulp

Ferramentas quimiométricas aplicadas a classificação de amostras de leite em pó e quantificação de proteínas

In this work we used chemometric tools to classify and quantify the protein content in samples of milk powder. We applied the NIR diffuse reflectance spectroscopy combined with multivariate techniques. First, we carried out an exploratory method of samples by principal component analysis (PCA), then the classification of independent modeling of class analogy (SIMCA). Thus it became possible to classify the samples that were grouped by similarities in their composition. Finally, the techniques of partial least squares regression (PLS) and principal components regression (PCR) allowed the quantification of protein content in samples of milk powder, compared with the Kjeldahl reference method. A total of 53 samples of milk powder sold in the metropolitan areas of Natal, Salvador and Rio de Janeiro were acquired for analysis, in which after pre-treatment data, there were four models, which were employed for classification and quantification of samples. The methods employed after being assessed and validated showed good performance, good accuracy and reliability of the results, showing that the NIR technique can be a non invasive technique, since it produces no waste and saves time in analyzing the samples

Desenvolvimento, aperfeiçoamento e validação de método cromatográfico para previsão da qualidade e propriedades físico-químicas do óleo diesel tipo B

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Desenvolvimento de método analítico para estudo metabolômico de cana-de-açucar

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Caracterização da qualidade e interpretação das propriedades físico-químicas de gasolinas C brasileiras através de cromatografia gasosa e métodos quimiométricos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Metabolomic evaluation of interactions in rhizosphere between Senna spectabilis and associated microorganisms

Pós-graduação em Química - IQ

Estratégias de alimentação para a optimização do processo de produção de PHAs por via bacteriana

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Química e Bioquímica

Assessment of the discrimination of animal fat by FT_Raman spectroscopy

In recent years, there has been an increased attention towards the composition of feeding fats. In the aftermath of the BSE crisis all animal by-products utilised in animal nutrition have been subjected to close scrutiny. Regulation requires that the material belongs to the category of animal by-products fit for human consumption. This implies the use of reliable techniques in order to insure the safety of products. The feasibility of using rapid and non-destructive methods, to control the composition of feedstuffs on animal fats has been studied. Fourier Transform Raman spectroscopy has been chosen for its advantage to give detailed structural information. Data were treated using chemometric methods as PCA and PLS-DA which have permitted to separate well the different classes of animal fats. The same methodology was applied on fats from various types of feedstock and production technology processes. PLS-DA model for the discrimination of animal fats from the other categories presents a sensitivity and a specificity of 0.958 and 0.914, respectively. These results encourage the use of FT-Raman spectroscopy to discriminate animal fats.

Kohti vesiensuojelun aikaa; veden laadun muutokset eteläisimmällä Saimaalla

Työn tarkoituksena on ollut tutkia vesianalytiikan kehitystä Suomessa, arvioida rutiini-analytiikan luotettavuutta, selvittää eteläisimmän Saimaan jätevesikuormituksen kehitys ja siihen vaikuttaneet tekijät, laatia aikasarjat eräiden tutkimusalueen keskeisten veden laadun seurantapaikkojen veden laadun kehityksestä ja esittää keinoja veden laadun kehityksen kuvaa¬miseksi tiivistämällä suuri havaintomateriaali yksinkertaisiksi tunnusluvuiksi. Työssä käsiteltä¬vä aikajakso alkaa 1900-luvun alusta ja päättyy vuoteen 1998. Tutkimus on osa laajempaa ko¬konaisuutta. Tutkimusalue käsittää Vuoksen vesistön keskusjärven, Saimaan, eteläisimmät osat eli Pien-Saimaan, Suur-Saimaan, Vuoksen niskan ja Haapaveden altaat sekä vesistön purku¬-uoman, Vuoksen virran (ks. kuvat 5.1. ja 5.2.). Veden laatu alueen luonnontilaisilla alueilla on luokiteltavissa osin oligotrofiseksi, osin lievästi dysoligotrofiseksi. Sadan viimeisen vuoden aikana teollinen toiminta on muuttanut sitä voimakkaasti. Vesiensuojeluun on eteläisimmän Saimaan alueella investoitu yli 1,5 miljardia markka viimeisten noin 30 vuoden aikana. Investointien tuloksena kuormitus on laskenut oleellisesti 1960-luvun maksimikuormituksesta. Jätevesien purkuvesistön veden laatu on tänä aikana myös merkittävästi parantunut. Tämä on osoitettu veden laadun seurantatuloksista tehtyjen erilaisten tarkastelujen avulla (aikasarjadiagrammit, tilasto tarkastelut, indeksilukuluokitukset, PCA- ja PLS- ja DPLS- monimuuttujamallinnukset). Nykyisin veden laatu on lähes koko tutkimusalu¬eella vähintään tyydyttävä. Fysikaalis-kemiallisen veden laadun seurannan historia on Suomessa kansainvälisesti ja kansallisesti pitkä, ja Saimaalta voidaan veden laadun kehitystä arvioida luotettavasti 40 vuoden ajalta. Tutkimusmetodiikat vesitutkimusten pioneerimaissa ovat olleet samankaltaisia ja niiden perusteella on laadittu myös eurooppalaisen vedenlaadunseurannan suositukset. Vaikka tulevai¬suudessa vesistöä ja sen tilan kehitystä on tarkasteltava ekologisena kokonaisuutena, ei tätä voida tehdä ilman nykyisen kaltaista monitorointia. Teollisuuden jätevesikuormitus on laskenut neljännesvuosisadan aikana hyvin merkittä¬västi tavalla, joka vielä kymmenkunta vuotta sitten tuntui saavuttamattomalta. Saimaan. kuten muunkin Suomen metsäteollisuuden taso onkin kansainvälisesti korkea ja täyttää jo nyt kuormi¬tuksen suhteen lähes 2000-luvun alun BAT-tekniikan vaatimukset. Veden laatu ei kuitenkaan ole kuormitetuilla alueilla kaikkialla vielä hyvä, joten vesiensuojeluun on edelleen panostettava, kun tavoitteena on vesien hyvä ekologinen tila. Vesistöstä käsin tarkasteltuna hitaasti hajoavan orgaanisen aineen määrän vähentäminen vedestä on oltava seuraavana tavoitteena. Tätä tukee myös BAT-tekniikan tarkastelu.

Co-frangitura oliva e nocciola: Studio del prodotto

In recent times, the choices of consumers have been more conscious and oriented to foods with health benefits. The present paper deals with the study of oil from crushing of olive and huzelnut with the aim of obtaining a “functional food”. Different samples of oil derived from the crushing of olive (O), olive with 5% of hazelnut (O5N) and olive with 10% of hazelnut (O10N), exposed to different temperatures (28 and 35°C) and times (15 and 30 minutes) of malaxation. The samples of oil were initially subjected to a qualitative assessment by the analysis of peroxide and free acidity. Following further analyses were carried out namely the determination of fatty acids and triglycerides by FAST GC-FID, the determination of tocopherols by HPLC-FLC, the analysis of sterols by GC/MS and the spectroscopic analysis with FT-MIR combined with statistical analysis with PCA and PLS. The results showed that increasing the time and temperature of malaxation there aren’t relevant significant differences (p<0,05) in the composition of fatty acids, triglycerides and tocopherols in the different oils, but there are higher extraction yields. The increase of content of hazelnut in phase of crushing causes the decrease of triglycerides C50 and C52, the increase of the class C54, total tocopherols and of total sterols as well. The samples analysed with FT-MIR spectroscopy have showed, on the contrary to conventional analytical techniques, a good discrimination between different oils despite of the similar chemical composition of olive and hazelnuts. After the PLS models were built from spectra FT-MIR in order to estimate the content of triglycerides C50, C52 and C54 and total tocopherols, with good R2 in full cross validation (R2>0,821).

Impact of different cultivation methods on the metabolic profile of apples studied by 1H HR-MAS NMR spectroscopy

The cultivation of dessert apples has to meet the consumer's increasing demand for high fruit quality and a sustainable mostly residue-free production while ensuring a competitive agricultural productivity. It is therefore of great interest to know the impact of different cultivation methods on the fruit quality and the chemical composition, respectively. Previous studies have demonstrated the feasibility of High Resolution Magic Angle Spinning (HR-MAS) NMR spectroscopy directly performed on apple tissue as analytical tool for metabonomic studies. In this study, HR-MAS NMR spectroscopy is applied to apple tissue to analyze the metabolic profiles of apples grown under 3 different cultivation methods. Golden Delicious apples were grown applying organic (Bio), integrated (IP) and low-input (LI) plant protection strategies. A total of 70 1H HR-MAS NMR spectra were analyzed by means of principle component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). Apples derived from Bio-production could be well separated from the two other cultivation methods applying both, PCA and PLS-DA. Apples obtained from integrated (IP) and low-input (LI) production discriminated when taking the third PLS-component into account. The identified chemical composition and the compounds responsible for the separation, i.e. the PLS-loadings, are discussed. The results are compared with fruit quality parameters assessed by conventional methods. The present study demonstrates the potential of HR-MAS NMR spectroscopy of fruit tissue as analytical tool for finding markers for specific fruit production conditions like the cultivation method.

Chemotaxonomic relationships in Celastraceae inferred from principal component analysis (PCA) and partial least squares (PLS)

This paper describes a chemotaxonomic analysis of a database of triterpenoid compounds from the Celastraceae family using principal component analysis (PCA). The numbers of occurrences of thirty types of triterpene skeleton in different tribes of the family were used as variables. The study shows that PCA applied to chemical data can contribute to an intrafamilial classification of Celastraceae, once some questionable taxa affinity was observed, from chemotaxonomic inferences about genera and they are in agreement with the phylogeny previously proposed. The inclusion of Hippocrateaceae within Celastraceae is supported by the triterpene chemistry.

NIRS and iSPA-PLS for predicting total anthocyanin content in jaboticaba fruit

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Uso da espectroscopia de reflectância do infravermelho próximo (NIRS) para previsão da composição bromatológica de vagens de algaroba e palma forrageira.

Espécies forrageiras adaptadas às condições semiáridas são uma alternativa para reduzir os impactos negativos na cadeia produtiva de ruminantes da região Nordeste brasileira devido à sazonalidade na oferta de forragem, além de reduzir custo com o fornecimento de alimentos concentrados. Dentre as espécies, a vagem de algaroba (Prosopis juliflora SW D.C.) e palma forrageira (Opuntia e Nopalea) ganham destaque por tolerarem o déficit hídrico e produzirem em períodos onde a oferta de forragem está reduzida, além de apresentam bom valor nutricional e serem bem aceitas pelos animais. Porém, devido à variação na sua composição, seu uso na alimentação animal exige o conhecimento profundo da sua composição para a elaboração de dietas balanceadas. No entanto, devido ao custo e tempo para análise, os produtores não fazem uso da prática de análise da composição químico-bromatológica dos alimentos. Por isto, a espectroscopia de reflectância no infravermelho próximo (NIRS) representa uma importante alternativa aos métodos tradicionais. Objetivou-se com este estudo desenvolver e validar modelos de predição da composição bromatológica de vagem de algaroba e palma forrageira baseados em espectroscopia NIRS, escaneadas em dois modelos de equipamentos e com diferentes processamentos da amostra. Foram coletadas amostras de vagem de algaroba nos estados do Ceará, Bahia, Paraíba e Pernambuco, e amostras de palma forrageira nos estados do Ceará, Paraíba e Pernambuco, frescas (in natura) ou pré-secas e moídas. Para obtenção dos espectros utilizaram-se dois equipamentos NIR, Perten DA 7250 e FOSS 5000. Inicialmente os alimentos foram escaneados in natura em aparelho do modelo Perten, e, com o auxílio do software The Unscrambler 10.2 foi selecionado um grupo de amostras para o banco de calibração. As amostras selecionadas foram secas e moídas, e escaneadas novamente em equipamentos Perten e FOSS. Os valores dos parâmetros de referência foram obtidos por meio de metodologias tradicionalmente aplicadas em laboratório de nutrição animal para matéria seca (MS), matéria mineral (MM), matéria orgânica (MO), proteína bruta (PB), estrato etéreo (EE), fibra solúvel em detergente neutro (FDN), fibra solúvel em detergente ácido (FDA), hemicelulose (HEM) e digestibilidade in vitro da matéria seca (DIVMS). O desempenho dos modelos foi avaliado de acordo com os erros médios de calibração (RMSEC) e validação (RMSECV), coeficiente de determinação (R2 ) e da relação de desempenho de desvio dos modelos (RPD). A análise exploratória dos dados, por meio de tratamentos espectrais e análise de componentes principais (PCA), demonstraram que os bancos de dados eram similares entre si, dando segurança de desenvolver os modelos com todas as amostras selecionadas em um único modelo para cada alimento, algaroba e palma. Na avaliação dos resultados de referência, observou-se que a variação dos resultados para cada parâmetro corroboraram com os descritos na literatura. No desempenho dos modelos, aqueles desenvolvidos com pré-processamento da amostra (pré-secagem e moagem) se mostraram mais robustos do que aqueles construídos com amostras in natura. O aparelho NIRS Perten apresentou desempenho semelhante ao equipamento FOSS, apesar desse último cobrir uma faixa espectral maior e com intervalos de leituras menores. A técnica NIR, associada ao método de calibração multivariada de regressão por meio de quadrados mínimos (PLS), mostrou-se confiável para prever a composição químico-bromatológica de vagem de algaroba e da palma forrageira. Abstract: Forage species adapted to semi-arid conditions are an alternative to reduce the negative impacts in the feed supply for ruminants in the Brazilian Northeast region, due to seasonality in forage availability, as well as in the reducing of cost by providing concentrated feedstuffs. Among the species, mesquite pods (Prosopis juliflora SW DC) and spineless cactus (Opuntia and Nopalea) are highlighted for tolerating the drought and producion in periods where the forage is scarce, and have high nutritional value and also are well accepted by the animals. However, its use in animal diets requires a knowledge about its composition to prepare balanced diets. However, farmers usually do not use feed composition analysis, because their high cost and time-consuming. Thus, the Near Infrared Reflectance Spectroscopy in the (NIRS) is an important alternative to traditional methods. The objective of this study to develop and validate predictive models of the chemical composition of mesquite pods and spineless cactus-based NIRS spectroscopy, scanned in two different spectrometers and sample processing. Mesquite pods samples were collected in the states of Ceará, Bahia, Paraiba and Pernambuco, and samples of forage cactus in the states of Ceará, Paraíba and Pernambuco. In order to obtain the spectra, it was used two NIR equipment: Perten DA 7250 and FOSS 5000. sSpectra of samples were initially obtained fresh (as received) using Perten instrument, and with The Unscrambler software 10.2, a group of subsamples was selected to model development, keeping out redundant ones. The selected samples were dried and ground, and scanned again in both Perten and FOSS instruments. The values of the reference analysis were obtained by methods traditionally applied in animal nutrition laboratory to dry matter (DM), mineral matter (MM), organic matter (OM), crude protein (CP), ether extract (EE), soluble neutral detergent fiber (NDF), soluble acid detergent fiber (ADF), hemicellulose ( HEM) and in vitro digestibility of dry matter (DIVDM). The performance of the models was evaluated according to the Root Mean Square Error of Calibration (RMSEC) and cross-validation (RMSECV), coefficient of determination (R2 ) and the deviation of Ratio of performance Deviation of the models (RPD). Exploratory data analysis through spectral treatments and principal component analysis (PCA), showed that the databases were similar to each other, and may be treated asa single model for each feed - mesquite pods and cactus. Evaluating the reference results, it was observed that the variation were similar to those reported in the literature. Comparing the preprocessing of samples, the performance ofthose developed with preprocessing (dried and ground) of the sample were more robust than those built with fresh samples. The NIRS Perten device performance similar to FOSS equipment, although the latter cover a larger spectral range and with lower readings intervals. NIR technology associate do multivariate techniques is reliable to predict the bromatological composition of mesquite pods and cactus.

A chemometric study on the analgesic activity of cannabinoid compounds using SDA, KNN and SIMCA methods

The supervised pattern recognition methods K-Nearest Neighbors (KNN), stepwise discriminant analysis (SDA), and soft independent modelling of class analogy (SIMCA) were employed in this work with the aim to investigate the relationship between the molecular structure of 27 cannabinoid compounds and their analgesic activity. Previous analyses using two unsupervised pattern recognition methods (PCA-principal component analysis and HCA-hierarchical cluster analysis) were performed and five descriptors were selected as the most relevants for the analgesic activity of the compounds studied: R (3) (charge density on substituent at position C(3)), Q (1) (charge on atom C(1)), A (surface area), log P (logarithm of the partition coefficient) and MR (molecular refractivity). The supervised pattern recognition methods (SDA, KNN, and SIMCA) were employed in order to construct a reliable model that can be able to predict the analgesic activity of new cannabinoid compounds and to validate our previous study. The results obtained using the SDA, KNN, and SIMCA methods agree perfectly with our previous model. Comparing the SDA, KNN, and SIMCA results with the PCA and HCA ones we could notice that all multivariate statistical methods classified the cannabinoid compounds studied in three groups exactly in the same way: active, moderately active, and inactive.