Orientadores: Roy Edward Bruns, Ieda Spacino Scarminio / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Química / Made available in DSpace on 2018-08-26T07:44:37Z (GMT). No. of bitstreams: 1 Soares_DanielyXavier_D.pdf: 3162068 bytes, checksum: 54251cdb5d5253a933e10b93e4732324 (MD5) Previous issue date: 2014 / Resumo: "Planejamento e otimização de processos multirespostas: tratamento quimiométrico" Foram estudados três parâmetros cromatográficos: tempo de retenção, resolução e largura dos picos, em cromatogramas obtidos para uma mistura de onze agrotóxicos. Ajustes de modelos de regressão foram construídos e validados por ANOVA. Devido a sua simplicidade, os resultados obtidos para tempo de retenção foram usados em um programa interativo para estudar as separações como função de todo domínio experimental do planejamento simplex centróide. Um planejamento de misturas envolvendo três solventes (etanol, diclorometano e hexano) foi usado para avaliar a extração de alcalóides em Erythrina speciosa. Resultados diferentes foram observados para os extratos da flor, caule e folha, evidenciando que perfis de alcalóides distintos podem ser obtidos a partir de diferentes partes da planta. Modelos de regressão foram construídos e validados por ANOVA para dois alcalóides (tentativamente identificados por espectrometria de massas como eritrartina e 11-metoxi-erisodina, isóbaros em m/z 330, e erisotrina em m/z 314, com base em literatura prévia).A análise das componentes principais foi aplicada ao um conjunto de dados de absorbância de folhas de quatro cultivares de café (IPR-59, CAT, 027 e 083) obtidos entre 350-1100 nm por um espectroradiômetro portátil LI_COR 1800. Esta análise somente conseguiu discriminar espectros obtidos na face adaxial e abaxial das folhas. Como estes dados seguem um planejamento fatorial para quatro fatores (irrigação, estratos extremos, pontos cardeais e face) valores de efeitos foram determinados para absorbância em três comprimentos de onda estratégicos, 520, 554 e 650 nm, que são importantes para a quantificação de conteúdos de clorofilas e antocianinas / Abstract: "Design and multiresponse optimization of processes: chemometric treatment" Three chromatographic separation criteria were evaluated: retention time, resolution and peak width, in chromatograms obtained from a mixture of eleven pesticides. Regression models were constructed and validated by ANOVA. The use of the interactive program proved to be a valuable tool for studying peak separation behavior for the entire experimental domain of the simplex centroid design. Three solvents (ethanol, dichloromethane and hexane) and their binary and ternary mixtures were evaluated as extraction media for alkaloids in Erythrina speciosa. Different results were obtained between extracts of flowers, stems and leaves, showing that distinct alkaloid profiles can be obtained from different sources within the plant. Regression models were constructed and validated by ANOVA for two alkaloids (tentatively identified by MS as erytrartine and 11-methoxy-erisodine, isobaric ions of m/z 330, and erysothrine of m/z 314, based on previous literature). Principal component analysis was applied to data sets of absorbance values for leaves of four coffee cultivars (IPR-59, CAT, 027 and 083) obtained between 350 ¿ 1100 nm by a LI_COR 1800 portable radioespectrometer. This analysis was only able to discriminate between spectra of the abaxial and adaxial faces of the leaves. Since the spectral data were consistent with a factorial design for four factors (irrigated/field water, superior/inferior strata, cardinal points and face) effect values for absorbance were calculated at four strategic wavelengths, 520, 554 and 650 nm that are important for quantifying chlorophyll and anthocyanin contents of coffee / Doutorado / Quimica Analitica / Doutora em Ciências

La gélatine est un biopolymère naturel obtenu après dénaturation et hydrolyse partielle de fibres de collagène, une protéine fibrillaire présente dans les tissus conjonctifs de toutes les espèces du règne animal. Elle est utilisée dans différentes industries, parmi lesquelles l’industrie agroalimentaire, pharmaceutique, photographique et cosmétique. Ses propriétés fonctionnelles dépendent du procédé de fabrication, mais également de l’origine des matières collagéniques. L’objectif de ce travail de thèse est la caractérisation de la matière première (couennes de porc), mais également de la gélatine obtenue lors du processus, par une méthode rapide et non destructive. L’utilisation de la spectroscopie proche infrarouge couplée à des méthodes chimiométriques, a permis de travailler à l’échelle du laboratoire, mais également sur la chaîne de production industrielle. Le premier chapitre porte sur l’étude de l’hétérogénéité des couennes de porc au laboratoire, en termes de teneur en protéines, matières grasses, matières sèches et collagène. Plusieurs modèles ont pu être développés pour prédire ces teneurs, à partir de spectres proche infrarouge collectés sur des couennes en mouvement. Les meilleurs modèles présentent des performances compatibles avec une utilisation dans l’usine. Le second chapitre adapte cette méthode à l’échelle industrielle, c’est-à-dire à partir du rendement en gélatine fabriquée pour un lot de 75t de couennes. L’approche prédictive ne s’est pas avérée concluante, cependant des approches de classification ont montré leur intérêt. Les deux essais suivants ont porté sur la gélatine. Le troisième chapitre porte sur le développement de modèles de prédiction des propriétés physico-chimiques d’échantillons de gélatine à partir de spectres proche infrarouge, mettant en évidence de hautes capacités de prédiction de ces paramètres (r²>0,9). Enfin, ce chapitre propose de relier les caractéristiques moléculaires de la gélatine à ses propriétés physico-chimiques, par la technique de Asymmetrical Flow Field-Flow Fractionation couplée à un détecteur de diffusion de la lumière Multiangulaire (MALS). Les paramètres de caractérisation de l’AFlFFF-MALS permettent de discriminer partiellement des échantillons de gélatine dont les paramètres de bloom et de viscosité sont différents. / Gelatin is a natural biopolymer obtained after denaturation and partial hydrolysis of collagen fibers, a fibrillar protein present in the connective tissues of all species of the animal kingdom. It is used in various industries, including the agri-food, pharmaceutical, photographic and cosmetic industries. Its functional properties depend on the manufacturing process, but also on the origin of the collagenous materials. The objective of this thesis is to characterize the raw material (pig rind), but also the gelatin obtained during the process, by a fast and non-destructive tool. The use of near-infrared spectroscopy coupled with chemometric methods allowed us to work on the scale of the laboratory but also on the industrial chain. The first study examines the heterogeneity of pig rinds, under laboratory conditions, in terms of protein, fat, moisture and collagen contents. Several models have been developed to predict these levels, from near infrared spectra collected on moving rinds. The best models have good performances. In the second industrial scale trial, an approach to gelatin yield from 75 tons batches was proposed. The predictive approach has not been conclusive; however, classification approaches have shown interesting results. The next two tests were on gelatin. The third test allowed the development of models for predicting the physicochemical properties of gelatin samples from near-infrared spectra, demonstrating very good predictive capabilities of these parameters (r²> 0.9). Finally, a final test allowed to link the molecular characteristics of the gelatin to its physicochemical properties, by the technique of Asymmetrical Field-Flow Fractionation coupled with a Multiangular Light Scattering Detector (MALS). The characterization parameters of AFlFFF-MALS make it possible to partially discriminate gelatin samples with different bloom and viscosity parameters.

京都大学 / 0048 / 新制・課程博士 / 博士(農学) / 甲第19019号 / 農博第2097号 / 新制||農||1029(附属図書館) / 学位論文||H27||N4901(農学部図書室) / 31970 / 京都大学大学院農学研究科地域環境科学専攻 / (主査)教授 近藤 直, 教授 清水 浩, 准教授 小川 雄一 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DGAM

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Stamen from Paeonia ostii 'Fengdan Bai' and Paeonia rockii is rich in phenolic compounds and popularly used as tea materials with various pharmaceutical functions. In order to investigate whether stamen from other tree peony cultivars could be used as a natural antioxidant, the quality of stamen from thirty-five cultivars collected from the same garden was evaluated based on their phenolic composition and content by high-performance liquid chromatography analysis and in vitro antioxidant properties coupled with comprehensive chemometrics analysis. The results revealed that phenolic contents and antioxidant capacities of tree peony stamen were unique and cultivar dependent. Stamen from 'Zi Erqiao' exhibited the highest total phenolic and flavonol content, and strongest antioxidant activities, while that of 'Fengdan Bai' and P. rockii were at below-average levels among test samples. Further, thirty-seven cultivars of tree peony were divided into three major groups with a significant difference in total metabolites content and antioxidant properties, which were mainly contributed by six phytochemical compounds. Among these, naringin and benzoylpaeoniflorin were found to be critical chemical markers for the identification of tree peony stamen with high quality by chemometric analysis. Moreover, correlation analysis suggested that stamen from the earlier flowering cultivars with the hidden pistil, double petal, shorter thrum, more carpel and volume were possibly of higher quality. Together, cultivars with stamen enriched in phenolics and antioxidants properties, and their relevant critical phenotypic and phytochemical traits were screened out. This study would benefit the rapid identification of tree peony stamen with high quality and provide a valuable reference for its development and utilization as functional foods and pharmaceutical resources.

Metabolomics is a powerful science that can be applied for the discovery of disease biomarkers, and investigation of altered metabolomes due to abiotic and biotic perturbations. This dissertation is focused on untargeted metabolomic applications to investigate fungal metabolite alterations associated with pathogenicity, fungal disease propagations, and symbiosis. This dissertation employs qualitative analysis of metabolite mixtures using HS-SPME coupled GC-MS and TMS derivatization followed by GC-MS analytical platforms. In the first study, we discovered a biomarker combination to diagnose fungal soft tissue disease in sweet potato at an early stage of disease propagation. We used an HS-SPME GC-MS untargeted metabolomics workflow to analyze the VOC associated with Rhizopus stolonifer infected and healthy sweet potatoes in situ and simulated warehouse environments. A single combination of 4 biomarkers was able to diagnose R. stolonifer fungal soft tissue disease (AUC = 0.980, 95% C.I. 0.937-1) and the early stage of the fungal soft rot disease (AUC = 0.999, 95% C.I. 0.978-1). We were able to detect the biomarkers: 1- propanol, ethyl alcohol, ethyl propionate and 3-methyl-3- buten-1-ol during disease progression in a simulated warehouse environment. Therefore, this study shows the feasibility of early diagnosis of fungal soft tissue disease by a real-time screening of volatile profiles of sweet potato in post-harvest storage. When considering the study of a particular species metabolome, it is crucial to develop a metabolite extraction protocol. In the second study, the performance of the six different metabolite extraction solvents mixtures was tested with the preferred mix being: butanol:methanol:water (2:1:1, v/v at -20 °C) which was used as a single solvent mix to extract both polar and relatively non-polar metabolites simultaneously in a single extraction step. The Macrophomina phaseolina fungal metabolome was investigated using the solvent mix. Finally, fungal mutualism was studied using untargeted metabolomics. Most often mycorrhizal metabolomics workflows are based on analyzing the Arbuscular Mycorrhizae colonized root metabolome. But here, we used hyphal materials to examine the mutualistic symbiotic association of the AM fungi. All untargeted metabolomic studies included chemometric data analysis and specific biomarkers and or metabolites were determined using multivariate statistics or prediction model building and validating.

Indiana University-Purdue University Indianapolis (IUPUI) / Canines can detect different diseases simply by smelling different biological sample types, including urine, breath and sweat. This has led researchers to try and discovery unique volatile organic compound (VOC) biomarkers. The power of VOC biomarkers lies in the fact that one day they may be able to be utilized for noninvasive, rapid and accurate diagnostics at a point of care using miniaturized biosensors. However, the identity of the specific VOC biomarkers must be demonstrated before designing and fabricating sensing systems. Through an extensive series of experiments, VOCs in urine are profiled by solid phase microextraction (SPME) coupled to gas chromatography-mass spectrometry (GC-MS) to identify biomarkers for breast cancer using murine models. The results from these experiments indicated that unique classes of urinary VOCs, primarily terpene/terpenoids and carbonyls, are potential biomarkers of breast cancer. Through implementing chemometric approaches, unique panels of VOCs were identified for breast cancer detection, identifying tumor location, determining the efficacy of dopaminergic antitumor treatments, and tracking cancer progression. Other diseases, including COVID-19 and hypoglycemia (low blood sugar) were also probed to identify volatile biomarkers present in breath samples. VOC biomarker identification is an important step toward developing portable gas sensors, but another hurdle that exists is that current sensors lack selectivity toward specific VOCs of interest. Furthermore, testing sensors for sensitivity and selectivity is an extensive process as VOCs must be tested individually because the sensors do not have modes of chromatographic separation or compound identification. Another set of experiments is presented to demonstrate that SPME fibers can be coated with materials, used to extract standard solutions of VOCs, and analyzed by GC-MS to determine the performance of various gas sensing layers. In the first of these experiments, polyetherimide (PEI) was coated onto a SPME fiber and compared to commercial polyacrylate (PAA) fibers. The second experiment tuned the extraction efficiency of polyvinylidene fluoride (PVDF) - carbon black (CB) composites and showed that they had higher sensitivity for urinary VOC extraction relative to a polydimethylsiloxane (PDMS) SPME fiber. These results demonstrate SPME GC-MS can rapidly characterize and tune the VOC adsorption capabilities of gas sensing layers.

Thesis (MSc)--Stellenbosch University, 2013. / ENGLISH ABSTRACT: Wine fermentation is a continuously changing biological process whereby the raw product, grape juice is transformed into a high value product wine. In an ideal situation the fermentation kinetics of batch fermentations should follow the same trend over time. This however is not the case in industrial wine fermentations where significant batch-to-batch variation is present. The time trajectories of fermentation processes are therefore often unpredictable in absolute terms. The monitoring of substrate (sugar) and product concentrations (ethanol) as well as other quality parameters during a wine fermentation, is therefore of extreme importance to ensure effective control and management of wine fermentation processes. Conventional methods for fermentation monitoring are however costly, time consuming and often unreliable. For these reasons the modern wine industry requires rapid, reliable, non-destructive monitoring techniques which would meet the criteria of providing critical real-time process information that is displayed in easily interpretable graphical format, in order to ensure the highest quality and continuous consistency throughout all the stages of a process. This research study in particular, addressed the current need for alternative fermentation monitoring strategies that meet these criteria, by evaluating the potential use of spectroscopy as an analytical technique for fermentation monitoring. The overall objective of this study was to use chemometric modelling of information obtained by Fourier transform mid-infrared (FT-MIR) and near-infrared (FT-NIR) spectroscopy, to quantitatively and qualitatively monitor both alcoholic (AF) and malolactic fermentation (MLF) processes. Towards this objective 11 batch fermentations elaborated with Oenococcus oeni and Lactobacillus plantarum strains in respectively a co-inoculation and sequential inoculation scenario, were sampled and analysed at regular time intervals with FT-MIR and FT-NIR spectroscopy and enzymatic reference methods during 2011. Samples were also analysed by gas chromatography flame ionisation detection (GC-FID) and mass spectrometry (GC-MS) at two critical stages during fermentation, namely 50% completion of MLF and 100% completion of MLF, in order to obtain a profile of the evolution of the aroma compounds associated with each inoculation scenario. Three clearly defined research objectives were set for this project. The first objective involved the expansion of the existing quantitative platform for fermentation monitoring. Towards the outcomes of this objective, partial least squares (PLS) calibration models for prediction of malic acid and lactic acid in fermenting must and wines elaborated in our study, were established, based on the MIR and NIR spectra. The models showed excellent predictive abilities in independent test set validation. This outcome made a significant contribution to our existing PLS calibration capacity, particularly towards monitoring of MLF. Quantitative data obtained with the PLS models were also used to graphically project the rate of AF in the different batches, by non-linear fitted regression plots that easily visualised the overall patterns of sugar and ethanol metabolism in the different fermentations. The second research objective involved the qualitative monitoring of fermentations. This approach used FT-MIR and FT-NIR spectra together with chemometrics to identify trends between the different fermentation treatments. Principal component analysis (PCA) clearly projected the time trend from the onset of fermentation, through AF and MLF. No unique bacterial trend was however observed with spectroscopy. These results illustrate the potential of these techniques to be used for modelling of fermentations in industrial situations, through providing critical information about the evolution of the process. Furthermore, these techniques provide tools for identifying problematic and deviating fermentations. A spectral conformity test based on simple calculations of the standard deviation between the absorbance at each recorded wavenumber in the spectra, further confirmed identification of the critical fermentation stages. This technique by-passes the need for spectral interpretation and is a very useful addition, particularly from the industry perspective, to the portfolio of methods established in this study. The third research objective adressed the need to evaluate the possibility to discriminate between the different process stages and LAB treatments using univariate (ANOVA) and multivariate chemometric techniques such as PCA, PLS discriminant analysis (PLS-DA) and Soft Independent Modelling of Class Analogy (SIMCA) for possible future interpretative and classification purposes. The exploratory tool of PCA was used to investigate the similarities and differences between the chemical footprints of the different treatments. PCA showed clear differentiation between the two process stages using chemical quantified data. Differentiation between the LAB treatments was visible with PCA, showing a more prominent separation at 50% completion of MLF. Furthermore the ability of spectroscopy for potential classification was shown using PLS-DA and SIMCA. This profiling study can be seen as a preliminary study setting the ground work for further in-depth research into the profiling of different LAB treatments and inoculation strategies. / AFRIKAANSE OPSOMMING: Wyngisting is ‘n voortdurend veranderende biologiese proses waarvolgens die rou produk, druiwesap, in ‘n produk van hoë waarde, naamlik wyn, verander word. Onder ideale omstandighede sou die gistingskinetika van lotgistings dieselfde tendens oor tyd volg. Dit is egter nie die geval in industriële wyngistings nie, waar noemenswaardige wisseling van lot tot lot teenwoordig is. Die tydsbaan van gistingsprosesse is dus in baie gevalle in absolute terme onvoorspelbaar. Die monitering van substraat- (suiker) en produkkonsentrasies (etanol), sowel as ander kwaliteitsparameters tydens ‘n wyngisting, is van die uiterste belang om doeltreffende beheer en bestuur van wyngistingsprosesse te verseker. Konvensionele metodes vir die monitering van gisting is egter duur, tydrowend en ook soms onbetroubaar. Om hierdie redes vereis die moderne wynbedryf vinnige, betroubare en nie-destruktiewe moniteringstegnieke wat aan die kriteria sou voldoen vir die verskaffing van kritiese, intydse prosesinligting wat in ‘n maklik interpreteerbare grafiese formaat vertoon word om die hoogste kwaliteit en voortdurende konsekwentheid tydens al die stadia van ‘n proses te verseker. Hierdie navorsingstudie het in besonder die huidige behoefte aan alternatiewe gistingsmoniteringstrategieë wat aan hierdie kriteria voldoen, aangespreek deur die potensiële gebruik van spektroskopie as ‘n analitiese tegniek vir die monitering van gisting te evalueer. Die oorhoofse doelwit van hierdie studie was die chemometriese modellering van inligting wat met behulp van Fourier transform middel-infrarooi (FT-MIR) en naby-infrarooi (FT-NIR) spektroskopie verkry is om die prosesse van alkoholiese en appelmelksuurgisting (AMG) kwantitatief en kwalitatief te monitor. Ten einde hierdie doelwit te bereik, is 11 lotgistings met Oenococcus oeni en Lactobacillus plantarum rasse uitgevoer in scenario’s van ‘n gesamentlike inokulasie en opeenvolgende inokulasie onderskeidelik. Monsters van hierdie gistings is met gereelde tydintervalle in 2011 geneem en analises is met FT-MIR en FT-NIR spektroskopie en ensiematiese verwysingsmetodes gedoen. Monsters is ook met gaschromatografiese vlam ionisasie-opsporing (GC-FID) en massaspektrometrie (GC-MS) op twee kritiese stadia tydens gisting geanaliseer, naamlik toe AMG 50% en 100% voltooid was, om ‘n profiel te verkry van die evolusie van die aromaverbindings wat met elke inokulasie-scenario verband hou. Drie duidelik gedefinieerde navorsingsdoelwitte is vir hierdie studie bepaal. Die eerste doelwit het die uitbreiding van die bestaande kwantitatiewe platform vir gistingsmonitering behels. Hiervoor is gedeeltelike kleinstekwadraat [partial least squares (PLS)] kalibrasiemodelle vir die voorspelling van appelsuur en melksuur in die gistende mos en wyne in ons studie op die basis van MIR- en NIR-spektra bepaal. Die modelle het in onafhanklike geldigheidsbepaling van die toetsstel uitstekende voorspellingsvermoëns getoon. Hierdie uitkoms het ‘n noemenswaardige bydrae gemaak tot ons bestaande PLS kalibrasiekapasiteit, veral om AMG te monitor. Die kwantitatiewe data wat met die PLS-modelle verkry is, is ook gebruik om die tempo van alkoholiese gisting in die verskillende lotte grafies uit te beeld deur middel van kromlynige passing van regressiepersele, waarmee dit maklik was om die algehele patrone van suiker- en etanolmetabolisme in die verskillende gistings te visualiseer. Die tweede navorsingsdoelwit het die kwalitatiewe monitering van gistings behels. Hierdie benadering het FT-MIR en FT-NIR spektra tesame met chemometrie gebruik om tendense tussen die verskillende gistingsbehandelings te identifiseer. Hoofkomponentanalise [principal component analysis (PCA)] het duidelik die tydtendens vanaf die aanvang van gisting, deur alkoholiese gisting en AMG, geprojekteer. Geen unieke bakteriese tendens is egter met spektroskopie waargeneem nie. Hierdie uitslae illustreer die potensiaal van hierdie tegnieke om vir die modellering van gistings in industriële situasies gebruik te word deur kritiese inligting oor die evolusie van die proses te verskaf. Verder verskaf hierdie tegnieke gereedskap vir die identifikasie van problematiese en afwykende gistings. ‘n Spektrale gelykvormigheidstoets gebaseer op eenvoudige berekeninge van die standaardafwyking tussen die absorbansie by elke aangetekende golfgetal in die spektra het ook die identifikasie van die kritiese gistingstadia bevestig. Hierdie tegniek omloop die noodsaak vir spektrale interpretasie en is ‘n baie nuttige byvoeging tot die portefeulje van metodes wat in hierdie studie bepaal is, veral vanuit ‘n bedryfsperspektief. Die derde navorsingsdoelwit het die behoefte aangespreek om tussen die verskillende prosesstadia en melksuurbakterie-behandelings te onderskei deur gebruik te maak van eenvariant- (ANOVA) en meervariant- chemometriese tegnieke soos PCA, PLSdiskriminantanalise en sagte onafhanklike modellering van klasanalogie [soft independent modelling of class analogy (SIMCA)] vir moontlike toekomstige verklarende en klassifikasiedoeleindes. Die ondersoekende gereedskap van PCA is gebruik om ooreenkomste en verskille tussen die chemiese voetspore van die verskillende behandelings te ondersoek. PCA het duidelike differensiasie tussen die twee prosesstadia getoon op grond van chemies gekwantifiseerde data. Differensiasie tussen die melksuurbakterie-behandelings was met PCA sigbaar, met ‘n meer prominente skeiding teen 50% voltooide AMG. Verder is die vermoë van spektroskopie vir potensiële klassifikasie met PLS-diskriminantanalise en SIMCA getoon. Die profielsamestelling in hierdie studie kan beskou word as ‘n voorlopige studie vir verdere diepgaande navorsing oor die profielsamestelling van verskillende melksuurbakteriebehandelings en inokulasiestrategieë. / The National Research Foundation and Winetech

Made available in DSpace on 2017-07-21T18:53:17Z (GMT). No. of bitstreams: 1 RenatoGiovanettiVieira.pdf: 2405514 bytes, checksum: 4c0b0fdb3b6fde03a233806b54422c4a (MD5) Previous issue date: 2011-07-29 / The domestic market is represented by an apple production bivarietal, Fuji and Gala, accounting for more than 90% of the total result of the research to produce high quality fruit with low cost and favorable climate in Brazil. Evaluation of chemometric analysis performed on samples of juice during 20 years of these varieties also identified chemical profile pattern of Gala and Fuji. Other Brazilian commercial varieties were used to validate this pattern, with limits from 0.15 to 0.35 g/100 mL (malic acid), 9.00 to 15.00 g/100 mL (total reducing sugar) and 100 to 600 mg / L (phenolic compounds), which represent the tastes sour, sweet and bitter. But these limits are unsatisfactory to the fermented juice industry and, since the fruits are apples, table and those not categorized for this condition is then called industrial. Existing orchards in Brazil specifically have these varieties, but some apples on the market are similar, being tested to prove it. Among the 24 varieties tested, only five presented a profile similar to that proposed industrial levels of acidity and higher phenolic compounds, the remainder being classified as Brazilian trade. However, some research centers are evaluating the production of selections descendants of wild apples with higher acidity and phenolic compounds compared to the Gala and Fuji apples. With 24 selections descendants of these samples, generated from an experiment with the commercial variety rootstock Baroness and three wild varieties were compared with the limits of the profile of Gala and Fuji apples. In order to highlight the results and exploit them were made of principal components analysis (PCA) and hierarchical clustering (HCA) with Gala and Fuji. To validate these exploratory methods using SIMCA (Soft Independent Modeling of Class Analogy) and KNN (K-Nearest Neighbor) tried to predict which of these new classes were the selections that could fit into only Gala, only Fuji, Gala or Fuji or or Gala or Fuji. With the results obtained, was compared with the results of malic acid versus phenolic compounds versus the ratio (malic acid / total reducing sugar) versus phenolic compounds found in the literature. Among the 24 selections, 21 showed industrial profile. The industrial samples showed levels of phenolic compounds above 600 mg / L, malic acid and above 0.5 g/100 mL and 50% with total reducing sugar content above 14 g/100 mL. The remaining resembles the commercial standard, but with sizes and shapes unsuitable for table apples. With the improvement and creation of new varieties, specific to the industry, the production of noble apple products can add more value with higher returns. Through statistical analysis and chemometric data analysis of despectinized juice sample, it is possible to determine whether the raw material received by the processing industry should be destined for processing or fresh consumption, depending on the field of industry. / O mercado nacional de maçã é representado por uma produção bivarietal, Fuji e Gala, correspondendo por mais de 90% do total, consequência das pesquisas para produção de frutas de alta qualidade, com baixo custo e propícias para o clima brasileiro. A avaliação quimiométrica das análises realizadas em amostras de suco durante 20 anos dessas variedades possibilitou identificar o perfil químico padrão das maçãs Gala e Fuji. Utilizou-se outras variedades comerciais brasileiras para validar este padrão, tendo limites de 0,15 a 0,35 g/100 mL (ácido málico), de 9,00 a 15,00 g/100 mL (açúcar redutor total) e de 100 a 600 mg/L (compostos fenólicos), que representam os sabores ácido, doce e amargo. Porém estes limites são insatisfatórios para a indústria de sucos e fermentados, visto que as frutas são maçãs de mesa, e aquelas não categorizadas para esta condição são então denominadas industriais. Os atuais pomares no Brasil não possuem especificamente estas variedades, mas algumas maçãs disponíveis no mercado são similares, sendo testadas para comprovar isso. Dentre as 24 variedades testadas, somente cinco apresentaram perfil semelhante à proposta industrial com teores de acidez e compostos fenólicos mais elevados, sendo as demais enquadradas como comerciais brasileiras. Porém alguns centros de pesquisas estão avaliando a produção de seleções descendentes de maçãs silvestres com maior teor de acidez e compostos fenólicos comparadas às maçãs Gala e Fuji. Com 24 amostras dessas seleções descendentes, geradas a partir de um experimento com porta enxerto da variedade comercial Baronesa e três variedades silvestres, foram comparadas com os limites do perfil das maçãs Gala e Fuji. Com a finalidade de evidenciar os resultados e explorá-los foram feitas análises de Componentes Principais (PCA) e de Agrupamentos Hierárquicos (HCA) juntamente com Gala e Fuji. Para validar estes métodos exploratórios, utilizando SIMCA (Soft Independent Modeling of Class Analogy) e KNN (K-Nearest Neighbor), tentou predizer quais eram as classes dessas novas seleções que poderiam enquadrar-se em somente Gala, somente Fuji, Gala ou Fuji ou nem Gala nem Fuji. Com os resultados obtidos, foi feita a comparação com gráficos elaborados a partir de resultados de ácido málico versus compostos fenólicos e da razão (ácido málico/açúcar redutor total) versus compostos fenólicos, encontrados na literatura. Dentre as 24 seleções, 21 apresentaram perfil industrial. As amostras industriais apresentaram níveis de compostos fenólicos acima de 600 mg/L e ácido málico acima de 0,5 g/100 mL e 50% com teores de açúcar redutor total acima de 14 g/100 mL. As restantes assemelham-se ao padrão comercial, porém com tamanhos e formatos inadequados para maçãs de mesa. Com o melhoramento e criação de novas variedades, específicas para a indústria, a produção de produtos nobres da maçã pode agregar mais valor com rendimento maior. Por meio de análises estatísticas e quimiométricas de dados das análises de amostras de suco despectinizado, é possível determinar se a matéria-prima recebida pela indústria de processamento deve ser destinada para processamento ou para consumo in natura, dependendo da área de atuação da indústria.

La plupart des médicaments anticancéreux sont des substances à marge thérapeutique étroite, les erreurs médicamenteuses peuvent avoir des conséquences majeures pour les patients. Il est de la responsabilité pharmaceutique de garantir le bon médicament à la bonne dose par la mise en place d’un contrôle qualité des préparations avant administration. Par ailleurs, ces molécules potentiellement cancérogènes, mutagènes et reprotoxiques présentent un risque pour les personnes exposées notamment le personnel de santé. L’objectif de ce travail de thèse a été de développer des outils permettant d’optimiser la sécurité du circuit de ces médicaments anticancéreux à l’hôpital tant pour le patient que pour le personnel de santé. Des outils analytiques associés à des méthodes d’interprétation des données issues de la chimiométrie et de la gestion de risque ont été mis en œuvre afin de répondre à cette problématique.Dans le cadre de la sécurisation du personnel, la recherche de traces de molécules anticancéreuses dérivées du platine a permis de mettre en évidence les zones les plus contaminées. Sur la base de ces contaminations et des conditions de travail, une méthodologie d’analyse de risque multicritère a été développée pour évaluer le risque d’exposition du personnel. Face au risque encouru, différentes mesures correctives ont été envisagées et des études évaluant plus spécifiquement l’efficacité détergente des opérations de décontamination des surfaces et des flacons ont été menées.En parallèle, des essais visant à sécuriser les préparations avant administration ont été conduits sur deux molécules anticancéreuses : le 5-fluorouracile et la gemcitabine. Au regard de leur caractère non destructif, non invasif et de ce fait, plus sécurisé, les spectroscopies vibrationnelles Raman et proche infrarouge ont été explorées. Les données spectrales (zones spectrales et prétraitements) ont été optimisées par des analyses multivariées ComDim pour développer des modèles de régression PLS prédisant la concentration en principe actif en solution. Les résultats ont montré la faisabilité et la complémentarité des techniques de spectroscopie Raman et proche infrarouge pour la détermination quantitative des molécules anticancéreuses. / Most of the anticancer drugs are defined by a narrow therapeutic margin; therefore medical errors can have major consequences on patients. Thus, it’s necessary to guarantee the good drug at the good dose by the implementation of a quality control of the preparation before administration. These potentially carcinogenic, mutagenic or teratogenic drugs present a risk for exposed people especially healthcare workers.The aim of this study was to develop tools which can optimize the safety of the cytotoxic medication circuit in hospitals, for the patient as much as for healthcare workers. In order to respond to these problematics, analytical tools have been associated with different methods of data interpretation of chemometric and risk management.To improve healthcare workers’ safety, environmental monitoring looking for traces of platinum compound cytotoxic drugs were performed to identify the most contaminated areas. Based on these contaminations and working conditions, a methodology of multi-criteria risk analysis has been developed to quantify the risk of exposure of healthcare workers. Regarding the risk, various corrective measures were considered. Thus, studies based on the detergent efficiency of decontamination protocols used to clean workplace surfaces and cytotoxic vials were conducted.In parallel, assays were performed on two anticancer molecules to secure cytotoxic preparations before administration: 5-fluorouracile and gemcitabine. Regarding their non-destructive, non-invasive properties and therefore, more secured handling, Raman and near infrared spectroscopy were explored. Spectral data (spectral zones and pretreatments) were optimized by multivariate analyses ComDim to develop models of regression PLS predicting the concentration of the active ingredient in solution. Results showed the feasibility and the complementarity of these two spectroscopies in the quantitative determination of the cytotoxic drugs.These works participate in the continuous approach of quality assurance implemented in numerous health institutions. We hope that they will contribute to durably decrease risks associated to cytotoxic drugs for both patients and healthcare workers.