Metaboloma parcial de raízes de genótipos de mandioca de mesa (Manihot esculenta Crantz), com ênfase nas frações amídicas e carotenóidicas, como ferramenta biotecnológica à avaliação da qualidade nutricional e de potencial de uso industrial

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro de Ciências Biológicas, Programa de Pós-Graduação em Biologia Vegetal, Florianópolis, 2013.A determinação do metaboloma parcial de raízes de genótipos de mandioca (Manihot esculenta Crantz) cultivados por agricultores familiares no estado de Santa Catarina - Brasil e conservados no bancode germoplasma da Epagri representa uma iniciativa inovadora e adequada, pois aprofunda o conhecimento sobre as peculiaridades metabólicas daqueles genótipos, contribuindo a uma caracterização mais detalhada do germoplasma. Esta abordagem subsidia a avaliação dopotencial das biomassas radiculares como fontes de compostos deinteresse nutricional à saúde humana. Assim, protocolos de análise dometaboloma de mandioca foram estabelecidos, com ênfase em genótiposcom polpa pigmentada e potencial uso industrial à produção de fécula.Para tal, uma plataforma analítica típica de estudos metabolômicos e.g.,LC, FTIR, UV-vis e DRX, associada a ferramentas de bioinformática,foi utilizada à análise do amido e frações (amilose e amilopectina), àdeterminação dos perfis carotenoídico e fenólico de amostras de dezacessos de mandioca. Os dados gerados revelam a existência degenótipos com constituições amídicas significativamente distintas. Astécnicas analíticas empregadas e os ensaios reológicos realizados,associados às analises quimiométricas (PCAs e clusters), possibilitaramdiscriminar os genótipos de acordo com as peculiaridades físicoquímicase funcionais da fração amídica, sugerindo potenciais de usoindustrial eventulamente discrepantes. Em uma segunda abordagem,considerando os conteúdos de metabólitos secundários, raízes degenótipos com polpa branca (Apronta mesa, Oriental, Salézio, Estação eCrioulo de Videira) apresentaram menores concentrações decarotenoides totais (1,38 ± 0,75 µg.g-1? 5,02 ± 1,27 µg.g-1),comparativamente ao genótipo com pigmentação rosada i.e., 169,8 ±17,9 µg.g-1. Genótipos de raízes amarelas (Pioneira, Amarela, Catarina eIAC-576-70) apresentaram conteúdo médio de 18,1 ± 3,31 µg.g-1 decarotenoides totais. A análise cromatográfica identificou os isômeros deposição cis-ß- e trans-ß-caroteno (majoritário), além de a-caroteno,luteína e ß-criptoxantina nos genótipos analisados, detectando apresença de licopeno somente no genótipo Rosada. Os conteúdosmédios de fenólicos totais em raízes frescas variaram de 32,59 ± 6,34µg.g-1 (IAC 576-70) a 128,32 ± 18,20 µg.g-1 (Rosada). A análisecromatográfica identificou os metabólitos: Epigalocatequina(majoritário), ácido gálico, quercetina, ácido clorogênico, ácido phidróxibenzóicoe epicatequina galato. Tomados em conjunto, osresultados obtidos podem ser empregados como ferramentas de apoioaos programas de melhoramento genético de mandioca assistidosbioquimicamente, otimizando o processo de seleção da diversidadegenética existente em bancos de germoplasma. Adicionalmente, osresultados enfatizam a importância da manutenção on farm destesgenótipos pelos agricultores familiares do sul do Brasil e em bancos degermoplasma, porque representam uma importante fonte de recursosfitogenéticos com características nutricionais e industriais promissoras. Abstract : The determination of the partial metabolome of cassava root (Manihotesculenta Crantz) of genotypes grown by family farmers in southernBrazil ( Santa Catarina state) and conserved at Epagri´s genebankrepresents an innovative and suitable strategy to gain insights as to theirmetabolic peculiarities. Such an approach also subsidizes the evaluationof the potential of those biomasses as sources of compounds withnutritional interest and industrial usage. Thus, this work developedprotocols for the metabolomic analysis of M. esculenta, focusing on tengenotypes with roots of pigmented flesh and claimed industrial potentialfor starch production. For that, the content and the physicochemicalproperties of the starch fraction and the carotenoid and phenolic profilesof the root samples were determined, by using a typical analyticalplatform of metabolomics studies, e.g., LC, FTIR, UV-vis, and XRD,associated to bioinformatic tools. Genotypes showed to differmeaningfully as to their starchy constitution. The chemical, rheological,and chemometrics analyzes (PCAs and clusters) allowed discriminatingthe studied genotypes according to the physicochemical and functionalproperties of their starch fractions, suggesting eventual distinctpotentials for industrial applications. In a second approach, the totalcontent of carotenoids showed to be lower in genotypes with whiteflesh roots (Apronta mesa, Oriental, Salézio, Estação and Crioulo deVideira - 1.38 ± 0.75 µg.g-1? 5.02 ± 1.27 µg.g-1) comparatively to redpigmented ones i.e., 169.8 ± 17.9 µg.g-1. Interestingly, in average,genotypes with yellow flesh roots (Pioneira, Amarela, Catarina, andIAC-576-70) showed to contain 18.1 ± 3.31 µg.g-1 of total carotenoids.Chromatographic analysis identified the positional isomers cis-ß- andtrans-ß-carotene (majoritary), as well as a-carotene, ß-cryptoxanthin,and lutein in all genotypes investigated and confirmed the presence oflycopene only for the Rosada genotype. In their turn, the mean values oftotal phenolic contents in fresh roots ranged from 32.59 ± 6.34 µg.g-1(IAC 576-70) to 128.32 ± 18.20 µg.g-1 (Rosada) and HPLC analysisidentified gallic acid, quercetin, epigallocatechin (majoritary),chlorogenic acid, ?-hydroxybenzoic acid, and epicatechin gallate as themain phenolic constituents of the cassava roots samples. Taken together,the results can support biochemically-assisted cassava breedingprograms, optimizing the process of selecting the genetic diversity in M.esculenta germplasm banks. Furthermore, the results emphasize theimportance of on farm maintenance of those genotypes, as well as oftheir germplasm banks, since they represent an important source ofgenetic resources with promising nutritional and industrial traits

UV-Vis and CIELAB based chemometric characterization of manihot esculenta carotenoid contents

Vitamin A deficiency is a prevalent health problem in many areas of the world, where cassava genotypes with high pro-vitamin A content have been identified as a strategy to address this issue. In this study, we found a positive correlation between the color of the root pulp and the total carotenoid contents and, importantly, showed how CIELAB color measurements can be used as a non-destructive and fast technique to quantify the amount of carotenoids in cassava root samples, as opposed to traditional methods. We trained several machine learning models using UV-visible spectrophotometry data, CIELAB data and a low-level data fusion of the two. Best performance models were obtained for the total carotenoids contents calculated using the UV-visible dataset as input, with R2 values above 90 %. Using CIELAB and fusion data, values around 60 % and above 90 % were found. Importantly, these results demonstrated how data fusion can lead to a better model performance for prediction when comparing to the use of a single data source. Considering all these findings, the use of colorimetric data associated with UV-visible and HPLC data through statistical and machine learning methods is a reliable way of predicting the content of total carotenoids in cassava root samples.To CNPq (National Counsel of Technological and Scientific Development) for financial support (Process n 407323/2013-9), to CAPES (Coordination for the Improvement of Higher Education Personnel (CAPES), and EPAGRI(AgriculturalResearchandRuralExtensionCompanyofSantaCatarina).Theresearchfellowshipfrom CNPqonbehalfofM.Maraschinisacknowledged.TheworkispartiallyfundedbyProjectPropMine,funded bytheagreementbetweenPortugueseFCT(FoundationforScienceandTechnology)andBrazilianCNPq.info:eu-repo/semantics/publishedVersio

Influence of solar radiation on the production of secondary metabolites in three rice (Oryza sativa) cultivars

Rice (Oryza sativa L.) is one of the most produced and consumed cereals worldwide and has its importance highlighted mainly in developing countries, where it plays a strategic economic and social role. Due to the importance of rice in the diet, its composition and nutritional characteristics are directly related to the health of the population. In the rice production systems, some climatic factors are determinants for the good performance of the crop, inducing the biosynthesis of primary and secondary metabolites. The present study determined the metabolic profiles through UV-visible spectrophotometry of leaf samples of three rice cultivars (Marques -- white, \\^Onix -- black, and Rubi -- red pericarp) throughout the rice's vegetative stages in two experimental times, from September to December 2015 and from January to April 2016. Solar radiation was recorded along the experimental period. To the organosolvent extracts of leaf samples, UV-vis spectrophotometric techniques were applied and the quantitative results of certain metabolites, e.g., chlorophylls, carotenoids, phenolics, flavonoids, and sugars, as well the antioxidant activity, which were analyzed by chemometrics tools. The results showed that biochemical parameters carotenoids, chlorophylls and sugars are more affected by the intensity of the radiation do que as vari\\'\a\veis phenolics, flavonoids and these alterations may be detected through statistical analysis of biochemical concentrations and UV-vis spectra.CAPES -Coordenação de Aperfeiçoamento de Pessoal de Nível Superior(407323/2013-9)info:eu-repo/semantics/publishedVersio

Discrimination of Brazilian propolis according to the seasoning using chemometrics and machine learning based on UV-Vis scanning data

Propolis is a chemically complex biomass produced by honeybees (Apis mellifera) from plant resins added of salivary enzymes, beeswax, and pollen. The biological activities described for propolis were also identified for donor plants resin, but a big challenge for the standardization of the chemical composition and biological effects of propolis remains on a better understanding of the influence of seasonality on the chemical constituents of that raw material. Since propolis quality depends, among other variables, on the local flora which is strongly influenced by (a)biotic factors over the seasons, to unravel the harvest season effect on the propolis chemical profile is an issue of recognized importance. For that, fast, cheap, and robust analytical techniques seem to be the best choice for large scale quality control processes in the most demanding markets, e.g., human health applications. For that, UV-Visible (UV-Vis) scanning spectrophotometry of hydroalcoholic extracts (HE) of seventy-three propolis samples, collected over the seasons in 2014 (summer, spring, autumn, and winter) and 2015 (summer and autumn) in Southern Brazil was adopted. Further machine learning and chemometrics techniques were applied to the UV-Vis dataset aiming to gain insights as to the seasonality effect on the claimed chemical heterogeneity of propolis samples determined by changes in the flora of the geographic region under study. Descriptive and classification models were built following a chemometric approach, i.e. principal component analysis (PCA) and hierarchical clustering analysis (HCA) supported by scripts written in the R language. The UV-Vis profiles associated with chemometric analysis allowed identifying a typical pattern in propolis samples collected in the summer. Importantly, the discrimination based on PCA could be improved by using the dataset of the fingerprint region of phenolic compounds ( = 280-400m), suggesting that besides the biological activities of those secondary metabolites, they also play a relevant role for the discrimination and classification of that complex matrix through bioinformatics tools. Finally, a series of machine learning approaches, e.g., partial least square-discriminant analysis (PLS-DA), k-Nearest Neighbors (kNN), and Decision Trees showed to be complementary to PCA and HCA, allowing to obtain relevant information as to the sample discrimination.Financial support and the research fellowship to the later author from CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico) are acknowledged. The work is partially funded by Project PropMine, funded by the agreement between Portuguese FCT and Brazilian CNPq. The authors also thank the FCT Strategic Project of UID/BIO/04469/2013 uni

Metabolomics combined with chemometric tools (PCA, HCA, PLS-DA and SVM) for screening cassava (Manihot esculenta Crantz) roots during postharvest physiological deterioration

Cassava roots are an important source of dietary and industrial carbohydrates and suffer markedly from postharvest physiological deterioration (PPD). This paper deals with metabolomics combined with chemometric tools for screening the chemical and enzymatic composition in several genotypes of cassava roots during PPD. Metabolome analyses showed increases in carotenoids, flavonoids, anthocyanins, phenolics, reactive scavenging species, and enzymes (superoxide dismutase family, hydrogen peroxide, and catalase) until 3–5 days postharvest. PPD correlated negatively with phenolics and carotenoids and positively with anthocyanins and flavonoids. Chemometric tools such as principal component analysis, partial least squares discriminant analysis, and support vector machines discriminated well cassava samples and enabled a good prediction of samples. Hierarchical clustering analyses grouped samples according to their levels of PPD and chemical compositions.We are thankful to PEC-PG ("Programa de Estudantes Convenio de Pos-Graduacao") coordinated by CAPES ("Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior") for fully-funded studentship. We are also grateful to Professor Bryan A. Hanson (DePauw University, Department of Chemistry and Biochemistry, Greencastle, Indiana, USA) for his valuable help in ChemoSpec package and R software data mining. Marcelo Maraschin thanks to CNPq for the research productivity fellowship

Carotenoid analysis of Cassava genotypes roots (Manihot Esculenta Crantz) cultivated in Southern Brazil using chemometric tools

Manihot esculenta roots rich in -carotene are an important staple food for populations with risk of vitamin A deficiency. Cassava genotypes with high pro-vitamin A activity have been identified as a strategy to reduce the prevalence of deficiency of this vitamin, In this study, the metabolomics characterization focusing on the carotenoid composition of ten cassava genotypes cultivated in southern Brazil by UV-visible scanning spectrophotometry and reverse phase-high performance liquid chromatography was performed. The data set was used for the construction of a descriptive model by chemometric analysis. The genotypes of yellow roots were clustered by the higher concentrations of cis--carotene and lutein. Inversely, cream roots genotypes were grouped precisely due to their lower concentrations of these pigments, as samples rich in lycopene differed among the studied genotypes. The analytical approach (UV-Vis, HPLC, and chemometrics) used showed to be efficient for understanding the chemodiversity of cassava genotypes, allowing to classify them according to important features for human health and nutrition.(undefined

Data supporting the role of enzymes and polysaccharides during cassava postharvest physiological deterioration

This data article is referred to the research article entitled The role of ascorbate peroxidase, guaiacol peroxidase, and polysaccharides in cassava (Manihot esculenta Crantz) roots under postharvest physiological deterioration by Uarrota et al. (2015). Food Chemistry 197, Part A, 737746. The stress duo to PPD of cassava roots leads to the formation of ROS which are extremely harmful and accelerates cassava spoiling. To prevent or alleviate injuries from ROS, plants have evolved antioxidant systems that include non-enzymatic and enzymatic defence systems such as ascorbate peroxidase, guaiacol peroxidase and polysaccharides. In this data article can be found a dataset called newdata, in RData format, with 60 observations and 06 variables. The first 02 variables (Samples and Cultivars) and the last 04, spectrophotometric data of ascorbate peroxidase, guaiacol peroxidase, tocopherol, total proteins and arcsined data of cassava PPD scoring. For further interpretation and analysis in R software, a report is also provided. Means of all variables and standard deviations are also provided in the Supplementary tables (data.long3.RData, data.long4.RData and meansEnzymes.RData), raw data of PPD scoring without transformation (PPDmeans.RData) and days of storage (days.RData) are also provided for data analysis reproducibility in R software.CNPq -Conselho Nacional de Desenvolvimento Científico e Tecnológic

UV-visible scanning spectrophotometry and chemometric analysis as tools for carotenoids analysis in cassava genotypes (Manihot esculenta Crantz)

In this study, the metabolomics characterization focusing on the carotenoid composition of ten cassava (Manihot esculenta) genotypes cultivated in southern Brazil by UV-visible scanning spectrophotometry and reverse phase-high performance liquid chromatography was performed. Cassava roots rich in -carotene are an important staple food for populations with risk of vitamin A deficiency. Cassava genotypes with high pro-vitamin A activity have been identified as a strategy to reduce the prevalence of deficiency of this vitamin. The data set was used for the construction of a descriptive model by chemometric analysis. The genotypes of yellow-fleshed roots were clustered by the higher concentrations of cis--carotene and lutein. Inversely, cream-fleshed roots genotypes were grouped precisely due to their lower concentrations of these pigments, as samples rich in lycopene (redfleshed) differed among the studied genotypes. The analytical approach (UV-Vis, HPLC, and chemometrics) used showed to be efficient for understanding the chemodiversity of cassava genotypes, allowing to classify them according to important features for human health and nutrition.FAPESC (Fundação de Amparo à Pesquisa e Inovação do Estado de Santa Catarina) and CNPq (Conselho Nacional de Desenvolvimento Cientıfico e Tecnologico) for financial support. The research fellowship from CNPq on behalf of the last author is acknowledged. The work is partially funded by Project PropMine, funded by the agreement between Portuguese FCT and Brazilian CNPq. The authors also thank the FCT Strategic Project of UID/BIO/04469/2013 uni