4 resultados para Square Root of NOT
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2016
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ABSTRACT: BACKGROUND: Cassava (Manihot esculenta Crantz) storage root provides a staple food source for millions of people worldwide. Increasing the carotenoid content in storage root of cassava could provide improved nutritional and health benefits. Because carotenoid accumulation has been associated with storage root color, this study characterized carotenoid profiles, and abundance of key transcripts associated with carotenoid biosynthesis, from 23 landraces of cassava storage root ranging in color from white-to-yellow-to-pink. This study provides important information to plant breeding programs aimed at improving cassava storage root nutritional quality. RESULTS: Among the 23 landraces, five carotenoid types were detected in storage root with white color, while carotenoid types ranged from 1 to 21 in storage root with pink and yellow color. The majority of storage root in these landraces ranged in color from pale-to-intense yellow. In this color group, total ß-carotene, containing all-E-, 9-Z-, and 13-Z-ß-carotene isomers, was the major carotenoid type detected, varying from 26.13 to 76.72 %. Although no ?-carotene was observed, variable amounts of a ?-ring derived xanthophyll, lutein, was detected; with greater accumulation of ?-ring xanthophylls than of ß-ring xanthophyll. Lycopene was detected in a landrace (Cas51) with pink color storage root, but it was not detected in storage root with yellow color. Based on microarray and qRT-PCR analyses, abundance of transcripts coding for enzymes involved in carotenoid biosynthesis were consistent with carotenoid composition determined by contrasting HPLC-Diode Array profiles from storage root of landraces IAC12, Cas64, and Cas51. Abundance of transcripts encoding for proteins regulating plastid division were also consistent with the observed differences in total ß-carotene accumulation. CONCLUSIONS: Among the 23 cassava landraces with varying storage root color and diverse carotenoid types and profiles, landrace Cas51 (pink color storage root) had low LYCb transcript abundance, whereas landrace Cas64 (intense yellow storage root) had decreased HYb transcript abundance. These results may explain the increased amounts of lycopene and total ß-carotene observed in landraces Cas51 and Cas64, respectively. Overall, total carotenoid content in cassava storage root of color class representatives were associated with spatial patterns of secondary growth, color, and abundance of transcripts linked to plastid division. Finally, a partial carotenoid biosynthesis pathway is proposed.
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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.
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The evaluation of the maturation in apple orchards is checked using destructive methods, sampling fruits and analyzing them in the laboratory, making the process slow and expensive. The use of not destructive method to determine fruit maturation in the orchard could accelerate delivery of results and help in determining harvest time, because non-destructive data would allow to verify the maturation on different blocks in the orchard. The aim of this work was to chart fruit maturation in 'Maxi Gala' grafted on two different rootstocks, using destructive and not destructive methods. The non-destructive method used was the portable DA-Meter. The trial was realized at Vacaria, southern Brazillocated 28,44 S and 50,85 W. The samples were harvested on two orchards during the seasons 2014/15 and 2015/16, during six weeks before harvest from January until the second week of February. The sampling was realized in five different points of the orchard, on rootstocks M.9 or Marubakaido with M.9 interstem. Ten-apple samples were collected weekly in each point in the orchard and then evaluated by destructive method (flesh firmness, starch degradation, total soluble solids and acidity) and the not destructive method (DA-Meter). For both seasons, the evolution of the fruit maturation of Maxi Gala showed a similar progression for both rootstocks. The non-destructive method correlated well with the traditional destructive methods, making it a tool for more practical and easy determination of the harvest date.