RESUMO
Carotenoids are an essential component of cashew and can be used in pharmaceuticals, cosmetics, natural pigment, food additives, among other applications. The present work focuses on optimizing and comparing conventional and ultrasound-assisted extraction methods. Every optimization step took place with a 1:1 (w:w) mixture of yellow and red cashew apples lyophilized and ground in a cryogenic mill. A Simplex-centroid design was applied for both methods, and the solvents acetone, methanol, ethanol, and petroleum ether were evaluated. After choosing the extractor solvent, a central composite design was applied to optimize the sample mass (59-201 mg) and extraction time (6-34 min). The optimum conditions for the extractor solvent were 38% acetone, 30% ethanol, and 32% petroleum ether for CE and a mixture of 44% acetone and 56% methanol for UAE. The best experimental conditions for UAE were a sonication time of 19 min and a sample mass of 153 mg, while the CE was 23 min and 136 mg. Comparing red and yellow cashews, red cashews showed a higher carotenoid content in both methodologies. The UAE methodology was ca. 21% faster, presented a more straightforward composition of extracting solution, showed an average yield of superior carotenoid content in all samples compared to CE. Therefore, UAE has demonstrated a simple, efficient, fast, low-cost adjustment methodology and a reliable alternative for other applications involving these bioactive compounds in the studied or similar matrix.
Assuntos
Anacardium , Carotenoides , Metanol , Solventes , UltrassomRESUMO
Calcium (Ca) and potassium (K) are essential nutrients in animal nutrition. Furthermore, the Ca content can influence meat tenderness because it is needed by the proteolytic system of calpains and calpastatins, major factors in postmortem tenderization of skeletal muscles. K content, which is needed for muscle contraction, can also affect meat tenderness. This study showed that K positively affects the Warner-Bratzler shear force (WBSF), measured at 14days of meat aging, which means that higher levels of K are related to lower meat tenderness. Additionally, a significant effect (P≤0.015) of a SNP in the calcium-activated neutral protease 1 (CAPN1) gene on Ca content was observed. Metal content in beef can affect not only nutritional values but also meat quality traits. Part of this effect may be related to variation in specific genes.
Assuntos
Cálcio/análise , Carne/análise , Potássio/análise , Fenômenos Fisiológicos da Nutrição Animal , Animais , Biomarcadores , Proteínas de Ligação ao Cálcio/genética , Proteínas de Ligação ao Cálcio/metabolismo , Calpaína/genética , Calpaína/metabolismo , Bovinos , Manipulação de Alimentos , Variação Genética , Genótipo , Proteínas Musculares/genética , Proteínas Musculares/metabolismo , Músculo Esquelético/química , Fenótipo , Polimorfismo de Nucleotídeo ÚnicoRESUMO
Laser induced breakdown spectroscopy (LIBS) is an atomic emission spectroscopy technique for simple, direct and clean analysis, with great application potential in environmental sustainability studies. In a single LIBS spectrum it is possible to obtain qualitative information on the sample composition. However, quantitative analysis requires a reliable model for analytical calibration. Multilayer perceptron (MLP), an artificial neural network, is a multivariate technique that is capable of learning to recognize features from examples. Therefore MLP can be used as a calibration model for analytical determinations. Accordingly, the present study proposes to evaluate the traditional linear fit and MLP models for LIBS calibration, in order to attain a quantitative multielemental method for contaminant determination in soil under sewage sludge application. Two sets of samples, both composed of two kinds of soils were used for calibration and validation, respectively. The analyte concentrations in these samples, used as reference, were determined by a reference analytical method using inductively coupled plasma optical emission spectrometry (ICP OES). The LIBS-MLP was compared to a LIBS-linear fit method. The values determined by LIBS-MLP showed lower prediction errors, correlation above 98% with values determined by ICP OES, higher accuracy and precision, lower limits of detection and great application potential in the analysis of different kinds of soils.