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| ZOU,Yu; MA,Kun; TIAN,Mixia. |
| Chemical composition and nutritive value of hot pepper seeds (Capsicum annuum) grown in Northeast Region of China were investigated. The proximate analysis showed that moisture, ash, crude fat, crude protein and total dietary fiber contents were 4.48, 4.94, 23.65, 21.29 and 38.76 g/100 g, respectively. The main amino acids were glutamic acid and aspartic acid (above 2 g/100 g), followed by histidine, phenylalanine, lysine, arginine, cysteine, leucine, tryptophan, serine, glycine, methionine, threonine and tyrosine (0.8-2 g/100 g). The contents of proline, alanine, valine and isoleucine were less than 0.8 g/100 g. The fatty acid profile showed that linoleic acid, palmitic acid, oleic acid, stearic acid and linolenic acid (above 0.55 g/100 g) as the most... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Hot pepper seed; Proximate composition; Amino acid composition; Fatty acid profile; Mineral element content. |
| Ano: 2015 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0101-20612015000400659 |
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| Zhang,Guangya; Ge,Huihua. |
| Background: Support vector machine (SVM), a novel powerful machine learning technology, was used to develop the non-linear quantitative structure-property relationship (QSPR) model of the G/11 xylanase based on the amino acid composition. The uniform design (UD) method was applied to optimize the running parameters of SVM for the first time. Results: Results showed that the predicted optimum temperature of leave-one-out (LOO) cross-validation fitted the experimental optimum temperature very well, when the running parameter C, ξ, and γ was 50, 0.001 and 1.5, respectively. The average root-mean-square errors (RMSE) of the LOO cross-validation were 9.53ºC, while the RMSE of the back propagation neural network (BPNN), was 11.55ºC. The... |
| Tipo: Journal article |
Palavras-chave: Amino acid composition; Optimum temperature; Support vector machine; Uniform design; Xylanase. |
| Ano: 2012 |
URL: http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-34582012000100007 |
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