4 resultados para principal component analysis (PCA)

em Universidad de Alicante


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Análisis multivariante de Componentes Principales (PCA)

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A combined chemometrics-metabolomics approach [excitation–emission matrix (EEM) fluorescence spectroscopy, nuclear magnetic resonance (NMR) and high performance liquid chromatography–mass spectrometry (HPLC–MS)] was used to analyse the rhizodeposition of the tritrophic system: tomato, the plant-parasitic nematode Meloidogyne javanica and the nematode-egg parasitic fungus Pochonia chlamydosporia. Exudates from M. javanica roots were sampled at root penetration (early) and gall development (late). EMM indicated that late root exudates from M. javanica treatments contained more aromatic amino acid compounds than the rest (control, P. chlamydosporia or P. chlamydosporia and M. javanica). 1H NMR showed that organic acids (acetate, lactate, malate, succinate and formic acid) and one unassigned aromatic compound (peak no. 22) were the most relevant metabolites in root exudates. Robust principal component analysis (PCA) grouped early exudates for nematode (PC1) or fungus presence (PC3). PCA found (PC1, 73.31 %) increased acetate and reduced lactate and an unassigned peak no. 22 characteristic of M. javanica root exudates resulting from nematode invasion and feeding. An increase of peak no. 22 (PC3, 4.82 %) characteristic of P. chlamydosporia exudates could be a plant “primer” defence. In late ones in PC3 (8.73 %) the presence of the nematode grouped the samples. HPLC–MS determined rhizosphere fingerprints of 16 (early) and 25 (late exudates) m/z signals, respectively. Late signals were exclusive from M. javanica exudates confirming EEM and 1H NMR results. A 235 m/z signal reduced in M. javanica root exudates (early and late) could be a repressed plant defense. This metabolomic approach and other rhizosphere -omics studies could help to improve plant growth and reduce nematode damage sustainably.

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Deformable Template models are first applied to track the inner wall of coronary arteries in intravascular ultrasound sequences, mainly in the assistance to angioplasty surgery. A circular template is used for initializing an elliptical deformable model to track wall deformation when inflating a balloon placed at the tip of the catheter. We define a new energy function for driving the behavior of the template and we test its robustness both in real and synthetic images. Finally we introduce a framework for learning and recognizing spatio-temporal geometric constraints based on Principal Component Analysis (eigenconstraints).