Persona: Monago Maraña, Olga
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Monago Maraña
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Publicación Characterization of the metabolic profile of olive tissues (roots, stems and leaves): relationship with cultivars' resistance/susceptibility to the soil fungus Verticillium dahliae.(MDPI, 2023-12-15) Serrano García, Irene; Olmo García, Lucía; Muñoz Cabello de Alba, Iván; León, Lorenzo; Rosa Navarro, Raúl de la; Serrano, Alicia; Gómez Caravaca, Ana María; Carrasco Pancorbo, Alegría; Monago Maraña, OlgaVerticillium wilt of olive (VWO) is one of the most widespread and devastating olive diseases in the world. Harnessing host resistance to the causative agent is considered one of the most important measures within an integrated control strategy of the disease. Aiming to understand the mechanisms underlying olive resistance to VWO, the metabolic profiles of olive leaves, stems and roots from 10 different cultivars with varying levels of susceptibility to this disease were investigated by liquid chromatography coupled to mass spectrometry (LC-MS). The distribution of 56 metabolites among the three olive tissues was quantitatively assessed and the possible relationship between the tissues’ metabolic profiles and resistance to VWO was evaluated by applying unsupervised and supervised multivariate analysis. Principal component analysis (PCA) was used to explore the data, and separate clustering of highly resistant and extremely susceptible cultivars was observed. Moreover, partial least squares discriminant analysis (PLS-DA) models were built to differentiate samples of highly resistant, intermediate susceptible/resistant, and extremely susceptible cultivars. Root models showed the lowest classification capability, but metabolites from leaf and stem were able to satisfactorily discriminate samples according to the level of susceptibility. Some typical compositional patterns of highly resistant and extremely susceptible cultivars were described, and some potential resistance/susceptibility metabolic markers were pointed out.Publicación Monitoring of chlorophylls during the maturation stage of plums by multivariate calibration of RGB data from digital images(MDPI, 2022-12-22) Domínguez Manzano, Jaime; Muñoz de la Peña, Arsenio; Durán Merás, Isabel; Monago Maraña, OlgaThe methodology developed in this study was based on digital imaging processing of plums harvested in eight different weeks during their ripening process. Mean RGB data, histograms, and matrices of RGB data were used to characterise the ripening stage of the plums, in both qualitative and quantitative approaches, by using classification and quantification chemometric methods. An exploratory analysis of data was performed using principal component analysis (PCA) and parallel factor analysis (PARAFAC) in RGB histograms and matrices data, respectively, showing differences in the colour features since the fourth week of harvesting. In the case of the quantitative approach, high correlation was achieved between the histogram data, using partial least squares (PLS), and total chlorophyll content. In addition, between three-way matrixes and total chlorophyll content, good correlations were obtained applying unfolded-PLS (U-PLS) and N-way-PLS (N-PLS). The most accurate results were obtained on the green channel. Analytical parameters obtained were good, with determination coefficients (R2) higher than 0.91 for all models in the first and second-order multivariate analysis. In addition, relative errors of prediction (REPs) were lower than 12% in all models for the green channel. Therefore, the proposed method was a satisfactory alternative to destructive physiological and biochemical methods in the determination of total chlorophylls in plum samples. In the routine analysis, first-order multivariate calibration with PLS analysis is a good option due to the simplicity of data processing.Publicación Acrylamide-fat correlation in californian-style black olives using near-infrared spectroscopy(MDPI, 2023-09-06) Montero Fernández, Ismael; Martín Tornero, Elísabet; Martín Vertedor, Daniel; Fernández Fernández, Antonio; Monago Maraña, OlgaCalifornian-style is one of the most important black table olive elaborations. During its processing, table olives produce acrylamide, a potential carcinogen compound generated during sterilization. In the present study, total fat and acrylamide content in Californian-style table olives were determined and a regression between them was performed (acrylamide concentration range: below limit of detection—2500 ng g−1 and 8–22% for total fat). Nowadays, there are fast and efficient new techniques, such as Near-Infrared Spectroscopy (NIRS) to measure fat content parameters. In that sense, NIRS was used to perform a fat content quantification model in olives in order to indirectly determine acrylamide content. Calibration models for fat quantification were obtained in defatted olive pastes from a unique variety and for olive pastes from different varieties. In the first case, best results were obtained since only one variety was used (R2 = 0.9694; RMSECV = 1.31%; and REP = 8.4%). However, in the second case, results were still acceptable R2 = 0.678, RMSECV = 2.3%, REP = 17.7% and RMSEV = 2.17%. Regression coefficients showed the most influence variables corresponded with fat. The determination coefficient for the fat and acrylamide correlation was high (r = 0.877), being an efficient approach to find out the contribution of fat degradation to acrylamide synthesis in table olives.