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Evaluation of fruit and seed diversity and characterization of carob (Ceratonia siliqua L.) cultivars in Algarve region
Authors:P Barracosa  J Osório  A Cravador
Institution:1. Departamento de Produção Vegetal, Escola Superior Agrária de Viseu – ISPV, Quinta da Alagoa – Ranhados, 3500-Viseu, Portugal;2. Universidade do Algarve-FERN, Campus de Gambelas, 8005-139 Faro, Portugal
Abstract:The genetic diversity of 15 carob (Ceratonia siliqua L.) cultivars located in an experimental field from Algarve (Portugal) was evaluated over 7 years using 12 fruit and seed phenotypic characters, in order to characterize carob cultivars. The values of morphological traits obtained by cultivar were compared with those from other countries of the Mediterranean basin. Statistically significant differences were found between cultivars for all characters which were examined, what indicates a high genetic diversity. The relationship among these characters was analyzed by principal component analysis (PCA) resulting in the separation of these cultivars classed in four groups (clusters I–IV) and in four ungrouped cultivars. A three dimension of the model was found to be significant and explained 74.5% of the total variation, in which the first component accounting for 34.6% of the total variation is dominated by fruit characters, while the second component is dominated by seed characters. Cultivars plotted on the left-lower quadrant on the space determined by principal components 1 and 2 are characterized by fruits with high seed yield more appropriated for industrial rentability. The correlation analyses established by cultivar provided a specific understanding about the way how fruit and seed characteristics correlate within each cultivar. This approach can be useful for the development of a breeding programme, aiming to increase the seed yield, seed thickness, individual and total seed weight by fruit, characteristics that are determinant to improve the industrial exploitation of carob.
Keywords:Carob  Cultivars  Morphological diversity  Principal component analysis  Correlation analysis
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