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您的检索式：作者名="Francesco SUNSERI"
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| 1 | Genetic variation in eggplant for Nitrogen Use Efficiency under contrasting NO3^- supply显示文摘Eggplant(Solanum melongena L.) yield is highly sensitive to N fertilization, the excessive use of which is responsible for environmental and human health damage.Lowering N input together with the selection of improved Nitrogen-Use-Efficiency(NUE) genotypes, more able to uptake, utilize, and remobilize N available in soils, can be challenging to maintain high crop yields in a sustainable agriculture. The aim of this study was to explore the natural variation among eggplant accessions from different origins, in response to Low(LN) and High(HN)Nitrate(NO3^-) supply, to identify NUE-contrasting genotypes and their NUE-related traits, in hydroponic and greenhouse pot experiments. Two eggplants, AM222 and AM22, were identified as N-use efficient and inefficient,respectively, in hydroponic, and these results were confirmed in a pot experiment, when crop yield was also evaluated. Overall, our results indicated the key role of Nutilization component(NUt E) to confer high NUE. The remobilization of N from leaves to fruits may be a strategy to enhance NUt E, suggesting glutamate synthase as a key enzyme. Further, omics technologies will be used for focusing on C-N metabolism interacting networks. The availability of RILs from two other selected NUE-contrasting genotypes will allow us to detect major genes/quantitative trait loci related to NUE. | Antonio Mauceri Laura Bassolino Antonio Lupini Franz Badeck Fulvia Rizza Massimo Schiavi Laura Toppino Maria Rosa Abenavoli Giuseppe L.Rotino Francesco Sunseri | 2020 | Journal of Integrative Plant Biology2020，62，4： | 3 |
| 2 | High frequency of plant regeneration in sunflower from cotyledons via somatic embryogenesis显示文摘 | M. Carola Fiore Teresa Trabace Francesco Sunseri | 1997 | Plant Cell Reports1997，，5： | 1 |
| 3 | Genetic diversity in old populations of sessile oak from Calabria assessed by nuclear and chloroplast SSR显示文摘In the framework of forest resources conservation, this study aims to understand the dynamic and the genetic structure of sessile oak forests in Calabria, Italy. Two old populations of sessile oak(Quercus petraea(Mattuschka) Liebl.) from two areas of Sila and Aspromonte massifs in Calabria were analyzed for genetic diversity and population structure based on 6 nuclear simple sequence repeat(nSSR) and 4 chloroplastic SSR(cpSSR) loci. The populations displayed high amount of genetic diversity, which was toughly structured according to their geographical origins. Number of alleles at SSR loci ranged from 11 to 20 with an average of 13.5 per locus. Gene diversity(expected heterozygosity, He) estimates ranged from 0.575 to 0.834 with a mean of 0.749. The observed heterozygosity(Ho) was on average 0.458 ranging from 0.150 to 0.682. Polymorphism information content(PIC) values ranged from 0.625 to 0.865 with an average of 0.787. The analysis of molecular variance(AMOVA) highlighted a significant higher estimated variance within populations compared to among populations. Finally, the analysis of haplotypes by using cpSSR suggested a higher diversification in the population from Sila. Hierarchical clustering analysis grouped the genotypes into two major clusters, which agreed with the geographic origin of populations, and was confirmed by the Discriminant Analysis of Principal Components(DAPC). The first cluster included plants/population from Sila massif, while the second encompassed mostly plants/population sampled in Aspromonte massif. Finally, model-based clustering by STRUCTURE analysis also supported the presence of clear genetic structuring in the collection with two major populations(K=2) supported to PCoA analysis as well. Finally, our data indicated the Aspromonte population as a marginal forest with fragmented distribution suggesting different strategies of preservation than in Sila massif. | Antonio LUPINI Meriem Miyassa ACI Antonio MAUCERI Giuseppe LUZZI Silvio BAGNATO Giuliano MENGUZZATO Francesco MERCATI Francesco SUNSERI | 2019 | Journal of Mountain Science2019，16，5： | 0 |
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