Analysis of Diterpens in Green and Roasted Coffee of Coffea arabica Cultivars Growing in the Same Edapho-Climatic Conditions.

Lipids are important components of coffee beverage flavor and aroma. Coffee oil is rich in diterpens of the kaurane family, mainly cafestol (C20H28O3) and kahweol (C20H26O3), which have increasingly received attention in recent years due to their physiological effects in human health. However, few studies have been conducted on the effects of the genetic variability for those lipids in Coffea arabica. In this work we initiate the characterization of cafestol and kahweol in different cultivars of Coffea arabica, growing in the same edaphoclimatic conditions. Mature coffee fruits from cultivars Catuaí, Icatu and three Catucaí derived the cultivars IPR 100, IPR 102 and IPR 106. They were harvested at the Agricultural Field Station of the Coop COCARI, Mandaguari, Paraná, Brazil, from May to July 2009. Although the time of harvesting was according to the maturation of each cultivar, harvesting and post-harvesting conditions were the same for all cultivars. The five samples were subjected to medium roasting for 8 to 11 minutes at 200-210 °C, until the degree of roasting light/media (L* around 28). The extraction of diterpens was carried out in green or roasted coffee by direct saponification with KOH, extraction with terc-butyl methyl ether, and clean up with water. A reverse-phase HPLC column with isocratic elution with acetonitrile/water (55/45 v/v) was used for detection and quantification of kahweol at 290 nm and cafestol at 220 nm. In green beans, the level of kahweol was higher than cafestol, for all three IPR cultivars. Meanwhile, the inverse was observed for green beans cultivars Catuaí and Icatu, where cafestol levels were higher than kahweol. The higher levels of kahweol in relation to cafestol were again observed in roasted coffee of the three IPR cultivars. In cultivars Icatu the values for kahweol and cafestol were similar (635 and 683 mg/100 g, respectively). The highest levels of kahweol were observed in cultivar IPR 106 (1096 mg/100 g). The cultivar IPR 102 showed the highest level of cafestol (394 mg/100g). Association of this data with gene expression profile can be useful to find genes involved in cafestol and kahweol metabolism as well as to develop molecular markers for diterpens in coffee

In silico analysis of cytochrome p450 genes involved in the metabolism of diterpenes in Coffea.

Brazil is the largest world producer and exporter of coffee, being also the second largest consumer market. Among the main goals of coffee breeders, studies aiming the improvement of cup quality and plant tolerance to biotic and abiotic stresses have extreme importance. Beverage nutraceutical properties and plant defense mechanisms are directly linked to diterpenes present in the lipid fraction of coffee beans, such as cafestol (Caf ) and caveol (Cav). Many members of P 450 gene family are involved in plant secondary metabolism, including diterpenes synthesis. In order to depict biochemical and genetic aspects of diterpenes byosinthesis, we did an in silico characterization of p450 gene family in Coffea spp., and we also quantified Caf and Cav in coffee fruit tissues for further gene expression studies involving diterpens metabolism. Using keyword and Blast search, 1396 ESTs related to Cyt p450 were selected from the Brazilian Coffee Genome Project (http://www.lge.ibi. unicamp.br/cafe). After assembling, we observed 157 putative unigenes, distributed in 92 contigs and 65 singlets. The contigs were analyzed using BLAST X versus public sequences databases (GenBank and Harvest Coffea), confirming their identity to 91 Cyt P450 genes. Expression profiles were inferred by electronic Northern blot of all contigs, allowing the selection of 7 candidate genes for transcriptional analysis based in fruit cDNA library expression. Caf and Cav were measured using HPLC in two different fruit developmental stages: 90 DAF (Days After Flowering) vs 120 DAF and in fruits (120 DAF) treated with 2?M methyl Jasmonate (MJ). Fruits at 120 DAF had an increase of 42% in Cav and 19% in Caf levels in relation to 90DAF fruits. MJ treatment resulted in samples with an average increase of 18% of Cav and 35% of Caf. RNAs were extracted from these samples for future transcriptional analyses. This study establish a platform for expression analysis of cyt P450 candidate genes in RNA samples from tissues with contrasting accumulation of Cav and Caf. (Texte intégral

Diterpenes biochemical profile and transcriptional analysis of cytochrome P450s genes in leaves, roots, flowers, and during Coffea arabica L. fruit development.

Lipids are among the major chemical compounds present in coffee beans, and they affect the flavor and aroma of the coffee beverage. Coffee oil is rich in kaurene diterpene compounds, mainly cafestol (CAF) and kahweol (KAH), which are related to plant defense mechanisms and to nutraceutical and sensorial beverage characteristics. Despite their importance, the final steps of coffee diterpenes biosynthesis remain unknown. To understand the molecular basis of coffee diterpenes biosynthesis, we report the content dynamics of CAF and KAH in several Coffea arabica tissues and the transcriptional analysis of cytochrome P450 genes (P450). We measured CAF and KAH concentrations in leaves, roots, flower buds, flowers and fruit tissues at seven developmental stages (30e240 days after flowering - DAF) using HPLC. Higher CAF levels were detected in flower buds and flowers when compared to fruits. In contrast, KAH concentration increased along fruit development, peaking at 120 DAF. We did not detect CAF or KAH in leaves, and higher amounts of KAH than CAF were detected in roots. Using P450 candidate genes from a coffee EST database, we performed RT-qPCR transcriptional analysis of leaves, flowers and fruits at three developmental stages (90, 120 and 150 DAF). Three P450 genes (CaCYP76C4, CaCYP82C2 and CaCYP74A1) had transcriptional patterns similar to CAF concentration and two P450 genes (CaCYP71A25 and CaCYP701A3) have transcript accumulation similar to KAH concentration. These data warrant further investigation of these P450s as potential candidate genes involved in the final stages of the CAF and KAH biosynthetic pathways

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Forest and woodland replacement patterns following drought-related mortality

Forest vulnerability to drought is expected to increase under anthropogenic climate change, and drought-induced mortality and community dynamics following drought have major ecological and societal impacts. Here, we show that tree mortality concomitant with drought has led to short-term (mean 5 y, range 1 to 23 y after mortality) vegetation-type conversion in multiple biomes across the world (131 sites). Self-replacement of the dominant tree species was only prevalent in 21% of the examined cases and forests and woodlands shifted to nonwoody vegetation in 10% of them. The ultimate temporal persistence of such changes remains unknown but, given the key role of biological legacies in long-term ecological succession, this emerging picture of postdrought ecological trajectories highlights the potential for major ecosystem reorganization in the coming decades. Community changes were less pronounced under wetter postmortality conditions. Replacement was also influenced by management intensity, and postdrought shrub dominance was higher when pathogens acted as codrivers of tree mortality. Early change in community composition indicates that forests dominated by mesic species generally shifted toward more xeric communities, with replacing tree and shrub species exhibiting drier bioclimatic optima and distribution ranges. However, shifts toward more mesic communities also occurred and multiple pathways of forest replacement were observed for some species. Drought characteristics, species-specific environmental preferences, plant traits, and ecosystem legacies govern post drought species turnover and subsequent ecological trajectories, with potential far-reaching implications for forest biodiversity and ecosystem services.Peer reviewe

The Politics of Federalism in Argentina: Implications for Governance and Accountability

This paper contributes to an agenda that views the effects of policies and institutional reforms as dependent on the structure of political incentives for national and subnational political actors. The paper studies political incentive structures at the subnational level and the mechanisms whereby they affect national-level politics and policymaking at the national level in Argentina, a highly decentralized middle-income democracy, Argentina. The Argentine political system makes subnational political power structures very influential in national politics. Moreover, most Argentine provinces are local bastions of power dominated by entrenched elites, characterized by scarce political competition, weak division of powers, and clientelistic political linkages. Political dominance in the provinces and political importance at the national level reinforce each other, dragging the Argentine political and policymaking system towards the practices and features of its most politically backward regions

TRY plant trait database - enhanced coverage and open access

This article has 730 authors, of which I have only listed the lead author and myself as a representative of University of HelsinkiPlant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.Peer reviewe

TRY plant trait database - enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives