Ozonated water and chlorine effects on the antioxidant properties of organic and conventional broccoli during postharvest.

There is growing interest in studies on sanitizers other than chlorine that can maintain the quality of organic products without affecting their phytochemical content. The effects of using chlorinated and ozonized water treatments, as sanitizing procedures, on the post-harvest quality of organic and conventional broccoli (Brassica oleracea L.) cv. Italica was evaluated. The biochemical parameters (chlorophyll, polyphenols, flavonoids, vitamin C and antioxidant capacity) of the broccoli samples were analyzed at day 0 (arrival of the plant from the field, original features), and 1, 4 and 7 days after harvest. The polyamine analysis was performed on arrival of the plant from the field and on the first and seventh days. The cultivation procedure influenced polyphenol, vitamin C and total chlorophyll content, and the highest value was observed in organic broccoli after the fourth day. Flavenoid content was higher in organic broccoli. The use of ozone appears not to have had an influence on the amount of polyphenolic, flavonoids and vitamin C during storage. Total chlorophyll content was less affected by ozonized water than by the chlorine treatment as at the first and fourth days of storage. The highest content of putrescine was found in conventional broccoli, while the highest levels of spermidine and spermine were found in organic broccoli. Antioxidant capacity was highest in organic broccoli after day 4 of storage and was affected by the bioactive compounds analyzed. Methods of cultivation influenced natural antioxidant and chlorophyll contents in broccoli under cold storage

Genome-based reclassification of azospirillum brasilense SP245 as the type strain of azospirillum baldaniorum sp. nov

Azospirillum sp. strain Sp245T, originally identified as belonging to Azospirillum brasilense, is recognized as a plant-growth-promoting rhizobacterium due to its ability to fix atmospheric nitrogen and to produce plant-beneficial compounds. Azospirillum sp. Sp245T and other related strains were isolated from the root surfaces of different plants in Brazil. Cells are Gram-negative, curved or slightly curved rods, and motile with polar and lateral flagella. Their growth temperature varies between 20 to 38 °C and their carbon source utilization is similar to other Azospirillum species. A preliminary 16S rRNA sequence analysis showed that the new species is closely related to A. brasilense Sp7T and A. formosense CC-Nfb-7T. Housekeeping genes revealed that Azospirillum sp. Sp245T, BR 12001 and Vi22 form a separate cluster from strain A. formosense CC-Nfb-7T, and a group of strains closely related to A. brasilense Sp7T. Overall genome relatedness index (OGRI) analyses estimated based on average nucleotide identity (ANI) and digital DNA–DNA hybridization (dDDH) between Azospirillum sp. Sp245T and its close relatives to other Azospirillum species type strains, such as A. brasilense Sp7T and A. formosense CC-Nfb-7T, revealed values lower than the limit of species circumscription. Moreover, core-proteome phylogeny including 1079 common shared proteins showed the independent clusterization of A. brasilense Sp7T, A. formosense CC-Nfb-7T and Azospirillum sp. Sp245T, a finding that was corroborated by the genome clustering of OGRI values and housekeeping phylogenies. The DNA G+C content of the cluster of Sp245T was 68.4–68.6%. Based on the phylogenetic, genomic, phenotypical and physiological analysis, we propose that strain Sp245T together with the strains Vi22 and BR12001 represent a novel species of the genus Azospirillum, for which the name Azospirillum baldaniorum sp. nov. is proposed. The type strain is Sp245T (=BR 11005T=IBPPM 219T) (GCF_007827915.1, GCF_000237365.1, and GCF_003119195.2).Fil: Ferreira, Natalia Dos Santos. Universidade Federal Rural Do Rio de Janeiro; BrasilFil: Sant´Anna, Fernando Hayashi. Universidade Federal do Rio Grande do Sul; BrasilFil: Reis, Veronica Massena. Ministerio da Agricultura Pecuaria e Abastecimento de Brasil. Empresa Brasileira de Pesquisa Agropecuaria; BrasilFil: Ambrosini, Adriana. Universidade Federal do Rio Grande do Sul; BrasilFil: Volpiano, Camila Gazolla. Universidade Federal do Rio Grande do Sul; BrasilFil: Rothballer, Michael. Helmholtz Center Munich German Research Center For Environmental Health; AlemaniaFil: Schwab, Stefan. Ministerio da Agricultura Pecuaria e Abastecimento de Brasil. Empresa Brasileira de Pesquisa Agropecuaria; BrasilFil: Baura, Valter Antonio. Universidade Federal do Paraná; BrasilFil: Balsanelli, Eduardo. Universidade Federal do Paraná; BrasilFil: Pedrosa, Fabio de Oliveira. Universidade Federal do Paraná; BrasilFil: Passaglia, Luciane Maria Pereira. Universidade Federal do Rio Grande do Sul; BrasilFil: de Souza, Emanuel Maltempi. Universidade Federal do Paraná; BrasilFil: Hartmann, Anton. Ludwig Maximilians Universitat; AlemaniaFil: Cassan, Fabricio Dario. Universidad Nacional de Rio Cuarto. Facultad de Ciencias Exactas Fisicoquímicas y Naturales. Instituto de Investigaciones Agrobiotecnológicas - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones Agrobiotecnológicas; ArgentinaFil: Zilli, Jerri Edson. Ministerio da Agricultura Pecuaria e Abastecimento de Brasil. Empresa Brasileira de Pesquisa Agropecuaria; Brasi

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

The complete genome sequence of Chromobacterium violaceum reveals remarkable and exploitable bacterial adaptability

Chromobacterium violaceum is one of millions of species of free-living microorganisms that populate the soil and water in the extant areas of tropical biodiversity around the world. Its complete genome sequence reveals (i) extensive alternative pathways for energy generation, (ii) ≈500 ORFs for transport-related proteins, (iii) complex and extensive systems for stress adaptation and motility, and (iv) wide-spread utilization of quorum sensing for control of inducible systems, all of which underpin the versatility and adaptability of the organism. The genome also contains extensive but incomplete arrays of ORFs coding for proteins associated with mammalian pathogenicity, possibly involved in the occasional but often fatal cases of human C. violaceum infection. There is, in addition, a series of previously unknown but important enzymes and secondary metabolites including paraquat-inducible proteins, drug and heavy-metal-resistance proteins, multiple chitinases, and proteins for the detoxification of xenobiotics that may have biotechnological applications

Forward-central two-particle correlations in p-Pb collisions at root s(NN)=5.02 TeV

Two-particle angular correlations between trigger particles in the forward pseudorapidity range (2.5 2GeV/c. (C) 2015 CERN for the benefit of the ALICE Collaboration. Published by Elsevier B. V.Peer reviewe

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost