MANCHA AQUOSA: IMPORTANTE BACTERIOSE DO MELOEIRO NO BRASIL

The Northeastern Region is the main melon producer of Brazil and the states of Rio Grandedo Norte and Ceará are responsible for 82 % of this production. Bacterial fruit blotch causedby Acidovorax avenae subsp. citrulli is one of the major diseases of melon reaching up to 100 %losses in raining seasons. Disease symptoms are more easily observed in fruits and controlmeasures are still not well stablished in Brazil. This review it is not comprehensive but coversthe principal aspects related to this disease involving importance, taxonomy, occurrence anddistribution, symptomatology, etiology, host range, survival, dissemination, penetration,epidemiology and management, published in Brazil and worldwide.O Nordeste é o maior produtor de melão no Brasil, destacando-se os estados do Rio Grandedo Norte e Ceará, com 82 % desta produção. A mancha-aquosa, causada pela bactéria Acidovoraxavenae subsp. citrulli, é uma das principais doenças dessa cultura com perdas econômicas estimadasem até 100 %, em períodos chuvosos. Os sintomas da doença são observados mais facilmentenos frutos e não se dispõem ainda de medidas de controle bem estabelecidas no Brasil. Estarevisão, apesar de não completa, aborda os principais aspectos dessa fitobacteriose, envolvendoimportância, taxonomia, ocorrência e distribuição, sintomatologia, etiologia, gama dehospedeiras, sobrevivência, disseminação, penetração, epidemiologia e manejo, contidos emliteratura internacional e nacional

IMPORTÂNCIA DE BACTÉRIAS PROMOTORAS DE CRESCIMENTO E DE BIOCONTROLE DE DOENÇAS DE PLANTAS PARA UMA AGRICULTURA SUSTENTÁVEL

Plant growth-promoting rhizobacteria (PGPR) are epiphytic or endophytic resident, non agents. Their beneficial effects may be observed in “in vitro” propagated plants and also “exvitro” mainly through the increase of foliar area, plant height, stem diameter, leaf number anddry matter, reduction of the acclimation time, higher plant survival, disease biocontrol andhigher yield. The endophytic PGPR has great potential and practical use. The main PGPRutilized in agriculture are species of Pseudomonas, Bacillus, Burkholderia, Streptomyces, Rhizobium,Bradyrhizobium, Acetobacter and Herbaspirilum, Agrobacterium radiobacter and Enterobacter cloacae, amongothers. This review discusses problems and solutions related to research on this importantgroup of bacteria aiming to maximize food production maintaining the ecological balance.As bactérias promotoras de crescimento de plantas (BPCP) são residentes epifíticas ouendofiticas, não patogênicas, que atuam diretamente promovendo o crescimento ouindiretamente como agentes de controle biológico de doenças de plantas. Os efeitos benéficosdas BPCP podem ser observados em plantas propagadas “in vitro” e “ex vitro” principalmentepelo aumento de área foliar, altura da planta, diâmetro do caule, número de folhas e matériaseca, redução do tempo de aclimatização, maior sobrevivência de mudas, controle de doençase aumento de produtividade. As BPCP endofíticas têm grande potencialidade e praticabilidadede uso. As principais BPCP empregadas na agricultura são espécies de Pseudomonas, Bacillus,Burkholderia, Streptomyces, Rhizobium, Bradyrhizobium, Acetobacter e Herbaspirilum, Agrobacteriumradiobacter e Enterobacter cloacae, entre outras. Nesta revisão são discutidos os problemas e soluçõesrelacionadas à pesquisa deste importante grupo de bactérias visando a maximização da produçãode alimentos com manutenção do equilíbrio ecológico

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

ATIVIDADE ENZIMÁTICA DE FUNGOS ENDOFÍTICOS E EFEITO NA PROMOÇÃO DO CRESCIMENTO DE MUDAS DE MARACUJAZEIRO-AMARELO

From leaves, stems and roots of healthy yellow passion fruit plants 93 isolates of endophytic fungi were obtained, with the colonization rates varying from 59.8 to 92.4% (leaves), 27.2 to 90% (stems) and 2.4 to 87.2 (roots). Twenty-nine of these isolates were evaluated for extracelular hydrolitic enzymes production (amylolitic, cellulolitic, lypolytic and proteolytic) and capacity to promove growth of yellow passion fruit seedlings. The isolates were identified as Fusarium (44.82%), Colletotrichum (37.93%), Acremonium, Glomerella, Curvularia, Alternaria and Aspergillus (3.45% each). The isolates EM11, EM50, EM172, EM20, EM81, EM72, EM135 and EM24 presented lypolytic activity with halos varying from 1.52 to 3.74 cm, and no isolate produced proteolytic, cellulolytic and amylolitic enzymes. Fifteen endophytic isolates promoted growth of yellow passion fruit seedlings, being the best EM173 (Alternaria), EM155 (Fusarium), EM139 (Curvularia), EM20 (Colletotrichum), EM6 (Acremonium) and EM151 (Colletotrichum) that increased aerial and root fresh biomass and root dry biomass of until 108.4, 204.4 and 70.2%, respectively, 90 days after the inoculation