Effect of essential oils from Eucalyptus on the growth of aflatoxigenic species

In Brazil, Eucalyptus species has been cultivated as source of energy and cellulose. They represent the most important cultivated forest in the country. In production areas, the leaves from the trees decay on the soil as green fertilizer. In this study were evaluated pure and blends of essential oils from different species of eucalyptus trees grown in Brazil for antifungal activity against aflatoxigenic species Aspergillus flavus and A. parasiticus. These fungal species can grow and contaminate grains during the storage period under high r.h. conditions, with an eventual production of aflatoxins. Antifungal activity was evaluated by the radial growth measurement of the fungi inoculated on maize meal extract agar basic medium. The eucalyptus oils were evaluated in a contact assay and a fumigant assay using pure and blended oils. Six concentrations of pure and blended oils were evaluated at the following doses: 0, 2, 4, 16, 32 and 84 μL per 20 mL of fungi culture medium. Fungal inocula from conidia suspensions containing 106 spores/mL was inoculated by a needle. Glass Petri dishes were incubated for 9 days at 28°C (± 0.3°C) in the dark. Antifungal activity was observed in all pure and blended oils, in different concentrations of contact and fumigant assay, for both fungi. Eucalyptus stageiriana oil and E. stageiriana + the hybrid E. grandis x E. urophylla oils blend controlled the total fungal growth at the lowest dose (20 μL). Keywords: Essential oil; Eucalyptus spp.; Aspergillus flavus; Aspergillus parasiticus; Antifungal activity

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