Sulfur modulates yield and storage proteins in soybean grains

This study evaluated the nutritional quality, yield, and storage protein modulation in soybean grains in response to levels and sources of sulfur (S) in a dystrophic Ultisol. We used five levels of S (0, 50, 100, 150 and 200 mg kg–1) and four sources of S (elemental S pastille - ESPA, gypsum - GY, gypsite - GI and elemental S powder - ESPO). Plants treated with 50 mg kg–1 of GY, GI, and ESPO and 200 mg kg–1 of ESPA had the largest grain yield values. Low S supply resulted in lower yields for all S sources tested. Sulfur deficiencies were observed at all levels for ESPA, resulting in lower concentrations of globulin and higher concentration of glutelin and albumin in the grains, possibly because the S content in the leaf was below the range adequate for soybean, leading to in lower yield values. In general, the application of S sources (GY, GI, and ESPO) increased all protein fractions. The results show that proper application of S is essential to optimize soybean yield and increase storage proteins in the grains. The granulometry of ESPA and ESPO fertilizers was a key factor for the availability of S to soybean plants. This study presents relevant information on S fertilization of soybeans, which could provide better grain nutritional quality and increased storage proteins with benefits to animal health

Direct Determination of Malachite Green and Leucomalachite Green in Natural Waters by Exploiting Solid-phase Sorption and Digital Image

Although malachite green (MG), a triphenylmethane dye, is banned for use in aquaculture in several countries, it is still widely employed to treat infections in fish and fish eggs. In living organisms, it is reduced to leucomalachite green (LMG) during physiological processes and can accumulate in adipose tissue. This work describes the development and verification of a simple and portable method, using preconcentration on an adsorbent surface and digital image analysis, for the determination of malachite green and leucomalachite green in natural waters. The optimum conditions of production and extraction in the film were evaluated univariate and the images were analyzed with the aid of Image J. The analytical curves were obtained from each color channel, using multiple linear regression (MLR) models for all parameters of the RGB system. Malachite green was adsorbed on a Florisil surface, followed by quantification using a calibration curve obtained with RGB image parameters, with the preconcentration factor was close to 10.  Accuracy was assessed using recovery tests on river natural waters samples, showing no significant matrix effect or additive error. The technique is suitable for environmental monitoring purposes. Simple method, practical and versatile. DOI: http://dx.doi.org/10.17807/orbital.v12i4.149

Direct Determination of Malachite Green and Leucomalachite Green in Natural Waters by Exploiting Solid-phase Sorption and Digital Image

Although malachite green (MG), a triphenylmethane dye, is banned for use in aquaculture in several countries, it is still widely employed to treat infections in fish and fish eggs. In living organisms, it is reduced to leucomalachite green (LMG) during physiological processes and can accumulate in adipose tissue. This work describes the development and verification of a simple and portable method, using preconcentration on an adsorbent surface and digital image analysis, for the determination of malachite green and leucomalachite green in natural waters. The optimum conditions of production and extraction in the film were evaluated univariate and the images were analyzed with the aid of Image J. The analytical curves were obtained from each color channel, using multiple linear regression (MLR) models for all parameters of the RGB system. Malachite green was adsorbed on a Florisil surface, followed by quantification using a calibration curve obtained with RGB image parameters, with the preconcentration factor was close to 10.  Accuracy was assessed using recovery tests on river natural waters samples, showing no significant matrix effect or additive error. The technique is suitable for environmental monitoring purposes. Simple method, practical and versatile. DOI: http://dx.doi.org/10.17807/orbital.v12i4.149

Comparative analysis of Amputee Soccer players and coach perception of intensity training

We investigate if there are agreement and differences between the training intensity and load prescribed by the coach and those perceived by Amputee Soccer (AS) players. Eleven AS players and the team coach participated in the study. Before each session, we registered the coach Rating Perceived Exertion (RPE) intended (not disclosed to the players). Immediately after the training session, the players responded to the same version of RPE individually. The load was quantified through the session-RPE (s-RPE) (RPE x minutes). In sessions 1 and 2, the coach overestimated the training RPE (p < 0.05; Effect size [ES] = 0.2 and 0.3), whereas in sessions 4 and 5 the values were underestimated (p < 0.05; ES = 0.3). In the case of s-RPE, the overestimation of RPE occurred in session 1 (p = 0.02; ES = 0.9), whereas in sessions 4 and 5 (p < 0.05; ES = 1.8 and 0.9) the coach underestimated the load values. We conclude that the training load planned by the coach is different and disagrees with the perception of the AS players in most of the training sessions.We investigate if there are agreement and differences between the training intensity and load prescribed by the coach and those perceived by Amputee Soccer (AS) players. Eleven AS players and the team coach participated in the study. Before each session, we registered the coach Rating Perceived Exertion (RPE) intended (not disclosed to the players). Immediately after the training session, the players responded to the same version of RPE individually. The load was quantified through the session-RPE (s-RPE) (RPE x minutes). In sessions 1 and 2, the coach overestimated the training RPE (p < 0.05; Effect size [ES] = 0.2 and 0.3), whereas in sessions 4 and 5 the values were underestimated (p < 0.05; ES = 0.3). In the case of s-RPE, the overestimation of RPE occurred in session 1 (p = 0.02; ES = 0.9), whereas in sessions 4 and 5 (p < 0.05; ES = 1.8 and 0.9) the coach underestimated the load values. We conclude that the training load planned by the coach is different and disagrees with the perception of the AS players in most of the training sessions

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

ATLANTIC EPIPHYTES: a data set of vascular and non-vascular epiphyte plants and lichens from the Atlantic Forest

Epiphytes are hyper-diverse and one of the frequently undervalued life forms in plant surveys and biodiversity inventories. Epiphytes of the Atlantic Forest, one of the most endangered ecosystems in the world, have high endemism and radiated recently in the Pliocene. We aimed to (1) compile an extensive Atlantic Forest data set on vascular, non-vascular plants (including hemiepiphytes), and lichen epiphyte species occurrence and abundance; (2) describe the epiphyte distribution in the Atlantic Forest, in order to indicate future sampling efforts. Our work presents the first epiphyte data set with information on abundance and occurrence of epiphyte phorophyte species. All data compiled here come from three main sources provided by the authors: published sources (comprising peer-reviewed articles, books, and theses), unpublished data, and herbarium data. We compiled a data set composed of 2,095 species, from 89,270 holo/hemiepiphyte records, in the Atlantic Forest of Brazil, Argentina, Paraguay, and Uruguay, recorded from 1824 to early 2018. Most of the records were from qualitative data (occurrence only, 88%), well distributed throughout the Atlantic Forest. For quantitative records, the most common sampling method was individual trees (71%), followed by plot sampling (19%), and transect sampling (10%). Angiosperms (81%) were the most frequently registered group, and Bromeliaceae and Orchidaceae were the families with the greatest number of records (27,272 and 21,945, respectively). Ferns and Lycophytes presented fewer records than Angiosperms, and Polypodiaceae were the most recorded family, and more concentrated in the Southern and Southeastern regions. Data on non-vascular plants and lichens were scarce, with a few disjunct records concentrated in the Northeastern region of the Atlantic Forest. For all non-vascular plant records, Lejeuneaceae, a family of liverworts, was the most recorded family. We hope that our effort to organize scattered epiphyte data help advance the knowledge of epiphyte ecology, as well as our understanding of macroecological and biogeographical patterns in the Atlantic Forest. No copyright restrictions are associated with the data set. Please cite this Ecology Data Paper if the data are used in publication and teaching events. © 2019 The Authors. Ecology © 2019 The Ecological Society of Americ