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Water stress can lead to physiological and morphological damage, affecting the growth and development of popcorn. The objective of this study was to identify the yield potential of 43 popcorn lines derived from a Latin American germplasm collection, based on agronomic and physiological traits, under full irrigation (WW) and water deficit conditions (WS), aiming to select superior germplasm. The evaluated agronomic traits included the ear length and diameter, number of grains per row (NGR) and rows per ear (NRE), grain yield (GY), popping expansion (EC), volume of expanded popcorn per hectare (VP), grain length (GL), width, and thickness. The physiological traits included the chlorophyll, anthocyanin, and flavonoid content in the leaves. The genetic variability and distinct behavior among the lines for all the agronomic traits under WW and WS conditions were observed. When comparing the water conditions, line L292 had the highest mean for the GY, and line L688 had the highest mean for the EC, highlighting them as the most drought-tolerant lines. A water deficit reduced the leaf greenness but increased the anthocyanin content as an adaptive response. The GY trait showed positive correlations with the VP, NGR, and GL under both water conditions, making the latter useful for indirect selection and thus of great interest for plant breeding targeting the simultaneous improvement of these traits.

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Most recent university campuses follow the North American model, built on city limits or countryside, with large separate buildings in open green spaces. Studies suggest that the prevalence and severity of mental health issues among university students has been increasing over the past decade in most countries. University services were created to face this growing problem, however individual-based interventions have limited effects on mental health and well-being of a large population. Our aim was to verify if and how the natural environment in campuses is focused on programs to cope with the issue of mental health and well-being among students. A systematic review of literature was undertaken with search in Scopus and LILACS with the keywords "green areas" AND "well-being" AND "Campus", following PRISMA guidelines. As a result, 32 articles were selected. Research on the topic is recent, mostly in the USA, Bulgaria, and China. Most studies used objective information on campuses' greenness and/or university students' perception. Mental health was usually measured by validated scores. Findings of all the studies indicated positive association between campus greenery and well-being of students. We conclude that there is a large potential for use of university campuses in programs and as sites for students' restoration and stress relief.

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The global population is at risk of vitamin D deficiency due to low exposure to sunlight and low intake of the vitamin through diet. The aim of this study was to investigate in women the association between vitamin D status and parathyroid hormone (PTH), ultraviolet radiation, lifestyle, ethnicity, social conditions, and residential greenness. A 1-year longitudinal study assessed vitamin D status in 309 women living at latitude 51°14' N. Blood samples were taken four times throughout the year for analysis of 25(OH)D and serum PTH concentration. After each seasonal visit, the individuals completed 4-day diet diaries and used two dosimeter badges for 1 week to estimate weekly UVR exposure. A questionnaire was applied to provide information about lifestyle and their ethnicity. Residential greenness was measured by Normalized Difference Vegetation Index (NDVI), within a 1000 m radius around each participant's home address. Women living in greener spaces were more likely to have improved vitamin D status (RR: 1.51; 95%CI: 1.13-2.02), as well as those who were more exposed to UVR (RR: 2.05; 95%CI: 1.44-2.92). Our results provide an insight into the connection between residential greenness, lifestyle, and vitamin D status comparing two ethnicities in a country with a temperate climate and with a high degree of urbanization.

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Bee pollen is considered an excellent dietary supplement with functional characteristics, and it has been employed in food and cosmetics formulations and in biomedical applications. Therefore, understanding its chemical composition, particularly crude protein contents, is essential to ensure its quality and industrial application. For the quantification of crude protein in bee pollen, this study explored the potential of combining digital image analysis and Random Forest algorithm for the development of a rapid, cost-effective, and environmentally friendly analytical methodology. Digital images of bee pollen samples (n = 244) were captured using a smartphone camera with controlled lighting. RGB channels intensities and color histograms were extracted using open source softwares. Crude protein contents were determined using the Kjeldahl method (reference) and in combination with RGB channels and color histograms data from digital images, they were used to generate a predictive model through the application of the Random Forest algorithm. The developed model exhibited good performance and predictive capability for crude protein analysis in bee pollen (R2 = 80.93 %; RMSE = 1.49 %; MAE = 1.26 %). Thus, the developed analytical methodology can be considered environmentally friendly according to the AGREE metric, making it an excellent alternative to conventional analysis methods. It avoids the use of toxic reagents and solvents, demonstrates energy efficiency, utilizes low-cost instrumentation, and it is robust and precise. These characteristics indicate its potential for easy implementation in routine analysis of crude protein in bee pollen samples in quality control laboratories.

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In the dynamic landscape of maternal and child health, understanding the intricate interplay between environmental factors and pregnancy outcomes is of paramount importance. This study investigates the relationship between maternal greenness exposure and preterm births in Brazil using data spanning from 2010 to 2019. Satellite-derived indices, including the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), were employed to assess greenness exposure during whole pregnancy in maternal residential area. Employing Cox proportional hazard models, we calculated the hazard ratios (HRs) with 95% confidence intervals (CIs) for changes in NDVI, while adjusting for individual and area-level covariates. In total, 24,010,250 live births were included. Prevalence of preterm birth was 11.5%, with a modest but statistically significant decreasing trend (p = 0.013) observed across the nation over the study period. The findings reveal a significant association between greenness exposure and a reduced risk of preterm birth. Specifically, for every 0.1 increase in NDVI, there was a 2.0% decrease in the risk of preterm birth (95%CI: 1.9%-2.2%). Stratified analyses based on maternal education and ethnicity indicated potential effect modifications, with stronger protective effects observed among younger mothers and those with less years of education. Sensitivity analyses using EVI yielded consistent results. In conclusion, this study suggests that higher maternal greenness exposure is linked to a decreased risk of preterm birth in Brazil. These findings imply that enhancing residential greenspaces could be a valuable public health strategy to promote maternal and child health in Brazil.

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Forest biodiversity conservation and species distribution modeling greatly benefit from broad-scale forest maps depicting tree species or forest types rather than just presence and absence of forest, or coarse classifications. Ideally, such maps would stem from satellite image classification based on abundant field data for both model training and accuracy assessments, but such field data do not exist in many parts of the globe. However, different forest types and tree species differ in their vegetation phenology, offering an opportunity to map and characterize forests based on the seasonal dynamic of vegetation indices and auxiliary data. Our goal was to map and characterize forests based on both land surface phenology and climate patterns, defined here as forest phenoclusters. We applied our methodology in Argentina (2.8 million km2 ), which has a wide variety of forests, from rainforests to cold-temperate forests. We calculated phenology measures after fitting a harmonic curve of the enhanced vegetation index (EVI) time series derived from 30-m Sentinel 2 and Landsat 8 data from 2018-2019. For climate, we calculated land surface temperature (LST) from Band 10 of the thermal infrared sensor (TIRS) of Landsat 8, and precipitation from Worldclim (BIO12). We performed stratified X-means cluster classifications followed by hierarchical clustering. The resulting clusters separated well into 54 forest phenoclusters with unique combinations of vegetation phenology and climate characteristics. The EVI 90th percentile was more important than our climate and other phenology measures in providing separability among different forest phenoclusters. Our results highlight the potential of combining remotely sensed phenology measures and climate data to improve broad-scale forest mapping for different management and conservation goals, capturing functional rather than structural or compositional characteristics between and within tree species. Our approach results in classifications that go beyond simple forest-nonforest in areas where the lack of detailed ecological field data precludes tree species-level classifications, yet conservation needs are high. Our map of forest phenoclusters is a valuable tool for the assessment of natural resources, and the management of the environment at scales relevant for conservation actions.

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Being a Re-Emerging Infectious Disease, dengue causes 390 million cases globally and is prevalent in many urban areas in South America. Understanding the fine-scale relationships between dengue incidence and environmental and socioeconomic factors can guide improved disease prevention strategies. This ecological study examines the association between dengue incidence and satellite-based vegetation greenness in 3826 census tracts nested in 474 neighborhoods in Belo Horizonte, Brazil, during the 2010 dengue epidemic. To reduce potential bias in the estimated dengue-greenness association, we adjusted for socioeconomic vulnerability, population density, building height and density, land cover composition, elevation, weather patterns, and neighborhood random effects. We found that vegetation greenness was negatively associated with dengue incidence in a univariate model, and this association attenuated after controlling for additional covariates. The dengue-greenness association was modified by socioeconomic vulnerability: while a positive association was observed in the least vulnerable census tracts, the association was negative in the most vulnerable areas. Using greenness as a proxy for vegetation quality, our results show the potential of vegetation management in reducing dengue incidence, particularly in socioeconomically vulnerable areas. We also discuss the role of water infrastructure, sanitation services, and tree cover in lowering dengue risk.

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The identification of traits associated with drought tolerance in popcorn is a contribution to support selection of superior plants under soil water deficit. The objective of this study was to choose morphological traits and the leaf greenness index, measured on different dates, to estimate grain yield (GY) and popping expansion (PE), evaluated in a set of 20 popcorn lines with different genealogies, estimated by multiple regression models. The variables were divided into three groups: morpho-agronomic traits-100-grain weight (GW), prolificacy (PR), tassel length (TL), number of tassel branches, anthesis-silking interval, leaf angle (FA) and leaf rolling (FB); variables related to the intensity of leaf greenness during the grain-filling period, at the leaf level, measured by a portable chlorophyll meter (SPAD) and at the canopy level, calculated as the normalized difference vegetation index (NDVI). The inbred lines were cultivated under two water conditions: well-watered (WW), maintained at field capacity, and water stress (WS), for which irrigation was stopped before male flowering. The traits GY (55%) and PE (28%) were most affected by water restriction. Among the morpho-agronomic traits, GW and PR were markedly reduced (>10%). Under dry conditions, the FA in relation to the plant stalk tended to be wider, the FB curvature greater and leaf senescence accelerated (>15% at 22 days after male flowering). The use of multiple regression for the selection of predictive traits proved to be a useful tool for the identification of groups of adequate traits to efficiently predict the economically most important features of popcorn (GY and PE). The SPAD index measured 17 days after male flowering proved useful to select indirectly for GY, while, among the morphological traits, TL stood out for the same purpose. Of all traits, PR was most strongly related with PE under WS, indicating its use in breeding programs. The exploitation of these traits by indirect selection is expected to induce increments in GY and PE.

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Submergence is a severe form of stress for most plants. Lotus japonicus is a model legume with potential use in assisting breeding programs of closely related forage Lotus species. Twelve L. japonicus genotypes (10 recombinant inbred lines (RILs) and 2 parental accessions) with different constitutive shoot to root dry mass ratios (S:R) were subjected to 7 days of submergence in clear water and allowed to recover for two weeks post-submergence; a set of non-submerged plants served as controls. Relative growth rate (RGR) was used to indicate the recovery ability of the plants. Leaf relative water content (RWC), stomatal conductance (gs), greenness of basal and apical leaves, and chlorophyll fluorescence (Fv/Fm, as a measure of photoinhibition) were monitored during recovery, and relationships among these variables and RGR were explored across genotypes. The main results showed (i) variation in recovery ability (RGR) from short-term complete submergence among genotypes, (ii) a trade-off between growth during vs. after the stress indicated by a negative correlation between RGR during submergence and RGR post-submergence, (iii) an inverse relationship between RGR during recovery and S:R upon de-submergence, (iv) positive relationships between RGR at early recovery and RWC and gs, which were negatively related to S:R, suggesting this parameter as a good estimator of plant water balance post-submergence, (v) chlorophyll retention allowed fast recovery as revealed by the positive relationship between greenness of basal and apical leaves and RGR during the first recovery week, and (vi) full repair of the submergence-damaged photosynthetic apparatus occurred more slowly (second recovery week) than full recovery of plant water relations. The inclusion of these traits contributing to submergence recovery in L. japonicus should be considered to speed up the breeding process of the closely related forage Lotus spp. used in current agriculture.

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A green analytical methodology for the determination of 16 priority polycyclic aromatic hydrocarbons (PAHs) and 8 related compounds in air particulate matter was developed and validated. The method was based on pressurized hot water extraction (PHWE) followed by miniaturized membrane-assisted solvent extraction (MASE) and programmed temperature vaporization-gas chromatography-ion trap tandem mass spectrometry detection (PTV-GC-MS/MS). The parameters studied for PHWE were percentage of organic modifier (25% MeOH), temperature (200 °C) and static extraction time (5 min). For MASE, extraction temperature (30 °C), time (90 min) and effect of an organic modifier were also optimized. The matrix effect was evaluated and compensated using deuterated labelled standards as surrogates for the quantitation of the target compounds. The analytical performance of the method was satisfactory: relative recoveries varied between 78 and 118% and repeatability and intermediate precision were <22% for all compounds. The Method Quantitation Limits (MQL) ranged from 0.9 (TPY) to 75.6 pg m-3 (NAP). Satisfactory results for accuracy and traceability were evidenced by the analysis of a reference material (SRM 1649b) and comparison with previously published methods. The greenness score was estimated and compared with other techniques widely used for the analysis of PAHs in particulate matter, having a lower relative environmental impact.

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Vegetation greenness (normalized difference vegetation index, NDVI) showed significant temporal and spatial correlations with precipitation and topography-derived features within the context of slope aspect (South- (SFS) and North-facing slopes (NFS) and an intermountain valley (IMV)) in a semi-arid Mediterranean-climate watershed in northwestern Baja California, México. Rank correlation with annual precipitation (1986-2016) showed a strong positive relationship with wet season NDVI at SFS (Rs = 0.82), IMV (Rs = 0.79), and NFS (Rs = 0.65) but moderate relation and only on hillslopes in the dry season (SFS, Rs = 0.47; NFS, Rs = 0.39). Thus, the vegetation on the more xeric SFS sites was more responsive to intra-annual and inter-annual precipitation than on either IMV or NFS. The correlation of NDVI with six topography-derived environmental attributes (elevation, slope gradient, curvature, drainage density, topographic wetness index, solar radiation) was weak to moderate, varied in degree and significance between years with exceptionally high or low NDVI, and often differed in sign between SFS, NFS, and IMV. Results showed that precipitation controlled vegetation greenness, under the three aspect conditions, more closely than did the other topography-derived features, and the sparse deciduous vegetation of SFS showed stronger associations with precipitation than IMV or NFS. The measurement of these relationships should be continued and complemented by other studies to improve the overall model, because they are important to modeling ecohydrology and productivity, and may be of use for projecting and hindcasting vegetation dynamics.

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Reservoirs are important in Brazil for the production of hydroelectric power and human water consumption. The objective was to evaluate the variability of total suspended solids (TSS) and chlorophyll-a as well as the rainfall/temperature and land use impacts on these optically active constituents (OAC). The study area is the Passo Real reservoir in south Brazil. The methodology was divided in four steps. First, we used wavelet to detect anomalous periods of rainfall and temperature (2002-2014). Second, we carried out 12 field campaigns to obtain in situ measurements for limnological characterization (2009-2010). The third step was the analysis of Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra and Aqua satellites data corrected and non-corrected for bidirectional effects. Finally, we evaluated potential drivers of OAC changes over time using cross-correlation analysis. The results showed a decrease in the TSS and chlorophyll-a concentrations from the upper to the lower streams of the reservoir. The exponential regression between the MODIS red reflectance and TSS had an adjusted r2 of 0.63. It decreased to 0.53 for the relationship between the green reflectance and chlorophyll-a. MODIS data corrected for bidirectional effects provided better OAC estimates than non-corrected data. The validation of MODIS TSS and chlorophyll-a estimates using a separate set of measurements showed a RMSE of 2.98mg/l and 2.33µg/l, respectively. MODIS estimates indicated a gradual transition in OAC from the upper to the lower streams in agreement with the patterns observed using field limnological data. The analysis of land use (greenness) showed two well-defined crop cycles per year. The highest seasonal concentrations of TSS and chlorophyll-a were observed in December and the lowest concentrations in April. Despite the interrelationships between both factors, our cross-correlation analysis indicated that the great concentrations of TSS and chlorophyll-a were primarily controlled by rainfall and secondarily by land use.

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Abstract:Remote sensing and traditional ecological knowledge (TEK) can be combined to advance conservation of remote tropical regions, e.g. Amazonia, where intensive in situ surveys are often not possible. Integrating TEK into monitoring and management of these areas allows for community participation, as well as for offering novel insights into sustainable resource use. In this study, we developed a 250 m resolution land-cover map of the Western Guyana Shield (Venezuela) based on remote sensing, and used TEK to validate its relevance for indigenous livelihoods and land uses. We first employed a hyper-temporal remotely sensed vegetation index to derive a land classification system. During a 1 300 km, eight day fluvial expedition in roadless areas in the Amazonas State (Venezuela), we visited six indigenous communities who provided geo-referenced data on hunting, fishing and farming activities. We overlaid these TEK data onto the land classification map, to link land classes with indigenous use. We characterized land classes using patterns of greenness temporal change and topo-hydrological information, and proposed 12 land-cover types, grouped into five main landscapes: 1) water bodies; 2) open lands/forest edges; 3) evergreen forests; 4) submontane semideciduous forests, and 5) cloud forests. Each land cover class was identified with a pulsating profile describing temporal changes in greenness, hence we labelled our map as "The Forest Pulse". These greenness profiles showed a slightly increasing trend, for the period 2000 to 2009, in the land classes representing grassland and scrubland, and a slightly decreasing trend in the classes representing forests. This finding is consistent with a gain in carbon in grassland as a consequence of climate warming, and also with some loss of vegetation in the forests. Thus, our classification shows potential to assess future effects of climate change on landscape. Several classes were significantly connected with agriculture, fishing, overall hunting, and more specifically the hunting of primates, Mazama americana, Dasyprocta fuliginosa, and Tayassu pecari. Our results showed that TEK-based approaches can serve as a basis for validating the livelihood relevance of landscapes in high-value conservation areas, which can form the basis for furthering the management of natural resources in these regions. Rev. Biol. Trop. 64 (4): 1661-1682. Epub 2016 December 01.

Resumen:La teledetección y el conocimiento ecológico tradicional (CET) se pueden combinar para avanzar en la conservación de regiones tropicales remotas como la Amazonía, donde la toma de datos intensiva in situ a menudo es imposible. Integrar el CET en el seguimiento y el manejo de estas áreas permite la participación de la comunidad, y ofrece nuevos puntos de vista sobre el uso sostenible de los recursos naturales. En este estudio se desarrolla un mapa de cobertura del suelo del Escudo Guayanés (Venezuela), con una resolución espacial de 250 m, basado en datos de teledetección, y se utiliza el CET para validar su relevancia en relación con la subsistencia de los pueblos indígenas y el uso que éstos hacen del territorio. En primer lugar se ha empleado un índice de vegetación basado en teledetección hiper-temporal para realizar una clasificación del territorio. Durante una expedición fluvial de 8 días, a lo largo de 1 300 km por áreas sin carreteras en el Estado Amazonas (Venezuela), se han visitado seis comunidades que han proporcionado datos geo-referenciados sobre sus actividades cinegéticas, pesqueras y agrícolas. Estos datos de CET se han superpuesto al mapa de clasificación, con el fin de relacionar las clases de coberturas con los usos indígenas. Se han caracterizado las clases de cobertura en función de patrones de cambio temporal del verdor y la topo-hidrografía, y se han propuesto 12 tipos de cobertura del suelo, agrupadas en cinco tipos principales de paisaje: 1) masas de agua; 2) campo abierto/ márgenes del bosque; 3) bosques siempre-verdes; 4) bosques semi-caducifolios submontanos; y 5) bosques nublados. Cada clase de cobertura del suelo se ha identificado con un perfil pulsátil que describe cambios temporales en el verdor, de ahí que el mapa haya sido titulado "El Pulso del Bosque". Estos perfiles de verdor han mostrado una tendencia ligeramente ascendente, durante el periodo 2000 a 2009, en las clases que representan pastizales y zonas de matorral, así como una tendencia ligeramente decreciente en las clases que representan bosques. Este hallazgo es compatible con la ganancia de carbono en los pastizales como consecuencia del calentamiento del clima, y también con una cierta pérdida de vegetación en los bosques. De este modo, nuestra clasificación muestra potencial para la evaluación de efectos futuros del cambio climático sobre el paisaje. Algunas clases han resultado estar significativamente relacionadas con la agricultura, la pesca, la caza como práctica general, y más concretamente con la caza de primates, de Mazama Americana, Dasyprocta fuliginosa, y Tayassu pecari. Los resultados demuestran la utilidad de las aproximaciones basadas en CET como base para validar la importancia del paisaje, en áreas con alto valor de conservación, para la supervivencia de las personas, lo que proporciona una base para avanzar en el manejo de los recursos naturales en estas regiones.

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