High concentration of salts in the soil impacts the availability of water and nutrients essential for plant growth and physiology. Therefore, management strategies that can mitigate the negative effects of salt stress are necessary, such as the use of plant hormones. Thus, this study aimed to evaluate the effect of salt stress and the application of melatonin on the growth and production aspects of radish plants. The experiment was carried out in a randomized block design, in a 3 × 3 factorial scheme, with four replications, considering one plant per experimental plot. The treatments consisted of three electrical conductivities of irrigation water - ECw (0.5, 2.75, and 5.0 dS m^-1) and three concentrations of melatonin (0, 0.5, and 1.0 mM). Growth variables were evaluated, namely plant height, stem diameter, number of leaves, leaf area, dry mass of leaves, petioles and roots, specific leaf area, leaf area ratio, and leaf weight ratio. In addition, production aspects were analyzed, namely bulb length, bulb diameter, and bulb fresh weight. Exogenous application of melatonin reduces the deleterious effects of salt stress on the growth and production aspects of radish plants. Application of melatonin at a dose of 0.5 mM is the most recommended to mitigate the effects of salt stress up to the level of 2.75 dS m^-1. The use of melatonin opens new perspectives for the development of management strategies aimed at optimizing growth and protecting the radish crop under saline conditions.

Northeast Brazil (NEB), particularly its semiarid region, represents an area highly susceptible to the impacts of climate change, including severe droughts, and intense anthropogenic activities. These stresses may be accelerating environmental degradation and desertification of soil in NEB. The main aim of this study was to gain geospatial insights into the biophysical parameters of surface energy balance and actual evapotranspiration on a multi-temporal scale, aiming to detect and analyze the spectral behavioral patterns of areas vulnerable to degradation processes, based on thematic maps at the surface, for NEB and mainly the semiarid region of NEB from 2000 to 2019. Geospatial data from 8-day MODIS sensor products were used, such as surface reflectance (Terra/MOD09A1 and Aqua/MYD09A1), surface temperature (Terra/MOD11A2 and Aqua/MYD11A2), and actual evapotranspiration (Terra/MOD16A2 and Aqua/MYD16A2), version 6. Therefore, in this study, pixel-to-pixel values were processed by calculating the average pixel statistics for each year. From the reflectance product, digital processing of the surface albedo and spectral vegetation indices was also carried out, using computational programming scripts and machine learning algorithms developed via the Google Earth Engine (GEE) platform. The study also presents a seasonal analysis of these components and their relationships over 20 years. Through vegetation indices and statistical correlations, a new predictive model of actual evapotranspiration was developed. The quantitative and spatiotemporal spectral patterns of the parameters were assessed through descriptive statistics, measures of central tendency and dispersion, and statistical error analyses and correlation indices. Thematic maps highlighted the pixel-to-pixel results, with patterns of high temperature distribution mainly in the central and northeastern part of NEB and the semiarid region of NEB, highlighting the formation of persistent heat islands over time. Meanwhile, in these areas, the maps of actual evapotranspiration showed a drastic reduction due to the lesser availability of energy. Over time, the semiarid region of NEB presented areas with little and/or no vegetation cover, which were highly well-defined between the years 2012 and 2019, confirming that these areas are extremely vulnerable to degradation and desertification processes due to significant loss of vegetative and water resilience. The components of energy balance were highly interconnected to climatological and environmental conditions, showing the severe results of drought and accentuation of the water deficit in NEB, presenting a greater condition of aridity in the semiarid region of NEB over time.

Water stress is the main abiotic factor that limits the development and commercial quality of ornamental plants, such as Zinnia elegans. This study aimed to evaluate the ability of exogenous melatonin (MEL) to attenuate the deleterious effects of water deficit by modulating stomatal physiological, biochemical and structural parameters. Z. elegans plants were subjected to four water regimes (80% FC, 20% FC, early stress and late stress) with (1.0 mM) and without MEL application. Severe water stress (20% FC) drastically reduced the rate of CO₂ assimilation (A) by 43.81% and stomatal conductance (gs) by 68.96%. However, the application of MEL significantly mitigated this damage, resulting in an increase in A of 26.99% gs of 43.75%, and relative water content of 28% in plants under severe stress compared with those in untreated stressed plants. The mechanism of action of MEL involves the modulation of stomatal motion and, as suggested, the promotion of osmotic fit and the protection of membrane integrity and photochemical efficiency. Exogenous melatonin acts as an effective bioregulator, improving the tolerance of Z. elegans to water deficit and sustaining its physiological performance and ornamental potential under stress conditions.

Soil erosion poses a significant global environmental challenge, causing land degradation, deforestation, river siltation, and reduced agricultural productivity. Although the Revised Universal Soil Loss Equation (RUSLE) has been widely applied in Brazil, its use in the tropical river basins of the Amazon remains limited. This study aimed to apply a GIS-integrated RUSLE model and compare its soil loss estimates with multiple linear regression (MLR) models based on terrain attributes, aiming to identify priority areas and key geomorphometric drivers of soil erosion in a tropical Amazonian river basin. A digital elevation model based on Shuttle Radar Topography Mission (SRTM) data, land use and land cover (LULC) maps, and rainfall and soil data were applied to the GIS-integrated RUSLE model; we then defined six risk classes—slight (0–2.5 t ha⁻¹ yr⁻¹), slight–moderate (2.5–5), moderate (5–10), moderate–high (10–15), high (15–25), and very high (>25)—and identified priority zones as those in the top two risk classes. The Caeté River Basin (CRB) was classified into six erosion risk categories: low (81.14%), low to moderate (2.97%), moderate (11.88%), moderate to high (0.93%), high (0.03%), and very high (3.05%). The CRB predominantly exhibited a low erosion risk, with higher erosion rates linked to intense rainfall, gentle slopes covered by Arenosols, and human activities. The average annual soil loss was estimated at 2.0 t ha⁻¹ yr⁻¹, with a total loss of 1005.44 t ha⁻¹ yr⁻¹. Additionally, geomorphological and multiple linear regression (MLR) analyses identified seven key variables influencing soil erosion: the convergence index, closed depressions, the topographic wetness index, the channel network distance, and the local curvature, upslope curvature, and local downslope curvature. These variables collectively explained 26% of the variability in soil loss (R² = 0.26), highlighting the significant role of terrain characteristics in erosion processes. These findings indicate that soil erosion control efforts should focus primarily on areas with Arenosols and regions experiencing increased anthropogenic activity, where the erosion risks are higher. The identification of priority erosion areas enables the development of targeted conservation strategies, particularly for Arenosols and regions under anthropogenic pressure, where the soil losses exceed the tolerance threshold of 10.48 t ha⁻¹ yr⁻¹. These findings directly support the formulation of local environmental policies aimed at mitigating soil degradation by stabilizing vulnerable soils, regulating high-impact land uses, and promoting sustainable practices in critical zones. The GIS-RUSLE framework is supported by consistent rainfall data, as verified by a double mass curve analysis (R² ranging from 0.64 to 0.77), and offers a replicable methodology for soil conservation planning in tropical basins with similar erosion drivers. This approach offers a science-based foundation to guide soil conservation planning in tropical basins. While effective in identifying erosion-prone areas, it should be complemented in future studies by dynamic models and temporal analyses to better capture the complex erosion processes and land use change impacts in the Amazon.

Na região semiárida grande parte das espécies florestais apresentam sementes com germinação lenta e desuniforme ao longo do tempo, por possuírem dormência. Diante do exposto, objetivou-se avaliar as características biométricas de frutos e sementes e a influência de tratamentos pré-germinativos na emergência de plântulas de Libidibia ferrea. Foram mensurados o comprimento, largura e espessura dos frutos e o número médio de sementes por fruto. Os dados de biometria foram submetidos à análise descritiva, sendo avaliados a média, máximo, mínimo, desvio padrão, coeficiente de variação e distribuição de frequência. Adotou-se o delineamento inteiramente casualizado, com oito tratamentos pré-germinativos: controle (ausência de tratamento); imersão em ácido clorídrico durante 5, 10, 15 e 20 minutos; imersão em soda cáustica durante 5 e 10 minutos; escarificação mecânica com lixa n° 150 na região oposta ao hilo e posterior imersão em água durante 24 horas. Foram avaliadas as seguintes características: porcentagem, índice de velocidade e tempo médio de emergência, comprimento e massa seca do sistema radicular e da parte aérea das plântulas. O tamanho médio dos frutos foi de 7,93 mm de comprimento, 23,19 mm de largura e 11,87 mm de espessura e 4,67 sementes viáveis por fruto. O uso da escarificação mecânica com lixa n° 150 na região oposta ao hilo com posterior embebição em água por 24 h, é o método mais indicado na superação de dormência de L. ferrea.