Search Results (45)

Pesticide exposure gradients between occupational, para-occupational, and general populations remain poorly characterized in North African agricultural contexts. This study evaluates urinary pesticide levels among farmers, indirectly exposed individuals, and a control group in Morocco’s Fez-Meknes region. A cross-sectional survey measured pesticide concentrations using LC-MS/MS in urine samples collected from 154 adults residing in both rural and urban areas. A questionnaire was used to gather information from participants regarding factors that may elevate the risk of pesticide exposure. The results revealed that farmers exhibited the highest concentrations of pesticides in their urine, including compounds classified as Ia/Ib by the World Health Organization. Indirectly exposed individuals showed moderate levels of contamination, with notable detections such as dichlofluanid (22.13 µg/L), while the control group had residual traces of neonicotinoids, notably imidacloprid (2.05 µg/L). Multivariate analyses revealed several sociodemographic factors significantly associated with increased pesticide exposure. The main risk factors identified included low education, residence in an agricultural area, and the consumption of untreated water (wells/rivers). Conversely, wearing personal protective equipment was associated with reduced urinary concentrations. This study highlights intense occupational exposure among farmers, secondary environmental contamination among residents living near treated areas, and the widespread dispersion of pesticide residues into urban areas. Full article

This study provides a comprehensive panorama of wastewater treatment on swine farms in Pará de Minas, MG, focusing on the performance of the anaerobic digester technologies adopted. Considering the economic and environmental importance of swine production, wastewater treatment is critical for mitigating environmental impacts while providing renewable energy opportunities. Data compilation from the Minas Gerais Institute of Agriculture (IMA), technical visits, and physicochemical analyses were conducted. Our results indicate that the region has significant potential to increase biogas production by expanding the number of plants and improving the efficiency of existing systems. Investments in scalable technological solutions tailored for small-scale operations are essential to enhance both wastewater treatment and biogas generation. This study demonstrates the potential for new business opportunities within the biogas value chain in Brazilian agribusiness. Full article

Rubber dandelion (Taraxacum kok-saghyz Rodin, TKS), also referred to as Russian dandelion, is one of the most promising natural rubber (NR)-producing plants that produce high-quality NR comparable to that from the Pará rubber tree (Hevea brasiliensis, Hb), currently the only commercial source. It needs further breeding to improve the agricultural traits. However, little has been known about the genetic mechanisms underlying the regulation of floral induction and flower development in TKS, an important trait that remains to be improved for commercial production. The MADS-box gene AGAMOUS-LIKE 24 (AGL24) plays important roles in floral induction and flower development. As the first step in understanding its roles in TKS, this study isolated and characterized the AGL24-homologous gene TkAGL24 in TKS. The TkAGL24 gene had a 705 bp coding sequence (CDS) that encoded a protein of 234 amino acids containing the conserved classic MADS-box type II domain and K-box domain, sharing 55.32% protein sequence identity with the AtAGL24 protein from Arabidopsis. TkAGL24 was highly expressed in leaf, latex, root, and peduncle but rarely or not in mature flower. The TkAGL24 protein was located in the nucleus and cytoplasm and did not have transcription activation activity in yeast cells. The overexpression of TkAGL24 in Arabidopsis could promote flowering and cause the abnormal development of flowers, similar to other AGL24-homologous genes from other species. Furthermore, the overexpression of TkAGL24 in TKS also affected the development of ligulate flowers. These results suggested that the cloned TkAGL24 gene is functional and may play important roles in floral induction and flower development in TKS, providing an insight into the possibility for the further studies of its roles and application to breeding. Full article

The expansion of agricultural frontiers in the Amazon region poses a significant threat to forest conservation and biodiversity persistence. This study focuses on Pará state, Brazil, aiming to identify and characterize the predominant production systems by combining remote sensing data and landscape structure metrics. A rule-based classification tree algorithm is applied to classify hexagonal cells based on land cover, deforestation patterns, and distance from dairy facilities. The results reveal three dominant production systems: Natural Region, Non-Intensive Beef, and Initial Front, with livestock production being prominent. The analysis indicates that there is a correlation between the productive area and deforestation, emphasizing the role of agriculture as a driver of forest loss. Moreover, road networks significantly influence production system spatial distribution, highlighting the importance of infrastructure in land use dynamics. The Shannon diversity index reveals that areas with production systems exhibit greater diversity in land use and land cover classes, reflecting a wider range of modifications. In contrast, natural vegetation areas show lower Shannon values, suggesting that these areas are more intact and are less affected by human activities. These findings underscore the urgent need for sustainable development policies that will mitigate threats to forest resilience and biodiversity in Pará state. Full article

Human-driven changes in land cover and use can significantly impact species ants community structures, often leading to a decline in taxonomic diversity or species homogenization. Ant morphology, used as a proxy for ecological function, offers a valuable framework for understanding the effects of anthropogenic disturbances on ant diversity. This study explored the morphological diversity of ant assemblages in agricultural ecosystems and secondary forests in Italy and the Brazilian Amazon, analyzing how these communities are structured and adapted to different environments. The research aims to understand the ecological interactions and the role of ants in maintaining biodiversity in these contexts. The study was conducted in the Ticino River Natural Park, Italy, and the Paragominas mosaic in Pará, Brazil. The ants were sampled using epigean pitfall traps at 15 agricultural and 13 forest sites. In the secondary forests, the species richness was significantly higher in both countries compared to agricultural areas. In general, the Community Weighted Mean (CWM) of the selected traits (head length, head width, interocular distance, mandible length, eye width, Weber’s length, and tibia length) of Brazilian ants was higher than those of Italian. However, the CWM of agricultural areas of the two countries was more similar. We noticed the convex hull (i.e., the volume of an assemblage in the morphological space) of Brazilian secondary forests was still larger than Italian secondary forests when both assemblages have the same number of species. Morphological homogenization was more pronounced in agricultural settings, whereas secondary forests showed more variability, highlighting the role of environmental filtering in shaping ant communities across land use types. Full article

Euterpe oleracea Mart., also known for its fruit açaí, is a palm native to the Amazon region. The state of Pará, Brazil, accounts for over 90% of açaí production. Demand for the fruit in national and international markets is increasing; however, climate change and diseases such as anthracnose, caused by the fungus Colletotrichum sp., lead to decreased production. To meet demand, measures such as expanding cultivation in upland areas are often adopted, requiring substantial economic investments, particularly in irrigation. Therefore, the aim of this study was to evaluate the potential of açaí rhizobacteria in promoting plant growth (PGPR). Rhizospheric soil samples from floodplain and upland açaí plantations were collected during rainy and dry seasons. Bacterial strains were isolated using the serial dilution method, and subsequent assays evaluated their ability to promote plant growth. Soil analyses indicated that the sampling period influenced the physicochemical properties of both areas, with increases observed during winter for most soil components like organic matter and C/N ratio. A total of 177 bacterial strains were isolated from rhizospheres of açaí trees cultivated in floodplain and upland areas across dry and rainy seasons. Among these strains, 24% produced IAA, 18% synthesized ACC deaminase, 11% mineralized organic phosphate, and 9% solubilized inorganic phosphate, among other characteristics. Interestingly, 88% inhibited the growth of phytopathogenic fungi of the genera Curvularia and Colletotrichum. Analysis under simulated water stress using Polyethylene Glycol 6000 revealed that 23% of the strains exhibited tolerance. Two strains were identified as Bacillus proteolyticus (PP218346) and Priestia aryabhattai (PP218347). Inoculation with these strains increased the speed and percentage of açaí seed germination. When inoculated in consortium, 85% of seeds germinated under severe stress, compared to only 10% in the control treatment. Therefore, these bacteria show potential for use as biofertilizers, enhancing the initial development of açaí plants and contributing to sustainable agricultural practices. Full article

The cocoa tree (Theobroma cacao L.) has seeds that after processing become a valuable agricultural commodity in the world. In Brazil, the state of Pará located in the Eastern Amazon is the main producer, accounting for more than 53% of the national production. Although the region is the largest producer, no studies are found in the literature containing data on the sensory quality of the beans. Thus, the purpose of this study is to establish the sensory profile of Amazonian cocoa from the main cocoa-producing regions of the Eastern Amazon (Lower Tocantins River, Northeast, West, Southeast and Trans-Amazon). The sensory profile was established from the Quantitative Descriptive Analysis (QDA), in addition to using an affective test to verify consumer preference for the chocolates produced. Physical, physicochemical and bioactive compound evaluations were carried out. Beans from different regions had a similar sensory profile; however, it was possible to observe some differences in certain descriptor terms. In the physical evaluation, the samples presented an acceptable commercial standard, and the humidity was within the values established by the legislation. It was found that the post-harvest and/or processing parameters had no influence on the quality attributes of cocoa beans. Full article

The Tocantins–Araguaia basin is one of South America’s largest river systems, across three Brazilian states (Maranhão, Tocantins, and Pará), within the Legal Amazon region. Despite draining extensive Cerrado savanna and rainforest ecosystems, it has suffered significant degradation, notably in the past 40 years. Human activities, including agricultural expansion, deforestation, and the introduction of non-native species, have worsened the environmental damage, which is alarming since many residents and villages along the middle Tocantins River rely on it for water supply, recreation, and fishing. This study assessed the concentration of potentially toxic and essential elements in water samples from four sampling sites distributed along the middle Tocantins River. The monitoring occurred throughout 2023, involving the measurement of parameters both on-site and in the laboratory. Water quality and its health implications were evaluated using the Weighted Arithmetic Water Quality Index (WAWQI), the Water Quality Index (WQI), and the health risk assessment index. The levels of aluminum, copper, iron, magnesium, and selenium exceeded legal standards. Seasonal fluctuations indicate a complex dynamic influenced by climatic or seasonal factors, with February showing the highest values. Site P1, located in urban areas, exhibited elevated mean concentrations for conductivity, total dissolved solids (TDS), and chlorophyll, indicating the need for continuous monitoring. The nitrogen concentrations at P1 raise concerns regarding drinking water quality, which is a concern for the region’s residents who use untreated river water. Despite seasonal variations in element concentrations, the overall WAWQI categorized all sections as “Excellent,” and the WQI rated as “Good.” Human health risk assessments detected no risks, but continuous monitoring and interventions are crucial for sustained water quality improvement. Full article

Protected areas (PAs) in the Brazilian Amazon have proven to be critical in preserving the rainforest but face increasing threats. Since 2019, illegal activities and land conflicts involving PAs have escalated due to the weakening of environmental institutions. Therefore, up-to-date research is needed to evaluate agricultural pressures on PAs—including Sustainable Use Areas, Indigenous Territories, and Strictly Protected Areas—given its importance in driving deforestation in the Amazon, and to identify hotspots of concern. We analyzed property registration, deforestation, pasture expansion, and cattle transaction records within 158 PAs in the Brazilian state of Pará, which holds most of the remaining forest and the highest rates of deforestation. Our findings show that nearly a quarter of Pará’s 2019–2022 deforestation occurred within PAs, undermining their effectiveness as conservation tools. Despite prohibitions, we found illegally registered private properties in most PA categories including indigenous territories and over a 100% increase in deforestation within PAs from 2015–2018. Over 90% of PAs contained pasturelands in 2022, but only half of them had registered cattle transactions within their borders, which suggests the presence of clandestine cattle activities in these areas as well. Indirect sales to slaughterhouses coming from PAs increased during the study period, potentially due to efforts by ranchers to obscure such cattle origins from companies that are increasingly monitoring their direct suppliers. Finally, we identified 17 high-risk PAs concentrating most threats. Focusing monitoring efforts on property registries and cattle transactions in these areas could significantly reduce illegal deforestation and illegal cattle ranching. While PAs are considered to be cornerstones of forest conservation efforts, our findings show that current policies fail to prevent cycles of land grabbing, illegal ranching, and deforestation that can eventually lead to the downgrading, downsizing, and degazetting of PAs. Given this context, validating property claims, tracing cattle sales, and penalizing deforestation are urgently needed to halt these cycles that threaten PAs. Full article

In recent years, treating and reusing polluted water for agricultural irrigation has become essential to ensuring water and food sustainability. In addition to the factors affecting human health in vegetables and fruits irrigated with treated wastewater, factors affecting consumer preferences, such as flavor and phenolic compounds, should also be examined. This study investigates the effect of treated wastewater irrigation on the aromatic compounds and phenolic composition of capia pepper, which holds a significant position and is extensively used in various food products in the food industry. Drip irrigation with treated and untreated wastewater from the Kalecik Wastewater Treatment Plant was applied to two pepper varieties in the Kalecik district of Ankara, Türkiye. This research found that wastewater irrigation impacted certain aroma components, including para-dichlorobenzene, alpha-cubebene, hexanoate, alpha-farnesene, limonene, isoamyl butyrate, squalene, and alpha-copaene, which contribute to the distinct aroma and fragrance of capia peppers. Total phenolic content, pH, and soluble solids were found to be high in peppers irrigated with wastewater, and it was observed that these parameters increased as the treatment levels of the wastewater decreased. The highest results were obtained in capia peppers irrigated with wastewater. Results indicate that heavy metal levels in peppers align with permissible limits, confirming the usability of both water sources. In the face of global water scarcity and the challenge of feeding an ever-growing population, studies like this offer valuable insights into sustainable and well-informed agricultural practices. Full article

The presence of green areas in urbanized cities is crucial to reduce the negative impacts of urbanization. However, these areas can influence the signal quality of IoT devices that use wireless communication, such as LoRa technology. Vegetation attenuates electromagnetic waves, interfering with the data transmission between IoT devices, resulting in the need for signal propagation modeling, which considers the effect of vegetation on its propagation. In this context, this research was conducted at the Federal University of Pará, using measurements in a wooded environment composed of the Pau-Mulato species, typical of the Amazon. Two machine learning-based propagation models, GRNN and MLPNN, were developed to consider the effect of Amazonian trees on propagation, analyzing different factors, such as the transmitter’s height relative to the trunk, the beginning of foliage, and the middle of the tree canopy, as well as the LoRa spreading factor (SF) 12, and the co-polarization of the transmitter and receiver antennas. The proposed models demonstrated higher accuracy, achieving values of root mean square error (RMSE) of $3.86$ dB and standard deviation (SD) of $3.8614$ dB, respectively, compared to existing empirical models like CI, FI, Early ITU-R, COST235, Weissberger, and FITU-R. The significance of this study lies in its potential to boost wireless communications in wooded environments. Furthermore, this research contributes to enhancing more efficient and robust LoRa networks for applications in agriculture, environmental monitoring, and smart urban infrastructure. Full article

Platonia insignis is a fruit tree native to Brazil of increasing economic importance, with its pulp trading among the highest market values. This study aimed to evaluate the structure and genomic diversity of P. insignis (bacurizeiro) accessions from six locations in the Brazilian States of Roraima, Amazonas, Pará (Amazon biome), and Maranhão (Cerrado biome). A total of 2031 SNP markers were obtained using genotyping-by-sequencing (GBS), from which 625 outlier SNPs were identified. High genetic structure was observed, with most of the genetic variability (59%) concentrated among locations, mainly between biomes (Amazon and Cerrado). A positive and significant correlation (r = 0.85; p < 0.005) was detected between genetic and geographic distances, indicating isolation by distance. The highest genetic diversity was observed for the location in the Cerrado biome (H_E = 0.1746; H_O = 0.2078). The locations in the Amazon biome showed low genetic diversity indexes with significant levels of inbreeding. The advance of urban areas, events of burning, and expansion of agricultural activities are most probably the main factors for the genetic diversity reduction of P. insignis. Approaches to functional analysis showed that most of the outlier loci found may be related to genes involved in cellular and metabolic processes. Full article

Livestock systems have been identified as major emitters of greenhouse gases due to the use of extensive areas with degraded pastures. The objective of this study was to analyze carbon (CO₂) and methane (CH₄) fluxes in the atmosphere as indicators of environmental sustainability in silvopastoral systems. CO₂ and CH₄ fluxes from soil to the atmosphere were monitored in a degraded pasture (predominant species: Panicum maximum cv. Mombaça) grown in full sun and compared with areas with tree species (Bertholletia excelsa, Dipteryx odorata, and Khaya grandifoliola) and productive pasture (Panicum maximum cv. Mombaça) grown in full sun. The study area was in Mojuí dos Campos, western Pará state, Eastern Amazon, Brazil. The evaluations were conducted in a Technological Reference Unit with a silvopastoral system, where animals used the shade of trees during high-temperature periods. The fluxes were measured using an ultraportable greenhouse gas analyzer coupled with static polyvinyl chloride ring chambers installed at the soil–air interface. In conclusion, areas with integrated systems (B. excelsa + pasture and K. grandifoliola + pasture) were better mitigators of CO₂ emissions; the highest emissions occurred in the degraded pasture area during the rainiest months. The CH₄ fluxes were more intense in the areas with degraded pasture and K. grandifoliola + pasture. Converting degraded pasture areas into integrated crop–livestock–forest systems reduced greenhouse gas emissions in the Amazon over 10 years of implementation. The implementation of integrated crop–livestock–forest systems in long-deforested areas with degraded pastures and a low production capacity showed high potential for changes focused on developing sustainable agriculture in the Amazon. Full article

In recent years, climate change has greatly affected agricultural activity, sustainability and production, making it difficult to conduct crop management and food security assessment. As a consequence, significant changes in agricultural land and land cover (LC) have occurred, mostly due to the introduction of new agricultural practices, techniques and crops. Earth Observation (EO) data, cloud-computing platforms and powerful machine learning methods can certainly support analysis within the agricultural context. Therefore, accurate and updated agricultural land and LC maps can be useful to derive valuable information for land change monitoring, trend planning, decision-making and sustainable land management. In this context, this study aims at monitoring temporal and spatial changes between 2001 and 2021 (with a four 5-year periods) within the Chi River Basin (NE–Thailand). Specifically, all available Landsat archives and the random forest (RF) classifier were jointly involved within the Google Earth Engine (GEE) platform in order to: (i) generate five different crop type maps (focusing on rice, cassava, para rubber and sugarcane classes), and (ii) monitoring the agricultural land transitions over time. For each crop map, a confusion matrix and the correspondent accuracy were computed and tested according to a validation dataset. In particular, an overall accuracy > 88% was found in all of the resulting five crop maps (for the years 2001, 2006, 2011, 2016 and 2021). Subsequently the agricultural land transitions were analyzed, and a total of 18,957 km² were found as changed (54.5% of the area) within the 20 years (2001–2021). In particular, an increase in cassava and para rubber areas were found at the disadvantage of rice fields, probably due to two different key drivers taken over time: the agricultural policy and staple price. Finally, it is worth highlighting that such results turn out to be decisive in a challenging agricultural environment such as the Thai one. In particular, the high accuracy of the five derived crop type maps can be useful to provide spatial consistency and reliable information to support local sustainable agriculture land management, decisions of policymakers and many stakeholders. Full article

In the Amazon region, land-use cover change has been identified as the primary factor responsible for deforestation and CO₂ emissions. Concurrently, the average sawn yield of wood industries in the Amazon serves as a vital sustainability indicator due to its linkage with forest degradation and CO₂ emissions. The first part of this study reviews published works and proposes a unified value of 46.54% with a standard deviation of 7.07% for the sawn yield in the State of Pará—Amazon Region. In the second part of this study, principal component analysis is applied to a ten-year historical series, from 2008 to 2018, encompassing 14 indicators across all 144 municipalities of the State of Pará. The results suggest that the socioeconomic dimension, with component loadings between 0.86 and 0.96, is predominantly influenced by population, value-added tax, and the number of households with electric consumption. The number of medical doctors per 1000 people (DOC) is also tied to the socioeconomic dimension, presenting component loadings between 0.72 and 0.80. Indicators such as cattle, deforestation, and CO₂ emissions correlate with the environmental dimension, registering component loadings above 0.7. The factors examined embody the Amazon’s socioeconomic and environmental problems, including cattle rearing, deforestation, agricultural areas, and consequent CO₂ emissions. Indeed, deforestation and CO₂ emissions arise primarily from agriculture and animal husbandry, particularly cattle rearing. Wood production indicators yield low values of component loadings, suggesting a weak correlation with the environmental dimension. However, they simultaneously imply that wood production activity has been associated with CO₂ emissions since 2014 and is therefore connected to land-use change. In summary, this work’s analysis suggests that wood products and wood residues are linked not only to socioeconomic factors but also to forest degradation and CO₂ emissions. Full article