https://repositorio.uema.br/jspui/handle/123456789/2240 2026-09-21T20:10:02Z 2026-09-21T20:10:02Z https://repositorio.uema.br/jspui/handle/123456789/6503 2026-09-15T19:01:19Z 2023-03-31T00:00:00Z

Título: Dinâmica socioambiental da produção de Attalea speciosa no ­Maranhão como subsídio para o desenvolvimento sustentável Abstact: The state of Maranhão is the largest producer of babassu in Brazil, a crop primarily exploited by women extractivists known as babassu coconut breakers. Extractivism was once recognized as one of the main productive activities in the agricultural context of Maranhão. Until the mid-1980s, babassu extraction played an important role in the state's economy, particularly after the decline of textile production. However, with the introduction of laws that legitimized the privatization and expropriation of public lands, restricting the access of babassu coconut breakers to babassu palm groves, this activity lost its significance as the coconut breakers lost access to the groves. This fact initiated conflicts over access to this natural resource, which has been decreasing due to the introduction of activities and the establishment of agricultural crops, pastures, and the expansion of deforested areas, which may have influenced the production and extraction of babassu kernels. Therefore, the objective of this study was to identify what has been happening with kernel production over three decades and what has affected the increase or decrease in babassu production in the mesoregions of the state of Maranhão. Data for the research were obtained from the IBGE/SIDRA database, MapBiomas, and Lapig, where geoprocessing techniques were applied using QGIS 3.16.4 software for spatial analysis of babassu kernel production dynamics in the state, and statistical analyses were performed within the routine of the R program. The correlation test and principal component analysis demonstrated that the mesoregions that showed the greatest decrease in kernel production were the eastern, western, and southern regions, with a 50% decrease in production over 30 years. This information will update cartographic data on babassu production and reconstruct the historical evolution of the extractivism of this palm tree, which is crucial for the subsistence of many families. In addition, it will contribute to public policies capable of preserving these areas and promoting greater monitoring and penalties for the improper preservation of these environments.

2023-03-31T00:00:00Z https://repositorio.uema.br/jspui/handle/123456789/6398 2026-09-15T18:56:00Z 2021-07-08T00:00:00Z

Título: Atributos do solo e ciclagem de nutrientes em sistema agrossilvipastoril com adubação nitrogenada Abstact: Knowing the influence of mineral nitrogen fertilization on agroforestry systems and its effects on soil attributes and forage production, as well as its role in the nutrient cycling process, is essential to promote the efficient use of nutrients in this ecosystem.Thus, the objective was to evaluate the effects of mineral nitrogen fertilization and forestry component on forage production, physical attributes and soil organic carbon fractions, on decomposition and chemical composition of Marandu grass litter and bovine excreta, in an agrosilvopastoral system , in the humid tropics of Maranhão.The experiment was conducted in 2019 and 2020, at the Technological Reference Unit - TRU in ICLF of EMBRAPA Cocais in Pindaré Mirim - MA. A randomized block design was used, with four nitrogen fertilization treatments (0, 100, 200 and 400 kg of N ha-1 year-1) and three replications in a total area of 3 ha divided into twelve equal plots kept under continuous stocking with two “tersters” animals, and with a variable stocking rate with “adjustment” animals, annealed steers with an average body weight of 150 to ±180 kg. For the purpose of evaluating forage production and soil attributes, samples were taken through transects perpendicular to the double rows of eucalyptus in each experimental plot.This was divided into five points: P1 (0 m), P2 (1.75 m), P3 (5.25 m), P4 (8.75 m) and P5 (12.25 m), which corresponded to the distances of the eucalyptus row. For each of these distances, the forage was collected to evaluate the production of dry matter of green forage and dry and then the mini trenches of 30 x 30 x 30 cm were opened to collect undeformed samples in the depths: 0 - 10, 10 - 20, 20 - 30 cm, to determine physical attributes (density, macroporosity, microporosity and total porosity).For the chemical attributes of the soil (organic carbon fractions), deformed samples were collected at the same depths perpendicular to the mini-trenches. To evaluate the decomposition of Marandu grass litter and bovine excreta, samples of senescent leaves and feces were used, which were incubated in nylon bags, in exclusion areas, in 2019 and 2020. The chemical composition of Dry Matter (DM), Organic Matter (OM), Fiber in Neutral Detergent (NDF), Fiber in Acid Detergent (ADF), N, C, and C:N ratio were determined. The results of forage mass production in the green and dry fractions of the marandu grass did not differ (P> 0.05) due to nitrogen fertilization, however the green forage mass was influenced by the distance of the double row of eucalyptus, with less production of 1733 kg DM ha-1, 49% of the total mass, closer to the trees. The organic carbon fractions ranged between 10.32 g kg-1 and 7.56 g kg-1 for total organic carbon (TOC) at the estimated doses of 17.14 and 411.43 kg of N ha-1 year-1, respectively. The particulate organic carbon (POC) contents ranged from 1.94 and 4.13 g kg-1 between 200 and 400 kg of N ha-1 yr-1 respectively, with a greater increase in POC for the estimated dose of 203 kg of N ha-1 yr- 1. There was a decrease in organic carbon associated with minerals (OCAM) at doses up to 278 kg of N ha-1 yr-1. The arboreal component influenced the macro and microporosity of the soil, however without effect for the fractions of organic carbon and density of the soil. In depth, the organic carbon fractions decrease with a significant difference between the 0-10 cm layers and the two underlying layers, with values between 11.24 and 8.07 g kg-1 for TOC, 3.85 and 2.39 g kg-1 for POC and 6.92 to 5.67 g kg-1 for OCAM at depths 0-10 and 20-30 cm. The same happens with the physical attributes, with the exception of microporosity. The attribute values ranged from 0.54 to 0.56 m3 m-3 for total porosity, from 0.12 to 0.15 m3 m-3 for macroporosity and from 1.45 to 1.49 g cm-3 for density of the soil at depths 0-10 and 20-30 cm. The production of green forage was reduced as well as the soil microporosity, and the opposite happens with the soil macroporosity close to the double row of trees in an agrosilvopastoral system. The use of nitrogen fertilization in agrosilvopastoral system modifies the physical fractions of organic carbon in the soil, reducing its levels in depth even during a relatively short period of system implementation. The agrosilvopastoral system, in the period evaluated, contributed to improve the physical quality of the soil, in depth and along the distance from the double rows of trees, however, it depends on the type of management used in the area. Litter decomposition between the years 2019 and 2020 was influenced by nitrogen fertilization, with a triple effect (P<0.0001) between the levels of fertilization x time x year. The average speed of decomposition was lower in the second year, with k = 0.00589925 g g-1day-1 against k = 0.00798675 g g-1day-1 in the first year. The average N mineralization in litter was 74% and 17% in feces, which provided an annual input of 146 kg N ha-1 yr-1 and 5 kg N ha-1 yr-1, respectively. There were no differences in the decomposition and chemical composition of excreta (P>0.05) between doses and incubation time for the analyzed variables. Both materials, litter and excreta, presented a high C:N ratio, above 30:1, revealing the greater difficulty of degradation of the material. The nitrogen levels applied did not influence litter and excreta decomposition. The contribution of nutrients via litter decomposition was faster than in the excreta component, due to higher nutrient concentration and decomposition rate. The incubation time of 128 days was not enough to express the real behavior of the litter decomposition. Thus, there is an increasing need for long-term experiments to assess nutrient decomposition in N-fertilized tropical pastures

2021-07-08T00:00:00Z https://repositorio.uema.br/jspui/handle/123456789/6397 2026-09-15T19:02:11Z 2023-06-27T00:00:00Z

Título: Abordagem eco fisiológica para avaliar a evolução do carbono no solo Abstact: By 2050, agricultural productivity will need to be nearly 50% higher than levels observed in 2012. This highlights the need for a production and development model that reconciles agricultural growth with the conservation and sustainability of agroecosystems. The use of management practices capable of increasing stable soil organic matter content is essential to this process. Practices such as the use of high-quality biomass and fertilization with polyvalent cations facilitate this. Therefore, this study aimed to evaluate the interaction effect between high-quality biomass and the polyvalent cations Ca and Si on biological quotients, and how this effect influences the accumulation of the stable fraction of soil organic matter. To achieve this objective, the variables evaluated were the metabolic quotient (qCO2), microbial quotient (CBM:C), calcium, and silicon. A randomized block design was used, comprising eight treatments and four replicates. The treatments consisted of combinations of legumes with calcium, silicon, and urea. The combination of silicon and legume biomass demonstrated the highest carbon use efficiency and the greatest incorporation of organic carbon into microbial biomass. However, the results indicated that combining legume biomass with both polyvalent cations enhanced microbial activity, which in turn promoted the accumulation and stabilization of organic carbon (C-org) within the soil organic matter.

2023-06-27T00:00:00Z https://repositorio.uema.br/jspui/handle/123456789/6394 2026-09-15T19:02:45Z 2024-01-29T00:00:00Z

Título: Análise da fenologia e produtividade da soja utilizando índices de vegetação em diferentes resoluções espaciais Abstact: The objective was to identify vegetation indices with the potential to identify phenological stages and estimate soybean yield using data from different sensor systems. The research was conducted in Balsas, Maranhão, Brazil, in a center-pivot irrigated area, with weekly assessments of phenology and Leaf Area Index (LAI). Spectral data were collected from the study area using the MSI and WFI sensors onboard the Sentinel-2 and Amazônia-1 satellites, respectively. The data were processed to calculate the NDVI, NDWI, SAVI, VARI, Green VI, and GLI indices. The efficiency of identifying phenological stages was determined using Anderson's discriminant analysis and the Random Forest machine learning algorithm. Yield estimation was performed using path analysis (a multivariate technique), with pre-filtering based on Pearson correlation represented by correlation networks. No single vegetation index from the sensor systems showed 100% effectiveness in identifying all phenological stages; however, specific RGB and NIR indices can be used to identify key stages, such as flowering (R1 and R2), the end of pod development (R4), and grain development within pods (R4 to R5.2). Vegetation indices—whether used individually or in RGB and NIR groups—are not efficient for identifying phenological stages on their own; using the indices jointly with the Random Forest algorithm is the most efficient method for this purpose. Furthermore, the Sentinel-2 sensor system outperforms the Amazônia-1 system in identifying soybean phenological stages. Regarding yield estimation, the SAVI and NDVI (infrared) indices enabled satisfactory estimation of soybean yield at the V5 and R2 stages, respectively, using the Amazonia-1 sensor system, while the VARI (RGB) index did so at the R2 and R5.2 stages using the Sentinel-2 sensor system. The spatial resolutions employed in this study were not a limiting factor for soybean yield estimation. Vegetation indices derived from orbital sensors are effective for rapidly and cost-efficiently identifying soybean phenological stages

2024-01-29T00:00:00Z