http://repositorio.ufc.br/handle/riufc/104 2026-06-10T19:49:46Z 2026-06-10T19:49:46Z Souza, Francisca Evelice Cardoso de http://repositorio.ufc.br/handle/riufc/86069 2026-04-28T12:48:02Z 2025-01-01T00:00:00Z

Título: Espectroscopia de reflectância vis-NIR-SWIR-MIR na caracterização de perfis e avaliação de atributos de solos típicos do Nordeste do Brasil Autor(es): Souza, Francisca Evelice Cardoso de Abstract: Soil is essential for life on Earth and for the performance of ecosystem services, making efficient monitoring of its attributes essential. Traditionally, soil is evaluated through wet chemistry laboratory analyses, but this technique has proven to be costly and time consuming. As a promising alternative, remote sensing using reflectance spectroscopy stands out for allowing rapid and low cost pedological analyses, which is especially advantageous for the study of heterogeneous regions susceptible to degradation, such as Northeast Brazil. Given this context, the objectives of this study were: to explore the potential of visible to mid-infrared spectra to characterize the spectral behavior of soils in the Northeast region; to quantify the physical and chemical attributes of these soils, including salinity and sodicity, using spectroscopy in the 350 - 15000 nm range and multivariate statistical algorithms. A total of 114 soil samples were evaluated, covering nine orders, collected from 24 soil profiles distributed across 13 cities in Ceará. Through wet chemistry analyses, the following attributes were determined: organic carbon, total nitrogen, available phosphorus, exchangeable potassium, calcium, magnesium, sodium, and aluminum, electrical conductivity, pH, base sum, cation exchange capacity, base saturation, and sodium saturation percentage. Spectral analysis evaluated soil reflectance in the visible, near infrared, short wave infrared (vis-Nir-SWIR), and mid infrared (MIR) ranges, with data preprocessed using Savitzky Golay smoothing and conversion to absorbance. The results of the conventional analysis were evaluated using descriptive statistics. The smoothed data were subjected to principal component analysis (PCA), and the PCA scores were used for cluster analysis with the unsupervised Fuzzy K means classification algorithm. To quantify the attributes, predictive models were developed with raw and preprocessed spectra using Partial Least Squares Regression, Support Vector Machine with linear and radial kernel functions, and Cubist Algorithm algorithms. The performance of the predictive models was evaluated by the metrics R², RMSE, RPD, and RPIQ. The results of the qualitative analysis rev ealed spectral behaviors with distinct patterns between soil orders. Unsupervised classification grouped samples based on horizon characteristics, with the MIR region showing greater sensitivity to identify more subtle variations between horizons. In the quantitative analysis, all attributes were predicted with at least satisfactory performance, except for calcium, which showed unsatisfactory performance with R² below 0.50. The models developed with MIR data consistently outperformed those in the vis NIR SW IR range for most attributes. The predictions of electrical conductivity and sodium saturation percentage showed reasonable performance, highlighting the potential of the technique for diagnosing soil salinity and sodicity. These highlighting the potential of the technique for diagnosing soil salinity and sodicity. These results confirm the potential of reflectance spectroscopy as an efficient and alternative tool for characterizing and predicting attributes in heterogeneous soils. Tipo: Tese

2025-01-01T00:00:00Z Santos, Ruggeri Mikahaknem Mariano http://repositorio.ufc.br/handle/riufc/85939 2026-04-22T17:46:57Z 2026-01-01T00:00:00Z

Título: A desertificação da caatinga: impactos na estrutura da comunidade de fungos e na atividade enzimática do solo Autor(es): Santos, Ruggeri Mikahaknem Mariano Abstract: The loss of productive capacity in soils used for agricultural and livestock purposes has increased worldwide, mainly due to overexploitation and the adoption of inadequate management practices. Soil compaction, salinization, erosion, and reduced plant biomass growth are common consequences of soils undergoing desertification. However, the impacts of this process on soil fungal communities are still poorly understood. Several restoration techniques have been developed to mitigate or reverse soil degradation. Therefore, the hypothesis tested was that desertification alters soil fungal diversity, the composition of fungal groups, and soil enzymatic activity, and that environmental restoration techniques—such as grazing exclusion, cover crop planting, and reforestation—can restore and increase soil fungal diversity in degraded areas of the Brazilian semiarid region. Soil samples (0–10 cm) were collected from four desertification nuclei in northeastern Brazil and classified into three scenarios: (i) areas with native Caatinga vegetation, (ii) areas affected by desertification, and (iii) areas under environmental restoration. Soil samples were subjected to physical (aggregate stability), chemical (C and N content, pH, and salinity), and biological analyses (total organic carbon, microbial carbon, enzymatic activity and stoichiometry, glomalin content, and fungal diversity through DNA sequencing of the ITS region). Amplicon sequencing analyses were performed using QIIME 2, and uni- and multivariate analyses were conducted in RStudio to integrate the datasets. Extracellular enzymes were sensitive to degradation and restoration processes across all nuclei. Overall, the degradation process did not promote significant changes in alpha diversity but caused shifts in beta diversity in all nuclei. The fungal genera Aspergillus and Penicillium showed higher relative abundance in native vegetation and restoration areas, whereas Curvularia was more abundant in degraded areas. Both soil degradation and restoration appear to favor the emergence of specialist groups under different environmental scenarios. Enzymatic activity, microbial carbon, glomalin content, and soil C and N levels showed strong positive correlations with the fungal community structure. Co-occurrence network analysis demonstrated that both soil degradation and environmental restoration promote shifts in dominant fungal groups, which establish new and complex interaction networks. Overall, soil degradation alters the functional structure of fungal communities, characterized by an increase in phytopathogenic groups and a reduction in saprotrophic groups. Tipo: Dissertação

2026-01-01T00:00:00Z Carrillo, Joseph Jordan Poveda http://repositorio.ufc.br/handle/riufc/85758 2026-04-10T17:18:35Z 2026-01-01T00:00:00Z

Título: Comunidade microbiana sintética (SYNCOM) promove redução da adubação nitrogenada na bananeira Autor(es): Carrillo, Joseph Jordan Poveda Abstract: Banana cultivation is essential for food security; however, its high dependence on nitrogen fertilizers results in increased production costs and environmental impacts. In this context, the use of Synthetic Microbial Communities (SynCom) emerges as a biotechnological alternative to enhance nutrient use efficiency. This study aimed to evaluate the agronomic efficiency of a SynCom composed of Bacillus strains and diazotrophic bacteria in promoting the growth of banana seedlings cv. Prata Catarina, with reduced nitrogen fertilizer input. The strains were functionally characterized in vitro for biological nitrogen fixation (BNF), indole-3-acetic acid (IAA) production, phosphorus solubilization and mineralization, as well as the production of biosurfactants and siderophores. Bacillus subtilis BR10788 and Azospirillum lipoferum BR11501 stood out for their high IAA production (46.06 and 43.51 μg mL⁻¹, respectively) and positive BNF activity. Phosphorus solubilization and mineralization showed low levels for all strains but indicated complementary functional potential. Azospirillum lipoferum BR11501 and Acidovorax sp. BR11652 exhibited higher biosurfactant and siderophore production, evidenced by emulsification indices of up to 68% and siderophore halos reaching 2.07 mm, highlighting their role in nutrient mobilization and root colonization. Under greenhouse conditions, co-inoculation of the selected strains (Bacillus LPPC282 × Azospirillum lipoferum BR11501 and Bacillus subtilis BR10788 × Acidovorax sp. BR11652) showed a synergistic effect superior to individual inoculation, promoting increases of up to 127.90% in shoot dry mass and 100% in root dry mass, even under reduced nitrogen levels. It is concluded that the developed SynCom exhibits high biotechnological potential, as the functional complementarity among auxin production, biological nitrogen fixation, and biosynthesis of biosurfactants and siderophores contributed to enhanced growth and biomass accumulation of banana seedlings. Tipo: Dissertação

2026-01-01T00:00:00Z Silva, Francisco Mateus da Cunha http://repositorio.ufc.br/handle/riufc/85696 2026-04-08T18:06:19Z 2025-01-01T00:00:00Z

Título: Avaliação de fósforo em solos utilizando espectroscópia de reflectância e algoritmos quimiométricos Autor(es): Silva, Francisco Mateus da Cunha Abstract: Maintaining adequate phosphorus levels in the soil is a determining factor for plant development, influencing vital metabolic processes. Its determination through laboratory methods based on chemical extraction reagents not only generates waste but also makes these techniques costly and time-consuming, rendering their continuous and regular application unfeasible in many agricultural scenarios. This hinders the precise characterization of agricultural areas. The present study aims to evaluate the predictive potential of reflectance spectroscopy for quantifying available phosphorus content in soils, through the application of different chemometric algorithms and transformations of spectral reflectance data acquired by an optical spectroradiometer within the 350–2500 nm range, along with variable selection. For this research, 75 samples of a Neossolo quartzarenico and 75 samples of an Argissolo acinzentado were collected in the Baixo Acaraú irrigation district, and subsequently treated with 15 different concentrations of the commercial fertilizer MAP in 5 replications. For spectral data acquisition, the FieldSpec Pro FR 3 optical sensor was used. In addition to raw reflectance, spectral normalization, Savitzky-Golay filtering, and continuum removal were applied for qualitative and chemometric analyses. Available phosphorus content in the samples was determined using a UV/VIS spectrophotometer based on the Mehlich 1 extraction solution. For the calibration of the phosphorus prediction models, multiple linear regression (MLR), principal component regression (PCR), and partial least squares regression (PLSR) were employed, considering all wavelengths as predictor variables, along with variable selection via Stepwise-Forward. The results showed that spectral normalization combined with PLSR regression on the full spectrum (450–2450 nm) was the most efficient approach for predicting available phosphorus. In the combined RQO + PAcd dataset, R² = 0.95, RMSE = 12.75 mg kg⁻¹, and RPD = 4.31 were obtained; for RQO alone, R² = 0.95, RMSE = 8.30 mg kg⁻¹, and RPD = 4.66; and for PAcd, R² = 0.92, RMSE = 17.76 mg kg⁻¹, and RPD = 3.30 consistently outperforming the PCR models in all cases. Variable selection through correlation filtering and stepwise–forward reinforced the relevance of bands associated with organic matter (650–850 nm), iron oxides (850–900 nm), and 2:1 clay minerals (1400, 1900, and 2200 nm). After variable selection, model performance was heterogeneous and generally inferior to models calibrated with all wavelengths, with PCR outperforming the other regression methods and only the normalized model of the combined dataset achieving an excellent category with R² = 0.84, RMSE = 23.65 mg kg⁻¹, and RPD = 2.49. Tipo: Dissertação

2025-01-01T00:00:00Z