DSpace Coleção: Artigo em periódico indexado (CNPS)

Avaliação da condutividade hidráulica saturada do solo num Argissolo Amarelo, sob sistema de integração pecuária-floresta no Médio Vale do Paraíba do Sul - Rio de Janeiro.

Thu, 01 Jan 2026 00:00:00 GMT

Título: Avaliação da condutividade hidráulica saturada do solo num Argissolo Amarelo, sob sistema de integração pecuária-floresta no Médio Vale do Paraíba do Sul - Rio de Janeiro. Autoria: TEIXEIRA, W. G.; BALIEIRO, F. de C.; VASQUES, G. M.; DONAGEMMA, G. K.; GONÇALVES, A. O.; MULLER, M. D.; MARTINS, C. E.; CARVALHO FILHO, A. de Conteúdo: Este estudo avaliou a condutividade hidráulica saturada avaliada no campo (Kfs) em um sistema de integração pecuária-floresta (IPF) no município de Valença, RJ que está implantado num Argissolo Amarelo Distrófico sob eucalipto e braquiária. O componente arbóreo atingiu maturidade aos 73 meses, com área basal de 9,22 m2 ha-1. Utilizou-se permeâmetro de poço automatizado, com poço escavado com 20 cm de profundidade. As medições abrangeram o renque (linha das árvores), a borda (na projeção da copa das árvores) e o pasto. A Kfs foi classificada como baixa em todas as posições (< 3,1 mm h⁻¹). A borda (3,05mm h⁻¹) apresentou valores significativamente superiores ao renque (0,97 mm h⁻¹) e ao pasto (1,09 mm h⁻¹). A restrição hídrica decorre do adensamento no horizonte BA e da transição para o Bt, que é consequência de processos pedogenéticos e do pisoteio animal. Tais condições situam o solo no limite inferior de condutividade para Argissolos no Brasil. Conclui-se que o solo possui restrição severa ao fluxo de água. A maior densidade de raízes das espécies, na borda, favorece a conectividade de poros. Chuvas intensas geram alto risco de enxurradas pela baixa permeabilidade.

Performance of the SWAP–WOFOST model for simulating cotton growth and yield under tropical cerrado conditions.

Thu, 01 Jan 2026 00:00:00 GMT

Título: Performance of the SWAP–WOFOST model for simulating cotton growth and yield under tropical cerrado conditions. Autoria: BENDER, E. P.; RODRÍGUEZ, L. D.; JANTALIA, C. P.; GONÇALVES, A. O.; TEIXEIRA, P. C.; LYRA, G. B. Conteúdo: Process-based agro-hydrological models are essential tools for assessing crop growth and yield under contrasting management and environmental conditions. This study assessed the performance of the coupled Soil-Water-Atmosphere-Plant and World Food Studies Simulation Model (SWAP–WOFOST) to simulate cotton (Gossypium hirsutum L., cv. FiberMax 975 Wild Strike®) growth and yield under tropical Cerrado conditions in western Bahia, Brazil. Field experiments were carried out during the 2014/2015 growing season under three nitrogen management treatments: ammonium sulfate®, prilled urea®, and a control without nitrogen fertilization. The SWAP component was calibrated to simulate soil water dynamics, whereas WOFOST was used to represent crop growth and yield. Model performance was evaluated using the coefficient of determination (R²), Willmott’s agreement index (d-index), Root Mean Square Error (RMSE), Nash–Sutcliffe efficiency (NSE), and the performance index (c-index). The SWAP model showed limited performance in simulating soil volumetric water content, with low precision (R²), agreement (d-index) and efficiency (NSE), indicating limitations in representing near-surface soil water dynamics, particularly after rainfall events. In contrast, the WOFOST component showed excellent performance in simulating leaf area index, reproductive structure biomass, and total aboveground biomass across all treatments. These results indicate that, despite limitations in soil water content representation, the coupled SWAP–WOFOST framework was robust for simulating cotton growth and yield responses under contrasting nitrogen management strategies. The model may support assessments of crop performance and nitrogen fertilization strategies under tropical Cerrado conditions.

Anthropic soils in SiBCS and WRB: review of criteria and conceptualization of the Anthropic horizon.

Thu, 01 Jan 2026 00:00:00 GMT

Título: Anthropic soils in SiBCS and WRB: review of criteria and conceptualization of the Anthropic horizon. Autoria: CORDEIRO, F. R.; FONTANA, A.; ANJOS, L. H. C. dos; TEIXEIRA, W. G. Conteúdo: The diagnostic anthropic A horizon in the Brazilian Soil Classification System (SiBCS) and the Pretic horizon in the World Reference Base for Soil Resources (WRB) comprise the surface mineral genetic horizons of soils formed under strong influence of original indigenous communities for a long time, notably in Brazil those known as Terras Pretas de Índio (TPI) or Amazonian Dark Earths (ADE). The surface horizons of these soils in Brazil are characterized by ceramic artifacts, charcoal, dark colors, and higher levels of carbon, calcium, magnesium, and phosphorus than the adjacent soils. This study aimed to propose additional quantitative criteria for the anthropic A horizon in the SiBCS and contribute to the Pretic horizon and Pretic Anthrosols in the WRB. A database of many studies on these soils was compiled, including morphological, physical, and chemical diagnostic characteristics of horizons classified as anthropic (Au) in anthropized soils. The following data was used to identify and differentiate these horizons: thickness, color (value and chroma), pH(H2O), calcium (Ca2+), magnesium (Mg2+), sum of bases (SB), cation exchange capacity (CEC), base saturation (V), available phosphorus (P – Mehlich-1 extractant), and organic carbon (Corg). For SiBCS, it is suggested to define the diagnostic anthropic A horizon based on a limit of organic carbon content (Corg) greater than or equal to 6.0 g kg-1 and a color with value ≤4 and chroma ≤3; to create the “anthropic character” for surface mineral diagnostic horizons with expressive anthropic modifications that do not meet the quantitative criteria of thickness, color, P, and Corg for the diagnostic anthropic A horizon; and to define a criteria of “anthric properties”, to be used in soils in which the surface mineral diagnostic horizons show recent and significant modifications due to agricultural and/or other activities, meeting a P content (Mehlich-1 extractant) ≥30 mg kg-1 and V ≥50 %, abrupt transition from the surface horizon to the subsequent one, and/or absence of transitional horizons AB and/or BA. In the WRB system, it is proposed that the Pretic horizon should maintain the P content (Mehlich-1 extractant) ≥30 mg kg-1, and in the Pretic Anthrosols class, to reduce the combined thickness of Pretic sub horizons to ≥0.30 m (0.30 m) within 1.00 m (1.00 m) of the mineral soil surface.

High resolution 4D soil organic carbon stock mapping at farm scale.

Thu, 01 Jan 2026 00:00:00 GMT

Título: High resolution 4D soil organic carbon stock mapping at farm scale. Autoria: ROSIN, N. A.; DEMATTÊ, J. A. M.; RODRÍGUEZ-ALBARRACÍN, H. S.; ROSAS, J. T. F.; BARTSCH, B. dos A.; NOVAIS, J. de J. M.; PELEGRINO, M. H. P.; CERRI, C. E. P.; MELLO, D. C. de; FALCIONI, R. Conteúdo: Soil organic carbon (SOC) is intrinsically linked to global carbon balance, climate change mitigation, soil health, and agricultural productivity. Therefore, obtaining accurate information on the spatial-temporal of the soil organic carbon stock (SOCS) is essential. We proposed a four-dimensional (4D) SOCS mapping approach, encompassing space (two dimensions), depth and time. A 100 × 100 m grid sampling was conducted in 1997 and 2022 at two depths (0–20 cm and 80–100 cm) in a sugarcane farm. Dynamic and static covariates representing the soil formation processes were used to fit three Cubist models. We tested three strategies for SOCS spatial-temporal mapping: 1) a model for each year, 2) a model fitted using only the data of the last year (2022) and 3) a multitemporal model using data of both periods. Based on external validation, strategy 1 and 3 produced more accurate and less biased maps, with coefficient of determination (R2) of 0.74, root mean square error (RMSE) of 7.69 ton ha−1 and bias of 3.43 ton ha−1 and R2 of 0.76, RMSE of 7.19 ton ha−1 and Bias of 3.25 ton ha−1 for strategy 3, respectively. Strategy 2 was less efficient (R2 = 0.71; RMSE = 11.06 ton ha−1; Bias = 7.93 ton ha−1). Strategy 3 is particularly useful for SOCS mapping when only limited temporal observations are available. Soil attributes (static) were most important covariates for modeling, followed by a bare soil image (dynamic) and vegetation information (dynamic). An increase in SOCS was observed in most sampling sites and predicted maps. The SOCS dynamic was related to soil type, geology and showed an inverse relationship with bare soil frequency. Finally, the SOCS saturation deficit was assessed by spatio-temporal mapping.