Revista Brasileira de Ciência do Solo (Dec 2024)

Cropping and soil management systems effects on soil organic matter fractions in diversified agricultural fields in the Cerrado

  • Antonino José Jacques Gambôa Fernandez de Oliveira Netto,
  • Lucas Medeiros Fagundes,
  • Luiz Alberto da Silva Rodrigues Pinto,
  • Emerson Trogello,
  • Marcos Gervasio Pereira

DOI
https://doi.org/10.36783/18069657rbcs20240017
Journal volume & issue
Vol. 48

Abstract

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ABSTRACT Soil organic matter (SOM) dynamics can be significantly influenced by various cultivation practices, particularly under environmental and edaphic conditions that enhance and accelerate the transformations of organic materials such as straw, root biomass, and organic fertilizers. This study aimed to evaluate the impact of different cultivation and soil management systems on SOM fractions in agricultural areas of the Cerrado Goiano region. The research was conducted across three areas with diverse production systems: 1) BV area, including soybean monoculture (SM01), integrated crop-livestock-forest (ICLF01), pasture (PA01), and Cerrado vegetation (NV01); 2) ML area, featured soybean-corn monoculture succession (SMS02), agroforestry (AF02), pasture (PA02), and native Cerrado vegetation (NV02); and 3) IF area, comprised soybean-corn succession (SMS03), integrated livestock-forest (ILF03), pasture (PA03), and native Cerrado vegetation (NV03). Disturbed and undisturbed soil samples were collected from two layers: 0.00-0.05 and 0.05-0.10 m. Samples were analyzed for total organic carbon, carbon storage, and SOM physical (granulometric and densimetric) and chemical (fulvic acid, humic acid, and humin) fractionations of soil organic matter (SOM). Additionally, water-floatable light organic matter (LOM), the carbon management index, and its components were determined. Soil organic matter fractions were similarly influenced by the characteristics of cultivation and management systems. However, there were more pronounced differences between systems in the BV area compared to the ML and IF areas. Among the parameters studied, LOM proved to be the most efficient and effective in distinguishing SOM input across different cultivation and soil management systems, particularly in pasture systems.

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