Impact of different crops on the spatial variability of the chemical attributes of Indian black earth in Southern Amazonas

• Autor(a) principal: Silva,João José Costa
• Data de Publicação: 2021
• Outros Autores: Campos,Milton César Costa, Brito Filho,Elilson Gomes de, Brito,Wildson Benedito Mendes, Leite,Alan Ferreira Lima, Simões,Emily Lira, Cunha,José Maurício, Oliveira,Flávio Pereira de
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Bragantia
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0006-87052021000100249
• topic: Amazon soils; use and management; anthropization

ABSTRACT In the Amazon region, soil patches with an anthropic A horizon are found, called Indian black earths (IBEs). Indian black earths are highly fertile and, therefore, are deforested by small local farmers to cultivate without basic management that maintains soil and crop sustainability. Therefore, in order to evaluate the effect of using different cultures on the spatial variability of soil chemical attributes, three cultivated IBEs and one IBE under natural forest were selected for georeferencing and sample collection. The collection was made with a mesh system with 88 points per IBE, stratified in three layers: 0–0.05, 0.05–0.10 and 0.10–0.20 m. The soil was sampled, dried in the shade and sieved to obtain the fine earth fraction for analysis of chemical attributes. Descriptive statistical and geostatistical analyses were applied to the results. The use and management of soil influenced the spatial behavior of the chemical attributes of IBEs. The cultivation of Brachiaria over many years favored the reduction of the spatial variability of chemical attributes. The use of cacao and coffee crops also favored the homogeneity of the IBEs in relation to the natural forest, but not as much as for Brachiaria, likely due to the succession of crops that preceded these crops. The IBE in the forest contains a high natural spatial correlation in the first 0.1 m of the surface; however, more than 70% of this correlation is linked to a random variation.