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| Magalhães,Wellington de A.; Freddi,Onã da S.; Wruck,Flávio J.; Petter,Fabiano A.; Tavanti,Renan F. R.. |
| ABSTRACT Assess the physical quality of agricultural soils it is important to establish the management more adequate for plant growth. In this study, the soil water retention curve and S index as indicators of soil physical quality were evaluated in five integrated production systems in the following forestry arrangements: Eucalyptus in a single line, double line and triple line (Eucalyptus I, II and III respectively), Balsa in triple line and Teak triple line. The density and arrangement of forest trees influence the soil physical properties. Less soil water retention was observed in the Teak and Balsa wood systems in the layers 0-0.10 and 0.10-0.20 m. The field capacity, permanent wilting point, and available water were lower under the projection from... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Eucalyptus; Pore size distribution; Soil structure; ICLF. |
| Ano: 2018 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162018000100064 |
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| Tavanti,Renan F. R.; Freddi,Onã da S.; Tavanti,Tauan R.; Rigotti,Adriel; Magalhães,Wellington de A.. |
| ABSTRACT The least limiting water range (LLWR) is a soil physical quality indicator that receives much attention. It has been criticized and put to the test regarding mathematical models that compose it since they describe the behavior of soil physical attributes in a simplified way. This study aimed to assess the efficiency of some pedofunctions proposed in the literature and artificial neural networks on the accuracy in predicting soil water retention at potentials equivalent to field capacity (θFC) and permanent wilting point (θPWP). In other words, to apply the best models to LLWR of two soil types (Oxisol and Ultisol) and verify changes in their structure. The results indicated that pedofunctions using sand, silt, clay, bulk density, and soil organic... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Soil physics; Soil physical quality indicator; Available water; Pedotransfer functions; Artificial neural networks. |
| Ano: 2019 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162019000400444 |
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