Irrigated corn yield as related to spatial variability of selected soil properties in a silty clay loam and sandy soils.

• Ano de defesa: 2000
• Autor(a) principal: COELHO, A. M.
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Palavras-chave em Português: Propriedade fisico-quimico; Maize; Chemicophysical properties; Irrigação; Milho; Zea Mays; Solo; irrigation; soil
• Link de acesso: http://www.alice.cnptia.embrapa.br/alice/handle/doc/484182

Precision farming is important to development agricultural production systems and has created a need for spatial data on crop yield and soil characteristics. The objectives of this research were to identify: (i) the spatial and structural variation of soil properties across the landscape; (ii) how yields are related to these soil properties; and (iii) how information of spatial variability within soil physical, chemical, and biological properties can be used to asses in field soil degradation. On farm research was conducted on center-pivot-irrigated fields in Adams and Buffalo Counties, Nebraska, during 1997 and 1998. Samples were taken and analyzed soil physical, chemical, and biological properties, plant population, leaf tissue analysis for nutrients, and grain yields. Factor analysis, multivariate linear regressions, and geostatistics were used to explore soil and crop variability, and classify and map soil properties in the fields. On the farm field with a finer textured silty clay loam soil, soil variation was decomposed into five factors, which accounted for 75% of the total variance. Regression models based on these showed that soil fertility as related to available phosphorus and manganese, as associated with organic matter, was associated with 73% of corn yield variability. However, the application of Mn and P fertilizers did not improve significantly the corn grain yield. These indicated that yields were limited by constraints other than P and Mn. The results suggest the need ofr careful interpretation when using statistical models to seek cause and effect relationships related to yield variability in fields. On the farm field characterized by sandy soils, most of the soil variation related to crop growth was described by five factors, which collectively explained 85% of the total soil variability. Regression models based on these factors were associated with 50% of the corn yield variation. Soil physical-chemical factor, as related to organic matter, texture, bulk density, and pH had the largest effect on the variation of corn yield. Loss of organic matter due to erosion, intensive tillage and input of nitrogen fertilizer, acidification and compaction were some indicators of soil and environmental degradation under current management practices.