Evaluation of Mn concentration provided by soil in citrus-growing regions


TÜTMEZ B., DAĞ A. , ERDEM H. H. , Torun B.

COMPUTERS AND ELECTRONICS IN AGRICULTURE, cilt.67, ss.27-34, 2009 (SCI İndekslerine Giren Dergi) identifier identifier

  • Cilt numarası: 67
  • Basım Tarihi: 2009
  • Doi Numarası: 10.1016/j.compag.2009.02.005
  • Dergi Adı: COMPUTERS AND ELECTRONICS IN AGRICULTURE
  • Sayfa Sayısı: ss.27-34

Özet

Manganese (Mn) is an essential nutrient element in citrus growing and Mn deficiency causes some problems related with physiological and morphological structure. Spatial evaluation of Mn obtained from soils in citrus-growing areas is the main objective of this paper. For this purpose, a citrus-growing region in Turkey has been selected and three effective estimation methods: kriging, neural-fuzzy modelling, and fuzzy interval arithmetic have been considered for the spatial evaluations. The model works primarily focus on the model accuracy and smoothing degree of estimations. In addition, error analysis and comparative assessments, which present the advantages and drawbacks of the models, are conducted in the paper. The results and performance evaluations prove the superiorities of soft computing approach in this evaluation. (C) 2009 Elsevier B.V. All rights reserved.
Abstract

Manganese (Mn) is an essential nutrient element in citrus growing and Mn deficiency causes some problems related with physiological and morphological structure. Spatial evaluation of Mn obtained from soils in citrus-growing areas is the main objective of this paper. For this purpose, a citrus-growing region in Turkey has been selected and three effective estimation methods: kriging, neural-fuzzy modelling, and fuzzy interval arithmetic have been considered for the spatial evaluations. The model works primarily focus on the model accuracy and smoothing degree of estimations. In addition, error analysis and comparative assessments, which present the advantages and drawbacks of the models, are conducted in the paper. The results and performance evaluations prove the superiorities of soft computing approach in this evaluation.