DOI: 10.1016/j.foreco.2013.07.028
Scopus记录号: 2-s2.0-84884989850
论文题名: Optimal soil-sampling design for rubber tree management based on fuzzy clustering
作者: Lin Q. ; Li H. ; Luo W. ; Lin Z. ; Li B.
刊名: Forest Ecology and Management
ISSN: 0378-1127
出版年: 2013
卷: 308 起始页码: 214
结束页码: 222
语种: 英语
英文关键词: Fuzzy cluster analysis
; Hevea brasiliensis
; Management zones
; Nutrient management
; Soil-sampling design
Scopus关键词: Available phosphorus
; Classification algorithm
; Classification results
; Fuzzy performance index
; Hevea brasiliensis
; Management zones
; Nutrient management
; Soil chemical property
; Algorithms
; Biogeochemistry
; Biological materials
; Chemical properties
; Cluster analysis
; Design
; Forestry
; Fuzzy clustering
; Management
; Optimization
; Organic compounds
; Rubber
; Rubber plantations
; Soil surveys
; Soil testing
; Soils
; Nutrients
; algorithm
; concentration (composition)
; design
; forest management
; fuzzy mathematics
; nutrient loss
; pH
; plantation forestry
; rubber
; sampling
; soil erosion
; spatial variation
; topsoil
; Algorithms
; Chemical Properties
; Design
; Forestry
; Nutrients
; Optimization
; Plantations
; Rubber
; Soil
; Surveys
; Testing
; Hevea brasiliensis
英文摘要: Farming management practices related to nutrient recommendation for rubber tree plantations have been a challenge for scientists, farm managers and local producers. Specific caves and building contour ledges to prevent nutrient losses through soil erosion often cause spatial variation of topsoil nutrients in such plantations of rubber trees (Hevea brasiliensis). The design of soil-sampling schemes to test chemical properties of the soil is critical for successful nutrient recommendation for rubber trees. Our objectives were to characterize the spatia variability of soil pH, macronutrient NPK and organic matter in rubber plantations and to evaluate the rationality of soil sampling schemes in rubber plantations for tree nutrient management. The study was conducted in an area of 84m2 consistent of nine rubber trees and soil samples (0-0.2m depth) were taken from 168 grid points with a dimension of 1m×0.5m. Concentrations of total nitrogen, organic matter, available phosphorus, available potassium and pH levels were determined for each soil sample. Based on their spatial variability patterns, the analyzed variables were divided into several homogeneous zones through fuzzy cluster algorithm. The number of subzones was determined using fuzzy performance index and normalized classification entropy to optimize the classification algorithm. The classification results showed that there were three optimal sampling zones for the soil chemical properties. The analysis of variance indicated that chemical properties were significantly different between the delineated zones. The delineated management zones could be used as a reference for making soil-sampling scheme in the rubber plantation. The results of this study have the implication in optimization of soil sampling planning for soil testing for nutrient recommendation. Fuzzy cluster algorithms could classify soil chemical properties into three practical zones by reducing intrazone variability, which would provide with useful information for making effective soil-sampling schemes in rubber tree plantations. © 2013. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/66348
Appears in Collections: 影响、适应和脆弱性
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作者单位: Department of Soil and Water Sciences, China Agricultural University, Beijing 100193, China; Rubber Research Institute, Chinese Academy of Tropical Agriculture Sciences, Danzhou 571737, China; Environment and Plant Protection Institute, Chinese Academy of Tropical Agriculture Sciences, Haikou 571101, China; Danzhou Scientific Observation and Agro-Environmental Experimental Station, Chinese Ministry of Agriculture, Danzhou 571737, China
Recommended Citation:
Lin Q.,Li H.,Luo W.,et al. Optimal soil-sampling design for rubber tree management based on fuzzy clustering[J]. Forest Ecology and Management,2013-01-01,308