Use of the farmer's experience variable in the generation of management zones

被引:8
作者
Schenatto, Kelyn [1 ]
de Souza, Eduardo Godoy [2 ]
Bazzi, Claudio Leones [3 ]
Betzek, Nelson Miguel [3 ]
Gavioli, Alan [3 ]
Beneduzzi, Humberto Martins [4 ]
机构
[1] Univ Tecnol Fed Parana, UTFPR, Dept Ciencia Comp, Santa Helena, PR USA
[2] Univ Estadual Oeste Parana, UNIOESTE, Ctr Ciencias Exatas & Tecnol, Cascavel, PR, Brazil
[3] UTFPR, Dept Ciencia Comp, Medianeira, PR USA
[4] IFPR, Inst Fed Parana, Foz Do Iguacu, PR, Brazil
来源
SEMINA-CIENCIAS AGRARIAS | 2017年 / 38卷 / 04期
关键词
Precision agriculture; Clustering; Farmer feeling; Management units; SOIL ELECTRICAL-CONDUCTIVITY; YIELD VARIABILITY; DELINEATION; CLASSIFICATION; DEFINITION; ATTRIBUTES; FIELDS;
D O I
10.5433/1679-0359.2017v38n4Supl1p2305
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
In the spatial variability management of fields, the approach based on management zones (MZs) divides the area into sub-regions, which have spatially homogeneous topography and soil conditions. Such MZs should lead to the same potential yields. Farmers understand which areas of a field have high and low yields, and use of this knowledge may allow the identification of MZs in a field based on production history. The objective of the present study was to evaluate the application of farmer's experience to determine MZs. The study was conducted in three agricultural fields located in the west of the Parana State in Brazil, and the MZs were generated considering three cases: a) without the use of the farmer's experience variable; b) with the variable of farmer's experience and the stable soil properties selected at the variable selection stage; and c) only with the farmer's experience variable. The generated MZs were evaluated using the Variance Reduction (VR) index, Fuzziness Performance Index (FPI), Modified Partition Entropy (MPE), Smooth Index (SI), and Analysis of Variance (ANOVA). The study showed that the use of farmer's experience to set MZs could be an efficient and simple tool, that it could reduce costs for the processes of setting MZs, compared to the traditional method of using stable soil variables and relief.
引用
收藏
页码:2305 / 2321
页数:17
相关论文
共 34 条
[1]  
[Anonymous], 2007, AGR SCI CHINA, DOI DOI 10.1016/S1671-2927(07)60033-9
[2]   Spatial and temporal mapping of groundwater salinity using ordinary kriging and indicator kriging: The case of Bafra Plain, Turkey [J].
Arslan, Hakan .
AGRICULTURAL WATER MANAGEMENT, 2012, 113 :57-63
[3]  
Bazzi C. L., 2015, Journal of Food, Agriculture & Environment, V13, P86
[4]   MANAGEMENT ZONES DEFINITION USING SOIL CHEMICAL AND PHYSICAL ATTRIBUTES IN A SOYBEAN AREA [J].
Bazzi, Claudio L. ;
Souza, Eduardo G. ;
Uribe-Opazo, Miguel A. ;
Nobrega, Lucia H. P. ;
Rocha, Davi M. .
ENGENHARIA AGRICOLA, 2013, 33 (05) :952-964
[5]   Identifying potential within-field management zones from cotton-yield estimates [J].
Boydell B. ;
McBratney A.B. .
Precision Agriculture, 2002, 3 (1) :9-23
[6]  
CROOKSTON R. K., 1996, USING DECISION CASES
[7]  
Czaplewski R.L., 1993, Expected Value and Variance of Moran Bivariate Spatial Autocorrelation Statistic for a Permutation Test
[8]   Spatial and temporal variability of wheat grain yield and quality in a Mediterranean environment: A multivariate geostatistical approach [J].
Diacono, Mariangela ;
Castrignano, Annamaria ;
Troccoli, Antonio ;
De Benedetto, Daniela ;
Basso, Bruno ;
Rubino, Pietro .
FIELD CROPS RESEARCH, 2012, 131 :49-62
[9]  
Dobermann A, 2003, AGRON J, V95, P924, DOI 10.2134/agronj2003.0924
[10]  
DOERGE T. A., 2000, MANAGEMENT ZONES CON