Analyzing the effects of climate variability on spatial pattern of yield in a maize-wheat-soybean rotation

被引:82
作者
Basso, Bruno
Bertocco, Matteo
Sartori, Luigi
Martin, Edward C.
机构
[1] Univ Basilicata, Dept Cropping Syst Forestry & Environm Sci, I-85100 Potenza, Italy
[2] Univ Padua, Dept Landscape & Agroforestry Syst, I-35020 Legnaro, PD, Italy
[3] Univ Arizona, Dept Agr & Biosyst Engn, Tucson, AZ 85721 USA
关键词
crop simulation model; maize; management zones; soybean; yield spatial variability; yield temporal stability; wheat;
D O I
10.1016/j.eja.2006.08.008
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
The identification of homogeneous management zones within a field is crucial for variable rate application of agronomic inputs. This study proposed a methodology to identify homogeneous management zones within a 8 ha field, based on the stability of measured and simulated yield patterns in a maize-soybean-wheat crop rotation in north-east Italy. Crop growth and yield were simulated over a 14-year period (1989-2002) using CERES-Maize, CROPGRO-Soybean and CERES-Wheat models to account for weather effects on yield spatial patterns. The overlay of long-term assessments of yield spatial and temporal data allowed for the identification of two stable zones with different yield levels, one with greater yield (called HS for high and stable yield) and one with lower yield (called LS for low and stable yield). The size of the HS zone identified using 14 years of simulated yield was smaller than the one obtained when considering only yield monitor data taken during the 5-year crop rotation. The LS zone was larger when using simulated data, confirming that the consistency of temporal stability increased by increasing the years considered. The models were able to closely simulate yield across the field when site-specific inputs were used, showing potential for use in yield map interpretation in the context of precision agriculture. Results showed that a combination of GIS tools and crop growth simulation models can be used to identify temporally stable zones, which is a fundamental prerequisite for adopting variable rate technologies. (c) 2006 Elsevier B.V. All rights reserved.
引用
收藏
页码:82 / 91
页数:10
相关论文
共 40 条
[1]  
Basso B, 2003, PRECISION AGRICULTURE, P61
[2]   Spatial validation of crop models for precision agriculture [J].
Basso, B ;
Ritchie, JT ;
Pierce, FJ ;
Braga, RP ;
Jones, JW .
AGRICULTURAL SYSTEMS, 2001, 68 (02) :97-112
[3]  
BASSO B, 2004, RIV AGROMETEOROLOGIA, V1, P34
[4]   Examples of strategies to analyze spatial and temporal yield variability using crop models [J].
Batchelor, WD ;
Basso, B ;
Paz, JO .
EUROPEAN JOURNAL OF AGRONOMY, 2002, 18 (1-2) :141-158
[5]  
BJARNE J, 2003, EUR J AGRON, V19, P23
[6]   The interpretation of trends from multiple yield maps [J].
Blackmore, S .
COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2000, 26 (01) :37-51
[7]   The analysis of spatial and temporal trends in yield map data over six years [J].
Blackmore, S ;
Godwin, RJ ;
Fountas, S .
BIOSYSTEMS ENGINEERING, 2003, 84 (04) :455-466
[8]   Tools for optimizing management of spatially-variable fields [J].
Booltink, HWG ;
van Alphen, BJ ;
Batchelor, WD ;
Paz, JO ;
Stoorvogel, JJ ;
Vargas, R .
AGRICULTURAL SYSTEMS, 2001, 70 (2-3) :445-476
[9]  
Boote KJ, 1998, SYST APPR S, V7, P99
[10]   Defining yield-based management zones for corn-soybean rotations [J].
Brock, A ;
Brouder, SM ;
Blumhoff, G ;
Hofmann, BS .
AGRONOMY JOURNAL, 2005, 97 (04) :1115-1128