Identification of different potential production areas for corn in Italy through multitemporal yield map analysis

被引:13
作者
Bocchi, Stefano
Castrignano, Annamaria
机构
[1] Dept Crop Sci, Sect Agron, I-20133 Milan, Italy
[2] CRA Agron Inst Res, I-70125 Bari, Italy
关键词
precision agriculture; spatial and temporal variation; geostatistics; yield map; educational research farm;
D O I
10.1016/j.fcr.2007.03.012
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
In order to optimize production factors, farmer has to know production variability and its origin at both the farm level and the field level. Improving Nitrogen management for cereal crops, which need high amounts of the element during the whole production cycle requires, as precision agriculture states, that within-field variability is accurately identified and interpreted. This is particularly difficult in those situations where agronomically significant variability is detected and even in small fields, as is generally the situation in some European countries. The present study is aimed at defining an integrated methodology to process production data which, through the combined use of hardware (GPS, grain sensor) and software (GIS, geostatistics) allows for acquisition, analysis and representation of information related to the variation of production potential within the field. Data on grain yield and 1000-grain weight obtained during a 4-year period from a corn (Zea mays L.) field were acquired and analysed to study spatial and temporal variability through geostatistical techniques. Synthetic maps of attitude and stability of production were obtained by combining individual production maps in a GIS environment. These results may prove to be very useful to identify isomanagement areas in precision agriculture. (c) 2007 Published by Elsevier B.V.
引用
收藏
页码:185 / 197
页数:13
相关论文
共 26 条
[1]  
BLACKMORE BS, 1997, 1 EUR C PREC AGR WAR
[2]   The interpretation of trends from multiple yield maps [J].
Blackmore, S .
COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2000, 26 (01) :37-51
[3]   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
[4]   Application of factorial kriging for mapping soil variation at field scale [J].
Bocchi, S ;
Castrignanò, A ;
Fornaro, F ;
Maggiore, T .
EUROPEAN JOURNAL OF AGRONOMY, 2000, 13 (04) :295-308
[5]   Study of spatial relationships among some soil physico-chemical properties of a field in central Italy using multivariate geostatistics [J].
Castrignanò, A ;
Giugliarini, L ;
Risaliti, R ;
Martinelli, N .
GEODERMA, 2000, 97 (1-2) :39-60
[6]   3D spatial variability of soil strength and its change over time in a durum wheat field in Southern Italy [J].
Castrignanò, A ;
Maiorana, M ;
Fornaro, F ;
Lopez, N .
SOIL & TILLAGE RESEARCH, 2002, 65 (01) :95-108
[7]  
Chiles J-P., 1999, GEOSTATISTICS MODELL
[8]  
Cressie N, 1993, STAT SPATIAL DATA, DOI [10.1002/9781119115151, DOI 10.1002/9781119115151]
[9]  
Delgado JA, 2005, J SOIL WATER CONSERV, V60, P402
[10]  
Goovaerts P, 1997, Geostatistics for natural resources evaluation