小麦,籽粒品质,预测模型,GIS,空间变异," /> 小麦,籽粒品质,预测模型,GIS,空间变异,"/> wheat,grain quality,prediction model,GIS,spatial variation,"/> <font face="Verdana">Spatial Variation Analysis of Wheat Grain Quality Based on Model and GIS#br# </font>

Scientia Agricultura Sinica ›› 2009, Vol. 42 ›› Issue (9): 3087-3095 .doi: 10.3864/j.issn.0578-1752.2009.09.009

• TILLAGE & CULTIVATION·PHYSIOLOGY & BIOCHEMISTRY • Previous Articles     Next Articles

Spatial Variation Analysis of Wheat Grain Quality Based on Model and GIS#br#

HUANG Fen, ZHU Yan, JIANG Dong, JING Qi, CAO Wei-xing#br#   

  1. (南京农业大学农学院/江苏省信息农业高技术研究重点实验室)
  • Received:2008-08-28 Revised:2008-12-30 Online:2009-09-10 Published:2009-09-10
  • Contact: CAO Wei-xing

Abstract:

【Objective】 The aim of this study is to explore the method of simulating the grain quality index and analyzing the spatial variation characteristics based on GIS and wheat quality index prediction model. 【Method】 Firstly, literature data with five varieties at five eco-sites were used for the evaluation of grain quality model at site scale. Secondly, based on the weather data sets of 2000-2003 at 40 eco-sites in Jiangsu province and experimental data from five eco-sites and six wheat cultivars, three main wheat grain quality indices at regional scale were calculated with two methods such as ‘calculate first, interpolate later’ (CI) and ‘interpolate first, calculate later’ (IC). Finally, the spatial variation characteristics of three wheat grain quality indices in Jiangsu province were analyzed, and three spatial distribution raster maps for grain protein content, wet gluten content and sedimentation were made based on the geo-statistics and GIS. 【Result】 The IC was suggested to be preferable for up scaling the grain quality model, with the RMSE less than 20% between simulated and observed values for three quality indices. The spatial autocorrelation of grain protein content, wet gluten content and sedimentation under research region was significant within the 7.16 km variation range, and the anisotropic structure varies more evidently in longitudinal and latitudinal directions. The spatial raster maps could show the distribution and the variation trend of regional grain quality effectively. 【Conclusion】 The result indicated that the IC based simulation on regional spatial variation of wheat grain quality is feasible. This study might provide reference for analysis of ecological variation on crop quality.

Key words: wheat')">wheat, grain quality, prediction model, GIS, spatial variation

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