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基于Meta分析和气象因子驱动的苏豫皖小麦籽粒蛋白质含量地理空间分布特征
引用本文:夏树凤,江广帅,赵 鸿,方 乾,胡诗琪,王 凡,蔡 剑,王 笑,周 琴,仲迎鑫,姜 东. 基于Meta分析和气象因子驱动的苏豫皖小麦籽粒蛋白质含量地理空间分布特征[J]. 麦类作物学报, 2021, 41(8): 1033-1043
作者姓名:夏树凤  江广帅  赵 鸿  方 乾  胡诗琪  王 凡  蔡 剑  王 笑  周 琴  仲迎鑫  姜 东
作者单位:南京农业大学农业农村部小麦区域技术创新中心,江苏南京210095
基金项目:江苏省自然科学基金项目(BK20190509);中国博士后科学基金项目(2019M651855);国家重点研发计划项目(2016YFD0300408);国家自然科学基金项目(31901458,31671633)
摘    要:为明确苏豫皖地区小麦籽粒蛋白质含量空间分布规律,收集该区域1999-2019年间与小麦籽粒蛋白质含量相关的研究文献及相应地点的气象数据,运用Meta分析方法建立基于气象因子驱动的小麦籽粒蛋白质含量模型,用ArcGIS反距离插值创建预测图,并利用2019年在江苏实际取样测定的小麦籽粒蛋白质数据予以模型验证;最后根据国家小麦品质标准进行小麦品质区划。结果表明,籽粒蛋白质含量随灌浆中期的总日照时数升高而升高,随播种-孕穗、灌浆前中期的总降水量增加而降低。在苏豫皖各地处于同一气象等级条件时,小麦籽粒蛋白质含量整体上从西向东呈降低趋势。采用2019年多点抽样获得的小麦籽粒蛋白质含量进行验证,发现分省拟合模型的效果较好,相对误差在-10%~0之间。苏豫皖三省中,中筋小麦主要分布在江苏省的中北部、安徽省中部少部分地区;中强筋小麦主要分布在江苏省的北部、安徽省的北部、中西部和西南部、河南省的东北部;强筋小麦主要分布在河南省东部、西北部和西南部;江苏省的南部和中部、安徽省的东南部最适宜弱筋小麦的种植。

关 键 词:小麦  籽粒蛋白质  Meta分析  ArcGIS  品质区划

Study on Spatial Distribution Characteristics of Wheat Grain Protein Content Based on Meta-Analysis and Meteorological Factors in Jiangsu, Anhui and Henan
XIA Shufeng,JIANG Guangshuai,ZHAO Hong,FANG Qian,HU Shiqi,WANG Fan,CAI Jian,WANG Xiao,ZHOU Qin,ZHONG Yingxin,JIANG Dong. Study on Spatial Distribution Characteristics of Wheat Grain Protein Content Based on Meta-Analysis and Meteorological Factors in Jiangsu, Anhui and Henan[J]. Journal of Triticeae Crops, 2021, 41(8): 1033-1043
Authors:XIA Shufeng  JIANG Guangshuai  ZHAO Hong  FANG Qian  HU Shiqi  WANG Fan  CAI Jian  WANG Xiao  ZHOU Qin  ZHONG Yingxin  JIANG Dong
Abstract:Grain protein content(GPC) is one of the most important indices to evaluate the quality of wheat, and it varies due to different meteorological factors and soil characteristics. The region including Jiangsu, Anhui and Henan are two major wheat production areas in China.Thus, clarifying the spatial distribution pattern of wheat GPC in this region can provide basis for accurately planning wheat production areas and establishing corresponding optimal cultivation techniques. Research literatures related to wheat GPC and meteorological data of corresponding places in this region from 1999 to 2019 were collected. The wheat GPC model driven by meteorological factors was established by using meta-analysis method. The prediction map was created by inverse distance interpolation through ArcGIS based on the former model. Then, this prediction map was verified by using the wheat GPC of samples in Jiangsu province in 2019. Finally, the wheat zone was classified according to the national standard of wheat quality. The results showed that the GPC increased with the increase of total sunshine hours at the middle stage of grain filling, but decreased with the increase of total rainfall during sowing to booting and early and middle stage of grain filling. The GPC of wheat decreased from west to east under the same meteorological level in Jiangsu, Anhui and Henan provinces. The wheat grain protein content obtained by multi-point sampling in 2019 was used to validate the results. It was found that the provincial fitting model was more accurate, and the relative predicting error was between -10% and 0.Among the three provinces of Jiangsu, Anhui and Henan, medium gluten wheat is mainly distributed in the north central part of Jiangsu province and a small part of central Anhui province; medium strong gluten wheat is mainly distributed in the north area of Jiangsu province, the north, central west and southwest areas of Anhui province, and the northeast area of Henan province; the strong gluten wheat is mainly distributed in the east, northwest and southwest parts of Henan province; the south and central parts of Jiangsu province and the southeast part of Anhui province are the most suitable for planting weak gluten wheat.
Keywords:Wheat(Triticum aestivum)   Grain protein content   Meta-analysis   ArcGIS   Quality zoning
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