Climate Regionalization of Buckwheat Quality Index Based on GIS Multivariate Analysis in Jinzhong Prefecture

  • Institute of Dry Farming Engineering, Shanxi Agricultural University, Taigu 030801, China

Received date: 2012-09-17

  Revised date: 2012-11-12

  Online published: 2012-12-25


Buckwheat is mainly distributed in central and western regions in China, is one of the major food crops and economic crops in these areas. The production and development of buckwheat have direct impact on farmers' income and agricultural economic development of these areas. The climate regionalization of buckwheat quality is the important basis of optimizing cultivation environment and quality variety layout, and has a great guiding meaning towards high quality production of buckwheat. So, exploring the best planting pattern of buckwheat can provide theoretical and practical basis for the regionalization and high quality buckwheat production at larger scales. But the current climate regionalization studies of buckwheat mainly focused on the suitable cultivation division using traditional research methods, and no report about climatic regionalization of buckwheat quality using principal components analysis (PCA) and GIS was found. In this study, the correlation of quality index of buckwheat and meteorological factors was analyzed, together with the geographical distribution information of buckwheat and the major meteorological factors which effected on quality index were screened out. The model was established based on PCA method in order go assess the comprehensive quality of buckwheat, then the ecological regionalization was determined using the ArcGIS spatial analysis technique. The results showed that temperature, rainfall and sunshine-hour were the main ecological factors which effected buckwheat quality index. It had bad effect on buckwheat growth and went against accumulate of quality index, if the daily highest temperature was more than 35℃ and mean temperature was higher. A plenty of precipitation in August and plenteous sunshine of whole stage were beneficial to accumulate of quality index. Combined with evaluation model, using GIS, Jinzhong Prefecture was divided into three regions, i.e. adapted, inferior adapted and bad adapted planting region, and it was largely in line with the actual condition. PCA combined with GIS method is the most powerful approach for regionalization, and the quantitative computing and qualitative analysis are integrated. So, there is a feasibility to carry through ecological regionalization of buckwheat quality using PCA method and GIS, and the regionalization results are objective and scientific. The method is concise, applicable and effective, which can really reflect the regionalization actual situation and provide reference for fine quality production of buckwheat.

Cite this article

FENG Mei-Chen, NIU Bei, YANG Wu-De, XIAO Lu-Ji . Climate Regionalization of Buckwheat Quality Index Based on GIS Multivariate Analysis in Jinzhong Prefecture[J]. Journal of Geo-information Science, 2012 , 14(6) : 807 -813 . DOI: 10.3724/SP.J.1047.2012.00807


[1] 杨武德,石建国,魏亦文. 现代杂粮生产[M]. 北京: 中国农业科技出版社, 2001, 5: 83-85.

[2] Kalinová J, Moudrý J, ?urn V. Technological quality of common buckwheat(Fagopyrum esculentum Moench.) [J]. Rostlinná Vyroba, 2002, 48(6): 279-284.

[3] 武春燕,李铁鹏,于靖,等. 荞麦芦丁开发利用中存在的问题及探讨[J]. 中国农村小康科技, 2006, 8: 60-62, 75.

[4] Kreft I, Škrabanja V, Ikeda S, et al. Genetika a šlechtění pohanky-zkušenosti z kooperaccního projektu pro pěstování a vyu?ití pohanky ve Slovinsku [C]. Itálii a Japonsku. In: Sbor. Ref. Odb. Konf. Pohanka setá, Praha, 11. 1997, 20-25.

[5] 牛波,冯美臣,杨武德. 不同肥料配比对荞麦产量和品质的影响[J]. 陕西农业科学, 2006(2): 8-10.

[6] 朱大洲,黄文江,马志宏,等. 基于近红外网络的小麦品质监测[J]. 中国农业科学, 2011, 44(9):1806-1814.

[7] 林春,辜晓青,祝必琴. 潘阳湖区棉花种植气候区划[J]. 气象与减灾研究, 2010, 33(1): 58-62.

[8] 高阳华,陈志军,梅勇,等. 重庆市优质稻气候资源及其开发利用研究[J]. 西南大学学报(自然科学版), 2007, 29(11): 110-114.

[9] 孔德胤,张喜林,王敏,等. 河套平原基于气象条件的甜菜品质区划[J]. 中国糖料, 2007, 2: 23-26.

[10] 余优森. 引种北海道荞麦的气候区划[J].甘肃农业科技, 1991, 8: 13-14.

[11] 孙志敏,刘双,李俊有. 赤峰市春小麦、荞麦适宜种植气候区划[J]. 内蒙古农业科技, 2010, 4: 112-118.

[12] 李雪巍,王小平,朱铁栓,等. 赤峰市大豆与荞麦种植气候区划[J]. 内蒙古农业科技, 2008, 4: 79, 81.

[13] 周雪丽,贤荣,程立刚. 太湖水质站网数据的主成分分析应用[J]. 地球信息科学, 2008, 10(2): 142-146.

[14] 张文霖. 主成分分析在满意度权重确定中的应用[J]. 市场研究, 2006, 6: 18-22.

[15] 张冬咏,李钧,李炳军,等. 区域农业可持续发展水平的评估方法及应用[J]. 河南农业大学学报, 2001(6): 172-174.

[16] 刘二永,汪云甲. 基于CUDA的IDW并行算法及其实验分析[J]. 地球信息科学学报, 2011, 13(5): 707-710.

[17] 潘瑜春,钟耳顺,赵春江. GIS空间数据库的更新技术[J]. 地球信息科学, 2004, 6(1): 36-40.

[18] 魏丽,殷剑敏,王怀清. GIS支持下的江西省优质早稻种植气候区划[J]. 中国农业气象, 2002, 23(2): 27-31.

[19] 孙文堂,苗春生,沈建国,等. 基于GIS的马铃薯种植气候区划及风险区划的研究[J]. 南京气象学院学报, 2004, 27(5): 650-659.

[20] 宁海龙,张大勇,胡国华,等. 东北三省蛋白质和油分含量生态区划[J]. 大豆科学, 2007, 26(4): 511-516.

[21] Zhang Q F,Wu F Q,Wang L,et al. Application of PCA integrated with CA and GIS in eco-economic regionalization of Chinese Loess Plateau[J]. Ecological Economics, 2011, 70: 1051-1056.

[22] Anderson R P, Raza A. The effect of the extent of the study region on GIS models of species geographic distributions and estimates of niche evolution: preliminary tests with montane rodents (genus Nephelomys) in Venezuel [J]. Journal of Biogeography, 2010, 37(7): 1378-1393.