基于产量的稻田肥力质量评价及障碍因子区划——以进贤县为例  

Yield-Based Soil Fertility Quality Assessment and Constraint Factor-Based Zoning of Paddy Soil——A Case Study of Jinxian County

作　　者：樊亚男 姚利鹏 瞿明凯 胡文友[1] 黄标[1] 赵永存[1] 

机构地区：[1]中国科学院土壤环境与污染修复重点实验室(南京土壤研究所),南京210008 [2]中国科学院大学,北京100049 [3]南京市环境保护科学研究院,南京210019

出　　处：《土壤学报》2017年第5期1157-1169,共13页Acta Pedologica Sinica

基　　金：国家科技支撑计划课题(2012BAD05B05)资助~~

摘　　要：土壤肥力质量评价及土壤肥力障碍因子分析,对于区域土壤利用和改良、指导农业生产结构布局具有重要意义。以江西省进贤县为研究区,通过水稻遥感解译测产,结合主成分分析进行土壤质量评价;采用综合指数法表征土壤肥力质量水平,分析该区域低肥力质量区域主要障碍因素,并进行障碍因子区划。结果表明,该地区土壤肥力质量评价的最小数据集(MDS)指标包括:有机质、阳离子交换量(CEC)、全钾(TK)、交换性钙(Ex.Ca)、容重、粉黏比;土壤质量综合指数与水稻产量相关系数达到0.73(p<0.01),以当地水稻平均产量7.215 t hm^(-2)确定土壤质量综合指数阈值为0.65。分析得出,该地区影响土壤肥力的主要障碍包括有机质含量低和容重较大反映的低熟化度障碍、中量元素缺乏反映的酸化障碍、全钾含量低和高粉黏比反映的结构障碍等。根据障碍因素将研究区域划分为三大障碍区:东南部丘陵区主要障碍因子为酸化和土壤结构障碍;中西部低岗平原主要为土壤酸化障碍;北部滨湖区主要障碍为水稻土熟化程度低。通过对不同区域施行针对性改良措施有益于提高土壤肥力。[Objective] Soil fertility quality assessment and constraint factors analysis of soil quality have vital theoretical and practical significances in regional soil improvement and utilization and guidance agricultural production. Paddy soil is an important component of the soil resources in China. Researchers have been using a set index system to evaluate soil fertility quality with results not so accurate. It is, therefore, essential to explore for a more accurate scientific method for the evaluation. [Method] Jinxian County of Jiangxi Province was cited as a case for the study. A total of 103 soil samples were collected from the topsoil （ 0 - 20 cm ） and subsoil （ 20 - 40 cm ） layers of the paddy fields in the region proportional to their respective areas and types and 51 rice sampling sites set aside as a dataset for verificationof the yield prediction based on remote sensing interpretation. A fairly more comprehensive dataset of soil properties was determined in the lab. Correlation analysis and principal component analysis （ PCA ） of the dataset with predicted yields were performed to determine minimum data set （ MDS ） and weight and membership read function models of the evaluation index system. Soil fertility was characterized in level with the comprehensive index method and main constraint factors of fertility quality in areas low in soil fertility quality. [Result] To evaluate accuracy of remote sensing interpretation, a fitting equation was established between measured and estimated yields. In the light of the determination coefficient （ R2 ） and root of mean square error （ RMSE ） of the fitting equation,the normalized difference vegetation index （NDVI） can reflect more accurately crop yield. According to the yield prediction based on remote sensing interpretation, yield of the rice crop in the region varied in the range from 2.085 to 11.430 t hm-2, and averaged 7.215 t hm-2. Through principal component analysis MDS indices, including organic matter, cation exchange capacity �

关 键 词：遥感解译估产 土壤属性 水稻 土壤肥力质量评价 土壤障碍因子 

分 类 号：S158.5[农业科学—土壤学] S159.2[农业科学—农业基础科学]