| 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 |
| |
| 引用本文： | 樊亚男,姚立鹏,瞿明凯,胡文友,黄 标,赵永存.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[J].土壤学报,2017,54(5):1157-1169. |
| |
| 作者姓名： | 樊亚男 姚立鹏 瞿明凯 胡文友 黄 标 赵永存 |
| |
| 作者单位： | 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;中国科学院大学,北京 100049;2. 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;南京市环境保护科学研究院,南京 210019;3. 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 |
| |
| 基金项目： | 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(p0.01),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。
|
| 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 |
| 收稿时间： | 2017/3/21 0:00:00 |
| 修稿时间： | 2017/6/12 0:00:00 |
Yield-Based Soil Fertility Quality Assessment and Constraint Factor-Based Zoning of Paddy Soil—A Case Study of Jinxian County |
| |
| FAN Yanan,YAO Lipeng,QU Mingkai,HU Wenyou,HUANG Biao and ZHAO Yongcun.Yield-Based Soil Fertility Quality Assessment and Constraint Factor-Based Zoning of Paddy Soil—A Case Study of Jinxian County[J].Acta Pedologica Sinica,2017,54(5):1157-1169. |
| |
| Authors: | FAN Yanan YAO Lipeng QU Mingkai HU Wenyou HUANG Biao and ZHAO Yongcun |
| |
| Affiliation: | Key Laboratory of Soil Environment and Pollution Remediation (Institute of Soil Science, Chinese Academy of Sciences),Key Laboratory of Soil Environment and Pollution Remediation (Institute of Soil Science, Chinese Academy of Sciences),Key Laboratory of Soil Environment and Pollution Remediation (Institute of Soil Science, Chinese Academy of Sciences),Key Laboratory of Soil Environment and Pollution Remediation (Institute of Soil Science, Chinese Academy of Sciences),Key Laboratory of Soil Environment and Pollution Remediation (Institute of Soil Science, Chinese Academy of Sciences),Key Laboratory of Soil Environment and Pollution Remediation (Institute of Soil Science, Chinese Academy of Sciences) |
| |
| Abstract: | 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(CEC),total potassium(TK),exchangeable calcium (Ex. Ca),bulk density(BD)and clay/silt,were acquired. CEC and TK were common ones in both topsoil and subsoil and the others standard ones. The correlation between soil quality comprehensive index(SQI) and rice yield was analyzed and calculated to be 0.73(p<0.01)in coefficient,showing that SQI may be used to indicate fertility level of the soil accurately. Based on the average yield,7.215 t hm-2,of the region, threshold value of SQI for the region was determined to be 0.65. Areas with SQI value below the threshold value are subject to the risk of low yield. Further analysis of the indices via principal component analysis shows that the main constraint factors of soil fertility in the area are low organic matter content and heavy soil texture indicating low mellowness of the soil,deficiency of meso-nutrients indicating acidification,and low potassium content and high silt/clay ratio indicating poor soil physical structure. According to restraint-factor-based zoning,the county could be divided into three regions. In the hilly area,southeast of the county,soil acidification and poor soil structure are the main constraint factors;in the low mount and plain area,central and west of the county,soil acidification is;and in the lake area,north of the county,low soil mellowness is. Consequently,proper measures should be taken in correspondence to the areas facing different constraint factors so as to improve soil fertility of the paddy fields.Conclusion]Yield-based soil fertility quality assessment is good for prediction of soil fertility accurately,and the models based on PCA,MDS,SQI and RS technologies can be used not only in paddy soil regions,but also in other types of region for evaluation of soil quality. Findings of the study show that over 30% of the paddy soil in the county are below the average level,but it is still not very clear what causes the low soil fertility. In order to reveal the reasons PCA will be performed to further reduce dimension of the evaluation indices,and zoning carried out on the town/township scale. Zoning on such a scale will sure be of great practical significance to the government in decision making and guiding agricultural production. |
| |
| Keywords: | Yield estimation based on remote sensing interpretation Soil properties Rice Soil fertility quality evaluation Soil constraint factors |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
| 点击此处可从《土壤学报》浏览原始摘要信息 |
|
点击此处可从《土壤学报》下载全文 |
|
