基于高光谱小波分维的茎瘤芥镉含量估算模型

doi:10.3864/j.issn.0578-1752.2018.01.007

Abstract

Abstract: 【Objective】The aim of this study was to reveal the relationship between the cadmium contents of tumorous stem at mature period and leaf spectral reflectance at the early stages of tumorous stem mustard (Brassica juncea var. tunida), a famous local vegetable in the Three Gorges Reservoir Region. The results could provide theoretical guidance for predicting cadmium contents of tumorous stem of tumorous stem mustard rapidly and accurately, which was helpful to know the edible quality in the early growth stage of vegetable. 【Method】A pot experiment was conducted to set up 0, 0.1, 0.2, 0.3 and 1 mg·kg^-1 with different concentrations of cadmium in soil (calculated according to dry soil weight) based on the present situation of soil cadmium contamination in the main planting area of tumorous stem mustard. The leaf spectral reflectance and cadmium contents were synchronously determined in the main four growth periods of vegetable. Wavelet-Fractal Analysis was used to obtain detailed information about leaf spectral reflectance based on db2-db8 wavelet bases under the fifth dimension. Using correlation and regression analysis, non-linear models were constructed for estimating cadmium contents of tumorous stem of tumorous stem mustard advanced in the early growth stage. 【Result】There was a relatively intense accumulation of cadmium in the leaves and tumorous stem of tumorous stem mustard, which increased with the increased cadmium concentrations in soil. There was a significant positive correlation between the cadmium contents of the tumorous stem and the leaves. The leaf spectral reflectance in four growth stages, especially in the early enlargement stage of tumorous stem, could well respond to the contaminated cadmium in soil. The fractal dimension coefficients of leaf spectral reflectance based on "db2-db8" were significantly negatively correlated with the leaf cadmium contents in the early enlargement stage of tumorous stem. The models were simulated based on the relationships among the cadmium concentration in the tumorous stem at mature period of tumorous stem mustard, the leaf fractal dimension coefficients in the early enlargement stage of tumorous stem and the contaminated cadmium in the soil. The model based on "db5"was the optimal simulation, which R²was 0.929 and Root Mean Square Error (RMSE) was 1.0540. 【Conclusion】The results showed that cadmium could accumulated in leaf and tumorous stem of tumorous stem mustard, which could threaten the human health and the food safety, so it should be paid more attentions. Wavelet-Fractal Analysis was suitable to assess the situation of heavy metal contamination of vegetable due to its sensitivity for subtle spectral information. The optimal model was established based on wavelet db5 of leaf spectral reflectance, that was Y=-0.029+32.878X^-7.656, with R² and RMSE was 0.929 and 1.0540, respectively, which could accurately predict the cadmium content of tumorous stem at the mature stage by using the spectral data from the early growth stage, and provide a theoretical foundation for knowing the edible quality in the early growth stage of tumorous stem mustard.

Key words: Three Gorges Reservoir Region, tumorous stem mustard, cadmium, wavelet-fractal dimension, estimation model

WANG Ting, ZHOU Cui, GU YanWen, MA WenChao, LIU Yuan, WEI Hong. Hyperspectral Estimation of Cadmium Content in Tumorous Stem Mustard Based on the Wavelet-Fractal Analysis[J].Scientia Agricultura Sinica, 2018, 51(1): 71-81.

0
/ / Recommend

Add to citation manager EndNote|Reference Manager|ProCite|BibTeX|RefWorks

URL: https://www.chinaagrisci.com/EN/10.3864/j.issn.0578-1752.2018.01.007

https://www.chinaagrisci.com/EN/Y2018/V51/I1/71

References

[1] 薛利红, 朱艳, 张宪, 曹卫星. 利用冠层反射光谱预测小麦籽粒品质指标的研究. 作物学报, 2004, 30(10): 1036-1041.

XUE L H, ZHU Y, ZHANG X, CAO W X. Predicting wheat grain quality with canopy reflectance spectra. Acta Agronomica Sinica, 2004, 30(10): 1036-1041. (in Chinese)

[2] 魏良明, 姜海鹰, 李军会, 严衍禄, 戴景瑞. 玉米杂交种品质性状的近红外光谱分析技术研究. 光谱学与光谱分析, 2005, 25(9):1404-1407.

WEI L M, JIANG H Y, LI J H, YAN Y L, DAI J R. Predicting the chemical composition of intact kernels in maize hybrids by near infrared reflectance spectroscopy. Spectroscopy and Spectral Analysis, 2005, 25(9): 1404-1407. (in Chinese)

[3] GRISPEN V M J, NELISSEN H J M, VERKLEIJ J A C. Phytoextraction with Brassica napus L.: A tool for sustainable management of heavy metal contaminated soils. Environmental Pollution, 2006, 144(1): 77-83.

[4] 姚会敏, 杜婷婷, 苏德纯. 不同品种芸薹属蔬菜吸收累积镉的差异. 中国农学通报, 2006, 22(1): 291-294.

YAO H M, DU T T, SU D C. Cadmium uptake and accumulation in vegetable species in Brassica Cruciferae. Chinese Agricultural Science Bulletin, 2006, 22(1): 291-294. (in Chinese)

[5] YANG Q W, Li H, Long F Y. Heavy metals of vegetables and soils of vegetable bases in Chongqing, Southwest China. Environmental Monitoring and Assessment, 2007, 130(1/3): 271-279.

[6] ZHANG C, WANG Y M, ZHANG Z L, WANG D Y, LUO C Z, XU F. Health risk assessment of heavy metals and as in vegetable and soil system in Chongqing, southwest of China. Journal of Residuals Science and Technology, 2015, 12(4): 231-240.

[7] 黄小娟, 江长胜, 郝庆菊. 重庆溶溪锰矿区土壤重金属污染评价及植物吸收特征. 生态学报, 2014, 34(15): 4201-4211.

HUANG X J, JIANG C S, HAO Q J. Assessment of heavy metal pollutions in soils and bioaccumulation of heavy metals by plants in Rongxi Manganese mineland of Chongqing. Acta Ecologica Sinica, 2014, 34(15): 4201-4211. (in Chinese)

[8] 刘丽琼, 魏世强, 江韬. 三峡库区消落带土壤重金属分布特征及潜在风险评价. 中国环境科学, 2011, 31(7): 1204-1211.

LIU L Q, WEI S Q, JIANG T. Distribution of soil heavy metals from water-level-fluctuating zone in Three-Gorge Reservoir Area and their evaluation of potential ecological risk. China Environmental Science, 2011, 31(7): 1204-1211. (in Chinese)

[9] 叶琛, 李思悦, 张全发. 三峡库区消落区表层土壤重金属污染评价及源解析. 中国生态农业学报, 2011, 19(1): 146-149.

YE C, LI S Y, ZHANG Q F. Sources and assessment of heavy metal contamination in water-level fluctuation zone of the Three Gorges Reservoir, China. Chinese Journal of Eco-Agriculture, 2011, 19(1): 146-149. (in Chinese)

[10] 王业春, 雷波, 杨三明, 张晟. 三峡库区消落带不同水位高程土壤重金属含量及污染评价. 环境科学, 2012, 33(2): 612-617.

WANG Y C, LEI B, YANG S M, ZHANG S. Concentrations and pollution assessment of soil heavy metals at different water-level altitudes in the draw-down areas of the Three Gorges Reservoir. Environmental Science, 2012, 33(2): 612-617. (in Chinese)

[11] CHANG C Y, YU H Y, CHEN J J, LI F B, ZHANG H H, LIU C P. Accumulation of heavy metals in leaf vegetables from agricultural soils and associated potential health risks in the Pearl River Delta, South China. Environmental Monitoring and Assessment, 2014, 186(3): 1547-1560.

[12] NABULO G, YOUNG S D, BLACK C R. Assessing risk to human health from tropical leafy vegetables grown on contaminated urban soils. Science of the Total Environment, 2010, 408(22): 5338-5351.

[13] KHAN S, REHMAN S, KHAN A Z, KHAN M A, SHAN M T. Soil and vegetables enrichment with heavy metals from geological sources in Gilgit, Northern Pakistan. Ecotoxicology and Environmental Safety, 2010, 73(7): 1820-1827.

[14] 刘小军, 田永超, 姚霞, 曹卫星, 朱艳. 基于高光谱的水稻叶片含水量监测研究. 中国农业科学, 2012, 45(3): 435-442.

LIU X J, TIAN Y C, YAO X, CAO W X, ZHU Y. Monitoring leaf water content based on hyperspectra in rice. Scientia Agricultura Sinica, 2012, 45(3): 435-442. (in Chinese)

[15] 陈智芳, 宋妮, 王景雷, 孙景生. 基于高光谱遥感的冬小麦叶水势估算模型. 中国农业科学, 2017, 50(5): 871-880.

CHEN Z F, SONG N, WANG J L, SUN J S. Leaf water potential estimating models of winter wheat based on hyperspectral remote sensing. Scientia Agricultura Sinica, 2017, 50(5): 871-880. (in Chinese)

[16] PRASANNAKUMAR N R, CHANDER S, SAHOO R N. Characterization of brown planthopper damage on rice crops through hyperspectral remote sensing under field conditions. Phytoparasitica, 2014, 42(3): 387-395.

[17] 马慧琴, 黄文江, 景元书. 遥感与气象数据结合预测小麦灌浆期白粉病. 农业工程学报, 2016, 32(9): 165-172.

MA H Q, HUANG W J, JING Y S. Wheat powdery mildew forecasting in filling stage based on remote sensing and meteorological data. Transactions of the Chinese Society of Agricultural Engineering, 2016, 32(9): 165-172. (in Chinese)

[18] RATHOD P H, BRACKHAGE C, VAN DER MEER F D, MULLER L, NOOMEN M F, ROSSITER D G, DUDEL G E. Spectral changes in the leaves of barley plant due to phytoremediation of metals-results from a pot study. European Journal of Remote Sensing, 2015, 48(3): 283-302.

[19] LUX A, MARTINKA M, VACULIK M, WHITE P J. Root responses to cadmium in the rhizosphere: A review. Journal of Experimental Botany, 2011, 62(1): 21-37.

[20] 简敏菲, 汪斯琛, 余厚平, 李玲玉, 简美锋, 余冠军. Cd²⁺、Cu²⁺胁迫对黑藻（Hydrilla verticillata）的生长及光合荧光特性的影响. 生态学报, 2016, 36(6): 1719-1727.

JIAN M F, WANG S C, YU H P, LI L Y, JIAN M F, YU G J. Influence of Cd²⁺ or Cu²⁺ stress on the growth and photosynthetic fluorescence characteristics of Hydrilla verticillata. Acta Ecologica Sinica, 2016, 36(6): 1719-1727. (in Chinese)

[21] 顾艳文, 李帅, 高伟, 魏虹. 基于光谱参数对小白菜叶片镉含量的高光谱估算. 生态学报, 2015, 35(13): 4445-4453.

GU Y W, LI S, GAO W, WEI H. Hyperspectral estimation of the cadmium content in leaves of Brassica rapa chinesis based on the spectral parameters. Acta Ecologica Sinica, 2015, 35(13): 4445-4453. (in Chinese)

[22] 李婷, 刘湘南, 刘美玲. 水稻重金属污染胁迫光谱分析模型的区域应用与验证. 农业工程学报, 2012, 28(12): 176-182.

LI T, LIU X N, LIU M L. Regional application and verification of spectral analysis model for assessing heavy-metal stress of rice. Transactions of the Chinese Society of Agricultural Engineering, 2012, 28(12): 176-182. (in Chinese)

[23] 何勇, 彭继宇, 刘飞, 张初, 孔汶汶. 基于光谱和成像技术的作物养分生理信息快速检测研究进展. 农业工程学报, 2015, 31(3): 174-189.

HE Y, PENG J Y, LIU F, ZHANG C, KONG W W. Critical review of fast detection of crop nutrient and physiological information with spectral and imaging technology. Transactions of the Chinese Society of Agricultural Engineering, 2015, 31(3): 174-189. (in Chinese)

[24] 刘美玲, 刘湘南, 李婷, 修丽娜. 水稻锌污染胁迫的光谱奇异性分析. 农业工程学报, 2010, 26(3): 191-197.

LIU M L, LIU X N, LI T, XIU L N. Analysis of hyperspectral singularity of rice under Zn pollution stress. Transactions of the Chinese Society of Agricultural Engineering, 2010, 26(3): 191-197. (in Chinese)

[25] 修丽娜, 刘湘南, 刘美玲. 镉污染水稻高光谱诊断分析与建模. 光谱学与光谱分析, 2011, 31(1): 192-196.

XIU L N, LIU X N, LIU M L. Analysis and modeling of hyperspectral singularity in rice under Cd pollution. Spectroscopy and Spectral Analysis, 2011, 31(1): 192-196. (in Chinese)

[26] LIU M L, LIU X N, DING W C, WU L. Monitoring stress levels on rice with heavy metal pollution from hyperspectral reflectance data using wavelet-fractal analysis. International Journal of Applied Earth Observation & Geoinformation, 2011, 13(2): 246-255.

[27] LIU M L, LIU X N, WU L, DUAN L Q, ZHONG B Q. Wavelet-based detection of crop zinc stress assessment using hyperspectral reflectance. Computers & Geosciences, 2011, 37(9): 1254-1263.

[28] LIAO Q H, WANG J H, YANG G J, ZHANG D Y, LI H L, FU Y Y, LI Z H. Comparison of spectral indices and wavelet transform for estimating chlorophyll content of maize from hyperspectral reflectance. Journal of Applied Remote Sensing, 2013, 7(3): 641-641.

[29] 国家环境保护局, 国家质量监督检验检疫总局. 土壤环境质量标准: GB15618—1995. 北京: 中国标准出版社, 1995: 2.

National Environmental Protection Agency, General Administration of Quality Supervision, Inspection and Quarantine of the People's Republic of China. Environmental Quality Standard for Soils: GB15618-1995. Beijing: Standards Press of China, 1995: 2. (in Chinese)

[30] 吴伶. 基于分形-小波模型的水稻铅污染胁迫遥感弱信息提取方法研究[D]. 北京: 中国地质大学, 2010.

WU L. Studying on extracting weak information of rice under Pb pollution stress from remotely sensed data based on fractal-wavelet model[D]. Beijing: China University of Geosciences(Beijing), 2010. (in Chinese)

[31] 刘美玲, 刘湘南, 曹仕, 李婷, 吴伶. 基于高光谱高频组份分形特征的水稻铅胁迫评估. 遥感学报, 2011, 15(4): 811-830.

LIU M L, LIU X N, CAO S, LI T, WU L. Assessment of Pb-induced stress levels on rice based on fractal characteristic of spectral high-frequency components. Journal of Remote Sensing, 2011, 15(4): 811-830. (in Chinese)

[32] HE L, ZHANG H Y, ZHANG Y S, SONG X, FENG W, KANG G Z, WANG C Y, GUO T C. Estimating canopy leaf nitrogen concentration in winter wheat based on multi-angular hyperspectral remote sensing. European Journal of Agronomy, 2016, 73: 170-185.

[33] 张永贺, 陈文惠, 郭乔影, 张清林. 桉树叶片光合色素含量高光谱估算模型. 生态学报, 2013, 33(3): 876-887.

ZHANG Y H, CHEN W H, GUO Q Y, ZHANG Q L. Hyperspectral estimation models for photosynthetic pigment contents in leaves of Eucalyptus. Acta Ecologica Sinica, 2013, 33(3): 876-887. (in Chinese)

[34] 艾金泉, 陈文惠, 陈丽娟, 张永贺, 周毅军, 郭啸川, 褚武道. 冠层水平互花米草叶片光合色素含量的高光谱遥感估算模型. 生态学报, 2015, 35(4): 1175-1186.

AI J Q, CHEN W H, CHEN L J, ZHANG Y H, ZHOU Y J, GUO X C, ZHU W D. Hyperspectral remote sensing estimation models for foliar photosynthetic pigment contents at canopy level in an invasive species, Spartina alterniflora. Acta Ecologica Sinica, 2015, 35(4): 1175-1186. (in Chinese)

[35] 中华人民共和国卫生部. 食品中污染物限量: GB2762—2012. 北京: 中国标准出版社, 2012: 4.

Ministry of Health of the People’s Republic of China. Limits of Contaminants in Food: GB2762-2012. Beijing: Standards Press of China, 2012: 4. (in Chinese)

[36] RODRIGUEZ-SERRANO M, ROMERO-PUERTAS M C, ZABALZA A, CORPAS F J, GOMEZ M, DELRIO L A, SANDALIO L M. Cadmium effect on oxidative metabolism of pea (Pisum sativum L.) roots. Imaging of reactive oxygen species and nitric oxide accumulation in vivo. Plant Cell Environment, 2006, 29(8): 1532-1544.

[37] 徐勤松, 施国新, 杜开和. 六价铬污染对水车前叶片生理生化及细胞超微结构的影响. 广西植物, 2002, 22(1): 92-96.

XU Q S, SHI G X, DU K H. Effects of Cr (VI) on physiological and ultrastructural changes in leaves of Ottelia alismoides (L.). Pers. Guihaia, 2002, 22(1): 92-96. (in Chinese)

[38] 齐婧冰, 樊风雷, 郭治兴. 基于高光谱分形分析的烟草冠层生长状况监测. 华南师范大学学报(自然科学版), 2016, 48(1): 94-100.

QI J B, FAN F L, GUO Z X. Monitoring tobacco canopy growth status based on hyperspectral fractal analysis. Journal of South China Normal University(Natural Science Edition), 2016, 48(1): 94-100. (in Chinese)

[39] 金铭, 刘湘南. 基于高光谱分形分析的水稻镉污染动态监测. 中国环境监测, 2011, 27(6): 68-73.

JIN M, LIU X N. Dynamically monitoring rice Cd pollution based on hyperspectral fractal analysis. Environmental Monitoring in China, 2011, 27(6): 68-73. (in Chinese)

[40] 姚云军, 秦其明, 张自力, 李百寿. 高光谱技术在农业遥感中的应用研究进展. 农业工程学报, 2008, 24(7): 301-306.

YAO Y J, QIN Q M, ZHANG Z L, LI B S. Research progress of hyperspectral technology applied in agricultural remote sensing. Transactions of the Chinese Society of Agricultural Engineering, 2008, 24(7): 301-306. (in Chinese)

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed

Comments

Recommended 0

No Suggested Reading articles found!

Hyperspectral Estimation of Cadmium Content in Tumorous Stem Mustard Based on the Wavelet-Fractal Analysis

RichHTML

PDF

Abstract

Cite this article

share this article

References

Related Articles 15

Metrics

Comments

Recommended 0

[1]	ZHOU Liang,XIAO Feng,XIAO Huan,ZHANG YuSheng,AO HeJun. Effects of Lime on Cadmium Accumulation of Double-Season Rice in Paddy Fields with Different Cadmium Pollution Degrees [J]. Scientia Agricultura Sinica, 2021, 54(4): 780-791.
[2]	PENG Ou,LIU YuLing,TIE BaiQing,YE ChangCheng,ZHANG Miao,LI YuanXingLu,ZHOU JunChi,XU Meng,ZHANG Yan,LONG Yong. Effects of Conditioning Agents and Agronomic Measures on Cadmium Uptake by Rice in Polluted Rice Fields [J]. Scientia Agricultura Sinica, 2020, 53(3): 574-584.
[3]	ZHU YaJing, ZHOU YaLi, LIU SuShuang, WEI JiaPing, LIU XiaoLin, SHEN YingZi, ZHAO HaiHong, MA Hao. GmHMADP Involved in Seed Vigor Formation of Soybean Under High Temperature and Humidity Stress and its Study Responsive to Copper and Cadmium Stress [J]. Scientia Agricultura Sinica, 2018, 51(14): 2642-2654.
[4]	Hua YU, YuXian SHANGGUAN, ShiHua TU, YuSheng QIN, Kun CHEN, DaoQuan CHEN, QianCong LIU. Sources of Cadmium Accumulated in Rice Grain [J]. Scientia Agricultura Sinica, 2018, 51(10): 1940-1947.
[5]	CHEN JiangMin, YANG YongJie, HUANG QiNa, HU PeiSong, TANG ShaoQing, WU LiQun, WANG JianLong, SHAO GuoSheng. Effects of Continuous Flooding on Cadmium Absorption and Its Regulation Mechanisms in Rice [J]. Scientia Agricultura Sinica, 2017, 50(17): 3300-3310.
[6]	WANG Xue-hua, DAI Li. Immobilization Effect and Its Physiology and Biochemical Mechanism of the Cadmium in Crop Roots [J]. Scientia Agricultura Sinica, 2016, 49(22): 4323-4341.
[7]	TAN Chang-wei, LUO Ming, YANG Xin, MA Chang, YAN Xiang, ZHOU Jian, DU Ying, WANG Ya-nan. Remote Sensing Estimation of Winter Wheat Theoretical Yield on Regional Scale Using Partial Least Squares Regression Algorithm Based on HJ-1A/1B Images [J]. Scientia Agricultura Sinica, 2015, 48(20): 4033-4041.
[8]	LU Mei-bin, CHEN Zhi-jun, LI Wei-xi, HU Xue-xu, LI Jing-mei, WANG Bu-jun. Survey and Dietary Exposure Assessment of Cadmium in Wheat from Two Main Wheat-Producing Regions in China [J]. Scientia Agricultura Sinica, 2015, 48(19): 3866-3876.
[9]	ZHU Zhi-wei, CHEN Ming-xue, MOU Ren-xiang, CAO Zhao-yun, ZHANG Wei-xing, LIN Xiao-yan. Advances in Research of Cadmium Metabolism and Control in Rice Plants [J]. Scientia Agricultura Sinica, 2014, 47(18): 3633-3640.
[10]	SONG Wen-en, CHEN Shi-bao. The Toxicity Thresholds (ECx) of Cadmium (Cd) to Rice Cultivars as Determined by Root-Elongation Tests in Soils and Its Predicted Models [J]. Scientia Agricultura Sinica, 2014, 47(17): 3434-3443.
[11]	SUN Cong, CHEN Shi-Bao, SONG Wen-恩, LI Ning. Accumulation Characteristics of Cadmium by Rice Cultivars in Soils and Its Species Sensitivity Distribution [J]. Scientia Agricultura Sinica, 2014, 47(12): 2384-2394.
[12]	KONG Long-1, 2 , TAN Xiang-Ping-1, HE Wen-Xiang-1, 3 , WEI Ge-Hong-2. Response of Soil Enzyme Activity in Different Type of Soils to Cadmium Exposure in China [J]. Scientia Agricultura Sinica, 2013, 46(24): 5150-5162.
[13]	WU Xiao-Sheng, WEI Shuai, WEI Yi-Min, GUO Bo-Li, YANG Ming-Qi, LIU Xiao-Ling. Effect of Sub-chronic Cadmium Exposure on Liver Biochemical Index in Wuzhishan Pig [J]. Scientia Agricultura Sinica, 2012, 45(3): 562-568.
[14]	WANG Ji-Cang, LIU Xue-Zhong, YUAN Yan, YI Chuan-Hui, BIAN Jian-Chun, LIU Zong-Ping. The Role of Oxidative Stress on the Apoptosis of Rat Hepatocytes Induced by Cadmium [J]. Scientia Agricultura Sinica, 2011, 44(18): 3895-3902.
[15]	YU Cai-Lian, LIU Bo, XU Xin. Effect of DA-6 on Enhanced Remediation Efficiency of Solanum nigrum L. in Serious Cadmium Polluted Soil [J]. Scientia Agricultura Sinica, 2011, 44(16): 3485-3490.