苹果冠层叶绿素含量高光谱估算模型

doi:10.6048/j.issn.1001-4330.2018.06.001

摘要/Abstract

摘要： 【目的】 研究一种快速、简便、无损的苹果冠层叶绿素含量估测模型。探索苹果品种岩富10号冠层的高光谱特征和叶绿素含量的估测方法,为该地区岩富10号苹果营养的快速诊断奠定基础,为红富士苹果精准化管理和-7光谱尺度研究提供参考依据。【方法】以红富士苹果(Malus domestica Borkh. cv. Red Fuji)主栽品种岩富10号叶绿素含量以及冠层高光谱反射率为数据源,分析叶绿素含量与冠层原始光谱(R)、微分光谱(R')之间的相关关系,利用敏感波段建立新的对应关系,构建岩富10号叶绿素含量的多种回归估测模型,并对不同模型进行了精度评价。【结果】微分光谱用于岩富10号叶绿素含量的估测精度要显著高于原始光谱反射率;利用敏感波段组合新定义的衍生变量拟合程度更优;在多种回归方式中,三次多项式模型的拟合程度最好,最优模型为357 nm等7个波段组合定义的新植被指数所建立的三次多项式模型,其精度为0.839。【结论】应用光谱技术对南疆塔里木盆地阿克苏地区岩富10号叶绿素含量进行定量反演是可行的。

关键词: 苹果; 高光谱; 叶绿素含量

Abstract: 【Objective】 The project aims to seek a fast, simple and non-destructive model for estimating chlorophyll content in apple canopy when using chlorophyll content and canopy hyperspectral reflectance ofMalus domestica Borkh. cv. Red Fuji cultivar Yanfu No.10 as data sources.【Method】Based on the analysis of the correlation between chlorophyll content and the original canopy spectral elements (R), a new correspondence was established by using sensitive bands, and a variety of regression models for estimating the chlorophyll content of Yanfu No. 10 are established, and the accuracy of different models was evaluated.【Result】The accuracy of estimating chlorophyll content of Yanfu No.10 by differential spectrum was significantly higher than that of original spectral reflectance, and better fitting degree of derivative variables was obtained by using the new definition of combination of sensitive bands; Among the multiple regression methods, the optimal model was a cubic polynomial model defined by a combination of seven bands, such as 357 nm, with the precision of 0.839.【Conclusion】Quantitative inversion of chlorophyll content of Yanfu No.10 in Aksu area of southern Xinjiang basin is feasible by using spectral technique. By studying the estimation method of hyperspectral characteristics and chlorophyll content of Yanfu No.10. Red Fuji canopy, good results have been achieved, which has laid a foundation for rapid diagnosis of regional apple tree nutrition, and provided information support for the precision management ofMalus domestica Borkh. cv. Red Fuji, as well. And at the same time, it has provided a reference for the spectral scale research.

Key words: Malus domestica Borkh. cv.; hyperspectral; chlorophyll content

中图分类号:

:S661.2

董淼, 王振锡. 苹果冠层叶绿素含量高光谱估算模型[J]. 新疆农业科学, 2018, 55(6): 981-990.

DONG Miao, WANG Zhen-xi. Models for Estimating Canopy Chlorophyll Content of Malus domestica Borkh. cv. Red Fuji Cultivar Yanfu No.10 Using Hyperspectral Reflectance[J]. Xinjiang Agricultural Sciences, 2018, 55(6): 981-990.

参考文献

[1] 楚万林, 齐雁冰, 常庆瑞,等. 棉花冠层叶片叶绿素含量与高光谱参数的相关性[J]. 西北农林科技大学学报: 自然科学版, 2016, 44(9): 65-73.
   CHU Wan-lin, QI Yan-bing, CHANG Qing-rui, et al. (2016). Relationship between chlorophyll content and hyperspectral parameters in canopy leaves of cotton [J]. Journal of Northwest A&F University(Natural Science Edition) , 44(9): 65-73. (in Chinese)
[2] 何彩莲, 郑顺林, 周少猛,等. 基于高光谱植被指数的马铃薯叶片叶绿素含量估测模型[J]. 华南农业大学学报, 2016, 37(5): 45-49.
   HE Cai-lian, ZHENG Shun-lin, ZHOU Shao-meng, et al. (2016). Estimation models of chlorophyll contents in potato leaves based on hyperspectral vegetation indices [J]. Journal of South China Agricultural University, 37(5): 45-49. (in Chinese)
[3] AnaCarlaMadeira, AmarilisMentions, MariaElviraFerreira, & Lourdestaborda, M. (2000). Relationship between spectroradiometric and chlorophyll measurements in green beans. Communications in Soil Science & Plant Analysis, 31(5-6): 631-643.
[4] 牛鲁燕, 孙家波, 刘延忠,等. 基于成像高光谱的小麦叶片叶绿素含量估测模型研究[J]. 河南农业科学, 2016, 45(4): 150-154.
   NIU Lu-yan, SUN Jia-bo, LIU Yan-zhong, et al .(2016). Research of estimation models of wheat chlorophyll content based on imaging hyperspectral data [J]. Journal of Henan Agricultural Sciences, 45(4): 150-154. (in Chinese)
[5] Pinar A.(1996). Grass chlorophyll and the reflectance red edge. International Journal of Remote Sensing, 17(2):351.
[6] Blackburn,G. A. , Pitman, J.L, (1999). Biophysical controls on the directional spectral reflectance properties of bracken (Pteridium aquilinum) canopies:Results of a filed experiment. International Journal of Remote Sensing, 20(11):2265-2282.
[7] 王登伟, 黄春燕, 张伟,等.高光谱数据与棉花叶绿素含量和叶绿素密度的相关分析[J]. 棉花学报, 2008, (5): 368-371.
   WANG Deng-wei, HUANG Chun-yan, ZHANG Wei, et al. (2008). Relationships Analysis between Cotton Chlorophyll Content, Chlorophyll Density and Hyperspectral Data[J]. Cotton Science, (5):368-371
[8] 袁媛. 夏玉米叶绿素及叶面积指数高光谱遥感估算[D]. 杨凌: 西北农林科技大学硕士论文, 2014.
   YUAN Yuan, (2014). Chlorophyll and leaf area index estimation based on hyperspectral remote sensing of summer corn [D]. Master Dissertation. Northwest A & F University, Yangling. (in Chinese)
[9] 张娟娟, 熊淑萍, 翟清云,等. 不同土壤质地小麦叶片叶绿素的高光谱响应及估测模型[J]. 麦类作物学报, 2014, 34(5): 642-647.
   ZHANG Juan-juan, XIONG Shu-ping, ZHAI Qing-yun, et al. (2014). Hyper-spectral remote sensing response and estimation model of leaf chlorophyll content of wheat under different soil textures [J]. Journal of Triticeae Crops, 34(5): 642-647. (in Chinese)
[10] 梁亮, 杨敏华, 张连蓬,等. 基于SVR算法的小麦冠层叶绿素含量高光谱反演[J]. 农业工程学报, 2012, 28(20): 162-171.
   LIANG Liang, YANG Min-hua, ZHANG Lian-peng, et al. (2012). Chlorophyll content inversion with hyperspectral technology for wheat canopy based on support vector regression algorithm [J]. Transactions of the Chinese Society of Agricultural Engineering, 28(20): 162-171. (in Chinese)
[11] 秦占飞. 西北地区水稻长势遥感监测研究[D]. 杨凌: 西北农林科技大学硕士论文, 2016.
   QIN Zhan-fei. (2016). Study on condition monitoring with remote sensing in northwest region [D]. Master Dissertation. Northwest A & F University, Yangling. (in Chinese)
[12] 杨杰, 田永超, 姚霞,等. 水稻上部叶片叶绿素含量的高光谱估算模型[J]. 生态学报, 2009, 29(12): 6 561-6 571.
   YANG Jie, TIAN Yong-chao, YAO Xia, et al. (2009). Hyperspectral estimation model for chlorophyll concentrations in top leaves of rice [J]. Acta Ecologica Sinica, 29(12): 6,561-6,571. (in Chinese)
[13] 孙雪梅, 周启发, 何秋霞. 利用高光谱参数预测水稻叶片叶绿素和籽粒蛋白质含量[J]. 作物学报, 2005, 31(7): 844-850.
   SUN Xue-mei, ZHOU Qi-fa, HE Qiu-xia. (2005). Hyperspectral variables in predicting leaf chlorophyll content and grain protein content in rice [J]. Acta Agronomica Sinica, 31(7): 844-850. (in Chinese)
[14] 唐延林. 水稻高光谱特征及其生物理化参数模拟与估测模型研究[D]. 杭州: 浙江大学博士论文, 2004.
   TANG Yan-lin. (2004). Study on the hyperspectral characteristics and simulating and estmiting models about biophysical and biochemical parameters of rice [D]. PhD Dissertation. Zhejiang University, Hangzhou. (in Chinese)
[15] 金震宇, 田庆久, 惠凤鸣,等. 水稻叶绿素浓度与光谱反射率关系研究[J]. 遥感技术与应用, 2003, 18(3): 134-137.
   JIN Zhen-yu, TIAN Qing-jiu, HUI Feng-ming, et al. (2003) Study of the relationship between rice chlorophyll concentration and rice reflectance [J]. Remote Sensing Technology and Application, 18(3): 134-137. (in Chinese)
[16] 蒋金豹, 陈云浩, 黄文江. 用高光谱微分指数估测条锈病胁迫下小麦冠层叶绿素密度[J]. 光谱学与光谱分析, 2010, 30(8): 2 243-2 247.
   JIANG Jin-bao, CHEN Yun-hao, HUANG Wen-jiang. (2010). Using Hyperspectral remote sensing to estimate canopy chlorophyll density of wheat under yellow rust stress [J]. Spectroscopy and Spectral Analysis, 30(8): 2,243-2,247. (in Chinese)
[17] 嵇璇. 基于光谱指数的温室马铃薯生长监测[D]. 呼和浩特: 内蒙古农业大学硕士论文, 2016.
   JI Xuan. (2016). Spcetal indices based monitoring of potato growth in greenhouse [D]. Master Thesis. Inner Mongolia Agricultural University, Hohhot. (in Chinese)
[18] 嵇璇. 基于光谱指数的温室马铃薯生长监测[D]. 呼和浩特: 内蒙古农业大学, 2016.
   JI Xuan. (2016). Spcetal indices based monitoring of potato growth in greenhouse [D]. Master Thesis. Inner Mongolia Agricultural University, Hohhot. (in Chinese)
[19] 赵佳佳, 冯美臣, 王超,等. 基于光谱植被指数的冬小麦叶绿素含量反演[J]. 山西农业大学学报(自然科学版), 2014, 34(5): 391-396.
   ZHAO Jia-jia, FENG Mei-chen, WANG Chao, et al. (2014). Simulating the content of chlorophyll in winter wheat based on spectral vegetation index [J]. Journal of Shanxi Agricultural University (Natural Science Edition) , 34(5): 391-396. (in Chinese)
[20] 杨杰. 基于叶片高光谱指数的水稻氮素及色素含量监测研究[D]. 南京: 南京农业大学博士论文, 2009.
   YANG Jie. (2009). Monitoring nitrogen and chlorophyll concentration based on leaf hyperspectral indices in rice [D]. PhD Dissertation. Nanjing Agricultural University, Nanjing. (in Chinese)
[21] 马航. 基于无人机高光谱遥感东北粳稻叶绿素含量监测及建模研究[D]. 沈阳: 沈阳农业大学硕士论文, 2017.
   MA Hang. (2017). Monitoring and modeling of chlorophyll content in northeast japonica based on hyperspectral remote sensing based on unmanned aerial vehicle [D]. Master Dissertation. Shengyang Agricultural University, Shengyang. (in Chinese)
[22] 陶文旷. 胁迫下植物光谱特征识别及生理指标估算研究[D]. 北京: 中国矿业大学硕士论文, 2017.
   TAO Wen-kuang. (2017). Spectral identification and physiological index estimation of plants under stress-with the sample of cerasus humilis [D]. Master Dissertation. China University of Mining and Technology, Beijing. (in Chinese)
[23] 梁爽, 赵庚星, 朱西存. 苹果树叶片叶绿素含量高光谱估测模型研究[J]. 光谱学与光谱分析, 2012, 32(5): 1 367-1 370.
   LANG Shuang, ZHAO Geng-xing, ZHU Xi-cun. (2012). Hyperspectral estimation models of chlorophyll content in apple leaves [J]. Spectroscopy and Spectral Analysis, 32(5): 1,367-1,370. (in Chinese)
[24] 贾永倩, 王振锡, 吴智乐,等. 杏树落果前后叶绿素含量的高光谱估算模型[J]. 森林工程, 2016, 32(6): 1-9.
   JIA Yong-qian, WANG Zhen-xi, WU Zhi-le, et al. (2016) Hyperspectral Estimation Models of the Chlorophyll Content Before and After Fruit Drop of Apricot Tree [J]. Forest Engineering, 32(6): 1-9. (in Chinese)
[25] 张小琪. 阿勒泰地区草地生物量遥感反演模型的建立[D]. 乌鲁木齐: 新疆农业大学硕士论文, 2013.
   ZHANG Xiao-qi. (2013). Construction of Remote Sensing Inversion Models for Estimating Grassland Biomass in the Aletai Region [D]. Master Dissertation. Xinjiang Agricultural University, Urumqi. (in Chinese)
[26] 胡珍珠, 潘存德, 王世伟,等. 轮台白杏叶片氮磷钾含量光谱估算模型[J]. 新疆农业科学, 2013, 50(2): 238-248.
   HU Zhen-zhu, PAN Cun-de, WANG Shi-wei, et al. (2013). Models for Estimating Foliar NPK Content of Armeniaca vulgaris 'Luntaibaixing' Using Spectral Reflectance [J]. Xinjiang Agricultural Sciences, 50(2): 238-248.
[27] 潘蓓. 苹果树冠层氮素、叶绿素及叶面积指数的高光谱估测[D]. 泰安: 山东农业大学硕士论文, 2013.
   PAN Bei. (2013). Hyperspectral estimation of apple tree canopy nitrogen chlorophyll and LAI status [D]. Master Dissertation. Shandong Agricultural University, Tai'an. (in Chinese)
[28] 乔振民. 农作物叶绿素含量高光谱遥感估算[D]. 长春: 吉林大学硕士论文, 2012.
   QIAO Zhen-min. (2012). Estimation of crop's chlorophyll content with hyperspectral remote sensing [D]. Master Dissertation. Jilin University, Changchun. (in Chinese)
[29] 梁亮. 小麦冠层理化参量的高光谱反演[D]. 长沙: 中南大学博士论文, 2010.
   LIANG Liang. (2010). Inversion of the wheat biophysical and biochemical parameters based on hyperspectral remote sensing [D]. PhD Dissertation. Central South University, Changsha. (in Chinese)
[30] 董晶晶, 牛铮. 高光谱反演叶片叶绿素及全氮含量[J]. 遥感信息, 2008,(5): 25-27.
   DONG Jing-jing, NIU Zheng. (2008). Inversion of leaf chlorophyll content and total nitrogen content using hyper-spectral reflectance [J]. Remote Sensing Information, (5): 25-27. (in Chinese)
[31] Johnson, L. F., Hlavka, C. A., & Peterson, D. L. (1994). Multivariate analysis of aviris data for canopy biochemical estimation along the oregon transect. Remote Sensing of Environment, 47(2): 216-230.
[32] Suplickploense, M. R., Alshammary, S. F., & Qian, Y. L. (2011). Spectral reflectance response of three turfgrasses to leaf dehydration. Asian Journal of Plant Sciences.