淹水胁迫下棉花叶片SPAD高光谱估算模型研究

doi:10.11963/1002-7807.wqxwqx.20171116

摘要/Abstract

摘要： 【目的】建立淹水胁迫下棉花叶片SPAD的高光谱模型。【方法】利用灌排可控的试验田在棉花花铃期模拟淹水处理，分析受涝1 d、3 d、6 d、9 d后棉花叶片光谱反射率、SPAD值的变化特征；并对淹水胁迫后棉花叶片高光谱特征参数与SPAD值进行相关与回归分析，探寻用于估算淹水胁迫下棉花叶片SPAD变化的高光谱模型。【结果】（1）受涝3 d时棉花倒4叶SPAD值就显著低于对照，到受涝9 d时SPAD值比对照减少15%左右。（2）棉花花铃期受涝后倒4叶绿光波段反射峰变陡，近红外短波段的反射率升高。花铃期受涝使棉花倒4叶红边位置 “蓝移”，涝害持续9 d时红边位置向短波方向移动了4～5 nm，红边幅度和红边面积呈先增大后减小趋势，在受涝6 d时达到最大，红边偏度和红边峰度增大。（3）涝后棉花叶片SPAD值与红边幅值（Dr）、红边位置（λr）、绿峰反射率（Rg）、绿峰位置（λg）、红谷位置（λo）、蓝边面积（SDb）、黄边偏度（Sy）、黄边峰度（Ky）、红边偏度（Sr）、红边峰度（Kr）等光谱特征参数极显著相关；分别以Sy、Sr、Kr为自变量的一元线性、多项式和指数模型估算SPAD值较优，其决定系数（R2）均大于0.9，均方根误差（RMSE）均小于1；多元逐步回归分析发现以λg、SDr/SDb（VI3）、Sb、Sy、Ky为自变量的多元线性模型估算SPAD值较优，R²高达0.973，RMSE为0.393。【结论】该模型可以作为估算淹水胁迫棉花叶片SPAD值的遥感模型。

关键词: 淹水胁迫; 光谱特征参数; SPAD; 棉花; 模型

Abstract: [Object] To setup the hyperspectral sensing models for estimating SPAD value of cotton leaves under waterlogging stress. [Method] Irrigation and drainage controllable plots were introduced to simulate the waterlogging stress treatment in the flowering and boll forming stage, during which the change characteristics of the cotton leaf spectral reflectance and SPAD value were observed after 1 d, 3 d, 6 d, 9 d waterlogging, respectively. To find out the hyperspectral sensing models for estimating SPAD value of cotton leaves under waterlogging stress, the correlation and regression relationships between SPAD value and spectrum parameters were analyzed. [Result] (1) The SPAD value of the fourth cotton leaf from the top was significantly lower than control when suffers from waterlogging for 3 d, when waterlogged 9 d the SPAD value decreased by around 15% compared with the control. (2) The cotton suffering from waterlogged damage in the flowering and boll forming stage caused the reflection peak in green light wave band became steep, while the near infrared spectral reflectance increased, and caused the reduction of red absorption and red edge position "blue shifts", the red edge position drifts towards short wave with 4～5 nm when suffers from waterlogging for 9 d. With increase of the waterlogged days, the red edge slope and red edge area increased with a maximum value at 6 d of waterlogging, meanwhile, the skewness and kurtosis of red edge increased. (3) After waterlogging, the SPAD value of the fourth cotton leaf from the top (chlorophyll content) had a remarkable correlation with red edge slope(Dr), red edge position(λr), green peak reflection(Rg), green peak position(λg), red well position(λo), blue edge area(SDb), yellow edge skewness(Sy), yellow edge kurtosis(Ky), red edge skewness(Sr), red edge kurtosis(Kr), etc. An experience linear, polynomial and exponential models for estimating SPAD value had been built through using the Sy, Sr, Kr as independent variables, respectively, their determination coefficient (R²) were greater than 0.9, and the root mean square error (RMSE) were less than 1; and an experience binary linear regression equation for estimating SPAD value had been built through multivariate regression using the λg, SDr/SDb(VI3), Sb, Sy, Ky as independent variables, the R² was as high as 0.973, and the RMSE was 0.393. [Conclusion] The model can be remote sensing model used as estimating leaf SPAD of cotton value under waterlogging stress.

Key words: waterlogging stress; spectrum parameter; SPAD; cotton; models

中图分类号:

S562︰TP701

吴启侠, 李晋波, 朱建强, 晏军, 苏荣瑞, 徐笑笑. 淹水胁迫下棉花叶片SPAD高光谱估算模型研究[J]. 棉花学报, 2017, 29(6): 579-588.

WU Qixia, LI Jinbo, ZHU Jianqiang, YAN Jun, SU Rongrui, XU Xiaoxiao. Hyperspectral Models for Estimating SPAD Value of Cotton Leaves under Waterlogging Stress[J]. Cotton Science, 2017, 29(6): 579-588.

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链接本文: https://journal.cricaas.com.cn/Jweb_mhxb/CN/10.11963/1002-7807.wqxwqx.20171116

https://journal.cricaas.com.cn/Jweb_mhxb/CN/Y2017/V29/I6/579

参考文献

[1] Hodgson A S, Chan K Y. The effect of short-term waterlogging during furrow irrigation of cotton in a cracking grey clay[J]. Australian Journal of Agricultural Research, 1982, 33(1): 109-116.
[2] Gillham F E M, Bell T M, Arin T, et al. Cotton production prospects for the next decade[R]//World Bank Technical Paper, 287. Washington, DC, USA: The World Bank, 1995: 277.
[3] Yang Wei, Zhu Jianqiang, Liu Wenhuai. Impact of waterlogging coupling with high temperature during cotton in flowering and boll-bearing on its photosynthetic physiology and yield[J]. Advance Journal of Food Science and Technology, 2012, 4(6): 344- 347.
[4] Kuai Jie, Zhou Zhiguo, Wang Youhua, et al. The effects of short-term waterlogging on the lint yield and yield components of cotton with respect to boll position[J]. European Journal of Agronomy, 2015, 67: 61-74.
[5] Kuai Jie, Liu Zhaowei, Wang Youhua, et al. Waterlogging during flowering and boll forming stages affects sucrose metabolism in the leaves subtending the cotton boll and its relationship with boll weight[J]. Plant Science, 2014, 223:79-98.
[6] 刘凯文, 苏荣瑞, 朱建强, 等. 棉花苗期叶片关键生理指标对涝渍胁迫的响应[J]. 中国农业气象, 2012, 33(3): 442-447.
Liu Kaiwen, Su Rongrui, Zhu Jiangqiang, et al. Dynamic responses of main physiological indices on cotton leaf to waterlogging stress at seedling stage[J]. Chinese Journal of Agrometeorology, 2012, 33(3): 442-447.
[7] 郭文琦, 陈兵林, 刘瑞显, 等. 施氮量对花铃期短期渍水棉花叶片抗氧化酶活性和内源激素含量的影响[J]. 应用生态学报, 2010, 21(1): 53-60.
Guo Wenqi, Chen Binglin, Liu Ruixian, et al. Effects of nitrogen application rate on cotton leaf antioxidant enzyme activities and endogenous hormone contents under short-term waterlogging at flowering and bolling-forming stage[J]. Chinese Journal of Applied Ecology, 2010, 21(1): 53-60.
[8] Milroy S P, Bange M P, Thongbai P. Cotton leaf nutrient concentrations in response to waterlogging under field conditions[J]. Field Crops Research, 2009, 1139(3): 246-255.
[9] 朱建强, 欧光华, 张文英, 等. 涝渍相随对棉花产量与品质的影响[J]. 中国农业科学, 2003, 36(9): 1050-1056.
Zhu Jiangqiang, Ou Guanghua, Zhang Wenying, et al. Influence of subsurface waterlogging followed by surface waterlogging on yield and quality of cotton[J]. Scientia Agricultura Sinica, 2003, 36(9): 1050-1056.
[10] Bange M P, Milroy S P, Thongbai P. Growth and yield of cotton in response to waterlogging[J]. Field Crops Research, 2004, 88(2): 129-142.
[11] Milroya S P, Bangeb M P. Reduction in radiation use efficiency of cotton under repeated transient waterlogging in the field[J]. Field Crops Research, 2013, 140: 51-58.
[12] 谢晓金, 申双和, 李映雪, 等. 高温胁迫下水稻红边特征及SPAD和LAI的监测[J]. 农业工程学报, 2010, 26(3): 183-190.
Xie Xiaojin, Shen Shuanghe, Li Yingxue, et al. Red edge characteristics and monitoring SPAD and LAI for rice with high temperature stress[J]. Transactions of the CSAE, 2010, 26(3): 183-190.
[13] 贾方方, 马新明, 李春明, 等. 不同水分处理对烟草叶片高光谱及红边特征的影响[J]. 中国生态农业学报, 2011, 19(6): 1330-1335.
Jia Fangfang, Ma Xinming, Li Chunming, et al. Effect of water condition on hyperspectral and red-edge characteristics of tobacco leaf[J]. Chinese Journal of Eco-Agriculture, 2011, 19(6):1330-1335.
[14] 冯先伟, 陈曦, 包安明, 等. 水分胁迫条件下棉花生理变化及其高光谱响应分析[J]. 干旱区地理, 2004, 27(2): 250-255.
Feng Xianwei, Chen Xi, Bao Anming, et al. Analysis on the cotton physiological change and its hyperspectral response under the water stress conditions[J]. Arid Land Geography, 2004, 27(2): 250-255.
[15] 谷艳芳, 丁圣彦, 陈海生, 等. 干旱胁迫下冬小麦高光谱特征和生理生态响应[J]. 生态学报, 2008, 28(6): 2690-2697.
Gu Yanfang, Ding Shengyan, Chen Haisheng, et al. Eco-physiological responses and hyperspectral characteristics of winter wheat under drought stress[J]. Acta Ecologica Sinca, 2008, 28(6): 2690-2697.
[16] 贺可勋, 赵书河, 来建斌, 等. 水分胁迫对小麦光谱红边参数和产量变化的影响[J]. 光谱学与光谱分析, 2013, 33(8): 2143- 2147.
He Kexun, Zhao Shuhe, Lai Jianbin, et al. Effects of water stress on red-edge parameters and yield in wheat cropping[J]. Spectroscopy and Spectral Analysis, 2013, 33(8): 2143-2147.
[17] 丛建鸥, 李宁, 许映军, 等. 干旱胁迫下冬小麦产量结构与生长、生理、光谱指标的关系[J]. 中国生态农业学报, 2010, 18(1): 67-71.
Cong Jianou, Li Ning, Xu Yingjun, et al. Relationship between indices of growth, physiology and reflectivity and yield of winter wheat under water stress[J]. Chinese Journal of Eco-Agriculture, 2010, 18(1): 67-71.
[18] 李章成, 周清波, 江道辉, 等. 棉花苗期冻害高光谱特征研究[J]. 棉花学报, 2008, 20(4): 306-311.
Li Zhangcheng, Zhou Qingbo, Jiang Daohui, et al. Study on hyperspectral features of the frostbite cotton at seedling stage[J]. Cotton Science, 2008, 20(4): 306-311.
[19] 武永峰, 胡新, 吕国华, 等. 晚霜冻影响下冬小麦冠层红边参数比较[J]. 光谱学与光谱分析, 2014, 34(8): 2190-2195.
Wu Yongfeng, Hu Xin, Lǚ Guohua, et al. Comparison of red edge parameters of winter wheat canopy under late frost stress [J]. Spectroscopy and Spectral Analysis, 2014, 34(8): 2190- 2195.
[20] 李军玲, 余卫东, 张弘, 等. 冬小麦越冬中期冻害高光谱敏感指数研究[J]. 中国农业气象, 2014, 35(6): 708-716.
Li Junling, Yu Weidong, Zhang Hong, et al. study on hyperspectral sensitivity index of winter wheat after freezing injury at mid-winter period[J]. Chinese Journal of Agrometeorology, 2014, 35(6): 708-716.
[21] Zhang Lei, Zhou Zhiguo, Zhang Guowei, et al. Monitoring the leaf water content and specific leaf weight of cotton in saline soil using leaf spectral reflectance[J]. European Journal of Agronomy, 2012, 41: 103-117.
[22] 姜志伟, 陈仲新, 任建强, 等. 粒子滤波同化方法在CERES-Wheat作物模型估产中的应用[J]. 农业工程学报, 2012, 28(14): 138-146.
Jiang Zhiwei, Chen Zhongxin, Ren Jianqiang, et al. Estimation of crop yield using CERES-Wheat model based on particle filter data assimilation method[J]. Transactions of the CSAE, 2012, 28(14): 138-146.
[23] 姚付启, 张振华, 杨润亚, 等. 基于红边参数的植被叶绿素含量高光谱估算模型[J]. 农业工程学报, 2009, 25(增2): 123-129.
Yao Fuqi, Zhang Zhenhua, Yang Runya, et al. Hyperspectral models for estimating vegetation chlorophyll content based on red edge parameter[J]. Transactions of the CSAE, 2009, 25(Suppl. 2): 123-129.
[24] 李文敏. 枫杨和湿地松幼苗生理参数的高光谱反演模型研究[D]. 陕西杨凌: 西北农林科技大学, 2014.
Li Wenmin. Research on hyperspectral models about physiological parameters of Pterocarya stenoptera C. DC. and Pinus elliottii Engelm.[D]. Yangling, Shaanxi: Northwest A&F University, 2014.