中国农业气象 ›› 2022, Vol. 43 ›› Issue (10): 832-845.doi: 10.3969/j.issn.1000-6362.2022.10.006

• 农业气象信息技术 栏目 • 上一篇    下一篇

基于高光谱参数建立苗期高温条件下草莓叶片叶绿素含量估算模型

罗靖,杨再强,杨立,袁昌洪,张丰寅,李岩宸,李春影   

  1. 1.南京信息工程大学气象灾害预报预警与评估协同创新中心,南京 210044;2.江苏省农业气象重点实验室,南京 210044;3.江苏省泰州市气象局,泰州 225300;4.皖西学院,六安 237012
  • 收稿日期:2021-12-03 出版日期:2022-10-20 发布日期:2022-10-21
  • 通讯作者: 杨再强,教授,研究方向为设施农业气象。 E-mail: yzq@nuist.edu.cn
  • 作者简介:罗靖,E-mail: 20211208035@nuist.edu.cn
  • 基金资助:
    国家重点研发计划项目(2019YFD1002202)

Establishment of an Estimation Model for Chlorophyll Content of Strawberry Leaves under High Temperature Conditions at Seedling Stage Based on Hyperspectral Parameters

LUO Jing, YANG Zai-qiang, YANG Li, YUAN Chang-hong, ZHANG Feng-yin, LI Yan-chen, LI Chun-ying   

  1. 1. Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing 210044, China; 2. Jiangsu Key Laboratory of Agrometeorology, Nanjing 210044; 3. Taizhou Meteorological Bureau, Jiangsu Province, Taizhou 225300; 4. West Anhui University, Lu'an 237012
  • Received:2021-12-03 Online:2022-10-20 Published:2022-10-21

摘要: 以“红颜”草莓(Fragaria×ananassa Duch“Benihope”)为试材,于2021年9−11月在人工气候室进行苗期(9~12片真叶,叶长≥5cm)动态高温环境控制实验,日最高温度以32℃为起点,设置日最高气温/日最低气温分别为32℃/22℃、35℃/25℃、38℃/28℃和41℃/31℃共4个水平,持续时间分别为2d、5d、8d和11d,以28℃/18℃为对照(CK)。试验期间空气相对湿度60%~70%,光周期12h/12h(6:00−18:00),光照强度800μmolm−2s−1。测定不同处理下叶片叶绿素含量及高光谱反射率,对原始光谱进行变换,从而细化光谱特征信息。在相关分析的基础上,建立原始和一阶敏感波段植被指数,进而筛选出表征叶绿素含量的光谱特征参数,以期构建叶绿素含量最佳估算模型。结果表明:(1)随着温度的升高和高温持续时间的延长,草莓叶片叶绿素a、叶绿素b和总叶绿素(a+b)含量呈下降趋势。(2)草莓叶片原始光谱在可见光区域均存在绿峰和红谷,除绿峰和红谷外各处理间差异不明显,高温条件下的近红外区域反射率与CK相比出现不同程度的上升。与原始光谱相比,一阶导数光谱曲线震荡更剧烈,且能够显著突出红边参数特征,各处理的红边位置λr稳定在716nm,红边幅值Dr与红边面积Sr差异显著;而在连续统去除光谱中各处理的绿峰(550nm附近)和红谷(675nm附近)被完全突显出来。(3)在光谱反射率与叶绿素含量相关性分析的基础上,选取原始光谱与一阶导数光谱在可见光和近红外波段相关性最强的R747、R800和R'716、R'906为敏感波段组合,构建植被指数。(4)PVI、MSAVI、TSAVI、TSAVI'、DVI'、MSAVI'、PVI'、SAVI'、Dr和Sr指数与叶绿素含量相关性达极显著水平,可作为表征设施草莓叶片叶绿素含量对苗期高温胁迫响应的高光谱特征参数。其中以TSAVI、DVI'和PVI'植被指数建立的逐步回归模型为叶绿素含量最佳估算模型,其决定系数(R2)为0.843,均方根误差(RMSE)为0.379,相对误差(RE)为12.65%。

关键词: 草莓, 高温胁迫, 高光谱参数, 叶绿素含量, 估算模型

Abstract: The experiments were conducted in the artificial climate chamber from September to November 2021, using "Hongyan" strawberry(Fragaria×ananassa Duch "Benihope") as the test material for dynamic high- temperature environmental control experiments at the seedling stage (9−12 true leaves, leaf length ≥ 5 cm), with a daily maximum temperature of 32°C as the starting point and four levels of daily maximum/daily minimum temperatures of 32°C/22°C, 35°C/25°C, 38°C/28°C, and 41°C/31°C for 2d, 5d, 8d, and 11d, respectively, and 28°C/18°C as the control (CK).The relative air humidity is 60%−70%, the photoperiod is 12h/12h (6:00−18:00), and the light intensity is 800μmol·m−2·s−1. The chlorophyll content and hyperspectral reflectance of leaves under different treatments were measured, and the original spectrum was changed to refine the spectral characteristic information. Based on the correlation analysis, the original and first-order sensitive band vegetation indices were established, and then the spectral characteristic parameters that characterize chlorophyll content were screened, in order to build the best estimation model of chlorophyll content. The results showed that: (1) the chlorophyll a, chlorophyll b and total chlorophyll (a+b) contents of strawberry leaves tended to decrease as the temperature increased and the duration of high temperature increased. (2) The original spectra of strawberry leaves had green peaks and red valleys in the visible region, except for the green peaks and red valleys, which did not differ significantly among treatments, and the reflectance in the NIR region under high temperature conditions showed different degrees of increase compared with CK. Compared with the original spectra, the first-order derivative spectral curves oscillated more strongly and were able to highlight the red edge parameters significantly. The red edge position λr of each treatment was stable at 716nm, and the difference between the red edge amplitude Dr and the red edge area Sr was significant; while the green peak (near 550 nm) and red valley (near 675nm) of each treatment were completely highlighted in the continuous uniform removal spectra. (3) Based on the correlation analysis between spectral reflectance and chlorophyll content, R747, R800 and R'716, R'906, which have the strongest correlation between the original and first derivative spectra in the visible and near-infrared bands, were selected as the combination of sensitive bands to construct the vegetation index. (4) PVI, MSAVI, TSAVI, TSAVI', DVI', MSAVI', PVI', SAVI', Dr and Sr indices correlated with chlorophyll content at highly significant levels and can be used as hyperspectral characteristic parameters to characterize the chlorophyll content of greenhouse strawberry leaves in response to high temperature stress at seedling stage. The stepwise regression model with TSAVI, DVI' and PVI' vegetation indices was the best estimation model for chlorophyll content, with a coefficient of determination (R2) of 0.843, root mean square error (RMSE) of 0.379 and relative error (RE) of 12.65%.

Key words: Strawberry, High temperature stress, Hyperspectral parameters, Chlorophyll content, Estimation model