冯 伟, 王晓宇, 宋 晓, 贺 利, 王晨阳, 郭天财. 白粉病胁迫下小麦冠层叶绿素密度的高光谱估测[J]. 农业工程学报, 2013, 29(13): 114-123. DOI: 10.3969/j.issn.1002-6819.2013.13.016
    引用本文: 冯 伟, 王晓宇, 宋 晓, 贺 利, 王晨阳, 郭天财. 白粉病胁迫下小麦冠层叶绿素密度的高光谱估测[J]. 农业工程学报, 2013, 29(13): 114-123. DOI: 10.3969/j.issn.1002-6819.2013.13.016
    Feng Wei, Wang Xiaoyu, Song Xiao, He Li, Wang Chenyang, Guo Tiancai. Hyperspectral estimation of canopy chlorophyll density in winter wheat under stress of powdery mildew[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2013, 29(13): 114-123. DOI: 10.3969/j.issn.1002-6819.2013.13.016
    Citation: Feng Wei, Wang Xiaoyu, Song Xiao, He Li, Wang Chenyang, Guo Tiancai. Hyperspectral estimation of canopy chlorophyll density in winter wheat under stress of powdery mildew[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2013, 29(13): 114-123. DOI: 10.3969/j.issn.1002-6819.2013.13.016

    白粉病胁迫下小麦冠层叶绿素密度的高光谱估测

    Hyperspectral estimation of canopy chlorophyll density in winter wheat under stress of powdery mildew

    • 摘要: 为了明确病害胁迫下作物生长特征及其危害程度,基于大田小区和盆栽小麦白粉病接种试验,在病害胁迫下不同生育时期测定群体光谱及叶绿素密度。综合分析群体光谱反射率、一阶微分及传统光谱特征参数与冠层叶绿素密度间关系,建立病害叶绿素密度估算模型并检验。结果表明,随病情指数增加,叶绿素含量下降,不同感性品种均如此,对白粉病易感品种的危害较重。病害冠层叶绿素密度与红光600~630 nm和红边690~718 nm的反射率及红边长波段(718~756 nm)的一阶微分间相关性最显著。在传统植被指数中,以SDr/SDb和VOG3为变量的估测模型拟合精度较高,决定系数R2分别为0.752和0.723,模型检验相对误差(RE)最小,RE分别为18.0%和18.6%。利用红边区域(680~760 nm)波段差异特性,选取680、718和756 nm波段新建红边角度指数(REAI),较传统植被指数的模型拟合精度更高,归一化角度指数NDAI (α,β)和比值角度指数RAI (α,β)的R2分别为0.783和0.776,模型检验误差更小,RE分别为16.8%和17.5%。因此,NDAI (α,β)是估测病害小麦冠层叶绿素密度的可靠指标,对利用该模型监测小麦光合潜力和病害影响评价具有积极意义。

       

      Abstract: Abstract: The diagnosis of crop health and growth status under various stresses is an important step in precision agriculture. In order to enhance the timeliness in monitoring the growing state and evaluating disease influence in wheat production by using hyperspectral remote sensing, three experiments were conducted with different disease degree treatments across different growth phases, and different cultivars were chosen including four cultivars of Yanzhan 4110, Yumai34, Yumai 49 and Xinong 979 considered as susceptible variety types, and three cultivars of Zhoumai 18, Zhengmai 366 and Aikang58 considered as medium resistant variety types to strengthen wide applicability of monitoring models. The spectrum reflectance and canopy chlorophyll density (CCD) infected with powdery mildew were measured in winter wheat diseased in the nursery and the field during the experiments' periods in 2009-2011. The relationships of spectra reflectance, the first derivative of reflectance, and existing spectral indices to CCD were analyzed respectively, and the monitoring models of the CCD of diseased wheat were established and tested. The results indicated that the canopy chlorophyll content resulted in an obvious declining trend in two different resistant varieties of wheat, and the powdery mildew damage was heavy for the susceptible variety Yanzhan4110 and slighter lower for the medium resistant variety zhoumai18. The correlations were most significant between CCD and spectral reflectance in red wave bands of 600-630 nm and red edge wave bands of 690-718 nm, and the first derivative spectrum in red edge wave bands of 718-756 nm. The models of SDr/SDb and VOG3 among existing spectral indices had the best fitting precision with a determination coefficient (R2) of 0.752 and 0.723 respectively, and the lowest relative errors (RE) between measured and estimated CCD as 18.0% and 18.6%. A new red edge angle index (REAI) selecting optimal bands of 680, 718 and 756 nm was found to be a good indicator for CCD, with fitting R2 of 0.783 for NDAI (α,β) and 0.776 for RAI (α,β), and test RE of 16.8% for NDAI (α,β) and 17.5% for RAI (α,β). The overall results indicated that hyperspectral vegetation indices can be used to reliably estimate CCD of wheat infected with powdery mildew, and CCD models based on a red edge angle index has great practical and application value for monitoring photosynthetic potential productivity and disease influence evaluation on wheat.

       

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