| 沈 佳1，2，熊永柱1，许燕婷1，刘惠娜3，程丹玲3.胁迫处理蜜柚叶片色素含量高光谱遥感估测模型研究[J].广东农业科学,2018,45(8):118-129 |
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胁迫处理蜜柚叶片色素含量高光谱遥感估测模型研究 |
| Study on hyperspectral remote sensing estimation Models of pigment contents of pomelo leavesunder different stresses |
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| DOI：10.16768/j.issn.1004-874X.2018.08.018 |
| 中文关键词: 光谱特征 色素含量 相关分析 蜜柚 梅州 |
| 英文关键词: spectral characteristics pigment content correlation analysis pomelo Meizhou |
| 基金项目:广东省自然科学基金（2017A030307040）；嘉应学院创新强校工程项目（CQX027）；广东省普通高
校人文社会科学省市共建重点研究基地项目（17KYKT13）；嘉应学院大学生创新创业训练国家级基金（201710582012） |
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| 摘要点击次数: 1807 |
| 全文下载次数: 643 |
| 中文摘要: |
| 通过在梅州蜜柚农业园实地采集健康成熟、缺锌成熟、受潜叶蛾胁迫成熟柚叶以及健康嫩叶
4 种不同健康状况叶片的高光谱数据，并通过生化手段测定柚叶样本的叶绿素总量和类胡萝卜素含量，分
析构建基于高光谱特征变量的不同环境胁迫下最优的蜜柚叶片色素含量估测模型。在分析色素含量值与原
始光谱反射率及其微分光谱、高光谱特征参数相关性的基础上，选取每个类别中与柚叶色素含量极显著相
关的波段和高光谱特征参数，通过单变量的线性、对数和指数模型以及多元线性逐步回归方法建立不同类
别柚叶色素含量的估测模型。结果表明，通过多元线性逐步回归建立的估测模型具有最高的精度，对健康
成熟柚叶叶绿素总量和类胡萝卜素含量的建模精度分别为0.850 和0.705，检验精度为0.754 和0.606；对
缺锌成熟柚叶2 种色素的建模精度为0.895 和0.904，检验精度为0.932 和0.908；对潜叶蛾胁迫成熟柚叶
叶绿素总量的建模精度为0.738，检验精度为0.834；健康嫩叶2 种色素的建模精度为0.911 和0.897，检验
精度为0.898 和0.944。推荐使用多元线性逐步回归模型来估测不同环境胁迫下蜜柚叶绿素总量和类胡萝卜
素含量。 |
| 英文摘要: |
| In this study, the hyperspectral data of four different kinds of leaves including healthy mature, zinc
deficiency mature, leaf-miner inflicted mature and healthy young leaves, which have different pigment content levels,
were collected in a pomelo agricultural garden in Meizhou city. It was attempting to investigate the best hyperspectral
remote sensing models of pigment contents estimation of pomelo leaves under different environmental stresses. The
total chlorophyll and carotenoid content of the leaf samples were determined by biochemical methods. On the basis of analyzing the correlation between pigment content value and original spectral reflectance, differential spectrum
and hyperspectral characteristic parameters, bands and hyperspectral characteristic parameters with extremely good
correlation （P < 0.01）with pomelo pigment content in each category were selected. The linear, logarithmic and
exponential models of single variable regression and multivariate linear stepwise regression were employed to estimate
the content of two pigments in the four kinds of pomelo leaves. The estimation models established by multivariate
linear stepwise regression have the highest precision. The modeling precision of chlorophyll and carotenoid of healthy
mature pomelo leaves is 0.850 and 0.705, and the testing accuracy is 0.754 and 0.606, respectively. The modeling
precision of two pigments for zinc deficiency mature leaves is 0.895 and 0.904 and the testing accuracy is 0.932 and
0.908, respectively. The modeling precision of chlorophyll for leaf-miner inflicted mature leaves is 0.738 and the
testing accuracy is 0.834, respectively. The modeling precision of two pigments for healthy young leaves is 0.911 and
0.897, and the testing accuracy is 0.898 and 0.944, respectively. It is suggested that the multivariate linear stepwise
regression models be used to estimate the chlorophyll and carotenoid contents of pomelo leaves under different stresses
based on hyperspectral remote sensing. |
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