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刘小阳

作品数:2 被引量:6H指数:2
供职机构:广西大学电气工程学院更多>>
发文基金:国家自然科学基金广西壮族自治区自然科学基金更多>>
相关领域:农业科学理学自动化与计算机技术更多>>

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不同施肥情况下甘蔗叶片的光谱特征分析及叶绿素含量检测(英文)被引量:4
2015年
In order to investigate the visible-NIR spectral features of the leaves of a sugarcane variety(ROC 22),the spectral reflectance and the chlorophyll content were measured in the laboratory,and their correlations were analyzed.Prediction models were built eventually.Results showed that the negative correlations with r greater than 0.8 was found in 527-578 nm and 701-731nm between spectral reflectance and chlorophyll content.And the red edge position(REP)was also found having high correlation with chlorophyll content,with the highest r of 0.8442.In order to explore the most sensitive bands for normalized difference vegetation index(NDVI),48471 NDVI values were computed with different wavebands for each sample and their correlations with chlorophyll were also analyzed.The distribution maps of NDVI and its correlations in a two-spectral-dimension space both indicated that the red bands had significant influence than the NIR bands.The suggested sensitive red range was 710-735 nm,especially720-725 nm;and the sensitive NIR range was from 780-850 nm,which had the higher robustness.The chlorophyll predication model with NDVI(725 and 840 nm)in tillering stage had determination coefficients of 0.7386,and was recommended for guiding the subsequent ridging fertilization.
李修华陈晓周永华农梦玲刘小阳农梦玲
关键词:CHLOROPHYLLSUGARCANE
基于反射光谱的PCA及BP神经网络法预测甘蔗叶片叶绿素含量被引量:2
2017年
叶绿素是植物进行光合作用的重要色素,叶绿素含量可以作为评价植物生长状况的重要参数。本研究基于甘蔗叶片的反射光谱,利用PCA及BP神经网络算法,建立了甘蔗叶片的叶绿素含量预测模型。PCA算法可以在尽可能少地丢失有用光谱信息的前提下,降低输入光谱矩阵的维数,最大限度地减少冗余信息。BP神经网络算法因其良好的非线性逼近能力可大大提高该模型的预测精度。研究发现:基于PCA和BP算法建立的叶绿素含量预测模型,其预测值与实测值之间的R2达0.8929,表明该模型具有较高的预测能力。
陈晓李修华周永华丁永军刘小阳马绍对赵立安
关键词:甘蔗叶片光谱反射率叶绿素含量PCA算法BP神经网络
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