| 柑橘叶片叶绿素含量高光谱无损检测模型 |
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| 引用本文： | 岳学军,全东平,洪添胜,王健,瞿祥明,甘海明.柑橘叶片叶绿素含量高光谱无损检测模型[J].农业工程学报,2015,31(1):294-302. |
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| 作者姓名： | 岳学军 全东平 洪添胜 王健 瞿祥明 甘海明 |
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| 作者单位： | 华南农业大学南方农业机械与装备关键技术教育部重点实验室,广州 510642; 国家柑橘产业技术体系机械研究室,广州 510642; 华南农业大学工程学院,广州 510642 |
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| 基金项目： | 国家自然科学基金（30871450）;广东省自然科学基金项目 |
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| 摘 要： | 针对柑橘叶片叶绿素含量的传统化学检测,不仅耗时长且损伤柑橘叶片,还依赖检测者实操技术,无法集成于精细农业中变量喷施农机具的诸多弊端,该文探讨快速无损检测柑橘叶片叶绿素含量方法。以117棵园栽萝岗甜橙树为研究对象,选用ASD Field Spec 3光谱仪对萌芽期、稳果期、壮果促梢期、采果期共4个生长时期的柑橘叶片进行高光谱反射率采集,并同步采用分光光度法测得叶片的叶绿素含量;以原始光谱及其变换形式作为模型输入矢量,分别在主成分分析(principle component analysis,PCA)降维的基础上利用支持向量机回归(support vector regression,SVR)算法和在小波去噪的基础上利用偏最小二乘回归(partial least square regression,PLSR)算法对柑橘叶片叶绿素含量进行建模预测,全生长期整体建模的校正集和验证集最佳模型决定系数R2分别为0.8713和0.8670,均方根误差RMSE(root-mean-square error)分别为0.1517和0.1544,试验结果表明,高光谱可快速无损地对柑橘叶片叶绿素含量进行精确的定量检测,为柑橘不同生长期的营养监测提供理论依据。
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| 关 键 词： | 叶绿素 主成分分析 无损检测 高光谱 柑橘叶片 支持向量机回归 偏最小二乘回归 |
| 收稿时间： | 2014/4/30 0:00:00 |
| 修稿时间： | 2014/11/13 0:00:00 |
Non-destructive hyperspectral measurement model of chlorophyll content for citrus leaves |
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| Yue Xuejun,Quan Dongping,Hong Tiansheng,Wang Jian,Qu Xiangming and Gan Haiming.Non-destructive hyperspectral measurement model of chlorophyll content for citrus leaves[J].Transactions of the Chinese Society of Agricultural Engineering,2015,31(1):294-302. |
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| Authors: | Yue Xuejun Quan Dongping Hong Tiansheng Wang Jian Qu Xiangming and Gan Haiming |
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| Institution: | 1. Key Laboratory of Key Technology on Agricultural Machine and Equipment , Ministry of Education, Guangzhou 510642,China2. Division of Citrus Machinery, China Agriculture Research System, Guangzhou 510642, China3. College of Engineering, South China Agricultural University, Guangzhou 510642, China,1. Key Laboratory of Key Technology on Agricultural Machine and Equipment , Ministry of Education, Guangzhou 510642,China2. Division of Citrus Machinery, China Agriculture Research System, Guangzhou 510642, China3. College of Engineering, South China Agricultural University, Guangzhou 510642, China,1. Key Laboratory of Key Technology on Agricultural Machine and Equipment , Ministry of Education, Guangzhou 510642,China2. Division of Citrus Machinery, China Agriculture Research System, Guangzhou 510642, China3. College of Engineering, South China Agricultural University, Guangzhou 510642, China,1. Key Laboratory of Key Technology on Agricultural Machine and Equipment , Ministry of Education, Guangzhou 510642,China2. Division of Citrus Machinery, China Agriculture Research System, Guangzhou 510642, China3. College of Engineering, South China Agricultural University, Guangzhou 510642, China,1. Key Laboratory of Key Technology on Agricultural Machine and Equipment , Ministry of Education, Guangzhou 510642,China2. Division of Citrus Machinery, China Agriculture Research System, Guangzhou 510642, China3. College of Engineering, South China Agricultural University, Guangzhou 510642, China and 1. Key Laboratory of Key Technology on Agricultural Machine and Equipment , Ministry of Education, Guangzhou 510642,China2. Division of Citrus Machinery, China Agriculture Research System, Guangzhou 510642, China3. College of Engineering, South China Agricultural University, Guangzhou 510642, China |
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| Abstract: | |
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| Keywords: | chlorophyll principle component analysis nondestructive examination hyperspectrum citrus leaves support vector regression partial least square regression |
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