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Spectroscopy Letters
An International Journal for Rapid Communication
Volume 53, 2020 - Issue 6
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Articles

Detection of chlorophyll content in growth potato based on spectral variable analysis

Ning LiuKey Laboratory of Modern Precision Agriculture System Integration Research, Ministry of Education, China Agricultural University, Beijing, China; ORCID Iconhttp://orcid.org/0000-0003-1129-9071View further author information
ORCID Icon,
Lang QiaoKey Laboratory of Modern Precision Agriculture System Integration Research, Ministry of Education, China Agricultural University, Beijing, China; View further author information
,
Zizheng XingKey Laboratory of Modern Precision Agriculture System Integration Research, Ministry of Education, China Agricultural University, Beijing, China; View further author information
,
Minzan LiKey Laboratory of Modern Precision Agriculture System Integration Research, Ministry of Education, China Agricultural University, Beijing, China; ;Key Laboratory of Agricultural information acquisition technology, Ministry of Agriculture, China Agricultural University, Beijing, ChinaView further author information
,
Hong SunKey Laboratory of Modern Precision Agriculture System Integration Research, Ministry of Education, China Agricultural University, Beijing, China; Correspondence[email protected]
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,
Junyi ZhangKey Laboratory of Modern Precision Agriculture System Integration Research, Ministry of Education, China Agricultural University, Beijing, China; View further author information
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Yao ZhangKey Laboratory of Agricultural information acquisition technology, Ministry of Agriculture, China Agricultural University, Beijing, ChinaView further author information
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Pages 476-488 | Received 30 Apr 2020, Accepted 19 May 2020, Published online: 16 Jul 2020

Citations (14)

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Rei Sonobe, Yudai Sugimoto, Ryohei Kondo, Haruyuki Seki, Erika Sugiyama, Yoshikazu Kiriiwa & Katsumi Suzuki. (2021) Hyperspectral wavelength selection for estimating chlorophyll content of muskmelon leaves. European Journal of Remote Sensing 54:1, pages 513-524.
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Articles from other publishers (13)

Jingyao Gai, Jingyong Wang, Sasa Xie, Lirong Xiang & Ziting Wang. (2023) Spectroscopic determination of chlorophyll content in sugarcane leaves for drought stress detection. Precision Agriculture 25:2, pages 543-569.
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Weidong Pan, Xiaodong Cheng, Rongyu Du, Xinhua Zhu & Wenchuan Guo. (2024) Detection of chlorophyll content based on optical properties of maize leaves. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 309, pages 123843.
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Chao Liu, Yifei Cao, Ejiao Wu, Risheng Yang, Huanliang Xu & Yushan Qiao. (2023) A Discriminative Model for Early Detection of Anthracnose in Strawberry Plants Based on Hyperspectral Imaging Technology. Remote Sensing 15:18, pages 4640.
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Ruomei Zhao, Lulu An, Weijie Tang, Lang Qiao, Nan Wang, Minzan Li, Hong Sun & Guohui Liu. (2023) Improving chlorophyll content detection to suit maize dynamic growth effects by deep features of hyperspectral data. Field Crops Research 297, pages 108929.
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Hongfei Zhu, Lianhe Yang & Zhongzhi Han. (2023) Quantitative aflatoxin B1 detection and mining key wavelengths based on deep learning and hyperspectral imaging in subpixel level. Computers and Electronics in Agriculture 206, pages 107561.
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Songtao Ban, Weizhen Liu, Minglu Tian, Qi Wang, Tao Yuan, Qingrui Chang & Linyi Li. (2022) Rice Leaf Chlorophyll Content Estimation Using UAV-Based Spectral Images in Different Regions. Agronomy 12:11, pages 2832.
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Huanbo Yang, Yaohua Hu, Zhouzhou Zheng, Yichen Qiao, Bingru Hou & Jun Chen. (2022) A New Approach for Nitrogen Status Monitoring in Potato Plants by Combining RGB Images and SPAD Measurements. Remote Sensing 14:19, pages 4814.
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Ning Liu, Wenshuai Ye, Gang Liu & Guo Zhao. (2022) Improving the accuracy of stripping voltammetry detection of Cd2+ and Pb2+ in the presence of Cu2+ and Zn2+ by machine learning: Understanding and inhibiting the interactive interference among multiple heavy metals. Analytica Chimica Acta 1213, pages 339956.
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Ruomei Zhao, Lulu An, Weijie Tang, Dehua Gao, Lang Qiao, Minzan Li, Hong Sun & Jinbo Qiao. (2022) Deep learning assisted continuous wavelet transform-based spectrogram for the detection of chlorophyll content in potato leaves. Computers and Electronics in Agriculture 195, pages 106802.
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Qinlin Xiao, Wentan Tang, Chu Zhang, Lei Zhou, Lei Feng, Jianxun Shen, Tianying Yan, Pan Gao, Yong He & Na Wu. (2022) Spectral Preprocessing Combined with Deep Transfer Learning to Evaluate Chlorophyll Content in Cotton Leaves. Plant Phenomics 2022.
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Xiapeng Jiang, Jianing Zhen, Jing Miao, Demei Zhao, Junjie Wang & Sen Jia. (2021) Assessing mangrove leaf traits under different pest and disease severity with hyperspectral imaging spectroscopy. Ecological Indicators 129, pages 107901.
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Changchun Li, Chunyan Ma, Peng ChenYingqi Cui, Jinjin Shi & Yilin Wang. (2021) Machine learning-based estimation of potato chlorophyll content at different growth stage using UAV hyperspectral data. Zemdirbyste-Agriculture 108:2, pages 181-190.
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Ning Liu, Ruomei Zhao, Lang Qiao, Yao Zhang, Minzan Li, Hong Sun, Zizheng Xing & Xinbing Wang. (2020) Growth Stages Classification of Potato Crop Based on Analysis of Spectral Response and Variables Optimization. Sensors 20:14, pages 3995.
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