|
|
|
|
|
|
Determination of Net Photosynthetic Rate of Plants Based on
Environmental Compensation Model |
LI Cong-cong1, LUO Qi-wu2, ZHANG Ying-ying1, 3* |
1. School of Electrical Engineering and Automation, Hefei University of Technology, Hefei 230009, China
2. School of Automation, Central South University, Changsha 410083, China
3. National and Local Joint Engineering Laboratory of Renewable Energy Access to Power Grid Technology (Hefei University of Technology), Hefei 230009, China
|
|
|
Abstract Increasing the photosynthetic rate of crops is one of the reliable methods for high yield breeding. The main method for measuring photosynthesis rate is infrared gas analysis, which owns dependable axiom and mature technology. However, the infrared light source is easily affected by the complex working environment in the field, especially the change in ambient temperature. Therefore, the measurement error is significant in the task of quantitative analysis, and the detection precision of gas with deficient concentration or weak concentration change is not exact. Based on the above questions, first of all, the tunable diode laser absorption spectroscopy (TDLAS) is applied to the measurement of plant photosynthetic rate in this paper, which employs the second harmonic peak difference to represent the relative variation of trace concentration of photosynthetic gas CO2 in unit sampling time. Secondly, we established an environment compensation model of a broad learning system based on firefly algorithm optimization (FA-BLS). The position information of each firefly in the model corresponds to a set of feasible solutions representing the weights and thresholds of the BLS. Through the continuous iteration and update optimization of firefly position to find the firefly with the highest brightness, that is to generate the weights and thresholds that make the model perform the best. Ultimately, the compensation value generated by FA-BLS is used to compensate for the original second harmonic peak difference with environmental impact, and the net photosynthetic rate per unit sampling time was obtained from the compensated second harmonic peak difference. The experimental results indicate that the firefly population size and the number of nodes in the enhancement layer of BLS are significant considerations affecting the output error of TDLAS-FA-BLS, which commendably inherits the advantages of BLS, such as fast training speed and short iteration time. It is worth mentioning that the average measurement time of FA-BLS is merely 0.81 s, and the chi square distance between model prediction output and test set data is only 0.29×10-4, which indicates its output error is similarly small. At the same time, the sample variance and sample standard deviation of the output error of FA-BLS are lower than those of BLS, which illustrates that FA-BLS overcomes the shortcomings of BLS, such as unstable network output and low generalization due to random selection of parameters. Consequently, the method based on TDLAS-FA-BLS for the determination of plant net photosynthetic rate can nicely meet the needs of high precision, real-time, stability and reliability in the complex field working environment and actual agricultural production.
|
Received: 2021-04-20
Accepted: 2021-06-09
|
|
Corresponding Authors:
ZHANG Ying-ying
E-mail: zhangyy@hfut.edu.cn
|
|
[1] Orr D J, Alcantanra A, Kapralov M V, et al. Plant Physiology, 2016, 172(2): 707.
[2] Yin J, Liu X Y, Miao Y L, et al. International Journal of Agricultural and Biological Engineering, 2019, 12(5): 156.
[3] Yin G F, Zhao N J, Shi C Y, et al. Optics Express, 2018, 26(6): A293.
[4] Du T T, Meng P, Huang J L, et al. Plant Methods, 2020, 16(1): 10.
[5] LIU Zi-huai, YANG Chun-hua, LUO Qi-wu, et al(刘紫怀,阳春华,罗旗舞,等). Acta Optica Sinica(光学学报), 2019, 39(10): 335.
[6] JU Yu, CHEN Hao, HAN Li, et al(鞠 昱,陈 昊,韩 立,等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2020, 40(12): 3665.
[7] Zhang Z R, Pang T, Yang Y, et al. Optics Express, 2016, 24(10): 13.
[8] Xin M Y, Song J L, Rao W, et al. Chinese Journal of Aeronautics, 2020, 33(12): 3158.
[9] Chen C L P, Liu Z L. IEEE Transactions on Neural Networks and Learning Systems, 2018, 29(1): 10.
[10] Zhao G X, Wang X S, Kong Y, et al. Remote Sensing, 2021, 13(4): 23.
[11] Han J, Xie L, Liu J, et al. Multimedia Tools and Applications, 2020, 79(23-24): 16627.
[12] LI Yi-kai, ZHANG Tong, CHEN C L Philip(李逸楷,张 通,陈俊龙). Acta Automatica Sinica(自动化学报), 2020, 46(10): 2060.
[13] Sheng B, Li P, Zhang Y H, et al. IEEE Transactions on Cybernetics, 2021, 51(3): 1463.
[14] Yu W K, Zhao C H. IEEE Transactions on Industrial Electronics, 2020, 67(6): 5081.
[15] Yang X S. Engineering with Computers, 2013, 29(2): 175.
|
[1] |
ZENG Si-xian1, REN Xin1, HE Hao-xuan1, NIE Wei1, 2*. Influence Analysis of Spectral Line-Shape Models on Spectral Diagnoses Under High-Temperature Conditions[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2715-2721. |
[2] |
PENG Wei, YANG Sheng-wei, HE Tian-bo, YU Ben-li, LI Jin-song, CHENG Zhen-biao, ZHOU Sheng*, JIANG Tong-tong*. Detection of Water Vapor Concentration in Sealed Medicine Bottles Based on Digital Quadrature Phase-Locked Demodulation Algorithm and TDLAS
Technology[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(03): 698-704. |
[3] |
ZHANG Le-wen1, 2, WANG Qian-jin1, 3, SUN Peng-shuai1, PANG Tao1, WU Bian1, XIA Hua1, ZHANG Zhi-rong1, 3, 4, 5*. Analysis of Interference Factors and Study of Temperature Correction Method in Gas Detection by Laser Absorption Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(03): 767-773. |
[4] |
ZHANG Bo-han, YANG Jun, HUANG Qian-kun, XIE Xing-juan. Research on Gas Pressure Measurement Method Based on Absorption Spectroscopy and Laser Interference Technology[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(12): 3692-3696. |
[5] |
LONG Jiang-xiong1, 2, ZHANG Yu-jun1*, SHAO Li1*, YE Qing1, 2, HE Ying3, YOU Kun3, SUN Xiao-quan1, 2. Traceable Measurement of Optical Path Length of Gas Cell Based on Tunable Diode Laser Absorption Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(11): 3461-3466. |
[6] |
CHEN Hao1, 2, JU Yu3,HAN Li1. Research on the Relationship Between Modulation Depth and Center of High Order Harmonic in TDLAS Wavelength Modulation Method[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(12): 3676-3681. |
[7] |
CHEN Yang, DAI Jing-min*, WANG Zhen-tao, YANG Zong-ju. A Near-Infrared TDLAS Online Detection Device for Dissolved Gas in Transformer Oil[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(12): 3712-3716. |
[8] |
WANG Guo-shui1, GUO Ao2, LIU Xiao-nan1, FENG Lei1, CHANG Peng-hao1, ZHANG Li-ming1, LIU Long1, YANG Xiao-tao1*. Simulation and Influencing Factors Analysis of Gas Detection System Based on TDLAS Technology[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(10): 3262-3268. |
[9] |
CHEN Hao1, 2, JU Yu3, HAN Li1, CHANG Yang3. Curve Fitting of TDLAS Gas Concentration Calibration Based on Relative Error Least Square Method[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(05): 1580-1585. |
[10] |
HUANG An1, 2, XU Zhen-yu1, XIA Hui-hui1, YAO Lu1, RUAN Jun1, HU Jia-yi1, ZANG Yi-peng1, 2, KAN Rui-feng1*. Measurement Method of Two-Dimensional Distribution of Temperature and Components in Gas Turbine Combustor Based on Wavelength Modulated Absorption Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(04): 1144-1150. |
[11] |
JU Yu1,CHEN Hao2, 3,HAN Li2,CHANG Yang1, ZHANG Xue-jian1. Based on TDLAS Technology Gas Concentration Calibration Algorithm for a Large Range[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40(12): 3665-3669. |
[12] |
CHEN Hao1, 2, JU Yu3, HAN Li1, CHANG Yang3. Algorithms for Calculating the Concentration of Gas Mixture Containting Different Background Gases in TDLAS Technology[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40(10): 3015-3020. |
[13] |
XIAO Hu-ying1, YANG Fan1, XIANG Liu1, HU Xue-jiao2*. Jet Vacuum Enhanced Tunable Diode Laser Absorption Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2019, 39(10): 2993-2997. |
[14] |
ZHANG Bu-qiang1, 2, XU Zhen-yu1, LIU Jian-guo1, XIA Hui-hui1, FAN Xue-li1, NIE Wei1, 2, YUAN Feng1, 2, KAN Rui-feng1. Modulation Characteristics of Laser Based on Wavelength Modulation Technology[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2019, 39(09): 2702-2707. |
[15] |
LI Zheng-hui1,3, YAO Shun-chun1,3*, LU Wei-ye2, ZHU Xiao-rui1,3, ZOU Li-chang1,3, LI Yue-sheng2, LU Zhi-min1,3. Study on Temperature Correction Method of CO2 Measurement by TDLAS[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(07): 2048-2053. |
|
|
|
|