基于手机图像反演的滴灌玉米光响应曲线特征参数研究
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摘要
为研究利用手机图像预测玉米光响应曲线特征参数的可行性,通过自主设计的便携式图像采集装置,获取不同施氮量下滴灌玉米大喇叭口期冠层图像,提取其冠层图像特征参数,计算玉米光响应特征参数表观量子效率(α)、最大净光合速率(P_(nmax))、光补偿点(LCP)和暗呼吸速率(R_d),找出与光响应特征参数相关性高的归一化冠层覆盖系数(C_C)作为自变量,建立C_C与玉米光响应曲线特征参数间动态模型,并根据模型评价指标R~2、RMSE和nRMSE筛选出各参数的最优模型。结果表明,C_C与α的最优模型为有理函数模型,与P_(nmax)最优模型为幂函数模型,与LCP最优模型为指数函数模型,与R_d以二次多项式模型为最优;各反演模型的R~2均不小于0. 876,RMSE介于0. 002～3. 673μmol/(m~2·s)之间,nRMSE不超过9. 071%,且各模型验证集的R~2均不小于0. 833,RMSE均不大于5. 989μmol/(m~2·s),nRMSE不超过9. 659%。将数字图像特征参数与作物光响应曲线特征参数有机结合,可为玉米光响应曲线特征参数的快速获取提供一定的理论依据。
The characteristic parameters of light response can indicate the process of photosynthesis,capacity of photosynthesis,and response of adversity stress in crops. In order to explore the feasibility of using cellphone photos to predict the light response characteristic parameters of maize,canopy images at the big flare stage of the drip irrigation maize under different nitrogen levels were obtained by the selfdeveloped portable image acquisition device. Feature parameters were extracted from the canopy image,and the photosynthetic physiological characteristics parameters were calculated,such as apparent quantum efficiency( α),dark respiration rate( R_d),light compensation point( LCP) and maximum net photosynthesis rate( P_(nmax)). A normalized canopy cover factor( C_C) was highly correlated with the light response characteristic parameters,as an independent variable was used to predict these parameters. The optimal model was selected according to the model evaluation indicators such as R~2,RMSE and nRMSE.The results showed that the optimal model of C_Cand α was the rational function model,the optimal model of P_(nmax)was the power function model,the optimal model of LCP was the exponential function model and the optimal model of R_dwas the quadratic polynomial model. The R~2 values of each model were greater than 0. 876,the values of RMSE were between 0. 002 μmol/( m~2·s) and 3. 673 μmol/( m~2·s),and the nRMSE was no more than 9. 071%. Meanwhile,the R~2 values of each model validation set were greater than 0. 833,the RMSE values were less than 5. 989 μmol/( m~2·s),and the nRMSE values were no more than 9. 659%. Combining the digital image feature parameters with the maize light response curve characteristic parameters method,it was recommended to quickly acquire characteristic parameters of maize light response curve,which provided a theoretical basis for the light response.
The characteristic parameters of light response can indicate the process of photosynthesis,capacity of photosynthesis,and response of adversity stress in crops. In order to explore the feasibility of using cellphone photos to predict the light response characteristic parameters of maize,canopy images at the big flare stage of the drip irrigation maize under different nitrogen levels were obtained by the selfdeveloped portable image acquisition device. Feature parameters were extracted from the canopy image,and the photosynthetic physiological characteristics parameters were calculated,such as apparent quantum efficiency( α),dark respiration rate( R_d),light compensation point( LCP) and maximum net photosynthesis rate( P_(nmax)). A normalized canopy cover factor( C_C) was highly correlated with the light response characteristic parameters,as an independent variable was used to predict these parameters. The optimal model was selected according to the model evaluation indicators such as R~2,RMSE and nRMSE.The results showed that the optimal model of C_Cand α was the rational function model,the optimal model of P_(nmax)was the power function model,the optimal model of LCP was the exponential function model and the optimal model of R_dwas the quadratic polynomial model. The R~2 values of each model were greater than 0. 876,the values of RMSE were between 0. 002 μmol/( m~2·s) and 3. 673 μmol/( m~2·s),and the nRMSE was no more than 9. 071%. Meanwhile,the R~2 values of each model validation set were greater than 0. 833,the RMSE values were less than 5. 989 μmol/( m~2·s),and the nRMSE values were no more than 9. 659%. Combining the digital image feature parameters with the maize light response curve characteristic parameters method,it was recommended to quickly acquire characteristic parameters of maize light response curve,which provided a theoretical basis for the light response.
引文
[1] FANG L,ZHANG S Y,ZHANG G G,et al. Application of five light-response models in the photosynthesis of Populus×Euramericana cv.‘zhonglin46’leaves[J]. Applied Biochemistry&Biotechnology,2015,176(1):86-100.
[2] CHEN Z Y,PENG Z S,YANG J,et al. A mathematical model for describing light-response curves in Nicotiana tabacum L.[J]. Photosynthetica,2011,49(3):467-471.
[3] FAN Z,QUAN Q,LI Y,et al. Exploring the best model for describing light-response curves in two Epimedium species[J].Technology and Health Care,2015,23(1):9-13.
[4] LAROCQUE G R. Coupling a detailed photosynthetic model with foliage distribution and light attenuation functions to compute daily gross photosynthesis in sugar maple(Acer saccharum Marsh.)stands[J]. Ecological Modelling,2002,148(3):213-232.
[5]王帅,韩晓日,战秀梅,等.不同氮肥水平下玉米光响应曲线模型的比较[J].植物营养与肥料学报,2014,20(6):1403-1412.WANG Shuai,HAN Xiaori,ZHAN Xiumei,et al. The comparative study on fitting light response curve model of photosynthesis of maize under different nitrogen fertilizer levels[J]. Journal of Plant Nutrition and Fertilizer,2014,20(6):1403-1412.(in Chinese)
[6] LAMPTEY S,LI L,XIE J,et al. Photosynthetic response of maize to nitrogen fertilization in the semiarid western loess plateau of China[J]. Crop Science,2017,57(5):2739-2752.
[7] LI G,ZHANG Z S,GAO H Y,et al. Effects of nitrogen on photosynthetic characteristics of leaves from two different stay-green corn(Zea mays L.)varieties at the grain-filling stage[J]. Canadian Journal of Plant Science,2017,92(4):671-680.
[8] ZHANG Y,WANG J,GONG S,et al. Nitrogen fertigation effect on photosynthesis,grain yield and water use efficiency of winter wheat[J]. Agricultural Water Management,2016,179:277-287.
[9] DING L,WANG K J,JIANG G M,et al. Effects of nitrogen deficiency on photosynthetic traits of maize hybrids released in different years[J]. Annals of Botany,2005,96(5):925-930.
[10] WALTER A,FINGER R,HUBER R,et al. Opinion:smart farming is key to developing sustainable agriculture[J].Proceedings of the National Academy of Sciences,2017,114(24):6148-6150.
[11]陈俊英,陈硕博,张智韬,等.无人机多光谱遥感反演花蕾期棉花光合参数研究[J/OL].农业机械学报,2018,49(10):230-239.CHEN Junying,CHEN Shuobo,ZHANG Zhitao,et al. Investigation on photosynthetic parameters of cotton during budding period by multi-spectral remote sensing of unmanned aerial vehicle[J/OL]. Transactions of the Chinese Society for Agricultural Machinery,2018,49(10):230-239. http:∥www. jcsam. org/jcsam/ch/reader/view_abstract. aspx? flag=1&file_no=20181026&journal_id=jcsam. DOI:10. 6041/j. issn. 1000-1298. 2018. 10. 026.(in Chinese)
[12] MOUALEU-NGANGUE D P,CHEN T W,STüTZEL H. A new method to estimate photosynthetic parameters through net assimilation rate intercellular space CO2concentration curve and chlorophyll fluorescence measurements[J]. New Phytologist,2016,213(3):1543.
[13] JIN P B,WANG Q,IIO A,et al. Retrieval of seasonal variation in photosynthetic capacity from multi-source vegetation indices[J]. Ecological Informatics,2012,7(1):7-18.
[14] GAMON J A,BOND B. Effects of irradiance and photosynthetic downregulation on the photochemical reflectance index in Douglas-fir and ponderosa pine[J]. Remote Sensing of Environment,2013,135:141-149.
[15]武海巍,于海业,田彦涛,等.基于核函数与可见光光谱的大豆植株群体净光合速率预测模型[J].光谱学与光谱分析,2016,36(6):1831-1836.WU Haiwei,YU Haiye,TIAN Yantao,et al. Prediction model on net photosynthetic rate of soybean plant groups based on kernel function and visible light spectrum[J]. Spectroscopy and Spectral Analysis,2016,36(6):1831-1836.(in Chinese)
[16]张雨晴,于海业,刘爽,等.玉米叶片净光合速率快速检测方法研究[J].农机化研究,2019,41(4):182-185.ZHANG Yuqing,YU Haiye,LIU Shuang,et al. Study on rapid detection method of net photosynthetic rate of maize leaves[J]. Journal of Agricultural Mechanization Research,2019,41(4):182-185.(in Chinese)
[17]程麒,黄春燕,王登伟,等.基于红外热图像的棉花冠层水分胁迫指数与光合特性的关系[J].棉花学报,2012,24(4):341-347.CHENG Qi, HUANG Chunyan, WANG Dengwei, et al. Correlation between cotton canopy CWSI and photosynthesis characteristics based on infrared thermography[J]. Cotton Science,2012,24(4):341-347.(in Chinese)
[18] YUAN Y,CHEN L,LI M,et al. Diagnosis of nitrogen nutrition of rice based on image processing of visible light[C]∥IEEE,2016:228-232.
[19] BARESEL J P,RISCHBECK P,HU Y,et al. Use of a digital camera as alternative method for non-destructive detection of the leaf chlorophyll content and the nitrogen nutrition status in wheat[J]. Computers and Electronics in Agriculture,2017,140:25-33.
[20] JIA B,HE H H B,MA F Y,et al. Use of a digital camera to monitor the growth and nitrogen status of cotton[J]. The Scientific World Journal,2014,2014:1-12.
[21]贾彪,马富裕.基于机器视觉的棉花氮素营养诊断系统设计与试验[J/OL].农业机械学报,2016,47(3):305-310.JIA Biao,MA Fuyu. Design and experiment of nitrogen nutrition diagnosis system of cotton based on machine vision[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2016,47(3):305-310. http:∥www. jcsam. org/jcsam/ch/reader/view_abstract. aspx? flag=1&file_no=20160343&journal_id=jcsam. DOI:10. 6041/j. issn. 1000-1298. 2016. 03.043.(in Chinese)
[22] YANG P,JIA B,ZHENG Z. Modeling cotton growth and nitrogen status using image analysis[J]. Agronomy Journal,2017,109(6):2630-2638.
[23] KOROBIICHUK I,LYSENKO V,OPRYSHKO O,et al. Crop monitoring for nitrogen nutrition level by digital camera[C]∥Conference on Automation,2018,743:595-603.
[24]牛庆林,冯海宽,杨贵军,等.基于无人机数码影像的玉米育种材料株高和LAI监测[J].农业工程学报,2018,34(5):73-82.NIU Qinglin,FENG Haikuan,YANG Guijun,et al. Monitoring plant height and leaf area index of maize breeding material based on UAV digital images[J]. Transactions of the CSAE,2018,34(5):73-82.(in Chinese)
[25] YE Z P,SUGGETT D J,ROBAKOWSKI P,et al. A mechanistic model for the photosynthesis-light response based on the photosynthetic electron transport of photosystem II in C3 and C4 species[J]. New Phytol,2013,199(1):110-120.
[26] YE Z P,ROBAKOWSKI P,SUGGETT D J. A mechanistic model for the light response of photosynthetic electron transport rate based on light harvesting properties of photosynthetic pigment molecules[J]. Planta,2013,237(3):837-847.
[27]贺英,邓磊,毛智慧,等.基于数码相机的玉米冠层SPAD遥感估算[J].中国农业科学,2018,51(15):66-77.HE Ying,DENG Lei,MAO Zhihui,et al. Remote sensing estimation of canopy SPAD value for maize based on digital camera[J]. Scientia Agricultura Sinica,2018,51(15):66-77.(in Chinese)
[28]李红军,李佳珍,雷玉平,等.无人机搭载数码相机航拍进行小麦、玉米氮素营养诊断研究[J].中国生态农业学报,2017,25(12):1832-1841.LI Hongjun,LI Jiazhen,LEI Yuping,et al. Diagnosis of nitrogen nutrition of winter wheat and summer corn using images from digital camera equipped on unmanned aerial vehicle[J]. Chinese Journal of Eco-Agriculture,2017,25(12):1832-1841.(in Chinese)
[29] LI Y,CHEN D,WALKER C N,et al. Estimating the nitrogen status of crops using a digital camera[J]. Field Crops Research,2010,118(3):221-227.
[30] KAWASHIMA S,NAKATANI M. An algorithm for estimating chlorophyll content in leaves using a video camera[J]. Annals of Botany(London),1998,81(1):49-54.
[31] WOEBBECKE D M,MEYER G E,VON BARGEN K,et al. Color indices for weed identification under various soil,residue,and lighting conditions[J]. Transactions of the ASAE,1995,38(1):259-269.
[32] WANG Y,WANG D,SHI P,et al. Estimating rice chlorophyll content and leaf nitrogen concentration with a digital still color camera under natural light[J]. Plant Methods,2014,10(1):36.
[2] CHEN Z Y,PENG Z S,YANG J,et al. A mathematical model for describing light-response curves in Nicotiana tabacum L.[J]. Photosynthetica,2011,49(3):467-471.
[3] FAN Z,QUAN Q,LI Y,et al. Exploring the best model for describing light-response curves in two Epimedium species[J].Technology and Health Care,2015,23(1):9-13.
[4] LAROCQUE G R. Coupling a detailed photosynthetic model with foliage distribution and light attenuation functions to compute daily gross photosynthesis in sugar maple(Acer saccharum Marsh.)stands[J]. Ecological Modelling,2002,148(3):213-232.
[5]王帅,韩晓日,战秀梅,等.不同氮肥水平下玉米光响应曲线模型的比较[J].植物营养与肥料学报,2014,20(6):1403-1412.WANG Shuai,HAN Xiaori,ZHAN Xiumei,et al. The comparative study on fitting light response curve model of photosynthesis of maize under different nitrogen fertilizer levels[J]. Journal of Plant Nutrition and Fertilizer,2014,20(6):1403-1412.(in Chinese)
[6] LAMPTEY S,LI L,XIE J,et al. Photosynthetic response of maize to nitrogen fertilization in the semiarid western loess plateau of China[J]. Crop Science,2017,57(5):2739-2752.
[7] LI G,ZHANG Z S,GAO H Y,et al. Effects of nitrogen on photosynthetic characteristics of leaves from two different stay-green corn(Zea mays L.)varieties at the grain-filling stage[J]. Canadian Journal of Plant Science,2017,92(4):671-680.
[8] ZHANG Y,WANG J,GONG S,et al. Nitrogen fertigation effect on photosynthesis,grain yield and water use efficiency of winter wheat[J]. Agricultural Water Management,2016,179:277-287.
[9] DING L,WANG K J,JIANG G M,et al. Effects of nitrogen deficiency on photosynthetic traits of maize hybrids released in different years[J]. Annals of Botany,2005,96(5):925-930.
[10] WALTER A,FINGER R,HUBER R,et al. Opinion:smart farming is key to developing sustainable agriculture[J].Proceedings of the National Academy of Sciences,2017,114(24):6148-6150.
[11]陈俊英,陈硕博,张智韬,等.无人机多光谱遥感反演花蕾期棉花光合参数研究[J/OL].农业机械学报,2018,49(10):230-239.CHEN Junying,CHEN Shuobo,ZHANG Zhitao,et al. Investigation on photosynthetic parameters of cotton during budding period by multi-spectral remote sensing of unmanned aerial vehicle[J/OL]. Transactions of the Chinese Society for Agricultural Machinery,2018,49(10):230-239. http:∥www. jcsam. org/jcsam/ch/reader/view_abstract. aspx? flag=1&file_no=20181026&journal_id=jcsam. DOI:10. 6041/j. issn. 1000-1298. 2018. 10. 026.(in Chinese)
[12] MOUALEU-NGANGUE D P,CHEN T W,STüTZEL H. A new method to estimate photosynthetic parameters through net assimilation rate intercellular space CO2concentration curve and chlorophyll fluorescence measurements[J]. New Phytologist,2016,213(3):1543.
[13] JIN P B,WANG Q,IIO A,et al. Retrieval of seasonal variation in photosynthetic capacity from multi-source vegetation indices[J]. Ecological Informatics,2012,7(1):7-18.
[14] GAMON J A,BOND B. Effects of irradiance and photosynthetic downregulation on the photochemical reflectance index in Douglas-fir and ponderosa pine[J]. Remote Sensing of Environment,2013,135:141-149.
[15]武海巍,于海业,田彦涛,等.基于核函数与可见光光谱的大豆植株群体净光合速率预测模型[J].光谱学与光谱分析,2016,36(6):1831-1836.WU Haiwei,YU Haiye,TIAN Yantao,et al. Prediction model on net photosynthetic rate of soybean plant groups based on kernel function and visible light spectrum[J]. Spectroscopy and Spectral Analysis,2016,36(6):1831-1836.(in Chinese)
[16]张雨晴,于海业,刘爽,等.玉米叶片净光合速率快速检测方法研究[J].农机化研究,2019,41(4):182-185.ZHANG Yuqing,YU Haiye,LIU Shuang,et al. Study on rapid detection method of net photosynthetic rate of maize leaves[J]. Journal of Agricultural Mechanization Research,2019,41(4):182-185.(in Chinese)
[17]程麒,黄春燕,王登伟,等.基于红外热图像的棉花冠层水分胁迫指数与光合特性的关系[J].棉花学报,2012,24(4):341-347.CHENG Qi, HUANG Chunyan, WANG Dengwei, et al. Correlation between cotton canopy CWSI and photosynthesis characteristics based on infrared thermography[J]. Cotton Science,2012,24(4):341-347.(in Chinese)
[18] YUAN Y,CHEN L,LI M,et al. Diagnosis of nitrogen nutrition of rice based on image processing of visible light[C]∥IEEE,2016:228-232.
[19] BARESEL J P,RISCHBECK P,HU Y,et al. Use of a digital camera as alternative method for non-destructive detection of the leaf chlorophyll content and the nitrogen nutrition status in wheat[J]. Computers and Electronics in Agriculture,2017,140:25-33.
[20] JIA B,HE H H B,MA F Y,et al. Use of a digital camera to monitor the growth and nitrogen status of cotton[J]. The Scientific World Journal,2014,2014:1-12.
[21]贾彪,马富裕.基于机器视觉的棉花氮素营养诊断系统设计与试验[J/OL].农业机械学报,2016,47(3):305-310.JIA Biao,MA Fuyu. Design and experiment of nitrogen nutrition diagnosis system of cotton based on machine vision[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2016,47(3):305-310. http:∥www. jcsam. org/jcsam/ch/reader/view_abstract. aspx? flag=1&file_no=20160343&journal_id=jcsam. DOI:10. 6041/j. issn. 1000-1298. 2016. 03.043.(in Chinese)
[22] YANG P,JIA B,ZHENG Z. Modeling cotton growth and nitrogen status using image analysis[J]. Agronomy Journal,2017,109(6):2630-2638.
[23] KOROBIICHUK I,LYSENKO V,OPRYSHKO O,et al. Crop monitoring for nitrogen nutrition level by digital camera[C]∥Conference on Automation,2018,743:595-603.
[24]牛庆林,冯海宽,杨贵军,等.基于无人机数码影像的玉米育种材料株高和LAI监测[J].农业工程学报,2018,34(5):73-82.NIU Qinglin,FENG Haikuan,YANG Guijun,et al. Monitoring plant height and leaf area index of maize breeding material based on UAV digital images[J]. Transactions of the CSAE,2018,34(5):73-82.(in Chinese)
[25] YE Z P,SUGGETT D J,ROBAKOWSKI P,et al. A mechanistic model for the photosynthesis-light response based on the photosynthetic electron transport of photosystem II in C3 and C4 species[J]. New Phytol,2013,199(1):110-120.
[26] YE Z P,ROBAKOWSKI P,SUGGETT D J. A mechanistic model for the light response of photosynthetic electron transport rate based on light harvesting properties of photosynthetic pigment molecules[J]. Planta,2013,237(3):837-847.
[27]贺英,邓磊,毛智慧,等.基于数码相机的玉米冠层SPAD遥感估算[J].中国农业科学,2018,51(15):66-77.HE Ying,DENG Lei,MAO Zhihui,et al. Remote sensing estimation of canopy SPAD value for maize based on digital camera[J]. Scientia Agricultura Sinica,2018,51(15):66-77.(in Chinese)
[28]李红军,李佳珍,雷玉平,等.无人机搭载数码相机航拍进行小麦、玉米氮素营养诊断研究[J].中国生态农业学报,2017,25(12):1832-1841.LI Hongjun,LI Jiazhen,LEI Yuping,et al. Diagnosis of nitrogen nutrition of winter wheat and summer corn using images from digital camera equipped on unmanned aerial vehicle[J]. Chinese Journal of Eco-Agriculture,2017,25(12):1832-1841.(in Chinese)
[29] LI Y,CHEN D,WALKER C N,et al. Estimating the nitrogen status of crops using a digital camera[J]. Field Crops Research,2010,118(3):221-227.
[30] KAWASHIMA S,NAKATANI M. An algorithm for estimating chlorophyll content in leaves using a video camera[J]. Annals of Botany(London),1998,81(1):49-54.
[31] WOEBBECKE D M,MEYER G E,VON BARGEN K,et al. Color indices for weed identification under various soil,residue,and lighting conditions[J]. Transactions of the ASAE,1995,38(1):259-269.
[32] WANG Y,WANG D,SHI P,et al. Estimating rice chlorophyll content and leaf nitrogen concentration with a digital still color camera under natural light[J]. Plant Methods,2014,10(1):36.