| 采用热红外和可见光图像无损测定棉花苗期叶面积 |
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| 引用本文： | 陈家乐,吴沣槭,韩迎春,李小飞,王占彪,冯璐,王国平,雷亚平,杨北方,辛明华,李亚兵.采用热红外和可见光图像无损测定棉花苗期叶面积[J].农业工程学报,2022,38(15):179-185. |
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| 作者姓名： | 陈家乐 吴沣槭 韩迎春 李小飞 王占彪 冯璐 王国平 雷亚平 杨北方 辛明华 李亚兵 |
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| 作者单位： | 1. 中国农业科学院棉花研究所棉花生物学国家重点实验室，安阳 455000;;2. 郑州大学农学院棉花生物学国家重点实验室郑州科研中心，郑州 450000;;1. 中国农业科学院棉花研究所棉花生物学国家重点实验室，安阳 455000; 2. 郑州大学农学院棉花生物学国家重点实验室郑州科研中心，郑州 450000; |
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| 基金项目： | 国家自然科学基金资助项目（No.31601264） |
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| 摘 要： | 叶面积是影响植物光合作用、蒸腾作用、呼吸作用及产量形成的重要形态指标之一，为实现作物叶面积准确、稳定和无损化测量，该研究基于红外线成像设备，提供了一种利用热红外和可见光图像测定棉花叶片面积的方法。以苗期棉花作为研究对象，通过红外成像相机T660获取棉花的热红外和可见光波段的图像，分别使用GrabCut算法和Hough圆检测提取红外图像中叶片和可见光图像中已知实际面积的圆状参照物（五角硬币）的像素面积，进而根据叶片区域和圆状参照物区域的像素倍数关系计算棉花的真实叶面积，将通过该研究所提方法计算的叶面积结果与传统的剪纸称重法、Image Pro Plus软件图像法进行皮尔逊相关性分析，检验该方法的可行性。分析表明，基于所提方法的测量值与剪纸称重法、Image Pro Plus软件图像法的结果之间均存在显著的线性相关关系（P<0.01）（相关系数分别为0.992,0.996）。3种方法对5盆棉花进行8次测量，结果显示，该研究所提方法测量值的平均变异系数为0.782%，在测量工作中表现稳定，为快速获取棉花苗期叶面积提供了一种准确稳健的理论方法。
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| 关 键 词： | 叶面积 棉花 热红外图像 GrabCut Hough圆检测 |
| 收稿时间： | 2019/9/18 0:00:00 |
| 修稿时间： | 2022/3/7 0:00:00 |
Nondestructive measurement of cotton leaf area at the seedling stage based on thermal infrared and visible images |
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| Chen Jiale,Wu Fengqi,Han Yingchun,Li Xiaofei,Wang Zhanbiao,Feng Lu,Wang Guoping,Lei Yaping,Yang Beifang,Xin Minghu,Li Yabing.Nondestructive measurement of cotton leaf area at the seedling stage based on thermal infrared and visible images[J].Transactions of the Chinese Society of Agricultural Engineering,2022,38(15):179-185. |
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| Authors: | Chen Jiale Wu Fengqi Han Yingchun Li Xiaofei Wang Zhanbiao Feng Lu Wang Guoping Lei Yaping Yang Beifang Xin Minghu Li Yabing |
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| Institution: | 1. State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Henan Anyang 455000, China;;2. Zhengzhou Research Base, State Key Laboratory of Cotton Biology, School of Agricultural Sciences, Zhengzhou University, Zhengzhou 450000, China;;1. State Key Laboratory of Cotton Biology, Institute of Cotton Research of Chinese Academy of Agricultural Sciences, Henan Anyang 455000, China; 2. Zhengzhou Research Base, State Key Laboratory of Cotton Biology, School of Agricultural Sciences, Zhengzhou University, Zhengzhou 450000, China; |
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| Abstract: | A leaf area has been one of the most important indicators of photosynthesis, transpiration, respiration, and yield components of plants. The physiological and ecological indicators can dominate plant growth, fruit development, and quality formation. The purpose of this study is to measure the leaf area of cotton by the thermal infrared and visible images. An accurate, convenient, stable, and nondestructive approach was also proposed for the early leaf area measurement in physiological and ecological research. The experimental cotton was cultivated in the greenhouse of the East Field Experimental Base of Cotton Research Institute, Chinese Academy of Agricultural Sciences from July to September 2021 (On July 20th, the cotton seeds were soaked in the hydrogen peroxide for two hours, and then sown in the pots, one cotton seedling per pot, totally 15 pots). When the cotton was in the seedling stage (August 25th, the number of euphylla was 1-4), the infrared imager T660 was used to take photos at 14:00 pm, where the radiation difference among soil, leaf and shadow reached the outstanding effect. Five pots of cotton seedlings were randomly selected to capture the images. Both thermal infrared and visible images were obtained eight from each pot. Taken together, 16 images were obtained from each cotton pot. A hand-held standard board with a circular reference was used to hold the inclined leaves in each capture, in order to reduce the distortion of cotton leaves in the image. Hough circle detection was used to extract the region of reference substance in the visible image. The GrabCut was used to extract the leaf regions in the thermal infrared image. The capture and thermal infrared images were firstly adjusted by the FLIR tools. After that, the pixel values of leaf regions of the two images were assigned the weights and then superimposed. The color filling was carried out using a 4-connected field, in order to eliminate the isolated pixels near the leaf regions. The pixel value of the leaf area was defined after the color filled the connected area. The leaf regions were converted into white (pixel value is 1, 1, 1]), whereas, the rest was converted into black (0, 0, 0]), according to the pixel values of the leaves. The following step was to convert the 3-channel image with the leaf information into a single-channel image. Then, the contour was extracted from the reference substance and the leaf regions. The leaf area was then calculated, according to the multiple relationships of the number of the pixels. The study-cutting weighing and Image Pro Plus image were used to measure the five pots of cotton seedlings for eight times after capture. The correlation analysis showed that there was a significant linear correlation (r1=0.992, P1<0.01; r2=0.996, P2<0.01). The difference between the method proposed in this paper, weighing, and Image Pro Plus method are all in the 0.67%-6.73% range. Additionally, the higher stability of the measurement was achieved, where the average coefficient of variation was 0.782%. Therefore, an accurate, stable, rapid, and nondestructive method can provide a promising convenience for physiological and ecological research in the early leaf area measurement. |
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| Keywords: | leaf area cotton thermal infrared image GrabCut Hough circle detection |
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