| 基于光场相机的大豆冠层叶面积无损测量方法研究 |
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| 引用本文： | 顾正敏,李臻峰,宋飞虎,张君生,庄为.基于光场相机的大豆冠层叶面积无损测量方法研究[J].浙江农业学报,2018,30(12):2144. |
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| 作者姓名： | 顾正敏 李臻峰 宋飞虎 张君生 庄为 |
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| 作者单位： | 1.江南大学 机械工程学院,江苏 无锡 214122;2.江苏省食品先进制造装备技术重点实验室,江苏 无锡 214122 |
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| 基金项目： | 国家自然科学基金(51406068);江苏省政策引导类计划(产学研合作)——前瞻性联合研究项目(BY2015019-16) |
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| 摘 要： | 大豆上、中、下冠层叶面积分布是大豆植株株型状况评价、产量预测的重要依据,而传统上、中、下冠层叶面积测量方法采用大田切片法,该方法过程繁琐,且会对叶片造成伤害。针对这一问题,引入光场相机重聚焦技术分别得到聚焦在上、中、下叶片的重聚焦图像,通过图像处理技术提取聚焦平面的叶片,去掉离焦平面的叶片,分别得到上、中、下层的投影面积。选用开花期103盆宏秋品种大豆植株作为校正集,根据光场相机的标定计算各冠层叶片的校正系数,获得修正后的各冠层叶片投影面积。建立大豆植株各冠层投影面积和真实叶面积的回归模型,并选20盆作为预测集来验证各回归模型。研究发现:上层叶面积模型的决定系数为0.945,预测集的最大误差为4.48%,均方根误差为4.376;中层叶面积模型的决定系数为0.796,预测集的最大误差为13.62%,均方根误差为7.273;下层叶面积模型的决定系数为0.914,预测集的最大误差为8.63%,均方根误差为1.529。上层和下层叶面积测量模型相关性高,由于上层叶片的遮挡,中层叶面积模型相关性略低。
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| 关 键 词： | 冠层叶面积 光场重聚焦 大豆植株 图像处理 回归模型 |
| 收稿时间： | 2018-02-10 |
Investigation of measurement method of soybean canopy leaf area based on light field camera |
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| GU Zhengmin,LI Zhenfeng,SONG Feihu,ZHANG Junsheng,ZHUANG Wei.Investigation of measurement method of soybean canopy leaf area based on light field camera[J].Acta Agriculturae Zhejiangensis,2018,30(12):2144. |
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| Authors: | GU Zhengmin LI Zhenfeng SONG Feihu ZHANG Junsheng ZHUANG Wei |
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| Institution: | 1. School of Mechanical Engineering, Jiangnan University, Wuxi 214122, China;
2. Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment and Technology, Wuxi 214122, China |
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| Abstract: | Soybean upper, middle and lower canopy leaf area distribution is an important basis for soybean plant type status assessment and yield prediction. Traditionally, the field slicing method was used to measure the upper, middle and lower canopy leaf area, which was cumbersome and could cause certain harm to the leaves. In order to solve this problem, the refocusing technology of light field camera was introduced to obtain the refocusing images focused on the upper, middle and lower leaves respectively. The focal plane blades were extracted by image processing technology and the leaves of the defocusing planes were removed to get the upper, middle, lower projection area respectively. In this study, 103 pots of Hongqiu variety soybean at flowering stage were selected as calibration set, and the calibration coefficients of each canopy leaf were calculated to obtain the revised projected area of each canopy leaf according to the calibration of light field camera. A regression model was established for each canopy projection area and the true leaf area of soybean plants, and 20 pots were selected as prediction sets to verify each regression model. The study found that the coefficient of determination of upper leaf area model was 0.945, the maximum error of prediction set was 4.48%, and the root mean square error was 4.376. The determination coefficient of the middle leaf area model was 0.796, the maximum error of the prediction set was 13.62%, and the root mean square error was 7.273. The lower leaf area model had a coefficient of determination of 0.914, the maximum error of the prediction set was 8.63%, and the root mean square error was 1.529. The correlation of the upper and lower leaf area measurements was high, and the correlation of the mid-leaf area model was lower due to the occlusion of the upper leaf. |
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| Keywords: | canopy leaf area light field refocusing soybean image processing regression model |
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