基于三维机器视觉的植物叶片萎蔫预测模型
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国家自然科学基金资助项目(31371537)、农业科技成果转化资金资助项目(2012GB23600634)和国际科技合作专项资助项目(2010DFA34670)


Prediction Model of Plant Leaf Wilting Using 3-D Machine Vision
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    摘要:

    采用基于激光斜射测距原理的三维扫描装置实时获取植株三维图像,从中提取叶面卷曲统计指数、分形维数和二维傅里叶变换直流分量作为萎蔫指数来定量研究植物的萎蔫程度,采用西葫芦、葫芦、南瓜及秋葵4种植物的嫩叶期体态变化检验了3种萎蔫指数与萎蔫程度的相关性,结果表明:3种萎蔫指数与萎蔫程度均具有较好的相关性,相关系数都达到了0.82以上。在此基础上,运用SPSS软件建立了3种萎蔫指数与环境饱和水气压差VPD及光合有效辐射的多元线性回归统计模型。

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    Wilting of plants appears when the water supply of plants is insufficient. Quantitative identification of wilting phenomena of plant stems, leaves and other parts is of important practical significance to improve agricultural production and efficient water irrigation. A scanning device based on the principle of laser ranging oblique is used to obtain real time 3-D plant images. Then leaf curl statistical index, fractal dimension and the DC component of two-dimensional Fourier spectrum were extracted as wilting index to quantify the degree of wilting plants. Three kinds of wilting indexes were tested on zucchini, gourds, pumpkins and okra leaves to find out the correlations with wilting extent. The experiments show that each wilting index had a good correlation with wilting extent (0.82 or more are reached). On this basis, a multiple linear regression model of three kinds of wilting indexes, vapor pressure deficit (VPD) and photosynthetically active radiation (PAR) was built.

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张 新,赵燕东,郑力嘉,Martin Kraft.基于三维机器视觉的植物叶片萎蔫预测模型[J].农业机械学报,2014,45(9):260-267. Zhang Xin, Zhao Yandong, Zheng Lijia, Martin Kraft. Prediction Model of Plant Leaf Wilting Using 3-D Machine Vision[J]. Transactions of the Chinese Society for Agricultural Machinery,2014,45(9):260-267.

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  • 收稿日期:2013-07-03
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  • 在线发布日期: 2014-09-10
  • 出版日期: 2014-09-10