基于数字图像技术的冬油菜氮素营养诊断

doi:10.3864/j.issn.0578-1752.2015.19.010

Abstract

Abstract: 【Objective】 In order to provide a scientific basis for digital image processing technique in nitrogen nondestructive diagnosis of winter rapeseed, a field experiment was carried out to explore the feasibility of digital image processing technique in nitrogen nondestructive diagnosis, determine the best digital parameter and regression equation. 【Method】 A field experiment was conducted with different nitrogen application rates (0, 90, 180, 270 and 360 kg·hm^-2). The pictures of winter rapeseed canopy were obtained with a digital camera, meanwhile, the conventional nitrogen diagnosis parameters of aboveground biomass, nitrogen concentration in leaf and leaf chlorophyll content at six-leaf period, ten-leaf period, bud period and blooming period, were determined and the correlations were analyzed. 【Result】 The red color intensity (R), normalized redness intensity (NRI) and the ratio of greenness and blueness intensity (G/B) had significant inverse correlations with the conventional N diagnosis parameters. But green color intensity (G), blue color intensity (B), the ratio of greenness and redness intensity (G/R), the ratio of blueness and redness intensity (B/R), the normalized greenness intensity (NGI) and the normalized blueness intensity (NBI) showed a significant positive correlation. Compared with other digital index, the normalized redness intensity (NRI) showed a prominently and very prominently inverse relationship with conventional N parameters and the regression equation with N application rate, aboveground biomass, leaf N concentration, chlorophyll in leaf, N uptake and N nutrition index is y(t·hm^-2)=-8.003x+2.706, y(t·hm^-2)=-106.072x+38.200, y(g·kg^-1)=-692.99x+261.84, y(mg·g^-1)=-12.750x+5.665, y(kg·hm^-2)=-4087.416x+1414.274 and y=-27.198x+9.812, the correlation values (R²) is 0.917^**, 0.746^** and 0.953^** between measured and estimated leaf N concentration, chlorophyll in leaf and NNI, RMSE and RE were 0.821, 26.32%, 0.330, 28.57% and 0.228, 28.39%, respectively. 【Conclusion】Digital image processing technique can be used in nitrogen nondestructive diagnosis of winter rapeseed, the stage before bud period is crucial period with NRI as the index for the N nitrogen diagnosis using digital image processing technique, and NRI is the best diagnosis index with linear regression equation.

Key words: winter rapeseed, digital image, nitrogen, nutritional diagnosis, equation model

WEI Quan-quan, LI Lan-tao, REN Tao, WANG Zhen, WANG Shao-hua, LI Xiao-kun, CONG Ri-huan, LU Jian-wei. Diagnosing Nitrogen Nutrition Status of Winter Rapeseed via Digital Image Processing Technique[J].Scientia Agricultura Sinica, 2015, 48(19): 3877-3886.

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