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| Determination of canopy leaf area index of maize based on smart phone |
| YIN Xiaoai1, YANG Xiuchao1, HOU Rui1,2, ZHAO Longshan1,2,3, ZHANG Jinxin3 |
1. College of Forestry, Guizhou University, 550025, Guiyang, China;
2. Research Centre for Soil Erosion & Eco-Restoration Sciences, Guizhou University, 550025, Guiyang, China;
3. Research Institute of Forestry, Chinese Academy of Forestry, 100091, Beijing, China |
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Abstract [Background] Crop canopy plays an important role on rainfall distribution and soil and water conservation, and leaf area index (LAI) is a common quantitative index of crop canopy. There are two kinds of direct method and indirect method in the current measurement of plant leaf area. The direct method is time consuming and has poor repeatability, while the indirect method is complicated and requires expensive equipment and is not convenient to be carried in field. Based on the existing problems of crop canopy measuring method, this study aims to explore a fast measurement method of maize LAI using the mobile phone. It provides scientific and technological conditions for further improving the method of determining canopy parameters by using smart phones and developing an effective mobile APP for canopy LAI measurement.[Methods] In this study, according to the characteristics of maize canopy, PVC pipe and simulated leaves were used to simulate the canopy model of maize plants at different growth stages (elongation period, small trumpet period, big trumpet period, tasseling period and mature period). The canopy LAI of maize was measured through the processes of mobile phone image acquisition, canopy shadow area extraction and correction, model construction and verification. The experiment included 3 solar altitude (30°, 60° and 90°). The number of maize plants was 1, 2, 3, 6 and 9 plants respectively to represent different sampling areas. The plant row spacing was 30 cm×50 cm.[Results] There was a significant correlation between the number of planted plants and the projected canopy area (P<0.05). There was no significant relationship between the solar altitude and the projected area taken by mobile phones (P>0.05), the canopy projection areas (SM) extracted from mobile phone images was taken as the independent variable, and the canopy projection area (SC) drawn on coordinate paper was taken as the dependent variable. The optimal fitting equation of the two was as follows:SC=-0.009 6S2M+171.38SM-3 612.3 (R2=0.98). The fitting degree of this equation was high and reached significant level (P<0.05). There was a power function relationship between the projected area (SC) drawn by coordinate paper and the actual area (Sleaf), and the function relationship was as follows:Sleaf=0.141 2S0.985C(R2=0.97), P<0.05, the regression equation had a high degree of fitting.[Conculsions] The LAI measurement method designed in this paper is feasible, that is, the canopy LAI could be accurately determined by extracting the shadow area taken by smart phones (R2=0.96). This method simplifies the canopy area measurement of maize and provides a convenient solution for the monitoring of canopy parameters in the field.
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Received: 26 October 2020
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