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2018 Vol.51, Issue 4 Preview Page
November 2018. pp. 471-481

Unmanned Aerial Vehicles (UAVs) are currently gaining a growing interest for agriculture applications due to its potential in precision agriculture such as the identification of weeds and crop production issues, diagnosing nutrient deficiencies, and the prediction of biomass and yield. This study reports on the development for estimating the growth parameters of red pepper. The red pepper field using UAV was studied, and image analysis technologies were studied to develop growth estimation model from acquired images. We used the normalized difference vegetation index (NDVI) that reflects the crop conditions, and vegetation fraction (VF) for 2 major cultivation regions from 2016 to 2017. For this study, UAV imagery was taken at Goesan and Jeongeup regions ten times from June to September during the red pepper growing season. Two plant growth parameters, plant height (P.H.) and fruit set (F.S.) were measured for ten plants per plot for each field campaign. A multiple linear regression model was carried out by using the NDVI and VF extracted from UAV image. As a result, in the case of the P.H. the coefficient of determination was 0.805 and the root mean squared error of measurement was 8.140 cm. And for the F.S., the coefficient of determination was 0.979 and the root mean squared error of measurement was 2.407. These results will also be useful for determining the UAV imagery necessary to estimate growth parameters of red pepper.

Growth estimation model of red pepper using UAV.

Regression equation RMSE R R2 R2adj D.W. P.H. = 438.923NDVIUAV + 121.841VFUAV ‒ 174.651NDVIUAVVFUAV ‒ 160.231 8.140 0.897 0.805 0.708 1.669 △F.S. = 1.994△P.H. ‒ 89.321△NDVIUAV ‒ 17.406 2.407 0.989 0.979 0.968 2.842

P.H.: Plant Height, F.S.: Fruit Set, △: Variation by growing stage.

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  • Publisher :Korean Society of Soil Science and Fertilizer
  • Publisher(Ko) :한국토양비료학회
  • Journal Title :Korean Journal of Soil Science and Fertilizer
  • Journal Title(Ko) :한국토양비료학회 학회지
  • Volume : 51
  • No :4
  • Pages :471-481
  • Received Date :2018. 09. 17
  • Accepted Date : 2018. 12. 05