Browse > Article
http://dx.doi.org/10.7780/kjrs.2021.37.4.5

Analysis of Growth Characteristics Using Plant Height and NDVI of Four Waxy Corn Varieties Based on UAV Imagery  

Jeong, Chan-Hee (Department of Agricultural and Rural Engineering, Chungbuk National University)
Park, Jong-Hwa (Department of Agricultural and Rural Engineering, Chungbuk National University)
Publication Information
Korean Journal of Remote Sensing / v.37, no.4, 2021 , pp. 733-745 More about this Journal
Abstract
Although waxy corn varieties developed after the 1980s show differences depending on development stages and conditions, studies on the characteristics of waxy corn during the growth stage are rare. The subject of this study was a field survey and unmanned aerial vehicle (UAV) image acquisition of four waxy corn varieties cultivated in Idam-ri, Gammul-myeon, Goesan-gun, Korea. The study was conducted in four stages at intervals of two weeks after planting in 2019. The growth characteristics of each of the four varieties were analyzed using growth curves obtained based on field survey and UAV imagery data. The characteristics of each growth stage of the four varieties of corn, as assessed using normalized difference vegetation index (NDVI) and plant height (P.H.) values, were as follows. The growth model was identified as a model in which three-parameter logistic (3PL) curves reflect the growth characteristics of corn well. In particular, it was found that the variations in growth rate shown by P.H. and NDVI values clearly explain the differences between corn varieties. Among the four cultivars, growth and development first occurred at the early vegetative stage in Daehakchal, followed by Mibaek 2, Miheukchal, and finally Hwanggeummatchal. The variationsin P.H. and NDVI were achieved quickly and earlier in Daehakchal, followed by Mibaek 2, Hwanggeummatchal, and Miheukchal. It was confirmed that these results reflected the characteristics of the fast white-type varieties, while the black-type varieties were delayed, as in a previous study. These results reflect the resistance to lodging that affects the cultivation environment and the response characteristics to nutrients and moisture. It was confirmed that UAV accurately provides growth information that is very useful for analyzing the growth characteristics of each corn variety.
Keywords
corn; growth curve; varieties; 3PL; plant height;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 Lee, D.H., H.J. Kim, and J.H. Park, 2021. UAV, a Farm Map, and Machine Learning Technology Convergence Classification Method of a Corn Cultivation, Agronomy, 11(8): 1554.   DOI
2 Han, L., G.J. Yang, H. Yang, B. Xu, Z.H. Li, and X.D. Yang, 2018. Clustering Field-Based Maize Phenotyping of Plant-Height Growth and Canopy Spectral Dynamics Using a UAV Remote-Sensing Approach, Frontiers in Plant Science, 9: 1638.   DOI
3 Kim, M.J., J.E. Lee, J.T. Kim, G.H. Jung, Y.Y. Lee, S.L. Kim, and Y.U. Kwon, 2014. Changesin ear and kernel characteristics of waxy corn during grain filling stage by double cropping, Korean Journal of Crop Science, 59(1): 73-82 (in Korean with English abstract).   DOI
4 KMA(Korea Meteorological Administration), 2019. Automatic Weather System data, https://data.kma.go.kr/data/grnd/selectAwsRltmList.do?pgmNo=56, Accessed on Jun. 26, 2021 (in Korean).
5 Niu, Y.X., L.Y. Zhang, H.H. Zhang, W.T. Han, and X.S. Peng, 2019. Estimating Above-Ground Biomass of Maize Using Features Derived from UAV-Based RGB Imagery, Remote Sensing, 11(11): 1261.   DOI
6 Lee, J.S., B.Y. Son, S.H. Shin, J.T. Kim, H.H. Bae, S.B. Baek, T.W. Jung, S.K. Kim, and Y.U. Kwon, 2018. 'Hwangmichal', a Yellow Waxy Corn F1 Hybrid with High Carotenoid Content, Korean Society of Breeding Science, 50(4): 510-515 (in Korean with English abstract).   DOI
7 MAFRA(Ministry of Agriculture Food and Rural Affairs), 2017. Agrix, https://agis.epis.or.kr/ASD/main/intro.do#, Accessed on Jun. 26, 2021 (in Korean).
8 NICS(National Institute of Crop Science), 2019. Guide book of major up-land crop cultivaries, National Institute of Crop Science, RDA., Jeonju, KR (in Korean).
9 Oliver, F.R., 1964. Methods of estimating the logistic growth function, Journal of the Royal Statistical Society: Series C (Applied Statistics), 13(2): 57-66.   DOI
10 Lee, D.H., H.S. Shin, and J.H. Park, 2020. Developing a p-NDVI Map for Highland Kimchi Cabbage Using Spectral Information from UAVs and a Field Spectral Radiometer, Agronomy, 10(11): 1798.   DOI
11 Vandamme, L.K.J., I.H.J.T. de Hingh, J. Fonseca, and P.R.F. Rocha, 2021. Similarities between pandemics and cancer in growth and risk models, Scientific Reports, 11(1): 1-10.   DOI
12 Park, K.J., J.Y. Park, S.H. Ryu, B.D. Goh, J.S. Seo, H.K. Min, T.W.Jung, C.S. Huh, and I.M. Ryu, 2007a. A new waxy corn hybrid cultivar," Mibaek 2" with good eating quality and lodging resistance, Korean Journal of Breeding Science, 39(1): 108-109 (in Korean with English abstract).
13 Park, K.J., S.H. Ryu, H.K. Min, J.S. Seo, J.Y. Park, B.D. Goh, J.S. Jang, and N.S. Kim, 2007b. A new black waxy corn hybrid cultivar, "Miheugchal" with good eating quality and high yield, Korean Journal of Breeding Science, 39(1): 106-107 (in Korean with English abstract).
14 Pienaar, L.V. and K.J. Turnbull, 01973. The Chapman-Richards generalization of Von Bertalanffy's growth model for basal area growth and yield in even-aged stands, Forest Science, 19(1): 2-22.   DOI
15 Ransom, J. and G. Endres, 2020. Corn growth and management: Quick Guide, North Dakota State University, Fargo, ND, USA.
16 Richards, F.J., 1959. A Flexible Growth Function for Empirical Use, Journal of experimental Botany, 10(2): 290-301.   DOI
17 Werker, A.R. and K.W. Jaggard, 1997. Modelling asymmetrical growth curves that rise and then fall: Applications to foliage dynamics of sugar beet(Beta vulgarisL.), Annals of Botany, 79(6): 657-665.   DOI
18 Zeide, B., 1993.Analysis of Growth Equations, Forest Science, 39(3): 594-616.   DOI
19 Zhou, L.F., X.H. Gu, S. Cheng, G.J. Yang, M.Y. Shu, and Q. Sun, 2020. Analysis of Plant Height Changes of Lodged Maize Using UAV-LiDAR Data, Agriculture, 10(5): 146.   DOI
20 Rouse, J.W. ,R.H. Haas, J.A. Schell, and D.W. Deering, 1974. Monitoring vegetation systems in the Great Plains with ERTS, Third Earth Resources Technology Satellite-1 Symposium- Volume I: Technical Presentations, NASASP-351, National Aeronautics and Space Administration, Washington D.C., USA, pp. 309-317.
21 Calka, B. and E. Bielecka, 2020. GHS-POPAccuracy Assessment: Poland and Portugal Case Study, Remote Sensing, 12(7): 1105.   DOI
22 Ayiomamitis, A., 1986. Logistic Curve Fitting and Parameter-EstimationUsingNonlinearNoniterative Least-Squares Regression-Analysis, Computers and Biomedical Research, 19(2): 142-150.   DOI
23 Baek, S.B., B.Y. Son, J.T. Kim, H.H. Bae, Y.S. Go, and S.L. Kim, 2020. Changes and Prospects in the Development of Corn Varieties in Korea, Korean Journal of Breeding Science, 52(S): 93-102 (in Korean with English abstract).   DOI
24 Birch, C.P.D. and M.W. Shaw, 1997. When can reduced doses and pesticide mixtures delay the build-up of pesticide resistance? Amathematical model, Journal of Applied Ecology, 34(4): 1032-1042.   DOI
25 Cartwright, R.D.,L. Espinoza, D. Gardisser, G. Huitink, T.L. Kirkpatrick, P. McLeod, J. Ross, B. Scott, K. Smith, G. Strudebaker, P. Tacker, D.O. TeBeest, E. Vories, and T. Windham, 2021. Corn Production Handbook, Cooperative Extension Service University of Arkansas, Little Rock, AR, USA.
26 FAO(Food and Agriculture Organization of the united nations), 2021. FAOSTAT, http://www.fao.org/faostat/en/#data/QC,Accessed on Jun. 10, 2021.