Article citationsMore>>

Martin, K.L., Anderson, R.H., Arnall, D.B., Brixcy, K.D., Casillas, M.A., Chung, B., Dobey, B.C., Kamenidou, S.K., Kariuki, S.K., Katsalirou, E.E., Morris, J.C., Moss, J.Q., Rohla, C.T., Sudbury, B.J., Tubana, B.S. and Raun, W.R. (2005) Mid-Season Prediction of Wheat-Grain Yield Potential Using Plant, Soil, and Sensor Measurements. Journal of Plant Nutrition, 29, 873-897.
https://doi.org/10.1080/01904160600649187

has been cited by the following article:

• TITLE: Winter Wheat Crop Height Estimation Using Small Unmanned Aerial System (sUAS)

  AUTHORS: Marife Kung Villareal, Alejandro Fernandez Tongco, Joe Mari J. Maja

  KEYWORDS: Small Unmanned Aerial Vehicle, Plant Height, DSM, DEM

  JOURNAL NAME: Agricultural Sciences, Vol.11 No.4, April 1, 2020

  ABSTRACT: Deploying the small Unmanned Aerial System (sUAS) for data collection of high-resolution images is a big potential in determining crop physiological parameters. The advantage of using sUAS technology is the ability to acquire a high-resolution orthophoto and a 3D Model which is highly suitable for plant height monitoring. Plant height estimation has a big impact in the growth and development of wheat because it is essential for obtaining biomass, which is a factor for higher crop yield. Plant height is an indicator of high yield estimation and it correlates to biomass, nitrogen content, and other plant growth parameters. The study is aimed to determine an accurate height of wheat using the sUAS generated Digital Surface Model (DSM). A high-resolution imagery between 1.0 - 1.2 cm/pixel was obtained from a 35 m altitude with area coverage of 1.01 hectares. The DSM and orthophoto were generated from the sUAS, and the computed wheat heights were derived from the difference of Digital Elevation Model (DEM) and DSM data. Field measurement using steel tape was done for ground truth. The sUAS-based wheat height data were evaluated using the ground truth of 66 wheat-rows by applying correlation and linear regression analysis. Datasets were collected from three different flight campaigns (March 2018-May 2018). The sUAS-based wheat height data were significantly correlated, obtaining the result of R2 = 0.988, R2 = 0.996 and R2 = 0.944 for the month of March, April and May 2018 respectively. The significance of linear regression results was also validated by computing for the p-value. The p-value results were 0.00064, 0.0000824 and 0.0058 respectively. The main concern is the lodging of winter wheat, especially during the month of April which affects the recording of the plant’s height. Because some of the wheat plants are now lying on the ground, so measurements are done vertically. Nonetheless, the results showed that sUAS technology is highly suitable for many agricultural applications.