Authors: Grianggai Samseemoung, Peeyush Soni and Chaiyan Sirikul
 
Journal: Agriculture 2017, 7(10), 87
 
Publisher: MDPI
 
Abstract
 
Through processing images taken from wireless WebCAMs on the low altitude remote sensing (LARS) platform, this research monitored crop growth, pest, and disease information in a dendrobium orchid’s plantation. Vegetetative indices were derived for distinguishing different stages of crop growth, and the infestation density of pests and diseases. Image data was processed through an algorithm created in MATLAB® (The MathWorks, Inc., Natick, USA). Corresponding to the orchid’s growth stage and its infestation density, varying levels of fertilizer and chemical injections were administered.
 
The acquired LARS images from wireless WebCAMs were positioned using geo-referencing, and eventually processed to estimate vegetative-indices (Red = 650 nm and NIR = 800 nm band center). Good correlations and a clear cluster range were obtained in characteristic plots of the normalized difference vegetation index (NDVI) and the green normalized difference vegetation index (GNDVI) against chlorophyll content. The coefficient of determination, the chlorophyll content values (μmol m−2) showed significant differences among clusters for healthy orchids (R2 = 0.985–0.992), and for infested orchids (R2 = 0.984–0.998).
 
The WebCAM application, while being inexpensive, provided acceptable inputs for image processing. The LARS platform gave its best performance at an altitude of 1.2 m above canopy. The image processing software based on LARS images provided satisfactory results as compared with manual measurements.
 

Photo: Experimental set up and field preparation, (a) Greenhouse; (b) Orchid plants; (c) Minolta SPAD 502 Meter (Konica Minolta Sensing Inc., Osaka, Japan) measuring plant leaves; (d) Calibration of volume flow rate control; (e) SKR 1800 (Skye Instruments, Ltd., Powys, UK) illumination sensor. (credits: Grianggai Samseemoung, Peeyush Soni and Chaiyan Sirikul)

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
 
 

Comments

No comments to display.