Image-based leaf analysis for detection of soil water status in sweet corn production

Mohd Salleh, Ain Nadira (2019) Image-based leaf analysis for detection of soil water status in sweet corn production. [Project Paper] (Submitted)

Text lp FK 2019 75.pdf Download (1MB)

Abstract

The detection of water stress in the plant is very important in agricultural production. The field capacity (FC) and permanent wilting point (PWP) which are important in irrigation scheduling can be estimated by some of the soil physical especially moisture content and chemical properties. Leaf physiological method and distillation method also can be done in detecting the plant moisture content. But, these methods are practically destructive, tedious, and expensive because of the instrument and sensor, time-consuming and also need a longer time to analyze the data for any decision, which is unsuitable for real-time water status assessment. In this research, the soil moisture content (MC), soil water tension (SWT), and leaves image were collected using TDR 350, tensiometer, and Android camera respectively. A relation between MC and SWT is plotted and it gives a strong correlation which is R²=0.9636. This was actually the conventional method that we have in doing the irrigation scheduling. Therefore, an alternative approach has been done by doing the relation between soil MC and Dark Green Colour Index (DGCI). In this approach, the same MC as the conventional approach has been used in plotting the relation. The DGCI value was extracted using an algorithm that was developed in the MATLAB. Results indicate that DGCI value has a strong correlation with soil MC with R² of 0.9417. So, it shows that this method also can be used to detect water stress in sweet corn plant and it is much more easier which is only by using the Android camera, which is a device almost everyone would have it.

Item Type:	Project Paper
Faculty:	Faculty of Engineering
Depositing User:	Ms Siti Mariam Giman
Date Deposited:	17 Nov 2022 07:19
Last Modified:	17 Nov 2022 07:19
URI:	http://psaspb.upm.edu.my/id/eprint/542

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