Web camera as low cost multispectral sensor for quantification of chlorophyll in soybean leaves

Marcelinus A.S. Adhiwibawa; Yonathan E. Setiawan; Kestrilia R. Prilianti; Tatas H. P. Brotosudarmo

doi:10.1117/12.2080951

9 January 2015 Web camera as low cost multispectral sensor for quantification of chlorophyll in soybean leaves

Marcelinus A.S. Adhiwibawa, Yonathan E. Setiawan, Kestrilia R. Prilianti, Tatas H. P. Brotosudarmo

Proceedings Volume 9444, International Seminar on Photonics, Optics, and Its Applications (ISPhOA 2014); 94440G (2015) https://doi.org/10.1117/12.2080951
Event: International Seminar on Photonics, Optics, and Applications 2014, 2014, Sanur, Bali, Indonesia

Abstract

Soybeans is one of main crops in Indonesia but the demand for soybeans is not followed by an increase in soybeans national production. One of the production limitation factor is the availability of lush cultivation area for soybeans plantation. Indonesian farners are usually grow soybeans in marginal cultivation area that requires soybeans varieties which tolerant with environmental stress such as drought, nutrition limitation, pest, disease and many others. Chlorophyll content in leaf is one of plant health indicator that can be used to determine environmental stress tolerant soybean varieties. However, there are difficulties in soybeans breeding research due to the manual acquisition of data that are time consume and labour extensive. In this paper authors proposed automatic system of soybeans leaves area and chlorophyll quantification based on low cost multispectral sensor using web camera as an indicator of soybean plant tollerance to environmental stress particularlly drought stress. The system acquires the image of the plant that is placed in the acquisition box from the top of the plant. The image is segmented using NDVI (Normalized Difference Vegetation Index) from image and quantified to yield an average value of NDVI and leaf area. The proposed system showed that acquired NDVI value has a strong relationship with SPAD value with r-square value 0.70, while the leaf area prediction has error of 18.41%. Thus the automation system can quantify plant data with good result.

Citation Download Citation

Marcelinus A.S. Adhiwibawa, Yonathan E. Setiawan, Kestrilia R. Prilianti, and Tatas H. P. Brotosudarmo "Web camera as low cost multispectral sensor for quantification of chlorophyll in soybean leaves", Proc. SPIE 9444, International Seminar on Photonics, Optics, and Its Applications (ISPhOA 2014), 94440G (9 January 2015); https://doi.org/10.1117/12.2080951

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
6 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Image segmentation

Image processing

Image acquisition

Cameras

Multispectral imaging

Sensors

Imaging systems

Show All Keywords

Keywords/Phrases

Search In:

Publication Years