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Multi-Spectral Images Tetracam agriculture Digital Camera to Estimate Nitrogen and Grain Yield of Rice at difference Growth Stages

Several methods are available to monitor the nitrogen content of rice during its various growth stages. However, monitoring still requires a quick, simple, accurate and inexpensive technique that needs to be developed. In this study, Tetracam Agriculture Digital Camera was used to acquire high spa...

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Main Authors: Mohd Soom, Mohd Amin, Wayayok, Aimrun, Abdul Rahim, Anuar, Saberioon, Mohammadmehdi, Gholizadeh, Asa
Format: Article
Language:English
English
Published: 2013
Online Access:http://psasir.upm.edu.my/id/eprint/28461/1/Multi.pdf
http://psasir.upm.edu.my/id/eprint/28461/
http://www.researchgate.net/publication/236891883_Multispectral_Images_Tetracam_Agriculture_Digital_to_Estimate_Nitrogen_and_Grain_Yield_of_Rice_at_Different_Growth_Stages
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spelling my.upm.eprints.284612015-10-08T06:15:35Z http://psasir.upm.edu.my/id/eprint/28461/ Multi-Spectral Images Tetracam agriculture Digital Camera to Estimate Nitrogen and Grain Yield of Rice at difference Growth Stages Mohd Soom, Mohd Amin Wayayok, Aimrun Abdul Rahim, Anuar Saberioon, Mohammadmehdi Gholizadeh, Asa Several methods are available to monitor the nitrogen content of rice during its various growth stages. However, monitoring still requires a quick, simple, accurate and inexpensive technique that needs to be developed. In this study, Tetracam Agriculture Digital Camera was used to acquire high spatial and temporal resolution images to determine the status of N and predict the grain yield of rice (Oryza sativa L.). Twelve pots of rice were subjected to four different N treatments (0, 125, 175 and 250 kg ha-1). Three replicates were arranged in a randomized complete block design to determine the status of N and predict rice yield. The images were captured at different growth stages (i.e., tillering, panicle initiation, booting and heading stage) of rice in each pot. N and grain yield were significantly correlated with NDVI (R2 = 0.78) and GNDVI (R2 = 0.88), especially at the panicle initiation and booting stages, respectively. The study demonstrated the suitability of using the Tetracam images as a sensor for estimating chlorophyll content and N. Moreover, the findings showed that the images revealed their potential use in forecasting grain yield at different growth stages of rice. 2013 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/28461/1/Multi.pdf Mohd Soom, Mohd Amin and Wayayok, Aimrun and Abdul Rahim, Anuar and Saberioon, Mohammadmehdi and Gholizadeh, Asa (2013) Multi-Spectral Images Tetracam agriculture Digital Camera to Estimate Nitrogen and Grain Yield of Rice at difference Growth Stages. The Philippine agriculturist, 96 (1). pp. 108-112. ISSN 0031-7454 http://www.researchgate.net/publication/236891883_Multispectral_Images_Tetracam_Agriculture_Digital_to_Estimate_Nitrogen_and_Grain_Yield_of_Rice_at_Different_Growth_Stages English
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
English
description Several methods are available to monitor the nitrogen content of rice during its various growth stages. However, monitoring still requires a quick, simple, accurate and inexpensive technique that needs to be developed. In this study, Tetracam Agriculture Digital Camera was used to acquire high spatial and temporal resolution images to determine the status of N and predict the grain yield of rice (Oryza sativa L.). Twelve pots of rice were subjected to four different N treatments (0, 125, 175 and 250 kg ha-1). Three replicates were arranged in a randomized complete block design to determine the status of N and predict rice yield. The images were captured at different growth stages (i.e., tillering, panicle initiation, booting and heading stage) of rice in each pot. N and grain yield were significantly correlated with NDVI (R2 = 0.78) and GNDVI (R2 = 0.88), especially at the panicle initiation and booting stages, respectively. The study demonstrated the suitability of using the Tetracam images as a sensor for estimating chlorophyll content and N. Moreover, the findings showed that the images revealed their potential use in forecasting grain yield at different growth stages of rice.
format Article
author Mohd Soom, Mohd Amin
Wayayok, Aimrun
Abdul Rahim, Anuar
Saberioon, Mohammadmehdi
Gholizadeh, Asa
spellingShingle Mohd Soom, Mohd Amin
Wayayok, Aimrun
Abdul Rahim, Anuar
Saberioon, Mohammadmehdi
Gholizadeh, Asa
Multi-Spectral Images Tetracam agriculture Digital Camera to Estimate Nitrogen and Grain Yield of Rice at difference Growth Stages
author_facet Mohd Soom, Mohd Amin
Wayayok, Aimrun
Abdul Rahim, Anuar
Saberioon, Mohammadmehdi
Gholizadeh, Asa
author_sort Mohd Soom, Mohd Amin
title Multi-Spectral Images Tetracam agriculture Digital Camera to Estimate Nitrogen and Grain Yield of Rice at difference Growth Stages
title_short Multi-Spectral Images Tetracam agriculture Digital Camera to Estimate Nitrogen and Grain Yield of Rice at difference Growth Stages
title_full Multi-Spectral Images Tetracam agriculture Digital Camera to Estimate Nitrogen and Grain Yield of Rice at difference Growth Stages
title_fullStr Multi-Spectral Images Tetracam agriculture Digital Camera to Estimate Nitrogen and Grain Yield of Rice at difference Growth Stages
title_full_unstemmed Multi-Spectral Images Tetracam agriculture Digital Camera to Estimate Nitrogen and Grain Yield of Rice at difference Growth Stages
title_sort multi-spectral images tetracam agriculture digital camera to estimate nitrogen and grain yield of rice at difference growth stages
publishDate 2013
url http://psasir.upm.edu.my/id/eprint/28461/1/Multi.pdf
http://psasir.upm.edu.my/id/eprint/28461/
http://www.researchgate.net/publication/236891883_Multispectral_Images_Tetracam_Agriculture_Digital_to_Estimate_Nitrogen_and_Grain_Yield_of_Rice_at_Different_Growth_Stages
_version_ 1643829472403652608
score 13.211869

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