Nutrient deficiency detection in maize (Zea mays L.) leaves using image processing / Nurul Shafekah Kassim

Maize is one of the world's leading food supplies. When maize becomes more important, the crop's production must continue to reproduce. Maize is an active feeder, so as the plant grows, the soils need to be adequately supplied with nutrients. Plants must be in deep green color to indicate...

Full description

Bibliographic Details
Main Author: Kassim, Nurul Shafekah
Format: Thesis
Language:English
Published: 2020
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/31511/1/31511.pdf
_version_ 1825737391395045376
author Kassim, Nurul Shafekah
author_facet Kassim, Nurul Shafekah
author_sort Kassim, Nurul Shafekah
collection UITM
description Maize is one of the world's leading food supplies. When maize becomes more important, the crop's production must continue to reproduce. Maize is an active feeder, so as the plant grows, the soils need to be adequately supplied with nutrients. Plants must be in deep green color to indicate the adequate nutrient. This project is developed to solve the main problem of plant tissue laboratory testing to detect nutrient deficiencies that consume a lot of time. The purpose of this study was to help agriculturist, farmers and researchers to identify the type of maize nutrient deficiency. This Maize Leaves Nutrient Deficiency Detection uses image processing techniques to determine the type of nutrient deficiency that occurs on the plant leaf. In order to increase the accuracy model, random forest technique was used as a classifier and some combination of the texture of feature extraction. This application was checked for accuracy after analysing the percentage of the overall application. The result shows that random forest can produce accurate results with 78.35 percent of accuracy.
first_indexed 2024-03-06T02:17:21Z
format Thesis
id oai:ir.uitm.edu.my:31511
institution Universiti Teknologi MARA
language English
last_indexed 2024-03-06T02:17:21Z
publishDate 2020
record_format dspace
spelling oai:ir.uitm.edu.my:315112020-06-26T04:17:25Z https://ir.uitm.edu.my/id/eprint/31511/ Nutrient deficiency detection in maize (Zea mays L.) leaves using image processing / Nurul Shafekah Kassim Kassim, Nurul Shafekah Data processing. Computer applications Electronic Computers. Computer Science S Agriculture (General) Maize is one of the world's leading food supplies. When maize becomes more important, the crop's production must continue to reproduce. Maize is an active feeder, so as the plant grows, the soils need to be adequately supplied with nutrients. Plants must be in deep green color to indicate the adequate nutrient. This project is developed to solve the main problem of plant tissue laboratory testing to detect nutrient deficiencies that consume a lot of time. The purpose of this study was to help agriculturist, farmers and researchers to identify the type of maize nutrient deficiency. This Maize Leaves Nutrient Deficiency Detection uses image processing techniques to determine the type of nutrient deficiency that occurs on the plant leaf. In order to increase the accuracy model, random forest technique was used as a classifier and some combination of the texture of feature extraction. This application was checked for accuracy after analysing the percentage of the overall application. The result shows that random forest can produce accurate results with 78.35 percent of accuracy. 2020 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/31511/1/31511.pdf Nutrient deficiency detection in maize (Zea mays L.) leaves using image processing / Nurul Shafekah Kassim. (2020) Degree thesis, thesis, Universiti Teknologi MARA, Cawangan Melaka. <http://terminalib.uitm.edu.my/31511.pdf>
spellingShingle Data processing. Computer applications
Electronic Computers. Computer Science
S Agriculture (General)
Kassim, Nurul Shafekah
Nutrient deficiency detection in maize (Zea mays L.) leaves using image processing / Nurul Shafekah Kassim
title Nutrient deficiency detection in maize (Zea mays L.) leaves using image processing / Nurul Shafekah Kassim
title_full Nutrient deficiency detection in maize (Zea mays L.) leaves using image processing / Nurul Shafekah Kassim
title_fullStr Nutrient deficiency detection in maize (Zea mays L.) leaves using image processing / Nurul Shafekah Kassim
title_full_unstemmed Nutrient deficiency detection in maize (Zea mays L.) leaves using image processing / Nurul Shafekah Kassim
title_short Nutrient deficiency detection in maize (Zea mays L.) leaves using image processing / Nurul Shafekah Kassim
title_sort nutrient deficiency detection in maize zea mays l leaves using image processing nurul shafekah kassim
topic Data processing. Computer applications
Electronic Computers. Computer Science
S Agriculture (General)
url https://ir.uitm.edu.my/id/eprint/31511/1/31511.pdf
work_keys_str_mv AT kassimnurulshafekah nutrientdeficiencydetectioninmaizezeamayslleavesusingimageprocessingnurulshafekahkassim