Cowpea leaf disease identification using deep learning
The identification of plant/crop diseases is of great interest to agriculture and in turn, the growth of nations. A systematic way of grouping different plant and crop diseases is essential for identifying and cataloguing the extensive information collected about the many different known plant disea...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-12-01
|
| Series: | Smart Agricultural Technology |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772375524002673 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1846124984504680448 |
|---|---|
| author | Rajesh Kannan Megalingam Gowtham Gopakumar Menon Swathi Binoj Deepika Asandi Sai Akhil Revi Kunnambath Sakthiprasad Kuttankulangara Manoharan |
| author_facet | Rajesh Kannan Megalingam Gowtham Gopakumar Menon Swathi Binoj Deepika Asandi Sai Akhil Revi Kunnambath Sakthiprasad Kuttankulangara Manoharan |
| author_sort | Rajesh Kannan Megalingam |
| collection | DOAJ |
| description | The identification of plant/crop diseases is of great interest to agriculture and in turn, the growth of nations. A systematic way of grouping different plant and crop diseases is essential for identifying and cataloguing the extensive information collected about the many different known plant diseases. There has been no significant research on classifying diseases in cowpea plants. This research employs Vision transformer model to classify the diseases found in the Cowpea plant, a native plant found in Kerala. Classifying diseases affecting cowpea leaves is a vital aspect of crop management and protection. Understanding the specific types of diseases present in a crop facilitates early detection and helps implement control measures. Accurate disease classification provides valuable insights into the impact of the disease on the crop. Along with this, for each classified disease, a Possible Treatments and Prevention Methods suggestion is proposed. Six deep learning models—InceptionV3, VGG16, VGG19, Ensemble model, CNN and Vision Transformer (ViT) models were compared for the prediction of diseases in cowpea plants using a dataset of 5100 images of diseases of cowpea plant leaves. ViT outperformed other models with accuracy of 96%. Disease classification helps monitor the disease's spread and evolution, leading to a better understanding of its impact on cowpea production and the development of more effective control methods for researchers, farmers, and agronomists. |
| format | Article |
| id | doaj-art-d5da41d6195742808747acc06b70116c |
| institution | Kabale University |
| issn | 2772-3755 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Smart Agricultural Technology |
| spelling | doaj-art-d5da41d6195742808747acc06b70116c2024-12-13T11:08:14ZengElsevierSmart Agricultural Technology2772-37552024-12-019100662Cowpea leaf disease identification using deep learningRajesh Kannan Megalingam0Gowtham Gopakumar Menon1Swathi Binoj2Deepika Asandi Sai3Akhil Revi Kunnambath4Sakthiprasad Kuttankulangara Manoharan5Corresponding author.; ACORD (Amrita Coconut Research and Development Center), Department of Electronics and Communication Engineering, Amrita Vishwa Vidyapeetham, Amritapuri, IndiaACORD (Amrita Coconut Research and Development Center), Department of Electronics and Communication Engineering, Amrita Vishwa Vidyapeetham, Amritapuri, IndiaACORD (Amrita Coconut Research and Development Center), Department of Electronics and Communication Engineering, Amrita Vishwa Vidyapeetham, Amritapuri, IndiaACORD (Amrita Coconut Research and Development Center), Department of Electronics and Communication Engineering, Amrita Vishwa Vidyapeetham, Amritapuri, IndiaACORD (Amrita Coconut Research and Development Center), Department of Electronics and Communication Engineering, Amrita Vishwa Vidyapeetham, Amritapuri, IndiaACORD (Amrita Coconut Research and Development Center), Department of Electronics and Communication Engineering, Amrita Vishwa Vidyapeetham, Amritapuri, IndiaThe identification of plant/crop diseases is of great interest to agriculture and in turn, the growth of nations. A systematic way of grouping different plant and crop diseases is essential for identifying and cataloguing the extensive information collected about the many different known plant diseases. There has been no significant research on classifying diseases in cowpea plants. This research employs Vision transformer model to classify the diseases found in the Cowpea plant, a native plant found in Kerala. Classifying diseases affecting cowpea leaves is a vital aspect of crop management and protection. Understanding the specific types of diseases present in a crop facilitates early detection and helps implement control measures. Accurate disease classification provides valuable insights into the impact of the disease on the crop. Along with this, for each classified disease, a Possible Treatments and Prevention Methods suggestion is proposed. Six deep learning models—InceptionV3, VGG16, VGG19, Ensemble model, CNN and Vision Transformer (ViT) models were compared for the prediction of diseases in cowpea plants using a dataset of 5100 images of diseases of cowpea plant leaves. ViT outperformed other models with accuracy of 96%. Disease classification helps monitor the disease's spread and evolution, leading to a better understanding of its impact on cowpea production and the development of more effective control methods for researchers, farmers, and agronomists.http://www.sciencedirect.com/science/article/pii/S2772375524002673Cowpea plantsDeep learningPlant disease classificationVision transformer model (ViT)Treatment and prevention methods |
| spellingShingle | Rajesh Kannan Megalingam Gowtham Gopakumar Menon Swathi Binoj Deepika Asandi Sai Akhil Revi Kunnambath Sakthiprasad Kuttankulangara Manoharan Cowpea leaf disease identification using deep learning Smart Agricultural Technology Cowpea plants Deep learning Plant disease classification Vision transformer model (ViT) Treatment and prevention methods |
| title | Cowpea leaf disease identification using deep learning |
| title_full | Cowpea leaf disease identification using deep learning |
| title_fullStr | Cowpea leaf disease identification using deep learning |
| title_full_unstemmed | Cowpea leaf disease identification using deep learning |
| title_short | Cowpea leaf disease identification using deep learning |
| title_sort | cowpea leaf disease identification using deep learning |
| topic | Cowpea plants Deep learning Plant disease classification Vision transformer model (ViT) Treatment and prevention methods |
| url | http://www.sciencedirect.com/science/article/pii/S2772375524002673 |
| work_keys_str_mv | AT rajeshkannanmegalingam cowpealeafdiseaseidentificationusingdeeplearning AT gowthamgopakumarmenon cowpealeafdiseaseidentificationusingdeeplearning AT swathibinoj cowpealeafdiseaseidentificationusingdeeplearning AT deepikaasandisai cowpealeafdiseaseidentificationusingdeeplearning AT akhilrevikunnambath cowpealeafdiseaseidentificationusingdeeplearning AT sakthiprasadkuttankulangaramanoharan cowpealeafdiseaseidentificationusingdeeplearning |