Multiclass Classification of Grape Diseases Using Deep Artificial Intelligence
Protecting agricultural crops is essential for preserving food sources. The health of plants plays a major role in impacting the yield of agricultural output, and their bad health could result in significant economic loss.This is especially important in small-scale and hobby-farming products such as...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-09-01
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| Series: | Agriculture |
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| Online Access: | https://www.mdpi.com/2077-0472/12/10/1542 |
| _version_ | 1797476306566250496 |
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| author | Mohammad Fraiwan Esraa Faouri Natheer Khasawneh |
| author_facet | Mohammad Fraiwan Esraa Faouri Natheer Khasawneh |
| author_sort | Mohammad Fraiwan |
| collection | DOAJ |
| description | Protecting agricultural crops is essential for preserving food sources. The health of plants plays a major role in impacting the yield of agricultural output, and their bad health could result in significant economic loss.This is especially important in small-scale and hobby-farming products such as fruits. Grapes are an important and widely cultivated plant, especially in the Mediterranean region, with an over USD 189 billion global market value. They are consumed as fruits and in other manufactured forms (e.g., drinks and sweet food products). However, much like other plants, grapes are prone to a wide range of diseases that require the application of immediate remedies. Misidentifying these diseases can result in poor disease control and great losses (i.e., 5–80% crop loss). Existing computer-based solutions may suffer from low accuracy, may require high overhead, and be poorly deployable and prone to changes in image quality. The work in this paper aims at utilizing a ubiquitous technology to help farmers in combatting plant diseases. Particularly, deep-learning artificial-intelligence image-based applications were used to classify three common grape diseases: black measles, black rot, and isariopsis leaf spot. In addition, a fourth healthy class was included. A dataset of 3639 grape leaf images (1383 black measles, 1180 black rot, 1076 isariopsis leaf spot, and 423 healthy) was used. These images were used to customize and retrain 11 convolutional network models to classify the four classes. Thorough performance evaluation revealed that it is possible to design pilot and commercial applications with accuracy that satisfies field requirements. The models achieved consistently high performance values (>99.1%). |
| first_indexed | 2024-03-09T20:56:58Z |
| format | Article |
| id | doaj.art-f11417d5521f43f3900612adecc9a187 |
| institution | Directory Open Access Journal |
| issn | 2077-0472 |
| language | English |
| last_indexed | 2024-03-09T20:56:58Z |
| publishDate | 2022-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Agriculture |
| spelling | doaj.art-f11417d5521f43f3900612adecc9a1872023-11-23T22:20:02ZengMDPI AGAgriculture2077-04722022-09-011210154210.3390/agriculture12101542Multiclass Classification of Grape Diseases Using Deep Artificial IntelligenceMohammad Fraiwan0Esraa Faouri1Natheer Khasawneh2Department of Computer Engineering, Jordan University of Science and Technology, Irbid 22110, JordanDepartment of Computer Engineering, Jordan University of Science and Technology, Irbid 22110, JordanDepartment of Software Engineering, Jordan University of Science and Technology, Irbid 22110, JordanProtecting agricultural crops is essential for preserving food sources. The health of plants plays a major role in impacting the yield of agricultural output, and their bad health could result in significant economic loss.This is especially important in small-scale and hobby-farming products such as fruits. Grapes are an important and widely cultivated plant, especially in the Mediterranean region, with an over USD 189 billion global market value. They are consumed as fruits and in other manufactured forms (e.g., drinks and sweet food products). However, much like other plants, grapes are prone to a wide range of diseases that require the application of immediate remedies. Misidentifying these diseases can result in poor disease control and great losses (i.e., 5–80% crop loss). Existing computer-based solutions may suffer from low accuracy, may require high overhead, and be poorly deployable and prone to changes in image quality. The work in this paper aims at utilizing a ubiquitous technology to help farmers in combatting plant diseases. Particularly, deep-learning artificial-intelligence image-based applications were used to classify three common grape diseases: black measles, black rot, and isariopsis leaf spot. In addition, a fourth healthy class was included. A dataset of 3639 grape leaf images (1383 black measles, 1180 black rot, 1076 isariopsis leaf spot, and 423 healthy) was used. These images were used to customize and retrain 11 convolutional network models to classify the four classes. Thorough performance evaluation revealed that it is possible to design pilot and commercial applications with accuracy that satisfies field requirements. The models achieved consistently high performance values (>99.1%).https://www.mdpi.com/2077-0472/12/10/1542grapeartificial intelligenceblack measlesblack rotisariopsis leaf spotdisease |
| spellingShingle | Mohammad Fraiwan Esraa Faouri Natheer Khasawneh Multiclass Classification of Grape Diseases Using Deep Artificial Intelligence Agriculture grape artificial intelligence black measles black rot isariopsis leaf spot disease |
| title | Multiclass Classification of Grape Diseases Using Deep Artificial Intelligence |
| title_full | Multiclass Classification of Grape Diseases Using Deep Artificial Intelligence |
| title_fullStr | Multiclass Classification of Grape Diseases Using Deep Artificial Intelligence |
| title_full_unstemmed | Multiclass Classification of Grape Diseases Using Deep Artificial Intelligence |
| title_short | Multiclass Classification of Grape Diseases Using Deep Artificial Intelligence |
| title_sort | multiclass classification of grape diseases using deep artificial intelligence |
| topic | grape artificial intelligence black measles black rot isariopsis leaf spot disease |
| url | https://www.mdpi.com/2077-0472/12/10/1542 |
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