Target detection algorithms can greatly improve the efficiency of tomato leaf disease detection and play an important technical role in intelligent tomato cultivation. However, there are some challenges in the detection process, such as the diversity...
As a result of climate change and global warming, plant diseases and pests are drawing attention because they are dispersing more quickly than ever before. The tomato leaf miner destroys the growth structure of the tomato, resulting in 80 to 100 perc...
Agricultural production is a critical sector that directly impacts the economy and social life of any society. The identification of plant disease in a real-time environment is a significant challenge for agriculture production. For accurate plant di...
Tomato leaf curl New Delhi virus (ToLCNDV) and tomato yellow leaf curl virus (TYLCV) are two important viral pathogens that severely affect Solanaceae and Cucurbitaceae plants. In order to reduce the further spread of these viruses, it is crucial to...
As tomatoes are the most consumed vegetable in the world, production should be increased to fulfill the vast demand for this vegetable. Global warming, climate changes, and other significant factors, including pests, badly affect tomato plants and ca...
Tomato is one of the most important economic crops in the world, but it is prone to diseases during the growth process, so the detection of tomato diseases is very important. However, when detecting tomato diseases in natural environments, existing m...
Tomato leaf diseases cause substantial yield and quality losses worldwide, yet reliable detection in real fields remains challenging. Two practical bottlenecks dominate current research: (i) limited data, including small samples for rare diseases, cl...
The precise identification of diseases in tomato leaves is of great importance for precise target pesticide application in a complex background scenario. Existing models often have difficulty capturing long-range dependencies and fine-grained feature...
Tomato cultivation is a vital agricultural practice worldwide, yet it faces significant challenges due to various diseases that adversely affect crop yield and quality. This paper presents a novel tomato disease detection system within an operational...
In today’s era, vegetables are considered a very important part of many foods. Even though every individual can harvest their vegetables in the home kitchen garden, in vegetable crops, Tomatoes are the most popular and can be used normally in e...
In this paper, we proposed a hybrid deep learning approach for detecting and classifying tomato plant leaf diseases early. This hybrid system is a combination of a convolutional neural network (CNN), convolutional attention module (CBAM), and support...
Leaf mildew is a common disease of tomato leaves. Its detection is an important means to reduce yield loss from the disease and improve tomato quality. In this study, a new method was developed for the multi-source detection of tomato leaf mildew by...
Tomato is a key economic crop whose yield and quality depend heavily on the early and accurate detection of leaf diseases. Conventional diagnosis based on manual observation is labor-intensive and prone to subjective bias. To overcome the limitations...
Increasing demand for sustainable agriculture necessitates precise and efficient crop management to minimize resource wastage and environmental impact. To improve the precision of pesticide application in tomato leaves, a real-time tomato leaf detect...
The frequent emergence of multiple diseases in tomato plants poses a significant challenge to agriculture, requiring innovative solutions to deal with this problem. The paper explores the application of machine learning (ML) technologies to develop a...
Smart agriculture has taken more attention during the last decade due to the bio-hazards of climate change impacts, extreme weather events, population explosion, food security demands and natural resources shortage. The Egyptian government has taken...
Pests have caused significant losses to agriculture, greatly increasing the detection of pests in the planting process and the cost of pest management in the early stages. At this time, advances in computer vision and deep learning for the detection...
In order to rapidly and nondestructively detect pesticide residues on tomato leaves, fluorescence spectroscopy and hyperspectral techniques were used to study the nondestructive detection of three different concentrations of benzyl-pyrazolyl esters o...
As an important economic crop, tomato is highly susceptible to diseases that, if not promptly managed, can severely impact yield and quality, leading to significant economic losses. Traditional diagnostic methods rely on expert visual inspection, whi...
The occurrence of tomato diseases has substantially reduced agricultural output and financial losses. The timely detection of diseases is crucial to effectively manage and mitigate the impact of episodes. Early illness detection can improve output, r...
Diseases of tomato leaves can seriously damage crop yield and financial rewards. The timely and accurate detection of tomato diseases is a major challenge in agriculture. Hence, the early and accurate diagnosis of tomato diseases is crucial. The emer...
Plant diseases pose the greatest threat to food supply integrity, and it is a significant challenge to identify plant diseases in their earliest stages to reduce the potential for associated economic damage. Through the use of computer vision, a cutt...
Plant diseases affect the availability and safety of plants for human and animal consumption and threaten food safety, thus reducing food availability and access, as well as reducing crop yield and quality. There is a need for novel disease detection...
29 September 2024
Tomato diseases, including Leaf blight, Leaf curl, Septoria leaf spot, and Verticillium wilt, are responsible for up to 50% of annual yield loss, significantly impacting global tomato production, valued at approximately USD 87 billion. In Ghana, ther...
In this study, we propose a multi-scale feature fusion network based on an improved RT-DETR model for the efficient detection of tomato leaf disease. Our model combines the multi-scale extended residual module by capturing contextual information at v...
The chickpea chlorotic dwarf virus (CpCDV) (from the genus Mastrevirus and the family Geminiviridae) and tomato leaf curl New Delhi virus (ToLCNDV) (from the genus Begomovirus and the family Geminiviridae) represent an important threat to different c...
Tomato leaf curl New Delhi virus (ToLCNDV) represents a threat to economically important horticultural crops. A real-time loop-mediated isothermal amplification (LAMP) assay for in-field ToLCNDV detection was developed, coupled to a rapid sample prep...
Early diagnosis of plant diseases is of vital importance since they cause social, ecological, and economic losses. Therefore, it is highly complex and causes excessive workload and time loss. Within the scope of this article, nine tomato plant leaf d...
This study introduces a You Only Look Once (YOLO) model for detecting diseases in tomato leaves, utilizing YOLOV8s as the underlying framework. The tomato leaf images, both healthy and diseased, were obtained from the Plant Village dataset. These ima...
Thrips-transmitted tomato spotted wilt orthotospovirus (TSWV) causes spotted wilt disease in peanuts. A serological test (DAS-ELISA) is often used to detect TSWV in peanut leaf samples. However, in a few studies, DAS-ELISA detected more TSWV infectio...
There is limited information on the distribution of blueberry viruses in the U.S. or around the world other than where the viruses were first discovered and characterized. A survey for blueberry viruses was carried out in the U.S. in 2015–2017....
With limited retrieval of reserves and restricted capability in plant pathology, automation of processes becomes essential. All over the world, farmers are struggling to prevent various harm from bacteria or pathogens such as viruses, fungi, worms, p...
Automatic leaf disease detection techniques are effective for reducing the time-consuming effort of monitoring large crop farms and early identification of disease symptoms of plant leaves. Although crop tomatoes are seen to be susceptible to a varie...
The incidence and severity of begomovirus diseases have been increasing around the world recently, and the ridge gourd [Luffa acutangula (Roxb.) L.] is the latest example of a crop that has become highly susceptible to the outbreak of the tomato leaf...
The detection of plant constituents is a crucial issue in precision agriculture, as monitoring these enables the automatic analysis of factors such as growth rate, health status, and crop yield. Tomatoes (Solanum sp.) are an economically and nutritio...
Plant diseases are currently a major threat to agricultural economies and food availability, having a negative environmental impact. Despite being a promising line of research, current approaches struggle with poor cross-site generalization, limited...
Tomato is one of the most essential and consumable crops in the world. Tomatoes differ in quantity depending on how they are fertilized. Leaf disease is the primary factor impacting the amount and quality of crop yield. As a result, it is critical to...
In Indonesia, tomato is one of the horticultural products with the highest economic value. To maintain enhanced tomato plant production, it is necessary to monitor the growth of tomato plants, particularly the leaves. The quality and quantity of toma...
Tomatoes are an important economic crop in China, and crop diseases often lead to a decline in their yield. Deep learning-based visual recognition methods have become an approach for disease identification; however, challenges remain due to complex b...
To address the real-time detection challenge of deploying deep learning-based tomato leaf disease detection algorithms on embedded devices, an improved tomato leaf disease detection algorithm based on YOLOv8n is proposed in this paper. It is able to...
In tomato leaf disease identification tasks, the high cost and consumption of deep learning-based recognition methods affect their deployment and application on embedded devices. In this study, an improved YOLOX-based tomato leaf disease identificati...
Salmonella serovars have been associated with the majority of foodborne illness outbreaks involving tomatoes, and E. coli O157:H7 has caused outbreaks involving other fresh produce. Contamination by both pathogens has been thought to originate from a...
The growing global population and accompanying increase in food demand has put pressure on agriculture to produce higher yields in the face of numerous challenges, including plant diseases. Tomato is a widely cultivated and essential food crop that i...
Among the most common and serious tomato plant pests, leafminer flies (Liriomyza sativae) are considered one of the major tomato-plant-damaging pests worldwide. Detecting the infestation and quantifying the severity of these pests are essential for r...
The rapid evolution of insecticide resistance in Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae) threatens effective pest management in key crops. This study characterized B. tabaci populations from cotton and tomato fields in Kashgar (September&...
Seed transmission is an important factor in the epidemiology of plant pathogens. Geminiviruses are serious pests spread in tropical and subtropical regions. They are transmitted by hemipteran insects, but a few cases of transmission through seeds wer...
In Myanmar, yellow mosaic and leaf curl diseases caused by whitefly-transmitted begomoviruses are serious problems for vegetables such as tomatoes and peppers. To investigate the incidence of begomoviruses in Myanmar between 2017 and 2019, a field su...
Early and accurate tomato disease detection using easily available leaf photos is essential for farmers and stakeholders as it help reduce yield loss due to possible disease epidemics. This paper aims to visually identify nine different infectious di...
Automatic fruit detection is a very important benefit of harvesting robots. However, complicated environment conditions, such as illumination variation, branch, and leaf occlusion as well as tomato overlap, have made fruit detection very challenging....
The Bemisia tabaci species complex consists of at least 44 cryptic species, which are potential vectors of approximately 320 begomovirus species, most of which are significant plant viruses. However, the relationship of begomovirus transmission throu...
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