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Utpal Barman, Parismita Sarma, Mirzanur Rahman, Vaskar Deka, Swati Lahkar, Vaishali Sharma and Manob Jyoti Saikia
Invading pests and diseases always degrade the quality and quantity of plants. Early and accurate identification of plant diseases is critical for plant health and growth. This work proposes a smartphone-based solution using a Vision Transformer (ViT) mo...
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Manjit Kumar Ray, Awdhesh Kumar Mishra, Yugal Kishore Mohanta, Saurov Mahanta, Ishani Chakrabartty, Neelam Amit Kungwani, Satya Kumar Avula, Jibanjyoti Panda and Ramesh Namdeo Pudake
It is crucial to increase agricultural yields to fulfill the rising demand for food and the security it provides for a growing population. To protect human food supplies and agricultural outputs, disease management is essential. Plant infections are a si...
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Rutuja Rajendra Patil, Sumit Kumar, Ruchi Rani, Poorva Agrawal and Sanjeev Kumar Pippal
Agriculture has observed significant advancements since smart farming technology has been introduced.The Green Movement played an essential role in the evolution of farming methods. The use of smart farming is accelerating at an unprecedented rate becaus...
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Aminu Musa, Mohammed Hassan, Mohamed Hamada and Farouq Aliyu
Recent advances in computing allows researchers to propose the automation of hydroponic systems to boost efficiency and reduce manpower demands, hence increasing agricultural produce and profit. A completely automated hydroponic system should be equipped...
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Normaisharah Mamat, Mohd Fauzi Othman, Rawad Abdoulghafor, Samir Brahim Belhaouari, Normahira Mamat and Shamsul Faisal Mohd Hussein
The implementation of intelligent technology in agriculture is seriously investigated as a way to increase agriculture production while reducing the amount of human labor. In agriculture, recent technology has seen image annotation utilizing deep learnin...
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Arunabha M. Roy and Jayabrata Bhaduri
In this paper, a deep learning enabled object detection model for multi-class plant disease has been proposed based on a state-of-the-art computer vision algorithm. While most existing models are limited to disease detection on a large scale, the current...
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Zhirui Luo, Qingqing Li and Jun Zheng
Transfer learning using pre-trained deep neural networks (DNNs) has been widely used for plant disease identification recently. However, pre-trained DNNs are susceptible to adversarial attacks which generate adversarial samples causing DNN models to make...
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René H.J. Heim, Ian J. Wright, Peter Scarth, Angus J. Carnegie, Dominique Taylor and Jens Oldeland
Disease management in agriculture often assumes that pathogens are spread homogeneously across crops. In practice, pathogens can manifest in patches. Currently, disease detection is predominantly carried out by human assessors, which can be slow and expe...
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Bulent Tugrul, Elhoucine Elfatimi and Recep Eryigit
Rapid improvements in deep learning (DL) techniques have made it possible to detect and recognize objects from images. DL approaches have recently entered various agricultural and farming applications after being successfully employed in various fields. ...
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Efrem Yohannes Obsie, Hongchun Qu, Yong-Jiang Zhang, Seanna Annis and Francis Drummond
Early detection and accurately rating the level of plant diseases plays an important role in protecting crop quality and yield. The traditional method of mummy berry disease (causal agent: Monilinia vaccinii-corymbosi) identification is mainly based on f...
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Huan Wang, Shi Qiu, Huping Ye and Xiaohan Liao
Plant growth is inevitably affected by diseases, and one effective method of disease detection is through the observation of leaf changes. To solve the problem of disease detection in complex backgrounds, where the distinction between plant diseases is h...
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Min Zhang, Zhaoai Shi, Guangming Chen, Aocheng Cao, Qiuxia Wang, Dongdong Yan, Wensheng Fang and Yuan Li
Seeds comprise an important way in which plant pathogens are introduced into new areas, and serve as carriers for their survival from one planting season to another. Seed health is a recognized factor in modern agricultural science, and affects ideal pla...
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Luana Centorame, Thomas Gasperini, Alessio Ilari, Andrea Del Gatto and Ester Foppa Pedretti
Machine learning is a widespread technology that plays a crucial role in digitalisation and aims to explore rules and patterns in large datasets to autonomously solve non-linear problems, taking advantage of multiple source data. Due to its versatility, ...
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Lulu Cai, Qian Tian, Qingqing Meng, Xiaoyang Bao, Peidong Xu, Ji Liu, Wenjun Zhao and Hui Wang
Stewart?s vascular wilt and leaf blight of sweet corn is caused by the Gram-negative enteric bacterium Pantoea stewartii subsp. stewartii. Stewart?s wilt results in substantial yield losses worldwide warranting rapid and accurate disease diagnosis. Recom...
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Mahnoor Khalid, Muhammad Shahzad Sarfraz, Uzair Iqbal, Muhammad Umar Aftab, Gniewko Niedbala and Hafiz Tayyab Rauf
In the twenty-first century, machine learning is a significant part of daily life for everyone. Today, it is adopted in many different applications, such as object recognition, object classification, and medical purposes. This research aimed to use deep ...
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Shamaila Zia-Khan, Melissa Kleb, Nikolaus Merkt, Steffen Schock and Joachim Müller
Late detection of fungal infection is the main cause of inadequate disease control, affecting fruit quality and reducing yield of grapevine. Therefore, infrared imagery as a remote sensing technique was investigated in this study as a potential tool for ...
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Alwyn Tan, Mo Salman, Bruce Wagner and Brian McCluskey
Biosurveillance defines the process of gathering, integrating, interpreting, and communicating essential information related to all-hazards threats or disease activity affecting human, animal, or plant health to achieve early detection and warning, contr...
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Hamna Waheed, Waseem Akram, Saif ul Islam, Abdul Hadi, Jalil Boudjadar and Noureen Zafar
The agriculture sector plays a crucial role in supplying nutritious and high-quality food. Plant disorders significantly impact crop productivity, resulting in an annual loss of 33%. The early and accurate detection of plant disorders is a difficult task...
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Zhichao Chen, Guoqiang Wang, Tao Lv and Xu Zhang
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 emergenc...
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Sergio Vélez, Enrique Barajas, José Antonio Rubio, Dimas Pereira-Obaya and José Ramón Rodríguez-Pérez
This study explores spectroscopy in the 350 to 2500 nm range for detecting powdery mildew (Erysiphe necator) in grapevine leaves, crucial for precision agriculture and sustainable vineyard management. In a controlled experimental vineyard setting, the sp...
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