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Lewis H. Ziska, Bethany A. Bradley, Rebekah D. Wallace, Charles T. Bargeron, Joseph H. LaForest, Robin A. Choudhury, Karen A. Garrett and Fernando E. Vega
The challenge of maintaining sufficient food, feed, fiber, and forests, for a projected end of century population of between 9–10 billion in the context of a climate averaging 2–4 °C warmer, is a global imperative. However, climate change...
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Bruno Cardoso, Catarina Silva, Joana Costa and Bernardete Ribeiro
With the increase of smart farming in the agricultural sector, farmers have better control over the entire production cycle, notably in terms of pest monitoring. In fact, pest monitoring has gained significant importance, since the excessive use of pesti...
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Javeria Amin, Muhammad Almas Anjum, Rida Zahra, Muhammad Imran Sharif, Seifedine Kadry and Lukas Sevcik
Pests are always the main source of field damage and severe crop output losses in agriculture. Currently, manually classifying and counting pests is time consuming, and enumeration of population accuracy might be affected by a variety of subjective measu...
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Ruicheng Gao, Zhancai Dong, Yuqi Wang, Zhuowen Cui, Muyang Ye, Bowen Dong, Yuchun Lu, Xuaner Wang, Yihong Song and Shuo Yan
In this study, a deep-learning-based intelligent detection model was designed and implemented to rapidly detect cotton pests and diseases. The model integrates cutting-edge Transformer technology and knowledge graphs, effectively enhancing pest and disea...
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Qing Dong, Lina Sun, Tianxin Han, Minqi Cai and Ce Gao
Timely and effective pest detection is essential for agricultural production, facing challenges such as complex backgrounds and a vast number of parameters. Seeking solutions has become a pressing matter. This paper, based on the YOLOv5 algorithm, develo...
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Wenji Yang and Xiaoying Qiu
The damage caused by pests to crops results in reduced crop yield and compromised quality. Accurate and timely pest detection plays a crucial role in helping farmers to defend against and control pests. In this paper, a novel crop pest detection model na...
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Zhichao Chen, Hongping Zhou, Haifeng Lin and Di Bai
The tea industry, as one of the most globally important agricultural products, is characterized by pests and diseases that pose a serious threat to yield and quality. These diseases and pests often present different scales and morphologies, and some pest...
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Madeleine G. Barton, Hazel Parry, Paul A. Umina, Matthew R. Binns, Thomas Heddle, Ary A. Hoffmann, Joanne Holloway, Dustin Severtson, Maarten Van Helden, Samantha Ward, Rachel Wood and Sarina Macfadyen
Despite the known benefits of integrated pest management, adoption in Australian broadacre crops has been slow, in part due to the lack of understanding about how pests and natural enemies interact. We use a previously developed process-based model to pr...
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Qixun Xiao, Wenying Zheng, Yifan He, Zijie Chen, Fanxin Meng and Liyan Wu
The use of Internet of Things (IoT) technology for real-time monitoring of agricultural pests is an unavoidable trend in the future of intelligent agriculture. This paper aims to address the difficulties in deploying models at the edge of the pest monito...
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Edmond Maican, Adrian Iosif and Sanda Maican
Using neural networks on low-power mobile systems can aid in controlling pests while preserving beneficial species for crops. However, low-power devices require simplified neural networks, which may lead to reduced performance. This study was focused on ...
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Ruixue Zhu, Fengqi Hao and Dexin Ma
Object detection in deep learning provides a viable solution for detecting crop-pest-infected regions. However, existing rectangle-based object detection methods are insufficient to accurately detect the shape of pest-infected regions. In addition, the m...
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Katarzyna Golan, Izabela Kot, Katarzyna Kmiec and Edyta Górska-Drabik
Insect pests have major effects on agricultural production and food supply. Pest control in conventional crop management in orchards is mainly based on agrochemicals, which entails economic, health and environmental costs. Other approaches, such as biolo...
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Esther Lantero, Beatriz Matallanas and Carmen Callejas
Mediterranean olive cultivation faces challenges in the global environmental change context. Pests and diseases caused by arthropods such as Bactrocera oleae, Prays oleae, and certain vectors of Xylella fastidiosa are expected to increase and spread in p...
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Tibor József, Szonja Réka Kiss, Ferenc Muzslay, Orsolya Máté, Gábor P. Stromájer and Tímea Stromájer-Rácz
Active substances detected in surface water in Hungary today include pain and anti-inflammatory agents and antiepileptics, as wastewater treatment mechanisms cannot remove these micropollutants. The aim of our research is to detect residues of four pain-...
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Jizhong Deng, Chang Yang, Kanghua Huang, Luocheng Lei, Jiahang Ye, Wen Zeng, Jianling Zhang, Yubin Lan and Yali Zhang
The realization that mobile phones can detect rice diseases and insect pests not only solves the problems of low efficiency and poor accuracy from manually detection and reporting, but it also helps farmers detect and control them in the field in a timel...
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Wenqing Xu, Weikai Li, Liwei Wang and Marcelo F. Pompelli
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Sitao Liu, Shenghui Fu, Anrui Hu, Pan Ma, Xianliang Hu, Xinyu Tian, Hongjian Zhang and Shuangxi Liu
Aiming at difficult image acquisition and low recognition accuracy of two rice canopy pests, rice stem borer and rice leaf roller, we constructed a GA-Mask R-CNN (Generative Adversarial Based Mask Region Convolutional Neural Network) intelligent recognit...
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Zijia Yang, Hailin Feng, Yaoping Ruan and Xiang Weng
Timely and accurate identification of tea tree pests is critical for effective tea tree pest control. We collected image data sets of eight common tea tree pests to accurately represent the true appearance of various aspects of tea tree pests. The datase...
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Shradha S. Aherkar, Surendra B. Deshmukh, Nitin. M. Konde, Aadinath N. Paslawar, Tanay Joshi, Monika M. Messmer and Amritbir Riar
The demand for organic cotton is primarily driven by manufacturers and brands with a corporate focus on environmental and social responsibility. These entities strive to be responsible stewards by seeking organic cotton, which not only offers environment...
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