• • Orcid

Education:

Master’s Degree

• Institution: Yunnan Agricultural University
• Location: Kunming, Yunnan, China
• Faculty: Big Data Academy
• Duration: September 1, 2020 – July 1, 2022

PhD

• Institution: Jilin Agricultural University
• Location: Changchun, Jilin, China
• Faculty: Plant Protection Institute
• Duration: September 1, 2022 – July 1, 2026

Area of Specialization:

Weibo Qin specializes in Agricultural Insects and Pest Control, focusing on innovative methods to protect crops and enhance agricultural productivity through the management of pest populations.

Academic Achievements:

During his academic career, Weibo Qin has pursued rigorous training and research, particularly in the integration of big data analytics with agricultural practices to improve pest control measures. His dedication to advancing the field of agricultural pest management has been demonstrated through various projects and research initiatives.

Experience:

Weibo Qin has accumulated significant knowledge and expertise in the field of plant protection, especially in agricultural insects and pest control. His education at prominent agricultural universities in China has equipped him with the skills necessary to contribute to sustainable agricultural practices.

Research Focus on Agricultural Insects:

Weibo Qin’s research primarily centers around Agricultural Insects and Pest Control, with a specific focus on the following areas:

Integrated Pest Management (IPM)

Weibo Qin investigates comprehensive strategies to manage pest populations effectively. His research aims to combine biological, cultural, mechanical, and chemical tools to minimize the economic, health, and environmental risks associated with pest control.

Biological Control Methods

A significant portion of Weibo Qin’s research is dedicated to exploring biological control agents such as predators, parasitoids, and pathogens. He studies their effectiveness in reducing pest populations without harming the environment, aiming to develop sustainable pest control practices.

Impact of Climate Change on Pest Dynamics

Weibo Qin examines how changing climate conditions affect the behavior, distribution, and lifecycle of agricultural pests. His research includes modeling the potential impacts of climate change on pest outbreaks and developing adaptive pest management strategies to mitigate these effects.

Use of Big Data in Pest Management

Leveraging his background in Big Data from his Master’s degree, Weibo Qin integrates data analytics into pest control research. He focuses on the use of big data to predict pest outbreaks, monitor pest populations, and assess the effectiveness of pest control measures in real-time.

Insect-Plant Interactions

Understanding the interactions between agricultural insects and their host plants is crucial for developing effective pest control methods. Weibo Qin’s research delves into the mechanisms of plant resistance and susceptibility to insect pests, aiming to enhance crop protection through the development of pest-resistant plant varieties.

Sustainable Agricultural Practices

Weibo Qin is committed to promoting sustainable agricultural practices that reduce reliance on chemical pesticides. His research supports the development and implementation of environmentally friendly pest control methods that ensure long-term agricultural productivity and ecosystem health.

Through his research, Weibo Qin contributes to advancing the field of agricultural pest management, aiming to enhance crop protection and promote sustainable agricultural practices.

 

Identification of Cotton Pest and Disease Based on CFNet-VoV-GCSP-LSKNet-YOLOv8s: A New Era of Precision Agriculture

• Journal: Frontiers in Plant Science
• Year: 2024
• DOI: 10.3389/FPLS.2024.1348402
• Contributors: Li, Rujia; He, Yiting; Li, Yadong; Qin, Weibo; Abbas, Arzlan; Ji, Rongbiao; Li, Shuang; Wu, Yehui; Sun, Xiaohai; Yang, Jianping
• Abstract: This study presents a novel approach for identifying cotton pests and diseases using an advanced combination of CFNet, VoV-GCSP, LSKNet, and YOLOv8s. This integrated model represents a breakthrough in precision agriculture, offering enhanced accuracy and efficiency in pest and disease detection.

Lightweight Network for Corn Leaf Disease Identification Based on Improved YOLO v8s

• Journal: Agriculture
• Year: 2024
• DOI: 10.3390/agriculture14020220
• Contributors: Rujia Li; Yadong Li; Weibo Qin; Arzlan Abbas; Shuang Li; Rongbiao Ji; Yehui Wu; Yiting He; Jianping Yang
• Abstract: The paper introduces an improved YOLO v8s-based lightweight network designed for the identification of corn leaf diseases. This innovation aims to provide a more efficient and accessible solution for farmers to detect and manage corn diseases promptly.

Dietary Assessment Across Various Life Stages of Seven-Spotted Lady Beetle (Coccinella septempunctata) (Coleoptera: Coccinellidae)

• Journal: The Journal of Basic and Applied Zoology
• Year: 2023
• DOI: 10.1186/S41936-023-00348-4
• Contributors: Abbas, Sohail; Abbas, Muneer; Alam, Aleena; Feng, Xiao; Raza, Ali; Shakeel, Muhammad; Qin, Weibo; Han, Xiao; Chen, Rizhao
• Abstract: This research investigates the dietary habits and requirements of the seven-spotted lady beetle across its various life stages. The findings provide valuable insights into the nutritional ecology of this beneficial insect, which plays a crucial role in biological pest control.

 

• • Scopus

🎓 Education:

Maria del Mar holds a Bachelor’s Degree in Biology, specializing in Cellular Biology and Genetics, from Universitat Autònoma de Barcelona (2005-2010). She pursued an Erasmus Internship in Oulu, Finland, and later obtained a Master’s Degree in Secondary Education and Vocational Training from Universidad Internacional de La Rioja (UNIR) in 2011.

🔬 Professional Experience:

With a diverse background, Maria del Mar has worked in various laboratories, including Hospital Clínic’s Primary Hemostasis Laboratory and Silliker Netherlands B.V. as a microbiology laboratory technician. She also served as a field and laboratory technician at INSTITUT DE RECERCA I TECNOLOGÍA AGROALIMENTÁRIA (IRTA), where she conducted soil microbiological analysis and supported experimental trials in molecular biology.

📊 Skills:

Maria del Mar possesses strong teamwork and communication skills, along with proficiency in laboratory techniques and software such as Excel, Word, PowerPoint, Outlook, R-studio, and SAS enterprise.

 

1. “Effect of Fertigation with Struvite and Ammonium Nitrate on Substrate Microbiota and N2O Emissions in a Tomato Crop on Soilless Culture System” (Agronomy, 2024)
   • This study likely investigates the impact of using struvite and ammonium nitrate in fertigation on the microbiota of substrates and N2O emissions in tomato crops grown in soilless culture systems. It addresses the sustainability and environmental implications of fertigation practices.
2. “The use of recovered struvite and ammonium nitrate in fertigation in a horticultural rotation: agronomic and microbiological assessment” (Environmental Technology, 2022)
   • This article likely assesses the agronomic and microbiological aspects of using recovered struvite and ammonium nitrate in fertigation within a horticultural rotation. It examines the feasibility and effectiveness of utilizing recycled nutrients in sustainable horticulture systems.
3. “Use of Recovered Struvite and Ammonium Nitrate in Fertigation in Tomato (Lycopersicum esculentum) Production for boosting Circular and Sustainable Horticulture” (Agriculture, 2021)
   • This publication explores the utilization of recovered struvite and ammonium nitrate in fertigation specifically for tomato production, with the aim of promoting circular and sustainable horticulture practices. It likely discusses strategies for enhancing nutrient efficiency and minimizing environmental impacts.
4. “Recovery of Phosphorus from Wastewater Profiting from Biological Nitrogen Treatment: Upstream, Concomitant or Downstream Precipitation Alternatives” (Agronomy, 2020)
   • Although not directly related to fertigation, this study focuses on the recovery of phosphorus from wastewater in conjunction with biological nitrogen treatment. It demonstrates an interest in sustainable nutrient management practices and the circular economy principles applied to agricultural systems.