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Triple bottom-line consideration of sustainable plant disease management:From economic,sociological and ecological perspectives

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Journal of Integrative Agriculture 2021年第10期20卷 2581-2591页

作者： HE Dun-chun Jeremy J.BURDON XIE Lian-hui Jiasui ZHAN Institute of Eco-technological Economics School of Economics and TradeFujian Jiangxia UniversityFuzhou 350108P.R.China Fujian Key Lab of plant Virology Institute of Plant VirologyFujian Agriculture and Forestry UniversityFuzhou 350002P.R.China CSIRO Agriculture CanberraA.C.T.2601Australia Department of Forest Mycology and plant Pathology Swedish University of Agricultural SciencesUppsala 75007Sweden

plant disease management plays an important role in achieving the sustainable development goals of the United Nations(UN)such as food security,human health,socio-economic improvement,resource conservation and ecological ***,technologies available are often limited due to different interests between producers and society and lacks of proper understanding of economic thresholds and the complex interactions among ecology,productivity and profitability.A comprehensive synergy and conflict evaluation of economic,sociological and ecological effects with technologies,productions and evolutionary principles as main components should be used to guide sustainable disease management that aims to mitigate crop and economic losses in the short term while maintaining functional farm ecosystem in the long ***,there should be an increased emphasis on technology development,public education and information exchange among governments,researchers,producers and consumers to broaden the options for disease management in the future.

关键词： plant disease management agricultural sustainability disease economics food security resource conservation

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Cross-comparative review of Machine learning for plant disease detection:apple,cassava,cotton and potato plants

Artificial Intelligence in Agriculture

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Artificial Intelligence in Agriculture 2024年第2期12卷 127-151页

作者： James Daniel Omaye Emeka Ogbuju Grace Ataguba Oluwayemisi Jaiyeoba Joseph Aneke Francisca Oladipo Department of Computer Science Federal UniversityLokojaNigeria Department of Computer Science Dalhousie UniversityHalifaxCanada Department of Computer Science Hampton UniversityVirginiaUSA

plant disease detection has played a significant role in combating plant diseases that pose a threat to global agri-culture and food *** these diseases early can help mitigate their impact and ensure healthy crop *** learning algorithms have emerged as powerful tools for accurately identifying and classifying a wide range of plant diseases from trained image datasets of affected *** algorithms,including deep learning algorithms,have shown remarkable success in recognizing disease patterns and early signs of plant *** early detection,there are other potential benefits of machine learning algorithms in overall plant disease management,such as soil and climatic condition predictions for plants,pest identification,proximity detection,and many *** the years,research has focused on using machine-learning algorithms for plant disease ***,little is known about the extent to which the research community has ex-plored machine learning algorithms to cover other significant areas of plant disease *** view of this,we present a cross-comparative review of machine learning algorithms and applications designed for plant dis-ease detection with a specific focus on four(4)economically important plants:apple,cassava,cotton,and *** conducted a systematic review of articles published between 2013 and 2023 to explore trends in the research community over the *** filtering a number of articles based on our inclusion criteria,including articles that present individual prediction accuracy for classes of disease associated with the selected plants,113 articles were considered *** these articles,we analyzed the state-of-the-art techniques,challenges,and future prospects of using machine learning for disease identification of the selected *** from our re-view show that deep learning and other algorithms performed significantly well in detecting plant *** addition,we fou

关键词： Machine learning plant diseases Agriculture plant disease management Convolutional neural networks

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Atmospheric-pressure microplasmas and their applications

Atmospheric-pressure microplasmas and their applications

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第十六届全国等离子体科学技术会议暨第一届全国等离子体医学研讨会

作者： Dongping Liu Ying Song Xianhui Zhang Longfei Ji Weiyuan Ni Zhenhua Bi Jinhai Niu School of Physics and Materials Engineering Dalian Nationalities University Fujian Key Laboratory for Plasma and Magnetic Resonance Department of Electric ScienceSchool of Physics and Mechanical & Electrical EngineeringXiamen University

In recent years,atmosphere-pressure cold plasmas were becoming increasingly important in biomaterial and industrial applications such as surface treatment, semiconductor fabrication,thin film deposition,food processin... 详细信息

关键词： atmospheric microplasma plant disease management plasma inactivation film deposition surface modification

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