顽强的植物学:面对有限的流动性和资源进行创新

IF 2.7 3区 生物学 Q2 PLANT SCIENCES Applications in Plant Sciences Pub Date : 2024-04-02 DOI:10.1002/aps3.11577
Gillian H. Dean, N. Ivalú Cacho, Alejandro Zuluaga Trochez, Gregory J. Pec
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For example, although national research programs in the Global North are generally well funded, these funds may be difficult to access for investigators who hold positions at smaller institutions, such as predominantly undergraduate institutions.</p><p>Regardless of geographic location, lack of training and access to expensive and specialized equipment can be limiting, and funding to acquire expensive equipment often does not include salary for maintenance and operation by trained personnel after the initial purchase and set up. In addition, research may be performed by new investigators such as undergraduate or graduate students, or when established labs wish to explore new areas of research or techniques without committing significant resources.</p><p>Globally, substantial and significant scientific research is performed in these under-resourced settings. The COVID-19 pandemic exacerbated this situation by disrupting supply chains and forcing researchers to work from home or in isolation at their workplace, resulting in dynamic adaptations in their approaches to generating or collecting data. Suddenly confronted with an inability to travel, many scientists looked to their local environment to leverage their skills to continue research closer to home. In light of these challenges, this <i>APPS</i> special issue, titled “Resilient botany: Innovation in the face of limited mobility and resources,” showcases the creative ways that plant scientists carried on with research during a global pandemic. The papers in this issue encompass a variety of fields and scales of research, ranging from investigations of plant structure at the microscopic level to utilizing big data to understand biodiversity, but they all have one thing in common: they are all accessible to researchers and practitioners challenged by funding or travel restrictions.</p><p>It has been well documented that cataloging global biodiversity is a daunting task that will take a concerted effort by many scientists and community scientists, especially given that much of the world's biodiversity is located in areas with under-resourced research communities. A large amount of data is already contained in herbaria, and digitizing this information is an important milestone toward improving access. The R package gatoRs presented by Patten et al. (<span>2024</span>) in this special issue addresses challenges in obtaining and processing digitized biodiversity data by offering a streamlined workflow. The package includes functions for downloading records from the Global Biodiversity Information Facility (GBIF) and Integrated Digitized Biocollections (iDigBio) and a cleaning function for specimen records. Notably, gatoRs accommodates variations in download structures between GBIF and iDigBio and allows user control through interactive cleaning steps. The pipeline aims to make biodiversity data processing efficient and accessible and is expected to benefit both experienced and novice users in the scientific community. Additionally, the package is a valuable tool for introducing classroom biodiversity concepts through herbarium specimens.</p><p>An often-overlooked component of biodiversity is the microbiota, the vast array of microorganisms that inhabit every corner of our world. These microscopic organisms play crucial roles in various ecosystems, contributing to nutrient cycling, decomposition of organic matter, and plant establishment and succession (Smith and Read, <span>2008</span>; Diamini et al., <span>2022</span>). Despite their importance, our understanding of microbiota remains limited, largely due to the challenges associated with studying them. In this context, the second paper in this issue introduces a new, cost-effective moist chamber culture technique designed to recover a broader spectrum of microbial species (Bordelon et al., <span>2024</span>). This technique emphasizes its low-cost, accessible approach, addressing the need for more cost-effective research methods and the involvement of community scientists. Bordelon et al. (<span>2024</span>) provide a robust discussion on the environmental factors affecting microbiota on live tree bark, including examples of microbiota found on rough bark of live trees and considerations for smooth bark live trees in the context of myxomycete cultures. The importance of pH, water-holding capacity, and bark characteristics is explored, providing insights into the diversity and abundance of myxomycetes associated with different tree species (Bordelon et al., <span>2024</span>).</p><p>In modern agriculture, the integration of advanced technologies such as remote sensing (Yang, <span>2020</span>), DNA-based detection methods (Martinelli et al., <span>2015</span>), and robotics and artificial intelligence (Balaska et al., <span>2023</span>) has become increasingly important for enhancing crop management and mitigating the impact of plant diseases (Spadaro and Gullino, <span>2019</span>). One prominent area of innovation is the application of computer vision (CV) (Ouhami et al., <span>2021</span>). This dynamic field leverages the capabilities of machine learning to revolutionize the way we detect and respond to diseases affecting crops (Ahmed and Reddy, <span>2021</span>). The significance of addressing plant pathogens is underscored by their potential to cause catastrophic consequences such as famine and economic collapse by rendering local cultivation unprofitable (Dai and Fan, <span>2022</span>). The third paper in this issue provides a focused review on the increasing use of CV for precise disease detection and optimal pesticide application timing, featuring case studies from agricultural practices in cocoa production. Here, Sykes et al. (<span>2024</span>) underscore the advantages of CV, including cost reduction and prevention of misapplication, discussing financial and ecological implications. The analysis goes beyond previous work, exploring technical concepts in applying CV to plant pathology, training data acquisition, and insights into machine learning methods. The authors highlight the significance of curated training data, exploring computationally efficient techniques and providing a comparative analysis of model architectures. Furthermore, Sykes et al. (<span>2024</span>) discuss the evolving role of machine learning in optimizing pesticide application and provide a comprehensive perspective on applying CV in plant pathology, including practical considerations for data gathering and a roadmap for commercial implementation.</p><p>In addition to these large-scale methods, there is also scope for developing reliable, inexpensive, and easily accessible protocols for performing laboratory-based experiments. In this special issue, we highlight two simple and robust plant anatomy and physiology methods for settings with fewer resources and limited infrastructure.</p><p>Koch et al. (<span>2024</span>) expand on a method first described by Díaz Dominguez et al. (<span>2022</span>) for measuring lichen thalli hydrophobicity that requires only a micropipette, distilled water, a tripod, and a phone or camera, thereby providing a cost-effective and rapid way of assessing this functional trait. By analyzing 93 lichen taxa, the authors’ results support the method's efficacy in capturing a spectrum of hydrophobicity levels, including both highly hydrophilic and highly hydrophobic species. This method, which can be used with both fresh and archival material, emerges as a valuable and versatile tool for ecophysiology-based lichen trait assessment across climates, lichen species, and growth forms, and offers insights into its potential as a predictor of climate change effects.</p><p>The sectioning of plant material is a classic method that has been used extensively to obtain details of a wide variety of tissue structures, with applications in taxonomy and plant anatomy (for a comprehensive overview, see Yeung et al., <span>2016</span>). Angeles and Madero-Vega (<span>2024</span>) share a low-cost sectioning medium created by dissolving biaxially oriented polypropylene (BOPP) in a commercially available polyurethane remover. The resulting BOPP syrup can be used for plant tissue sectioning, as well as for obtaining surface prints of both wood and leaf parts. BOPP is a plastic material widely used in the food industry for wrapping produce and other food items, and is usually seen as a waste product. Therefore, it is an attractive starting material for this low-cost method as it is widely available at no cost in many countries.</p><p>In summary, this special issue presents affordable and innovative approaches addressing challenges in biodiversity cataloging, microbiota discovery, agriculture, anatomy, and physiology. The gatoRs R package streamlines access to and use of digitized biodiversity data, while a cost-effective moist chamber culture technique enhances our understanding of microbiota. The integration of computer vision in agriculture, discussed by Sykes et al. (<span>2024</span>), demonstrates its potential for precise disease detection and pesticide application. Furthermore, the issue showcases accessible methods for lichen thalli hydrophobicity assessment and plant tissue sectioning, emphasizing simple and cost-effective ways to advance research in plant physiology and anatomy. Together, these contributions offer valuable insights and practical tools for researchers, educators, and community scientists in resource-limited settings. [Correction added on 8 April 2024 after first online publication: In the last paragraph, the sentence “The gatoRs R package streamlines the digitization of biodiversity data,…” was inaccurate. The sentence has been corrected.]</p><p>G.J.P. and G.H.D. initiated this special issue, and N.I.C. and A.Z.T. contributed to its development. G.J.P., N.I.C., and A.Z.T. acted as handling editors for manuscripts. 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These microscopic organisms play crucial roles in various ecosystems, contributing to nutrient cycling, decomposition of organic matter, and plant establishment and succession (Smith and Read, <span>2008</span>; Diamini et al., <span>2022</span>). Despite their importance, our understanding of microbiota remains limited, largely due to the challenges associated with studying them. In this context, the second paper in this issue introduces a new, cost-effective moist chamber culture technique designed to recover a broader spectrum of microbial species (Bordelon et al., <span>2024</span>). This technique emphasizes its low-cost, accessible approach, addressing the need for more cost-effective research methods and the involvement of community scientists. Bordelon et al. (<span>2024</span>) provide a robust discussion on the environmental factors affecting microbiota on live tree bark, including examples of microbiota found on rough bark of live trees and considerations for smooth bark live trees in the context of myxomycete cultures. The importance of pH, water-holding capacity, and bark characteristics is explored, providing insights into the diversity and abundance of myxomycetes associated with different tree species (Bordelon et al., <span>2024</span>).</p><p>In modern agriculture, the integration of advanced technologies such as remote sensing (Yang, <span>2020</span>), DNA-based detection methods (Martinelli et al., <span>2015</span>), and robotics and artificial intelligence (Balaska et al., <span>2023</span>) has become increasingly important for enhancing crop management and mitigating the impact of plant diseases (Spadaro and Gullino, <span>2019</span>). One prominent area of innovation is the application of computer vision (CV) (Ouhami et al., <span>2021</span>). This dynamic field leverages the capabilities of machine learning to revolutionize the way we detect and respond to diseases affecting crops (Ahmed and Reddy, <span>2021</span>). The significance of addressing plant pathogens is underscored by their potential to cause catastrophic consequences such as famine and economic collapse by rendering local cultivation unprofitable (Dai and Fan, <span>2022</span>). The third paper in this issue provides a focused review on the increasing use of CV for precise disease detection and optimal pesticide application timing, featuring case studies from agricultural practices in cocoa production. Here, Sykes et al. (<span>2024</span>) underscore the advantages of CV, including cost reduction and prevention of misapplication, discussing financial and ecological implications. The analysis goes beyond previous work, exploring technical concepts in applying CV to plant pathology, training data acquisition, and insights into machine learning methods. The authors highlight the significance of curated training data, exploring computationally efficient techniques and providing a comparative analysis of model architectures. Furthermore, Sykes et al. (<span>2024</span>) discuss the evolving role of machine learning in optimizing pesticide application and provide a comprehensive perspective on applying CV in plant pathology, including practical considerations for data gathering and a roadmap for commercial implementation.</p><p>In addition to these large-scale methods, there is also scope for developing reliable, inexpensive, and easily accessible protocols for performing laboratory-based experiments. 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引用次数: 0

摘要

2020 年,在 COVID-19 大流行之初,《植物科学应用》(Applications in Plant Sciences, APPS)出版了一期题为 "利用有限资源开展植物学研究:植物科学中的低成本方法"(Dean 等人,2020 年)。该论文集的目的是强调资源不足环境下研究人员可使用的可靠、低成本方法。植物科学家面临资源限制的原因很多。在一些国家,国家资金不足是一个主要问题,对研究基础设施的长期投资也很有限。与此同时,在研究资金较为充裕的国家,研究人员也会遇到导致资源匮乏的因素。例如,虽然全球北方国家的国家研究计划通常资金充足,但对于在较小机构(如以本科生为主的机构)任职的研究人员来说,可能很难获得这些资金。无论地理位置如何,缺乏培训以及无法获得昂贵的专业设备都可能是限制因素,而且购买昂贵设备的资金通常不包括在最初购买和安装后由受过培训的人员进行维护和操作的工资。此外,研究工作可能是由本科生或研究生等新研究人员进行的,或者是已有实验室希望在不投入大量资源的情况下探索新的研究领域或技术时进行的。COVID-19 大流行扰乱了供应链,迫使研究人员在家工作或在工作场所隔离工作,导致他们在生成或收集数据的方法上进行动态调整,从而加剧了这种状况。由于突然无法出差,许多科学家寄希望于当地的环境,利用自己的技能在离家较近的地方继续开展研究。鉴于这些挑战,本期《亚太植物学》特刊以 "有复原力的植物学:面对有限的流动性和资源的创新 "为题,展示了植物科学家在全球大流行期间继续开展研究的创造性方法。本期论文涉及不同的研究领域和规模,从微观层面的植物结构研究到利用大数据了解生物多样性,但它们都有一个共同点:它们都可供受到资金或旅行限制挑战的研究人员和从业人员使用。植物标本馆中已经包含了大量数据,将这些信息数字化是改善信息获取的一个重要里程碑。Patten 等人(2024 年)在本特刊中介绍的 R 软件包 gatoRs 通过提供简化的工作流程,解决了获取和处理数字化生物多样性数据的难题。该软件包包括从全球生物多样性信息机制(GBIF)和综合数字化生物收藏(iDigBio)下载记录的功能,以及标本记录的清理功能。值得注意的是,gatoRs 能够适应 GBIF 和 iDigBio 下载结构的变化,并允许用户通过交互式清理步骤进行控制。该管道旨在使生物多样性数据处理变得高效、易用,预计科学界有经验的用户和新手都能从中受益。此外,该软件包还是通过标本馆标本介绍课堂生物多样性概念的重要工具。生物多样性的一个经常被忽视的组成部分是微生物群,即居住在我们世界每个角落的大量微生物。这些微小的生物在各种生态系统中发挥着至关重要的作用,有助于养分循环、有机物的分解以及植物的建立和演替(Smith 和 Read,2008 年;Diamini 等人,2022 年)。尽管微生物区系非常重要,但我们对它们的了解仍然有限,这主要是由于研究微生物区系所面临的挑战。在这种情况下,本期的第二篇论文介绍了一种新的、具有成本效益的湿室培养技术,旨在回收更广泛的微生物物种(Bordelon 等人,2024 年)。该技术强调其低成本、易获得的方法,满足了对更具成本效益的研究方法和社区科学家参与的需求。Bordelon 等人(2024 年)对影响活树皮上微生物群的环境因素进行了详尽的讨论,包括在活树粗糙树皮上发现的微生物群实例,以及在木霉菌培养中对光滑树皮活树的考虑。
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Resilient botany: Innovation in the face of limited mobility and resources

In 2020, at the beginning of the COVID-19 pandemic, Applications in Plant Sciences (APPS) published a special issue titled “Conducting botanical research with limited resources: Low-cost methods in the plant sciences” (Dean et al., 2020). The goal of that collection was to highlight robust, low-cost methods that could be used by researchers in under-resourced settings. Plant scientists face resource limitations for many reasons. In some countries, inadequate national funding is a major issue, as well as limited long-term investment in research infrastructure. At the same time, factors contributing to low-resource settings are also experienced by researchers in countries where research funding is more abundant. For example, although national research programs in the Global North are generally well funded, these funds may be difficult to access for investigators who hold positions at smaller institutions, such as predominantly undergraduate institutions.

Regardless of geographic location, lack of training and access to expensive and specialized equipment can be limiting, and funding to acquire expensive equipment often does not include salary for maintenance and operation by trained personnel after the initial purchase and set up. In addition, research may be performed by new investigators such as undergraduate or graduate students, or when established labs wish to explore new areas of research or techniques without committing significant resources.

Globally, substantial and significant scientific research is performed in these under-resourced settings. The COVID-19 pandemic exacerbated this situation by disrupting supply chains and forcing researchers to work from home or in isolation at their workplace, resulting in dynamic adaptations in their approaches to generating or collecting data. Suddenly confronted with an inability to travel, many scientists looked to their local environment to leverage their skills to continue research closer to home. In light of these challenges, this APPS special issue, titled “Resilient botany: Innovation in the face of limited mobility and resources,” showcases the creative ways that plant scientists carried on with research during a global pandemic. The papers in this issue encompass a variety of fields and scales of research, ranging from investigations of plant structure at the microscopic level to utilizing big data to understand biodiversity, but they all have one thing in common: they are all accessible to researchers and practitioners challenged by funding or travel restrictions.

It has been well documented that cataloging global biodiversity is a daunting task that will take a concerted effort by many scientists and community scientists, especially given that much of the world's biodiversity is located in areas with under-resourced research communities. A large amount of data is already contained in herbaria, and digitizing this information is an important milestone toward improving access. The R package gatoRs presented by Patten et al. (2024) in this special issue addresses challenges in obtaining and processing digitized biodiversity data by offering a streamlined workflow. The package includes functions for downloading records from the Global Biodiversity Information Facility (GBIF) and Integrated Digitized Biocollections (iDigBio) and a cleaning function for specimen records. Notably, gatoRs accommodates variations in download structures between GBIF and iDigBio and allows user control through interactive cleaning steps. The pipeline aims to make biodiversity data processing efficient and accessible and is expected to benefit both experienced and novice users in the scientific community. Additionally, the package is a valuable tool for introducing classroom biodiversity concepts through herbarium specimens.

An often-overlooked component of biodiversity is the microbiota, the vast array of microorganisms that inhabit every corner of our world. These microscopic organisms play crucial roles in various ecosystems, contributing to nutrient cycling, decomposition of organic matter, and plant establishment and succession (Smith and Read, 2008; Diamini et al., 2022). Despite their importance, our understanding of microbiota remains limited, largely due to the challenges associated with studying them. In this context, the second paper in this issue introduces a new, cost-effective moist chamber culture technique designed to recover a broader spectrum of microbial species (Bordelon et al., 2024). This technique emphasizes its low-cost, accessible approach, addressing the need for more cost-effective research methods and the involvement of community scientists. Bordelon et al. (2024) provide a robust discussion on the environmental factors affecting microbiota on live tree bark, including examples of microbiota found on rough bark of live trees and considerations for smooth bark live trees in the context of myxomycete cultures. The importance of pH, water-holding capacity, and bark characteristics is explored, providing insights into the diversity and abundance of myxomycetes associated with different tree species (Bordelon et al., 2024).

In modern agriculture, the integration of advanced technologies such as remote sensing (Yang, 2020), DNA-based detection methods (Martinelli et al., 2015), and robotics and artificial intelligence (Balaska et al., 2023) has become increasingly important for enhancing crop management and mitigating the impact of plant diseases (Spadaro and Gullino, 2019). One prominent area of innovation is the application of computer vision (CV) (Ouhami et al., 2021). This dynamic field leverages the capabilities of machine learning to revolutionize the way we detect and respond to diseases affecting crops (Ahmed and Reddy, 2021). The significance of addressing plant pathogens is underscored by their potential to cause catastrophic consequences such as famine and economic collapse by rendering local cultivation unprofitable (Dai and Fan, 2022). The third paper in this issue provides a focused review on the increasing use of CV for precise disease detection and optimal pesticide application timing, featuring case studies from agricultural practices in cocoa production. Here, Sykes et al. (2024) underscore the advantages of CV, including cost reduction and prevention of misapplication, discussing financial and ecological implications. The analysis goes beyond previous work, exploring technical concepts in applying CV to plant pathology, training data acquisition, and insights into machine learning methods. The authors highlight the significance of curated training data, exploring computationally efficient techniques and providing a comparative analysis of model architectures. Furthermore, Sykes et al. (2024) discuss the evolving role of machine learning in optimizing pesticide application and provide a comprehensive perspective on applying CV in plant pathology, including practical considerations for data gathering and a roadmap for commercial implementation.

In addition to these large-scale methods, there is also scope for developing reliable, inexpensive, and easily accessible protocols for performing laboratory-based experiments. In this special issue, we highlight two simple and robust plant anatomy and physiology methods for settings with fewer resources and limited infrastructure.

Koch et al. (2024) expand on a method first described by Díaz Dominguez et al. (2022) for measuring lichen thalli hydrophobicity that requires only a micropipette, distilled water, a tripod, and a phone or camera, thereby providing a cost-effective and rapid way of assessing this functional trait. By analyzing 93 lichen taxa, the authors’ results support the method's efficacy in capturing a spectrum of hydrophobicity levels, including both highly hydrophilic and highly hydrophobic species. This method, which can be used with both fresh and archival material, emerges as a valuable and versatile tool for ecophysiology-based lichen trait assessment across climates, lichen species, and growth forms, and offers insights into its potential as a predictor of climate change effects.

The sectioning of plant material is a classic method that has been used extensively to obtain details of a wide variety of tissue structures, with applications in taxonomy and plant anatomy (for a comprehensive overview, see Yeung et al., 2016). Angeles and Madero-Vega (2024) share a low-cost sectioning medium created by dissolving biaxially oriented polypropylene (BOPP) in a commercially available polyurethane remover. The resulting BOPP syrup can be used for plant tissue sectioning, as well as for obtaining surface prints of both wood and leaf parts. BOPP is a plastic material widely used in the food industry for wrapping produce and other food items, and is usually seen as a waste product. Therefore, it is an attractive starting material for this low-cost method as it is widely available at no cost in many countries.

In summary, this special issue presents affordable and innovative approaches addressing challenges in biodiversity cataloging, microbiota discovery, agriculture, anatomy, and physiology. The gatoRs R package streamlines access to and use of digitized biodiversity data, while a cost-effective moist chamber culture technique enhances our understanding of microbiota. The integration of computer vision in agriculture, discussed by Sykes et al. (2024), demonstrates its potential for precise disease detection and pesticide application. Furthermore, the issue showcases accessible methods for lichen thalli hydrophobicity assessment and plant tissue sectioning, emphasizing simple and cost-effective ways to advance research in plant physiology and anatomy. Together, these contributions offer valuable insights and practical tools for researchers, educators, and community scientists in resource-limited settings. [Correction added on 8 April 2024 after first online publication: In the last paragraph, the sentence “The gatoRs R package streamlines the digitization of biodiversity data,…” was inaccurate. The sentence has been corrected.]

G.J.P. and G.H.D. initiated this special issue, and N.I.C. and A.Z.T. contributed to its development. G.J.P., N.I.C., and A.Z.T. acted as handling editors for manuscripts. G.H.D. wrote the first draft of this article, with contributions from all other authors.

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来源期刊
CiteScore
7.30
自引率
0.00%
发文量
50
审稿时长
12 weeks
期刊介绍: Applications in Plant Sciences (APPS) is a monthly, peer-reviewed, open access journal promoting the rapid dissemination of newly developed, innovative tools and protocols in all areas of the plant sciences, including genetics, structure, function, development, evolution, systematics, and ecology. Given the rapid progress today in technology and its application in the plant sciences, the goal of APPS is to foster communication within the plant science community to advance scientific research. APPS is a publication of the Botanical Society of America, originating in 2009 as the American Journal of Botany''s online-only section, AJB Primer Notes & Protocols in the Plant Sciences. APPS publishes the following types of articles: (1) Protocol Notes describe new methods and technological advancements; (2) Genomic Resources Articles characterize the development and demonstrate the usefulness of newly developed genomic resources, including transcriptomes; (3) Software Notes detail new software applications; (4) Application Articles illustrate the application of a new protocol, method, or software application within the context of a larger study; (5) Review Articles evaluate available techniques, methods, or protocols; (6) Primer Notes report novel genetic markers with evidence of wide applicability.
期刊最新文献
Issue Information An efficient and effective RNA extraction protocol for ferns florabr: An R package to explore and spatialize species distribution using Flora e Funga do Brasil Issue Information A unified framework to investigate and interpret hybrid and allopolyploid biodiversity across biological scales
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