Applications in Plant Sciences最新文献

{"title":"From leaves to labels: Building modular machine learning networks for rapid herbarium specimen analysis with LeafMachine2","authors":"William N. Weaver,&nbsp;Stephen A. Smith","doi":"10.1002/aps3.11548","DOIUrl":"10.1002/aps3.11548","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Premise</h3>\u0000 \u0000 <p>Quantitative plant traits play a crucial role in biological research. However, traditional methods for measuring plant morphology are time consuming and have limited scalability. We present LeafMachine2, a suite of modular machine learning and computer vision tools that can automatically extract a base set of leaf traits from digital plant data sets.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>LeafMachine2 was trained on 494,766 manually prepared annotations from 5648 herbarium images obtained from 288 institutions and representing 2663 species; it employs a set of plant component detection and segmentation algorithms to isolate individual leaves, petioles, fruits, flowers, wood samples, buds, and roots. Our landmarking network automatically identifies and measures nine pseudo-landmarks that occur on most broadleaf taxa. Text labels and barcodes are automatically identified by an archival component detector and are prepared for optical character recognition methods or natural language processing algorithms.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>LeafMachine2 can extract trait data from at least 245 angiosperm families and calculate pixel-to-metric conversion factors for 26 commonly used ruler types.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Discussion</h3>\u0000 \u0000 <p>LeafMachine2 is a highly efficient tool for generating large quantities of plant trait data, even from occluded or overlapping leaves, field images, and non-archival data sets. Our project, along with similar initiatives, has made significant progress in removing the bottleneck in plant trait data acquisition from herbarium specimens and shifted the focus toward the crucial task of data revision and quality control.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"11 5","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71432179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rapid imaging in the field followed by photogrammetry digitally captures the otherwise lost dimensions of plant specimens","authors":"Nicole James,&nbsp;Alex Adkinson,&nbsp;Austin Mast","doi":"10.1002/aps3.11547","DOIUrl":"10.1002/aps3.11547","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Premise</h3>\u0000 \u0000 <p>We recognized the need for a customized imaging protocol for plant specimens at the time of collection for the purpose of three-dimensional (3D) modeling, as well as the lack of a broadly applicable photogrammetry protocol that encompasses the heterogeneity of plant specimen geometries and the challenges introduced by processes such as wilting.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods and Results</h3>\u0000 \u0000 <p>We developed an equipment list and set of detailed protocols describing how to capture images of plant specimens in the field prior to their deformation (e.g., with pressing) and how to produce a 3D model from the image sets in Agisoft Metashape Professional.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The equipment list and protocols represent a foundation on which additional improvements can be made for specimen geometries outside of the range of the six types considered, and an easy entry into photogrammetry for those who have not previously used it.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"11 5","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71419883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A pipeline for the rapid collection of color data from photographs","authors":"Yvonne Luong,&nbsp;Ariel Gasca-Herrera,&nbsp;Tracy M. Misiewicz,&nbsp;Benjamin E. Carter","doi":"10.1002/aps3.11546","DOIUrl":"10.1002/aps3.11546","url":null,"abstract":"Abstract Premise There are relatively few studies of flower color at landscape scales that can address the relative importance of competing mechanisms (e.g., biotic: pollinators; abiotic: ultraviolet radiation, drought stress) at landscape scales. Methods We developed an R shiny pipeline to sample color from images that were automatically downloaded using query results from a search using iNaturalist or the Global Biodiversity Information Facility (GBIF). The pipeline was used to sample ca. 4800 North American wallflower (Erysimum, Brassicaceae) images from iNaturalist. We tested whether flower color was distributed non‐randomly across the landscape and whether spatial patterns were correlated with climate. We also used images including ColorCheckers to compare analyses of raw images to color‐calibrated images. Results Flower color was strongly non‐randomly distributed spatially, but did not correlate strongly with climate, with most of the variation explained instead by spatial autocorrelation. However, finer‐scale patterns including local correlations between elevation and color were observed. Analyses using color‐calibrated and raw images revealed similar results. Discussion This pipeline provides users the ability to rapidly capture color data from iNaturalist images and can be a useful tool in detecting spatial or temporal changes in color using citizen science data.","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"11 5","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71419879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"FieldPrism: A system for creating snapshot vouchers from field images using photogrammetric markers and QR codes","authors":"William N. Weaver,&nbsp;Stephen A. Smith","doi":"10.1002/aps3.11545","DOIUrl":"10.1002/aps3.11545","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Premise</h3>\u0000 \u0000 <p>Field images are important sources of information for research in the natural sciences. However, images that lack photogrammetric scale bars, including most iNaturalist observations, cannot yield accurate trait measurements. We introduce FieldPrism, a novel system of photogrammetric markers, QR codes, and software to automate the curation of snapshot vouchers.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods and Results</h3>\u0000 \u0000 <p>Our photogrammetric background templates (FieldSheets) increase the utility of field images by providing machine-readable scale bars and photogrammetric reference points to automatically correct image distortion and calculate a pixel-to-metric conversion ratio. Users can generate a QR code flipbook derived from a specimen identifier naming hierarchy, enabling machine-readable specimen identification for automatic file renaming. We also developed FieldStation, a Raspberry Pi–based mobile imaging apparatus that records images, GPS location, and metadata redundantly on up to four USB storage devices and can be monitored and controlled from any Wi-Fi connected device.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>FieldPrism is a flexible software tool designed to standardize and improve the utility of images captured in the field. When paired with the optional FieldStation, researchers can create a self-contained mobile imaging apparatus for quantitative trait data collection.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"11 5","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71419881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A maceration technique for soft plant tissue without hazardous chemicals","authors":"Phillip C. Klahs,&nbsp;Elizabeth K. McMurchie,&nbsp;Jordan J. Nikkel,&nbsp;Lynn G. Clark","doi":"10.1002/aps3.11543","DOIUrl":"10.1002/aps3.11543","url":null,"abstract":"Abstract Premise Current methods for maceration of plant tissue use hazardous chemicals. The new method described here improves the safety of dissection and maceration of soft plant tissues for microscopic imaging by using the harmless enzyme pectinase. Methods and Results Leaf material from a variety of land plants was obtained from living plants and dried herbarium specimens. Concentrations of aqueous pectinase and soaking schedules were optimized, and tissues were manually dissected while submerged in fresh solution following a soaking period. Most leaves required 2–4 h of soaking; however, delicate leaves could be macerated after 30 min while tougher leaves required 12 h to 3 days of soaking. Staining techniques can also be used with this method, and permanent or semi‐permanent slides can be prepared. The epidermis, vascular tissue, and individual cells were imaged at magnifications of 10× to 400×. Only basic safety precautions were needed. Conclusions This pectinase method is a cost‐effective and safe way to obtain images of epidermal peels, separated tissues, or isolated cells from a wide range of plant taxa.","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"11 5","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71419866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatially resolved detection of small molecules from press-dried plant tissue using MALDI imaging","authors":"Zane G. Long,&nbsp;Jonathan V. Le,&nbsp;Benjamin B. Katz,&nbsp;Belen G. Lopez,&nbsp;Emily D. Tenenbaum,&nbsp;Bonnie Semmling,&nbsp;Ryan J. Schmidt,&nbsp;Felix Grün,&nbsp;Carter T. Butts,&nbsp;Rachel W. Martin","doi":"10.1002/aps3.11539","DOIUrl":"10.1002/aps3.11539","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Premise</h3>\u0000 \u0000 <p>Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) is a chemical imaging method that can visualize spatial distributions of particular molecules. Plant tissue imaging has so far mostly used cryosectioning, which can be impractical for the preparation of large-area imaging samples, such as full flower petals. Imaging unsectioned plant tissue presents its own difficulties in extracting metabolites to the surface due to the waxy cuticle.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We address this by using established delipidation techniques combined with a solvent vapor extraction prior to applying the matrix with many low-concentration sprays.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Using this procedure, we imaged tissue from three different plant species (two flowers and one carnivorous plant leaf). Material factorization analysis of the resulting data reveals a wide range of plant-specific small molecules with varying degrees of localization to specific portions of the tissue samples, while facilitating detection and removal of signal from background sources.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>This work demonstrates applicability of MALDI-MSI to press-dried plant samples without freezing or cryosectioning, setting the stage for spatially resolved molecule identification. Increased mass resolution and inclusion of tandem mass spectrometry are necessary next steps to allow more specific and reliable compound identification.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"11 5","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71419884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A comparison of methods for excluding light from stems to evaluate stem photosynthesis","authors":"Nadia A. Valverdi,&nbsp;Camilla Acosta,&nbsp;Gabriella R. Dauber,&nbsp;Gregory R. Goldsmith,&nbsp;Eleinis Ávila-Lovera","doi":"10.1002/aps3.11542","DOIUrl":"10.1002/aps3.11542","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Premise</h3>\u0000 \u0000 <p>A comparison of methods using different materials to exclude light from stems to prevent stem CO₂ exchange (i.e., photosynthesis), without affecting stem conductance to water vapor, surface temperature, and relative humidity, was conducted on stems of avocado trees in California.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods and Results</h3>\u0000 \u0000 <p>The experiment featured three materials: aluminum foil, paper-based wrap, and mineral-based paint. We examined stem CO₂ exchange with and without the light exclusion treatments. We also examined stem surface temperature, relative humidity, and photosynthetic active radiation (PAR) under the cover materials. All materials reduced PAR and stem CO₂ exchange. However, aluminum foil reduced stem surface temperature and increased relative humidity.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Methods used to study stem CO₂ exchange through light exclusion have historically relied on methods that may induce experimental artifacts. Among the methods tested here, mineral-based paint effectively reduced PAR without affecting stem surface temperature and relative humidity around the stem.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"11 6","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://bsapubs.onlinelibrary.wiley.com/doi/epdf/10.1002/aps3.11542","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43884912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction to GOgetter: A pipeline for summarizing and visualizing GO slim annotations for plant genetic data","authors":"","doi":"10.1002/aps3.11544","DOIUrl":"10.1002/aps3.11544","url":null,"abstract":"<p>Sessa, E. B., R. R. Masalia, N. Arrigo, M. S. Barker, and J. A. Pelosi. 2023. GOgetter: A pipeline for summarizing and visualizing GO slim annotations for plant genetic data. <i>Applications in Plant Sciences</i> 11(4): e11536.</p><p>In the Acknowledgments, a grant number was left out of the sentence “Funding was provided by the National Science Foundation (DEB #1844930 to E.B.S.).” This should have read “Funding was provided by the National Science Foundation (DEB #1844930 and IOS #2310485 to E.B.S.).”</p><p>We apologize for this error.</p>","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"11 5","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41986151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"RootBot: High-throughput root stress phenotyping robot","authors":"Mia Ruppel,&nbsp;Sven K. Nelson,&nbsp;Grace Sidberry,&nbsp;Madison Mitchell,&nbsp;Daniel Kick,&nbsp;Shawn K. Thomas,&nbsp;Katherine E. Guill,&nbsp;Melvin J. Oliver,&nbsp;Jacob D. Washburn","doi":"10.1002/aps3.11541","DOIUrl":"10.1002/aps3.11541","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Premise</h3>\u0000 \u0000 <p>Higher temperatures across the globe are causing an increase in the frequency and severity of droughts. In agricultural crops, this results in reduced yields, financial losses, and increased food costs at the supermarket. Root growth maintenance in drying soils plays a major role in a plant's ability to survive and perform under drought, but phenotyping root growth is extremely difficult due to roots being under the soil.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods and Results</h3>\u0000 \u0000 <p>RootBot is an automated high-throughput phenotyping robot that eliminates many of the difficulties and reduces the time required for performing drought-stress studies on primary roots. RootBot simulates root growth conditions using transparent plates to create a gap that is filled with soil and polyethylene glycol (PEG) to simulate low soil moisture. RootBot has a gantry system with vertical slots to hold the transparent plates, which theoretically allows for evaluating more than 50 plates at a time. Software pipelines were also co-opted, developed, tested, and extensively refined for running the RootBot imaging process, storing and organizing the images, and analyzing and extracting data.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The RootBot platform and the lessons learned from its design and testing represent a valuable resource for better understanding drought tolerance mechanisms in roots, as well as for identifying breeding and genetic engineering targets for crop plants.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"11 6","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://bsapubs.onlinelibrary.wiley.com/doi/epdf/10.1002/aps3.11541","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41711925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction to “A comparison of freezer-stored DNA and herbarium tissue samples for chloroplast assembly and genome skimming”","authors":"","doi":"10.1002/aps3.11540","DOIUrl":"10.1002/aps3.11540","url":null,"abstract":"<p>McAssey, E. V., Downs, C., Yorkston, M., Morden, C., and Heyduk, K. 2023. A comparison of freezer-stored DNA and herbarium tissue samples for chloroplast assembly and genome skimming. <i>Applications in Plant Sciences</i> 11(3): e11527</p><p>A statistical error was found after article publication. The relevant text from the Results section is provided below, with the corrected values shown in bold text. The error does not affect the findings of the study.</p><p>“Herbarium tissue library samples had significantly smaller insert sizes of mapped chloroplast reads compared to their freezer-stored DNA paired samples, taking into account covariates of read numbers and year (<b><i>F</i>_1,25 = 229.243</b>, <i><b>P</b></i> &lt; <b>0.001</b>). There was also a significant interaction effect between library size and sampling year (<b><i>F</i>_1,25 = 9.753</b>, <i>P</i> &lt; 0.01). Similarly, herbarium tissue samples also had higher amounts of adapter sequences in the reads (<b><i>F</i>_1,25 = 85.009</b>, <i>P</i> &lt; 0.001), with sampling year a significant covariate in the model (<b><i>F</i>_1,25 = 6.378</b>, <i>P</i> &lt; 0.05).”</p><p>We apologize for this error.</p>","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"11 4","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10439819/pdf/APS3-11-e11540.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10034571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}