{"title":"A GIS-based method for the analysis of digital rhizotron images","authors":"C. Gasch, T. Collier, S. Enloe, S. Prager","doi":"10.3117/PLANTROOT.5.69","DOIUrl":null,"url":null,"abstract":"Quantification of belowground plant response via rhizotron root image analysis is difficult and time-consuming, yet a plant's root response is of great interest to many researchers. Here, we present an automated, time efficient method for examining digital rhizotron images. A total of 285 digital images (218 mm by 300 mm) were collected using a flatbed scanner from 16 rhizotron boxes from an experiment designed to evaluate the root response of Dalmatian toadflax, Linaria dalmatica (L.) Miller to herbivory by the Dalmatian toadflax stem mining weevil, Mecinus janthinus Germar, a widely used biological control agent. Images were quantified for root length and area using two methods: manually digitizing images using Root Measurement System (RMS) software, and semi- automated analysis using Feature Analyst™, an extension for a geographic information system. Feature Analyst length and area values were highly positively correlated with RMS area values, but were not correlated with RMS length measurements. The semi-automated Feature Analyst approach required one-eighth of the time required to analyze images using the manual RMS method. Feature Analyst for digital image analysis warrants more investigation, but appears to be a promising method for quantifying belowground plant characteristics.","PeriodicalId":20205,"journal":{"name":"Plant Root","volume":"5 1","pages":"69-78"},"PeriodicalIF":1.0000,"publicationDate":"2011-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3117/PLANTROOT.5.69","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Plant Root","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3117/PLANTROOT.5.69","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"PLANT SCIENCES","Score":null,"Total":0}
引用次数: 7
Abstract
Quantification of belowground plant response via rhizotron root image analysis is difficult and time-consuming, yet a plant's root response is of great interest to many researchers. Here, we present an automated, time efficient method for examining digital rhizotron images. A total of 285 digital images (218 mm by 300 mm) were collected using a flatbed scanner from 16 rhizotron boxes from an experiment designed to evaluate the root response of Dalmatian toadflax, Linaria dalmatica (L.) Miller to herbivory by the Dalmatian toadflax stem mining weevil, Mecinus janthinus Germar, a widely used biological control agent. Images were quantified for root length and area using two methods: manually digitizing images using Root Measurement System (RMS) software, and semi- automated analysis using Feature Analyst™, an extension for a geographic information system. Feature Analyst length and area values were highly positively correlated with RMS area values, but were not correlated with RMS length measurements. The semi-automated Feature Analyst approach required one-eighth of the time required to analyze images using the manual RMS method. Feature Analyst for digital image analysis warrants more investigation, but appears to be a promising method for quantifying belowground plant characteristics.
期刊介绍:
Plant Root publishes original papers, either theoretical or experimental, that provide novel insights into plant roots. The Journal’s subjects include, but are not restricted to, anatomy and morphology, cellular and molecular biology, biochemistry, physiology, interactions with soil, mineral nutrients, water, symbionts and pathogens, food culture, together with ecological, genetic and methodological aspects related to plant roots and rhizosphere. Work at any scale, from the molecular to the community level, is welcomed.