Accurate inference of shoot biomass from high-throughput images of cereal plants

<p>Abstract</p> <p>With the establishment of advanced technology facilities for high throughput plant phenotyping, the problem of estimating plant biomass of individual plants from their two dimensional images is becoming increasingly important. The approach predominantly cited in...

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Main Authors: Tester Mark, Roy Stuart, Berger Bettina, Rajendran Karthika, Frick Ross A, Golzarian Mahmood R, Lun Desmond S
Format: Article
Language:English
Published: BMC 2011-02-01
Series:Plant Methods
Online Access:http://www.plantmethods.com/content/7/1/2
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spelling doaj-3d7555ad423046acb780290790c80d3b2020-11-25T00:14:39ZengBMCPlant Methods1746-48112011-02-0171210.1186/1746-4811-7-2Accurate inference of shoot biomass from high-throughput images of cereal plantsTester MarkRoy StuartBerger BettinaRajendran KarthikaFrick Ross AGolzarian Mahmood RLun Desmond S<p>Abstract</p> <p>With the establishment of advanced technology facilities for high throughput plant phenotyping, the problem of estimating plant biomass of individual plants from their two dimensional images is becoming increasingly important. The approach predominantly cited in literature is to estimate the biomass of a plant as a linear function of the projected shoot area of plants in the images. However, the estimation error from this model, which is solely a function of projected shoot area, is large, prohibiting accurate estimation of the biomass of plants, particularly for the salt-stressed plants. In this paper, we propose a method based on plant specific weight for improving the accuracy of the linear model and reducing the estimation bias (the difference between actual shoot dry weight and the value of the shoot dry weight estimated with a predictive model). For the proposed method in this study, we modeled the plant shoot dry weight as a function of plant area and plant age. The data used for developing our model and comparing the results with the linear model were collected from a completely randomized block design experiment. A total of 320 plants from two bread wheat varieties were grown in a supported hydroponics system in a greenhouse. The plants were exposed to two levels of hydroponic salt treatments (NaCl at 0 and 100 mM) for 6 weeks. Five harvests were carried out. Each time 64 randomly selected plants were imaged and then harvested to measure the shoot fresh weight and shoot dry weight. The results of statistical analysis showed that with our proposed method, most of the observed variance can be explained, and moreover only a small difference between actual and estimated shoot dry weight was obtained. The low estimation bias indicates that our proposed method can be used to estimate biomass of individual plants regardless of what variety the plant is and what salt treatment has been applied. We validated this model on an independent set of barley data. The technique presented in this paper may extend to other plants and types of stresses.</p> http://www.plantmethods.com/content/7/1/2
collection DOAJ
language English
format Article
sources DOAJ
author Tester Mark
Roy Stuart
Berger Bettina
Rajendran Karthika
Frick Ross A
Golzarian Mahmood R
Lun Desmond S
spellingShingle Tester Mark
Roy Stuart
Berger Bettina
Rajendran Karthika
Frick Ross A
Golzarian Mahmood R
Lun Desmond S
Accurate inference of shoot biomass from high-throughput images of cereal plants
Plant Methods
author_facet Tester Mark
Roy Stuart
Berger Bettina
Rajendran Karthika
Frick Ross A
Golzarian Mahmood R
Lun Desmond S
author_sort Tester Mark
title Accurate inference of shoot biomass from high-throughput images of cereal plants
title_short Accurate inference of shoot biomass from high-throughput images of cereal plants
title_full Accurate inference of shoot biomass from high-throughput images of cereal plants
title_fullStr Accurate inference of shoot biomass from high-throughput images of cereal plants
title_full_unstemmed Accurate inference of shoot biomass from high-throughput images of cereal plants
title_sort accurate inference of shoot biomass from high-throughput images of cereal plants
publisher BMC
series Plant Methods
issn 1746-4811
publishDate 2011-02-01
description <p>Abstract</p> <p>With the establishment of advanced technology facilities for high throughput plant phenotyping, the problem of estimating plant biomass of individual plants from their two dimensional images is becoming increasingly important. The approach predominantly cited in literature is to estimate the biomass of a plant as a linear function of the projected shoot area of plants in the images. However, the estimation error from this model, which is solely a function of projected shoot area, is large, prohibiting accurate estimation of the biomass of plants, particularly for the salt-stressed plants. In this paper, we propose a method based on plant specific weight for improving the accuracy of the linear model and reducing the estimation bias (the difference between actual shoot dry weight and the value of the shoot dry weight estimated with a predictive model). For the proposed method in this study, we modeled the plant shoot dry weight as a function of plant area and plant age. The data used for developing our model and comparing the results with the linear model were collected from a completely randomized block design experiment. A total of 320 plants from two bread wheat varieties were grown in a supported hydroponics system in a greenhouse. The plants were exposed to two levels of hydroponic salt treatments (NaCl at 0 and 100 mM) for 6 weeks. Five harvests were carried out. Each time 64 randomly selected plants were imaged and then harvested to measure the shoot fresh weight and shoot dry weight. The results of statistical analysis showed that with our proposed method, most of the observed variance can be explained, and moreover only a small difference between actual and estimated shoot dry weight was obtained. The low estimation bias indicates that our proposed method can be used to estimate biomass of individual plants regardless of what variety the plant is and what salt treatment has been applied. We validated this model on an independent set of barley data. The technique presented in this paper may extend to other plants and types of stresses.</p>
url http://www.plantmethods.com/content/7/1/2
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