title: Quantifying the Onset and Progression of Plant Senescence by Color Image Analysis for High Throughput Applications.
abstract: Leaf senescence, an indicator of plant age and ill health, is an important phenotypic trait for the assessment of a plant's response to stress. Manual inspection of senescence, however, is time consuming, inaccurate and subjective. In this paper we propose an objective evaluation of plant senescence by color image analysis for use in a high throughput plant phenotyping pipeline. As high throughput phenotyping platforms are designed to capture whole-of-plant features, camera lenses and camera settings are inappropriate for the capture of fine detail. Specifically, plant colors in images may not represent true plant colors, leading to errors in senescence estimation. Our algorithm features a color distortion correction and image restoration step prior to a senescence analysis. We apply our algorithm to two time series of images of wheat and chickpea plants to quantify the onset and progression of senescence. We compare our results with senescence scores resulting from manual inspection. We demonstrate that our procedure is able to process images in an automated way for an accurate estimation of plant senescence even from color distorted and blurred images obtained under high throughput conditions.
authors.affiliation: Phenomics and Bioinformatics Research Centre, University of South Australia, Mawson Lakes, SA 5095, Australia.
authors.forename: Jinhai
authors.initials: J
authors.lastname: Cai
authors.affiliation: Australian Centre for Plant Functional Genomics, University of Adelaide, Hartley Grove, Urrbrae SA 5064, Australia.
authors.forename: Mamoru
authors.initials: M
authors.lastname: Okamoto
authors.affiliation: Australian Centre for Plant Functional Genomics, University of Adelaide, Hartley Grove, Urrbrae SA 5064, Australia.
authors.forename: Judith
authors.initials: J
authors.lastname: Atieno
authors.affiliation: South Australian Research and Development Institute, 2b Hartley Grove, Urrbrae SA 5064, Australia.
authors.forename: Tim
authors.initials: T
authors.lastname: Sutton
authors.affiliation: Australian Centre for Plant Functional Genomics, University of Adelaide, Hartley Grove, Urrbrae SA 5064, Australia.
authors.forename: Yongle
authors.initials: Y
authors.lastname: Li
authors.affiliation: Phenomics and Bioinformatics Research Centre, University of South Australia, Mawson Lakes, SA 5095, Australia.
authors.forename: Stanley J
authors.initials: SJ
authors.lastname: Miklavcic
mesh_terms: D000465:Algorithms; D029863:Cicer / Q000254:growth & development; D003116:Color; D057166:High-Throughput Screening Assays / Q000379:methods; D061848:Optical Imaging / Q000295:instrumentation / Q000379:methods*; D063245:Plant Development; D014908:Triticum / Q000254:growth & development