title: Nondestructive and intuitive determination of circadian chlorophyll rhythms in soybean leaves using multispectral imaging.
abstract: The circadian clock, synchronized by daily cyclic environmental cues, regulates diverse aspects of plant growth and development and increases plant fitness. Even though much is known regarding the molecular mechanism of circadian clock, it remains challenging to quantify the temporal variation of major photosynthesis products as well as their metabolic output in higher plants in a real-time, nondestructive and intuitive manner. In order to reveal the spatial-temporal scenarios of photosynthesis and yield formation regulated by circadian clock, multispectral imaging technique has been employed for nondestructive determination of circadian chlorophyll rhythms in soybean leaves. By utilizing partial least square regression analysis, the determination coefficients R(2), 0.9483 for chlorophyll a and 0.8906 for chlorophyll b, were reached, respectively. The predicted chlorophyll contents extracted from multispectral data showed an approximately 24-h rhythm which could be entrained by external light conditions, consistent with the chlorophyll contents measured by chemical analyses. Visualization of chlorophyll map in each pixel offers an effective way to analyse spatial-temporal distribution of chlorophyll. Our results revealed the potentiality of multispectral imaging as a feasible nondestructive universal assay for examining clock function and robustness, as well as monitoring chlorophyll a and b and other biochemical components in plants.
authors.affiliation: School of Biotechnology and Food Engineering, Hefei University of Technology, Hefei 230009, China.
authors.forename: Wen-Juan
authors.initials: WJ
authors.lastname: Pan
authors.affiliation: School of Medical Engineering, Hefei University of Technology, Hefei 230009, China.
authors.forename: Xia
authors.initials: X
authors.lastname: Wang
authors.affiliation: Department of Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung 80424, Taiwan.
authors.forename: Yong-Ren
authors.initials: YR
authors.lastname: Deng
authors.affiliation: Department of Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung 80424, Taiwan.
authors.forename: Jia-Hang
authors.initials: JH
authors.lastname: Li
authors.affiliation: School of Biotechnology and Food Engineering, Hefei University of Technology, Hefei 230009, China.
authors.forename: Wei
authors.initials: W
authors.lastname: Chen
authors.affiliation: 1] Department of Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung 80424, Taiwan [2] Department of Healthcare Administration and Medical Informatics, Kaohsiung 80708, Taiwan.
authors.forename: John Y
authors.initials: JY
authors.lastname: Chiang
authors.affiliation: Rice Research Institute, Anhui Academy of Agricultural Sciences, Hefei 230031, China.
authors.forename: Jian-Bo
authors.initials: JB
authors.lastname: Yang
authors.affiliation: 1] School of Biotechnology and Food Engineering, Hefei University of Technology, Hefei 230009, China [2] School of Medical Engineering, Hefei University of Technology, Hefei 230009, China.
authors.forename: Lei
authors.initials: L
authors.lastname: Zheng
mesh_terms: D002734:Chlorophyll / Q000378:metabolism*; D002940:Circadian Rhythm; D018515:Plant Leaves / Q000378:metabolism / Q000502:physiology*; D013025:Glycine max / Q000378:metabolism / Q000502:physiology*
chemical_list: D002734:Chlorophyll