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Non-invasive Probing of Winter Dormancy via Time-frequency Analysis of Induced Chlorophyll Fluorescence in Deciduous Plants as Exemplified by Apple (Malus × domestica Borkh.)

26 Sept 2022 · 10.20944/preprints202209.0395.v1

Abstract

Dormancy is a physiological state that confers winter hardiness to and orchestrates phenological phase progression in temperate perennial plants. Weather fluctuations caused by climate change increasingly disturb dormancy onset and release in many plant species including tree crops leading to aberrant growth, flowering, and fruiting. Currently, research in this field is impeded by the lack of affordable non-invasive methods for on-line monitoring of dormancy. We report on an automatic framework for low-cost, long-term, and scalable dormancy studies in deciduous plants. The proposed method is based on continuous near-field sensing of the photosynthetic activity of shoots via pulse-amplitude modulated chlorophyll fluorescence sensors connected remotely to a data processing system. The resulting high-resolution time series of JIP-test parameters indicative of the responsiveness of the photosynthetic apparatus to environmental stimuli are subjected to frequency-domain analysis. The proposed approach allows to overcome the variance coming from diurnal changes of insolation and to derive estimations on the depth of dormancy. Our approach was validated over three seasons in an experimental apple (Malus × domestica Borkh.) orchard by collating the non-invasive estimations with the results of traditional methods (growing of the cuttings obtained from the tress at different phases of dormancy) and the output of commonly used chilling requirement models. We discuss the advantages of the proposed monitoring framework such as prompt detection of freeze damages along with its potential limitations.

Plant phenotyping relevance

植物の休眠深度を非侵襲的に推定する蛍光センサーと時系列解析のフレームワークを開発し、従来法およびモデルと照合検証しており、表現型取得法が研究の中心である。

abstractWe report on an automatic framework for low-cost, long-term, and scalable dormancy studies in deciduous plants.
abstractThe proposed method is based on continuous near-field sensing of the photosynthetic activity of shoots via pulse-amplitude modulated chlorophyll fluorescence sensors connected remotely to a data processing system.
abstractOur approach was validated over three seasons in an experimental apple (Malus × domestica Borkh.) orchard by collating the non-invasive estimations with the results of traditional methods

Code and data availability

The authors state that the analysis code, accompanied by a subset of the data, is publicly available on GitHub. This is a paper-specific computational analysis asset for the chlorophyll fluorescence/JIP-test time-frequency analysis. The full raw data and derived parameters are only available on request, so they are not

Codepublic

ic projects in priority areas of scientific and technological development (grant number 075-15-2020-774). Data Availability Statement: The raw data and derived parameters are available from the corre- sponding author on reasonable request. Code used in the analysis, accompanied with a subset of the data, is available on GitHub (https://github.com/Lodinn/PAM-timeseries). Acknowledgments: The indoors chlorophyll fluorescence measurements were carried out at the Phototrophic Organisms Phenotyping user facilities of Lomonosov Moscow State University. The

Open resource ↗Lodinn/PAM-timeseries · pdf-layout-page:15 lines:1-58

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