4.7 Article

Overcoming Physiological Bottlenecks of Leaf Vitality and Root Development in Cuttings: A Systemic Perspective

Journal

FRONTIERS IN PLANT SCIENCE
Volume 11, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fpls.2020.00907

Keywords

internal quality; senescence; adventitious rooting; plant development; phytohormones; primary metabolism; environment; modeling

Categories

Funding

  1. German Federal Ministry of Food and Agriculture (BMEL) - Federal Office for Agriculture and Food (BLE) [2818HSE02]

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Each year, billions of ornamental young plants are produced worldwide from cuttings that are harvested from stock plants and planted to form adventitious roots. Depending on the plant genotype, the maturation of the cutting, and the particular environment, which is complex and often involves intermediate storage of cuttings under dark conditions and shipping between different climate regions, induced senescence or abscission of leaves and insufficient root development can impair the success of propagation and the quality of generated young plants. Recent findings on the molecular and physiological control of leaf vitality and adventitious root formation are integrated into a systemic perspective on improved physiologically-based control of cutting propagation. The homeostasis and signal transduction of the wound responsive plant hormones ethylene and jasmonic acid, of auxin, cytokinins and strigolactones, and the carbon-nitrogen source-sink balance in cuttings are considered as important processes that are both, highly responsive to environmental inputs and decisive for the development of cuttings. Important modules and bottlenecks of cutting function are identified. Critical environmental inputs at stock plant and cutting level are highlighted and physiological outputs that can be used as quality attributes to monitor the functional capacity of cuttings and as response parameters to optimize the cutting environment are discussed. Facing the great genetic diversity of ornamental crops, a physiologically targeted approach is proposed to define bottleneck-specific plant groups. Components from the field of machine learning may help to mathematically describe the complex environmental response of specific plant species.

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