High Throughput Image-Based Phenotyping for Determining Morphological and Physiological Responses to Single and Combined Stresses in Potato

High throughput image-based phenotyping is a powerful tool to non-invasively determine the development and performance of plants under specific conditions over time. By using multiple imaging sensors, many traits of interest can be assessed, including plant biomass, photosynthetic efficiency, canopy temperature, and leaf reflectance indices. Plants are frequently exposed to multiple stresses under field conditions where severe heat waves, flooding, and drought events seriously threaten crop productivity. When stresses coincide, resulting effects on plants can be distinct due to synergistic or antagonistic interactions. To elucidate how potato plants respond to single and combined stresses that resemble naturally occurring stress scenarios, five different treatments were imposed on a selected potato cultivar (Solanum tuberosum L., cv. Lady Rosetta) at the onset of tuberization, i.e. control, drought, heat, waterlogging, and combinations of heat, drought, and waterlogging stresses. Our analysis shows that waterlogging stress had the most detrimental effect on plant performance, leading to fast and drastic physiological responses related to stomatal closure, including a reduction in the quantum yield and efficiency of photosystem II and an increase in canopy temperature and water index. Under heat and combined stress treatments, the relative growth rate was reduced in the early phase of stress. Under drought and combined stresses, plant volume and photosynthetic performance dropped with an increased temperature and stomata closure in the late phase of stress. The combination of optimized stress treatment under defined environmental conditions together with selected phenotyping protocols allowed to reveal the dynamics of morphological and physiological responses to single and combined stresses. Here, a useful tool is presented for plant researchers looking to identify plant traits indicative of resilience to several climate change-related stresses.

Bibliographic Details

Main Authors:	Abdelhakim, Lamis Osama Anwar, Pleskačová, Barbora, Rodriguez-Granados, Natalia Yaneth, Sasidharan, Rashmi, Perez-Borroto, Lucia Sandra, Sonnewald, Sophia, Gruden, Kristina, Vothknecht, Ute C., Teige, Markus, Panzarová, Klára
Format:	Article/Letter to editor biblioteca
Language:	English
Subjects:	Life Science,
Online Access:	https://research.wur.nl/en/publications/high-throughput-image-based-phenotyping-for-determining-morpholog
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