Impacts of zebra chip disease and irrigation on leaf physiological traits in potato

Authors: RHO, HYUNGMIN - National Taiwan University; Oshaughnessy, Susan; Colaizzi, Paul; WORKNEH, FEKEDE - Texas A&M Agrilife; PAETZOLD, LI - Texas A&M Agrilife; RUSH, CHARLES - Texas A&M Agrilife

Submitted to: Agricultural Water Management
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/4/2022
Publication Date: 5/20/2022
Citation: Rho, H., O'Shaughnessy, S.A., Colaizzi, P.D., Workneh, F., Paetzold, L., Rush, C.M. 2022. Impacts of zebra chip disease and irrigation on leaf physiological traits in potato. Agricultural Water Management. 269. Article 107705. https://doi.org/10.1016/j.agwat.2022.107705.
DOI: https://doi.org/10.1016/j.agwat.2022.107705

Interpretive Summary: In the Texas High Plains region, water for crop production is limited and farmers are exploring potato production to improve the value of available irrigation water. However, Zebra Chip disease is prevalent throughout the region and plants infested by the disease produce smaller yields or brown streaked tubers that are not marketable. Farmers also waste water by continuing to irrigate. Early detection of the disease in plants would help improve water use efficiency. Scientists from ARS and Texas A&M AgriLife investigated the use of direct and indirect plant measurements for early detection of Zebra Chip disease. Larger differences between canopy and air temperature were found in infested plants as compared with non-infested plants. This finding indicates that monitoring potato canopy temperature can be a method for early detection of Zebra Chip disease.

Technical Abstract: Zebra chip disease (ZC) is caused by the fastidious, phloem-limited, bacterial pathogen ‘Candidatus Liberibacter solanacearum (Lso), which is transmitted from plant to plant by the potato psyllid (Bactericera cockerelli (Sulc)). Understanding how ZC impacts potato (Solanum tuberosum L.) physiology, could help growers in making more informed crop management decisions. Measurements of instantaneous leaf physiological responses, such as photosynthetic carbon dioxide uptake and water release on the leaf surface, can be used not only for fast screening of affected plants in the field but also for optimizing irrigation management. Over the 2019 and 2020 field seasons, we characterized time-course photosynthetic physiological responses of potato plants infested by potato psyllids (Bactericera cockerelli (Sulc)) carrying the Lso haplotypes A+B. Potato plants were subjected to different variable-rate irrigation (VRI) treatments (100 percent, 80 percent, and 60 percent of field capacity of the soil) through a center-pivot sprinkler system to examine the impact of the disease on key physiological parameters of photosynthesis and transpiration. Leaf and air temperatures, and hyperspectral profiles of the canopy were also measured and compared. The measurements were made during midday weekly from 25 to 50 days after plant infestation (DAI) with bacteriliferous psyllids. The results showed that many of the measured variables, including stomatal conductance, photosynthesis rate, transpiration rate, quantum yields, and normalized difference in vegetation index started to decrease beginning approximately 28 to 35 DAI, gradually worsening until 50 DAI, in both 2019 and 2020, as the infection proceeded. The decreases in stomatal conductance in infected plants led to decreases in photosynthesis and transpiration. In turn, reduced transpiration resulted in increased leaf temperature due to decrease in evaporative cooling on the leaf surface. Higher leaf temperatures under hot and dry conditions with high light intensity during the daytime would further reduce photosynthetic light harvesting, which is supported by our data, indicating the damage to the photosynthetic pigment formation and machinery. These findings support the previous report that increased leaf temperature in infected plants may have been derived from the closure of stomata in hypersensitive reactions to infection. These stomatal responses were detected within 28 DAI, a week earlier than the differences in hyperspectral profiles observed 35 DAI, and could be implemented in early disease detection strategies using measurements of leaf temperature.