Agar-based polyethylene glycol (PEG) infusion model for pea (<em>Pisum sativum</em> L.) — perspectives of translation to legume crop plants

Abstract

Due to the oncoming climate changes water deficit represents one of the most important abiotic stressors which dramatically affects crop productivity worldwide. Because of their importance as the principal source of food protein, legumes attract a special interest of plant scientists. Moreover, legumes are involved in symbiotic association with rhizobial bacteria, which is morphologically localized to root nodules. These structures are critical for fixation of atmospheric nitrogen and highly sensitive to drought. Therefore, new drought-tolerant legume cultivars need to be developed to meet the growing food demand. However, this requires a comprehensive knowledge of the molecular mechanisms behind the plant stress response. To access these mechanisms, adequate and reliable drought stress models need to be established. The agar-based polyethylene glycol (PEG) infusion model allows a physiologically relevant reduction of soil water potential (Ψw), although it is restricted to seedlings and does not give access to proteomics and metabolomics studies. Earlier, we successfully overcame this limitation and optimized this model for mature Arabidopsis plants. Here we make the next step forward and address its application to one of the major crop legumes — pea. Using a broad panel of physiological and biochemical markers, we comprehensively prove the applicability of this setup to legumes. The patterns of drought-related physiological changes are well-interpretable and generally resemble the stress response of plants grown in soil-based stop-watering models. Thus, the proposed model can be efficiently used in the study of stress-related metabolic adjustment in green parts, roots and root nodules of juvenile and flowering plants.

Monitoring Drought Stress in Common Bean Using Chlorophyll Fluorescence and Multispectral Imaging

“…There are many experimental setups to induce and monitor drought stress. The most commonly used are soil-based drought models [ 20 , 21 ], which are based on the gradual decline or immediate interruption of plant watering, and agar-based models (widely used in plant biology) [ 22 , 23 ]. Drought stress can be monitored by relative water content, osmotic adjustment, various physiological responses (efficiency of photosynthesis and stomatal conductance), and, increasingly, by chlorophyll fluorescence and multispectral imaging [ 24 , 25 ].…”