Assessment of Drought and Zinc Stress Tolerance of Novel Miscanthus Hybrids and Arundo donax Clones Using Physiological, Biochemical, and Morphological Traits

Biology (Basel). 2023 Dec 14;12(12):1525. doi: 10.3390/biology12121525.

Abstract

High-yield potential perennial crops, such as Miscanthus spp. and Arundo donax are amongst the most promising sources of sustainable biomass for bioproducts and bioenergy. Although several studies assessed the agronomic performance of these species on diverse marginal lands, research to date on drought and zinc (Zn) resistance is scarce. Thus, the objective of this study was to investigate the drought and Zn stress tolerance of seven novel Miscanthus hybrids and seven Arundo clones originating from different parts of Italy. We subjected both species to severe drought (less than 30%), and Zn stress (400 mg/kg-1 of ZnSO4) separately, after one month of growth. All plants were harvested after 28 days of stress, and the relative drought and Zn stress tolerance were determined by using a set of morpho-physio-biochemical and biomass attributes in relation to stress tolerance indices (STI). Principal component analysis (PCA), hierarchical clustering analysis (HCA) and stress tolerance indices (STI) were performed for each morpho-physio-biochemical and biomass parameters and showed significant relative differences among the seven genotypes of both crops. Heatmaps of these indices showed how the different genotypes clustered into four groups. Considering PCA ranking value, Miscanthus hybrid GRC10 (8.11) and Arundo clone PC1 (11.34) had the highest-ranking value under both stresses indicating these hybrids and clones are the most tolerant to drought and Zn stress. In contrast, hybrid GRC3 (-3.33 lowest ranking value) and clone CT2 (-5.84) were found to be the most sensitive to both drought and Zn stress.

Keywords: Arundo clones; Miscanthus hybrids; Zn tolerance; bioenergy; drought tolerance; growth parameters; hierarchical clustering analysis (HCA); plant physiology; principal component analysis (PCA).