PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
April 1, 2017Journal of Experimental Botany31 citationsOpen Access

Phenotypic differences determine drought stress responses in ecotypes of Arundo donax adapted to different environments

View Full Paper
MAMastaneh AhrarDDDilyana DonevaMTMassimiliano Tattini

Key Points

Key points are not available for this paper at this time.

Abstract

Arundo donax has been identified as an important biomass and biofuel crop. Yet, there has been little research on photosynthetic and metabolic traits, which sustain the high productivity of A. donax under drought conditions. This study determined phenotypic differences between two A. donax ecotypes coming from stands with contrasting adaptation to dry climate. We hypothesized that the Bulgarian (BG) ecotype, adapted to drier conditions, exhibits greater drought tolerance than the Italian (IT) ecotype, adapted to a more mesic environment. Under well-watered conditions the BG ecotype was characterized by higher photosynthesis, mesophyll conductance, intrinsic water use efficiency, PSII efficiency, isoprene emission rate and carotenoids, whereas the IT ecotype showed higher levels of hydroxycinnamates. Photosynthesis of water-stressed plants was mainly limited by diffusional resistance to CO2 in BG, and by biochemistry in IT. Recovery of photosynthesis was more rapid and complete in BG than in IT, which may indicate better stability of the photosynthetic apparatus associated to enhanced induction of volatile and non-volatile isoprenoids and phenylpropanoid biosynthesis. This study shows that a large phenotypic plasticity among A. donax ecotypes exists, and may be exploited to compensate for the low genetic variability of this species when selecting plant productivity in constrained environments.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Ahrar et al. (2017) studied this question.

synapsesocial.com/papers/69d88d438c03fbaff8bef569https://doi.org/10.1093/jxb/erx125
Ask AI
Helpful
Bookmark
Share
View Full Paper