Assessment of germination performance and early seedling growth of Malaysian indica rice genotypes under drought conditions for strategic cropping during water scarcity

• Main Authors: Evamoni, Fatematuz Zuhura, Nulit, Rosimah, Yap, Chee Kong, Ibrahim, Mohd Hafiz, Sidek, Noorhazira
• Format: Article
• Published: Agricultural Research Institute, INIA 2023
• Online Access: http://psasir.upm.edu.my/id/eprint/106740/; https://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-58392023000300281&lng=en&nrm=iso&tlng=en

Drought is a major abiotic constraint on rice (Oryza sativa L.) production in Malaysia. Malaysian Agricultural Research and Development Institute (MARDI) has released more than 50 indica rice genotypes so far. However, little has been studied about their drought tolerance. The study aimed to evaluate the germination and early seedling growth performances of 15 rice genotypes under polyethylene glycol (PEG) 6000-induced drought stresses. Four osmotic potentials of PEG 6000 (0, -0.3, -0.6, -0.9 MPa) were used in the study denoted as control, low, moderate and severe stresses respectively. Data on seed germination percentage, germination index, germination energy, germination rate, seedling height, seedling vigor I and II, fresh and dry weight of seedlings were measured. Studied parameters varied greatly among genotypes with different osmotic stresses. The findings suggested most of the rice genotypes showed an apparent reduction in germination and growth traits, while MR211 showed less reduction under all of the stresses. The Multivariate clustering grouped genotypes into five different clusters, where cluster V (MR220, MR269, MR253, MR297, MR303 and MR284) incorporated six genotypes showed better germination and growth under different osmotic potentials, followed by cluster IV (MR211 and MR307). Cluster II incorporated one genotype MARDI WARNA98 which had minimal germination and growth attributes. Principal component analysis (PCA) was performed to identify the maximum contributing variables for diversity, revealed maximum variation by first two components (81.8 and 7.7) respectively. Therefore, PEG 6000 can be used as an efficient tool for discrimination and identification of drought tolerance in rice.