Evaluation of selected rice cultivars' phenotypic traits and chlorophyll content under sub-mergence stress

Abstract

Currently, rice production in Nigeria is on the increase with the aim of meeting the nation’s need but floods (mainly seasonal) has been among the major factors limiting rice production. Rice is generally a semi aquatic plant well adapted to partially flooded fields but flash flooding may leads to complete submergence there by resulting into huge economic losses mainly due to reduction in gases (hypoxia) and light intensity needed for photosynthesis. The research was conducted at the Biological Garden, Department of Biological Sciences, Federal University Birnin Kebbi. The experiment was set off in a Completely Randomized Design (CRD) consisting of four rice cultivars with control and three replications. Length of internodes, number of nodes per plant, plant height, root length and chlorophyll contents were evaluated using standard methods and protocols. The study analyzed the impact of flooding on rice cultivars, finding significant differences in node number, internode length, plant height, root lengths, and chlorophyll content. The highest number of nodes was found in CP Yartunga, followed by Faro with 6.33 per plant. The highest plant height was 15.50 cm in Faro, while the highest chlorophyll content was 0.41 mg/g in CP 44. The research reveals that rice cultivars recover from flooding stress, with CP Yartunga having the highest number of nodes per plant and Faro having the highest internode length. No significant differences were found in plant height, root length, or chlorophyll content among the evaluated cultivars. Faro had the lowest chlorophyll content. The study reveals that under stress, chlorophyll content in various locations decreases significantly, with a significant drop in recovery and node numbers. Lastly, node recovery is substantial, suggesting lower injury levels. The present study suggests that cultivars like Faro and CP 44 show better resilience, suggesting potential breeding programs focusing on structural traits.