Exploring the physiological basis of yield enhancement in New Generation Rice (NGR): a comparative assessment with non-NGR rice genotypes

Autor: Panda, Babyrani, Mondal, Subhankar, Mohanty, Ashish, Senapaty, Jeetendra, Meher, Jitendriya, Sahoo, Chitta R., Samal, Kailash C., Dash, Manasi, Chakraborty, Koushik, Dash, Sushanta K.
Zdroj: Plant Physiology Reports; December 2023, Vol. 28 Issue: 4 p543-555, 13p
Abstrakt: As the research is progressing toward sustainable yield increment with minimal environmental impact, the breeding of New Generation Rice (NGR) has emerged as a promising strategy that is based on the ideotype concept. We performed a study to find out the influence of a few key morpho-physiological and yield-related traits on grain yield in NGR and non-NGR genotypes to see whether a few important physiological traits viz. flag leaf photosynthetic rate can be used as a selection criterion for enhanced grain yield in rice. For this, a panel of 211 genotypes including 47 NGR lines and 164 non-NGR lines was studied for their physiological and yield attributing traits such as flag leaf area, SPAD chlorophyll meter reading, total chlorophyll content, photosynthetic rate, stomatal conductance, transpiration rate, straw weight, total biomass, harvest index, pushing resistance, culm strength, and grain yield. Trait-specific analysis indicated a positive association of grain yield with straw weight, total biomass, harvest index, and pushing resistance for both groups. However, a significantly positive correlation and regression coefficient of grain yield with the photosynthetic rate was observed only in the case of the NGR lines, while the association was non-significant in non-NGR lines. Additionally, the photosynthetic rate was found to be significantly correlated with straw weight, total biomass, and pushing resistance in NGR lines. Thus, grain yield in NGR lines can be predicted by photosynthetic rate. This makes NGR lines an efficient candidate for breeding programmes with a target of breaking the yield ceiling, using photosynthetic rate as selection criteria.
Databáze: Supplemental Index