Screening and comprehensive evaluation of rice (Oryza sativa L. subsp. japonica Kato) germplasm resources for nitrogen efficiency in Xinjiang, China

Abstract

Comprehensive screening of rice (Oryza sativa L. subsp. japonica Kato) germplasm resources with different nitrogen (N) efficiency levels is effective for improving N use efficiency (NUE) while reducing pollution and providing high quality, yield, and efficiency agriculture. We investigated 14 indices of 38 varieties under three N application levels to assess differences among genotypes. Rice varieties were classified for screening and identifying N efficient. Descriptive statistical analysis results indicated significant differences in relative yield, and also in NUE indices (agronomic utilization rate and partial productivity of N fertilizer). The genotype main effects and genotype–environment interaction effects (GGE) biplot analysis was used to evaluate suitable varieties, compare the stable and high yield capabilities of different varieties, find the ideal variety, and describe the correlation, discrimination and representativeness of the indices under different N application levels. Descriptive statistical, discrimitiveness and representativeness and factor analysis were used to select indices, in which the panicle number per plant and soil and plant analyzer development (SPAD) value were the key indices for evaluation and identification. Heatmap and hierarchical cluster analysis based on the average value of evaluation indices, and scatter plot based on the comprehensive value of N efficiency (P) according to formula showed that all varieties could be divided into five types under different N treatments. Our findings work toward developing N efficient rice varieties to improve NUE, reduce N fertilizer application and thus N waste, consequently mitigating the effects of rice production on the environment to ensure food security and sustainable agricultural development.

Nitrogen Use Efficiency Phenotype and Associated Genes: Roles of Germination, Flowering, Root/Shoot Length and Biomass

“…The higher reproductive variation in normal N levels ( Figure 1B ) relative to low N levels ( Figure 1C ) has implications for NUE, which is a derivative of reproductive performance (grain yield/N). High variation for reproductive parameters was reported in rice ( Tiwari et al, 2019 ), but not in the context of N-response or NUE, while variation in chlorophyll has been recently linked with NUE ( Jia et al, 2020 ). The restoration of variation from vegetative to reproductive phase is an unprecedented observation that prompts us to recommend the use of seeds of modal weight to control internal variation in vegetative parameters while phenotyping for any quantitative trait.…”

“…We showed earlier that germination and flowering can predict rice yield ( Sitaramam et al, 2008 ), while germination time and crop duration constitute phenotypic parameters for NUE ( Sharma et al, 2018 ). Others linked NUE in rice with root growth ( Morita et al, 1988 ; Xu et al, 2012 ; Yang et al, 2012 ; Li et al, 2015 ; Peng et al, 2015 ; Rogers and Benfey, 2015 ; Kiba and Krapp, 2016 ; Nguyen et al, 2016 ; Steffens and Rasmussen, 2016 ; Xie et al, 2017 ; Rao et al, 2018 ; Duque and Villordon, 2019 ), chlorophyll ( Ladha et al, 2007 ; Thind and Gupta, 2010 ; Mathukia et al, 2014 ; Jia et al, 2020 ), dense and erect panicle ( Sun et al, 2014 ), panicle number ( Jia et al, 2020 ), plant height ( Sitaramam et al, 2008 ; Kumar et al, 2014 ; Nguyen et al, 2016 ; Selvaraj et al, 2017 ), and biomass ( Nguyen et al, 2016 ; Selvaraj et al, 2017 ).…”

“…However, there has been some recent progress in identifying phenotypic parameters for N-response/NUE in model plants ( Li et al, 2017 ). In rice, the parameters include leaf chlorophyll content ( Ladha et al, 2007 ; Thind and Gupta, 2010 ; Mathukia et al, 2014 ; Jia et al, 2020 ), dense and erect panicle ( Sun et al, 2014 ) and root length and density ( Morita et al, 1988 ; Xu et al, 2012 ; Yang et al, 2012 ; Li et al, 2015 ; Peng et al, 2015 ; Rogers and Benfey, 2015 ; Kiba and Krapp, 2016 ; Steffens and Rasmussen, 2016 ; Xie et al, 2017 ; Duque and Villordon, 2019 ). But no study has comprehensively evaluated all the phenotypic parameters for N-response in urea and nitrate, nor distinguished between N-response and NUE phenotypically in any crop.…”

Physiological, Agronomical, and Proteomic Studies Reveal Crucial Players in Rice Nitrogen Use Efficiency under Low Nitrogen Supply

“…Therefore, carbon and N assimilation and their remobilization are crucial for NUE and grain production in plants. Furthermore, NUE variation has been conferred by genetic variants in rice [ 44 , 45 ], and the genetic basis for NUE remains unexplored [ 46 ].…”

Stability and G × E Analysis of Oil Yield of Sunflower Single Cross Hybrids In Diverse Environments

“…There are a numerous numerical and graphical stability methods to analyze the extent of G×E interaction and determining the both high yield and stable genotypes under varying environmental conditions. Among the graphical stability methods, the GGE biplot (genotypes main effect plus G×E interaction) has previously been used to modeling of G×E interaction in multi-environment trials (METs) in different crops (Yan et al, 2000;Gauch, 2006;Rakshit et al, 2012;Mohammadi and Amri, 2013;Hassani et al, 2018;Dallo et al, 2019;Hamidou et al, 2019;Da Cruz et al, 2020;Jia et al, 2020). The GGE biplot analysis is a very useful graphical tool because provides graphic images and effective overview of the original data and results (Yan, 2015).…”