Identification of High Nitrogen Use Efficiency Phenotype in Rice (Oryza sativa L.) Through Entire Growth Duration by Unmanned Aerial Vehicle Multispectral Imagery - Liang, Ting; Duan, Bo; Luo, Xiaoyun; Ma, Yi; Yuan, Zhengqing; Zhu, Renshan; Peng, Yi; Gong, Yan; Fang, Shenghui; Wu, Xianting (Frontiers in Plant Science, 2021)
High Nitrogen Use Efficiency (NUE) phenotype identification is a long-time challenge for rice breeding and sustainable agriculture in order to reduce nitrogen (N) fertilizer costs and decrease environmental damages caused by N overapplication. The challenge comes mainly from two aspects: 1) high NUE genetic sources are biologically scarce; 2) from the technique side of view, fewer easy, nondestructive but reliable methodology are available to evaluate plant N variations lively through the entire growth duration (GD). To conquer the challenges, a valuable Honglian type hybrid rice LY9348 is identified as a high NUE rice variety both in Nitrogen Uptake Efficiency (NUpE) and Nitrogen Utilization Efficiency (NUtE) through nitrogen dosage field analysis. Canopy nitrogen content (CNC) is used to illustrate N accumulations and changes in LY9348 by a high-throughput Unmanned Aerial Vehicle Remote Sensing Platform (UAV-RSP) to screen two mixed categories (51 vs. 42 varieties) selected from representative higher NUE indica rice collections. Five Vegetative Indices (VIs) are compared and Normalized Difference Red Edge Index (NDRE) is in the best correlation with CNC (r=0.80). Compared six key developmental stages of rice varieties from transplanting to maturation, the high NUE phenotype of LY9348 is shown as a dy-namic CNC curve, which the N accumulation is moderately high during vegetative developmental stages but distinguishably higher in reproduction developmental stages with a slower reduction rate. CNC curves of different rice varieties are analyzed to construct two non-linear regression models between N%, N% x leaf area index (LAI) with NDRE sepa-rately. Both models are capable to extract the specific high NUE phenotype of LY9348 in time-series with the coefficient of determination (R2) above 0.61 (Model I) and 0.86 (Model II). Parameters influencing the correlation accuracy between NDRE and N% are evaluated to be better by taking the tillering stage data out, separating short and long GD varieties apart for analysis and adding canopy structures such as LAI into consideration. The high NUE phenotype of LY9348 can be traced and reidentified in different years, locations and genetic germplasm groups, therefore, an effective and reliable high-throughput method in assisting high NUE breeding selections is proposed.