Identification and characterization of high-yielding, short-duration rice genotypes for tropical Asia

Identification of High Nitrogen Use Efficiency Phenotype in Rice (Oryza sativa L.) Through Entire Growth Duration by Unmanned Aerial Vehicle Multispectral Imagery

Identification of high Nitrogen Use Efficiency (NUE) phenotypes has been a long-standing challenge in breeding rice and sustainable agriculture to reduce the costs of nitrogen (N) fertilizers. There are two main challenges: (1) high NUE genetic sources are biologically scarce and (2) on the technical side, few easy, non-destructive, and reliable methodologies are available to evaluate plant N variations through the entire growth duration (GD). To overcome the challenges, we captured a unique higher NUE phenotype in rice as a dynamic time-series N variation curve through the entire GD analysis by canopy reflectance data collected by Unmanned Aerial Vehicle Remote Sensing Platform (UAV-RSP) for the first time. LY9348 was a high NUE rice variety with high Nitrogen Uptake Efficiency (NUpE) and high Nitrogen Utilization Efficiency (NUtE) shown in nitrogen dosage field analysis. Its canopy nitrogen content (CNC) was analyzed by the high-throughput UAV-RSP to screen two mixed categories (51 versus 42 varieties) selected from representative higher NUE indica rice collections. Five Vegetation Indices (VIs) were compared, and the Normalized Difference Red Edge Index (NDRE) showed the highest correlation with CNC (r = 0.80). Six key developmental stages of rice varieties were compared from transplantation to maturation, and the high NUE phenotype of LY9348 was shown as a dynamic N accumulation curve, where it was moderately high during the vegetative developmental stages but considerably higher in the reproductive developmental stages with a slower reduction rate. CNC curves of different rice varieties were analyzed to construct two non-linear regression models between N% or N% × leaf area index (LAI) with NDRE separately. Both models could determine the specific phenotype with the coefficient of determination (R 2) above 0.61 (Model I) and 0.86 (Model II). Parameters influencing the correlation accuracy between NDRE and N% were found to be better by removing the tillering stage data, separating the short and long GD varieties for the analysis and adding canopy structures, such as LAI, into consideration. The high NUE phenotype of LY9348 could be traced and reidentified across different years, locations, and genetic germplasm groups. Therefore, an effective and reliable high-throughput method was proposed for assisting the selection of the high NUE breeding phenotype.

Assessment of agro-morphological, physiological and yield traits diversity among tropical rice

Rice (Oryza sativa L.) is an essential staple food crop, but the per acre average rice yield is less than its substantial potential in many countries. Rice breeders and growers would benefit from a robust genotypes with better morpho-physiological and yield-related traits. Here, seventy-four new rice genotypes were phenotyped over two years for their gas exchange and yield potential-related traits under Mississippi rice-growing conditions. A wide range of variability was observed among genotypes for all measured traits. Detailed phenotyping of rice genotypes revealed two key relationships that function together to contribute to yield potential under the southern US climate. The first one, grain yield, grain number, and spikelet fertility, showed considerable correlation (r = 0.45 to 0.79, p < 0.001) to harvest index. Conversely, days to anthesis had a high and negative correlation with harvest index (r = −0.79, p < 0.001), which suggests that selection for short duration genotypes with efficient partitioning could improve the yields under southern US climatic conditions. Additive response index revealed a higher positive association with yield traits (R² = 0.59) than physiological (R² = 0.28) and morphological traits (R² = 0.21). Compared with the commercial genotype Rex, 21.6% and 47.3% of the rice genotypes had a higher gas exchange and yield response scores. IR08A172, IR07K142 and IR07F287 were ranked as high performers in physiological and yield response indices. Our study highlights that selection for short-duration yield-related traits with efficient sink capacity traits is desirable for future breeding programs.