Single-time fertilization (STF) with controlled release blended fertilizer (CRBF) improves grain yield and nitrogen use efficiency (NUE) in rice production.  However, the impact of soil nitrogen (N) distribution and root growth on rice yield and NUE under STF with CRBF remains unclear.  Here, a two-year field experiment investigated the effects of two fertilizer types (normal urea (U) and CRBF) and two single-time fertilization methods (broadcast and side-deep fertilization) on the soil N distribution, plant N uptake, root characteristics, grain yield, and NUE.  The results showed that CRBF under STF increased the averages of plant dry matter accumulation, N uptake, grain yield, nitrogen recovery efficiency (NRE), and nitrogen agronomic efficiency (NAE) by 8.29, 21.85, 10.57, 79.28, and 74.8% compared to the other treatments, respectively.  Side-deep fertilization with CRBF further increased NUE by 12.78% compared to broadcast.  Moreover, CRBF under STF increased the leaf SPAD value and glutamine synthetase (GS)/glutamine oxoglutarate aminotransferase (GOGAT) activity by 5.93 and 25.58%, respectively.  CRBF under STF increased the soil inorganic N concentration and showed a “rising early and stabilizing later” pattern.  In addition, CRBF under STF improved rice root growth and increased the averages of root biomass, total root number, root average diameter, total root length, total root surface area, and total root volume by 28.30, 28.56, 18.64, 13.38, 35.26, and 37.06%, respectively, at the tillering and heading stages.  Partial least squares path modeling indicated that CRBF under STF increased the soil inorganic N concentration which improved root morphology, thereby increasing N uptake and improving the rice yield and NUE.  Taken together, our findings show that CRBF with single-time fertilization is the preferred N fertilizer strategy for achieving high yield and efficiency in rice, and that side-deep fertilization is the optimal fertilization method.

Heading date is one of the most important indicators to evaluate adaptation in wheat. In this study, we used three association panels to construct a genome-wide recombination landscape consisting of 97 recombination hotspots regions (RHR) in wheat. We further identified 1,043 RHR in six bi-parental populations, and 88 recombination hotspots overlapped with association panels. We next identified 2223 significant SNPs forming 55 clusters for heading date by phenotype-based genome-wide association studies (pGWAS), and 53 stable SNPs associated with 13 candidate genes were detected in at least two environments. Twenty-one QTLs were mapped in bi-parental populations and five QTL intervals overlapped RHR. By integration of collinearity analysis, recombination hotspots, and haplotype analysis, five homoeologous interval pairs were discovered, of which 7D_Hap1 advanced heading by 8.7 days. Further analysis showed that heading date-network genes were involved into transcription regulation and post-translational modification (PTM). Meanwhile, expression GWAS (eGWAS) on heading date regulatory core module identified 307 potential novel genes acting in heading date regulatory network. These findings provide new insights into wheat phenological adaptation and developed resources for developing climate-resilient wheat cultivars.