To achieve superior rice-grain quality, more emphasis has been placed on the genetic diversity of breeding programs, although this improvement could be seriously restricted in the absence of comparable agricultural management practices. Nitrogen (N) application and planting density are two important agronomic practices influencing rice growth, yield, and grain quality. This study investigated the four main aspects of rice-grain quality, namely, milling (brown-rice, milled-rice, and head-rice percentage), appearance (length/width ratio, chalky-kernel percentage, and chalkiness), nutrition (protein content), and cooking and eating quality (apparent amylose content, gel consistency, and pasting viscosities) of two rice cultivars (Shendao 47 and Jingyou 586) under four N rates (0, 140, 180, and 220 kg ha⁻¹), and three planting densities (25 × 10⁴, 16.7 × 10⁴, and 12.5 × 10⁴ hills ha⁻¹) in a field trial from 2015 to 2016. The four main aspects of rice-grain quality were significantly influenced by cultivar. Several aspects were affected by the interactions of N rate and cultivar. No significant interaction between N rate and plating density was detected for all grain-quality parameters. A higher N rate increased the percentages of brown rice and head rice, chalky-kernel percentage, and setback and peak time values, but reduced the length/width ratio, chalkiness, apparent amylose content, gel consistency, and peak-, trough-, and final-viscosity values. These results indicate that the N rate has a beneficial effect on milling and nutritional quality, but a detrimental effect on appearance and cooking and eating quality. Jingyou 586 and Shendao 47 had different responses to planting density in terms of grain quality. Our study indicates that low planting density for Jingyou 586, but a medium one for Shendao 47, is favorable for grain quality.

The vascular bundle especially in the peduncle is one of crucial limiting factors of rice yield, and it determines how plants efficiently transport photosynthetic products, mineral nutrients and water from leaf and root to panicle. However, the genetic base of rice vascular bundle related traits in the peduncle still remains unknown. The 423 panel showed substantial natural variations of peduncle vascular bundle. In total, 48 quantitative trait loci/locus (QTL) affecting the eight traits were identified throughout the genome by applying a significance threshold of P < 1.0 × 10− 4. Combined determining linkage disequilibrium (LD) blocks associated with significant SNPs and haplotype analyses allowed us to shortlist six candidate genes for four important QTL regions affecting the peduncle vascular bundle traits, including one cloned gene (NAL1) and three newly identified QTL (qLVN6, qSVN7, and qSVA8.1). Further the most likely candidate genes for each important QTL were also discussed based on functional annotation. Genetic base on peduncle vascular bundle related traits in rice was systematically dissected, and most likely candidate genes of the known gene NAL1 and the three newly identified QTL (qLVN6, qSVN7, and qSVA8.1) were analyzed. The results provided valuable information for future functional characterization and rice breeding for high yield through optimizing transportation efficiency of photosynthetic products by marker-assisted selection.

Rice yield potential is largely determined by the balance among source capacity, sink strength, and flow fluency. Our previous study indicated that the gene GNP1 encoding gibberellin biosynthesis gene GA20ox1 affects grain number per panicle (GNP) in rice, thus resulting in increase of grain yield. To clarify GNP1 effect on sink, source and flow in regulating rice grain yield, we compared Lemont, a japonica (geng) cultivar, with its near-isogenic line (NIL-GNP1^TQ) in Lemont background with introgression of the allele at GNP1 from Teqing, a high-yielding indica (xian) cultivar. NIL-GNP1^TQ exhibited averagely 32.8% more GNP than Lemont with the compensation by reduced seed setting rate, panicle number and single-grain weight. However, NIL-GNP1^TQ still produced averagely 7.2% higher grain yield than Lemont in two years, mainly attributed to significantly more filled grain number per panicle, and greater vascular system contributing to photoassimilates transport to spikelets. The significantly decreased grain weight of superior spikelets (SS) in NIL-GNP1^TQ was ascribed to a significant decrease of grain size while the significantly decreased grain weight of inferior spikelets (IS) ascribed to both grain size and poor grain-filling as compared with Lemont. The low activities of key enzymes of carbon metabolism might account for the poor grain-filling in IS, which resulted in more unfilled grains or small grain bulk density in NIL-GNP1^TQ. In addition, low seed setting rate and grain weight of IS in NIL-GNP1^TQ might be partially resulted from significantly lower carbohydrate accumulation in culms and leaf sheath before heading compared with Lemont. Our results indicated that significantly increased GNP from introgression of GNP1^TQ into Lemont did not highly significantly improve grain yield of NIL-GNP1^TQ as expected, due primarily to significant low sink activities in IS and possible insufficient source supply which didn’t fully meet the increased sink capacity. The results provided useful information for improving rice yield potential through reasonably introgressing or pyramiding the favorable alleles underlying source-related or panicle number traits by marker-assisted selection.

Stomatal density (D) and size (S) are an important adaptive mechanism for abiotic stress tolerance and photosynthesis capacity in rice. However, the genetic base of rice stomata-related traits still remains unclear. We identified quantitative trait loci (QTLs) associated with D and S on abaxial and adaxial leaf surfaces using genome-wide association analysis with 451 diverse accessions in two environments. D and S showed significant differences between indica (xian) and japonica (geng) accessions and significantly negative phenotypic correlations. A total of 64 QTLs influencing eight stomata-related traits were identified using 2,936,762 high-quality single nucleotide polymorphism markers. Twelve QTLs were consistently detected for the same traits in nine chromosomal regions in both environments. In addition, 12 QTL clusters were simultaneously detected for the same stomata-related traits on abaxial and adaxial leaf surfaces in the same environment, probably explaining the genetic bases of significant correlations of the stomata-related traits. We screened 64 candidate genes for the nine consistent QTL regions using haplotype analysis. Among them, LOC_Os01g66120 for qD_ada1, OsSPCH2 (LOC_Os02g15760) for qD_ada2.1 and qD_aba2.1, LOC_Os02g34320 for qS_ada2.2, OsFLP (LOC_Os07g43420) or LOC_Os07g43530 for qS_aba7.1, and LOC_Os07g41200 for qW_ada7 and qW_aba7 were considered as the most likely candidate genes based on functional annotations. The results systematically dissected the genetic base of stomata-related traits and provide useful information for improving rice yield potential via increasing abiotic stress tolerance and photosynthesis capacity under stressed and non-stressed conditions through deploying the favorable alleles underlying stomata-related traits by marker-assisted selection.