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Grain yield in rice is a complex trait and it is controlled by a number of quantitative trait loci (QTL). To dissect the genetic basis of rice yield, QTL analysis for nine yield traits was performed using an F2 population containing 190 plants, which was developed from a cross between Youyidao (YYD) and Sanfenhe (SFH), and each plant in the population evaluated with respect to nine yield traits. In this study, the correlations among the nine yield traits were analyzed. The grain yield per plant positively correlated with six yield traits, except for grain length and grain width, and showed the highest correlation coefficient of 0.98 with the number of filled grains per plant. A genetic map containing 133 DNA markers was constructed and it spanned 1831.7 cM throughout 12 chromosomes. A total of 36 QTLs for the yield traits were detected on nine chromosomes, except for the remaining chromosomes 5, 8, and 9. The phenotypic variation was explained by a single QTL that ranged from 6.19% to 36.01%. Furthermore, a major QTL for grain width and weight, qGW2-1, was confirmed to be newly identified and was narrowed down to a relatively smaller interval of about ~2.94-Mb. Collectively, we detected a total of 36 QTLs for yield traits and a major QTL, qGW2-1, was confirmed to control grain weight and width, which laid the foundation for further map-based cloning and molecular design breeding in rice. [ABSTRACT FROM AUTHOR]

Healthy seed germination is important for improving the yield and quality of maize, but the molecular mechanisms regulating maize seed germination are still unclear. Significant progress has been made in the study of rice quality functional genomics, with the cloning of many important genes related to the regulation of rice quality traits. Selecting crop varieties with high and stable yields, as well as improving quality and economic benefits, has become a long-term topic while facing the continuous increasing population and the adverse effects of environmental changes. Therefore, developing fragrant rice varieties, strengthening the breeding of high-quality conventional indica rice, and developing functional rice with special nutritional value or specific needs of specific populations are important directions for future rice breeding. [Extracted from the article]

Grain size and weight are the key traits determining rice quality and yield and are mainly controlled by quantitative trait loci (QTL). In this study, one minor QTL that was previously mapped in the marker interval of JD1009-JD1019 using the Huanghuazhan/Jizi1560 (HHZ/JZ1560) recombinant inbred line (RIL) population, qTGW1-2, was validated to regulate grain size and weight across four rice-growing seasons using twenty-one near isogenic line (NIL)-F2 populations. The twenty-one populations were in two types of genetic background that were derived from the same parents HHZ and JZ1560. Twelve F9, F10 or F11 NIL-F2 populations with the sequential residual heterozygous regions covering JD1009-RM6840 were developed from one residual heterozygote (RH) in the HHZ/JZ1560 RIL population, and the remaining nine BC3F3, BC3F4 or BC3F5 NIL-F2 populations with the sequential residual heterozygous regions covering JD1009-RM6840 were constructed through consecutive backcrosses to the recurrent parent HHZ followed with marker assistant selection in each generation. Based on the QTL analysis of these genetic populations, qTGW1-2 was successfully confirmed to control grain length, width and weight and further dissected into two QTLs, qTGW1-2a and qTGW1-2b, which were respectively narrowed down to the marker intervals of JD1139-JD1127 (~ 978.2-kb) and JD1121-JD1102 (~ 54.8-kb). Furthermore, the two types of NIL-F2 populations were proved to be able to decrease the genetic background noise and increase the detection power of minor QTL. These results provided an important basis for further map-based cloning and molecular design breeding with the two QTLs in rice. [ABSTRACT FROM AUTHOR]

Gibberellins (GAs) are diterpenoid phytohormones regulating various aspects of plant growth and development, such as internode elongation and seed germination. Although the GA biosynthesis pathways have been identified, the transcriptional regulatory network of GA homeostasis still remains elusive. Here, we report the functional characterization of a GA-inducible OsABF1 in GA biosynthesis underpinning plant height and seed germination. Overexpression of OsABF1 produced a typical GA-deficient phenotype with semi-dwarf and retarded seed germination. Meanwhile, the phenotypes could be rescued by exogenous GA3, suggesting that OsABF1 is a key regulator of GA homeostasis. OsABF1 could directly suppress the transcription of green revolution gene SD1, thus reducing the endogenous GA level in rice. Moreover, OsABF1 interacts with and transcriptionally antagonizes to the polycomb repression complex component OsEMF2b, whose mutant showed as similar but more severe phenotype to OsABF1 overexpression lines. It is suggested that OsABF1 recruits RRC2-mediated H3K27me3 deposition on the SD1 promoter, thus epigenetically silencing SD1 to maintain the GA homeostasis for growth and seed germination. These findings shed new insight into the functions of OsABF1 and regulatory mechanism underlying GA homeostasis in rice. [ABSTRACT FROM AUTHOR]

Rice is a staple food crop in Asia. The rice farming industry has been influenced by global urbanization, rapid industrialization, and climate change. A combination of precise agricultural and smart water management systems to investigate the nutrition state in rice is important. Results indicated that plant nitrogen and chlorophyll content at the maximum tillering stage were significantly influenced by the interaction between water and fertilizer. The normalized difference vegetation index (NDVI) and normalized difference red edge (NDRE), obtained from the multispectral images captured by a UAV, exhibited the highest positive correlations (0.83 and 0.82) with plant nitrogen content at the maximum tillering stage. The leave-one-out cross-validation method was used for validation, and a final plant nitrogen content prediction model was obtained. A regression function constructed using a nitrogen nutrition index and the difference in field cumulative nitrogen had favorable variation explanatory power, and its adjusted coefficient of determination was 0.91. We provided a flow chart showing how the nutrition state of rice can be predicted with the vegetation indices obtained from UAV image analysis. Differences in field cumulative nitrogen can be further used to diagnose the demand of nitrogen topdressing during the panicle initiation stage. Thus, farmers can be provided with precise panicle fertilization strategies for rice fields. [ABSTRACT FROM AUTHOR]