Cotton is one of the important cash crops and a fiber crop most widely grown and the highest yielding as well. Cotton fiber is woven to be the fabrics commonly used in our daily life due to its excellent performance and great production in the world, especially in China. To access to such high quantities must ensure the requirements of materials such as nutrients for plant growth and take care of the smallest details to make the production cost less, to improve the utilization efficiency, such as nitrogen (N) fertilizer. Hence, N fertilization studies are not only about the dosages, timing and ratio, but also the uptake processes by the plant, N effect on cotton yield and its formation, as well as the movement and metabolism within the plant. As economic and ecological issues are concerned, economizing N fertilization is paid more and more attention. Many approaches have been done and suggested in order to improve NUE like combine the plant sensing techniques and precision application. Simulations and recent field trials demonstrate that site-specific nitrogen management helped reduce technological constraints to higher AE achievement, profit and more sustainable N management. Therefore, improving nitrogen use efficiency (NUE) is one of the key points to ensure cotton production development sustainable. In this review, we try to highlight the accomplishments of N effect on cotton growth and yield, NUE and factors related to NUE in cotton production based on the current knowledge, and from our viewpoint we propose some possible approaches to improve NUE through N managements in terms of application splits, rates, and timing.

Background: Wet direct-seeded rice is a possible alternative to conventional puddled transplanted rice; the former uses less water and reduces labor requirements. Improving seed reserve utilization efficiency (SRUE) is a key factor in facilitating the application of this technology. However, the QTLs controlling this trait are poorly investigated. In this study, a genome-wide association study (GWAS) was conducted using a natural population composed of 542 accessions of rice (Oryza sativa L.) which were genotyped using 266 SSR markers. Large phenotypic variations in SRUE were found in the studied population. Results: The average SRUE over 542 accessions across two years (2016 and 2017) was 0.52 mg.mg − 1 , ranging from 0.22 mg.mg-1 to 0.93 mg.mg − 1 , with a coefficient of variation of 22.66%. Overall, 2879 marker alleles were detected in the population by 266 pairs of SSR markers, indicating a large genetic variation existing in the population. Using general linear model method, 13 SSR marker loci associated with SRUE were detected and two (RM7309 and RM434) of the 13 loci, were also detected using mixed linear model analyses, with percentage of phenotypic variation explained (PVE) greater than 5% across two years. The 13 association loci (P < 0.01) were located on all chromosomes except chromosome 11, with PVE ranging from 5.05% (RM5158 on chromosome 5) to 12% (RM297 on chromosome 1). Association loci RM7309 on chromosome 6 and RM434 on chromosome 9 revealed by both models were detected in both years. Twenty-three favorable alleles were identified with phenotypic effect values (PEV) ranging from 0.10 mg.mg − 1 (RM7309-135 bp on chromosome 9) to 0.45 mg.mg − 1 (RM297-180 bp on chromosome 2). RM297-180 bp showed the largest phenotypic effect value (0.44 mg.mg − 1 in 2016 and 0.45 mg.mg − 1 in 2017) with 6.72% of the accessions carrying this allele and the typical carrier accession was Manyedao, followed by RM297-175 bp (0.43 mg.mg − 1 in 2016 and 0.44 mg.mg − 1 in 2017). Conclusion: Nine novel association loci for SRUE were identified, compared with previous studies. The optimal parental combinations for pyramiding more favorable alleles for SRUE were selected and could be used for breeding rice accessions suitable for wet direct seeding in the future.

Background: The general combining ability (GCA) of parents in hybrid rice affects not only heterotic level of grain yield and other important agronomic traits, but also performance of grain quality traits of F 2 bulk population which is the commodity consumed by humans. In order to make GCA improvement for quality traits in parents of hybrid rice by molecular marker assisted selection feasible, genome-wide GCA loci for quality traits in parents were detected through association analysis between the effects of GCA and constructed single nucleotide polymorphism linkage disequilibrium blocks (SNPLDBs), by using unhusked rice grains harvested from F 1 plants of 48 crosses of Indica rice and 78 crosses of Japonica rice. GCA-SNPLDBs association analysis. Results: Among the 8 CMS and 6 restorer lines of indica rice subspecies, CMS lines Zhenpin A, Zhenshan97 A, and 257A, and restorers Kanghui98, Minghui63 and Yanhui559 were recognized as good general combiners based on their GCA effect values for the 9 quality traits (brown rice rate, milled rice rate, head rice rate, percentage of chalky grains, chalky area size, chalkiness degree, gelatinization temperature, gel consistency and amylose content). Among the 13 CMS and 6 restorer lines of japonica rice subspecies, CMS 863A, 6427A and Xu 2A, and restorers C418, Ninghui8hao and Yunhui4hao showed elite GCA effect values for the 9 traits. GCA-SNPLDB association analysis revealed 39 significant SNPLDB loci associated with the GCA of the 9 quality-related traits, and the numbers of SNPLDB loci located on chromosome 1,