| Literature DB >> 35035142 |
Shabir H Wani1, Roshni Vijayan2, Mukesh Choudhary3, Anuj Kumar4, Abbu Zaid5, Vishal Singh6, Pardeep Kumar3, Jeshima Khan Yasin7.
Abstract
Nitrogen, the vital primary plant growth nutrient at deficit soil conditions, drastically affects the growth and yield of a crop. Over the years, excess use of inorganic nitrogenous fertilizers resulted in pollution, eutrophication and thereby demanding the reduction in the use of chemical fertilizers. Being a C4 plant with fibrous root system and high NUE, maize can be deployed to be the best candidate for better N uptake and utilization in nitrogen deficient soils. The maize germplasm sources has enormous genetic variation for better nitrogen uptake contributing traits. Adoption of single cross maize hybrids as well as inherent property of high NUE has helped maize cultivars to achieve the highest growth rate among the cereals during last decade. Further, considering the high cost of nitrogenous fertilizers, adverse effects on soil health and environmental impact, maize improvement demands better utilization of existing genetic variation for NUE via introgression of novel allelic combinations in existing cultivars. Marker assisted breeding efforts need to be supplemented with introgression of genes/QTLs related to NUE in ruling varieties and thereby enhancing the overall productivity of maize in a sustainable manner. To achieve this, we need mapped genes and network of interacting genes and proteins to be elucidated. Identified genes may be used in screening ideal maize genotypes in terms of better physiological functionality exhibiting high NUE. Future genome editing may help in developing lines with increased productivity under low N conditions in an environment of optimum agronomic practices. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12298-021-01113-z. © Prof. H.S. Srivastava Foundation for Science and Society 2021.Entities:
Keywords: Co-expression networks; Maize; Mapping; NUE; Productivity; Quantitative trait loci
Year: 2021 PMID: 35035142 PMCID: PMC8720126 DOI: 10.1007/s12298-021-01113-z
Source DB: PubMed Journal: Physiol Mol Biol Plants ISSN: 0974-0430