Increased application of inorganic nitrogen has been the key component responsible for growth in cereal production. Due to continuously increasing application of Nitrogen (N) and its lower use efficiency along with environmental and health implications of leftover N, improving nitrogen use efficiency (NUE) through management and genetic manipulation require immediate attention. The way N is uptaken through better root architecture and improved transporters and assimilated and remobilized into storage organ influences NUE. Partitioning of N between leaves and stems, photosynthetic efficiency, rubisco activity and senescence of leaf decide N utilization efficiency. Genetic manipulation to improve NUE requires information on the extent of exploitable genetic variability and their genetic control, however, limited information about these traits limits development of efficient genotypes. MAS for QTLs associated with key enzymes involved in N uptake and utilization or transgenic by overexpressing the enzymatic gene shows great promise in the future. Furthermore, the interaction of NUE and other plant traits should be evaluated.

Root system architecture (RSA), also known as root morphology, is critical in plant acquisition of soil resources, plant growth, and yield formation. Many QTLs associated with RSA or root traits in maize have been identified using several bi-parental populations, particularly in response to various environmental factors. In the present study, a meta-analysis of QTLs associated with root traits was performed in maize using 917 QTLs retrieved from 43 mapping studies published from 1998 to 2020. A total of 631 QTLs were projected onto a consensus map involving 19,714 markers, which led to the prediction of 68 meta-QTLs (MQTLs). Among these 68 MQTLs, 36 MQTLs were validated with the marker-trait associations available from previous genome-wide association studies for root traits. The use of comparative genomics approaches revealed several gene models conserved among the maize, sorghum, and rice genomes. Among the conserved genomic regions, the ortho-MQTL analysis uncovered 20 maize MQTLs syntenic to 27 rice MQTLs for root traits. Functional analysis of some high-confidence MQTL regions revealed 442 gene models, which were then subjected to in silico expression analysis, yielding 235 gene models with significant expression in various tissues. Furthermore, 16 known genes viz., DXS2, PHT, RTP1, TUA4, YUC3, YUC6, RTCS1, NSA1, EIN2, NHX1, CPPS4, BIGE1, RCP1, SKUS13, YUC5, and AW330564 associated with various root traits were present within or near the MQTL regions. These results could aid in QTL cloning and pyramiding in developing new maize varieties with specific root architecture for proper plant growth and development under optimum and abiotic stress conditions.

Nitrogen uptake being part of nitrogen use efficiency (NUE) is largely decided by root traits. Root traits variability has hardly been explored by breeders mainly because of difficulties in scoring. The hydroponic system requiring lesser space for precise phenotyping of large numbers of genotypes independently of the growing season can be a suitable alternative. However, the effectiveness of hydroponic screening methods needs to be verified under the soil condition of the field or pot. In the present study, root traits and NUE were investigated in 19 genotypes under two conditions (hydroponic and pipe filled with soil). Both environments revealed large variability for root traits and NUE under high and low N conditions establishing the absence of any direct selection for these traits in the past. Under both sets of experimentation, NUpE was largely responsible for improved nitrogen efficiency mainly because of higher root biomass. The significant association between the two screening methods i.e. hydroponic and pot filled with soil under both low and high N condition support large scale screening for root traits under hydroponic condition.

Nitrogen use efficiency (NUE) in wheat may significantly reduce the excessive use of N fertilizers. However, being a quantitative trait, understanding its genetic basis is required for efficient wheat breeding. The present study was carried out to dissect the complex trait through the mapping of quantitative trait locus (QTLs) related to NUE component traits in Indian wheat. A linkage map was constructed using F₂ population derived from two parents contrasting for nitrogen-responsive traits using simple sequence repeat (SSR) markers. Phenotyping for root dry weight, N uptake and utilization were carried out under a high nitrogen environment. Twenty-seven main effect QTLs for eight traits and 26 interaction QTLs for three traits were detected. The main effect QTLs explained a significant amount of phenotypic variance up to the extent of 11.18%. The QTLs were also found to have significant epistatic interactions governed by both additive and non-additive gene action. In particular, chromosome 2A harbours QTLs for many traits viz. SDW, RDW, TDW, R:S, %N, NUtE, and NUpE, including epistasis and interaction QTLs that were flanked by markers Xwmc728-Xwmc473 and Xwmc779-Xgwm249. Taken together, the genomic regions on 2A, 4A, and 7A were found to contain QTLs for a majority of the studied NUE traits that can be potentially exploited in future wheat breeding programmes.

Genetic improvement for nitrogen use efficiency (NUE) can play a very crucial role in sustainable agriculture. Root traits have hardly been explored in major wheat breeding programs, more so in spring germplasm, largely because of the difficulty in their scoring. A total of 175 advanced/improved Indian spring wheat genotypes were screened for root traits and nitrogen uptake and nitrogen utilization at varying nitrogen levels in hydroponic conditions to dissect the complex NUE trait into its component traits and to study the extent of variability that exists for those traits in Indian germplasm. Analysis of genetic variance showed a considerable amount of genetic variability for nitrogen uptake efficiency (NUpE), nitrogen utilization efficiency (NUtE), and most of the root and shoot traits. Improved spring wheat breeding lines were found to have very large variability for maximum root length (MRL) and root dry weights (RDW) with strong genetic advance. In contrast to high nitrogen (HN), a low nitrogen (LN) environment was more effective in differentiating wheat genotypes for NUE and its component traits. Shoot dry weight (SDW), RDW, MRL, and NUpE were found to have a strong association with NUE. Further study revealed the role of root surface area (RSA) and total root length (TRL) in RDW formation as well as in nitrogen uptake and therefore can be targeted for selection to further the genetic gain for grain yield under high input or sustainable agriculture under limited inputs.