High-molecular-weight secretory proteins and low-molecular-weight exudates (carboxylates, phenols, free amino acids and sugars) released from roots of soybean (Glycine max (L.) Merr.) differentially influence genotypic phosphorus (P) acquisition efficiency (PAE). We hypothesised that genotypes with higher root exudation potential would exhibit enhanced P acquisition, and screened 116 diverse soybean genotypes by labelling shoots with 14CO2. A root exudation index (REI) derived from total 14C in the root exudate at sufficient (250 µm) and low (4 µm) P levels was used to classify genotypes for PAE. Genotypes with REI >2.25 exhibited significantly higher exudation at low than at sufficient P, which in turn increased PAE. Under low P availability, efficient genotypes exude a greater quantity of organic compounds into the rhizosphere. This increases P availability to meet the crop requirement, enabling the crop to produce consistent biomass and seed yield with reduced fertiliser addition. Such maintenance of growth and yield potential by mining the inherent soil P is a favourable trait in genotypes, reducing dependence on P fertilisers. Measuring REI at seedling stage to select P-efficient plants accelerates the screening process by accommodating large numbers of genotypes.

Marker-assisted selection (MAS) has been widely used in the last few decades in plant breeding programs for the mapping and introgression of genes for economically important traits, which has enabled the development of a number of superior cultivars in different crops. In sugarcane, which is the most important source for sugar and bioethanol, marker development work was initiated long ago; however, marker-assisted breeding in sugarcane has been lagging, mainly due to its large complex genome, high levels of polyploidy and heterozygosity, varied number of chromosomes, and use of low/medium-density markers. Genomic selection (GS) is a proven technology in animal breeding and has recently been incorporated in plant breeding programs. GS is a potential tool for the rapid selection of superior genotypes and accelerating breeding cycle. However, its full potential could be realized by an integrated approach combining high-throughput phenotyping, genotyping, machine learning, and speed breeding with genomic selection. For better understanding of GS integration, we comprehensively discuss the concept of genetic gain through the breeder’s equation, GS methodology, prediction models, current status of GS in sugarcane, challenges of prediction accuracy, challenges of GS in sugarcane, integrated GS, high-throughput phenotyping (HTP), high-throughput genotyping (HTG), machine learning, and speed breeding followed by its prospective applications in sugarcane improvement.

Nitrogen (N) is a critical element for plant growth and its application has proven to be a valuable agricultural practice. However, unavoidable economic and environmental problems associated with excessive use of N-fertilizers demands its better management. The solution lies in improving the N use efficiency to sustain productivity even at low N levels. Evaluation of 32 maize genotypes using physiological and biochemical traits under optimum (4.5 mM) and low N (0.5 mM) was carried out. The contrasting low-N sensitive (HM-4) and low-N tolerant (PEHM-2) genotypes were used for comparative proteome-profiling of leaves under optimum and low N as well as restoration of low N on 3rd (NR3) and 5th (NR5) days after re-supplying N. The analysis of differential expression pattern of proteins was performed by 2-D gel electrophoresis. Significant variations in the expression of proteins were observed under low N, which were genotype specific. In the leaf proteome, 25 spots were influenced by N treatment and 4 spots were different between the two genotypes. Most of the proteins that were differentially accumulated in response to N level and were involved in photosynthesis and metabolism, affirming the relationship between N and carbon metabolism. In addition to this, greater intensity of some defense proteins in the low N tolerant genotype was found that may have a possible role in imparting it tolerance under N starvation conditions. The new insights generated on maize proteome in response to N-starvation and restoration would be useful towards improvement of N-use efficiency in maize.