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Decision Support System for Agrotechnology Transfer (DSSAT v4.5) Cropping System Model (CSM) was used to study the impact of climate change and variability on productivity of different kharif (rice, maize, jowar and bajra) and rabi crops (wheat and barley) at Varanasi. Keeping in view the observed trends in climate variability, productivity of different kharif and rabi crops were simulated under plausible synthetic climatic scenarios of changes in temperature, solar radiation and carbon dioxide. Productivity of kharif crops viz. rice, maize, jowar and bajra and rabi crops viz. wheat, and barley decreased with an increase in temperature or a decrease in solar radiation above normal. However, productivity of different kharif and rabi crops increased under expected enhanced CO2 concentrations. Highest productivity decreased in barley crop (40.7%) of rabi season and minimum in rice crop (5%) of kharif season with an increase of 3.0 0C in temperature from normal. Whereas, maximum productivity decreased in barley crop (5.0%) of rabi season and minimum in jowar crop (1.8%) of kharif season with a decrease of 2.5 per cent in solar radiation from normal. Highest productivity increase in barley crop (58.2%) of rabi season and lowest in jowar crop (4.2%) of kharif season were simulated under expected enhanced CO2 concentration of 660 ppm. The maximum decrease in productivity of barley crop (45%) in rabi season and minimum inrice crop (7%) in kharif season were simulated when a decrease in temperature by 3 0C and solar radiation by 2.5 per cent from normal. Highest counter-balance on productivity of rice crop (13%) in kharif season and lowest in barja crop (-23%) of kharif season were simulated when an increase in temperature by 3 0C from normal under expected enhanced CO2 concentration of 660 ppm.

Linkage disequilibrium (LD)-based marker-trait association (MTA) was used to identify markers for sucrose and yield contributing traits in a panel of 108 sugarcane genotypes from sub-tropical India. Population structure (Q), kinship (K), and MTA study exploited a set of 989 marker loci generated from 123 genomic-and expressed sequence tag-SSR primers. The mixed linear model (MLM) coupled with a modified algorithm for population structure (Q) analysis was able to control both type I and type II errors and provided a deeper understanding of the genetics, population stratification and its manifestations on LD in the sugarcane genome. Significant associations were identified for four markers with cane diameter, seven markers each with cane length and number of millable canes (NMCs), eleven markers with number of nodes, six with sucrose per cent, and five markers with average cane weight. A total of 15 markers stable for all the 3 years of study explained 57 % trait variation for NMCs, 34 % for cane width, 27 % for cane length, 20 % for sucrose content, and 19 % for number of nodes. The frequent deviation of structure-based profiles from pedigree-based grouping in this complex heterozygous system reinforced the importance of using genotypic data for selection and breeding. The results contribute to a deeper insight of the complex genome and the identified MTAs could be exploited to fine-tune marker-assisted breeding programmes in genetically complex sugarcane crop.

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