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The field investigations were conducted at Vegetable Research Farm, Department of vegetable Science, Punjab Agricultural University, Ludhiana with the objective to standarize the agronomic practices for mechical harvesting of garden pea. Therefore, effect of different agronomic traits including time of sowing, spacing and sowing method on yield and its attributing traits were studied on single-harvest garden pea. The experiment was laid out in split-plot design with 30 treatments comprising five dates of sowing in main plots and 2 different planting methods (flat and bed) sown at three different spacing in subplots and replicated three times. The bed size was standardized according to front-loading width of the pea combine. Significant interactions were observed between the date of sowing and spacing for a number of pods per plant, green seeds per pod, green pod yield per plant, green pod yield per plot; date of sowing and sowing method for pod length; spacing and sowing method for plant height. However, for all the traits, there was non-significant 3-way interaction. The late sown (20th December) crop resulted in the least number of pods per plant, green seeds per pod, green pod yield per plant and green pod yield per plot which was due to high temperature and low relative humidity conditions at pod development and filling stage. It is concluded that the garden pea cultivar Punjab-89 sown on 5th November at the spacing of 20 × 7.5 cm on beds (bed width of 1.0 m) resulted in significantly highest green pod yield of 12.75 kg/9 m2 in the single harvest. Therefore, the 3 beds of 1 m width can be harvested together with pea combine (because combine has working front width of 3.1 m) results into maximum yield when pea crops is sown on 5th November @ 20 × 7.5 cm spacing.

Abstract Timely transition to flowering, maturity and plant height are important for agronomic adaptation and productivity of Indian mustard (B. juncea), which is a major edible oilseed crop of low input ecologies in Indian subcontinent. Breeding manipulation for these traits is difficult because of the involvement of multiple interacting genetic and environmental factors. Here, we report a genetic analysis of these traits using a population comprising 92 diverse genotypes of mustard. These genotypes were evaluated under deficient (N75), normal (N100) or excess (N125) conditions of nitrogen (N) application. Lower N availability induced early flowering and maturity in most genotypes, while high N conditions delayed both. A genotyping-by-sequencing approach helped to identify 406,888 SNP markers and undertake genome wide association studies (GWAS). 282 significant marker-trait associations (MTA's) were identified. We detected strong interactions between GWAS loci and nitrogen levels. Though some trait associated SNPs were detected repeatedly across fertility gradients, majority were identified under deficient or normal levels of N applications. Annotation of the genomic region (s) within ± 50 kb of the peak SNPs facilitated prediction of 30 candidate genes belonging to light perception, circadian, floral meristem identity, flowering regulation, gibberellic acid pathways and plant development. These included over one copy each of AGL24, AP1, FVE, FRI, GID1A and GNC. FLC and CO were predicted on chromosomes A02 and B08 respectively. CDF1, CO, FLC, AGL24, GNC and FAF2 appeared to influence the variation for plant height. Our findings may help in improving phenotypic plasticity of mustard across fertility gradients through marker-assisted breeding strategies.

A set of 96 Brassica juncea–Erucastrum cardaminoides introgression lines (ILs) were developed with genomic regions associated with Sclerotinia stem rot (Sclerotinia sclerotiorum) resistance from a wild Brassicaceous species E. cardaminoides. ILs were assessed for their resistance responses to stem inoculation with S. sclerotiorum, over three crop seasons (season I, 2011/2012; II, 2014/2015; III, 2016–2017). Initially, ILs were genotyped with transferable SSR markers and subsequently through genotyping by sequencing. SSR based association mapping identified six marker loci associated to resistance in both A and B genomes. Subsequent genome-wide association analysis (GWAS) of 84 ILs recognized a large number of SNPs associated to resistance, in chromosomes A03, A06, and B03. Chromosomes A03 and A06 harbored the maximum number of resistance related SNPs. Annotation of linked genomic regions highlighted an array of resistance mechanisms in terms of signal transduction pathways, hypersensitive responses and production of anti-fungal proteins and metabolites. Of major importance was the clustering of SNPs, encoding multiple resistance genes on small regions spanning approximately 885 kb region on chromosome A03 and 74 kb on B03. Five SNPs on chromosome A03 (6,390,210-381) were associated with LRR-RLK (receptor like kinases) genes that encode LRR-protein kinase family proteins. Genetic factors associated with pathogen-associated molecular patterns (PAMPs) and effector-triggered immunity (ETI) were predicted on chromosome A03, exhibiting 11 SNPs (6,274,763-994). These belonged to three R-Genes encoding TIR-NBS-LRR proteins. Marker trait associations (MTAs) identified will facilitate marker assisted introgression of these critical resistances, into new cultivars of B. juncea initially and, subsequently, into other crop Brassica species.