Search

The knowledge of functionally characterized genes and linked markers that govern grain yield and its related traits were used to unravel the markers/genes that associate with diversity of yield traits in a panel 30 novel rice genotypes comprising of indica, japonica, aromatic, landraces, interspecific crosses (O.glaberrima/O.sativa) etc. The ANOVA showed significant differences (P=<0.001) for all traits among the genotypes. Molecular analysis was done by employing 37 gene-specific markers targeting 24 yield governing genes in rice. Two markers viz., RM223(YLD) on chromosome 8 and GW004(GW2, LOC_Os02g14720) on chromosome 2 were identified as polymorphic. Average PIC (polymorphic information content) value for these primers was 0.37, suggesting the availability of accountable variability at these loci. Cluster analysis grouped the genotypes into three clusters. Marker-trait-association analysis revealed significant association of the marker GW004 with panicle length, plant height and filled grains in rice. Pearson correlation study also supported the molecular associations through significant phenotypic associations for trait pairs plant height and filled grains, panicle length and plant height. The phenotypic variance explained (R2%) by the marker across panicle length, plant height and filled grains was =15%, suggesting major role of the locus/gene in controlling respective traits. Thus, GW004 marker could be employed in breeding programs for simultaneous selection of three traits panicle length, plant height and filled grains. From the current study it can be concluded that allelic variation studies using novel genotypes can result in the identification of suitable donors along with trait associated markers for rice yield improvement. [ABSTRACT FROM AUTHOR]

Rice (Oryza sativa L.) stands as a important cereal sustaining over half of the world's population. This study delves into the challenges confronting breeders in the realm of crop improvement, specifically focusing on the intricate task of designing an ideotype--a genotype amalgamating diverse attributes for optimal performance. Traditional methodologies, exemplified by the Smith--Hazel (SH) index, grapple with issues such as multicollinearity and the complexities of economic weighting decisions. In response to these challenges, the Multi-Trait Genotype--Ideotype Distance Index (MGIDI), conceptualized by Olivoto and Nardino (2021), emerges as a ground breaking approach. Principal Component Analysis (PCA) aids in the reduction of trait dimensionality, revealing four key factors that collectively contribute to 79.444% of total variability. The Scree plot guides factor selection, ensuring a targeted analysis. The MGIDI index computation yields a total genetic gain of 273.025%, with specific traits like spikelet fertility and seedling dry weight exhibiting significant gains. Six high-performing rice accessions--SM227, NLR33892, MTU3626, 239(3), SMB3, and 405C3 were identified through MGIDI. These identified genotypes serve as valuable resources for developing recombinant populations, aligning with sustainable and effective crop improvement strategies. Additionally, these promising varieties exhibit strengths across various traits, offering potential for simultaneous trait improvement in future breeding programmes. The efficiency of MGIDI is highlighted through its innovative application in simultaneous trait selection, underscoring its significance across a wide range of crops. [ABSTRACT FROM AUTHOR]

Micronutrient malnutrition affects more than one-half of the world's population, especially women and pre-school children. Poor consumers in developing countries acquire roughly one-half of their total iron intakes and a higher percentage of zinc intakes from staple foods. Bio-fortification, an approach of breeding crop plants for higher micronutrient concentration, is a cost effective and sustainable solution for tackling the micronutrient deficiencies. Developing countries, where micronutrient deficiencies are widespread, contribute world's maximum peanut area and production. Thus, peanut can contribute significantly towards reduction of protein-energy and micronutrient malnutrition. With the advent of molecular markers, by using segregating populations for the trait of interest for breeders, it has now become effective to map genes or Quantitative Traits Loci (QTLs) and identify valuable alleles for the corresponding traits. In the present study, an F2:3 mapping population derived from the cross ICGV 06099 × ICGV 93468 was genotyped using 33 polymorphic SSR markers to identify the putative genomic regions associated with the kernel iron and zinc concentrations in groundnut using Single Marker Analysis (SMA). Results revealed that three markers viz., SEQ1B09 (0.23 %), IPAHM245 (2.19 %) and SEQ9G05 (6.34 %) showed significant association with the kernel iron and three markers viz., GM2638 (1.75 %), IPAHM245 (2.25 %) and SEQ9G05 (6.01 %) showed significant association with kernel zinc concentration. Significant positive association (0.549) was observed between kernel iron and zinc concentrations. Validation of these markers in an alternate F2:3 population derived from the cross ICGV 06040 × ICGV 87141 also showed strong association of these markers with the traits of interest. [ABSTRACT FROM AUTHOR]