BackgroundBakanae or foot rot disease caused by Fusarium fujikuroi [teleomorph: Gibberella fujikuroi (Sawada) Ito] is emerging as a serious disease in rice. The disease causes both quantitative and qualitative losses to the grains under the field conditions. Breeding for resistance to Bakanae disease is a promising strategy to manage this emerging disease. In this study, we used a population of 168 F14 recombinant inbred lines (RILs) derived from two indica rice parents Pusa 1342, a highly resistant variety and Pusa Basmati 1121, a highly susceptible variety to map quantitative trait loci (QTLs) governing resistance against Bakanae disease.ResultsThe disease reaction of 168 F14 RILs were measured on the seedlings inoculated using Fusarium fujikuroi culture using high-throughput screening protocol under glasshouse conditions. Utilizing inclusive composite interval mapping, three QTLs governing resistance to Bakanae were identified, namely qBK1.1, qBK1.2 and qBK1.3 which accounted 4.76, 24.74 and 6.49 % of phenotypic variation, respectively. The major effect QTL designated qBK1.2 was mapped in 0.26 Mb region between RM5336 and RM10153. A total of 55 annotated genes were identified within the identified QTL region qBK1.2.ConclusionsThe novel QTLs identified in this study are useful resource for efficiently breeding rice cultivars resistant to Bakanae disease. This is the first report on identification of QTLs governing resistance against Bakanae in rice using inclusive composite interval mapping strategy in a RIL population.

Bakanae or foot rot disease caused by Fusarium fujikuroi (teleomorph: Gibberella fujikuroi, Sawada, Wollenweber) is emerging as a serious disease of rice. A simple, reliable and high-throughput method for screening the disease would enable rapid screening of germplasm aimed at identifying resistance sources, mapping QTLs/genes and developing resistant rice cultivars. In the present study, a highthroughput, reliable bioassay to screen rice germplasm for resistance to bakanae disease was developed and compared with the conventional screening technique. This technique involves soaking of rice seeds in fungal spore suspension (1.0x10 6 spores ml-1) for 24 hours at room temperature. Seedling growth at 30°/25° (±3)°C day/night temperature and 60/80(±10)% day/night relative humidity in glasshouse gave the best results. The new protocol described here produces consistent and reproducible bakanae disease symptoms and enables screening of hundreds of rice germplasm within 15 days without any loss of precision in screening of rice genotypes against bakanae disease. The resistant and susceptible genotypes can be used for developing mapping population and identification of QTLs/genes conferring resistance to bakanae disease.

the study was undertaken to identify the quantitative trait loci (QtLs) governing yield and its related traits using a recombinant inbred line (RIL) population derived from the popular rice hybrid, KRH-2 (IR58025A/KMR3R). A genetic map spanning 294.2 cM was constructed with 126 simple sequence repeats (SSR) loci uniformly distributed across the rice genome. QTL analysis using phenotyping and genotyping information identified a total of 22 QTLs. Of these, five major effect QTLs were identified for the following traits: total grain yield/plant (qYLD3-1), panicle weight (qPW3-1), plant height (qPH12-1), flag leaf width (qFLW4-1) and panicle length (qPL3-1), explaining 20.23-22.76% of the phenotypic variance with LOD scores range of 6.5-10.59. Few genomic regions controlling several traits (QTL hotspot) were identified on chromosome 3 for total grain yield/plant (qYLD3-1) and panicle length (qPL3-1). Significant epistatic interactions were also observed for total grain yield per plant (YLD) and panicle length (PL). While most of these QTLs were observed to be co-localized with the previously reported QTL regions, a novel, major QTL associated with panicle length (qPL3-1) was also identified. SNP genotyping of selected high and low yielding RILs and their QTL mapping with 1,082 SNPs validated most of the QTLs identified through SSR genotyping. This facilitated the identification of novel major effect QTLs with much better resolution and precision. In-silico analysis of novel QTLs revealed the biological functions of the putative candidate gene (s) associated with selected traits. Most of the high-yielding RILs possessing the major yield related QTLs were identified to be complete restorers, indicating their possible utilization in development of superior rice hybrids.

Peanut is gaining importance more for its confectionery and nutritive values than for its oil content around the world. Improving confectionery qualities is an added advantage for farming community. Hence, in the present study, multivariate analytical tools were used to identify parents with complementary traits for using them in breeding programme. PCA revealed contribution of pod yield, 100-seed weight, oil content, and O/L ratio towards variance. Pod yield was positively associated with 100-seed weight, oil and protein contents. Oil content had weak association with protein content, oleic acid and O/L ratio. UPGMA clustering revealed grouping of cultivars based on origin and its area recommendation. Cultivars superior for yield (GPBD-4, M-28-2 and JL 24) and confectionery traits (S-230 and Dh-8) were identified. Strong positive relation of yield with confectionery traits indicates possibility of breeding high yielding confectionery grade cultivars. Multivariate analytical tools could be used to identify parents for location specific breeding for improvement of Confectionary traits.

Searching rice cultivars or variety with good processing and high in important essential nutrients are prime important in the present context of rice research. The north eastern hill region of India which is a mega biodiversity hot spot of the world has numerous cultivars of rice with tremendous potential of high quality rice. Eighteen indigenous cultivars of Tripura, a north eastern hill state of India were subjected to the study. Majority of the cultivars were of short bold grain type. Eleven cultivars were aromatic type with one cultivar of strong aroma comparable to Basmati rice. Eleven cultivars were found to possess higher hulling percentage more than 65% and six cultivars with more than 65% out turn. Majority of the cultivars had low amylose contents (<20%). Four cultivars were having higher total crude protein (>10%), six cultivars were having higher iron contents (>10ppm). In most of the characters, heritability (h 2 ) was more than the genetic advance indicating more of environmental effect. Amylose, crude fibre and iron, genetic advance was high; selection for these traits will improve the genotypic value of selected plants over the parents. High heritability coupled with high genetic advance was found in iron and amylose. The association of crude protein is significant but negative with carbohydrates and amylose, while with crude fat and zinc, the association is significant and positive. Carbohydrate was significantly and positively correlated with ash percent and iron concentration and negatively associated with total fat. There was no significant correlation between carbohydrate and amylose.

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Twenty one genotypes of pigeon pea were evaluated in a randomized complete block design during the Kharif season of 2007-08, 2008-09 and 2009-10 based upon number of primary branches per plant, pod length, number of grains per pod, 100-seed weight and seed yield per plant. The stability was studied by deploying AMMI (additive main effects and multiplicative interaction) model. The significant differences among the years were observed and measured more than 50% of the treatment sum of squares. First principal component axis (PCA1) of the interaction captured more than 60% of the interaction sum of squares for almost all the traits studied. The mean seed yield per plant was found highest (39.15 g) and at par similar in all the three years. Nine stable and high yielding genotypes viz., PUSA 2003-1; CORG-2001-5; WREG- 28; PANT-A-286; H-94-6; GT 101; ICPL-99004; ICPL-85010 and UPAS-120 exhibited stable performance under the rainfed environmental conditions for more than one traits studied and also under more than one year.

Selection of genotype for target environment is affected by genotype-by-environment interactions (GEI) and AMMI model is widely used tool to analyse GEI. AMMI does not quantify stability measure making it difficult to rank genotypes. To overcome this lacuna AMMI model output is used to quantify stability measures and rank genotypes. Of several stability measures available in literature, only AMMI stability value (ASV) is implemented in package ‘agricole’ and others have not been implemented in any other R packages. ‘ammistability’ uses output from ‘AMMI’ function in ‘agricolae’ package and computes various stability parameters for AMMI model. Further, genotypes are ranked on the basis of simultaneous selection of yield and stability (SSI). Package also helps to study association among several stability measures.