Rice blast disease caused by Magnaporthe oryzae is one of the most destructive disease causing huge losses to rice yield in different parts of the world. Therefore, an attempt has been made to find out the resistance by screening and studying the genetic diversity of eighty released rice varieties by National Rice Research Institute, Cuttack (NRVs) using molecular markers linked to twelve major blast resistance (R) genes viz Pib, Piz, Piz-t, Pik, Pik-p, Pikm Pik-h, Pita/Pita-2, Pi2, Pi9, Pi1 and Pi5. Out of which, nineteen varieties (23.75%) showed resistance, twenty one were moderately resistant (26.25%) while remaining forty varieties (50%) showed susceptible in uniform blast nursery. Rice varieties possessing blast resistance genes varied from four to twelve and the frequencies of the resistance genes ranged from 0 to 100%. The cluster analysis grouped the eighty NRVs into two major clusters at 63% level of genetic similarity coefficient. The PIC value for seventeen markers varied from 0 to 0.37 at an average of 0.20. Out of seventeen markers, only five markers, 195R-1, Pi9-i, Pita3, YL155/YL87 and 40N23r corresponded to three broad spectrum R genes viz. Pi9, Pita/Pita2 and Pi5 were found to be significantly associated with the blast disease with explaining phenotypic variance from 3.5% to 7.7%. The population structure analysis and PCoA divided the entire 80 NRVs into two sub-groups. The outcome of this study would help to formulate strategies for improving rice blast resistance through genetic studies, plant-pathogen interaction, identification of novel R genes, development of new resistant varieties through marker-assisted breeding for improving rice blast resistance in India and worldwide.

Drought is an important global hazard, challenging the sustainable agriculture and food security of nations. Measuring agricultural drought vulnerability is a prerequisite for targeting interventions to improve and sustain the agricultural performance of both irrigated and rain-fed agriculture. In this study, crop-generic agricultural drought vulnerability status is empirically measured through a composite index approach. The study area is Haryana state, India, a prime agriculture state of the country, characterised with low rainfall, high irrigation support and stable cropping pattern. By analysing the multiyear rainfall and crop condition data of kharif crop season (June-October) derived from satellite data and soil water holding capacity and groundwater quality, nine contributing indicators were generated for 120 blocks (sub-district administrative units). Composite indices for exposure, sensitivity and adaptive capacity components were generated after assigning variance-based weightages to the respective input indicators. Agricultural Drought Vulnerability Index (ADVI) was developed through a linear combination of the three component indices. ADVI-based vulnerability categorisation revealed that 51 blocks are with vulnerable to very highly vulnerable status. These blocks are located in the southern and western parts of the state, where groundwater quality is saline and water holding capacity of soils is less. The ADVI map has effectively captured the spatial pattern of agricultural drought vulnerability in the state. Districts with large number of vulnerable blocks showed considerably larger variability of de-trended crop yields. Correlation analysis reveals that crop condition variability, groundwater quality and soil factors are closely associated with ADVI. The vulnerability index is useful to prioritise the blocks for implementation of long-term drought management plans. There is scope for improving the methodology by adding/fine-tuning the indicators and by optimising the weights.

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The grain size is one of the complex trait of rice yield controlled by a plethora of interaction of several genes in different pathways. The present study was undertaken to investigate the influence of seven known grain size regulating genes: DEP1, GS7, GS3, GW8, GL7, GS5 and GW2. A wide phenotypic variation for grain length, grain width and grain length-width ratio were observed in 89 germplasm. The correlation analysis showed a strong association among these three grain traits viz. GL, GW, GLWR and TGW which play important roles in determining the final rice grain size. Except for GW2, all six genes showed strong association with grain size traits. A total of 21 alleles were identified with an average of 2.1 allele/locus in 89 germplasm of which seven alleles were found to be favourable alleles for improving the grain size with the frequency range of 24 (26.97%) to 82 (92.13%); the largest was found in GS5 followed by GW8, GL7, DEP1, GS3 and GS7 genes. Through ANOVA, four markers (GS3-PstI, S9, GID76 and GID711) of three genes (GS3, DEP1 and GL7) were found significantly associated with all the three traits (GL, GLWR and TGW). Concurrent results of significant associations of grain size traits with other markers were observed in both analysis of variance and genetic association through the general linear model. Besides, the population structure analysis, cluster analysis and PCoA divided the entire germplasm into three sub-groups with the clear-cut demarcation of long and medium grain types. The present results would help in formulating strategies by selecting suitable candidate markers/genes for obtaining preferred grain shape/size and improving grain yield through marker-assisted breeding.

Soybean crops showing systemic mottling, mosaic and leaf deformation were observed at high disease incidences (25.1–71.0%) in the kharif season of 2011 and 2012 in the experimental farm of the Indian Agricultural Research Institute (IARI), New Delhi. Symptomatic soybean leaves contained flexuous particles (650 × 12 nm), suggesting an infection by a Carlavirus. The causal virus was characterized as a strain of Cowpea mild mottle virus (CPMMV) on the basis of mechanical inoculation, whitefly transmission, seed transmission and sequencing of the viral genome. This is the first report of natural infection by a distinct strain of CPMMV in soybean in India.