GGE biplot analysis to evaluate genotype, environment and their interactions in sorghum multi-location data

Sorghum [Sorghum bicolor (L.) Moench] is a very important crop in the arid and semi-arid tropics of India and African subcontinent. In the process of release of new cultivars using multi-location data major emphasis is being given on the superiority of the new cultivars over the ruling cultivars, while very less importance is being given on the genotype?×?environment interaction (GEI). In the present study, performance of ten Indian hybrids over 12 locations across the rainy seasons of 2008 and 2009 was investigated using GGE biplot analysis. Location attributed higher proportion of the variation in the data (59.3–89.9%), while genotype contributed only 3.9–16.8% of total variation. Genotype?×?location interaction contributed 5.8–25.7% of total variation. We could identify superior hybrids for grain yield, fodder yield and for harvest index using biplot graphical approach effectively. Majority of the testing locations were highly correlated. ‘Which-won-where’ study partitioned the testing locations into three mega-environments: first with eight locations with SPH 1606/1609 as the winning genotypes; second mega-environment encompassed three locations with SPH 1596 as the winning genotype, and last mega-environment represented by only one location with SPH 1603 as the winning genotype. This clearly indicates that though the testing is being conducted in many locations, similar conclusions can be drawn from one or two representatives of each mega-environment. We did not observe any correlation of these mega-environments to their geographical locations. Existence of extensive crossover GEI clearly suggests that efforts are necessary to identify location-specific genotypes over multi-year and -location data for release of hybrids and varieties rather focusing on overall performance of the entries.     

Genetics of resistance to Sesamia inferens infestation and its correlation with yield in maize

Sesamia inferens (Walker) causes 25.7–78.9% losses in maize production in South and South‐East Asia. The genetic basis of host plant resistance is the prerequisite for resistance breeding. Twenty‐four populations derived from S. inferens resistant × susceptible inbreds were used to study the genetic regulation of resistance to S. inferens in maize, to determine the importance of genetic effects through generation mean analysis (GMA) and to understand correlation between resistance and yield. Resistant and susceptible inbreds differed significantly in leaf and stem injury ratings (LSIR), a measure of host plant resistance. Mean LSIR range among resistant and susceptible parents was 2.15–2.55 and 7.83–8.22, respectively. The broad‐sense heritability ranged from 0.40 to 0.71, and the mean number of effective factors ranged from 1.9 to 2.6. The resistance against S. inferens was largely governed by additive × additive (i), followed by dominance (d) and additive (a) gene effects. Significant negative correlation (?0.27 to ?0.96) was observed between LSIR and yield. The findings suggest reciprocal recurrent selection for development of new inbreds with resistance followed by their involvement in hybrid development to exploit additive and non‐additive gene effects/variance.     

Modelling regional level spatial distribution of aphid (Lipaphis erysimi) growth in Indian mustard using satellite-based remote sensing data

Abstract

We developed a procedure for preparing a model for mapping spatially distributed zones of aphid pest (Lipaphis erysimi) outbreaks at a regional level. This study employed near-surface meteorological parameters derived from National Oceanic and Atmospheric Administration (NOAA) Television and Infra-Red Operational Satellites (TIROS) Operational Vertical Sounder (TOVS) data and field observations of disease infestation. The study area comprised three sites representing semi-arid and sub-humid regions of dominant Indian mustard (Brassica juncea L.)-growing regions of India. A model based on TOVS-derived cumulative surface air temperature and minimum specific humidity (SpH) was developed to estimate the date of ‘aphid onset’ (first appearance), date of peak infestation and location of severity with respect to aphid population density. Aphid population growth rate during the linear growth phase between aphid onset to peak was computed using SpH-weighted temperature and dates of sowing of the crop (crop age). Sowing dates of mustard crop, of northwest India, were obtained from spectral growth profiles derived from time series remote sensing (RS) products of the SPOT-4 VEGETATION sensor. Estimated dates of peak aphid infestation and peak population showed a strong match with the observed data. The location of peak aphid population density was depicted in each spatial grid of 25×25 km² for parts of northwest India. The simulated aphid population build-up and date of peak population density was validated with observed data for an unknown site in the Sriganganager district, Rajasthan state, India. Comparison of predicted dates of attaining peak aphid population with observations showed a deviation of ±7 days. After validation, the regional level model was applied over a large area of a mustard-growing region for varying dates of sowing, surface air temperature and specific humidity, to show the spatial distribution of aphid growing severity zones (population density) and to predict dates of severe aphid infestation (peak population) at each grid level in the region.     

Effect of street trees on microclimate and air pollution in a tropical city

One of the fastest growing cities in India, Bangalore is facing challenges of urban microclimate change and increasing levels of air pollution. This paper assesses the impact of street trees in mitigating these issues. At twenty locations in the city, we compare segments of roads with and without trees, assessing the relationship of environmental differences with the presence or absence of street tree cover. Street segments with trees had on average lower temperature, humidity and pollution, with afternoon ambient air temperatures lower by as much as 5.6 °C, road surface temperatures lower by as much as 27.5 °C, and SO₂ levels reduced by as much as 65%. Suspended Particulate Matter (SPM) levels were very high on exposed roads, with 50% of the roads showing levels approaching twice the permissible limits, while 80% of the street segments with trees had SPM levels within prescribed limits. In an era of exacerbated urbanization and climate change, tropical cities such as Bangalore will have to face some of the worst impacts including air pollution and microclimatic alterations. The information generated in this study can help appropriately assess the environmental benefits provided by urban trees, providing useful inputs for urban planners.     

Development of NILs from heterogeneous inbred families for validating the rust resistance QTL in peanut (Arachis hypogaea L.)

Heterogeneous inbred families segregating for rust resistance were identified from the two crosses involving susceptible (TAG 24 and TG 26) and resistant (GPBD 4) varieties of peanut. Rust‐resistant (less than score 5) and rust‐susceptible (more than score 5) plants were identified in each HIF and evaluated under rust epiphytotic conditions. The set of plants belonging to the same HIF, but differing significantly in rust resistance, not in other morphological and productivity traits, was regarded as near‐isogenic lines (NILs). Largely, rust‐resistant NILs had GPBD 4‐type allele, and susceptible NILs carried either TAG 24 or TG 26‐type allele at the three SSR loci (IPAHM103, GM1536 and GM2301) linked to a major genomic region governing rust resistance. Comparison of the remaining genomic regions between the NILs originating from each of the HIFs using transposon markers indicated a considerably high similarity of 86.4% and 83.1% in TAG 24 × GPPBD 4 and TG 26 × GPBD 4, respectively. These NILs are useful for fine mapping and expression analysis of rust resistance.     

Analysis of coat protein gene sequences of begomoviruses associated with different weed species in India

Sida cordifolia L., Croton bonplandianum L., Malachra capitata L., Eclipta prostrata L., Clerodendron inerme L., Acalypha indica L., and Urena lobata L. are common weeds found all over India. They are often infected by different begomovirus complexes and may act as reservoirs of crop-infecting begomoviruses. Cloning and sequencing were done to partially characterize the begomovirus complexes associated with these weed species from the eastern part of India and their genetic pattern was compared with respective geographical isolates throughout India. Coat protein (CP) genes were found to be amplified from all the infected samples tested in this study, whereas betasatellite molecules amplified only from four infected samples (Sida, Croton, Malachra and Urena). Sequence analysis using CP genes and betasatellites of the present begomovirus complexes showed significant variation among their geographical isolates and also exhibited closeness to different crop-infecting begomovirus complexes. The majority of the weed-infecting begomovirus complexes characterized in this paper are reported for the first time from India.