Management of diseases and insect-pests of French bean in Northwestern Indian Himalayan region using integrated approaches

French bean (Phaseolus vulgaris L.) production is adversely affected by many pathogens and insect-pests worldwide. In the present investigation, effect of different bio-fortified composts, organic amendments, botanicals and pesticides were evaluated against diseases and insect- pests of french bean. The results showed that seed treatment and drenching with Trichoderma harzianum strain 11, followed by soil application of fortified farmyard manure resulted in the lowest root rot incidence, highest germination, vigour and yield in french bean. In another set of experiment, soil incorporation of Parthenium hysterophorus, Urtica dioicaandLantana camarawere found to reduce root rot incidence with high germination and pod yield. Among the bioproducts and botanicals tested, foliar spray of cow dung extract (50%) reduced angular leaf spot, rust and bacterial blight severity by 51, 69 and 25 per cent, respectively. Among the fungicides, foliar application of azoxystrobin 23 SC (0.1%) and difenoconazole 25EC (0.025%), also reduced angular leaf spot and rust severity by 93 and 90 per cent, respectively. Among different insect pest management strategies under field conditions, cartap hydrochloride and batain seed extract registered low sucking bug (Chauliops choprai) population. Integrated approaches including bio-agents, botanicals along with chemicals for managing these diseases and insect-pests were found appropriate options. Out of six different IPM modules evaluated, seed treatment with carbendazim along with foliar spray of 0.1% azoxystrobin and cartap hydrochloride resulted in lowest root rot, rust, angular leaf spot, bacterial blight and Chaulopsis choprai bug population in French bean

Multivariate analysis of pearl millet data to delineate genetic variation

Loss of biodiversity not only disturbs the process of plant development aimed at genetic amelioration but also disrupts the fundamental services that ecosystems provided to humanity. Assessment of variability is a multidimensional problem. The multivariate statistics can help in a comparative assessment of genetic variability. A set of 66 lines of pearl millet was analyzed for cluster and principal component analysis (PCA). PCA identified six principal components which explained 77.7 per cent of total variability among the 66 genotypes. The PC1 characters –main ear weight, dry fodder weight, total ear weight, grain yield, growth rate and plant height, the major characters of plant biomass and the basis for grain yield contributed maximum 35.94 per cent variability among the lines. The remaining PCs accounted for progressively lesser and lesser amount of variability. The lowest contribution 5.27 per cent was recorded by PC 6, the characters grain starch, starch recovery and ear girth. Only grain starch contributed positively to all the six components. The genotypes 50 (77/371), 3 (IPC-115), 41 (204/2 MP), 12 (IPC-1462), 37 (TCH-37-1), 22 (TCH-10-1), 61 (1307), 14 (862-P2), 20 (TCH-3-2), 40 (204-2-3) were found to be better performers and diverse on the basis of principal factor scores with regard to grain yield and yield contributing characters. Hierarchical cluster analysis grouped 66 genotypes into six clusters, cluster 1 included maximum number of 21 genotypes and clusters 3 and 6 had the lowest number of 6 genotypes. The results on hierarchical cluster analysis almost mimicked the PCA. The grouping pattern of genotypes obtained by cluster analysis and PCA plots was almost similar. A wide range of diversity for most of the traits observed would enable to pick lines with suitable traits to be used in a breeding programme. Genetic diversity was not essentially associated with geographic diversity

Sensors for Harsh Environment: Radiation Resistant FBG Sensor System

This paper presents radiation resistant characteristics of fibre Bragg grating (FBG) sensors written in a photosensitive fiber and connected to a silica core radiation resistant optical fibre, aiming to develop a sensor system suitable for both sensing and data transmission in harsh environment. The silica core fluorine-down-doped clad optical fibre has been specifically designed and fabricated for this study using the modified chemical vapor deposition technique. Key waveguide parameters, including the width of the fluorine doped inner cladding have been optimized to obtain a low loss (<;0.2 dB/km) at the operating wavelength region of 1550 nm. The fibre fabrication process, mainly the deposition condition, has also been optimized to achieve smooth deposition and sintering of silica core layers, to minimize radiation induced absorption. As a result, radiation induced absorption of ~2.2 dB/km at 1550 nm under accumulated dose of 25 MRad at dose rate of 0.39 MRad/hr has been successfully achieved. To create an effective sensor system for harsh environmental conditions, this specialty fibre is connected to a number of FBGs (sensors) fabricated in photosensitive fibres prior to their extensive evaluations by being exposed to different accumulated dose of gamma radiation. Their corresponding Bragg wavelength shifts (BWS) and peak amplitudes were continuously monitored. It was found that the radiation induced BWS can be greatly reduced by shielding the sensors using stainless steel tubing. The temperature sensitivity and peak amplitude were found to be largely unchanged before and after exposure to Gamma radiation of 25 MRad which shows their potential use for temperature measurements in radiation environments with an uncertainty of around 0.1 °C

MAPPING OF STRIP FOREST IN ADAMPUR RANGE (HARYANA) A GEO-INFORMATICS APPROACH

Haryana state is an intensively cultivated state, and deficient in natural forests. One of the mandate of Haryana Forest Department (HFD) is to afforest for maintenance of environmental stability and restoration of ecological balance affected by serious depletion of forests, woodlands and water, and to increase tree cover in the state. National Forest Policy (1988) has set a goal to bring one third of Country’s area under forest and tree cover. Stock and dynamics of Trees Outside Forests (TOF) along with natural forests need to be understood holistically to appreciate the ecosystem services e.g., timber and non-wood products as tangible benefits along with services like carbon, water and weather moderation. The present study has attempted to demonstrate the utility of High Resolution Worldview-II (WV) satellite data (ortho rectified) that offeres immense scope to analyze the strip forests in Hisar district (Haryana, India). The study area Adampur Range (Hisar District) lies between the north latitudes 29&deg;0′52.229″ to 29&deg;25′6.746″ and east longitudes 75&deg;14′0.266″ to 75&deg;45′11.093″ with a total geographical area of about 1092.04&thinsp;sq.&thinsp;km. The adopted methodology involves onscreen digitization of the strip forest areas in the Adampur range (Hisar Distirct). The ToF formation identification and delineation includes the forest land besides roads, river, streams, canals, distributaries and railway lines etc. The shape files were converted into .kml files and overlaid on the Google Earth data for validation. An attempt has been made to compare the area difference between the Haryana Forest Department (HFD) notification details with that of the digitized strip forest lands. It was observed that the surveyed forest area is found to be 1717.37&thinsp;ha. against the notified forest area of 1714.45&thinsp;ha. showing a difference of 2.92&thinsp;ha. approximately in the studied beat boundaries

Driving factors of aerosol properties over the foothills of central Himalayas based on 8.5 years continuous measurements

This study presents analysis of in situ measurements conducted over the period 2005–2014 in the Indian Himalayas to give a thorough overview of the factors and causes that drive aerosol properties. Aerosol extensive properties (namely, particle number concentration, scattering coefficient, equivalent black carbon, PM2.5, and PM10) have 1.5–2 times higher values in the early to late afternoon than during the night, and a strong seasonality. The interannual variability is ±20% for both PM2.5 and total particle number concentration. Analysis of the data shows statistically significant decreasing trends of −2.3 μg m−3 year−1 and −2.7 μg m−3 year−1 for PM2.5 and PM10, respectively, over the study period. The mountainous terrain site (Mukteshwar, MUK) is primarily under the influence of air from the plains. This is due to convective transport processes that are enhanced by local and mesoscale topography, leading to pronounced valley/mountain winds and consequently to atmospheric boundary layer air lifting from the plains below. The transport from plains is evident in seasonal‐diurnal patterns observed at MUK. The timing of the patterns corresponds with changes in turbulence and water vapor (q). According to our analysis, using these as proxies is a viable method for examining boundary layer influence in the absence of direct atmospheric boundary layer height measurements. Comparing the measurements with climate models shows that even regional climate models have problems capturing the orographic influence accurately at MUK, highlighting the importance of long‐term direct measurements at multiple points to understand aerosol behavior in mountainous areas

Correction for a measurement artifact of the Multi-Angle Absorption Photometer (MAAP) at high black carbon mass concentration levels

The Multi-Angle Absorption Photometer (MAAP) is a widely-used instrument for aerosol black carbon (BC) measurements. In this paper, we show correction methods for an artifact found to affect the instrument accuracy in environments characterized by high black carbon concentrations. The artifact occurs after a filter spot change – as BC mass is accumulated on a fresh filter spot, the attenuation of the light (raw signal) is weaker than anticipated. This causes a sudden decrease, followed by a gradual increase in measured BC concentration. The artifact is present in the data when the BC concentration exceeds ~3 μg m&lt;sup&gt;−3&lt;/sup&gt; at the typical MAAP flow rate of 16.7 L min&lt;sup&gt;−1&lt;/sup&gt; or 1 m&lt;sup&gt;3&lt;/sup&gt; h&lt;sup&gt;−1&lt;/sup&gt;. The artifact is caused by erroneous dark counts in the photodetector measuring the transmitted light, in combination with an instrument internal averaging procedure of the photodetector raw signals. It was found that, in addition to the erroneous temporal response of the data, concentrations higher than 9 μg m&lt;sup&gt;−3&lt;/sup&gt; (at the flow rate of 16.7 L min&lt;sup&gt;−1&lt;/sup&gt;) are underestimated by the MAAP. The underestimation increases with increasing BC accumulation rate. At a flow rate of 16.7 L min&lt;sup&gt;−1&lt;/sup&gt; and concentration of about 24 μg m&lt;sup&gt;−3&lt;/sup&gt; (BC accumulation rate ~0.4 μg min&lt;sup&gt;−1&lt;/sup&gt;), the underestimation is about 30%. There are two ways of overcoming the MAAP artifact. One method is by logging the raw signal of the 165° photomultiplier measuring the reflected light from the filter spot. As this signal is not affected by the artifact, it can be converted to approximately correct absorption and BC values. However, as the typical print formats of the MAAP do not give the reflected signal as an output, a semi-empirical correction method was developed based on laboratory experiments to correct for the results in the post-processing phase. The correction function was applied to three MAAP datasets from Gual Pahari (India), Beijing (China), and Welgegund (South Africa). In Beijing, the results could also be compared against a photoacoustic spectrometer (PAS). The correction improved the quality of all three MAAP datasets substantially, even though the individual instruments operated at different flow rates and in different environments

FOREST CANOPY DENSITY ASSESSMENT USING HIGH RESOLUTION LISS-4 DATA IN YAMUNANAGAR DISTRICT, HARYANA

Forest plays an important role not only in providing ecological services but also economic goods to human beings. However, with increase in population there is a wide gap between demand and supply of these goods and services. This has lead to reduction in forest cover which needs to be taken care on regular time interval. To manage the existing forest area and also to increase the forest cover Forest Canopy Density (FCD) methodology is the main factor which was given by International Tropical timber Organization (ITTO). High resolution remote sensing LISS-4 data gives us chance to assess the quality of forest in terms of FCD as Rikimaru et al (1999) stated that FCD is one important parameter to assess forest cover quality. High resolution LISS-4 data analysis for FCD was never attempted before. Authors here attempted to assess the FCD utilizing methodology adopted by Rikimaru (1999), Huang (2001), Azizia (2008). The adopted methodology is one of the most efficient and cost effective way to derive the FCD. For this study Resourcesat-2 LISS-4 post monsoon data of year 2017 for Yamunanagar district was used to assess FCD within notified forest boundary. Notified forest boundaries at cadastral level prepared previously by Haryana Space Applications Centre (HARSAC) was used. The degree of forest canopy density is expressed in percentages: i.e. &lt;&thinsp;10% FCD (scrub land), 10–20% (Open Forest-I), 20–40% (Open Forest-II), 40–60% (Moderate Dense), 60–80% (Medium Dense) and &gt;&thinsp;80% (Highly Dense). Forest Canopy Density was based on three indices i.e. Advanced Vegetation Index (AVI), Bare Soil Index (BSI) and Canopy Shadow Index (CSI). Accuracy assessment was done based on ground data and comparison with Coterminous Google Earth imagery and it was found that the devised methodology has achieved overall accuracy of 93% with kappa coefficient of 0.9153. The result shows that maximum forest area in Yamunanagar district is in medium dense FCD category which is approximately 23948.08 acres. This study tells us that 24.2% of the total forest area is under scrub land and open forest which should be focussed for activities in working plan to increase the forest cover. This paper highlights the utility of high resolution satellite data for monitoring and management of forest and improvement in its quality. This attempt provided large scale (1&thinsp;:&thinsp;10,000) maps to the forest managers to better equip them in planning for afforestation, reforestation and rehabilitation of water logged areas, environment management and their future aspect

Genome sequence of a dengue virus serotype 2 strain identified during the 2019 outbreak in Bangladesh

A nearly complete genome sequence of a dengue virus serotype 2 strain detected in the serum of a patient in 2019 during the largest outbreak of dengue fever in Bangladesh is reported

An overview of the first decade of PollyNET : an emerging network of automated Raman-polarization lidars for continuous aerosol profiling

© Author(s) 2016. This work is distributed under the Creative Commons Attribution 3.0 LicenseA global vertically resolved aerosol data set covering more than 10 years of observations at more than 20 measurement sites distributed from 63° N to 52° S and 72° W to 124° E has been achieved within the Raman and polarization lidar network PollyNET. This network consists of portable, remote-controlled multiwavelength-polarization-Raman lidars (Polly) for automated and continuous 24/7 observations of clouds and aerosols. PollyNET is an independent, voluntary, and scientific network. All Polly lidars feature a standardized instrument design with different capabilities ranging from single wavelength to multiwavelength systems, and now apply unified calibration, quality control, and data analysis. The observations are processed in near-real time without manual intervention, and are presented online at http://polly.tropos.de/. The paper gives an overview of the observations on four continents and two research vessels obtained with eight Polly systems. The specific aerosol types at these locations (mineral dust, smoke, dust-smoke and other dusty mixtures, urban haze, and volcanic ash) are identified by their Ångström exponent, lidar ratio, and depolarization ratio. The vertical aerosol distribution at the PollyNET locations is discussed on the basis of more than 55 000 automatically retrieved 30 min particle backscatter coefficient profiles at 532 nm as this operating wavelength is available for all Polly lidar systems. A seasonal analysis of measurements at selected sites revealed typical and extraordinary aerosol conditions as well as seasonal differences. These studies show the potential of PollyNET to support the establishment of a global aerosol climatology that covers the entire troposphere.Peer reviewe

Spatial distributions and seasonal cycles of aerosol climate effects in India seen in a global climate-aerosol model

Climate-aerosol interactions in India are studied by employing the global climate-aerosol model ECHAM5-HAM and the GAINS inventory for anthropogenic aerosol emissions. Model validation is done for black carbon surface concentrations in Mukteshwar and for features of the monsoon circulation. Seasonal cycles and spatial distributions of radiative forcing and the temperature and rainfall responses are presented for different model setups. While total aerosol radiative forcing is strongest in the summer, anthropogenic forcing is considerably stronger in winter than in summer. Local seasonal temperature anomalies caused by aerosols are mostly negative with some exceptions, e.g., parts of northern India in March-May. Rainfall increases due to the elevated heat pump (EHP) mechanism and decreases due to solar dimming mechanisms (SDMs) and the relative strengths of these effects during different seasons and for different model setups are studied. Aerosol light absorption does increase rainfall in northern India, but effects due to solar dimming and circulation work to cancel the increase. The total aerosol effect on rainfall is negative for northern India in the months of June-August, but during March-May the effect is positive for most model setups. These differences between responses in different seasons might help converge the ongoing debate on the EHPs and SDMs. Due to the complexity of the problem and known or potential sources for error and bias, the results should be interpreted cautiously as they are completely dependent on how realistic the model is. Aerosol-rainfall correlations and anticorrelations are shown not to be a reliable sole argument for deducing causality