Evaluation of Barley Genotypes Against Spot Blotch Disease in Inner Tarai Region of Nepal

Spot blotch caused by Bipolaris sorokiniana (Sacc. in Sorok.) Shoem. is an important disease of barley (Hordeum vulgare L.). A total of 126 barley genotypes received from Hill Crops Research Program, Kabre, Dolakha having SoluUwa as a susceptible check and Bonus as a resistant check were evaluated as barley disease screening nursery (BDSN) under natural epiphytotic condition at National Maize Research Program, Rampur, Chitwan during winter seasons of 2017 and 2018. The nursery was planted in augmented design. The resistant and susceptible checks were repeated and planted after each 10 tested entries. The unit plot size was 2 rows of one meter length for each genotype planted continuously with 25cm row to row spacing. The seed rate was 100 kg/ha. The recommended fertilizer dose of 23:30:0 N:P2O5:K2O kg/ha was applied. The double digit scale (00 to 99) was used to measure overall foliar infection on the whole plant during flowering, soft dough and hard dough stages. Other agronomic practices were followed as per recommendation. Genotypes B86019-1K-3K-0K3, ACC 2087, ACC 2441, ACC GHv-06816, ACC 1597, ACC 1612, ACC 2059 and ACC 2032 were resistant against spot blotch disease. Similarly, 32 barley genotypes were moderately resistant and rest of the tested genotypes were susceptible to the disease. The selected resistant barley genotypes can be used in crossing program and/or promoted for further testing to develop spot blotch resistant varieties for inner Tarai region of Nepal

Management of blast disease of finger millet (Eleusine coracana L. Gaertn) caused by Pyricularia grisea under field conditions in Dolakha, Nepal

Lack of understanding regarding the choice of chemical fungicides or botanicals with their optimal doze and spraying schedule is one of the major problems concerning mid-hill farmers to control finger millet diseases in Nepal. In order to assess the effectiveness of the four fungicides, namely Bavistin 50 WP (Carbendazim 50%), SAAF (Carbendazim 12% + Mancozeb 63% WP), RIDOMIL-MZ 72 WP (Metalyxl 8% + Mancozeb 64% WP), BAAN 75 WP (Tricyclazole 75%), and two botanicalsermented anaerobically in cattle urine, an artificial epiphytotic field. In the years 2018 and 2019, the experiment was run using a randomized complete block design with three replications. Carbendazim, one of the chosen treatments, had the greatest impact in lowering the AUDPC values for leaf blast (1818, 1191) as well as neck (4,53) and finger blast (10,45) incidence percentage in both 2018 and 2019 years. Tricyclazole, SAAF, RIDOMIL-MZ, and Lantana camara fermented in cow urine were also discovered to be beneficial throughout the year.  So it is recommended to deploy fungicides in a controlled manner through rotation and mixed applications, which is advantageous for both grain and seed production even for minor and underutilized crops from an economic aspect

On-farm Diversity Assessment and Evaluation of Finger Millet Genotypes in the Mid Hills of Nepal

The objective of the study is to assess the phenotypic diversity among the finger millet genotypes and evaluate overall performance for the recommendation of genotypes to the farming community of mid hills of Nepal. The overall performance of 8 candidate genotypes selected  from diversity block of 46 varieties in 2015, were assessed in randomized complete block design (RCBD) with three replicates under on-farm conditions in Lamjung district during 2016. Highly significant (p?0.01) variability among the selected 8 genotypes for agro-morphological traits viz., plant height, number of fingers per head, grain yield, 1000 grain weight, straw yield, days to heading and maturity was revealed. Strong inter-correlation among grain yield, plant height, time to flowering and straw yield was detected. The traits viz., plant height, grain yield, straw yield, days to heading and days to maturity were the most important traits contributing to the overall variability and thus, provide options for selection

Doping liquid argon with xenon in ProtoDUNE Single-Phase: effects on scintillation light

Doping of liquid argon TPCs (LArTPCs) with a small concentration of xenon is a technique for light-shifting and facilitates the detection of the liquid argon scintillation light. In this paper, we present the results of the first doping test ever performed in a kiloton-scale LArTPC. From February to May 2020, we carried out this special run in the single-phase DUNE Far Detector prototype (ProtoDUNE-SP) at CERN, featuring 720 t of total liquid argon mass with 410 t of fiducial mass. A 5.4 ppm nitrogen contamination was present during the xenon doping campaign. The goal of the run was to measure the light and charge response of the detector to the addition of xenon, up to a concentration of 18.8 ppm. The main purpose was to test the possibility for reduction of non- uniformities in light collection, caused by deployment of photon detectors only within the anode planes. Light collection was analysed as a function of the xenon concentration, by using the pre-existing photon detection system (PDS) of ProtoDUNE-SP and an additional smaller set-up installed specifically for this run. In this paper we first summarize our current understanding of the argon-xenon energy transfer process and the impact of the presence of nitrogen in argon with and without xenon dopant. We then describe the key elements of ProtoDUNE-SP and the injection method deployed. Two dedicated photon detectors were able to collect the light produced by xenon and the total light. The ratio of these components was measured to be about 0.65 as 18.8 ppm of xenon were injected. We performed studies of the collection efficiency as a function of the distance between tracks and light detectors, demonstrating enhanced uniformity of response for the anode-mounted PDS. We also show that xenon doping can substantially recover light losses due to contamination of the liquid argon by nitrogen

Supernova Pointing Capabilities of DUNE

The determination of the direction of a stellar core collapse via its neutrino emission is crucial for the identification of the progenitor for a multimessenger follow-up. A highly effective method of reconstructing supernova directions within the Deep Underground Neutrino Experiment (DUNE) is introduced. The supernova neutrino pointing resolution is studied by simulating and reconstructing electron-neutrino charged-current absorption on $^{40}$Ar and elastic scattering of neutrinos on electrons. Procedures to reconstruct individual interactions, including a newly developed technique called ``brems flipping'', as well as the burst direction from an ensemble of interactions are described. Performance of the burst direction reconstruction is evaluated for supernovae happening at a distance of 10 kpc for a specific supernova burst flux model. The pointing resolution is found to be 3.4 degrees at 68% coverage for a perfect interaction-channel classification and a fiducial mass of 40 kton, and 6.6 degrees for a 10 kton fiducial mass respectively. Assuming a 4% rate of charged-current interactions being misidentified as elastic scattering, DUNE's burst pointing resolution is found to be 4.3 degrees (8.7 degrees) at 68% coverage.Comment: 25 pages, 16 figure

Neutrino interaction vertex reconstruction in DUNE with Pandora deep learning

The Pandora Software Development Kit and algorithm libraries perform reconstruction of neutrino interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at the Deep Underground Neutrino Experiment, which will operate four large-scale liquid argon time projection chambers at the far detector site in South Dakota, producing high-resolution images of charged particles emerging from neutrino interactions. While these high-resolution images provide excellent opportunities for physics, the complex topologies require sophisticated pattern recognition capabilities to interpret signals from the detectors as physically meaningful objects that form the inputs to physics analyses. A critical component is the identification of the neutrino interaction vertex. Subsequent reconstruction algorithms use this location to identify the individual primary particles and ensure they each result in a separate reconstructed particle. A new vertex-finding procedure described in this article integrates a U-ResNet neural network performing hit-level classification into the multi-algorithm approach used by Pandora to identify the neutrino interaction vertex. The machine learning solution is seamlessly integrated into a chain of pattern-recognition algorithms. The technique substantially outperforms the previous BDT-based solution, with a more than 20% increase in the efficiency of sub-1 cm vertex reconstruction across all neutrino flavours

The track-length extension fitting algorithm for energy measurement of interacting particles in liquid argon TPCs and its performance with ProtoDUNE-SP data

This paper introduces a novel track-length extension fitting algorithm for measuring the kinetic energies of inelastically interacting particles in liquid argon time projection chambers (LArTPCs). The algorithm finds the most probable offset in track length for a track-like object by comparing the measured ionization density as a function of position with a theoretical prediction of the energy loss as a function of the energy, including models of electron recombination and detector response. The algorithm can be used to measure the energies of particles that interact before they stop, such as charged pions that are absorbed by argon nuclei. The algorithm's energy measurement resolutions and fractional biases are presented as functions of particle kinetic energy and number of track hits using samples of stopping secondary charged pions in data collected by the ProtoDUNE-SP detector, and also in a detailed simulation. Additional studies describe the impact of the dE/dx model on energy measurement performance. The method described in this paper to characterize the energy measurement performance can be repeated in any LArTPC experiment using stopping secondary charged pions

Performance of a modular ton-scale pixel-readout liquid argon time projection chamber

The Module-0 Demonstrator is a single-phase 600 kg liquid argon time projection chamber operated as a prototype for the DUNE liquid argon near detector. Based on the ArgonCube design concept, Module-0 features a novel 80k-channel pixelated charge readout and advanced high-coverage photon detection system. In this paper, we present an analysis of an eight-day data set consisting of 25 million cosmic ray events collected in the spring of 2021. We use this sample to demonstrate the imaging performance of the charge and light readout systems as well as the signal correlations between the two. We also report argon purity and detector uniformity measurements and provide comparisons to detector simulations