scholarly journals Sustainability assessment of the resistance of smooth bromegrass varieties to the causative agent of helminthosporiosis on an artificial infectious background

2021 ◽  
Vol 104 (2) ◽  
pp. 120-123
Author(s):  
N. Y. Kostenko
Keyword(s):  
Sustainability Assessment ◽  
Perennial Grass ◽  
Common Disease ◽  
Standard Variety ◽  
Seed Productivity ◽  
High Quality ◽  
Smooth Bromegrass ◽  
Brown Leaf Spot ◽  
Brown Leaf

Smooth bromegrass (Bromopsis inermis Holub.) is widespread perennial grass and high quality feed. It is characterized by hight frost resistance. The main direction in breeding work is breeding of varieties with high seed productivity and with increased resistance to diseases. The research was carried out using an artificial infectious background in the immunology laboratory in FWRC FPA (previously, the All-Russian Williams Fodder Research Institute). This research took place in Lobnya, Mytishchi district, Moscow region, in 2018 -2020 years. Long-term phytosanitary monitoring of crops showed that the most common disease of this culture is brown leaf spot (helminthosporium). Seed germination decreases by 21-41% to this patgen. 16 samples of smooth bromegrass was planted in the artificial infectious background to determine their disease resistance in 2018 According to the study carried out, it was found that the disease reaches its peak at the stage of seed ripening. Sample # 2 and sample # 12 on average exceeded the standard variety Fakelny by 12% for resistance to pathogens of helminthosporiosis (among the studied samples, according to three-year data). Sample # 2 and sample # 12 can be recommended for inclusion in the breeding process to create modern intensive type varieties.

Recurrent Phenotypic Selection for Resistance to Brown Leaf Spot in Smooth Bromegrass 1

Crop Science ◽  
1986 ◽  
Vol 26 (3) ◽  
pp. 533-536 ◽  
Author(s):  
Clyde C. Berg ◽  
Robert T. Sherwood ◽  
Kenneth E. Zeiders
Keyword(s):  
Leaf Spot ◽  
Phenotypic Selection ◽  
Smooth Bromegrass ◽  
Brown Leaf Spot ◽  
Brown Leaf ◽  
Selection For

Inheritance of Brown Leaf Spot Resistance in Smooth Bromegrass 1

Crop Science ◽  
1983 ◽  
Vol 23 (1) ◽  
pp. 138-140 ◽  
Author(s):  
C. C. Berg ◽  
R. T. Sherwood ◽  
K. E. Zeiders ◽  
R. R. Hill
Keyword(s):  
Leaf Spot ◽  
Smooth Bromegrass ◽  
Brown Leaf Spot ◽  
Brown Leaf

ANALYSIS OF ABDOMINAL TYPHOID INCIDENCE IN THE SOUTH REGION OF THE KYRGYZ REPUBLIC

2020 ◽  
pp. 43-48
Author(s):  
Zakirova J.S. ◽  
Nadirbekova R.A. ◽  
Zholdoshev S.T.
Keyword(s):  
Drinking Water ◽  
Typhoid Fever ◽  
Risk Groups ◽  
The Body ◽  
Kyrgyz Republic ◽  
Radiation Factor ◽  
High Quality ◽  
Two Generations ◽  
Immunological Deficiency

The article analyze the long-term morbidity, spread of typhoid fever in the southern regions of the Kyrgyz republic, and remains a permanent epidemic focus in the Jalal-Abad region, where against the low availability of the population to high-quality drinking water, an additional factor on the body for more than two generations and radiation factor, which we confirmed by the spread among the inhabitants of Mailuu-Suu of nosological forms of the syndrome of immunological deficiency, as a predictor of risk groups for infectious diseases, including typhoid fever.

One-step synthesis of high-quality vanadium disulfide quantum dots for long-term lysosome-targetable imaging

2021 ◽  
pp. 130544
Author(s):  
Dan Yang ◽  
Liwen Chen ◽  
Le Wang ◽  
Zhongjie Cui ◽  
Zhuoqi Wen ◽  
...  
Keyword(s):  
Quantum Dots ◽  
High Quality ◽  
One Step

scholarly journals Lyell, the Geikies and Croll's observations on terrestrial glacial sediments and landforms

2021 ◽  
pp. 1-14
Author(s):  
James ROSE
Keyword(s):  
Climate Change ◽  
High Quality ◽  
Glacial Sediments ◽  
Direct Observations ◽  
The Social ◽  
The Status ◽  
Social And Physical Environment ◽  
Glacial Landforms

ABSTRACT Within the context of the work and achievements of James Croll, this paper reviews the records of direct observations of glacial landforms and sediments made by Charles Lyell, Archibald and James Geikie and James Croll himself, in order to evaluate their contributions to the sciences of glacial geology and Quaternary environmental change. The paper outlines the social and physical environment of Croll's youth and contrasts this with the status and experiences of Lyell and the Geikies. It also outlines the character and role of the ‘Glasgow School’ of geologists, who stimulated Croll's interest into the causes of climate change and directed his focus to the glacial and ‘interglacial’ deposits of central Scotland. Contributions are outlined in chronological order, drawing attention to: (i) Lyell's high-quality observations and interpretations of glacial features in Glen Clova and Strathmore and his subsequent rejection of the glacial theory in favour of processes attributed to floating icebergs; (ii) the significant impact of Archibald Geikie's 1863 paper on the ‘glacial drift of Scotland’, which firmly established the land-ice theory; (iii) the fact that, despite James Croll's inherent dislike of geology and fieldwork, he provided high-quality descriptions and interpretations of the landforms and sediments of central Scotland in order to test his theory of climate change; and (iv) the great communication skills of James Geikie, enhanced by contacts and evidence from around the world. It is concluded that whilst direct observations of glacial landforms and sediments were critical to the long-term development of the study of glaciation, the acceptance of this theory was dependent also upon the skills, personality and status of the Geikies and Croll, who developed and promoted the concepts. Sadly, the subsequent rejection of the land-ice concept by Lyell resulted in the same factors challenging the acceptance of the glacial theory.

scholarly journals Unconventional effects of long-term storage of microwave-modified chicken egg white lysozyme preparations

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Grzegorz Leśnierowski ◽  
Tianyu Yang ◽  
Renata Cegielska-Radziejewska
Keyword(s):  
Microwave Radiation ◽  
Egg White ◽  
Process Time ◽  
High Quality ◽  
Chicken Egg ◽  
Egg White Lysozyme ◽  
Physicochemical Changes ◽  
Long Term Storage ◽  
Term Storage

AbstractThermal modification is an effective method that induces significant expansion of the antimicrobial properties and other valuable properties of chicken egg white lysozyme. In our latest research, a new innovative method of enzyme modification was developed, in which microwave radiation was used as an energy source to process liquid lysozyme concentrate (LLC). After modification, high-quality preparations were obtained. However, long-term storage in a concentrated form initiated various processes that caused darkening over time and could also lead to other significant changes to their structure and, consequently, to their functional properties. This necessitated multidirectional research to explain this phenomenon. This paper presents the results of research aimed at assessing the physicochemical changes in the properties of microwave-modified lysozyme in the form of a liquid concentrate after long-term storage under refrigeration conditions. The assessment also considered the conditions under the acidity of the modifying medium and the duration of the microwave modification. The analysis showed that the values of the basic parameters determining the quality and usefulness of the modified enzyme significantly improved during long-term storage of the preparations. The greatest changes were observed in the preparations modified for the longest time and in the most acidic environment (process time 260 s, pH 2.0), the number of oligomers under these conditions increased by 18% after 12 months of holding, and the surface hydrophobicity increased by as much as 31%. In addition, microbiological tests showed that the preparations of microwave-modified lysozyme had an effect on gram-positive bacteria as well as on gram-negative, and this effect was significantly enhanced after 12 months. The results confirm that LLC modification with microwave radiation is a highly efficient method to prepare high-quality and high utility potential lysozyme. Notably, an interesting and important phenomenon was the observation of the unconventional behaviour of the preparations during their long-term storage, which increased their utility potential significantly.

scholarly journals The Passive Microwave Neural Network Precipitation Retrieval Algorithm for Climate Applications (PNPR-CLIM): Design and Verification

2021 ◽  
Vol 13 (9) ◽  
pp. 1701
Author(s):  
Leonardo Bagaglini ◽  
Paolo Sanò ◽  
Daniele Casella ◽  
Elsa Cattani ◽  
Giulia Panegrossi
Keyword(s):  
Neural Network ◽  
Passive Microwave ◽  
Retrieval Algorithm ◽  
Climate Data ◽  
High Quality ◽  
Data Record ◽  
Global Precipitation ◽  
Climate Data Record

This paper describes the Passive microwave Neural network Precipitation Retrieval algorithm for climate applications (PNPR-CLIM), developed with funding from the Copernicus Climate Change Service (C3S), implemented by ECMWF on behalf of the European Union. The algorithm has been designed and developed to exploit the two cross-track scanning microwave radiometers, AMSU-B and MHS, towards the creation of a long-term (2000–2017) global precipitation climate data record (CDR) for the ECMWF Climate Data Store (CDS). The algorithm has been trained on an observational dataset built from one year of MHS and GPM-CO Dual-frequency Precipitation Radar (DPR) coincident observations. The dataset includes the Fundamental Climate Data Record (FCDR) of AMSU-B and MHS brightness temperatures, provided by the Fidelity and Uncertainty in Climate data records from Earth Observation (FIDUCEO) project, and the DPR-based surface precipitation rate estimates used as reference. The combined use of high quality, calibrated and harmonized long-term input data (provided by the FIDUCEO microwave brightness temperature Fundamental Climate Data Record) with the exploitation of the potential of neural networks (ability to learn and generalize) has made it possible to limit the use of ancillary model-derived environmental variables, thus reducing the model uncertainties’ influence on the PNPR-CLIM, which could compromise the accuracy of the estimates. The PNPR-CLIM estimated precipitation distribution is in good agreement with independent DPR-based estimates. A multiscale assessment of the algorithm’s performance is presented against high quality regional ground-based radar products and global precipitation datasets. The regional and global three-year (2015–2017) verification analysis shows that, despite the simplicity of the algorithm in terms of input variables and processing performance, the quality of PNPR-CLIM outperforms NASA GPROF in terms of rainfall detection, while in terms of rainfall quantification they are comparable. The global analysis evidences weaknesses at higher latitudes and in the winter at mid latitudes, mainly linked to the poorer quality of the precipitation retrieval in cold/dry conditions.

scholarly journals A method for simulating risk profiles of wheat yield in data-sparse conditions

2021 ◽  
pp. 1-12
Author(s):  
G. Bracho-Mujica ◽  
P.T. Hayman ◽  
V.O. Sadras ◽  
B. Ostendorf
Keyword(s):  
Reference Site ◽  
Climate Impacts ◽  
Weather Data ◽  
Climate Data ◽  
High Quality ◽  
Risk Profiles ◽  
Record Length ◽  
Daily Weather Data ◽  
Study Sites

Abstract Process-based crop models are a robust approach to assess climate impacts on crop productivity and long-term viability of cropping systems. However, these models require high-quality climate data that cannot always be met. To overcome this issue, the current research tested a simple method for scaling daily data and extrapolating long-term risk profiles of modelled crop yields. An extreme situation was tested, in which high-quality weather data was only available at one single location (reference site: Snowtown, South Australia, 33.78°S, 138.21°E), and limited weather data was available for 49 study sites within the Australian grain belt (spanning from 26.67 to 38.02°S of latitude, and 115.44 to 151.85°E of longitude). Daily weather data were perturbed with a delta factor calculated as the difference between averaged climate data from the reference site and the study sites. Risk profiles were built using a step-wise combination of adjustments from the most simple (adjusted series of precipitation only) to the most detailed (adjusted series of precipitation, temperatures and solar radiation), and a variable record length (from 10 to 100 years). The simplest adjustment and shortest record length produced bias of modelled yield grain risk profiles between −10 and 10% in 41% of the sites, which increased to 86% of the study sites with the most detailed adjustment and longest record (100 years). Results indicate that the quality of the extrapolation of risk profiles was more sensitive to the number of adjustments applied rather than the record length per se.

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