Monitoring of the phytosanitary status of field crops in technological research

2017 ◽  
Vol 1 (92) ◽  
pp. 93-99 ◽  
Author(s):  
M.S. Korneychuk

The articles brought dotsіlnіst monitoring procedure fіtosanіtarnogo become polovih crops tehnologіchnih doslіdah. Place your viyavlennya i Metodi oblіku shkіdnikіv i hvorob. Venue of systematically monіtoringu rozvitku shkіdlivih ob’єktіv dozvolyaє otsіniti zahisnu role priyomіv included in the scheme doslіdu and for perevischennya ekonomіchnogo threshold shkodochinnostі background zastosuvati bіologіchnі chi hіmіchnі zasobi i zberegti doslіd.

2019 ◽  
Vol 13 (1) ◽  
pp. 27-36
Author(s):  
Andreas Neubert

Due to the different characteristics of the piece goods (e.g. size and weight), they are transported in general cargo warehouses by manually-operated industrial trucks such as forklifts and pallet trucks. Since manual activities are susceptible to possible human error, errors occur in logistical processes in general cargo warehouses. This leads to incorrect loading, stacking and damage to storage equipment and general cargo. It would be possible to reduce costs arising from errors in logistical processes if these errors could be remedied in advance. This paper presents a monitoring procedure for logistical processes in manually-operated general cargo warehouses. This is where predictive analysis is applied. Seven steps are introduced with a view to integrating predictive analysis into the IT infrastructure of general cargo warehouses. These steps are described in detail. The CRISP4BigData model, the SVM data mining algorithm, the data mining tool R, the programming language C++ for the scoring in general cargo warehouses represent the results of this paper. After having created the system and installed it in general cargo warehouses, initial results obtained with this method over a certain time span will be compared with results obtained without this method through manual recording over the same period.


2015 ◽  
Vol 39 (1) ◽  
pp. 153-154
Author(s):  
Mirosław Meissner

Abstract Elżbieta M. Walerian, Ph.D., D.Sc., a retired employee of the Institute of Fundamental Technological Research of the Polish Academy of Sciences (IPPT PAN), passed away after a serious illness, on the 26th December 2013. She was one of the scientific leaders in the Section of Environmental Acoustics of IPPT PAN and her career, educational and organizational activities were inseparably linked with the acoustics. Elżbieta Walerian was born on August 9th 1950 in Poznań. She graduated from the Faculty of Mathematics, Physics and Chemistry of the Adam Mickiewicz University in Poznań, receiving her Master of Science degree in the environmental acoustics in 1973. Five years later, under the supervision of Professor Ignacy Malecki, she obtained her PhD title, in the physical acoustics, in IPPT PAN in Warsaw. In 1979 she began working at the Section of Environmental Acoustics of IPPT PAN, where she dealt with the diffraction of acoustic waves and a description of the sound field produced by vehicles moving in an urban area.


2018 ◽  
Vol 1 (94) ◽  
pp. 38-44
Author(s):  
А.M. Malienkо ◽  
N.E. Borуs ◽  
N.G. Buslaeva

In the article, the results of research on the methodology for conducting studies with corn culture under various methods of sowing and weather conditions. The aim of the research was to establish and evaluate the reliability and high accuracy of the experiment, with a decrease in the area's acreage and taking one plant per repetition. Based on the results of the analysis of biometric parameters and yields, the possibility of sampling from 5 to 108 plants was established statistically and mathematically to establish the accuracy of the experiment. The established parameters of sites in experiments with maize indicate the possibility of obtaining much more information from a smaller unit of area, that is, to increase labor productivity not only with tilled crops. This is the goal of further scientific research with other field crops taking 1 plant of repetitions, observing the conditions of leveling the experimental plot according to the fertility of the soil and sowing seeds with high condition. The data obtained give grounds for continuing research on the minimum space required and the sample in the experiments.


The results of long-term research on the influence of main indicators on their agro-resource potential are summarized on gray forest soils of the upper Volga region. For the conditions of the Vladimir Opolie, the probable yield of biomass and the main products of field crops were calculated at different coefficients ofphotosynthetic active radiation (FAR) use. Calculations of the main product yields are made taking into account the distribution of biomass to by-products and crop-root residues. For field crops of the studied crop rotations, the coefficients of precipitation utilization are estimated. They varied from 44 to 71%, depending on the crop rotation culture. On the slope of the southern exposure when cultivating winter cereals and perennial grasses, the main moisture losses were observed in the spring during snowmelt, when growing spring crops and potatoes, they were close in the autumn and spring periods. The sizes of moisture use by crops depending on the fertilizer systems for the creation of 1 C of grain units (g.u.) and from sub-arable layers are determined. In comparison with the liming background, the use of organic fertilizers reduced the water consumption coefficient from 9.6 to 8.5 mm/C g.u., their combination with a single dose of NPK - up to 7.3, and with a double dose - up to 6.8 mm / C g.u. Based on the amount of moisture used by crops, their possible yields are calculated. In spring crops, the amount of precipitation consumed (326-356 mm) corresponds to the use of 2.7-3% of the FAR and provides 54-60 C/ha of grain, in winter rye and wheat - about 4% of the FAR (yield 71-80 C/ha). In perennial grasses for 2 mowing, the moisture consumed is enough to use about 3% of the FAR., in potatoes -1.5%.


2020 ◽  
Author(s):  
T. K. Kvasha ◽  
◽  
O. F. Paladchenko ◽  
I. V. Molchanova ◽  
◽  
...  

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