Potential crop production prediction by some simple calculation methods, as compared with computer simulations

1986 ◽  
Vol 19 (4) ◽  
pp. 249-272 ◽  
Author(s):  
M.N. Versteeg ◽  
H. van Keulen
Keyword(s):  
Computer Simulations ◽  
Crop Production ◽  
Simple Calculation ◽  
Calculation Methods ◽  
Production Prediction

scholarly journals Variant calculation system – the instrument of economic performance management of a multifunctional agricultural enterprise

2008 ◽  
Vol 54 (No. 8) ◽  
pp. 376-383
Author(s):  
E. Škorecová ◽  
M. Farkašová
Keyword(s):  
Performance Management ◽  
Crop Production ◽  
Financial Statements ◽  
Multifunctional Agriculture ◽  
Calculation Methods ◽  
Agricultural Enterprise ◽  
Time Period ◽  
The Difference ◽  
Calculation System ◽  
Gradual Transformation

The article is focused on the importance of using the variant calculation methods in the management of companies’ performance under the conditions of multifunctional agriculture. It mentions the difference between the calculations formed for the needs of valuating the production in the financial statements and the managerial calculations. Attention is paid to overhead costs in agriculture, their development is depicted with tables and graphs. The development of overhead costs during the time period of 1997–2006 is presented in crop production and outputs of wheat and rapeseed, in livestock production in Slovakia and in the outputs of cattle (6–24 months) and pigs (1–12 months). The fastidiousness of market environment of the globalized economies requires a gradual transformation from the classical calculation system into the managerial calculation system, which provides a multidimensional insight into the product as well as the market. The sequence of establishing the variant calculation methods is also introduced together with the reasons of under-valuating calculations in the managerial practice.

FIRE PERFORMANCE OF NON-LOADBEARING LIGHT STEEL FRAMING WALLS – NUMERICAL AND SIMPLE CALCULATION METHODS

2017 ◽  
Vol 3 (2) ◽  
pp. 13-23
Author(s):  
Paulo A. G. Piloto ◽  
◽  
Mohamed S. Khetata ◽  
Ana B. R. Gavilán ◽  
◽  
...  
Keyword(s):  
Simple Calculation ◽  
Fire Performance ◽  
Calculation Methods ◽  
Steel Framing

The fire effect on non-load bearing LSF walls – Numerical and simple calculation methods

2020 ◽  
Vol 5 (1) ◽  
pp. 10-16
Author(s):  
Larissa L. L. Ferreira ◽  
Paulo A. G. Piloto ◽  
Giovanni Bratti
Keyword(s):  
Simple Calculation ◽  
Calculation Methods ◽  
Load Bearing ◽  
Fire Effect

scholarly journals Method of pump, pipe, and tank selection for aeroponic nutrient management systems based on crop requirements

2020 ◽  
Vol 51 (2) ◽  
pp. 119-128
Author(s):  
Milon Chowdhury ◽  
Md. Shaha Nur Kabir ◽  
Hyeon-Tae Kim ◽  
Sun-Ok Chung
Keyword(s):  
Flow Rate ◽  
Management System ◽  
Crop Production ◽  
Nutrient Management ◽  
Management Systems ◽  
Coefficient Of Determination ◽  
Efficiency Coefficient ◽  
Calculation Methods ◽  
Irrigation Interval

The system-specific selection of aeroponic nutrient system components, specifically pumps, pipes, and tanks, is very important to improve system efficiency and minimize costs, as these components vary for different systems with different crop water requirements and design specifications. In this study, methods were suggested for determining the most suitable sizes of pumps, pipes, and tanks based on the plant water consumption and irrigation interval targeted to improve the usual procedures to design an aeroponic nutrient management system, and applied to a case. Factors affecting the size calculation are discussed, and calculation methods were suggested based on basic hydraulic principles. A recycle-type aeroponic nutrient management system, cultivating 500 plants in 21 plant beds, was considered for a case study. Application of the size calculation methods in the case study showed that an irrigation pump with a 37 Lmin–1 flow rate at 900 kPa capacity and nutrient pumps with a 5 Lmin–1 flow rate at 40 kPa capacity with 19-mmdiameter pipes were required to deliver the mixed nutrients and supply stock solutions into the mixing tank, along with nutrient mixing, stock nutrients, and distilled water tanks of 750, 40, and 685 L, respectively. Calculation was demonstrated to show the variations in the sizing of the pumps, pipes, and tanks by number of plants. Validation tests were performed for the selected irrigation pump capacity, and the results showed that the Nash-Sutcliffe efficiency coefficient (NSE), coefficient of determination (R2), and root-mean-square error (RMSE) values were 0.410, 0.98, 0.109 Lmin–1 and 0.775, 0.99, 34.91 kPa for flow rate and pressure, respectively. The case study also showed that these sizing procedures increased the plant bed coverage efficiency of the irrigation pump by 33%, while increasing the nutrient mixing tank size by 133%. This study would provide useful information on the efficient sizing of pumps, pipes, and tanks for minimizing costs and maximizing crop production in aeroponic nutrient management systems.

Using Simulated Data to Support the Calibration Process of ED-XRF Analysis

2015 ◽  
Vol 1120-1121 ◽  
pp. 1435-1440
Author(s):  
Dániel Koncz-Horváth ◽  
Zoltán Gácsi
Keyword(s):  
Simulated Data ◽  
Simple Calculation ◽  
Spectral Lines ◽  
Ratio Method ◽  
Calculation Methods ◽  
Standard Samples ◽  
Peak Intensity Ratio ◽  
Calibration Process ◽  
Cu Alloys ◽  
Peak Intensity

In the general practice of ED-XRF measurements, the values of elemental concentrations are derived from complicated calculation methods. Hereby a simple mathematical formula is suggested, which provides an easy way to prepare standard samples. On the other hand, the simulation of spectral lines may also be a helpful tool for the calibration process. In this study, measured and simulated data were used for the quantitative analysis of ternary Au-Ag-Cu alloys. To determine the calibration points, the peak intensity ratio method was applied and the calibration curves were fitted. This work presents the results of a twofold investigation aimed at: a) finding a suitable computational tool to optimise the parameters of the underlying equations and b) testing the reliability of the simulated data to determine the concentrations of multi-element standard samples. Based on comparisons of calculated concentrations it can be stated that a simple calculation method with simulated data provides an easy tool to define calibration standards. It is also demonstrated that the parameters of the linear plots can be optimised to yield improved results.

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