1. DETERMINATION OF UPTAKEN ELEMENT CONCENTRATIONS IN DIFFERENT PLANTS USING BY WEB BASED APPLICATION 1 László Várallyai, Béla Kovács, József Thuri

2. 2 Soil Monitoring in Hungary The Soil Information and Monitoring System (SIM) is an independent subsystem of the integrated Environmental Information and Monitoring System. The Soil Information Monitoring System (SIM) covers the whole country and provides opportunity to create similar information systems for the natural resources (atmosphere, supply of water, flora and biological resources etc.). The aim is to relate these databases. The SIM territorial measuring grid consists of 1236 measuring points. These points are representatives. Distribution of the points by soil types represents the variety of soil types of the country. 1.module in 1991-ben (SIM) Soil Information Monitoring System Soil Information Monitoring System National Environmental Protection Information and Monitoring System

3. 3 Mérőhálózat kialakítása: The SIM monitoring network consist of 3 type of sense : summary 1236 points forest (183 points) agricultural land (865 points) environmentally threatened "hot spot" regions (189 points) (degraded soils, ameliorated soils, "hot spots" of industrial, agricultural, urban and transport pollution, military fields, watersheds of important lakes and reservoirs etc.)

4. Simple method based on Pythgoras theorem 4

5. Calculating concentration If the distances are determined for all points, are chosen the 10 least. These distances are z 1, z 2, z 3, ……, z 10. From these distances and element concentrations of the ”Known measuring points” can be calculated the given element concentration c x by using linear evaluation. 5

6. Research objectives To extend soil information monitoring point samples taking into consideration topography (kriging). To develop knowledge transfer for decision-makers and consultants to determine the element content of different soils at certain points. To create a complex system in order to monitor microelements that are harmful mainly to human body. 6

7. Analysation of soil monitoring samples by Kriging method Kriging is an interpolation method that predicts unknown values of a random process. More precisely, a Kriging prediction is a weighted linear combination of all output values already observed. These weights depend on the distances between the input for which the output is to be predicted and the inputs already simulated. Kriging assumes that the closer the inputs are, the more positively correlated the outputs are. This assumption is modelled through the correlogram or the related variogram. 7

8. Comparison of calculated data The results obtained by Kriging method for 21 elements, where the concentration is above the detecting limit can be seen in case of three, five and ten closest neighbouring points. 3 neighbouring points: K, P, Sr 5 neighbouring points: --- 10 neighbouring points: Al, B, Ba, Ca, Co, Cr, Cu, Fe, Mg, Mn, Ni, Pb, S, Ti, V, Y, Zn, Na -------------------------------------------------------------------------------------------------------------- Spatial relationships are not calculated (only statistical method)! 3 neighbouring points: K, P, Sr, Ni, Cu, B, Co, Ti 5 neighbouring points: Al, Fe, Ca, Mg, Mn, S, Ba, Cr, V, Pb, Y, Zn 10 neighbouring points: Na 8

9. Knowledge transfer of the data by statistical and Kriging method Creating a registration system to access data, obtained by statistical and Kriging methods. 9

10. Using the system 10

11. 11 Monitoring microelements Applied informatics went through considerable development at the end of the XX th century. Thus it is possible now to analyse soil pollution by computer controlled systems. It is really important since now we can monitor how pollution can get from the soil through pesticides, wastes, Nitrogen and Phosphorous fertilizers to plants and from there directly or indirectly (through plants and animals) to our food. Polluted food can cause illnesses in our important organs. Considering the above mentioned pollution, experimental data can be quickly and exactly processed and we can have a considerable amount of new information.

12. Nagyhörcsök 12

13. 13 Experiment in Nagyhörcsök Experimental Station The trial was set up in Nagyhörcsök (Hungary) in 1991 on a calcareous chernozem soil formed on loess, containing: 5% CaCO 3, 3% humus, soil texture is loamy with 20% clay and 40% fine fraction. The soil is well supplied with Mn, sufficiently supplied with Mg and Cu, moderately supplied with N and K, and weakly supplied with P and Zn. The applied treatments simulate soil contamination conditions that may occur in industrial areas, near highways, settlements and in city gardens. The 4 load levels (0, 90, 270 and 810 kg element/ha) were applied as a single dose in the spring of 1991. Soils were sampled in 1993, 1996 and 2000 at the maximal depths of 60, 90 and 290 cm, respectively.

14. Conversion of the measured data by ICP-OES/MS The ICP-OES/MS instrument averages the measured data and calculates the deviation for each element. The measured data have to be converted, rounded and placed into a table on the basis of a certain aspect for further processing. This process takes a long time in spite of the fact that a fixed Excel macro was available at the department. Processing of the databases takes at least one hour depending on the number of measured elements and samples. 14

15. 15 Display of the programme We carried out the conversion, rounding and placing into table with Microsoft Visual C# 2010 developing system, since its objects and programming opportunities provided more possibilities than an Excel macro. We saved the figures received when running the program into an Excel worksheet in order to make further data processing easier.

16. Export to Excel worksheet The saved figures are exported into an Excel worksheet. These data are converted and rounded. The column headers are the sample_IDs, the row headers are the analytical lines. The ”<KH” symbol meaning is under the detection limit. 16

17. Storing data in the database The central table is the ”Meresi_Adat”, where we store the chemical symbols and the measured microelement concentrations of the plant and plant parts, the type of soil and the dose the soil was treated with. It is important to store the year of the sampling. The other three tables store the different plants, plant parts and the soil types. In case of soil measurement is important to know from which depth profile is the sample. The plants are as follows: carrot, maize, peas, winter wheat, potato etc. The plant parts are as follows: root, stem, leaf, bloom, seed. 17

18. Upload data from Excel file to the database 18

19. Web-based application One of the main functions of the web application is quering measurement results. In this case we have an opportunity to configure through a wizard that what information would like to get from the database. 19

20. Sample data in the Figure 20

21. Review saved queries page 21

22. First test analyses We can create special queries to give the ”Soil”, the ”Plant” and the ”Plant_part”, the ”Sample_year” and ”Soil dose” parameters. Using these parameters we can get the give element concentration value and exported to Excel or SPSS to analyze the data by statistical method. The first step is to test this new programme. Two examples can be seen for the molybdenum concentration changes in the leaf and seed of maize. The molybdenum treatment was (90, 270, 810 kg/hectare). 22 Leaf Seed