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					       AN EVALUATION OF SELECTED SOIL
     PROPERTIES AND THEIR EFFECT ON THE
       BIOLOGICAL ACTIVITY OF SOILS IN
        ORGANIC FARMING IN THE CZECH
                  REPUBLIC
           Sarapatka, B.A, Pokorny, E.B, Hejatkova, K.C, Matlova, V. D, Krskova, M.E

Abstract - In our research we have evaluated a series of soil indicators to determine the correlation between
individual soil properties in organic farming. Regression analysis has proven that the biological activity of the soil
on organically farmed areas (grasslands) as expressed by respiration is mainly influenced by the bulk density,
moisture, porosity, humus content, the proportion of cation exchange capacity and total nitrogen content. The
multiple regressions have proven the important dependency of basal respiration to the moisture, bulk density and
total nitrogen. The supply of organic matter to the soil environment, thus greatly influences the studied soil
biological activity. Similar dependences were visible in the results of both conventional and organic farming on
arable land.


Introduction
Soil quality belongs among the topical environmental issues in the Czech Republic. According to Sarapatka,
Novak and Bednar (2006) the most serious degradation of soils in the Czech Republic is caused by water
erosion, but other types of degradation, e.g. loss of organic matter, are also significant. One of the approaches
attempting to deal with soil degradation is organic farming, currently practised on 263,299 ha of farmland in
the Czech Republic (6.16% of agricultural soil in the country). The majority of this area (89.4%) is covered by
grass stands (Collective, 2005). An appropriate evaluation of soil quality requires the selection of relevant
indicators. According to Doran and Parkin (1966) health indicators should correlate well with ecosystem
processes; integrate physical, chemical and biological soil properties and processes; be sensitive to
management practices; be relatively simple to use under field conditions and easy to assess by both specialists
and producers. Therefore, we have also focused on the operatational practicability of the indicators. We have
evaluated a series of soil indicators to determine the correlation between individual soil properties in organic
farming. In further research we plan to investigate other correlations with quantitative questions on the subject
of grass associations.

Materials and methods
The soil samples were collected from 18 farms (54 areas) during 2001-2004. The prevailing soil type was
cambisol. Landscape use reflected the land cover which was permanent grass stand, the quality of the
association was also followed. The basic physical (bulk density, porosity, water and air regime, texture) and
chemical (humus content and quality, Ntot, pH, CEC, basic elements, conductivity) features were studied
according to common pedological laboratory methods (Zbíral et al., 1995-1997). The results of basal respiration
were correlated with the results of physical and chemical analysis and probatory dependences were expressed
by approximate regress polynoms of bot the first and second degree of compatibility.


Results
We considered the biological activity of soil as measured by respiration, one of the basic features which is easily
measured and used as an indicator of soil quality (Harris et al. 1966). The use of microbiological and
enzymological methods for investigating soil quality is well known (e.g. Nannipieri et al. 1990, Dick, Breakwell
and Turco 1996, Sikora et al. 1995). The methods are in close relation to other soil features, but in contrast to
subsequent methods they could show changes sooner and, in keeping with subsequent bio-indicators, they
integrate the pedological, chemical and biological states of the soil.
          The respiration test yielded important results in all variants. It has correlated well (5% significance
level) with several physical and chemical soil features. The effect of the bulk density was conclusively proved.
Optimal bulk density values for basal respiration power are mass volumes around 1g.cm-3. Further increasing
the values leads to a decrease in respiration. It ceases at 1.8 cm-3 according to a regression curve. The
relationship between respiration power and bulk density has been published in more articles but its
quantification on a large scale of mass volumes has not been previously carried out until now. Basal respiration
is greatly influenced by soil porosity and pore distribution. With increasing porosity basal respiration increases.
The increase in basal respiration with growing at 30 min. moisture reflects the preparation of the sample in the
lab before analysis. In samples with prevailing capillary pores the preparation of the sample (loosening) causes
a substantial improvement in the respiratory conditions. The humus content, as an energy source for
respiration, markedly influences physical conditions (structure, bulk density). Within the permanent grass stand
studied we marked as 8% as optimal. The dependence is linear; positive where an increasing value of humus
content causes an increase in basal respiration, 90% of the values are lower than 8.15%. This
demonstrativeness was found between the values of cation exchange capacity and basal respiration. This
dependency is positive with maximum basal respiration values achieved at CEC 350 mmol.kg-1. A similar
positive dependency exists between the total nitrogen content of soil and basal respiration. Maximum basal
respiration values are achieved at a nitrogen content of 0.5%. So, high values are possible on grass stand
whereas on arable land they could only be sporadically achieved. In effect: the bigger Ntot content the higher
the basal respiration.




                                              2.5                                                                                                                                 2.5
 basal respiration (mg CO2.100g-1 per hour)




                                                                                                                                     basal respiration (mg CO2.100g-1 per hour)
                                                                                                                                                                                                                    y = 0.2068*x


                                              2.0                                                                                                                                 2.0




                                              1.5                                                                                                                                 1.5


                                                                                                   y = 2.8264*x - 1.5785*x2
                                              1.0                                                                                                                                 1.0




                                              0.5                                                                                                                                 0.5



                                              0.0                                                                                                                                 0.0



                                                     0.4   0.6   0.8     1.0           1.2          1.4          1.6           1.8                                                      0   2   4        6      8          10

                                                                         bulk density (g.cm-3)                                                                                                      humus (%)




                                              2.5
 basal respiration (mg CO2.100g-1 per hour)




                                              2.0



                                                                                                    y = 5.5271*x - 5.3239*x2
                                              1.5




                                              1.0




                                              0.5




                                              0.0
                                                    0.0    0.1     0.2         0.3           0.4           0.5           0.6

                                                                                 Ntot (%)




Conclusions
Regression analysis has proven that the biological activity of the soil on organically farmed areas as expressed
by respiration is mainly influenced by the bulk density, moisture, porosity, humus content, the proportion of
cation exchange capacity and total nitrogen content. The multiple regressions have proven the important
dependency of basal respiration to the moisture, bulk density and total nitrogen. The supply of organic matter
to the soil environment, thus greatly influences the studied soil biological activity. Similar dependences were
visible in the results of both conventional and organic farming on arable land. The next investigative step,
phytocenological recordings, will be acquired and then the received dependences will be examined in relation to
the quality of the association of grass stand using multivariate analysis. These results will be reviewed with data
received from other projects of the grass stands ecosystems study.



References
Collective (2005): Annual report of KEZ 2004. KEZ, o.p.s., 83 pp. + app.

Dick, R.P., Breakwell, D.P. and Turco, R.F. (1996). Soil enzyme activities and biodiversity measurements as
integrative microbiological indicators. In: Doran, J.W. et Jones, A.J. (eds.) Methods for assessing soil quality.
Soil Science Society of America, Inc., WI: 273 - 292.

Doran, J. W. and Parkin, T. B. (1996). Quantitative indicators of soil duality:A minimum data set.
In: Doran, J.W., Jones, A.J. (Eds.): Methoods for assessing soil quality. Soil Science Society of America, Inc.
Madison, Wisconsin: 25 – 38.

Harris, R.F. et al. (1996). A conceptual framework for assessment and management of soil quality and health.
SSSA Special Publication No 49, Madison, Wisc., SSSA: 61 – 82.

Nannipieri, P., Ceccanti, B.and Grego, S. (1990). Ecological significance of the biological activity in soil.
In: Bollag, J.M., Stotzky, G. (ed.) Soil biochemistry, vol. 6. Martin Dekker, New York: 293 – 366.
Sarapatka, B., Novak, P. and Bednar, M. (2006). Evaluation of soil degradation in condition within the Czech
Republic. Proceedings, World Congress of ISSS (in press).

Sikora, L.J., Yakovchenko, V. and Kaufmann, D.D. (1995). A proposed soil quality indicator.
In: Cook, H.F., Lee, H.C. (Eds.): Soil management in sustainable agriculture. Wye college Press: 312 – 318.

Zbiral, J. (Ed.) (1995 – 1997). Methods of soil analysis. Central institute for supervising and trstiny
in agriculture Brno. 3 parts. (in Czech).

First A. Author is from the Palacký University, Olomouc and Bioinstitut, tr. Svobody 26, 771 46 Olomouc, Czech Republic (borivoj.sarapatka@upol.cz)
Second B. Author is from the Mendel University of Agriculture and Forestry, Zemedelska 1, 613 00 Brno (pokorny@mendelu.cz)
Third C. Author is from the ZERA, Namest nad Oslavou, Czech Republic (hejatkova@cmcnamest.cz)
Fourth D. Author is from Research Institute of Animal Production, 104 01 Prague – Uhrineves, Czech Republic (matlova.vera@vuzv.cz)
Fifth E. Author is from the Palacky University, tr. Svobody 26, 771 46 Olomouc, Czech Republic (krskova@cvt.upol.cz)

				
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