DIGITALNA ARHIVA ŠUMARSKOG LISTA
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M. Kobal, M. Urbančič, N. Potočić, B. De Vos, P. Simončič: PEDOTRANSFER FUNCTIONS FOR BULK DENSITY... Šumarski list br. 1–2, CXXXV (2011), 19-27 23 Figure4 Segmented regression relations- hip between soil bulk density (. b ) and organic carbon content (OC) in the mineral soil [g/kg] Slika4. Segmentirana regresija odnosa gustoće tla (. b ) i sadržaj organ- skog ugljika (OC) u mineralnom sloju tla [g/kg] SFI 4 and SFI 5 inTable 2) did not significantly im- prove the prediction of SFI 1 (partial F-test, p > 0.05). Unexpectedly, soil texture, especially clay content, was not statistically significant variable in the models; contrary tomany studies revealing that clay content is related with soil bulk density (Kaur, 2002; Leo na- vičiute,2000). The segmented regression method (SFI 6) improved prediction of .b (partial F-test, p < 0.001). The inde - pendent variable OC was partitioned into two intervals and a separate line segment was fitted to each interval. The boundary between two segments (breakpoint) was 36.0 g/kg OC (Figure 4).Nearly 80 % of the total va riabi- lity in.b was explained by using segmented regression. Figure 5 Evaluation indices for published PTFs and local PTF (SFI 6) Slika 5. Indeksi evaluacije za objavljene i lokalni PTF (SFI 6) 3.2 Validation of local and published PTFs for mineral part of soil Validacija lokalnih i objavljenih pedotransfer funkcija za mineralni sloj tla For the validation of local and published PTFs,bulk density was calculated using four published PTFs and predicted values were compared with local PTF (SFI 6).The prediction quality of all five PTFs is presented in Figure 5.All four validation indices confirmed the highest prediction powerof our local PTF (Figure 5)by |