Predicting soil organic matter content using soil color at three locations with different land use in Zagreb (Croatia)

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Predicting soil organic matter content using soil color at three locations with different land use in Zagreb (Croatia)
Autor: Rubinic, Vedran ; Pavlovic, Alan ; Magdic, Ivan
Assuntos: Agricultural ecology ; Analysis ; Croatia ; humus ; Land use ; linear regression ; munsell color system ; pedotransfer function ; Soil acidity
É parte de: Journal of Central European agriculture, 2021-09, Vol.22 (3), p.646-656
Descrição: Soil organic matter (SOM) plays a key role in ecosystems. Reduction of its content due to land-use changes has a negative impact on the soil, but also on the wider environment. Accordingly, SOM content is routinely analyzed in the laboratory. As these are expensive and/or time-consuming, indirect ones are also tested. The aim of this study was to examine the possibility of predicting SOM content by linear regression using soil color as the predictor, at three locations in Zagreb (Croatia), with different soil types (eutric cambisol anthropogenic, humofluvisol, pseudogley) and different land uses (plough land, meadow, forest, respectively). At each location, 5 samples of the surface soil layer were taken. Soil color was determined using the Munsell system, and the hue was 2.5Y and 10YR in dry and moist soil, respectively. Laboratory analyzes showed that the soils are very acid to neutral silt loams. In line with the land-use, they differed significantly in SOM content and were poorly humic (plough land), moderately to highly humic (meadow), and highly humic (forest). Correlation between soil color dimensions and SOM content was significant only for the dry samples, between chroma and SOM and between value/chroma ratio and SOM. Regression analysis showed high coefficients of determination for these two relationships ([R.sup.2] = 0.88 for chroma-SOM, [R.sup.2] = 0.76 for value/chroma-SOM). The results suggest that visual soil color determination can be used to estimate SOM content, but only in dry soil. The model calibrated in this paper needs to be validated using samples of other (different) soils. Keywords: humus, Munsell color system, linear regression, pedotransfer function SAETAK Organska tvar tla (OTT) ima kljucnu ulogu u ekosustavima. Smanjenje njenog sadraja zbog promjena u nacinu koritenja zemljita negativno utjece na sama tla, ali i na iri okoli. U skladu s tim, sadraj OTT redovito se analizira u laboratoriju. Kako su te analize skupe ili dugotrajne, testiraju se i one neizravne. Cilj rada bio je ispitati mogucnost predvidanja sadraja OTT linearnom regresijom koristeci boju tla kao prediktor, i to na tri lokacije u Zagrebu (Hrvatska), gdje je na svakoj utvrden razliciti tip tla (eutricno smede antropogenizirano, humofluvisol, pseudoglej) i razliciti nacin koritenja (redom: oranica, livada, uma). Na svakoj lokaciji je uzeto po 5 uzoraka povrinskog sloja tla. Boja tla odredena je Munsellovim sustavom, pri cemu je komponenta hue iznosila 2,5Y u suhom i 10YR u mokrom tlu. U laboratoriju je utvrdeno da su tla vrlo kisele do neutralne prakaste ilovace. U skladu s nacinom koritenja zemljita, signifikantno su se razlikovala u sadraju OTT te su bila slabo humozna (oranica), dosta do jako humozna (livada) i jako humozna (uma). Korelacija izmedu komponenti boje tla i sadraja OTT je utvrdena samo za uzorke u suhom stanju, i to izmedu komponente chroma i OTT te izmedu omjera komponenti value/chroma i OTT. Regresijom su utvrdeni visoki koeficijenti determinacje za navedena dva odnosa ([R.sup.2]=0,88 za chroma-OTT, [R.sup.2]=0,76 za value/chroma-OTT). Dobiveni rezultati sugeriraju da se vizualna metoda odred!vanja boje tla moe koristiti za procjenu sadraja OTT, ali iskljucivo u suhom tlu. Model kalibriran u ovom radu potrebno je validirati na uzorcima drugih (razlicitih) tala. Kljucne rijeci: humus, Munsell sustav boja, linearna regresija, pedotransfer funkcija DETAILED ABSTRACT IN ENGLISH Soil organic matter (SOM) plays a key role in ecosystems, especially in agroecosystems. Sensu stricto, SOM comprises the transformed (humified) organic residues which are often labeled as humus. Reduction of its content due to land-use changes has a negative impact on the soil, but also on the wider environment. Accordingly, SOM content is routinely analyzed in the laboratory. As these analyzes are expensive and/or time-consuming, indirect ones are also being tested. Some of the indirect methods include modelling of the SOM content based on the data for other (correlated and easily available) soil properties, such as soil color. Soil color is routinely determined during most soil surveys, requiring not much effort and resources. The aim of this study was to examine the possibility of predicting SOM content by linear regression using soil color as the predictor, at three locations in Zagreb (Croatia), with different soil types (eutric cambisol anthropogenic, humofluvisol, pseudogley) and different land uses (plough land, meadow, forest, respectively). All soils are found on flat terrain, at around 130 m above sea level. The climate of the studied area is humid, moderate continental. At each location, 5 samples of the surface soil layer were taken. Soil color was visually determined using the three dimensions of the Munsell system: hue, value, and chroma. Hue was 2,5Y and 10YR in dry and moist soil, respectively (with the moist soil samples having lower values). Chroma varied across the samples. The color was analyzed in soil peds under standardized conditions (light, moisture). Laboratory analyzes (soil pH, soil particle size distribution by pipette-method, SOM content by wet digestion after the Tjurin method) showed that the soils are very acid to neutral silt loams. In line with the land-use, they significantly differed in SOM content and were poorly humic (plough land), moderately to highly humic (meadow), and highly humic (forest). Statistical analyzes were performed using MS Excel and Minitab 19, and involved ANOVA, Kruskal-Wallis test, Pearson correlation, and linear regression procedures. The correlation between soil color dimensions and SOM content was significant only for the dry soil samples, between chroma and SOM and between value/chroma ratio and SOM. Regression analysis showed high coefficients of determination for these two relationships ([R.sup.2] = 0,88 for chroma-SOM, [R.sup.2] = 0,76 for value/chroma-SOM), with the following prediction errors: RMSE=1,08% and MAE=0,83% (chroma-SOM); RMSE=1,34% and MAE=1,10% (value/chroma-SOM). The obtained results suggest visual soil color determination can be used to estimate SOM content, but only in dry soils. However, the model calibrated in this paper needs to be validated on samples from other (different) soils. Moreover, further research should be conducted using a large number of samples, collected from soils across Croatia and the wider region.
Editor: Sveuciliste U Zagrebu
Idioma: Inglês;Búlgaro

Predicting soil organic matter content using soil color at three locations with different land use in Zagreb (Croatia)

Rubinic, Vedran ; Pavlovic, Alan ; Magdic, Ivan

Sveuciliste U Zagrebu

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