There are many studies about soil organic carbon (SOC) around the world but, in extensive territories, it is more difficult to obtain data due to the number of variables involved in the models and their high cost. In large regions with poor infrastructure, low-cost SOC models are needed. With this in mind, our objective was to estimate the SOC using a simple model based on soil textural data. The work was focused on savanna soil and validated the model in the Brazilian Savanna. Two models were constructed, one for topsoil (0–0.3 m) and other for subsoil (0.3–1.0 m). The SOC models can be carried out in a textural triangle together with SOC values. The results showed that subsoil models were more accurate than topsoil models, but both had good performance. The models give support to SOC-related preliminary research in gross and fast estimates, requiring only reduced financial contribution to calculate SOC in a large region of interest.

1. Muscolo A, Panuccio MR, Mallamaci C, et al. Biological indicators to assess short-term soil quality changes in forest ecosystems. Ecological Indicators. 2014; 45: 416-423. doi: 10.1016/j.ecolind.2014.04.047

2. Chenu C, Angers DA, Barré P, et al. Increasing organic stocks in agricultural soils: Knowledge gaps and potential innovations. Soil and Tillage Research. 2019; 188: 41-52. doi: 10.1016/j.still.2018.04.011

3. Thoumazeau A, Bessou C, Renevier MS, et al. Biofunctool®: a new framework to assess the impact of land management on soil quality. Part A: concept and validation of the set of indicators. Ecological Indicators. 2019; 97: 100-110. doi: 10.1016/j.ecolind.2018.09.023

4. Gomes LC, Faria RM, de Souza E, et al. Modelling and mapping soil organic carbon stocks in Brazil. Geoderma. 2019; 340: 337-350. doi: 10.1016/j.geoderma.2019.01.007

5. Morais VA, Mello JM de, Mello CR de, et al. Spatial distribution of the litter carbon stock in the Cerrado biome in Minas Gerais state, Brazil. Ciência e Agrotecnologia. 2017; 41(5): 580-589. doi: 10.1590/1413-70542017415006917

6. Chen Z, Shuai Q, Shi Z, et al. National-scale mapping of soil organic carbon stock in France: New insights and lessons learned by direct and indirect approaches. Soil & Environmental Health. 2023; 1(4): 100049. doi: 10.1016/j.seh.2023.100049

7. McBratney AB, Santos MLM, Minasny B. On digital soil mapping. Geoderma. 2003; 117: 3-52. doi: 10.1016/S0016-7061(03)00223-4

8. Mutuku EA, Vanlauwe B, Roobroeck D, et al. Visual soil examination and evaluation in the sub-humid and semi-arid regions of Kenya. Soil and Tillage Research. 2021; 213: 105135. doi: 10.1016/j.still.2021.105135

9. Garsia A, Moinet A, Vazquez C, et al. The challenge of selecting an appropriate soil organic carbon simulation model: A comprehensive global review and validation assessment. Global Change Biology. 2023; 29(20): 5760-5774. doi: 10.1111/gcb.16896

10. MMA (Ministério do Meio Ambiente). Available online: http://www.mma.gov.br/biomas/cerrado (accessed on 3 January 2019).

11. Scaramuzza CA de M, Sano EE, Adami M, et al. Land-use and land-cover mapping of the Brazilian Cerrado based mainly on landsat-8 satellite images. Revista Brasileira de Cartografia. 2017; 69(6). doi: 10.14393/rbcv69n6-44309

12. Mello FFC, Cerri CEP, Davies CA, et al. Payback time for soil carbon and sugar-cane ethanol. Nature Climate Change. 2014; 4: 605-609. doi: 10.1016/j.geoderma.2009.05.015

13. Zhang J, Wang X, Wang J. Impact of land use change on profile distributions of soil organic carbon fractions in the Yanqi Basin. CATENA. 2014; 115: 79-84. doi: 10.1016/j.catena.2013.11.019

14. Cherubin MR, Franco ALC, Cerri CEP, et al. Sugarcane expansion in Brazilian tropical soils—Effects of land use change on soil chemical attributes. Agriculture, Ecosystems & Environment. 2015; 211: 173-184. doi: 10.1016/j.agee.2015.06.006

15. Bordonal R de O, Lal R, Ronquim CC, et al. Changes in quantity and quality of soil carbon due to the land-use conversion to sugarcane (Saccharum officinarum) plantation in southern Brazil. Agriculture, Ecosystems & Environment. 2017; 240: 54-65. doi: 10.1016/j.agee.2017.02.016

16. Deng L, Zhu G yu, Tang Z sheng, et al. Global patterns of the effects of land-use changes on soil carbon stocks. Global Ecology and Conservation. 2016; 5: 127-138. doi: 10.1016/j.gecco.2015.12.004

17. Zinn YL, Lal R, Resck DVS. Texture and organic carbon relations described by a profile pedotransfer function for Brazilian Cerrado soils. Geoderma. 2005; 127(1-2): 168-173. doi: 10.1016/j.geoderma.2005.02.010

18. Ruggiero PGC, Batalha MA, Pivello VR, Meirelles ST. Soil-vegetation relationships in Cerrado (Brazilian savanna) and semideciduous forest, Southeastern Brazil. Plant Ecology. 2002; 160: 1-16.

19. Neufeldt H, Resck DVS, Ayarza MA. Texture and land use effects on soil organic matter in Cerrado Oxisols, Central Brazil. Geoderma. 2002; 107: 151-164.

20. Reatto A, Correia JR, Spera ST, Martins ES. Soils of the Cerrado Biome: pedological aspects (Portuguese). In: Sano SM, Almeida SP, Ribeiro JF (editors). Cerrado ambiente e flora. Planaltina: Empresa Brasileira de Pesquisa Agropecuária. 2008. pp. 107-149.

21. Brasil. Ministry of the Environment. Mapping the Use and Cover of the Cerrado: TerraClass Cerrado Project 2013 (Portuguese). Brasília: MMA; 2015. 67p.

22. Alvares CA, Stape JL, Sentelhas PC, et al. Köppen’s climate classification map for Brazil. Meteorologische Zeitschrift. 2013; 22(6): 711-728. doi: 10.1127/0941-2948/2013/0507

23. Coutinho LM. Brazilian biomes (Portuguese). São Paulo: Oficina de Textos; 2016.

24. Haridasan M. Aluminium accumulation by some cerrado native species of central Brazil. Plant and Soil. 1982; 65(2): 265-273. doi: 10.1007/bf02374657

25. Embrapa. Brazilian Agricultural Research Corporation—National Soil Research Center (Portuguese). Sistema Brasileiro de Classificação de Solos. Embrapa, Brasília, 4ed. 2014.

26. Lopes AS. Cerrado soils: characteristics, properties and management (Portuguese). 1937—Piracicaba: Instituto da Potassa & Fosfato: Instituto Internacional da Potassa; 1983. 162p.

27. Parizzi TNT, Bento DF. Soil characteristics of savannah soils across Brasil. Published online 2017. doi: 10.1594/PANGAEA.881658

28. Bishop TFA, McBratney AB, Laslett GM. Modelling soil attribute depth functions with equal-area quadratic smoothing Splines. Geoderma, Amsterdam. 1999; 91: 27-45. doi: 10.1016/S0016-7061(99)00003-8

29. Malone BP, McBratney AB, Minasny B, Laslett GM. Mapping continuous depth functions of soil carbon storage and available water capacity. Geoderma. 2009; 154: 138-152. doi: 10.1038/s41597-023-02056-8

30. Pereira MWM. Modeling the continuous variation of organic carbon in soil depth (Portuguese). Dissertação (Mestrado em Engenharia Agrícola)—Faculdade de Engenharia Agrícola da Universidade Estadual de Campinas., Campinas; 2014.

31. Mtama JG, Burras CL, Msanya BM. Pedotransfer Functions for Cation Exchange Capacity, Available Water Holding Capacity and Soil Organic Carbon for Representative Soils of Southern Highland Zone of Tanzania. International Journal of Agriculture and Biological Sciences. 2018; 2522-6584.

32. Mwango SB, Wickama J, Msanya BM, et al. The use of pedo-transfer functions for estimating soil organic carbon contents in maize cropland ecosystem in the Coastal Plains of Tanzania. CATENA. 2019; 172: 163-169. doi: 10.1016/j.catena.2018.08.031

33. Efron B. The Jackknife, the Bootstrap and Other Resampling Plans. doi: 10.1137/1.9781611970319

34. Adami M. Estimating soybean planting dates using MODIS image time series (Portuguese). Tese (Doutorado em Sensoriamento Remoto), INPE, São José dos Campos; 2010. 163p.

35. Rossi M. Pedological map of the state of São Paulo: Revised and expanded (Portuguese). São Paulo: Instituto Florestal; 2017. 118p.

36. Davis ROE, Bennett HH. Grouping of soils on the basis of mechanical analysis. USDA Department Circular. 1927. 419.

37. Laub M, Blagodatsky S, Lang R, et al. A mixed model for landscape soil organic carbon prediction across continuous profile depth in the mountainous subtropics. Geoderma. 2018; 330: 177-192. doi: 10.1016/j.geoderma.2018.05.020

38. Vos C, Don A, Prietz R, et al. Field-based soil-texture estimates could replace laboratory analysis. Geoderma. 2016; 267: 215-219. doi: 10.1016/j.geoderma.2015.12.022

39. Morais VA, Ferreira GWD, de Mello JM, et al. Spatial distribution of soil carbon stocks in the Cerrado biome of Minas Gerais, Brazil. CATENA. 2020; 185: 104285. doi: 10.1016/j.catena.2019.104285

40. Padarian J, Minasny B, McBratney AB. Machine learning and soil sciences: a review aided by machine learning tools. SOIL. 2020; 6(1): 35-52. doi: 10.5194/soil-6-35-2020

41. Sakin E, Sakin ED. Relationships between particle size distribution and organic carbon of soil horizons in the Southeast area of Turkey. Bulgarian Chemical Communications. 2015; 47(2): 526-530.

42. Jobbágy EG, Jackson RB. The vertical distribution of soil organic carbon and its relation to climate and vegetation. Ecological Applications. 2000; 10(2): 423-436. doi: 10.1890/1051-0761

43. Hilinski TE. Century 5: Implementation of Exponential Depth Distribution of Organic Carbon in the CENTURY Model. Department of Soil and Crop Sciences, Colorado State University; 2001.

44. Lorenz K, Lal R. The depth distribution of soil organic carbon in relation to land use and management and the potential of carbon sequestration in subsoil horizons. Adv. Agron. 2005; 88: 35-66. doi: 10.1016/S0065-2113(05)88002-2

45. Hiederer R. Distribution of Organic Carbon in Soil Profile Data. EUR 23980 EN. Luxembourg: Office for Official Publications of the European Communities; 2009; p. 126.

46. Castro EA, Kauffman JB. Ecosystem structure in the Brazilian Cerrado a vegetation gradient of aboveground biomass, root mass and consumption by fire. Journal of Tropical Ecology. 1998; 14: 263-283. doi: 10.1017/S0266467498000212

47. Smith DM, Inman-Bamber NG, Thorburn PJ. Growth and function of the sugarcane root system. Field Crops Research. 2005; 92(2-3): 169-183. doi: 10.1016/j.fcr.2005.01.017

48. Meersmans J, van Wesemael B, De Ridder F, et al. Modelling the three-dimensional spatial distribution of soil organic carbon (SOC) at the regional scale (Flanders, Belgium). Geoderma. 2009; 152(1-2): 43-52. doi: 10.1016/j.geoderma.2009.05.015

49. Franzluebbers AJ. Soil organic matter stratification ratio as an indicator of soil quality. Soil & Tillage Research. 2002; 66: 95-106. doi: 10.1016/S0167-1987(02)00018-1

50. Shah AN, Tanveer M, Shahzad B, et al. Soil compaction effects on soil health and cropproductivity: an overview. Environmental Science and Pollution Research. 2017; 24(11): 10056-10067. doi: 10.1007/s11356-017-8421-y

51. Batjes NH, Ribeiro E, van Oostrum A. Standardised soil profile data to support global mapping and modelling (WoSIS snapshot 2019). Earth System Science Data. 2020; 12(1): 299-320. doi: 10.5194/essd-12-299-2020

52. Ruggiero PGC, Pivello VR, Sparovek G, et al. Relação entre solo, vegetação e topografia em área de cerrado (Parque Estadual de Vassununga, SP): como se expressa em mapeamentos? Acta Botanica Brasilica. 2006; 20(2): 383-394. doi: 10.1590/s0102-33062006000200013

53. Carvalho JLN, Cerri CEP, Cerri CC, et al. Changes of chemical properties in an oxisol after clearing of native Cerrado vegetation for agricultural use in Vilhena, Rondonia State, Brazil. Soil and Tillage Research. 2007; 96(1-2): 95-102. doi: 10.1016/j.still.2007.04.001