A Studying the Possibility of Estimating Soil Organic Carbon of Soils Under PINUS BRUTIA and QUERCUS AEGILOPS L. Trees in Sarke-Duhok By Using ASD FieldSpec 3 Spectroradiometer
DOI:
https://doi.org/10.25271/sjuoz.2020.8.1.651Keywords:
Vis-NIR spectroscopy, ASD fieldSpec, PINUS BRUTIA, QUERCUS AEGILOPS, SOC, forest soil, soil reflectivityAbstract
Visible and Near-infrared (VNIRS) spectroscopy is a very fast non-destructive and environmentally friendly analytical technique. It has been suggested as an alternative to conventional methods for assessing and monitoring soil quality. Accurate VNIRS prediction of soil organic carbon (SOC) has been reported by many researchers in different world regions. Sixteen surface soil samples (0-30cm depth) from Sarke - Duhok were collected, eight samples under Zawita Pine (Pinus brutia) and the other eight-under oak (Quercus aegilops L.) trees. Soil colour was measured in the field and soil samples were air-dried and sieved by using a 2.0 mm sieve and analyzed in the laboratory to estimate the PH, EC, CaCo3, texture, and SOC according to Walkley and Black methods. Laboratory reflectance spectra were acquired for each sample from 350 to 2500 nm by using the Analytical Spectral Device (ASD) FieldSpec 3spectroradiometer for each of the different spectrum bands (410, 570, 660, 849, 1543 and 2187nm). Results showed that the reflectivity values of soil under both Oak and Pine trees in the IR region (849, 1543, 2187nm) were almost more than that at the visible portion (410,570, 660nm). Also, the determination coefficient (R2) results indicated that the bands 570, 1543 and 2187nm showed significant relationships between soil reflectivity and SOC% under Oak trees, R2 was 58.2 %, 89.9%, and 93.9% respectively. While under the Pine tree, the only band that showed a significant relationship was band 1543nm, its R2 was 58.3%. From the current results, as the main objectives, it is obvious that the ASD FieldSpec 3 spectroradiometer is quite an efficient and un-destructive tool that can be used for SOC estimation under Oak & pine trees especially at the IR spectrum (band 1543nm). The relationship between the variables was moderately strong; R2 was 89.88 and 58.3 alternatively. The standard error was low (0.0399, 0.0185), which indicates that the predicted values are close to the real values. Besides that, under Oak trees results indicated that there was a high R2 between the variables at bands 570 & 2187 nm, the R2 values were 58.21 and 93.92, alternatively.
References
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Mitran T, Ravisankar T, Fyzee MA, Suresh JR, Sujatha G, Sreenivas K .2015. Retrieval of soil physicochemical properties towards assessing salt-affected soils using hyperspectral data. Geocarto Int 30(6):701–721.
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Pinheiro É.; Ceddia M.; Clingensmith C.; Grunwald S.; Vasques G. 2017.Prediction of soil physical and chemical properties by visible and near-infrared diffuse reflectance spectroscopy in the central amazon. Remote Sens. 9, 293. marcosceddia@gmail.com.
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Sabah H. A., Namik A. and Daood W. Y. 2012. Using of ASD Spectral reflectance and GIS techniques for mapping and analyzing of some salt soils distributed in the northern al-jazirah irrigation project. Remote Sensing Center,University of Mosul, Iraqi National Journal of Earth Sciences, Vol. 13, No. 1, pp. 35 - 44, 2013.
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Sarbast I. Abdi, 2017 Hydrologic characteristic of tow sub- catchments within the Duhok dam catchments. University of Duhok.
Šestak, I., Mesić, M., Zgorelec, Ž ihyu67j., Perčin, A., Stupnišek, I. 2018. Visible and near infrared reflectance spectroscopy for field-scale assessment of Stagnosols properties. Plant, Soil and Environment, 64 (6), 276–282.
Shepherd K.D., Vanlauwe B., Gachengo C.N., Palm C.A. 2005: Decomposition and mineralization of organic residues predicted using near infrared spectroscopy. Plant and Soil, 277: 315–333.
Sherestha BP, Devkota B.2013. Carbon stocks in the Oak and Pine forest in SalaysDistrict, Nepal. Banko Janakari.; 23(2):30-36.
Sherman, D.M., Waite, T.D., 1985. Electronic spectra of Fe3+ oxides and oxiyhydroxides in the near infrared to ultraviolet. American Mineralogist 70(11-12), 1262-1269.
Shi T, Cui L, Wang J, Fei T, Chen Y, Wu G 2013. Comparison of multivariate methods for estimating soil total nitrogen with visible/near-infrared spectroscopy. Plant Soil. 366: 363–375.
Stenberg, B. 2010. Effects of soil sample pretreatments and standardised rewetting as interacted with sand classes on Vis-NIR predictions of clay and soil organic carbon. Geoderma. 158, 15-22.
Sun, W. J., X. J. Li, and B. B. Niu. 2018. Prediction of soil organic carbon in a coal mining area by Vis-NIR spectroscopy. PLOS One 13(4):e0196198.
Vahil I. H. B., 2013. Soil Physico-Chemical Properties as Influenced by Slope Position Under Different Vegetation Covers in Dohuk Governorate. University of Duhok.
Velasquez E., Lavelle P., Barrios E., and Joffre R., Reversat F. 2005: Evaluating soil quality in tropical agroecosystems of Colombia using NIRS. Soil Biology and Biochemistry, 37: 889–898.
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Viscarra Rossel, R.A. and C. Chen. 2011. Digitally mapping the information contente of visible-near infrared spectra of surficial Australian soils. Rem. Sens. Environ. 115(6), 1443-1455.
Viscarra Rossel, R.A.; Walvoort, D.J.J.; McBratney, A.B.; Janik, L.J.; Skjemstad, J.O.2006. Visible, near infrared, mid infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soil properties. Geoderma, 131, 59–75.
Walkley, A.; Black, I.A. 1934. An examination of the degtjareff method for determining soil organic matter, and a proposed modification of the chromic acid titration method. Soil Sci. 37, 29–38.
Wetzel, D. L. 1983. Near-infrared reflectance analysis: Sleeper among spectroscopic techniques. Anal. Chemistry.55:1165-117
Bhadra, S. K., & Bhavanarayana, M. 1997. Estimation of the Influence of Soil Moisture on Soil Colour. Zeitschrift Für Pflanzenernährung Und Bodenkunde, 160(3), 401–405.
Bonett, J.P., Camacho-Tamayo, J.H., Vélez Sánchez, J.E., 2016. Estimating soil properties with mid-infrared spectroscopy. Rev. U.D.C.A Act. & Div. Cient 19 (1), 55–66.
Brunet D, Barthès BG, Chotte JL, Feller C 2007. Determination of carbon and nitrogen contents in Alfisols, Oxisols and Ultisols from Africa and Brazil using NIRS analysis: effects of sample grinding and set heterogeneity. Geoderma. 139: 106–117.
C.D. Christy, 2008. ‘‘Real-Time Measurement of Soil Attributes Using on-the-Go near Infra- red Reflectance Spectroscopy’’. Comput.Electron. Agric.. 61(1): 10-19.
Cécillon, L., B.G. Barthès, C. Gomez, D. Ertlen, V. Genot, M. Hedde, et al. 2009. Assessment and monitoring of soil quality using near-infrared reflectance spectroscopy (NIRS). Eur. J. Soil Sci. 60:770–784. doi:10.1111/j.1365-2389.2009.01178.
Chabrillat, S., Goetz, A.F.H., Krosley, L., Olsen, H.W., 2002. Use of hyper spectral images in the identification and mapping of expansive clay soils and the role of spatial resolution. Remote Sens. Environ. 82, 431–445.
Chang, C.-W., D.A. Laird, M.J. Mausbach, and C.R. Hurburgh, Jr. 2001. Nearinfrared refl ectance spectroscopy—Principal components regression analyses of soil properties. Soil Sci. Soc. Am. J. 65:480–490.
Chaturvedi, Shalini; Melkania, Uma. 2013. Soil Organic Carbon Stock in Mixed Oak and Mixed Pine Forest of Kumaon Himalaya. Indian Forester, [S.l.], p. 218-221.
Clark, R.N., 1999. Spectroscopy of Rocks and Minerals and Principles of Spectroscopy. In: Rencz, A.N. (Ed.), Remote Sensing for the Earth Sciences, Manual of Remote Rensing, vol. 3. John Wiley and Sons, New York, pp. 3–58.
Conforti, M., Matteucci, G., Buttafuoco, G. 2018 Using laboratory Vis-NIR spectroscopy for monitoring some forest soil properties. Journal of Soils and Sediments, 18 (3), 1009–1019.
Epema, G.F.; Kooistra, L.; Wanders, J. 2013: Spectroscopy for the assessment of soil properties in reconstructed river floodplains. In Proceedings of the 3rd EARSeL Workshop on Imaging Spectroscopy, Herrsching, Germany pp. 13–16.
FAO (2005): The Importance of Soil Organic Matter: Key to Drought-Resistant Soil and Sustained Food. Rome, Food and Agriculture Organization of the United Nations, 5–9.
Feyziyev F., Babayev M., Priori S., L’Abate G. (2016): Using visible-near infrared spectroscopy to predict soil properties of Mugan Plain, Azerbaijan. Open Journal of Soil Science, 6: 52–58.
Fystro G (2002). The prediction of C and N content and their potential mineralization in heterogeneous soil samples using Vis-NIR spectroscopy and comparative methods. Plant Soil. 246: 139–149.
GAO, L,2017, Spectroscopy Based Estimation of Soil Organic Matter in Brown-Forest Areas of the Shandong Peninsula, China,
Garcia-Pausas, J., P. Casals and J. Romanya, 2004. Litter decomposition and faunal activity in Mediterranean forest soils: Effects of N content and the moss layer. Soil Biol. Biochem., 36: 989-997.
Hajar A. A. and Salar M. A. 2016 .Assessment of soil quality indicators on different slope aspects in Duhok’s highlands (Kurdistan region – Iraq). Journal of Zankoy Sulaimani. JZS 18- 2 (Part-A)
He T, Wang J, Lin Z, Cheng Y. 2009. Spectral features of soil organic matter. Geo-Spatial Information Science 12(1):33–40.
Jia S.Y., Yang X.L., Zhang J.M., Li G. 2014: Quantitative analysis of soil nitrogen, organic carbon, available phosphorus, and available potassium using near-infrared spectroscopy combined with variable selection. Soil Science, 179: 211–219.
Kinoshita, R., B.N. Moebius-Clune, H.M. van Es, W.D. Hively, and A.V. Bilgilis. 2012. Strategies for soil quality assessment using visible and near-infrared reflectance spectroscopy in a Western Kenya chronosequence. Soil Sci. Soc. Am. J. 76:1776–1788. doi:10.2136/sssaj2011.0307.
Klein C., Dutrow B (2000) Manual of mineral science. John Wiley & Sons Inc, New York.
Luce M.St., Ziadi N., Zebarth B.J., Grant C.A., Tremblay G.F., Gregorich E.G. 2014: Rapid determination of soil organic matter quality indicators using visible near infrared reflectance spectroscopy. Geoderma, 232–234: 449–458.
McCoy R.M. (2005): Field Methods in Remote Sensing. New York, the Guilford Press.
Mikhaylova N.A., Orlov D.1986. Optical properties of soils and soil components / N.A. Mikhaylova, D.S. Orlov, Moskva: Nauka,. 118 p.
Milos, B., Bensa, A., 2017. Prediction of soil organic carbon using VIS-NIR spectroscopy: application to Red Mediterranean soils from Croatia. Eurasian J. Soil Sci. 6, 365–373.
Mitran T, Ravisankar T, Fyzee MA, Suresh JR, Sujatha G, Sreenivas K .2015. Retrieval of soil physicochemical properties towards assessing salt-affected soils using hyperspectral data. Geocarto Int 30(6):701–721.
Ogen Y, 2018, Evaluating the detection limit of organic matter using point and imaging spectroscopy, Geoderma,vol. 321, 1july 2018,p100-109.
Pinheiro É.; Ceddia M.; Clingensmith C.; Grunwald S.; Vasques G. 2017.Prediction of soil physical and chemical properties by visible and near-infrared diffuse reflectance spectroscopy in the central amazon. Remote Sens. 9, 293. marcosceddia@gmail.com.
Q. Fang, H. Hong, L. Zhao 2018, “Visible and near-infrared reflectance spectroscopy for investigating soil mineralogy: a review,” Journal of Spectroscopy, vol. 2018, Article ID 3168974, 14 pages.
Sabah H. A., Namik A. and Daood W. Y. 2012. Using of ASD Spectral reflectance and GIS techniques for mapping and analyzing of some salt soils distributed in the northern al-jazirah irrigation project. Remote Sensing Center,University of Mosul, Iraqi National Journal of Earth Sciences, Vol. 13, No. 1, pp. 35 - 44, 2013.
Santa Regina I., Tarazona T. (2001) Nutrient cycling in a natural beech forest and adjacent planted pine in northern Spain. Forestry 74:11–28.
Sarbast I. Abdi, 2017 Hydrologic characteristic of tow sub- catchments within the Duhok dam catchments. University of Duhok.
Šestak, I., Mesić, M., Zgorelec, Ž ihyu67j., Perčin, A., Stupnišek, I. 2018. Visible and near infrared reflectance spectroscopy for field-scale assessment of Stagnosols properties. Plant, Soil and Environment, 64 (6), 276–282.
Shepherd K.D., Vanlauwe B., Gachengo C.N., Palm C.A. 2005: Decomposition and mineralization of organic residues predicted using near infrared spectroscopy. Plant and Soil, 277: 315–333.
Sherestha BP, Devkota B.2013. Carbon stocks in the Oak and Pine forest in SalaysDistrict, Nepal. Banko Janakari.; 23(2):30-36.
Sherman, D.M., Waite, T.D., 1985. Electronic spectra of Fe3+ oxides and oxiyhydroxides in the near infrared to ultraviolet. American Mineralogist 70(11-12), 1262-1269.
Shi T, Cui L, Wang J, Fei T, Chen Y, Wu G 2013. Comparison of multivariate methods for estimating soil total nitrogen with visible/near-infrared spectroscopy. Plant Soil. 366: 363–375.
Stenberg, B. 2010. Effects of soil sample pretreatments and standardised rewetting as interacted with sand classes on Vis-NIR predictions of clay and soil organic carbon. Geoderma. 158, 15-22.
Sun, W. J., X. J. Li, and B. B. Niu. 2018. Prediction of soil organic carbon in a coal mining area by Vis-NIR spectroscopy. PLOS One 13(4):e0196198.
Vahil I. H. B., 2013. Soil Physico-Chemical Properties as Influenced by Slope Position Under Different Vegetation Covers in Dohuk Governorate. University of Duhok.
Velasquez E., Lavelle P., Barrios E., and Joffre R., Reversat F. 2005: Evaluating soil quality in tropical agroecosystems of Colombia using NIRS. Soil Biology and Biochemistry, 37: 889–898.
Viscarra Rossel, R. A., Walvoort, D. J. J., McBratney, A. B., Janik, L. J., and Skjemstad, J. O. 2006c. Visible, near infrared, mid infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soil properties. Geoderma 131, 59–75.
Viscarra Rossel, R.A. and C. Chen. 2011. Digitally mapping the information contente of visible-near infrared spectra of surficial Australian soils. Rem. Sens. Environ. 115(6), 1443-1455.
Viscarra Rossel, R.A.; Walvoort, D.J.J.; McBratney, A.B.; Janik, L.J.; Skjemstad, J.O.2006. Visible, near infrared, mid infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soil properties. Geoderma, 131, 59–75.
Walkley, A.; Black, I.A. 1934. An examination of the degtjareff method for determining soil organic matter, and a proposed modification of the chromic acid titration method. Soil Sci. 37, 29–38.
Wetzel, D. L. 1983. Near-infrared reflectance analysis: Sleeper among spectroscopic techniques. Anal. Chemistry.55:1165-117
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2020-03-30
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Gravi, K. A., & Ibrahim, S. M. (2020). A Studying the Possibility of Estimating Soil Organic Carbon of Soils Under PINUS BRUTIA and QUERCUS AEGILOPS L. Trees in Sarke-Duhok By Using ASD FieldSpec 3 Spectroradiometer. Science Journal of University of Zakho, 8(1), 34–41. https://doi.org/10.25271/sjuoz.2020.8.1.651
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