Spectral assessment of soil properties in semi-arid tropical regions of southern Karnataka Plateau

References

• Asgari N, Ayoubi S, Demattêal JAM, Dotto AC. 2020b. Carbonates and organic matter in soils characterized by reflected energy from 350–25000 nm wavelength. J Mt Sci. 17(7):1636–1651. doi:10.1007/s11629-019-5789-9.
   Web of Science ®Google Scholar
• Asgari N, Ayoubi S, Jafari A, Demattêal JAM. 2020a. Incorporating environmental variables, remote and proximal sensing data for digital soil mapping of USDA soil great groups. Int J Remote Sens. 41(19):7624–7648. doi:10.1080/01431161.2020.1763506.
   Web of Science ®Google Scholar
• Bartholomeus H, Schaepman-Strub G, Blok D, Sofronov R, Udaltsov S. 2012. Spectral estimation of soil properties in siberian tundra soils and relations with plant species composition. Appl Environ Soil Sci. 241535:1–13. doi:10.1155/2012/241535
   Google Scholar
• Bellon-Maurel V, McBratney A. 2011. Near-infrared (NIR) and mid-infrared (MIR) spectroscopic techniques for assessing the amount of carbon stock in soils – critical review and research perspectives. Soil Biol Biochem. 43(7):1398–1410. doi:10.1016/j.soilbio.2011.02.019.
   Web of Science ®Google Scholar
• Ben-Dor E, Irons JR, Epema GF. 1999. Soil reflectance. In: Rencz A, Ryerson R, editors. Remote sensing for the earth sciences, Manual of remote sensing. 3rd ed. New York, NY: John Wiley & Sons.
   Google Scholar
• Ben-Dor E, Patkin K, Banin A, Karnieli A. 2002. Mapping of several soil properties using DAIS-7915 hyperspectral scanner data - a case study over clayey soils in Israel. International Journal of Remote Sensing. 23(6):1043–1062. doi:10.1080/01431160010006962.
   Web of Science ®Google Scholar
• Bishop JL, Pieters CM, Edwards JO. 1994. Infrared spectroscopic analyses on the nature of water in montmorillonite. Clays Clay Miner. 42(6):702–716. doi:10.1346/CCMN.1994.0420606.
   Web of Science ®Google Scholar
• Bouma J, Stoorvogel JJ, Sonneveld MPW. 2012. Land evaluation for landscape units. In: Huang PM, Li Y, Sumner ME, editors. Handbook of soil sciences: properties and processes. 2nd ed. CRC Press/Taylor Francis; 34(1–20).
   Google Scholar
• Breiman L. 2001. Random forests. Machine Learning. 45(1):5–32. doi:10.1023/A:1010933404324.
   Web of Science ®Google Scholar
• Brown DJ, Shepherd KD, Walsh MG, Mays MD, Reinsch TG. 2006. Global soil characterization with VNIR diffuse reflectance spectroscopy. Geoderma. 132(3–4):273–290. doi:10.1016/j.geoderma.2005.04.025.
   Web of Science ®Google Scholar
• Brys G, Hubert M, Struyf A. 2004. A robust measure of skewness. J Comput Graph Stat. 13(4):996–1017. doi:10.1198/106186004X12632.
   Web of Science ®Google Scholar
• Cécillon L, Barthès BG, Gomez C, Ertlen D, Génot V, Hedde M, Stevens A, Brun JJ. 2009. Assessment and monitoring of soil quality using near‐infrared reflectance spectroscopy (NIRS). Eur J Soil Sci. 605:770–784. doi:10.1111/j.1365-2389.2009.01178.x
   Google Scholar
• Chodak M, Niklińska M, Beese F. 2007. Near-infrared spectroscopy for analysis of chemical and microbiological properties of forest soil organic horizons in a heavy-metal-polluted area. Biol Fertil Soils. 44(1):171–180. doi:10.1007/s00374-007-0192-z.
   Web of Science ®Google Scholar
• Clark RN, King TVV, Klejwa M, Swayze GA, Vergo N. 1990. High spectral resolution reflectance spectroscopy of minerals. J Geophys Res Solid Earth. 95(B8):12653–12680. doi:10.1029/JB095iB08p12653.
   Web of Science ®Google Scholar
• Cozzolino D, Moron A. 2003. The potential of near-infrared reflectance spectroscopy to analyse soil chemical and physical characteristics. J Agric Sci Technol. 140(1):65–71. doi:10.1017/S0021859602002836.
   Google Scholar
• Das BS, Sarathjith MC, Santra P, Sahoo RN, Srivastava R, Routray A, Ray SS. 2015. Hyperspectral remote sensing: opportunities, status and challenges for rapid soil assessment in India. Curr Sci. 860–868. doi:10.18520/CS/V108/I5/860-868
   Web of Science ®Google Scholar
• Demattê JAM, da Silva Terra F. 2014. Spectral pedology: a new perspective on evaluation of soils along pedogenetic alterations. Geoderma. 217:190–200. doi:10.1016/j.geoderma.2013.11.012
   Web of Science ®Google Scholar
• Dharumarajan S, Lalitha M, Gomez C, Vasundhara R, Kalaiselvi B, Rajendra Hegde. 2022. Prediction of soil hydraulic properties using VIS-NIR spectral data in semi- arid region of Northern Karnataka Plateau. Geoderma Reg. 28: e00475. https://doi.org/10.1016/j.geodrs.2021.e00475.
   Web of Science ®Google Scholar
• Dominati E, Patterson M, Mackay A. 2010. A framework for classifying and quantifying the natural capital and ecosystem services of soils. Ecol Econ. 69(9):1858–1868. doi:10.1016/j.ecolecon.2010.05.002.
   Web of Science ®Google Scholar
• Dwivedi RS, Singh AN, Raju KK. 1981. Spectral reflectance of some typical Indian soils as affected by tillage and cover types. J Indian Soc Remote Sens. 9(2):33–40. doi:10.1007/BF02991462.
   Google Scholar
• Gomez C, Coulouma G. 2018. Importance of the spatial extent for using soil properties estimated by laboratory VNIR/SWIR spectroscopy: examples of the clay and calcium carbonate content. Geoderma. 330:244–253. doi:10.1016/j.geoderma.2018.06.006
   Web of Science ®Google Scholar
• Gomez C, Lagacherie P, Coulouma G. 2008. Continuum removal versus PLSR method for clay and calcium carbonate content estimation from laboratory and airborne hyperspectral measurements. Geoderma. 148(2):141–148. doi:10.1016/j.geoderma.2008.09.016.
   Web of Science ®Google Scholar
• Gulfo E, Sahoo RN, Sharma RK, Khanna M. 2012. Soil moisture assessment using hyperspectral remote sensing. Proceedings of the Second National Workshop on Challenges and Opportunities of Water Resources Management; November 2012; Tana Basin, Upper Blue Nile Basin, Ethiopia. Blue Nile Water Institute: Bahir Dar University.
   Google Scholar
• Hegde R, Niranjana KV, Srinivas S, Danorkar BA, Singh SK. 2018. Site-specific land resource inventory for scientific planning of Sujala watersheds in Karnataka. Curr Sci. 115(4):645–652. doi:10.18520/cs/v115/i4/644-652.
   Web of Science ®Google Scholar
• Hewitt A, Dominati E, Webb T, Cuthill T. 2015. Geoderma Soil natural capital quantification by the stock adequacy method. Geoderma. 241–242:107–114. doi:10.1016/j.geoderma.2014.11.014
   Web of Science ®Google Scholar
• Hinkle DE, Wiersma W, Jurs SG. 2003. Applied statistics for the behavioral sciences. Boston; London: Houghton Mifflin; p. 1–663.
   Google Scholar
• Islam K, Singh B, McBratney A. 2003. Simultaneous estimation of several soil properties by ultra-violet, visible, and near-infrared reflectance spectroscopy. Soil Res. 41:1101–1114. doi:10.1071/SR02137
   Web of Science ®Google Scholar
• Jackson ML, Miller RH, Forkiln RE. 1973. Soil chemical analysis. New Delhi: Prentic-Hall of India Pvt. Ltd.
   Google Scholar
• Kadupitiya HK, Sahoo RN, Ray SS, Chakraborty D, Ahmed N. 2010. Quantitative assessment of soil chemical properties using visible (VIS) and near-infrared (NIR) proximal hyperspectral data. Trop Agric. 158:41–60.
   Google Scholar
• Kuhn M, Johnson K. 2013. Applied predictive modeling. New York; NY: Springer; p. 1–600. doi:10.1007/978-1-4614-6849-3
   Google Scholar
• Lagacherie P, Baret F, Feret J-B, Netto JM, Robbez-Masson JM. 2008. Estimation of soil clay and calcium carbonate using laboratory, field and airborne hyperspectral measurements. Remote Sens Environ. 112(3):825–835. doi:10.1016/j.rse.2007.06.014.
   Web of Science ®Google Scholar
• Lalitha M, Dharumarajan S, Kumar KS, Parvathy S, Koyal A, Kalaiselvi B, Hegde R, Singh SK. 2019. Evaluation of soil moisture retention characteristics using pedo-transfer functions for soils of dry semi-arid region. J Soil Water Conserv India. 47(2):163–171.
   Google Scholar
• Lalitha M, Hegde R, Dharumarajan S, Koyal A. 2021b. Soil fertility evaluation in rainfed regions of different agro-climatic zones of Karnataka, India. Agric Res. 11:215–218. doi:10.1007/s40003-021-00561-z
   Web of Science ®Google Scholar
• Lalitha M, Kumar P. 2016. Soil carbon fractions influenced by temperature sensitivity and land use management. Agrofor Syst. 90(6):961–964. doi:10.1007/s10457-015-9876-9.
   Web of Science ®Google Scholar
• Lalitha M, Kumar KSA, Nair KM, Dharumarajan S, Koyal A, Khandal S, Kaliraj S, Hegde R. 2021a. Evaluating pedogenesis and soil Atterberg limits for inducing landslides in the Western Ghats, Idukki District of Kerala, South India. Nat Hazards. 106(1):487–507. doi:10.1007/s11069-020-04472-0.
   Web of Science ®Google Scholar
• Marakkala Manage LP, Greve MH, Knadel M, Moldrup P, De Jonge LW, Katuwal S. 2018. Visible‐near‐infrared spectroscopy prediction of soil characteristics as affected by soil‐water content. Soil Sci Soc Am J. 82(6):1333–1346. doi:10.2136/sssaj2018.01.0052.
   Web of Science ®Google Scholar
• McBratney A, Field DJ, Koch A. 2014. The dimensions of soil security. Geoderma. 213:203–213. doi:10.1016/j.geoderma.2013.08.013
   Web of Science ®Google Scholar
• Meinshausen N. 2006. Quantile regression forests. J Mach Learn Res. 7:983–999.
   Web of Science ®Google Scholar
• Mondal B, Sekhon B, Sharma S, Singh M, Sahoo R, Barman A, Sinha Y, Chattopadhyay A, Banerjee K. 2017. VIS-NIR reflectance spectroscopy for assessment of soil microbiological properties. Int J Curr Microbiol Appl Sci. 6:719–728. doi:10.20546/ijcmas.2017.612.075
   Google Scholar
• Mouazen AM, De Baerdemaeker J, Ramon H. 2005. Towards development of on-line soil moisture content sensor using a fibre-type NIR spectrophotometer. Soil Tillage Res. 80(1–2):171–183. doi:10.1016/j.still.2004.03.022.
   Web of Science ®Google Scholar
• Mouazen AM, Maleki MR, De Baerdemaeker J, Ramon H. 2007. On-line measurement of some selected soil properties using a VIS-NIR sensor. Soil Tillage Res. 93(1):13–27. doi:10.1016/j.still.2006.03.009.
   Web of Science ®Google Scholar
• Naimi S, Ayoubia S, Di Raimo LADL, Dematte JAM. 2022. Quantification of some intrinsic soil properties using proximal sensing in arid lands: application of Vis-NIR, MIR, and pXRF spectroscopy. Geoderma Reg. 28:e00484. doi:10.1016/j.geodrs.2022.e00484.
   Web of Science ®Google Scholar
• Ng W, Minasny B, Malone BP, Sarathjith MC, Das BS. 2019. Optimizing wavelength selection by using informative vectors for parsimonious infrared spectra modelling. Comput Electron Agric. 158:201–210. doi:10.1016/j.compag.2019.02.003.
   Web of Science ®Google Scholar
• Pal DK 2021. Genesis and Usefulness of 0.7 nm Minerals (Kaolinite and Kaolin) in Indian Tropical Soils: Exploring Realm. Clay Res. 40(1):52–69. doi:10.5958/0974-4509.2021.00006.1.
   Google Scholar
• Pinheiro ÉFM, Ceddia MB, Clingensmith CM, Grunwald S, Vasques GM. 2017. Prediction of soil physical and chemical properties by visible and near-infrared diffuse reflectance spectroscopy in the central Amazon. Remote Sens. 9(4):293. doi:10.3390/rs9040293.
   Google Scholar
• Piper CS. 1966. Soil and plant analysis. Bombay; India: Hans Publishers.
   Google Scholar
• Pirie A, Singh B, Islam K. 2005. Ultra-violet, visible, near-infrared, and mid-infrared diffuse reflectance spectroscopic techniques to predict several soil properties. Soil Res. 43(6):713–721. doi:10.1071/SR04182.
   Web of Science ®Google Scholar
• Post JL, Noble PN. 1993. The near-infrared combination band frequencies of dioctahedral smectites, micas, and illites. Clays Clay Miner. 41(6):639–644. doi:10.1346/CCMN.1993.0410601.
   Web of Science ®Google Scholar
• Reeves IIIJB, Follett RF, McCarty GW, Kimble JM. 2006. Can near or mid‐infrared diffuse reflectance spectroscopy be used to determine soil carbon pools? Commun Soil Sci Plant Anal. 37(15–20):2307–2325. doi:10.1080/00103620600819461.
   Web of Science ®Google Scholar
• Richard LA. 1954. Diagnosis and improvement of saline and alkalis soils. Washington DC: Agric. Handbook 60, US Dept. Agric; p. 160.
   Google Scholar
• Richter N, Jarmer T, Chabrillat S, Oyonarte C, Hostert P, Kaufmann H. 2009. Free iron oxide determination in Mediterranean soils using diffuse reflectance spectroscopy. Soil Sci Soc Am J. 73(1):72–81. doi:10.2136/sssaj2008.0025.
   Web of Science ®Google Scholar
• Rodionov A, Welp G, Damerow L, Berg T, Amelung W, Pätzold S. 2015. Towards on-the-go field assessment of soil organic carbon using Vis–NIR diffuse reflectance spectroscopy: developing and testing a novel tractor-driven measuring chamber. Soil Tillage Res. 145:93–102. doi:10.1016/j.still.2014.08.007
   Web of Science ®Google Scholar
• Rossel RAV, Behrens T. 2010. Using data mining to model and interpret soil diffuse reflectance spectra. Geoderma. 158(1–2):46–54. doi:10.1016/j.geoderma.2009.12.025.
   Web of Science ®Google Scholar
• Rossel RAV, McGlynn RN, McBratney AB. 2006a. Determining the composition of mineral-organic mixes using UV–vis–NIR diffuse reflectance spectroscopy. Geoderma. 137(1–2):70–82. doi:10.1016/j.geoderma.2006.07.004.
   Web of Science ®Google Scholar
• Rossel RAV, Walvoort DJJ, McBratney AB, Janik LJ, Skjemstad JO. 2006b. Visible, near-infrared, mid infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soil properties. Geoderma. 131(1–2):59–75. doi:10.1016/j.geoderma.2005.03.007.
   Web of Science ®Google Scholar
• Santra P, Sahoo RN, Das BS, Samal RN, Pattanaik AK, Gupta VK. 2009. Estimation of soil hydraulic properties using proximal spectral reflectance in visible, near-infrared, and shortwave-infrared (VIS-NIR–SWIR) region. Geoderma. 152(3–4):338–349. doi:10.1016/j.geoderma.2009.07.001.
   Web of Science ®Google Scholar
• Sarathjith MC, Das BS, Vasava HB, Mohanty B, Sahadevan AS, Wani SP, Sahrawat KL. 2014. Diffuse reflectance spectroscopic approach for the characterization of soil aggregate size distribution. Soil Sci Soc Am J. 78(2):369–376. doi:10.2136/sssaj2013.08.0377.
   Web of Science ®Google Scholar
• Saxena RK, Verma KS, Srivastava R, Yadav J, Patel NK, Nasre RA, Barthwal AK, Shiwalkar AA, Londhe SL. 2003. Spectral reflectance properties of some dominant soils occurring on different altitudinal zones in Uttaranchal Himalayas. Agropedology. 13(2):35–43.
   Google Scholar
• Schollenberger CJ, Simon RH. 1945. Determination of exchange capacity and exchangeable bases in soil—ammonium acetate method. Soil Sci. 59(1):13–24. doi:10.1097/00010694-194501000-00004.
   Web of Science ®Google Scholar
• Shivaprasad CR, Reddy RS, Sehgal J, Velayutham M. 1998. Soils of Karnataka for optimizing land use. The report published by the National bureau of soil survey and land use planning. Nagpur; India: NBSS Publ. 47b (Soils of India Series); p. 1–111.
   Google Scholar
• Singh M, Srivastava R, Sethi M, Sood A. 2014. Development of spectral reflectance methods and low-cost sensors for real-time application of variable rate inputs in precision farming. Ludhiana; India: National Agricultural Innovation Project (ICAR); Punjab Agricultural University.
   Google Scholar
• Soil Survey Staff. 2010. Keys to Soil Taxonomy. 11th. Washington DC: USDA-NRCS.
   Google Scholar
• Solanke PC, Srivastava R, Prasad J, Nagaraju MSS, Patil NG, Nasre RA, Naitam RK, Wakode RR. 2021. Spectral reflectance properties of vertisols and associated soils of Nagpur District in Maharashtra. Journal of the Indian Society of Soil Science. 69(1):21–27. doi:10.5958/0974-0228.2021.00016.5.
   Google Scholar
• Srivastava R, Prasad J, Saxena R. 2004. Spectral reflectance properties of some shrink-swell soils of Central India as influenced by soil properties. Agropedology. 14:45–54.
   Google Scholar
• Srivastava R, Sethi M, Yadav RK, Bundela DS, Singh M, Chattaraj S, Singh SK, Nasre RA, Bishnoi SR, Dhale S. 2017. Visible-near infrared reflectance spectroscopy for rapid characterization of salt-affected soil in the Indo-Gangetic Plains of Haryana, India. J Indian Soc Remote Sens. 45(2):307–315. doi:10.1007/s12524-016-0587-0.
   Web of Science ®Google Scholar
• 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(1–2):15–22. doi:10.1016/j.geoderma.2010.04.008.
   Web of Science ®Google Scholar
• Stenberg B, Rosse RAV, Mouazen AM, Wetterlind J. 2010. Visible and near-infrared spectroscopy in soil science. Adv Agron. 107:163–215. doi:10.1016/S0065-2113(10)07005-7
   Web of Science ®Google Scholar
• Stevens A, Nocita M, Tóth G, Montanarella L, van Wesemael B. 2013. Prediction of soil organic carbon at the European scale by visible and near infrared reflectance spectroscopy. Plos One. 8(6):e66409. doi:10.1371/journal.pone.0066409.
   PubMed Web of Science ®Google Scholar
• Stevens A, van Wesemael B, Bartholomeus H, Rosillon D, Tychon B, Ben-Dor E. 2008. Laboratory, field and airborne spectroscopy for monitoring organic carbon content in agricultural soils. Geoderma. 144(1–2):395–404. doi:10.1016/j.geoderma.2007.12.009.
   Web of Science ®Google Scholar
• Tennesen BM. 2014. Rare earth. Science. 346(6210):692–695. doi:10.1126/science.346.6210.692.
   PubMed Web of Science ®Google Scholar
• Terra FS, Demattê JAM, Viscarra Rossel RA. 2015. Spectral libraries for quantitative analyses of tropical Brazilian soils: comparing vis–NIR and mid-IR reflectance data. Geoderma. 255-256:81–93. doi:10.1016/j.geoderma.2015.04.017
   Web of Science ®Google Scholar
• Udelhoven T, Emmerling C, Jarmer T. 2003. Quantitative analysis of soil chemical properties with diffuse reflectance spectrometry and partial least-square regression: a feasibility study. Plant Soil. 251(2):319–329. doi:10.1023/A:1023008322682.
   Web of Science ®Google Scholar
• Vasques GM, Grunwald S, Sickman JO. 2009. Modeling of soil organic carbon fractions using visible–near‐infrared spectroscopy. Soil Sci Soc Am J. 73(1):176–184. doi:10.2136/sssaj2008.0015.
   Web of Science ®Google Scholar
• Vibhute AD, Kale KV, Mehrotra SC, Dhumal RK, Nagne AD. 2018. Determination of soil physicochemical attributes in farming sites through visible, near-infrared diffuse reflectance spectroscopy and PLSR modeling. Ecol Process. 7(1):1–12. doi:10.1007/s11629-019-5789-9.
   Google Scholar
• Walkley A, Black IA. 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(1):29–38. doi:10.1097/00010694-193401000-00003.
   Google Scholar
• Zeraatpisheh M, Ayoubi S, Jafari A, Finke P. 2017. Comparing the efficiency of digital and conventional soil mapping to predict soil types in a semi-arid region in Iran. Geomorphology. 285:186–204. doi:10.1016/j.geomorph.2017.02.015
   Web of Science ®Google Scholar