A simple digital imaging method for estimating black-soil organic matter under visible spectrum

References

• Al-Abbas AH, Swain PH, Baumgardner MF. 1972. Relating organic matter and clay content to the multispectral radiance of soils. Soil Sci. 114:477–485.
   Web of Science ®Google Scholar
• Bandyopadhyay S, Peralta-Videa JR, Hernandez-Viezcas JA, Montes MO, Keller AA, Gardea-Torresdey JL. 2012. Microscopic and spectroscopic methods applied to the measurements of nanoparticles in the environment. Appl Spectrosc Rev. 47:180–206.
   Web of Science ®Google Scholar
• Ben-Dor E. 2002. Quantitative remote sensing of soil properties. Adv Agron. 75:173–243.
   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. 132:273–290.
   Web of Science ®Google Scholar
• Cheng XF, Shi XZ, Yu DS, Pan XZ, Wang HJ, Sun WX. 2004. Using GIS spatial distribution to predict soil organic carbon in subtropical China. Pedosphere. 14:425–431.
   Web of Science ®Google Scholar
• Conforti M, Buttafuoco G, Leone AP, Aucelli PPC, Robustelli G, Scarciglia F. 2013. Studying the relationship between water-induced soil erosion and soil organic matter using Vis–NIR spectroscopy and geomorphological analysis: a case study in a southern Italy area. Catena. 110:44–58.
   Web of Science ®Google Scholar
• Coulson KL, Reynolds DW. 1971. The spectral reflectance of natural surfaces. J Appl Meteorol. 10:1285–1295.
   Google Scholar
• Croft H, Anderson K, Kuhn NJ. 2009. Characterizing soil surface roughness using a combined structural and spectral approach. Eur J Soil Sci. 60:431–442.
   Web of Science ®Google Scholar
• Fan RQ, Yang XM, Zhang XP, Shen Y, Liang AZ, Shi XH, Wei SC, Chen XW. 2012. Prediction of soil organic carbon in different soil fractions of black soils in Northeast China using near-infrared reflectance spectroscopy. Spectrosc Spect Anal. 32:349–353.
   Web of Science ®Google Scholar
• Ge Y, Thomasson JA, Morgan CL, Searcy SW. 2007. VNIR diffuse reflectance spectroscopy for agricultural soil property determination based on regression-kriging. Trans ASABE. 50:1081–1092.
   Web of Science ®Google Scholar
• Gong ZT, Zhang GL, Chen ZC. 2007. Pedogenesis and soil taxonomy. Beijing: Science Press.
   Google Scholar
• Karlen DL, Mausbach MJ, Doran JW, Cline RG, Harris RF, Schuman GE. 1997. Soil quality: a concept, definition and framework for evaluation. Soil Sci Soc Am J. 61:4–10.
   Web of Science ®Google Scholar
• Kaspar TC, Pulido DJ, Fenton TE, Colvin TS, Karlen DL, Jaynes DB, Meek DW. 2004. Relationship of corn and soybean yield to soil and terrain properties. Agron J. 96:700–709.
   Web of Science ®Google Scholar
• Kravchenko AN, Bullock DG. 2000. Correlation of corn and soybean grain yield with topography and soil properties. Agron J. 92:75–83.
   Web of Science ®Google Scholar
• Levin N, Ben-Dor E, Singer A. 2005. A digital camera as a tool to measure colour indices and related properties of sandy soils in semi-arid environments. Int J Remote Sens. 26:5475–5492.
   Web of Science ®Google Scholar
• Li D, Chen XZ, Peng ZP, Chen SS, Chen WQ, Han LS, Li YJ. 2012. Prediction of soil organic matter content in a litchi orchard of South China using spectral indices. Soil Till Res. 123:78–86.
   Web of Science ®Google Scholar
• Liu HJ, Zhang YZ, Zhang B. 2009. Novel hyperspectral reflectance models for estimating black-soil organic matter in Northeast China. Environ Monit Assess. 154:147–154.
   PubMed Web of Science ®Google Scholar
• Liu Y, Swinton SM, Miller NR. 2006. Is site-specific yield response consistent over time? Does it pay? Am J Agr Econ. 88:471–483.
   Web of Science ®Google Scholar
• Liu YC, Chan WH, Chan YQ. 1995. Automatic white balance for digital still camera. IEEE T Consum Electr. 41:460–466.
   Web of Science ®Google Scholar
• Lu YL, Bai YL, Yang LP, Wang L, Wang H. 2011. Homogeneity of retrieval models for soil organic matter of different soil types in Northeast Plain using hyperspectral data. Plant Nutri Fertil Sci. 17:456–463. Chinese.
   Google Scholar
• McBratney AB, Stockmann U, Angers DA, Minasny B, Field DJ. 2014. Challenges for soil organic carbon research. In: Alfred, E, Hartemink, AE, McSweeney, K, editors. Soil carbon. New York: Springer; p. 3–16.
   Google Scholar
• Sarkhot DV, Grunwald S, Ge Y, Morgan CLS. 2011. Comparison and detection of total and available soil carbon fractions using visible/near infrared diffuse reflectance spectroscopy. Geoderma. 164:22–32.
   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. 144:395–404.
   Web of Science ®Google Scholar
• Tekin Y, Tumsavas Z, Mouazen AM. 2012. Effect of moisture content on prediction of organic carbon and pH using visible and near-infrared spectroscopy. Soil Sci Soc Am J. 76:188–198.
   Web of Science ®Google Scholar
• The National Soil Survey Office. 1994. Soil species of China. Vol. 2. Beijing: China Agriculture Press.
   Google Scholar
• Vasques GM, Grunwald S, Sickman JO. 2008. Comparison of multivariate methods for inferential modeling of soil carbon using visible/near-infrared spectra. Geoderma. 146:14–25.
   Web of Science ®Google Scholar
• Viscarra Rossel RA, Chappell A, De Caritat P, McKenzie NJ. 2011. On the soil information content of visible–near infrared reflectance spectra. Eur J Soil Sci. 62:442–453.
   Web of Science ®Google Scholar
• Xie XL, Sun B, Zhou HZ, Li AB. 2004. Soil organic carbon storage in China. Pedosphere. 14:491–500.
   Web of Science ®Google Scholar
• Yang XM, Xie HT, Drury CF, Reynolds WD, Yang JY, Zhang XD. 2012. Determination of organic carbon and nitrogen in particulate organic matter and particle size fractions of Brookston clay loam soil using infrared spectroscopy. Eur J Soil Sci. 63:177–188.
   Web of Science ®Google Scholar