EFFECT OF FARM MACHINERY ON SOME SOIL PHYSICAL PROPERTIES USING HYPERSPECTRAL DATA | ||
| Misr Journal of Agricultural Engineering | ||
| Article 1, Volume 35, Issue 2, April 2018, Pages 395-406 PDF (458.6 K) | ||
| Document Type: Original Article | ||
| DOI: 10.21608/mjae.2018.95755 | ||
| Authors | ||
| G. M. Nasr1; W. M. Abd Elkawy2; A. H. Al-nahry3; S. M. Abd Elhafeez4 | ||
| 11Prof. of Agric. Eng. Fac. of Agric. Cairo Univ., Giza, Egypt. | ||
| 2Prof. of Soil Sciences. Fac. of. Agric. Cairo Univ., Giza, Egypt. | ||
| 3Prof. of Soil Sciences. National Authority for Remote Sensing & Space Sciences, Egypt. | ||
| 4Agricultural specialist, National Authority for Remote Sensing & Space Sciences, Egypt. | ||
| Abstract | ||
| Traditional soil analyses are expensive, time-consuming, and may also result in environmental pollutants. The objective of this study was to develop a methodology to predict soil physical properties specifically the soil bulk density using spectral reflectance (SR) as an alternative to traditional methods. Additionally to critically examine the suitability of Visible and Near-infrared (Vis- NIR) (350–2500 nm) measurements for calibration procedures and methods to predict the value of soil bulk density. Five different seedbed preparation systems were applied. Spectroradiometer ASD was used to measure the soil spectral reflectance of each system. Stepwise multiple linear regression (SMLR) was used to construct calibration models subjected to the independent validation. The obtained regression models were of good quality (R2 = 0.959, 0.868, 0.811, 0.751 and 0.677 for system 5, system 1, system 3, system 4 and system 2, respectively). Thus, Visible and Near-infrared (Vis-NIR) reflection spectroscopy is cost- and time-effective procedure that can be used as an alternative to the traditional methods of measuring soil physical properties. | ||
| Keywords | ||
| seedbed preparation; physical properties; bulk density; spectral reflectance; spectroradiometer; multi linear regression (MLR) | ||
| References | ||
|
Abdel-Nour, N.; Ngadi, M.; Prasher, M. and Karimi, Y. 2009. Combined maximum R2 and partial least square wavelengths selection and analysis of spectroscopic data. International Journal of poultry science, 8(2), 170-178.
Aboelghar, M. and Abdel Wahab H. 2013. Spectral footprint of Botrytis cinerea, a novel way for fungal characterization. Advances in Bioscience and Biotechnology, 4, pp. 374-382.
Al Malikia, A.; Owens, G. and Bruce, D. 2012. Capabilities of remote sensing hyperspectral images for the detection of lead contamination. A review. Remote Sensing and Spatial Information Sciences, Volume I-7.
Awes, R. S. 2017. Detection of heavy metals contamination in southern soils of Port Said governorate using remote sensing techniques. M.Sc. Thesis, Soil and Water Dept., Fac. of Agric., Suez Canal Univ. Egypt.Demattệ, J. A. M.; Nanni, M. R.; da Silva, A. P.; de Melo Filho, J. F.; Dos Santos, W. C. and Campos, R. C. 2010. Soil density evaluated by spectral reflectance as an evidence of compaction effects. International Journal of Remote Sensing, 31, 403-422.Mohamed, E. S.; Ali, A. M.; El Shirbeny, M. A.; Abd El Razek Afaf A. and Savin I. Yu. 2016. Near infrared spectroscopy techniques for soil contamination assessment in the nile delta. Eurasian Soil Science, 49(6), 632–639.
Parveen, R.; Kulkarni, S. and Mytri, V. D. 2017. Study of IRS 1C-LISS III image and identification of land cover features based on spectral responses. Geospatial World Forum.
Valainis, O.; Rucins, A. and Vilde, A. 2014. Technological operational assessment of one pass combined agricultural machinery for seedbed preparation and seeding. Engineering for Rural Development, 37-43.
Yones, M. S.; Aboelghar, M. A.;El-Shirbeny, M. A.; Khdry, G.A.; Ali, A. M., and Saleh, N.S. 2014. Hyperspectral Indices For Assessing Damage By The Red Palm Weevil Rhynchophorus Ferrugineus (Coleoptera: Curculionidae) In Date Palms. International Journal of Geosciences and Geomatics, 2, 16-23. | ||
|
Statistics Article View: 190 PDF Download: 252 |
||
