Abstract
The soil properties assessment is very important for identifying the soil content for requirement of fertilizers as well as discovery of fertilizers. In the traditional, soil properties analysis has been obtained through routine soil physicochemical laboratory analysis. However, these laboratory methods do not fulfill the rapid requirements. Accordingly, spectroscopic remote sensing methods can be used to nondestructively detect and characterize soil content without chemical analysis. In the present research, we use spectroscopy techniques for soil properties analysis. The non-imaging spectral data of agglomerated farming soils were acquired by the ASD Field spec 4 spectroradiometer. It provides the large range of data in Visible (350–700 nm) and Near-Infrared (700–2500 nm) region. Total 110 soil specimens were collected in pre-monsoon and post-monsoon, respectively, with mixed, organic, chemical fertilizers treatment applied for banana and cotton crops in the context of surface and subsurface for finding the influence of fertilizers. The soil sample was collected from Raver Tehsil of Jalgaon District of Maharashtra, India. The soil spectra of VNIR region were preprocessed to get pure spectra. Then process the acquired spectral data by statistical methods for quantitative analysis of soil properties. The detected soil properties were carbon, Nitrogen, soil organic matter, pH, phosphorus, potassium, moisture sand, silt, and clay. In this paper, required statistical methods are used for quantitative analysis of soil properties. The quantitative analysis represents the availability of soil properties.
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Borole, V.Y., Kulkarni, S.B. (2022). Statistical Analysis of Soil Properties Using Non-imaging Spectral Data for Quantitative Analysis of Raver Tehsil. In: Satyanarayana, C., Samanta, D., Gao, XZ., Kapoor, R.K. (eds) High Performance Computing and Networking. Lecture Notes in Electrical Engineering, vol 853. Springer, Singapore. https://doi.org/10.1007/978-981-16-9885-9_5
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