• Shruti U. Hiwale
• Rupali R. Surase
• Sandeep V. Gaikwad
• Amol D. Vibhute

Soil physiochemical attributes detection is difficult and crucial part in soil science, soil attributes are varied in spatially and temporally with the complexity of nature. Soil physiochemical laboratory analysis method is very time consuming and difficult. However, this paper introduced hyperspectral reflectance spectroscopy and studied within visible (350-700nm) and near infrared (700-2500nm), Imagery spectroscopy (400-1000nm) is used to categories the spatial characteristics of soil contents. 30 soil samples collected from the vegetable farm near Tahsil, District Jalna region Maharashtra. Spectra of soil samples acquired using Analytical Spectral Device (ASD) Field spec 4 spectroradiometer. Imagery data were collected from PIKA L spectroscopy. The spectra data were preprocessed and given input to the regression model. A partial least squares regression PLSR model was used for prediction of soil attributes from spectroscopy data. The correlation result (R2) for Zinc, Iron, Copper, Magnesium are as 0.903, 0.829, 0.948, 0.952 with RMSE 0.036, 0.0037, 0.028, 0.018 whereas for as imagery part of spectroscopy used the index NIODI for fe and predicted result as Fe: 0.09848 respectively.

Soil attribute, Imagery Spectroscopy PIKA L, ASD Field Spect 4, PLSR partial least squares regression

"Assessment of micronutrients using from soil using hyperspectral data", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.332-338, April-2019, Available :http://www.jetir.org/papers/JETIR1904E56.pdf

"Assessment of micronutrients using from soil using hyperspectral data", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp332-338, April-2019, Available at : http://www.jetir.org/papers/JETIR1904E56.pdf