Graduate Defense: Suresh Thapa
“Virtual Soil Spectrum Analysis Laboratory”
11:00 am –
12:00 pm
Zoom
Graduate Defense: Suresh Thapa
October 23, 2020
11 a.m.
Zoom
“Virtual Soil Spectrum Analysis Laboratory”
Soil is indispensable for sustaining life systems on earth. Degradation of soil health adversely affects ecological balance and food security. Regular monitoring of the soil properties allows scientists to assess the soil health, and helps in preserving and managing soil. Traditional methods used for soil analysis cannot meet the scale, throughput and resolution of soil data needed for modern day applications like precision agriculture. Visible-Near Infrared Spectroscopy (VNIR) and Mid-Infrared Spectroscopy (MIR) have been established as a complementary technique to derive the soil properties rapidly from a single spectrum. In this work, a web-based application called Virtual Soil Spectrum Analysis Laboratory (VSSAL) was built that uses machine learning in the backend to predict the soil properties from the VNIR/MIR soil spectra provided by the user. VSSAL speeds up the modeling process by providing pre-trained models and providing an interface to easily sample, pre-process, and calibrate the custom models. A test was conducted using three VNIR and one MIR test datasets. The results obtained are encouraging and show the potential of spectroscopy in routine soil analysis.
Zoom URL: https://unl.zoom.us/j/91084473903
Committee Members:
Dr. Hongfeng Yu (Advisor)
Dr. Yufeng Ge
Dr. Mohammad Rashedul Hasan
October 23, 2020
11 a.m.
Zoom
“Virtual Soil Spectrum Analysis Laboratory”
Soil is indispensable for sustaining life systems on earth. Degradation of soil health adversely affects ecological balance and food security. Regular monitoring of the soil properties allows scientists to assess the soil health, and helps in preserving and managing soil. Traditional methods used for soil analysis cannot meet the scale, throughput and resolution of soil data needed for modern day applications like precision agriculture. Visible-Near Infrared Spectroscopy (VNIR) and Mid-Infrared Spectroscopy (MIR) have been established as a complementary technique to derive the soil properties rapidly from a single spectrum. In this work, a web-based application called Virtual Soil Spectrum Analysis Laboratory (VSSAL) was built that uses machine learning in the backend to predict the soil properties from the VNIR/MIR soil spectra provided by the user. VSSAL speeds up the modeling process by providing pre-trained models and providing an interface to easily sample, pre-process, and calibrate the custom models. A test was conducted using three VNIR and one MIR test datasets. The results obtained are encouraging and show the potential of spectroscopy in routine soil analysis.
Zoom URL: https://unl.zoom.us/j/91084473903
Committee Members:
Dr. Hongfeng Yu (Advisor)
Dr. Yufeng Ge
Dr. Mohammad Rashedul Hasan