NDLI: Research on spectral characteristics model of lettuce canopy nitrogen content

Content Provider	IEEE Xplore Digital Library
Author	Gao Hongyan Mao Hanping Zhang Xiaodong Sun Jun
Copyright Year	2011
Description	Author affiliation: Key Laboratory of Modern Agricultural Equipment and Technology, Ministry of Education & Jiangsu Province, Jiangsu University, Zhenjiang 212013, China (Gao Hongyan; Mao Hanping; Zhang Xiaodong; Sun Jun)
Abstract	Lettuce canopy spectral reflectance was measured by hand-held portable spectrum analyzer, the reflectance characteristics was analyzed in the different nitrogen levels and different growth. After the first derivative treatment, then correlation analysis, lettuce canopy nitrogen associated with the four-sensitive band ,which were 400 ∼ 470nm, 510 ∼ 590nm, 600 ∼ 670nm, 680 ∼ 750nm. Further used stepwise regression analysis, selected the sensitive wavelengths in different growth stages. Partial least squares regression was used for setting up prediction models in different growth. 24 samples were verified models in the same period, the measured and predicted of the correlation coefficient were 0.8570, 0.8853 and 0.8591, and RMSE were 0.6355, 0.6122 and 0.5472.
Starting Page	2335
Ending Page	2338
File Size	304423
Page Count	4
File Format	PDF
ISBN	9781424493043
e-ISBN	9781424493067
DOI	10.1109/CISP.2011.6100675
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-10-15
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Reflectivity Correlation Partial Least Squares Regression Analysis Lettuce Laboratories Reflectance Spectra Predictive models Educational institutions Nitrogen Mathematical model
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Neural Network with Partial Least Square Prediction Model Based on SSA—MGF

Prediction of soluble solid content of starfruit using spectral imaging combined with partial least squares and support vector regression

Prediction Model of Grain Crude Protein and Amylose Content with Canopy Spectral Reflectance in Rice

Possibilities of Multi-spectral Data for the Assessment of Soil Nitrogen Content

The study of regression based on grey system theory

Analysis of Individual Career Decision-Making Based on Partial Least-Squares Regression Model

Evaluating Soil Organic Matter with visible spectroscopy

Foliar Spectra and Traits of Bog Plants across Nitrogen Deposition Gradients

Chlorophyll concentration estimation model based on canopy spectra of Spartina Anglica

Research on spectral characteristics model of lettuce canopy nitrogen content

Similar Documents

Neural Network with Partial Least Square Prediction Model Based on SSA—MGF

Prediction of soluble solid content of starfruit using spectral imaging combined with partial least squares and support vector regression

Prediction Model of Grain Crude Protein and Amylose Content with Canopy Spectral Reflectance in Rice

Possibilities of Multi-spectral Data for the Assessment of Soil Nitrogen Content

The study of regression based on grey system theory

Analysis of Individual Career Decision-Making Based on Partial Least-Squares Regression Model

Evaluating Soil Organic Matter with visible spectroscopy

Foliar Spectra and Traits of Bog Plants across Nitrogen Deposition Gradients

Chlorophyll concentration estimation model based on canopy spectra of Spartina Anglica

Research on spectral characteristics model of lettuce canopy nitrogen content