Share Email Print
cover

Proceedings Paper

Measuring the chlorophyll content in leaves by near infrared analysis
Author(s): Huanyu Jiang; Yingshi Bao; Yibin Ying
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Chlorophyll content in leaves is one of the important internal information for predicting plants growth status. In this study, we use near infrared (NIR) spectroscopy technique to predict chlorophyll content in pepper leaves. Calibration models were created from spectral and constituent measurements, chlorophyll content measured by a SPAD-502 chlorophyll meter, 74 samples served as the calibration sets and 16 samples served as the validation sets. Partial least squares (PLS) and principal component regression (PCR) analysis technique were used to develop the prediction models, and four different mathematical treatments were used in spectrums processing: smoothing, baseline correction, different wavelength range, first and second derivative. When we use PLS analysis and select spectra with second derivate, we can get high correlation efficient and low RMSEC value, but big difference between RMSEC and RMSEP. The best calibration model when we delete four outlier samples, when we process spectra with second derivate at full wavelength, we can get highest correlation coefficient (r=0.97537), a relative lower RMSEC value (2.33), and a small difference between RMSEC (2.33) and RMSEP (5.49). Result showed that NIR technique is a non-destructive way; it can acquire chlorophyll content in pepper leaves quickly and conveniently.

Paper Details

Date Published: 9 November 2005
PDF: 11 pages
Proc. SPIE 5996, Optical Sensors and Sensing Systems for Natural Resources and Food Safety and Quality, 599617 (9 November 2005); doi: 10.1117/12.630055
Show Author Affiliations
Huanyu Jiang, Zhejiang Univ. (China)
Yingshi Bao, Zhejiang Univ. (China)
Jinhua College of Profession and Technology (China)
Yibin Ying, Zhejiang Univ. (China)


Published in SPIE Proceedings Vol. 5996:
Optical Sensors and Sensing Systems for Natural Resources and Food Safety and Quality
Yud-Ren Chen; George E. Meyer; Shu-I Tu, Editor(s)

© SPIE. Terms of Use
Back to Top