TY - GEN
T1 - Evaluation of phalaenopsis flowering quality using near infrared spectroscopy
AU - Chen, Suming
AU - Chuang, Yung Kun
AU - Tsai, Chao Yin
AU - Yao-Chien, A. Chang
AU - I-Chang Yang, Yang
AU - Yung-Huei Chang, Chang
AU - Chu-Chun Tai, Tai
AU - Jiunn-Yan Hou, Hou
PY - 2013
Y1 - 2013
N2 - Carbohydrate contents have been demonstrated as indicators for flowering quality of Phalaenopsis plants. In this study, near infrared reflectance (NIR) spectroscopy was employed for quantitative analysis of carbohydrate contents like fructose, glucose, sucrose, and starch in Phalaenopsis. The modified partial least squares regression (MPLSR) method was adopted for spectra analyses of 176 grown plant samples (88 shoots and 88 roots), over the full wavelength range (FWR, 400 to 2498 nm). For fructose concentrations, the smoothing 1st derivative model can produce the best effect (Rc = 0.961, SEC = 0.210% DW, SEV = 0.324% DW) in the wavelength ranges of 1400-1600, 1800-2000, and 2200-2300 nm. For glucose concentrations, the smoothing 1st derivative model can produce the best effect (Rc = 0.975, SEC = 0.196% DW, SEV = 0.264% DW) in the wavelength range of 1400-1600, 1800-2000, and 2100-2400 nm. For sucrose concentrations, the smoothing 1st derivative model can produce the best effect (Rc = 0.961, SEC = 0.237% DW, SEV = 0.322% DW) in the wavelength range of 1300-1400, 1500-1800, 2000-2100, and 2200-2300 nm. For starch concentrations, the smoothing 1st derivative model can produce the best effect (Rc = 0.873, SEC = 0.697% DW, SEV = 0.774% DW) in the wavelength ranges of 500-700, 1200-1300, 1700-1800, and 2200-2300 nm. This study successfully developed the calibration models for inspecting concentrations of carbohydrates to predict the flowering quality in different cultivation environments of Phalaenopsis. The specific wavelengths can be used to predict the quality of Phalaenopsis flowers and thus to adjust cultivation managements.
AB - Carbohydrate contents have been demonstrated as indicators for flowering quality of Phalaenopsis plants. In this study, near infrared reflectance (NIR) spectroscopy was employed for quantitative analysis of carbohydrate contents like fructose, glucose, sucrose, and starch in Phalaenopsis. The modified partial least squares regression (MPLSR) method was adopted for spectra analyses of 176 grown plant samples (88 shoots and 88 roots), over the full wavelength range (FWR, 400 to 2498 nm). For fructose concentrations, the smoothing 1st derivative model can produce the best effect (Rc = 0.961, SEC = 0.210% DW, SEV = 0.324% DW) in the wavelength ranges of 1400-1600, 1800-2000, and 2200-2300 nm. For glucose concentrations, the smoothing 1st derivative model can produce the best effect (Rc = 0.975, SEC = 0.196% DW, SEV = 0.264% DW) in the wavelength range of 1400-1600, 1800-2000, and 2100-2400 nm. For sucrose concentrations, the smoothing 1st derivative model can produce the best effect (Rc = 0.961, SEC = 0.237% DW, SEV = 0.322% DW) in the wavelength range of 1300-1400, 1500-1800, 2000-2100, and 2200-2300 nm. For starch concentrations, the smoothing 1st derivative model can produce the best effect (Rc = 0.873, SEC = 0.697% DW, SEV = 0.774% DW) in the wavelength ranges of 500-700, 1200-1300, 1700-1800, and 2200-2300 nm. This study successfully developed the calibration models for inspecting concentrations of carbohydrates to predict the flowering quality in different cultivation environments of Phalaenopsis. The specific wavelengths can be used to predict the quality of Phalaenopsis flowers and thus to adjust cultivation managements.
KW - flowering quality
KW - fructose
KW - glucose
KW - near-infrared reflectance spectroscopy
KW - Phalaenopsis
KW - starch
KW - sucrose
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U2 - 10.1117/12.2030710
DO - 10.1117/12.2030710
M3 - Conference contribution
AN - SCOPUS:84880740638
SN - 9780819497437
VL - 8881
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Sensing Technologies for Biomaterial, Food, and Agriculture 2013
T2 - Sensing Technologies for Biomaterial, Food, and Agriculture 2013
Y2 - 23 April 2013 through 25 April 2013
ER -