17 May 2013 Evaluation of Phalaenopsis flowering quality using near infrared spectroscopy
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Abstract
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.
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Suming Chen, Suming Chen, Yung-Kun Chuang, Yung-Kun Chuang, Chao-Yin Tsai, Chao-Yin Tsai, Yao-Chien A. Chang, Yao-Chien A. Chang, I-Chang Yang, I-Chang Yang, Yung-Huei Chang, Yung-Huei Chang, Chu-Chun Tai, Chu-Chun Tai, Jiunn-Yan Hou, Jiunn-Yan Hou, } "Evaluation of Phalaenopsis flowering quality using near infrared spectroscopy", Proc. SPIE 8881, Sensing Technologies for Biomaterial, Food, and Agriculture 2013, 88810F (17 May 2013); doi: 10.1117/12.2030710; https://doi.org/10.1117/12.2030710
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