Evaluation of phalaenopsis flowering quality using near infrared spectroscopy

Suming Chen, Yung Kun Chuang, Chao Yin Tsai, A. Chang Yao-Chien, Yang I-Chang Yang, Chang Yung-Huei Chang, Tai Chu-Chun Tai, Hou Jiunn-Yan Hou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish
Title of host publicationSensing Technologies for Biomaterial, Food, and Agriculture 2013
Volume8881
DOIs
Publication statusPublished - 2013
Externally publishedYes
EventSensing Technologies for Biomaterial, Food, and Agriculture 2013 - Yokohama, Japan
Duration: Apr 23 2013Apr 25 2013

Conference

ConferenceSensing Technologies for Biomaterial, Food, and Agriculture 2013
CountryJapan
CityYokohama
Period4/23/134/25/13

Fingerprint

Near-infrared Spectroscopy
Near infrared spectroscopy
Flowering
infrared spectroscopy
Wavelength
smoothing
Smoothing
evaluation
carbohydrates
Carbohydrates
Evaluation
wavelengths
Derivatives
Derivative
Fructose
Range of data
Starch
starches
sucrose
Sugar (sucrose)

Keywords

  • flowering quality
  • fructose
  • glucose
  • near-infrared reflectance spectroscopy
  • Phalaenopsis
  • starch
  • sucrose

ASJC Scopus subject areas

  • Applied Mathematics
  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics

Cite this

Chen, S., Chuang, Y. K., Tsai, C. Y., Yao-Chien, A. C., I-Chang Yang, Y., Yung-Huei Chang, C., ... Jiunn-Yan Hou, H. (2013). Evaluation of phalaenopsis flowering quality using near infrared spectroscopy. In Sensing Technologies for Biomaterial, Food, and Agriculture 2013 (Vol. 8881). [88810F] https://doi.org/10.1117/12.2030710

Evaluation of phalaenopsis flowering quality using near infrared spectroscopy. / Chen, Suming; Chuang, Yung Kun; Tsai, Chao Yin; Yao-Chien, A. Chang; I-Chang Yang, Yang; Yung-Huei Chang, Chang; Chu-Chun Tai, Tai; Jiunn-Yan Hou, Hou.

Sensing Technologies for Biomaterial, Food, and Agriculture 2013. Vol. 8881 2013. 88810F.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Chen, S, Chuang, YK, Tsai, CY, Yao-Chien, AC, I-Chang Yang, Y, Yung-Huei Chang, C, Chu-Chun Tai, T & Jiunn-Yan Hou, H 2013, Evaluation of phalaenopsis flowering quality using near infrared spectroscopy. in Sensing Technologies for Biomaterial, Food, and Agriculture 2013. vol. 8881, 88810F, Sensing Technologies for Biomaterial, Food, and Agriculture 2013, Yokohama, Japan, 4/23/13. https://doi.org/10.1117/12.2030710
Chen S, Chuang YK, Tsai CY, Yao-Chien AC, I-Chang Yang Y, Yung-Huei Chang C et al. Evaluation of phalaenopsis flowering quality using near infrared spectroscopy. In Sensing Technologies for Biomaterial, Food, and Agriculture 2013. Vol. 8881. 2013. 88810F https://doi.org/10.1117/12.2030710
Chen, Suming ; Chuang, Yung Kun ; Tsai, Chao Yin ; Yao-Chien, A. Chang ; I-Chang Yang, Yang ; Yung-Huei Chang, Chang ; Chu-Chun Tai, Tai ; Jiunn-Yan Hou, Hou. / Evaluation of phalaenopsis flowering quality using near infrared spectroscopy. Sensing Technologies for Biomaterial, Food, and Agriculture 2013. Vol. 8881 2013.
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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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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.

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