Potable NIR spectroscopy predicting soluble solids content of pears based on LEDs

Journal of Physics: Conference Series

Volumn 277, Issue 1, 2011, Pages

  Liu, Yande ^a   Liu, Wei ^a   Sun, Xudong ^a   Gao, Rongjie ^a   Pan, Yuanyuan ^a   Ouyang, Aiguo ^a  

^a EAST CHINA JIAOTONG UNIVERSITY   (China)

Author keywords

Artificial neural network; LEDs; Near infrared spectroscopy; Partial least squares; Portable; Soluble solids content

Indexed keywords

CALIBRATION; DEEP NEURAL NETWORKS; FORECASTING; FRUITS; INFRARED DEVICES; LEAST SQUARES APPROXIMATIONS; MEAN SQUARE ERROR; NEAR INFRARED SPECTROSCOPY; NEURAL NETWORKS; PHOTONICS;

CORRELATION COEFFICIENT; MULTIVARIATE LINEAR REGRESSIONS; NEAR INFRA RED; NIR SPECTROSCOPY; PARTIAL LEAST SQUARE (PLS); PORTABLE; ROOT MEAN SQUARE ERRORS; SOLUBLE SOLIDS CONTENT;

LIGHT EMITTING DIODES;

EID: 79953831319     PISSN: 17426588     EISSN: 17426596     Source Type: Conference Proceeding    
DOI: 10.1088/1742-6596/277/1/012026     Document Type: Conference Paper

References (17)

1. T. Temm a, K. Hanamatsu, and F. Shinoki, "Development of a portable near infrared sugar-measuring instrument," J. Near Infrared Spectrosc., vol. 10, pp. 77-83, 2002.
2. Y.B. Ying, Y.D. Liu, J.P. Wang, X.P. Fu, and Y.B. Li, "Fourier transform near infrared determination of total soluble solids and available acid in intact peaches," Transactions of the ASAE, vol. 48 (1), pp. 229-23, 2005.
3. Y.D. Liu, Y.B. Ying, and H.Y. Jiang, "Rapid determination of maturity in apple using outlet detection and calibration model optimization,"Transactions of the ASAE, vol. 49 (1), pp. 91-95, 2006.
4. T. Temma, K. Hanamatsu and F. Shinoki, J.Near Infrared Spectrosc. 10, 77 2002.
5. Chemleds. Telcom Devices datasheet.
6. B.A. Matveev, et al., Mid-infrared (3-5 mm) LEDs as sources for gas and liquid sensors, Sensors and Actuators B 38-39 (1997) 339-343. (Pubitemid 127428314)
7. Pascal Chalus, Serge Walter, and Michel Ulmschneider, "Combined wavelet transform - artificial neural network use in tablet active content determination by near-infrared spectroscopy," Analytica Chimica Acta, vol. 591, PP. 219-224, 2007.
8. Jouko Malinen, Markku Känsäkoski, Raimo Rikola, and Colin G. Eddison "LED-based NIR spectrometer module for hand-held and process analyser applications," Sensors and Actuators B, vol. 51, pp. 220-224, 1998.
9. Edvaldo da N'obrega Gaĩao et al, "An inexpensive, portable and microcontrolled near infrared LED-photometer for screening analysis of gasoline," Talanta, vol. 75, PP. 792-796, 2008.
10. F. Despagne, D.L. Massart, Analyst .157-178.174-180, 1998.
11. D. Perez-Marin, A. Garrido-Varo, J.E. Guerrero, Talanta 72 28-42, 2007.
12. B.N.Peshlov, F.E.Dowell, F.A.Drummond, and D.W.Donshue, "Comparison of three near infrared spectrophotometers for infestation detection in wild blueberries using multivariate calibration models," J. Near Infrared Spectrosc, vol. 17, PP. 203-212, 2009.
13. Lingzhi Zhao , Ying Dou , Ye Guoa, Yonghong Chen, and Yulin Ren, "Artificial neural networks for non-destructive determination of acetylspiramycin powder by short-wavelength NIR spectroscopy," Vibrational Spectroscopy, vol. 47, pp. 21-25, 2008.
14. R. Lu, and D. Ariana, "A near-infrared sensing technique for measuring internal quality of apple fruit," Applied Engineering in Agriculture, vol. 18 (5), pp. 585-590, 2002.
15. Yongni Shao, Yong He, Antihus H ,Gomez , Annia G .pereir ,Zhengjun Qiu, and Yun Zhang, "Visible/near infrared spectrometric technique for nondestructive assessment of tomato'Heatwave'(Lycopersicum esculentum) quality charateristics," Journal of Food Engineering , vol . 81, pp. 672-678, 2007.
16. Y.D. Liu, Y.B. Ying, X.P. Fu, and H.S. Lu, "Experiments on predicting sugar content in apples by FT-NIR technique," Journal of Food Engineering, vol. 80, pp. 986-989, 2007.
17. B.M. Nicolaï, K.I. Theron, J. Lammertyn, and Kernel, "PLS regression on wavelet transformed NIR spectra for prediction of sugar content of appe,"Chemometrics and Intelligent Laboratory Systems, vol. 85 (2), pp. 243-252., 2007.