Wavelength Selection of Hyperspectral Scattering Image Using New Semi-supervised Affinity Propagation for Prediction of Firmness and Soluble Solid Content in Apples

Food Analytical Methods

Volumn 6, Issue 1, 2013, Pages 334-342

  Zhu, Qibing ^a   Huang, Min ^a   Zhao, Xin ^a   Wang, Shuang ^a  

^a JIANGNAN UNIVERSITY   (China)

Author keywords

Apple; Firmness; Hyperspectral scattering image; Partial least squares; Semi supervised affinity propagation; Soluble solids content; Wavelength selection

Indexed keywords

AGRICULTURAL ROBOTS; FORECASTING; FRUITS; GENETIC ALGORITHMS; LEAST SQUARES APPROXIMATIONS; MEAN SQUARE ERROR; NONDESTRUCTIVE EXAMINATION;

APPLE; FIRMNESS; HYPERSPECTRAL SCATTERINGS; PARTIAL LEAST SQUARE (PLS); SEMI-SUPERVISED AFFINITY PROPAGATION; SOLUBLE SOLIDS CONTENT; WAVELENGTH SELECTION;

PREDICTIVE ANALYTICS;

MALUS X DOMESTICA;

EID: 84872245581     PISSN: 19369751     EISSN: 1936976X     Source Type: Journal    
DOI: 10.1007/s12161-012-9442-2     Document Type: Article

References (23)

1. Abbott JA (1999) Quality measurement of fruits and vegetables. Postharvest Biol Technol 15: 207-225.
2. Armstrong PR, Stone ML, Brusewitz GH (1997) Peach firmness determination using two different nondestructive vibrational sensing instruments. Trans ASAE 40: 699-703.
3. Dan T, Dai L (2009) Spectral wavelength selection based on PLS projection analysis. Spectrosc Spectr Anal 29: 351-354.
4. Frey BJ, Dueck D (2007) Clustering by passing messages between data points. Science 315: 972-976.
5. Huang S, Chen Q (2009) On clustering algorithm of high dimensional data based on similarity measurement. Comput Appl Softw 26: 102-105.
6. Huang M, Lu R (2010) Optimal wavelengths selection for hyperspectral scattering prediction of apple firmness and soluble solids content. Trans ASABE 53: 1175-1182.
7. Koumonsis K, Katsaras C (2006) A saw-tooth genetic algorithm combining the effects of variable and reinitialization to enhance performance. IEEE Trans Evol Comput 10: 19-28.
8. Kracik J (2011) Combining marginal probability distributions via minimization of weighted sum of Kullback-Leibler divergences. Int J Approx Reason 14: 1-13.
9. Lu R (2004) Multispectral imaging for predicting firmness and soluble solids content of apple fruit. Postharvest Biol Technol 31: 147-157.
10. Lu R (2007) Nondestructive measurement of firmness and soluble solids content for apple fruit using hyperspectral scattering images. Sens & Instrumen Food Qual Saf 1: 19-27.
11. Lu R, Ariana D (2002) A near-infrared sensing technique for measuring internal quality of apple fruit. Appl Eng Agric 18: 585-590.
12. Lu R, Guyer DE, Beaudry RM (2000) Determination of firmness and sugar content of apples using near-infrared diffuse reflectance. J Texture Stud 31: 615-630.
13. McGlone VA, Jordan RB, Martinsen PJ (2002) Vis/NIR estimation at harvest of pre- and post-storage quality indices for 'Royal Gala' apple. Postharvest Biol Technol 25: 135-144.
14. Mendoza F, Lu R, Ariana D, Cen H, Bailey BB (2011) Integrated spectral and image analysis of hyperspectral scattering data for prediction of apple fruit firmness and soluble solids content. Postharvest Biol Technol 62: 149-160.
15. Min M, Lee WS (2005) Determination of significant wavelengths and prediction of nitrogen content for citrus. Trans ASAE 48: 455-461.
16. Peng Y, Lu R (2006) An LCTF-based multispectral imaging system for estimation of apple fruit firmness. Part I. Acquisition and characterization of scattering images. Trans ASAE 49: 259-267.
17. Peng Y, Lu R (2008) Analysis of spatially resolved hyperspectral scattering images for assessing apple fruit firmness and soluble solids content. Postharvest Biol Technol 48: 52-62.
18. Qian Y, Yao F, Jia S (2009) Band selection for hyperspectral imagery using affinity propagation. IET Comput Vis 34: 213-222.
19. Qin J, Lu R (2007) Measurement of the absorption and scattering properties of turbid liquid foods using hyperspectral imaging. Appl Spectrosc 61: 388-396.
20. Qin J, Lu R (2008) Measurement of the optical properties of fruits and vegetables using spatially resolved hyperspectral diffuse reflectance imaging technique. Postharvest Biol Technol 49: 355-365.
21. Qin J, Lu R, Peng Y (2009) Prediction of apple internal quality using spectral absorption and scattering properties. Trans ASABE 52(2): 499-507.
22. Wang S, Huang M, Zhu Q (2012) Model fusion for prediction of apple firmness using hyperspectral scattering image. Comput Electron Agric 80: 1-7.
23. Zude M, Herold BJ, Roger M, Bellon-Maurel V, Landahl S (2006) Non-destructive tests on the prediction of apple fruit flesh firmness and soluble solids content on tree and in shelf life. J Food Eng 77: 254-260.