Use of Unfold PCA for on-line plant stress monitoring and sensor failure detection

Biosystems Engineering

Volumn 103, Issue 1, 2009, Pages 23-34

  Villez, Kris ^a,b   Steppe, Kathy ^c   De Pauw, Dirk J W ^d  

^a Fac Sci l'Agric et de l'Aliment   (Canada)

^b GHENT UNIVERSITY   (Belgium)

^c Faculty of Bioscience Engineering   (Belgium)

^d Phyto IT   (Belgium)

Author keywords

[No Author keywords available]

Indexed keywords

BATCH DATA PROCESSING; CROPS; DATA ACQUISITION; DATA HANDLING; LARGE DATASET; ONLINE SYSTEMS; PROCESS MONITORING; STRESSES;

BIOTECHNOLOGICAL APPLICATIONS; CONTINUOUS MONITORING; EARLY WARNING SYSTEM; INTELLIGENT HANDLING; ON-LINE DATA ACQUISITION; ON-LINE PROCESS MONITORING; PLANT STRESS MONITORING; SENSOR FAILURE DETECTION;

DAMAGE DETECTION;

LYCOPERSICON ESCULENTUM; MALUS X DOMESTICA;

EID: 63249113521     PISSN: 15375110     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.biosystemseng.2009.01.014     Document Type: Article

References (50)

1. Aguado D., Ferrer J., and Seco A. Multivariate SPC of a sequencing batch reactor for wastewater treatment. Chemometrics and Intelligent Laboratory Systems 85 (2007) 82-93
2. Bacci L., De Vincenzi M., Rapi B., Arca B., and Benincasa F. Two methods for the analysis of colorimetric components applied to plant stress monitoring. Computers and Electronics in Agriculture 19 (1998) 167-186
3. Bicciato S., Bagno A., Soldà M., Manfredini R., and Di Bello C. Fermentation diagnosis by multivariate statistical analysis. Applied Biochemistry and Biotechnology 102-103 (2002) 49-62
4. Chou C., and Verhaegen M. Subspace algorithm for the identification of multivariable dynamic errors-in-variables models. Automatica 33 (1997) 1857-1869
5. Daudet F.-A., Améglio T., Cochard H., Archilla O., and Lacointe A. Experimental analysis of the role of water and carbon in tree stem diameter variations. Journal of Experimental Botany 56 (2005) 135-144
6. Deslauriers A., Anfodillo T., Rossi S., and Carraro V. Using simple causal modeling to understand how water and temperature affect daily stem radial variation in trees. Tree Physiology 27 (2007) 1125-1136
7. Doltra J., Oncins J.A., Bonani J., and Cohen M. Evaluation of plant-based water status indicators in mature apple trees under field conditions. Irrigation Science 25 (2007) 351-359
8. Fereres E., and Goldhamer D.A. Suitability of stem diameter variations and water potential as indicators for irrigation scheduling in almond trees. Journal of Horticultural Science & Biotechnology 78 (2003) 139-144
9. Fransson M., and Folestad S. Real-time alignment of batch process data using COW for on-line process monitoring. Chemometrics and Intelligent Laboratory Systems 84 (2006) 56-61
10. Gallardo M., Thompson R.B., Valdez L.C., and Fernandez M.D. Use of stem diameter variations to detect plant water stress in tomato. Irrigation Science 24 (2006) 241-255
11. Génard M., Fishman S., Vercambre G., Huguet J.-G., Bussi C., Besset J., and Habib R. A biophysical analysis of stem and root diameter variations in woody plants. Plant Physiology 126 (2001) 188-202
12. Gins G., Espinosa J., Smets I.Y., Van Brempt W., and Van Impe J.F.M. Data alignment via dynamic time warping as a prerequisite for batch-end quality prediction. Lecture Notes in Artificial Intelligence 4065 (2006) 506-510
13. Goldhamer D.A., and Fereres E. Irrigation scheduling protocols using continuously recorded trunk diameter measurements. Irrigation Science 20 (2001) 115-125
14. Gurden S.P., Westerhuis J.A., Bro R., and Smilde A.K. A comparison of multiway regression and scaling methods. Chemometrics and Intelligent Laboratory Systems 59 (2001) 121-136
15. Herzog K.M., Häsler R., and Thum R. Diurnal changes in the radius of a subalpine Norway spruce stem: their relation to the sap flow and their use to estimate transpiration. Trees - Structure and Function 10 (1995) 94-101
16. Intrigliolo D.S., and Castel J.R. Continuous measurement of plant and soil water status for irrigation scheduling in plum. Irrigation Science 23 (2004) 93-102
17. Intrigliolo D.S., and Castel J.R. Usefulness of diurnal trunk shrinkage as a water stress indicator in plum trees. Tree Physiology 26 (2006) 303-311
18. Irvine J., and Grace J. Continuous measurements of water tensions in the xylem of trees based on the elastic properties of wood. Planta 202 (1997) 455-461
19. Jackson J., and Mudholkar G. Control procedures for residuals associated with Principal Component Analysis. Technometrics 21 (1979) 341-349
20. Johnson R., and Wichern D. Applied Multivariate Statistical Analysis. fifth edition (2002), Prentice-Hall Inc, Upple Saddle River, NJ, USA
21. Jones H.G. Irrigation scheduling: advantages and pitfalls of plant-based methods. Journal of Experimental Botany 55 (2004) 2427-2436
22. Kassidas A., MacGregor J.F., and Taylor P.A. Synchronization of batch trajectories using dynamic time warping. AIChE Journal 44 (1998) 864-875
23. Kozlowski T.T., and Winget C.H. Diurnal and seasonal variation in radii of tree stems. Ecology 45 (1964) 149-155
24. Lee D.S., and Vanrolleghem P.A. Monitoring of a sequencing batch reactor using adaptive multiblock principal component analysis. Biotechnology and Bioengineering 82 (2003) 489-497
25. Lee D.S., Park J.M., and Vanrolleghem P.A. Adaptive multiscale principal component analysis for on-line monitoring of a sequencing batch reactor. Journal of Biotechnology 116 (2005) 195-210
26. Lennox B., Montague G.A., Hiden H.G., Kornfeld G., and Goulding P.R. Process monitoring of an industrial fed-batch fermentation. Biotechnology and Bioengineering 74 (2001) 125-135
27. Lennox J., and Rosén C. Adaptive multiscale principal components analysis for online monitoring of wastewater treatment. Water Science and Technology 45 4-5 (2002) 227-235
28. Li W., Yue H., Valle-Cervantes S., and Qin S.J. Recursive PCA for adaptive process monitoring. Journal of Process Control 10 (2000) 471-486
29. Louwerse D.J., and Smilde A.K. Multivariate statistical process control of batch processes based on three-way models. Chemical Engineering Science 55 (2000) 1225-1235
30. Montgomery D. Introduction to Statistical Quality Control. Fifth ed. (2005), John Wiley & Sons, Inc, Hoboken, NJ, USA
31. Nomikos P., and MacGregor J.F. Monitoring batch process using multiway principal component analysis. AIChE Journal 40 (1994) 1361-1375
32. Naor A., and Cohen S. Sensitivity and variability of maximum trunk shrinkage, midday stem water potential, and transpiration rate in response to withholding irrigation from field-grown apple trees. Hortscience 38 (2003) 547-551
33. Ortuño M.F., Garcia-Orellana Y., Conejero W., Ruiz-Sanchez M.C., Alarcon J.J., and Torrecillas A. Stem and leaf water potentials, gas exchange, sap flow and trunk diameter fluctuations for detecting water stress in lemon trees. Trees - Structure and Function 20 (2006) 1-8
34. Ramaker H.-J., van Sprang E.N.M., Westerhuis J.A., and Smilde A.K. The effect of the size of the training set and number of principal components on the false alarm rate in statistical process monitoring. Chemometrics and Intelligent Laboratory Systems 73 (2004) 181-187
35. Ramsay J.O., and Silverman B.W. Functional Data Analysis. Second ed. (2005), Springer, New York, USA
36. Rosén C., and Lennox J.A. Multivariate and multiscale monitoring of wastewater treatment operation. Water Research 35 (2001) 3402-3410
37. Ruiz M L; Colomer J; Rubio M; Meléndez J; Colprim J (2004). Situation assessment of a sequencing batch reactor using multiblock MPCA and fuzzy classification. In: Proceedings of the 4th ECAI Workshop on Binding Environmental Sciences and Artificial Intelligence (BESAI), Valencia, Spain, August 22-23, 2004.
38. Sarolta A., and Kinley R.D. Multivariate statistical monitoring of batch processes: an industrial case study of fermentation supervision. Trends in Biotechnology 19 (2001) 53-62
39. Schulze E.D., Beck E., and Müller-Hohenstein K. Plant Ecology (2005), Springer Verlag, Berlin, Germany
40. Steppe K., De Pauw D.J.W., Lemeur R., and Vanrolleghem P.A. A mathematical model linking tree sap flow dynamics to daily stem diameter fluctuations and radial stem growth. Tree Physiology 26 (2006) 257-273
41. Tracy N.D., Young J.C., and Mason R.L. Multivariate control charts for individual observations. Journal of Quality Technology 24 (1992) 88-95
42. Ündey C., and Çinar A. Statistical monitoring of multistage, multiphase batch processes. IEEE Control Systems Magazine 22 (2002) 40-52
43. Venkatasubramanian V., Rengaswamy R., and Kavuri S.N. A review of process fault detection and diagnosis - Part III: Process history based methods. Computers and Chemical Engineering 27 (2003) 327-346
44. Villez K., Ruiz M., Sin G., Colomer J., Rosén C., and Vanrolleghem P.A. Combining multiway principal component analysis and clustering for efficient data mining of historical data sets of SBR processes. Water Science & Technology 57 10 (2007) 1659-1666
45. Wold S., Geladi P., Esbensen K., and Öhman J. Multi-way principal components and PLS-analysis. Journal of Chemometrics 1 (1987) 47-56
46. Wold S. Exponentially weighted moving principal component analysis and projections to latent structures. Chemometrics and Intelligent Laboratory Systems 23 (1994) 149-161
47. Yoo C.K., Villez K., Lee I.-B., Rosén C., and Vanrolleghem P.A. Multi-model statistical process monitoring and diagnosis of a sequencing batch reactor. Biotechnology and Bioengineering 96 (2006) 687-701
48. Yoo C.K., Villez K., Van Hulle S.W.H., and Vanrolleghem P.A. Enhanced process monitoring for wastewater treatment systems. Environmetrics 18 (2007) 1-16
49. Zweifel R., and Häsler R. Dynamics of water storage in mature subalpine Picea abies: temporal and spatial patterns of change in stem radius. Tree Physiology 21 (2001) 561-569
50. Zweifel R., Zimmermann L., and Newbery D.M. Modeling tree water deficit from microclimate: an approach to quantifying drought stress. Tree Physiology 25 (2005) 147-156