Spatial portability of numerical models of leaf wetness duration based on empirical approaches

Agricultural and Forest Meteorology

Volumn 150, Issue 7-8, 2010, Pages 871-880

  Kim, Kwang Soo ^a   Taylor, S Elwynn ^b   Gleason, Mark L ^b   Nutter, Forrest W ^b   Coop, Leonard B ^c   Pfender, William F ^d   Seem, Robert C ^e   Sentelhas, Paulo C ^f   Gillespie, Terry J ^g   Dalla Marta, Anna ^h   Orlandini, Simone ^h  

^a THE NEW ZEALAND INSTITUTE FOR PLANT AND FOOD RESEARCH LIMITED   (New Zealand)

^b IOWA STATE UNIVERSITY   (United States)

^c OREGON STATE UNIVERSITY   (United States)

^d U S DEPARTMENT OF AGRICULTURE   (United States)

^e New York State Agricultural Experiment Station   (United States)

^f UNIVERSITY OF SÃO PAULO   (Brazil)

^g UNIVERSITY OF GUELPH   (Canada)

^h UNIVERSITY OF FLORENCE   (Italy)

Author keywords

Empirical model; Fuzzy logic; Leaf wetness duration; RH; Surface wetness

Indexed keywords

AGRICULTURAL APPLICATION; CLIMATE CONDITIONS; DATA ACQUISITION; EMPIRICAL ANALYSIS; FUZZY MATHEMATICS; LEAF; MODEL VALIDATION; NUMERICAL MODEL; SENSOR; SPATIAL DISTRIBUTION; WEATHER; WETTABILITY;

EID: 77954815791     PISSN: 01681923     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.agrformet.2010.02.006     Document Type: Article

References (36)

1. Basist A., Grody N.C., Peterson T.C., Williams C.N. Using the special sensor microwave/imager to monitor land surface temperatures, wetness, and snow cover. J. Appl. Meteorol. 1998, 37:888-911.
2. Batzer J.C., Gleason M.L., Taylor S.E., Koehler K.J., Monteiro J.E.B.A. Spatial heterogeneity of leaf wetness duration in apple trees and its influence on performance of a warning system for sooty blotch and flyspeck. Plant Dis. 2008, 92:164-170.
3. Breuer N.E., Cabrera V.E., Ingram K.T., Broad K., Hildebrand P.E. AgClimate: a case study in participatory decision support system development. Climatic Change 2008, 87:385-403.
4. Crowe J.M., Coakley S.M., Emge R.G. Forecasting dew duration at Pendleton, Oregon using simple weather observations. J. Appl. Meteorol. 1978, 17:1482-1487.
5. Dalla Marta A., Magarey R.D., Orlandini S. Modelling leaf wetness duration and downy mildew simulation on grapevine in Italy. Agric. Forest Meteorol. 2005, 132:84-95.
6. Davis D.R., Hughes J.E. A new approach to recording the wetting parameter by the use of electrical resistance sensors. Plant Dis. Rep. 1970, 54:474-479.
7. Dietterich T.G. An experimental comparison of three methods for constructing ensembles of decision trees: bagging, boosting, and randomization. Mach. Learn. 2000, 40:139-157.
8. Duttweiler K.B., Gleason M.L., Dixon P.M., Sutton T.B., McManus P.S., Monteiro J.E.B.A. Adaptation of an apple sooty blotch and flyspeck warning system for the Upper Midwest United States. Plant Dis. 2008, 92:1215-1222.
9. Francl L.J., Panigrahi S. Artificial neural network models of wheat leaf wetness. Agric. Forest Meteorol. 1997, 88:57-65.
10. Gleason M.L., Taylor S.E., Loughin T.M., Koehler K.J. Development and validation of an empirical model to estimate the duration of dew periods. Plant Dis. 1994, 78:1011-1016.
11. Hornbuckle B.K., England A.W., Anderson M.C., Viner B.J. The effect of free water in a maze canopy on microwave emission at 1.4GHz. Agric. Forest Meteorol. 2006, 138:180-191.
12. Huber L., Gillespie T.J. Modeling leaf wetness in relation to plant disease epidemiology. Ann. Rev. Phytopathol. 1992, 30:553-577.
13. Idso S.B., Jackson R.D. Thermal radiation from the atmosphere. J. Geophys. Res. 1969, 74:5397-5403.
14. Kim K.S., Taylor S.E., Gleason M.L. Development of a leaf wetness model using a fuzzy logic system. Agric. Forest Meteorol. 2004, 127:53-64.
15. Kim K.S., Taylor S.E., Gleason M.L., Koehler K.J. Model to enhance site-specific estimation of leaf wetness duration. Plant Dis. 2002, 86:179-185.
16. Kim K.S., Taylor S.E., Gleason M.L., Villalobos R., Arauz L.F. Estimation of leaf wetness duration using empirical models in northwestern Costa Rica. Agric. Forest Meteorol. 2005, 129:53-67.
17. Klemm O., Milford C., Sutton M.A., Spindler G., van Putten E. A climatology of leaf surface wetness. Theor. Appl. Climatol. 2002, 71:107-117.
18. Klir G.J., Yuan B. Fuzzy Sets and Fuzzy Logic: Theory and Applications 1995, Prentice Hall PTR, Upper Saddle River, NJ.
19. Kruit R.J.W., Jacobs A.F.G., Holtslag A.A.M. Measurements and estimates of leaf wetness over agricultural grassland for dry deposition modelling of trace gases. Atmos. Environ. 2008, 42:5304-5316.
20. Lau Y.F., Gleason M.L., Zriba N., Taylor S.E., Hinz P.N. Effects of coating, deployment angle, and compass orientation on performance of electronic wetness sensors during dew periods. Plant Dis. 2000, 84:192-197.
21. Madeira A.C., Kim K.S., Taylor S.E., Gleason M.L. A simple cloud-based energy balance model to estimate dew. Agric. Forest Meteorol. 2002, 111:55-63.
22. Magarey R.D., Seem R.C., Weiss A., Gillespie T., Huber L. Estimating surface wetness on plants. Micrometeorology in Agricultural Systems 2004, 199-226. Am. Soc. Agronomy, Crop Sci. Soc. Am., Soil Sci. Soc. Am., Madison, WI, 584 pp. J.L. Hatfield, J.M. Baker (Eds.).
23. Magarey, R.D., 1999. A theoretical standard for surface wetness estimation. Ph.D. Diss. Cornell University, Ithaca, NY.
24. Magarey R.D., Russo J.M., Seem R.C. Simulation of surface wetness with a water-budget and energy balance approach. Agric. Forest Meteorol. 2006, 139:373-381.
25. Nelles O. Nonlinear System Identification: From Classical Approaches to Neural Networks and Fuzzy Models 2000, Springer, New York, NY.
26. Pedro M.J., Gillespie T.J. Estimating dew duration. I. Utilizing micrometeorological data. Agric. Forest Meteorol. 1982, 25:283-296.
27. Schaefer J.T. The critical success index as an indicator of warning skill. Weather Forecast. 1990, 5:570-575.
28. Sentelhas P.C., Dalla Marta A., Orlandini S., Santos E.A., Gillespie T.J., Gleason M.L. Suitability of relative humidity as an estimator of leaf wetness duration. Agric. Forest Meteorol. 2008, 148:392-400.
29. Sentelhas P.C., Gillespie T.J. Estimating hourly net radiation for leaf wetness duration modelling using the Penman-Monteith equation. Theor. Appl. Climatol. 2008, 91:205-215.
30. Sentelhas P.C., Gillespie T.J., Batzer J.C., Gleason M.L., Monteiro J.E., Pezzopane J.R., Pedro M.J. Spatial variability of leaf wetness duration in different crop canopies. Int. J. Biometeorol. 2005, 49:363-370.
31. Sentelhas P.C., Gillespie T.J., Gleason M.L., Monteiro J.E., Pezzopane J.R.M., Pedro M.J. Evaluation of a Penman-Monteith approach to provide " reference" and crop canopy leaf wetness duration estimates. Agric. Forest Meteorol. 2006, 141:105-117.
32. Sentelhas P.C., Gillespie T.J., Gleason M.L., Monteiro J.E., Helland S.T. Operational exposure of leaf wetness sensors. Agric. Forest Meteorol. 2004, 126:59-72.
33. Sentelhas P.C., Monteiro J.E.B.A., Gillespie T.J. Electronic leaf wetness duration sensor: why it should be painted. Int. J. Biometeorol. 2004, 48:202-205.
34. Slingo J.M. The development and verification of a cloud prediction scheme for the ECMWF model. Quart. J. Roy. Meteorol. Soc. 1987, 113:899-927.
35. Sutton J.C., Gillespie T.J., Hildebrand P.D. Monitoring weather factors in relation to plant disease. Plant Dis. 1984, 68:78-84.
36. Willmott C.J., Ackleson S.G., Davis R.E., Feddema J.J., Klink K.M., Legates D.R., O'Donnell J., Rowe C.M. Statistics for the evaluation and comparison of models. J. Geophys. Res. 1985, 90:8995-9005.