Plant Response-Based Sensing for Control Strategies in Sustainable Greenhouse Production

Journal of Agricultural Meteorology

Volumn 61, Issue 1, 2005, Pages 15-22

  Kacira, Murat ^a   Sase, Sadanori ^b   Okushima, Limi ^b   Ling, Peter P ^c  

^a HARRAN UNIVERSITY   (Turkey)

^b NATIONAL INSTITUTE FOR RURAL ENGINEERING   (Japan)

^c OHIO STATE UNIVERSITY   (United States)

Author keywords

Automatic control; Greenhouse; Plant monitoring; Speaking plant; Sustainable

Indexed keywords

EID: 84863692861     PISSN: 00218588     EISSN: 18810136     Source Type: Journal    
DOI: 10.2480/agrmet.61.15     Document Type: Article

References (44)

1. Bailey, B. J., 1985: Microclimate, physical processes and greenhouse technology. Acta Hortic, 174, 35-42.
2. Baker, N. R. and Ort, D. R., 1992: Light and crop photosynthetic performance. In Crop photosynthesis: Spatial and temporal determinants (eds. by Baker, N. R. and Thomas, H.). Elsevier Science Publishers, London, pp. 289-312.
3. Boulard, T., 2004: Modeling the distributed greenhouse climate at crop and leaf level. In Proc. of International Workshop on Environmental Control and Structural Design for Protected Cultivation, June 14-16, Suwon, Korea, pp. 44-53.
4. Buschmann, C.,Schweiger, J.,Lichtenthaler, H. K. and Richter, P., 1996: Application of the Karls-ruhe CCD-OMA LIDAR-fluoro sensor in stress detection of plants. J. Plant Physiol., 148, 548-554.
5. Chappelle, E. W., Wood, F. M., Jr., McMurtrey, J. E. and Newcomb, W. W., 1984: Laser-induced fluorescence of green plants: I. A technique for the remote detection of plant stress and species differentiation. Appl. Optics, 23 (1), 134-138.
6. Clawson, K. L., Jackson, R. D. and Pinter, P. J., 1989: Evaluating plant water stress with canopy temperature differences. Agron. J., 81, 858-863.
7. Durairaj, C. D., Okushima, L. and Sase, S., 2000: Asimulated investigation to measure acoustic emissions caused byroot growth. Trans. ASAE, 43 (6), 1905-1910.
8. Gardner, B. R., Blad, B. L., Garrity, D. P. and Watts, D. G., 1981: Relationships between crop temperature, grain yield, evapotranspiration, and phenological development in two hybrids of moisture stressed sorghum. Irrigation Sci., 2, 213-224.
9. Giacomelli, G. A., Ling, P. P. and Kole, J., 1998: Determining nutrient stress in lettuce plants with machine vision technology. HortTechnology, 8 (3), 361-365.
10. Graef, S., Claupein, W. and Schubert, S., 2004: Identification of nutrient deficiencies in corn using reflectance measurements. In Digital imaging and spectral techniques: Applications to precision agriculture and crop physiology. ASA Special Publications, American Societyof Agronomy, Madison, Vol. 66, pp. 165-175.
11. Hashimoto, Y. and Nonami, H., 1992: Measurement and control in transplant production systems. In Transplant production systems (eds. byKurata, K. and Kozai, T.). Kluwer Academic Publishers, Dordrecht, pp. 117-136.
12. Hattendorf, M. J., Evans, D. W. and Peaden, R. N., 1990: Canopytemperature and stomatal conductance of water-stressed dormant and nondormant alfalfa types. Agron. J., 82, 873-877.
13. Idso, S. B., Jackson, R. D., Pinter, P. J., Reginato, R. J. and Hatfield, J. L., 1981: Normalizing the stress degree dayparameter for environmental variability. Agric. Meteorol., 24, 45-55.
14. Idso, S. B., Jackson, R. D. and Reginato, R. J., 1977: Remote sensing of crop yields. Science, 196, 19-25.
15. Jackson, R. D., Idso, S. B., Reginato, R. J. and Pinter, P. J., 1981: Canopytemperature as a crop water stress indicator. Water Resour. Res., 11 (4), 1133-1138.
16. Jones, H. G., 1999a: Use of infrared thermometry for estimation of stomatal conductance in irrigation scheduling. Agric. For. Meteorol., 95, 135-149.
17. Jones, H. G., 1999b: Use of thermographyfor quantitative studies of spatial and temporal variation of stomatal conductance over leaf surfaces. Plant Cell Environ., 22, 1043-1055.
18. Jones, H. G. and Leinonen, I., 2003: Thermal imaging for the studyof plant water relations. J. Agric. Meteorol., 59 (3), 205-217.
19. Jones, H. G., Aikman, D. A. and McBurney, T., 1997: Improvements to infra-red thermometryfor irrigation scheduling. Acta Hortic., 449, 259-266.
20. Jones, H. G., Stoll, M., Santos, T., de Sousa, C., Chaves, M. M. and Grant, O. M., 2002: Use of infrared thermographyfor monitoring of stomatal closure in the field: application to grapevine. J. Exp. Bot., 53, 2249-2260.
21. Kacira, M., Ling, P. P. and Short, T. H., 2002a: Establishing crop water stress index (CWSI) threshold values for earlyand non-contact detection of plant water stress. Trans. ASAE, 45 (3), 775-780.
22. Kacira, M., Ling, P. P. and Short, T. H., 2002b: Machine vision extracted plant movement for earlydetection of plant water stress. Trans. ASAE, 45 (4), 1147-1153.
23. Kurata, K. and Yan, J., 1996: Water stress estimation of tomato canopybased on machine vision. Acta Hortic., 440, 389-394.
24. Ling, P. P., Giacomelli, G. A. and Rusell, T. P., 1995: Monitoring of plant development in controlled environment with machine vision. Adv. Space Res., 18 (4-5), 101-112.
25. McDonald, M. B., Fujimura, K., Sako, Y., Evans, A. F. and Bennett, M. A., 2004: Computer imaging to improve seed qualitydeterminations. In Digital Imaging and Spectral Techniques: Applications to Precision Agriculture and Crop Physiology. ASA Special Publications, American Societyof Agronomy, Madison, Vol. 66, pp. 15-28.
26. Murase, H., 2002: Precision technologies for protected agriculture. Presented at the 2002 ASAE Annual International/CIGR XVth World Congress, July 28-31, Chicago, USA. ASAE Paper No. 023034.
27. Norikane, J. H. and Kurata, K., 2001: Water stress detection bymonitoring fluorescence of plants under ambient light. Trans. ASAE, 44 (6), 1915-1922.
28. Nyakwende, E., Paull, C. J. and Atherton, J. G., 1997: Non-destructive determination of leaf area in tomato plants using image processing. J. Hortic. Sci., 12 (2), 255-262.
29. Okushima, L., Shimojo, M., Higo, Y., Ohtani, T. and Sase, S., 1996: Possibilityof root growth measurement underground byacoustic emission sensor. Presented at the Progress in Acoustic Emission VIII, The Japanese Soc. for NDI.
30. Oosterhuis, D. M., Walker, S. and Eastham, J., 1985: Soybean leaflet movements as an indicator of crop water stress. Crop Sci., 25, 1101-1106.
31. O'Toole, J. C. and Hatfield, J. L., 1983:Effect of wind on the crop water stress index derived by infrared thermometry. Agron. J., 15, 811-817.
32. O'Toole, J. C., Turner, N. C., Namuco, O. P., Dingkuhn, M. and Gomez, K. A., 1984: Comparison of some water stress measurement methods. Crop Set, 24, 1121-1128.
33. Pinter, P. J., Fry, K. E., Guinn, G. and Mauney, J. R., 1983: Infrared thermometry: A remote sensing technique for predicting yield in water-stressed cotton. Agrie. Water Manag., 6, 385-395.
34. Qiu, G. Y., Miyamoto, K., Sase, S. and Okushima, L., 2000: Detection of crop transpiration and water stress by temperature-related approach under field and greenhouse conditions. Jpn. Agrie. Res. Quart., 34 (1), 29-37.
35. Revollon, P., Chasseriaux, G., Riviere, L. M. and Gardet, R., 1998: The use of image processing for tracking the morphological modification of For-sythia following an interruption of watering. In Proe. of International Conferenee on Agrieultural Engineering, AgEng OSLO98, August 24-27, Oslo, Norway, pp. 872-873.
36. Sase, S. and Ling, P. P., 1996: Quantification of lighting spectral quality effect on lettuce development using machine vision. Aeta Hortie., 440, 434-440.
37. Sase, S., Nara, M., Okuya, T. and Sueyoshi, K., 1992: Determining seedling characteristics using computer vision and its applications to an expert system for grading seedlings. Aeta Hortie., 319, 683-688.
38. Seginer, I., Elster, R. T., Goodrum, J. W. and Rieger, M. W., 1992: Plant wilt detection by computer-vision tracking of leaf tips. Trans. ASAE, 35 (5), 1563-1567.
39. Shifeng, Y., Pei, L., Okushima, L., Sase, S. and Qiu, G. Y., 2003: Automatic and precise irrigation system based on estimation of water stress in tomato. In Proe. of the Conferenee on Total Maximum Daily Load (TMDL) Environmental Regulations-II, 8-12 November 2003, Albuquerque, New Mexico, USA. ASAE Publication No. 701P 1503.
40. Stanghellini, C., De Lorenzi, F., Bosma, A. H. and Werkhoven, C., 1992: Early detection of water stress in sub-humid climates. Report 92-9, IMAG-DLO, Wageningen, The Netherlands.
41. Takakura, T., Kozai, T., Tachibana, K. and Jordan, K. A., 1974: Direct digital control of plant growth. I. Design and operation of the system. Trans. ASAE, 17, 1150-1154.
42. Udink Ten Cate, A. J., Bot, G. P. A. and van Dixhoorn, J. J., 1978: Computer control of greenhouse climates. Aeta Hortie., 87, 265-272.
43. Wanjura, D. F. and Upchurch, D. R., 1998: Evaluation of analytical methods for daily estimation of crop water stress. ASAE Paper No. 982122. ASAE, St. Joseph, Michigan.
44. Yang, Y. and Ling, P. P., 2003: Improved model inversion procedure for plant water status assessment under artificial lighting using PROSPECT + SAIL model. Presented at the 2003 ASAE Annual International Meeting, July 27-30, Las Vegas, USA. ASAE Paper No. 033118.