Characteristics of active spectral sensor for plant sensing

Transactions of the ASABE

Volumn 55, Issue 1, 2012, Pages 293-301

  Kim, Y ^a   Glenn, D M ^b   Park, J ^a   Ngugi, H K ^c   Lehman, B L ^c  

^a Purdue University   (United States)

^b APPALACHIAN FRUIT RESEARCH STATION   (United States)

^c PENNSYLVANIA STATE UNIVERSITY   (United States)

Author keywords

Illumination; Infrared radiation; Precision agriculture; Sensors; Spectral analysis; Vegetation indices

Indexed keywords

ACTIVE SENSOR; AMBIENT ILLUMINATION; CANOPY COVERAGE; ILLUMINATION CONDITIONS; ILLUMINATION EFFECT; MEASUREMENT ACCURACY; PLANT FOLIAGE; PLANT STRESS; PRECISION AGRICULTURE; REFLECTED LIGHT; SENSOR PERFORMANCE; SENSOR RESPONSE; SOLAR ANGLE; SPECTRAL SENSORS; SPECTRAL SIGNATURE; STAND-OFF DISTANCE (SOD); TARGET SURFACE; VEGETATION INDEX;

FORESTRY; INFRARED RADIATION; LIGHTING; SPECTRUM ANALYSIS; SUN;

SENSORS;

ACCURACY ASSESSMENT; CANOPY ARCHITECTURE; ENVIRONMENTAL STRESS; EXPERIMENTAL STUDY; FOLIAGE; INFRARED RADIATION; NDVI; PLANT COMMUNITY; PRECISION AGRICULTURE; RELATIVE HUMIDITY; SENSOR; SOLAR RADIATION; SPECTRAL ANALYSIS;

EID: 84859786475     PISSN: 21510032     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (31)

1. Beck, J., and T. Vyse. 1995. Structure and method usable for differentiating a plant from soil in a field. U.S. Patent No. 5,389,781.
2. Bravo, C., D. Moshou, J. West, A. McCartney, and H. Ramon. 2003. Early disease detection in wheat fields using spectral reflectance. Biosystems Eng. 84(2): 137-145. (Pubitemid 36247146)
3. Bronson, K. F., J. D. Booker, W. J. Keeling, R. K. Boman, T. A. Wheeler, R. J. Lascano, and R. L. Nichols. 2005. Cotton canopy reflectance at landscape scale as affected by nitrogen fertilization. Agron. J. 97(3): 654-660.
4. Flynn, S. E., C. T. Dougherty, and O. Wendroth. 2008. Assessment of pasture biomass with the normalized difference vegetation index from active ground-based sensors. Agron. J. 100(1): 114-121.
5. Freeman, K. W., K. Girma, D. B. Arnall, R. W. Mullen, K. L. Martin, R. K. Teal, and W. R. Raun. 2007. By-plant prediction of corn forage biomass and nitrogen uptake at various growth stages using remote sensing and plant height. Agron. J. 99(2): 530-536. (Pubitemid 46761164)
6. Jones, C. L., P. R. Weckler, N. O. Maness, R. Jayasekara, M. L. Stone, and D. Chrz. 2007. Remote sensing to estimate chlorophyll concentration in spinach using multi-spectral plant reflectance. Trans. ASABE 50(6): 2267-2273. (Pubitemid 351157823)
7. Kim, Y., and J. F. Reid. 2006. Modeling and calibration of a multi-spectral imaging sensor for in-field crop nitrogen assessment. Applied Eng. in Agric. 22(6): 935-941. (Pubitemid 46157849)
8. Kim, Y., and J. F. Reid. 2007. Bidirectional effect on a spectral image sensor for in-field crop reflectance assessment. Intl. J. Remote Sensing 28(21): 4913-4926. (Pubitemid 351444925)
9. Lu, R., and D. Ariana. 2002. A near-infrared sensing technique for measuring internal quality of apple fruit. Applied Eng. in Agric. 18(5): 585-590.
10. Martin, K. L., K. Girma, K. W. Freeman, R. K. Teal, B. Tubafia, D. B. Arnall, B. Chung, O. Walsh, J. B. Solie, M .J. Stone, and W. R. Raun. 2007. Expression of variability in corn as influenced by growth stage using optical sensor measurements. Agron. J. 99(2): 384-389. (Pubitemid 46761146)
11. McMurtrey, J. E., E. W. Chappelle, M. S. Kim, J. J. Meisinger, and L. A. Corp. 1994. Distinguishing nitrogen fertilization levels in field corn (Zea mays L.) with actively induced fluorescence and passive reflectance measurements. Remote Sensing Environ. 47(1): 36-44.
12. Morra, M. J., M. H. Hall, and L. L. Freeborn. 1991. Carbon and nitrogen analysis of soil fractions using near-infrared reflectance spectroscopy. SSSA J. 55(1): 288-291.
13. NTech. 2007. Model 505 GreenSeeker Hand-Held Optical Sensor Unit: Operating Manual. Ukiah, Cal.: NTech Industries, Inc.
14. Oliveira, L. F. 2008. Reflectance sensors to predict mid-season nitrogen need of cotton. MS thesis. Columbia, Mo.: University of Missouri-Columbia, Department of Agronomy. Available at: https://mospace.umsystem.edu/xmlui/handle/ 10355/5775. Accessed 18 October 2011.
15. OSU. 2003. GreenSeeker sensor contamination, Spring 2003. Stillwater, Okla.: Oklahoma State University, Nitrogen Use Efficiency. Available at: http://nue.okstate.edu/Sensor- Contamination.htm. Accessed 27 April 2010.
16. Perez-Priego, O., P. J. Zarco-Tejada, J. R. Miller, G. Sepulcre-Canto, and E. Fereres. 2005. Detection of water stress in orchard trees with a high-resolution spectrometer through chlorophyll fluorescence in-filling of the O2-A band. IEEE Trans. Geosci. and Remote Sensing 43(12): 2860-2869.
17. Ranson, K. J., C. S. T. Daughtry, L. L. Biehl, and M. E. Bauer. 1985. Sun-view angle effects on reflectance factors of corn canopies. Remote Sensing Environ. 18(2): 147-161.
18. Raun, W. R., J. B. Solie, G. V. Johnson, M. L. Stone, R. W. Mullen, K. W. Freeman, W. E. Thomason, and E. V. Lukina. 2002. Improving nitrogen use efficiency in cereal grain production with optical sensing and variable-rate application. Agron. J. 94(4): 815-820. (Pubitemid 34812747)
19. Schepers, J. S. 2008. Active sensor tidbits. Unpublished article. Lincoln, Neb.: USDA-ARS.
20. Solie, J. B. 2004. GreenSeeker sensor/applicator for variable rate application of nitrogen fertilizer. In Proc. 7th Intl. Conf. on Precision Agriculture. Madison, Wisc.: ASA/CSSA/SSSA.
21. Solie, J. B., M. L. Stone, W. R. Raun, G. V. Johnson, K. Freeman, R. Mullen, D. E. Needham, S. Reed, and C. N. Washmon. 2002. Real-time sensing and N fertilization with a field scale GreenSeeker applicator. In Proc. 6th Intl. Conf. on Precision Agriculture. Madison, Wisc.: ASA/CSSA/SSSA.
22. Sonmez, N. K., Y. Emekli, M. Sari, and R. Bastug. 2008. Relationship between spectral reflectance and water stress conditions of Bermuda grass (Cynodon dactylon L.). New Zealand J. Agric. Res. 51(3): 223-263.
23. Stone, M. L., J. B. Solie, W. R. Raun, R. W. Whitney, S. L. Taylor, and J. D. Ringer. 1996a. Use of spectral radiance for correcting in-season fertilizer nitrogen deficiencies in winter wheat. Trans. ASABE 39(5): 1623-1631. (Pubitemid 27005836)
24. Stone, M. L., J. B. Solie, R. W. Whitney, W. R. Raun, and H. L. Lees. 1996b. Sensors for detection of nitrogen in winter wheat. SAE Paper No. 96-1757. Warrendale, Pa.: Society of Automotive Engineering.
25. Stone, M. L., N. Duane, J. B. Solie, W. R. Raun, and G. V. Johnson. 2003. Optical spectral reflectance sensor and controller. U.S. Patent No. 6,596,996.
26. Suarez, L., P. J. Zarco-Tejada, G. Sepulcre-Canto, O. Perez-Priego, J. R. Miler, J. C. Jimenez-Munoz, and J. Sobrino. 2008. Assessing canopy PRI for water stress detection with diurnal airborne imagery. Remote Sensing Environ. 112(2): 560-575.
27. Suarez, L., P. J. Zarco-Tejada, J. A. J. Berni, V. Genzlez-Dugo, and E. Fereres. 2009. Modeling PRI for water stress detection using radiative transfer models. Remote Sensing Environ. 113(4): 730-744.
28. Sui, R., J. B. Wilkerson, W. E. Hart, L. R. Wilhelm, and D. D. Howard. 2005. Multi-spectral sensor for detection of nitrogen status in cotton. Applied Eng. in Agric. 21(2): 167-172. (Pubitemid 40573696)
29. Tumbo, S. D., D. G. Wagner, and P. H. Heinemann. 2002. Hyperspectral characteristics of corn plants under different chlorophyll levels. Trans. ASABE 45(3): 815-823. (Pubitemid 36108526)
30. West, J. S., C. Bravo, R. Oberti, D. Lemaire, D. Moshou, and H. A. McCartney. 2003. The potential of optical canopy measurement for targeted control of field crop diseases. Annual Rev. Phytopathol. 41: 593-614. (Pubitemid 37399694)
31. Yang, C., J. H. Everitt, and J. M. Bradford. 2006. Evaluating high-resolution QuickBird satellite imagery for estimating cotton yield. Trans. ASABE 49(5): 1599-1606. (Pubitemid 44953139)