Association of spectral reflectance indices with plant growth and lint yield in upland cotton

Crop Science

Volumn 52, Issue 2, 2012, Pages 849-857

  Gutierrez, Mario ^a   Norton, Randall ^a   Thorp, Kelly R ^b   Wang, Guangyao ^a  

^a UNIVERSITY OF ARIZONA   (United States)

^b AGRICULTURAL RESEARCH SERVICE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

GOSSYPIUM HIRSUTUM;

EID: 84863137046     PISSN: 0011183X     EISSN: 14350653     Source Type: Journal    
DOI: 10.2135/cropsci2011.04.0222     Document Type: Article

References (41)

1. Ahmad, N. 2000. Integrated nutrition management in Pakistan: Status and opportunities. p. 18-37. In Proc. Symp. Integrated Plant Nutr. Manage., Islamabad, Pakistan. 8-10 Nov. 1999. National Fertilizer Development Centre, Islamabad, Pakistan.
2. Aparicio, N., D. Villegas, J. Casadesus, J.L. Araus, and C. Royo. 2000. Spectral vegetation indices as nondestructive tools for determining durum wheat yield. Agron. J. 92:83-91.
3. Araus, J.L., J. Casadesus, and J. Bort. 2001. Recent tools for the screening of physiological traits determining yield. p. 59-77. In M.P. Reynolds, J.I. Ortiz-Monasterio, and A. McNab. (ed.) Application of physiology in wheat breeding. CIMMYT, Mexico, D.F., Mexico.
4. Benedetti, R., and P. Rossini. 1993. On the use of NDVI profiles as a tool for agricultural statistics: The case study of wheat yield estimate and forecast in Emilia Romagna. Remote Sens. Environ. 45:311-326.
5. Breitenbeck, G.A., and D.J. Boquet. 1993. Effect of N fertilization on nutrient uptake by cotton. p. 1298-1300. In Proc. Beltwide Cotton Conf., New Orleans, LA. 10-14 Jan. 1993. National Cotton Council, Memphis, TN.
6. Bronson, K.F., T.T. Chua, J.D. Booker, J.W. Keeling, and R.J. Lascano. 2003. In-season nitrogen status sensing in irrigated cotton: II. Leaf nitrogen and biomass. Soil Sci. Soc. Am. J. 67:1439-1448.
7. Bronson, K.F., A. Malapati, P.C. Scharf, and R.L. Nichols. 2011. Canopy reflectance-based nitrogen management strategies for subsurface drip irrigated cotton in the Texas high plains. Agron. J. 103:422-430.
8. Chen, P., D. Haboudane, N. Tremblay, J. Wang, P. Vigneault, and B. Li. 2010. New spectral indicator assessing the efficiency of crop nitrogen treatment in corn and wheat. Remote Sens. Environ. 114:1987-1997.
9. Daughtry, C.S.T., C.L. Walthall, M.S. Kim, E. Brown de Colstoun, and J.E. McMurtrey. 2000. Estimating corn leaf chlorophyll concentration from leaf and canopy reflectance. Remote Sens. Environ. 74:229-239.
10. Eitel, J.U.H., D.S. Long, P.E. Gessler, and E.R. Hunt. 2008. Combined spectral index to improve ground-based estimates of nitrogen status in dryland wheat. Agron. J. 100:1694-1702.
11. Gitelson, A.A. 2004. Wide dynamic range vegetation index for remote quantification of biophysical characteristics of vegetation. J. Plant Physiol. 161:165-173.
12. Gitelson, A., and M.N. Merzlyak. 1996. Signature analysis of leaf reflectance spectra: Algorithm development for remote sensing of chlorophyll. J. Plant Physiol. 148:494-500.
13. Grismer, M.E. 2002. Regional cotton lint yield, ETc and water value in Arizona and California. Agric. Water Manage. 54:227-242.
14. Gupta, R.K. 1993. Comparative study of AVHRR ratio vegetation index and normalized difference vegetation index in district level agricultural monitoring. Int. J. Remote Sens. 14:55-73.
15. Gutierrez, M., M.P. Reynolds, W.R. Raun, M.L. Stone, and A.R. Klatt. 2010. Spectral water indices for assessing yield in elite bread wheat genotypes grown under well irrigated, water deficit stress, and high temperature conditions. Crop Sci. 50:197-214.
16. Guyot, G., F. Baret, and D.J. Major. 1988. High spectral resolution: Determination of spectral shifts between the red and the near infrared. Int. Arch. Photogramm. Remote Sens. 11:750-760.
17. Hatfield, J.L., A.A. Gitelson, J.S. Schepers, and C.L. Walthall. 2008. Application of spectral remote sensing for agronomic decisions. Agron. J. 100:117-131.
18. Huete, A., K. Didan, T. Miura, E.P. Rodriguez, X. Gao, and L.G. Ferreira. 2002. Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sens. Environ. 83:195-213.
19. Jordan, C.F. 1969. Derivation of leaf area index from quality of light on the forest floor. Ecology 50:663-666.
20. Li, H., R.J. Lascano, E.M. Barnes, J. Booker, L.T. Wilson, K.F. Bronson, and E. Segarra. 2001. Multispectral reflectance of cotton related to crop growth, soil water and texture, and site elevation. Agron. J. 93:1327-1337.
21. Ma, B.L., L.M. Dwyer, C. Costa, E.R. Cober, and M.J. Morrison. 2001. Early prediction of soybean yield from canopy reflectance measurements. Agron. J. 93:1227-1234.
22. Mistele, B., and U. Schmidhalter. 2010. Tractor-based quadrilateral spectral reflectance measurements to detect biomass and total aerial nitrogen in winter wheat. Agron. J. 102:499-506.
23. Muller, K., U. Bottcher, F. Meyer-Schatz, and H. Kage. 2008. Analysis of vegetation indices derived from hyperspectral reflection measurements for estimating crop canopy parameters of oilseed rape (Brassica napus L.). Biosystems Eng. 101:172-182.
24. Pinter, P.J., B.A. Kimball, J.R. Mauney, G.R. Hendrey, K.F. Lewin, and J. Nagy. 1994. Effects of free-air carbon dioxide enrichment on PAR absorption and conversion efficiency by cotton. Agric. For. Meteorol. 70:209-230.
25. Plant, R.E., D.S. Munk, B.R. Robert, R.L. Vargas, D.W. Rains, R.L. Travis, and R.B. Hutmacher. 2000. Relationships between remotely sensed reflectance data and cotton growth and yield. Trans. ASAE 43:535-546.
26. Raun, W.R., G.V. Johnson, M.L. Stone, J.B. Solie, E.V. Lukina, W.E. Thomason, and J.S. Schepers. 2001. In-season prediction of potential grain yield in winter wheat using canopy reflectance. Agron. J. 93:131-138.
27. Ryan, S.E., and L.S. Porth. 2007. A tutorial on the piecewise regression approach applied to bedload transport data. Gen. Tech. Rep. RMRS-GTR-189. U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, Fort Collins, CO.
28. Serrano, L., I. Filella, and J. Penuelas. 2000. Remote sensing of biomass and yield of winter wheat under different nitrogen supplies. Crop Sci. 40:723-731.
29. Shen, M., Y. Tang, J. Klein, P. Zhang, S. Gu, A. Shimono, and J. Chen. 2008. Estimation of aboveground biomass using in situ hyperspectral measurements in five major grassland ecosystems on the Tibetan Plateau. J. Plant Ecol. 1:247-257.
30. Solie, J.B., W.R. Raun, R.W. Whitney, M.L. Stone, and J.D. Ringer. 1996. Optical sensor based field element size and sensing strategy for nitrogen application. Trans. ASAE 39:1983-1992.
31. Tucker, C.J. 1979. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sens. Environ. 8:127-150.
32. Wanjura, D.F., and J.L. Hatfield. 1987. Sensitivity of spectral vegetative indices to crop biomass. Trans. ASAE 30:810-816.
33. Wiegand, C.L., A.J. Richardson, D.E. Escobar, and A.H. Gerbermann. 1991. Vegetation indices in crop assessments. Remote Sens. Environ. 35:105-119.
34. Wood, C.W., P.W. Tracy, D.W. Reeves, and K.L. Edmisten. 1992. Determination of cotton nitrogen status with a hand-held chlorophyll meter. J. Plant Nutr. 15:1435-1448.
35. Xue, L., W. Cao, W. Luo, and Y. Zhu. 2005. Canopy spectral reflectance characteristics of rice with different cultural practices and their fuzzy cluster analysis. Rice Sci. 12:57-62.
36. Zarco-Tejada, P.J., S.L. Ustin, and M.L. Whiting. 2005. Temporal and spatial relationships between within-field yield variability in cotton and high-spatial hyperspectral remote sensing imagery. Agron. J. 97:641-653.
37. Zhao, D., and D.M. Oosterhuis. 2000. Nitrogen application effect on leaf photosynthesis, nonstructural carbohydrate concentrations and yield of field-grown cotton. p. 69-71 In D.M. Oosterhuis (ed.) Proc. 2000 Arkansas Cotton Res., Phillips County Community College, Helena, AR. 15 Feb. 2000. Arkansas Agricultural Experiment Station, Fayetteville, AR.
38. Zhao, D., K.R. Reddy, V.G. Kakani, J.J. Read, and S. Koti. 2005. Selection of optimum reflectance ratios for estimating leaf nitrogen and chlorophyll concentrations of field-grown cotton. Agron. J. 97:89-98.
39. Zhao, D., K.R. Reddy, V.G. Kakani, J.J. Read, and S. Koti. 2007. Canopy reflectance in cotton for growth assessment and lint yield prediction. Eur. J. Agron. 26:335-344.
40. Zhao, D., K.R. Reddy, V.G. Kakani, and J.J. Read. 2010. Remotesensing algorithms for estimating nitrogen uptake and nitrogen- use efficiency in cotton. Acta Agric. Scand. Sec. B: Soil Plant Sci. 60:500-509.
41. Zhu, Y., X. Yao, Y.C. Tian, X.J. Liu, and W.X. Cao. 2007. Analysis of common canopy vegetation indices for indicating leaf nitrogen accumulations in wheat and rice. Int. J. Appl. Earth Obs. Geoinf. 10:1-10.