Estimating harvest index of winter wheat from canopy spectral reflectance information

Journal of Food, Agriculture and Environment

Volumn 9, Issue 3-4, 2011, Pages 420-425

  Li, Heli ^a,b   Luo, Yi ^a   Xue, Xiaoping ^c   Zhao, Yujin ^c   Zhao, Hong ^c   Li, Feng ^c  

^a INSTITUTE OF GEOGRAPHIC SCIENCES AND NATURAL RESOURCES RESEARCH   (China)

^b UNIVERSITY OF CHINESE ACADEMY OF SCIENCES   (China)

^c Shandong Meteorological Bureau   (China)

Author keywords

Harvest index; Spectral reflectance; Vegetation indices; Winter wheat

Indexed keywords

NITROGEN;

AGRICULTURAL PARAMETERS; ARTICLE; CANOPY; DIFFERENCE VEGETATION INDEX; ENHANCED VEGETATION INDEX; FEASIBILITY STUDY; FLOWERING; GREEN CHLOROPHYLL INDEX; HARVEST INDEX; MODIFIED SOIL ADJUSTED VEGETATION INDEX; NONHUMAN; NORMALIZED DIFFERENCE VEGETATION INDEX; PLANT GROWTH; RATIO VEGETATION INDEX; REFLECTOMETRY; RENORMALIZED DIFFERENCE VEGETATION INDEX; SOIL ADJUSTED VEGETATION INDEX; TRANSFORMED VEGETATION INDEX; WINTER WHEAT;

TRITICUM AESTIVUM;

EID: 80655140566     PISSN: 14590255     EISSN: 14590263     Source Type: Journal    
DOI: None     Document Type: Article

References (33)

1. Becker-Reshef, I., Vermote, E., Lindeman, M. and Justice, C. 2010. A generalized regression-based model for forecasting winter wheat yields in Kansas and Ukraine using MODIS data. Remote Sens. Environ. 114:1312-1323.
2. Donald, C. M. and Hamblin, J. 1976. The biological yield and harvest index of cereals as agronomic and plant breeding criteria. Adv. Agron. 28:361-405.
3. Sinclair, T. R. 1998. Historical changes in harvest index and crop nitrogen accumulation. Crop Sci. 38:638-643.
4. Lobell, D. B., Asner, G. P., Ortiz-Monasterio, J. I. and Benning, T. L. 2003. Remote sensing of regional crop production in the Yaqui Valley, Mexico: Estimates and uncertainties. Agr. Ecosyst. Environ. 94:205-220.
5. Stöckle, C. O., Donatelli, M. and Nelson, R. 2003. CropSyst, a cropping systems simulation model. Eur. J. Agron. 18:289-307.
6. Pirmoradian, N. and Sepaskhah, A. R. 2006. A very simple model for yield prediction of rice under different water and nitrogen applications. Biosyst. Eng. 93:25-34.
7. Sharma, R. C., Smith, E. L. and McNew, R. W. 1987. Stability of harvest index and grain yield in winter wheat. Crop Sci. 27:104-108.
8. Moriondo, M., Maselli, F. and Bindi, M. 2007. A simple model of regional wheat yield based on NDVI data. Eur. J. Agron. 26:266-274.
9. Sadras, V. O. and Connor, D. J. 1991. Physiological basis of the response of harvest index to the fraction of water transpired after anthesis: A simple model to estimate harvest index for determinate species. Field Crops Res. 26:227-239.
10. Kemanian, A. R., Stockle, C. O., Huggins D. R. and Viega, L. M. 2007. A simple method to estimate harvest index in grain crops. Field Crops Res. 103:208-216.
11. Bastiaanssen, W. G. M. and Ali, S. 2003. A new crop yield forecasting model based on satellite measurements applied across the Indus basin, Pakistan. Agr. Ecosyst. Environ. 94:321-340.
12. Duchemin, B., Maisongrande, P., Boulet, G. and Benhadj, I. 2008. A simple algorithm for yield estimates: Evaluation for semi-arid irrigated winter wheat monitored with green leaf area index. Environ. Modell. Softw. 23:876-892.
13. Richards, R. A. and Townley-Smith, T. F. 1987. Variation in leaf area development and its effect on water use, yield and harvest index of droughted wheat. Aust. J. Agr. Res. 38:983-992.
14. Er-Raki, S., Chehbouni, A., Guemouria, N., Duchemin, B., Ezzahar, J. and Hadria, R. 2007. Combining FAO-56 model and ground-based remote sensing to estimate water consumptions of wheat crops in a semi-arid region. Agr. Water Manage. 87:41-54.
15. Ines, A. V. M., Honda, K., Das Gupta, A., Droogers, P. and Clemente, R. S. 2006. Combining remote sensing-simulation modeling and genetic algorithm optimization to explore water management options in irrigated agriculture. Agr. Water Manage. 83:221-232.
16. Mo, X., Liu, S., Lin, Z., Xu, Y., Xiang, Y. and McVicar, T. R. 2005. Prediction of crop yield, water consumption and water use efficiency with a SVAT-crop growth model using remotely sensed data on the North China Plain. Ecol. Mod. 183:301-322.
17. Tao, F., Yokozawa, M., Zhang, Z., Xu, Y. and Hayashi, Y. 2005. Remote sensing of crop production in China by production efficiency models: Models comparisons, estimates and uncertainties. Ecol. Mod. 183:385-396.
18. Huete, A., Didan, K., Miura, T., Rodriguez, E. P., Gao, X. and Ferreira, L. G. 2002. Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sens. Environ. 83:195-213.
19. Hinzman, L. D., Bauer, M. E. and Daughtry, C. S. T. 1986. Effects of nitrogen fertilization on growth and reflectance characteristics of winter wheat. Remote Sens. Environ. 19:47-61.
20. Hansen, P. M. and Schjoerring, J. K. 2003. Reflectance measurement of canopy biomass and nitrogen status in wheat crops using normalized difference vegetation indices and partial least squares regression. Remote Sens. Environ. 86:542-553.
21. Li, F., Gnyp, M. L., Jia, L., Miao, Y., Yu, Z., Koppe, W., Bareth, G., Chen, X. and Zhang, F. 2008. Estimating N status of winter wheat using a handheld spectrometer in the North China Plain. Field Crops Res. 106:77-85.
22. Rudorff, B. F. T. and Batista, G. T. 1990. Spectral response of wheat and its relationship to agronomic variables in the tropical region. Remote Sens. Environ. 31:53-63.
23. Scotford, I. M. and Miller, P. C. H. 2004. Estimating tiller density and leaf area index of winter wheat using spectral reflectance and ultrasonic sensing techniques. Biosyst. Eng. 89:395-408.
24. Wiegand, C. L., Maas, S. J., Aase, J. K., Hatfield, J. L., Pinter, P. J., Jr., Jackson, R. D., Kanemasu, E. T. and Lapitan, R. L. 1992. Multisite analyses of spectral-biophysical data for wheat. Remote Sens. Environ. 42:1-21.
25. Xue, L. H., Cao, W. X. and Yang, L. Z. 2007. Predicting grain yield and protein content in winter wheat at different N supply levels using canopy reflectance spectra. Pedosphere 17:646-653.
26. Baethgen, W. E., Christianson, C. B. and Lamothe, A. G. 1995. Nitrogen fertilizer effects on growth, grain yield, and yield components of malting barley. Field Crops Res. 43:87-99.
27. Latiri-Souki, K., Nortcliff, S. and Lawlor, D. W. 1998. Nitrogen fertilizer can increase dry matter, grain production and radiation and water use efficiencies for durum wheat under semi-arid conditions. Eur. J. Agron. 9:21-34.
28. Olesen, J. E., Berntsen, J., Hansen, E. M., Petersen, B. M. and Petersen, J. 2002. Crop nitrogen demand and canopy area expansion in winter wheat during vegetative growth. Eur. J. Agron. 16:279-294.
29. Bannari, A., Morin, D., Bonn, F. and Huete, A. R. 1995. A review of vegetation indices. Remote Sensing Reviews 13:95-120.
30. Roujean, J. L. and Breon, F. M. 1995. Estimating PAR absorbed by vegetation from bidirectional reflectance measurements. Remote Sens. Environ. 51:375-384.
31. Gitelson, A. A., Viña, A., Ciganda, V., Rundquist, D. C. and Arkebauer, T. J. 2005. Remote estimation of canopy chlorophyll content in crops. Geophys. Res. Lett. 32, L08403, doi:10.1029/2005GL022688.
32. Qi, J., Chehbouni, A., Huete, A. R., Kerr, Y. H. and Sorooshian, S. 1994. A modified soil adjusted vegetation index. Remote Sens. Environ. 48:119-126.
33. Huete, A. R. 1988. A Soil-Adjusted Vegetation Index (SAVI). Remote Sens. Environ. 25:295-309.