I would start with chapter 10B in my textbook:Lambers H, Chapin, F.S., and Pons, T.L. 2008 Plant physiological ecology. Springer-Verlag, New York.

Dear Mr Wang,

You can also have a look on following paper, it may serve your purpose.

https://www.researchgate.net/publication/261324408_Managing_Irrigation_Water_by_Yield_and_Water_Productivity_Assessment_of_a_Rice-Wheat_System_Using_Remote_Sensing  

Article Managing irrigation water by yield and water productivity as...

Hi Mr Wang,

Specifically for soybean yield, I have developed a spectral model based on EVI/MODIS data which is very useful for estimations in advance to crop harvest. Please take a look at Gusso et al., (2013) in the International Journal of Geosciences.

Regards

Anibal

Thank you very much for your suggestion.

That question is suitable for writing a book.

There exist many methods in doing this.such as the Crop yield estimator using spatial parameter broadcasting services where remote sensing is highly applicable

Hi, The topic is a kind of vast an deep one, there was a workshop by FAo on that,

http://www.fao.org/asiapacific/rap/agricultural-statistics-in-ap/meetings-events/expert-meeting-crop-monitor/en/

I am using Monteith algorithm for rice yield in my phd thesis. find the source  paper by bastiansen and ali, :

ftp://131.175.31.10/users/Giorgio.Guariso/papers/crop satellite Pakistan.pdf

Most remote sensing estimates of yield are based on NIR/Visible information, which integrates leaf greenness, leaf biomass and, to a lesser extent, water content. Basically, they attempt to quantify what a good farmer's eye can see when predicting yield. In most cases, the indices perform better at critical stages, such as anthesis, although for some crops time-integration could be useful (e.g. for maize to determine green area duration). However, depending on your purpouse, accuracy is not very high, and the spectral features require site-specific calibration and, in earlier stages, when plant cover is limited, to consider soil properties.

Have a look at some of these papers:

Ferrio, J. P., Villegas, D., Zarco, J., Aparicio, N., Araus, J. L., & Royo, C. (2005). Assessment of durum wheat yield using visible and near-infrared reflectance spectra of canopies. Field Crops Research, 94(2), 126-148.

Cabrera‐Bosquet, L., Crossa, J., von Zitzewitz, J., Serret, M. D., & Luis Araus, J. (2012). High‐throughput Phenotyping and Genomic Selection: The Frontiers of Crop Breeding ConvergeF. Journal of integrative plant biology, 54(5), 312-320.

Weber, V. S., Araus, J. L., Cairns, J. E., Sanchez, C., Melchinger, A. E., & Orsini, E. (2012). Prediction of grain yield using reflectance spectra of canopy and leaves in maize plants grown under different water regimes. Field Crops Research, 128, 82-90.

Su, T., Feng, S. Y., & Cui, X. Y. (2013). Regional Yield Estimation for Spring Maize with Multi-Temporal Remotely Sensed Data in Junchuan, China. Advanced Materials Research, 610, 3601-3605.

thanks very much for evevryone's vuluable suggestion,also welcome others to add much more answer.

Have a look at this paper for an introduction:

Serrano, L., Filella, I. and Josep Penuelas, j. (2000)̃:

Remote Sensing of Biomass and Yield of Winter Wheat under Different Nitrogen Supplies. Crop Science 40, 723-731.

And these two may also be of interest:

Laigang Wang, Yongchao Tian, Xia Yao, Yan Zhu, Weixing Cao (2014): Predicting grain yield and protein content in wheat by fusing multi-sensor and multi-temporal remote-sensing images. Field Crops Research 164, 178-188.

GNYP, M.L., BARETH, G., LI, F., LENZ-WIEDEMANN, V., KOPPE, W., MIAO, Y., HENNIG, S.D., JIA L.L., LAUDIEN, R., CHEN, X.P. and ZHANG, F. (2014): Development and implementation of a multiscale biomass model using hyperspectral vegetation indices for winter wheat in the North China Plain. J. Appl. Earth Observ. Geoinf. 33, 232-242. DOI: 10.1016/j.jag.2014.05.006

Victoria Lenz-Wiedemann, thank you very much.

Dear Qianfeng,

You may find these contributions helpful:

http://dx.doi.org/10.1080/01431160410001698870

http://dx.doi.org/10.1080/01431161.2010.493566

Kind regards, Balázs

Balázs Székely ,thank you very much for your information.