Abbasi, M. R., & Sepaskhah, A. R. (2011). Response of different rice cultivars (Oryza sativa L.) to water-saving irrigation in greenhouse conditions. International Journal of Plant Production, 5(1), 37-48.

Ahmadi, S. H., Mosallaeepour, E., Kamgar-Haghighi, A. A., & Sepaskhah, A. R. (2015). Modeling maize yield and soil water content with AquaCrop under full and deficit irrigation managements. Water Resources Management, 29(8), 2837–2853. doi:10.1007/s11269-015-0973-3

Amanullah, & Inamullah. (2016). Dry matter partitioning and harvest index differ in rice genotypes with variable rates of phosphorus and zinc nutrition. Rice Science, 23(2), 78–87. doi:10.1016/j.rsci.2015.09.006

Aranjuelo, I., Sanz-Saez, A., Jauregui, I., Irigoyen, J. J., Araus, J. L., Sanchez-Diaz, M., & Erice, G. (2013). Harvest index, a parameter conditioning responsiveness of wheat plants to elevated CO2. Journal of Experimental Botany, 64(7), 1879–1892. doi:10.1093/jxb/ert081

Austin, R. B., Bingham, J., Blackwell, R. D., Evans, L. T., Ford, M. A., Morgan, C. L., & Taylor, M. (1980). Genetic improvements in winter wheat yields since 1900 and associated physiological changes. The Journal of Agricultural Science, 94(03), 675. doi:10.1017/ s0021859600028665

Azizian, A. (2013). Modification of maize growth and yield simulation model (MSM) for different water, nitrogen and salinity levels. Ph.D. Dissertation, Shiraz University, Shiraz, Iran.

Azizian, A., & Sepaskhah, A. R. (2014). Maize response to water, salinity and nitrogen levels: yield-water relation, water-use efficiency and water uptake reduction function. International Journal of Plant Production, 8(2), 183-214.

Azizian, A., Sepaskhah, A. R., & Zand-Parsa, Sh. (2015). Modification of a maize simulation model under different water, nitrogen and salinity levels. International Journal of Plant Production, 9(4), 609-632.

Calderini, D. F., Dreccer, M. F., & Slafer, G. A. (1995). Genetic improvement in wheat yield and associated traits. A re-examination of previous results and the latest trends. Plant Breeding, 114(2), 108–112. doi:10.1111/j.1439-0523.1995.tb00772.x

Challinor, A. J., Wheeler, T. R., Craufurd, P. Q., & Slingo, J. M. (2005). Simulation of the impact of high temperature stress on annual crop yields. Agricultural and Forest  Meteorology, 135(1-4), 180–189. doi:10.1016/j. agrformet. 2005.11.015

Eitzinger, J., Trnka, M., Hösch, J., Žalud, Z., & Dubrovský, M. (2004). Comparison of CERES, WOFOST and SWAP models in simulating soil water content during growing season under different soil conditions. Ecological Modelling, 171(3), 223–246. doi:10.1016/j. ecolmodel. 2003.08.012

Evans, J. R. (2013). Improving photosynthesis. Plant physiology, 162(4), 1780–1793. doi:10.1104/pp. 113.219006

Gutam, S. (2011). Dry matter partitioning, grain filling and grain yield in wheat genotypes. Communications in Biometry and Crop Science, 6(2), 48-63

Kemanian, A. R., Stöckle, C. O., Huggins, D. R., & Viega, L. M. (2007). A simple method to estimate harvest index in grain crops. Field Crops Research, 103(3), 208–216. doi:10.1016/j.fcr.2007.06.007

Mahbod, M., Sepaskhah, A. R., & Zand-Parsa, S. (2014). Estimation of yield and dry matter of winter wheat using logistic model under different irrigation water regimes and nitrogen application rates. Archives of Agronomy and Soil Science, 60(12): 1661–161667. doi:10.1080/03650340.2014.917169

Mahbod, M., Zand-Parsa, S., & Sepaskhah, A. R. (2015). Modification of maize simulation model for predicting growth and yield of winter wheat under different applied water and nitrogen. Agricultural Water Management, 150, 18–34. doi:10.1016/j.agwat.2014.11.009

Majnooni-Heris, A., Zand-Parsa, S., Sepaskhah, A. R., Kamgar-Haghighi, A. A., & Yasrebi, J. (2011). Modification and validation of maize simulation model (MSM) at different applied water and nitrogen levels under furrow irrigation. Archives of Agronomy and Soil Science, 57(4), 401–420. doi:10.1080/03650340903512553

Moosavizadeh-Mojarad, R., & Sepaskhah, A. R. (2012). Comparison between rice grain yield predictions using artificial neural networks and a very simple model under different levels of water and nitrogen application. Archives of Agronomy and Soil Science, 58(11), 1271–1282. doi: 10.1080/03650340.2011.577423

Moser, S. B., Feil, B., Jampatong, S., & Stamp, P. (2006). Effects of pre-anthesis drought, nitrogen fertilizer rate, and variety on grain yield, yield components, and harvest index of tropical maize. Agricultural Water Management, 81(1-2), 41–58. doi:10.1016/j.agwat.2005.04.005

Prasad, P. V. V., Boote, K. J., & Allen, L. H. (2006). Adverse high temperature effects on pollen viability, seed-set, seed yield and harvest index of grain-sorghum [Sorghum bicolor (L.) Moench] are more severe at elevated carbon dioxide due to higher tissue temperatures. Agricultural and Forest Meteorology, 139(3-4), 237–251. doi:10.1016/ j. agrformet. 2006.07.003

Prihar, S. S., & Stewart, B. A. (1990). Using upper-bound slope through origin to estimate genetic harvest index. Agronomy Journal, 82(6), 1160. doi:10.2134/agronj1990.00021962008200060027x

Richards, R. A., & Townley-Smith, T. F. (1987). Variation in leaf area development and its effect on water use, yield and harvest index of droughted wheat. Australian Journal of Agricultural Research, 38(6), 983. doi:10.1071/ar9870983

Sepaskhah, A. R., Fahandezh-Saadi, S., & Zand-Parsa, S. (2011). Logistic model application for prediction of maize yield under water and nitrogen management. Agricultural Water Management, 99(1), 51–57. doi:10.1016/j.agwat. 2011.07.019

Sepaskhah, A. R., & Ilampour, S. (1996). Relationships between yield, crop water stress index (CWSI) and transpiration of cowpea (Vigna sinensis L). Agronomie, 16(5), 269–279. doi:10.1051/agro:19960501

Sepaskhah, A. R., & Yarami, N. (2016). Evaluation of macroscopic water extraction model for salinity and water stress in saffron yield production. International Journal of Plant Production, 4(3), 175-186.

Sepaskhah, A. R., Amini-Nejad, M., & Kamgar-Haghighi, A. A. (2013). Developing a dynamic yield and growth model for saffron under different irrigation regimes. International Journal of Plant Production, 7(3), 473-504.

Sepaskhah, A. R., & Beirouti, Z. (2009). Effect of irrigation interval and water salinity on growth of madder (Rubinatinctorum L.). International Journal of Plant Production, 3(3), 1-16.

Sepaskhah, A. R., & Ghasemi, M. M. (2008). Every-other-furrow irrigation with different irrigation intervals for grain sorghum. Pakistan Journal of Biology Science, 11 (9), 1234-1239.

Shabani, A. (2011). Development and test of SEM model to estimate capillary rise from shallow ground water for rice cultivation in greenhouse condition. PhD seminar course. Shiraz University, Shiraz, Iran (In Persian).

Shabani, A., Kamkar-Haghighi, A. A., Sepaskhah, A. R., Emam, Y., & Honar, T. (2010). Effect of water stress on seed yield, yield components and quality of winter rapeseed (Brassica napus L.) cv. Licord. Iranian Journal of Crop Science, 12 (4), 409-421. (In Persian)

Shabani, A., Sepaskhah, A. R., & Kamgar-Haghighi, A. A. (2014). Estimation of yield and dry matter of rapeseed using logistic model under water salinity and deficit irrigation. Archives of Agronomy and Soil Science, 60(7), 951–969. doi:10.1080/03650340.2013.858807

Shabani, A., Sepaskhah, A. R., & Kamgar-Haghighi, A. A. (2015). A model to predict the dry matter and yield of rapeseed under salinity and deficit irrigation. Archives of Agronomy and Soil Science, 61(4), 525–542. doi:10.1080/03650340.2014.938645

Shabani, A., Sepaskhah, A. R., & Kamgar-Haghighi, A. A. (2013). Responses of agronomic components of rapeseed (Brassica napus L.) as influenced by deficit irrigation, water salinity and planting method. International Journal of Plant Production, 7 (2), 313-340.

Sharifi, R. S., Sedghi, M., & Gholipouri, A. (2009). Effect of population density on yield and yield attributes of maize hybrids. Research Journal of Biological Sciences, 4(4), 375-379.

Sinclair, T. R. (1986). Water and nitrogen limitations in soybean grain production I. Model development. Field Crops Research, 15(2), 125–141. doi:10.1016/0378-4290(86)90082-1

Sinclair, T. R. (1998). Historical Changes in Harvest Index and Crop Nitrogen Accumulation. Crop Science, 38(3), 638. doi:10.2135/cropsci1998.0011183x003800030002x

Soltani, A., Torabi, B., & Zarei, H. (2005). Modeling crop yield using a modified harvest index-based approach: application in chickpea. Field Crops Research, 91(2-3), 273–285. doi:10.1016/j.fcr.2004.07.016

Steduto, P., Hsiao, T. C., Raes, D., & Fereres, E. (2009). AquaCrop—the FAO crop model to simulate yield response to water: I. concepts and underlying principles. Agronomy Journal, 101(3), 426-437. doi:10.2134/ agronj 2008.0139s

Talebnejad, R., & Sepaskhah, A. R. (2013). Effects of water-saving irrigation and groundwater depth on direct seeding rice growth, yield, and water use in a semi-arid region. Archives of Agronomy and Soil Science, 60(1), 15–31. doi:10.1080/03650340.2013.770598

Talebnejad, R., & Sepaskhah, A. R. (2016). Modification of transient state analytical model under different saline groundwater depths, irrigation water salinities and deficit irrigation for quinoa. International Journal of Plant Production, 10(3), 365-390.

Tollenaar, M., Deen, W., Echarte, L., & Liu, W. (2006). Effect of crowding stress on dry matter accumulation and harvest index in maize. Agronomy Journal, 98(4), 930-937. doi:10.2134/agronj2005.0336

Turner, N. C., Wright, G. C., & Siddique, K. H. M. (2001). Adaptation of grain legumes (pulses) to water-limited environments. Advances in Agronomy, 71, 193–231. doi:10.1016/s0065-2113(01)71015-2

Unkovich, M., Baldock, J., & Forbes, M. (2010). Variability in harvest index of grain crops and potential significance for carbon accounting. Advances in Agronomy, 105, 173–219. doi:10.1016/s0065-2113(10)05005-4

Vanuytrecht, E., Raes, D., Steduto, P., Hsiao, T. C., Fereres, E., Heng, L. K., & Moreno, P. M. (2014). AquaCrop: FAO's crop water productivity and yield response model. Environmental Modelling and Software, 62, 351-360. doi:10.1016/j.envsoft.2014.08.005

Wang, Q., Cui, J., Wang, X., Zhang, T., Zhou, H., Hu, T., & Han, J. (2011). Algorithmic models of seed yield and its components in smooth bromegrass (Bromus inermis L.) via large sample size under field conditions. Euphytica, 185(3), 363–375. doi:10.1007/s10681-011-0541-8

Wnuk, A., Górny, A. G., Bocianowski, J., & Kozak, M. (2013). Visualizing harvest index in crops. Communications in Biometry and Crop Science, 8(2), 48-59.

Yarami, N., & Sepaskhah, A. R. (2016). Modification of the saffron model for growth and yield prediction under different irrigation water salinity, manure application and planting methods. International Journal of Plant Production, 10(2), 175-196

Zand-Parsa, S., (2001). A simulation model for prediction of water and nitrogen effects on corn yield. Ph.D. Dissertation, Shiraz University, Shiraz, Iran.

Zand-Parsa, S., Sepaskhah, A. R., & Ronaghi, A. (2006). Development and evaluation of integrated water and nitrogen model for maize. Agricultural Water Management, 81(3), 227–256. doi:10.1016/j.agwat.2005.03.010

Ziaei, A., & Sepaskhah, A. (2003). Model for simulation of winter wheat yield under dryland and irrigated conditions. Agricultural Water Management, 58(1), 1–17. doi:10.1016/s0378-3774(02)00080-x