برآورد خلأ عملکرد مزارع گندم با استفاده از رهیافت‌های GIS، RS و مدل SSM (مطالعه موردی: حوضه قره‌سوی شهرستان گرگان)

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانش‌آموخته کارشناسی ارشد، گروه زراعت، دانشگاه علوم کشاورزی و منابع طبیعی گرگان، گرگان، ایران

2 دانشیار، گروه زراعت، دانشگاه علوم کشاورزی و منابع طبیعی گرگان، ایران

3 استاد، گروه زراعت، دانشگاه علوم کشاورزی و منابع ع طبیعی گرگان، ایران

4 کارشناس ارشد، اداره کل منابع طبیعی و آبخیزداری استان گلستان، گرگان، ایران

چکیده

با توجه به افزایش قیمت غلات و نگرانی در مورد امنیت غذایی جهانی، تحقیقات در مورد خلأ عملکرد طی سال‌های اخیر به‌سرعت در حال افزایش است. تخمین دقیق اندازه و توریع مکانی خلأ عملکرد کاربردهای زیادی از جمله در کشاورزی دقیق دارد. این پژوهش به‌منظور برآورد خلأ عملکرد گندم در حوضه قره‌سوی شهرستان گرگان با استفاده از سامانه اطلاعات جغرافیایی (GIS)، سنجش از دور و مدل SSM انجام شد. بدین‌منظور از مدل SSM برای برآورد عملکرد تابش محدود، از تصاویر ماهواره لندست 8 جهت استخراج شاخص‌های گیاهی، از روابط رگرسیونی برای تعیین رابطه شاخص‌های گیاهی با عملکرد ثبت‌شده برای تولید لایه رستری عملکرد تخمین‌زده شده، از رابطه تابش‌رسیده و عملکرد تابش محدود برای تولید لایه رستری عملکرد تابش محدود حوضه و از تابع تفاضل برای تعیین خلأ عملکرد استفاده شد. نتایج نشان داد که عملکرد تابش محدود، عملکرد واقعی و خلأ عملکرد اراضی زیر کشت گندم که از روش نظارت‌شده از سایر کشت‌ها جدا شده بود، به‌ترتیب بین 42/5 تا 94/7 تن در هکتار، 27/2 تا 39/5 تن در هکتار و 67/1 تا 88/4 تن در هکتار متغیر بود. ضریب عملکرد منطقه‌ای نیز بین 32/0 تا 76/0 محاسبه شد و نشان داد که مناطق تحت کشت گندم این حوضه دارای واریانس قابل‌توجهی هستند. بنابراین، با توجه به اینکه ویژگی­های خاک و شرایط اقلیمی و توپوگرافی طی زمان کم و بیش بدون تغییر می‌مانند، پیشنهاد می­شود عامل مدیریت به‌عنوان یکی از مهم‌ترین عوامل تعیین‌کننده خلأ عملکرد در حوضه قره‌سو مورد بررسی قرار گیرد.

کلیدواژه‌ها


عنوان مقاله [English]

Yield gap estimation in wheat-grown fields using GIS and RS approach and SSM model (A case study: Qaresso basin, Gorgan, Iran)

نویسندگان [English]

  • Meysam Badsar 1
  • Behnam Kamkar 2
  • Afshin Soltani 3
  • Omid Abdi 4
1 Graduated M. Sc., Dept. of Agronomy, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran
2 Assoc. Prof., Dept. of Agronomy, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran
3 Prof., Dept. of Agronomy, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran
4 M. Sc., Dept. of Natural Resources and Watershed Management of Golestan Province, Gorgan, Iran
چکیده [English]

Considering rising cereal prices and concern about global food security, researches are increasingly carrying out on the yield gap during recent years. Accurate estimation of the quantity and spatial distribution of the yield gap has many practical applications, such as using in precision farming. This study was aimed to evaluate the yield gap of wheat-grown fields in Qaresoo basin, Gorgan, Iran, using GIS, RS and the SSM model. For this purpose, the SSM model was used to estimate the radiation limited yield; the Landsat 8 to extract crop indices; regression models to relate crop indices and recorded yield in order to provide predicted yield raster layer; received radiation and the radiation-limited yield to provide studied basin’s radiation-limited yield and finally minus function to determine the final yield gap. The radiation-limited yield, predicted yield and yield gap of wheat grown fields, (which were detected using supervised method than other crops-grown fields), varied from 5.42 to 7.94 t.ha-1, 2.27 to 5.39 t.ha-1 and 1.67 to 4.88 t.ha-1 respectively. The results revealed that wheat-grown fields had a remarkable variance with respect to calculated regional yield factor (from 0.32 to 0.76). Considering environmental factors (soil-related, climatic and topographic factors), It is proposed to consider management factors as one of the important determiners of yield gap.

کلیدواژه‌ها [English]

  • Crop indices
  • Landsat 8
  • Radiation limited yield
  • Regional yield factor
Abeledo, L. G., Savin, R. and Slafer, G. A. 2008. Wheat productivity in the Mediterranean Ebro Valley: Analyzing the gap between attainable and potential yield with a simulation model. European Journal of Agronomy 28: 541-550.##Aggarval, P. K. 1994. Constraints in wheat productivity in India. In: Aggarval, P.K., Kalra, N. (Eds.). Simulating the effect of climatic factors, genotype and management on productivity of wheat in India. Agricultural Research Institute, New Delhi, India. pp: 1-11.##Aggarval, P. K., Hebbar, K. B., Venugopalam, M. V., Rani, S., Bala, A., Biswal, A. and Wani, S. P. 2008. Quantification of yield gaps in rain-fed rice, wheat, cotton and mustard in India. Global Theme on Agroecosystems Report No. 43. ICRISAT, Patancheru, India, 36 p.##Alexandratos, N. 1995. World Agriculture: Towards 2010. FAO. Wiley, NewYork. 383 p.##Balaghi, R., Tychon, B., Eerens, H. and Jlibene, M. 2008. Empirical regression models using NDVI, rainfall and temperature data for the early prediction of wheat grain yields in Morocco. International Journal of Applied Earth Observation and Geoinformation 10: 438-452.##Bhatia, V. S., Singh, P., Wani, S. P., Chauhan, G. S., Rao, A. V. R., Mishra, A. K. and Srinivas, K. 2008. Analysis of potential yields and yield gaps of rainfed soybean in India using CROPGRO-Soybean model. Agricultural and Forest Meteorology 148: 1252-1265.##Boogaard, H., Wolf, J., Niemeyer, S. and Van Ittersum, M. 2013. A regional implementation of WOFOST for calculating yield gaps of autumn-sown wheat across the European Union. Field Crops Research 143: 120-142.##Cassman, K. G., Dobermann, A., Walters, D. T. and Yang, H. 2003. Meeting cereal demand while protecting natural resources and improving environmental quality. Annual Review of Environment and Resources 28: 315–358.##Chen, C., Baethgen, W. E. and Robertson, A. 2013. Contributions of individual variation in temperature, solar radiation and precipitation to crop yield in the North China Plain, 1961-2003. Climatic Change 116 (3-4): 767-788.##Chen, Z. Q. and Chen, J. F. 2010. The Simulation of Extraterrestrial Solar Radiation Based on SOTER in Zhangpu Sample Plot and Fujian Province. Journal of Computers 5 (1): 144 - 149.##Darvishzadeh,  R.,  Motakan,  A. A.  and  Eskandari,  N.  2011.  Evaluation  of ALOSAVNIR- spectral indices for prediction of rice biomass. Geographical Landscape 14: 61-73. (In Persian with English Abstract).##FAO. 1996. Agro-ecological zoning. Guidelines. FAO, Land and Water Development. 78 p.##Fatemi, S. B. and Rezaei, Y. 2006. Foundations remote sensing. Azadeh Press. 257 p. (In Persian).##Fischer, R. A., Byerlee, D. and Edmeades, G. O. 2009. Can technology deliver on the yield challenge to 2050? In: FAO Expert Meeting on How to Feed the World in 2050. 24-26 June 2009. FAO, Rome. Retrieved July 16, 2014, from ftp://ftp.fao.org/docrep/fao/012/ak977e/ak977e00.pdf.##Fischer, R. A. and Edmeades, G. O. 2010. Breeding and cereal yield progress. Crop Science Society of America 50: 85-98.##Ghaemi, M., Sanaeinejad, H., Astaraei, A. R. and Mirhosseini, P. 2010. Study and comparison of different vegetation indices using by ETM+ satellite imagery studies vegetation Neyshabur region, Khorasan Razavi. Iranian Journal of Field Crops Research 8 (1): 128-137. (In Persian with English Abstract).##Gharineh, M. H., Bakhshandeh, A. M., Andarzian, B. and Fayezizadeh, N. 2012. Agro-climatic zonation for Khouzestan province based on potential yield of Irrigation wheat using by WOFOST model. Journal of Agroecology 4 (3): 255-264. (In Persian with English Abstract).##Hall, A. J., Feoli, C., Ingaramo, J. and Balzarini, M. 2013. Gaps between farmer and attainable yields across rainfed sunflower growing regions of Argentina. Field Crops Research 143: 151-156.##Hochman, Z., Gobbett, D., Holzworth, D., McClelland, T., Van Reese, H., Marinoni, O., Garcia, J. N. and Horan, H. 2013. Reprint of quantifying yield gaps in rainfed cropping systems: A case study of wheat in Australia. Field Crops Research 143: 65-75.##Huete, A. R. 1988. A soil-adjusted vegetation index (SAVI). Remote Sensing of Environment 25: 295-309.##Jalal Kamali, M. R. 2008. Review on wheat position in the past, present and future world. 10th Iranian Crop Science Congress, 18-20 July, Tehran, Iran. (In Persian).##Jodaei, A. R. 2000. Study of effective factors in wheat yield at Urmia. 3rd Conference of Agricultural Economics. February 18 – March 1, Mashhad, Iran. (In Persian).##Kamkar, B., Koocheki, A., Nasiri Mahalati, M. and Rezvani Moghadam, P. 2007. Analysis of yield gap of cumin in 9 areas of North Khorasan, South Khorasan and Khorasan Razavi provinces using modeling method.Iranian Journal of Field Crops Research 5: 332-342. (In Persian with English Abstract).##Kamkar, B., Koocheki, A., Nasiri Mahalati, M. and Rezvani Moghadam, P. 2007. Analysis of yield gap of cumin in 9 areas of North Khorasan, South Khorasan and Khorasan Razavi Provinces using modeling method. Iranian Journal of Field Crops Research 5: 332-342. (In Persian with English Abstract).##Laborte, A. G., de Bie, C. A. J. M., Smaling, E. M. A., Moya, P. F., Boling, A. A. and Van Ittersum, M. K. 2012. Rice yields and yield gaps in South East Asia: past trends and future outlook. European Journal of Agronomy 36: 9-20.##Li, K., Yang, X., Liu, Z., Zhang, T., Lu, S. and Liu, Y. 2014. Low yield gap of winter wheat in the North China Plain. European Journal of Agronomy 50: 1-12.##Li-Hong, X., Wei-Xing, C. and Lin-Zhang, L. 2007. Predicting grain yield and protein content in winter wheat at different supply levels using canopy reflectance spectra. Pedosphere 17 (5): 646-653.##Lobell, D. B., Cassman, K. G. and Field, C. B. 2009. Crop yield gaps: their importance, magnitudes and causes. Annual Review of Environment and Resources 34: 179-204.##Mahmoodan, S. 2014. Comparison of wheat yield between common and modern wheat cropping system using geographical information system approach. M. Sc. Dissertation, University of Gorgan, Gorgan, Iran. (In Persian).##Meng, Q., Hou, P., Wu, L., Chen, X., Cui, Z. and Zhang, F. 2013. Understanding production potentials and yield gaps in intensive maize production in China. Field Crops Research 143: 91-97.##Mkhabela, M. S., Bullock, P., Raj, S., Wang, S. and Yang, Y. 2011. Crop yield forecasting on the Canadian Prairies using MODIS NDVI data. Agricultural and Forest Meteorology 151: 385-393.##Mohammdi Ahmad Mahmoodi, A. 2013. Monitoring production biomass army wheat fields Golestan province using geographical information system and remote sensing. M. Sc. Dissertation, University of Gorgan, Gorgan, Iran. (In Persian).##Mukherjee, J., Gebro, G., Sood, A., Mahey, R. K., Bal, S. K., Singh, H. and Sidha, P. 2010. Wheat yield and acreage prediction using LISS-III and AWiFS sensors data of Indian remote sensing satellite of Rupnager district of Punjab, India. Italian Journal of Remote Sensing 42 (3): 155-157.##Nasiri Mahalati, M. 2001. Modeling of growth process crop plants. Jahad Daneshgahi Mashhad. 274 p. (In Persian).##Nasiri Mahalati, M. and Koochaki. A. R. 2010. Agroecological zone wheat in Khorasan provinces: Estimation of potantial and yield gap.Iranian Journal of Field Crops Research7 (2): 695-709. (In Persian with English Abstract).##Nazarifar, M. H., Momeni, R. and Jafari, H. 2006. Assessment of effect radiation in maximum yield crop production of Karoon basin and zoning of water use efficiency using geographical information system (GIS). First Regional Conference on Optimal Utilization of Water Resources and Watersheds, Zayanderood Karun. September 5-6, Shahrekord University, Shahrekord, Iran. (In Persian).##Nekahi, M. Z., Soltani, A., Siahmarguee, A. and Bagherani, N. 2014. Yield gap associated with crop management in wheat (A case study: Golestan province, Bandar-e Gaz). Electronic Journal of Crop Production 7 (2): 135-156. (In Persian with English Abstract).##Nonhebel, S. 1997. Harvesting the sun’s energy using aroecosystems. Quantitative approaches in system analysis, No. 13. Wageningen., The Netherlands. 77 p.##Oliver, Y. M. and Robertson, M. J. 2013. Quantifying the spatial pattern of the yield gap within a farm in a low rainfall Mediterranean climate. Field Crops Research 150: 29-41.##Priya, S. and Shibasaki, S. 2001. National spatial crop yield simulation using GIS based crop production model. Ecological Modelling 135: 113-129.##Rahmani, N., Shahedi, K. and Miryaghoobzade, M. H. 2011. Assessment of vegetation indices used for remore sensing (A case study: Harsik basin). 18th National Conference and Exhibition Geomatics 2011 and Conferences of the Internatinal Society for Remote Sensing, May15, Tehran, Iran. (In Persian).##Ren, J., Chen, Z., Q., Zhou and Tang, H. 2008. Regional yield estimation for winter wheat with MODIS-NDVI data in Shandong, China. International Journal of Applied Earth Observation and Geoinformation 10: 403-413.##Sanaeinejad, H., Astaraei, A. R., Mirhosseini, P., Keshavarzi, A. and Ghaemi, M. 2008a. Use of satellite imagery for vegetation studies: Comparison of different vegetation indices (A case study: Neyshabour region). 5th National Congress of Agricultural Machinery Engineering and Mechanization. August 27-28, Mashhad, Iran. (In Persian).##Sanaeinejad, H., Nassiri Mahallati, M., Zare, H., Salehnia, N. and Ghaemi, M. 2014. Wheat yield estimation using Landsat images and field observation (A case study: Mashhad). Journal of plant Production 20 (4): 45-63. (In Persian with English Abstract).##Sanaeinejad, H., Shah Tahmasebi, A. R., Sadri Haghighi, R. and Kelarestani, K. 2008b. A study spectral reflex variance of wheat fields in Mashhad using MODIS images. Agriculture Science and Technology 45: 11-19. (In Persian with English Abstract).##Sánchez, N., González, R., Prado, J., Martínez-Fernández, J. and Pérez-Gutiérrez, C. 2006. Estimating and remote sensing. Ecological Modelling 222: 2530-2541.##Sedighi, M. 2004. Application of geographic information system (GIS) in organizing documents in earth science information and documentation center of Iran. International Journal of Information Science and Management 20: 29-49.##Soltani, A. 2011. Modeling of development, growth and yield in wheat. Research design report. Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran. 115 p. (In Persian).##Soltani, A. and Sinclair, T. R. 2012. Modeling physiology of crop development, growth and yield. CAB International, Wallingford, UK.##Son, N. T., Chen, C. F., Chen, C. R., Chang, L. Y., Duc, H. N. and Nguyen, L. D. 2013. Prediction of rice crop yield using MODIS EVI−LAI data in the Mekong Delta, Vietnam. International Journal of Remote Sensing 34 (20): 7275-7292.##Taei Semiromi, J., Ghanbari, A., Amiri, E., Ghaffari, A., Siahsar, B. and Ayoubi, Sh. 2011. Agroecological zoning of wheat in the Borujen watershed: Rainfed and irrigated wheat cropping system evaluation. Journal of Sustainable Agriculture and Production Science 22:1-12. (In Persian with English Abstract).##Timsina, J., Pathak, H., Humphreys, E., Godwin, D., Singh, B., Shukla, A. K. and Singh, U. 2004. Evaluation of final yield and yield gap analysis in rice using, CERES rice ver. 4.0 in northwest India. 4th International Crop Science Congress, September 28 – October 1, Brisbane, Australia.##Torabi, B. 2011. Analyzing wheat yield constraints in Gorgan using simulation model and analytic hierarchy process (AHP). Ph. D. Dissertation, University of Gorgan, Gogan, Iran. (In Persian).##Torabi, B., Soltani, A., Galeshi, S. and Zeinali, E. 2011. Analyzing wheat yield constraints in Gorgan. Electronic Journal of Crop Production 4: 1-17. (In Persian with English Abstract).##Van Ittersum, M. K., Cassman, K. G., Grassini, P., Wolf, J., Tittonell, P. and Hochman, Z. 2013. Yield gap analysis with local to global relevance: A review. Field Crops Research 143: 4-17.##Van Ittersum, M. K. and Rabbinge, R. 1997. Concepts in production ecology for analysis and quantification of agricultural input-output combinations. Field Crops Research 52: 197-208.##Wang, L., Tian, Y., Yao, X., Zhu, Y. and Cao, W. 2014. Predicting grain yield and protein content in wheat by fusing multisensory and multi-temporal remote-sensing images. Field Crops Research 164: 178-188.##Wu, D., Yu, Q., Lua, C. and Hengsdijk, H. 2006. Quantifying production potentials of winter wheat in the North China plain. European Journal of Agronomy 24 (3): 226-235.##Yegane, H., Khaje Addin, J. and Sofyanian, A. R. 2008. A study on capability spectral indices of MODIS sensor in estimating vegetation production Semirop pasture. Journal of Pasture 2 (1): 63-77. (In Persian with English Abstract).##Zarea, A., Koochaki, A. and Nasiri Mahalati, M. 2006. Trend analysis of yield, production and cultivated area of cereal in Iran during the last 50 years and prediction of future situation. Iranian Journal of Field Crops Research 4 (1): 42-69. (In Persian with English Abstract).