تحقیقات کاربردی علوم جغرافیایی

تحقیقات کاربردی علوم جغرافیایی

بررسی عوامل مؤثر بر تغییرات تولید گندم در اقلیم های مختلف استان فارس

نویسندگان
لیلا شریفی 1
سعید بازگیر 2
حسین محمدی 3
علیرضا دربان آستانه 4
مصطفی کریمی احمدآباد 5
1 دانشجوی دکتری اقلیم شناسی کشاورزی دانشگاه تهران
2 استادیار هواشناسی کشاورزی، گروه جغرافیای دانشگاه تهران، ایران.
3 استاد گروه آب و هواشناسی دانشگاه تهران، ایران.
4 استادیار گروه جغرافیا و برنامه ریزی روستایی، دانشگاه تهران، ایران.
5 استادیار گروه آب و هواشناسی دانشگاه تهران
10.29252/jgs.20.57.371
چکیده
در یک سامانه ­ی کشاورزی، تولید محصول با شرایط اقلیمی مرتبط است. بنابراین، فهم عمیق تر تأثیر تغییرات اقلیمی مناطق بر میزان تولید، تضمین کننده امنیت غذای جهان می ­باشد. گندم از راهبردی­ترین محصولات زراعی بوده و بررسی جوانب مختلف تولید آن از ضروریات هر جامعه کشاورزی می­ باشد. طبق مطالعات، تولید گندم تحت تأثیر متغیرهای مختلفی از جمله زیست­ محیطی، فردی و اجتماعی، اقتصادی و تکنولوژیکی است. این پژوهش با هدف برآورد میزان اثر این متغیرها در تغییرات تولید گندم در اقلیم­های مختلف استان فارس انجام شده است. داده­های مورد نیاز از طریق نمونه­ گیری طبقه ­ای تصادفی چندمرحله­ ای و طی 522 پرسشنامه تکمیل شده از طریق مصاحبه حضوری با کشاورزان استان گردآوری و تحلیل شده­ است. سنجش نگرش­ کشاورزان در طیف لیکرت بوده و از توابع تولید کاب داگلاس، ترانسندنتال و ترانسلوگ برای برآورد میزان تأثیر متغیرها استفاده شده است. نتایج حاصل از مقایسه متغیرهای مؤثر در سه تابع کاب داگلاس، ترانسن دنتال و ترانسلوگ؛ برتری ترانسلوگ را نشان می­ دهد. از دیدگاه کشاورزان استان در تابع ترانسلوگ، به ترتیب؛ رطوبت خاک در زمان کشت (0/69)، بارش مؤثر در فصل رشد (0/68) و در تاریخ کشت (0/66)، موج گرمایی در زمان برداشت (0/63)، بارش آسیب زننده (0/59)، سود حاصل از تولید گندم (0/51)، تحصیلات کشاورز (0/49)، کیفیت خاک (0/49) و روش کشت (0/49) با ضریب تعیین­های ذکر شده در کنار آن­ها؛ مهمترین عوامل تبیین کننده تولید گندم در استان فارس می­ باشند. متغیرهای مستقل در تابع ترانسلوگ، 92 درصد از تغییرات تغییرات تولید گندم در استان فارس را تبیین می کنند.
کلیدواژه‌ها
گندم
نواحی اقلیمی
استان فارس
عملکرد تولید

عنوان مقاله English

Effective factors on variations of wheat production in climatic regions of Fars province

نویسندگان English

leyla sharifi 1
saeed bazgeer 2
hosain mohmmadi 3
alireza darbaneh astaneh 4
mostafa karimi ahmadabad 5
1 PhD student in Agricultural Climatology, Department of Geography, University of Tehran, Iran.
2 Assistant Professor of Agricultural Meteorology, Department of Geography, University of Tehran, Iran
3 Professor of Agricultural Climatology, Department of Geography, University of Tehran, Iran.
4 Assistant Professor of Geography and Rural Planning, Department of Geography, University of Tehran, Iran.
5 Assistant Professor of Dynamic Climatology, Department of Geography, University of Tehran, Iran
چکیده English

In an agricultural system, crop production is related to climatic conditions. Therefore, a deeper understanding of the impact of regional climate change on production ensures global food security. Wheat is one of the most strategic crops and examining different aspects of its production is a necessity of every agricultural community. According to studies, wheat production is affected by various variables including environmental, individual and social, economic and technological. The aim of this study was to estimate the effect of these variables on changes in wheat production in different climates of Fars province. The required data were collected and analyzed through multi-stage random stratified sampling and 522 completed questionnaires through face-to-face interviews with farmers in the province. Farmers' attitudes were measured in the Likert scale and Cobb Douglas, Transcendental and Translog production functions were used to estimate the effect of variables. Results of comparing effective variables in three Cobb-Douglas, Transcendental and Translog functions; demonstrates the superiority of translog. From the perspective of the farmers of the province in the translog function, respectively; Soil moisture at planting time (0.692), effective rainfall during growing season (0.68) and at planting date (0.66), heat wave at harvest time (0.63), damaging rainfall (0.59) , Profit from wheat production (0.51), farmer education (0.49), soil quality (0.49) and cultivation method (0.49) with the coefficient of the mentioned criteria next to them; The most important factors explaining wheat production in Fars province. Independent variables in the translog function explain 92% of the changes in wheat production in Fars province.

کلیدواژه‌ها English

Wheat
Climatic regions
Fars province
Production function
Adams, R. M.,(1992), Climate A griculture and the Environment, Sustainable Agricultural Development; The Role of International Cooperation . IAAE, University of Oxford. 19(95): 200-215.
Balagtas, M.T. Holt.,(2009), The commodity terms of trade, unit roots, and nonlinear alternatives: A smooth transition approach, American Journal of Agricultural Economics, 91 (1): 87-105.
Bamidele, F. S. Babatunde, R. O. and Rasheed, A. (2008), Productivity analysis of cassava-based production systems in the Guinea savannah: Case study of Kwara State, Nigeria, AmericanEurasian Journal of Scientific Research, 3(1): 33-39.
Barros, V.R, Dokken, D.J, Mach, K.J, Mastrandrea M.D, Bilir T.E., et al,.( 2019), IPCC, Climate Change Impacts, Adaptation, and Vulnerability, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 50-97.
Bellemare, M.F., (2015), Rising food prices, food price volatility, and social unrest, American Journal of Agricultural Economics, 97 (1): 1-21.
Bhatt, N. J. (2014), Productivity in small and medium enterprises of India: A Cobb-Douglas production function approach. IUP Journal of Management Research, 13(1): 29.
Bidarkota, M.J. Crucini, K,. (2000), Commodity prices and the terms of trade, Review of International Economics, 8 (4): 647-666.
Buck-Sorlin, J, Process-based model, (2013). Encyclopaedia of Systems Biology, Springer, New York, USA, 2(21): 1755.
Chand, S. and Yala, C. (2009), Land tenure and productivity: farm-level evidence from Papua New Guinea, Land Economics, 85(3): 442-453.
Chen, P.T. Wu, X.N. Zhao, P., (2013), Naraine Effect of different mulches on harvested rainfall use efficiency for corn (Zea mays L.) in semi-arid regions of Northwest China, Arid Land Res. Manage, 27 (20): 272-285.
Conceicao, P., Fuentes-Nieva, R., Horn-Phathanothai, L. and Ngororano, A,. (2016), Food security and human development in Africa: Strategic considerations and directions for further research, African Development Review, 23(2): 237–246.
FAO, (2012 & 2016), FAO Statistical Databases. http://faostat.fao.org, 45-67 & 89. Harker, J.T. O'Donovan, K. Turkington, R.E. Blackshaw, N.Z. Lupwayi, E.G. Smith, E.N. Johnson, D. Pageau, S.J. Shirtliffe, R.H. Gulden, J. Rowsell, L.M. Hall, C.J. Willenborg, (2016), Diverse rotations and optimal cultural practices control wild oat (Avena fatua L.), Weed Sci., 64 (16): 170-180.
Huamin, H. Huang, L. Jianfeng, (2010).Parameter estimation of the mixed Logit model and its application, Journal of Transportation Systems Engineering and Information Technology, 10(5): 73-78.
Hylleberg, S., Engle, R.F., Granger, C.W.J., Yoo, B.S. (1990), Seasonal integration and
Lehnhoff, Z.J. Miller, M.J. Brelsford, S. White, B.D. Maxwell, (2013), Relative canopy height influences wild oat (Avenafatua) seed viability, dormancy, and germination, Weed Sci., 2013 (61) : 564-569.
Licker R, Kucharik CJ, Dore T, Lindeman MJ, Makowski D,.(2013), Climatic impacts on winter wheat yields in Picardy, France and Rostov, Russia:1973-2010, Agricultural and Forest Meteorology, 176(21): 25-37.
Lu, H., Xie, H., He, Y., and Wu, Z. 2018. Assessing the impacts of land fragmentation and plot size on yields and costs: A translog production model and cost function approach, Agricultural Systems, Volume 161, March 2018, Pp: 81-88.
McFadden, K. Train,(2000). Mixed MNL models for discrete response, Journal of applied Econometrics, 41(2): 447-470.
Mihailović, B. Lalić, S. Malinović, I. Arsenić,(2004) The use of climate model for purposes of field and vegetable crops production, Field Veg. Crops Res., 40 (124): 35-44.
Moore, F.C., Baldos, U.L.C., Hertel, T.,(2017). Economic impacts of climate change on agriculture: a comparison of process-based and statistical yield models. Environ. Res. Lett. 12 (6), 1–9.
Petersen, J., Haastrup, M., Knudsen, L., Olesen, J.E.,( 2017), Causes of yield stagnation in winter wheat in Denmark. DJF Report Plant Science, Faculty of Agricultural Sciences, Aarhus University, Aarhus, Denmark. 97(14): 47-59.
Piñera-Chavez F.J, Berry P.M, Foulkes M.J, Molero G., (2019), Avoiding lodging in irrigated spring wheat Genetic variation of stem and root structural properties. Field Crops Research, 196(5):64-74.
Qin walter, S. Peter, R,. (2006), Impact of tillage on maize rooting in a Cambisol and Luvisol in Switzerland, Soil Till. Res., 85 (26): 50-61.
Rahimia,j, A. Khalilia, J. Bazrafshan, L., (2014), Estimation of effective precipitation for winter wheat in different regions of Iran using an Extended Soil-Water Balance Model, Desert, 19(2): 91-98.
Reeve, J B Endelman, B. E Miller, D J Hole,. (2012),Residual effects of compost on soil quality and dryland wheat yield sixteen years after compost application, Soil Sci Soc Am J, 76 (342): 278-285.
Scheaffer, R.L., Mendenhall, W., Ott, R.L., and Gerow, K.G.,(2012), Elementary survey sampling. 7th edition,USA, Boston, MA, USA: Cengage Learning., 45-58.
Song, J.R. Guo, Z.P. Zhang, T.J. Kou, A.X. Deng, C.Y. Zheng, J. Ren, W.J. Zhang., (2013), Impacts of planting systems on soil moisture: soil temperature and corn yield in rainfed area of Northeast China, Eur. J. Agron., 50 (201): 66-74.
Staben, F, Bezdicek, L Smith, F Fauci,. (1997), Assessment of soil quality in conservation reserve program and wheat-fallow soils, Soil Sci Soc Am J, 61 (127): 124-130.
Stute, A. Clement, G. Lohmann, (2018). Global climate models: past, present, and future, Proc. Natl. Acad. Sci., 98 (19): 10529-10530.
Slingo, K. Bates, N. Nikiforakis, M. Piggott, M. Roberts, L. Shaffrey, P.L. Weller, M., (2016). Developing the next-generation climate system models: challenges and achievements, Philos. Trans. Math. Phys. Eng. Sci., 367 (116): 815-831.
Meng, R. Carew, W. Florkowski, A. Klepacka, (2017).Analyzing temperature and precipitation influences on yield distributions of canola and spring wheat in Saskatchewan, J. Appl. Meteorol. Climatology, 56 (4): 897-913.
Tao F.L, Zhang Z, Xiao D.P, Zhang S, RoÈ tter RP, Shi WJ,. (2014), Responses of wheat growth and yield to climate change in different climate zones of China, 1981-2009. Agricultural and Forest Meteorology, 189(190): 91-104.
Vigini M. C., Fazey I., Reed M. S., Stringer L. C., Robinson G. M., Evely A. C.,(2017), Integrating Local and Scientific Knowledge for Environmental Management, Journal of Environmental Management, 7(91): 12-27.
Wang, J.A. Palta, C. Wei, Y. Chen, X. Deng., (2018), Nitrogen fertilization improved water-use efficiency of winter wheat through increasing water use during vegetative rather than grain filling Agric. Water Manage., 197 (8): 41-53.
Wang, S. Gong, D. Xu, Y. Yu, Y. Zhao,. (2013), Impact of drip and level-basin irrigation on growth and yield of winter wheat in the North China plain, Irrig. Sci, 31(28): 1025-37.
Wu, Z. Liu, M. and Davis, J., ( 2005), Land consolidation and productivity in Chinese household crop production. China Economic Review, 16(1): 28-49.
Yalew, A. van Griensven, M.L. Mul, P. van der Zaag, (2016), Land suitability analysis for agriculture in the Abbay basin using remote sensing, GIS and AHP techniques, Model. Earth Syst. Environ., 2 (216): 101.
Yin, G. Chen, Q. Chai, Y. Guo, F. Feng, C. Zhao, A. Yu, C. Liu., (2017), Effect of tillage and straw retention mode on seedling emergence and yield of spring wheat in the Hexi Irrigation Area Chinese J. Eco-Agric., 25 (20): 180-187.
Yolcu, O. Cetin.,(2015), Nitrogen fertigation to improve nitrogen use efficiency and crude protein on silage corn, Turk J. Field Crops, 20 (215): 233-241.
Yu, C.X. Han, X. Xing Yan, X.H. Li, G.L. Jiang, Y.M. Yan, . (2013), Rapid characterization of wheat low molecular weight glutenin subunits by ultra-performance liquid chromatography (UPLC), J. Agric. Food Chem., 61 (23): 4026-4034.
Zhang, J.W. Tang, J. Yan, Y.L. Zhang, Y. Zhang, X.C. Xia, Z.H. He,. (2009), The gluten protein and interactions between components determine mixograph properties in an F6 recombinant inbred line population in bread wheat, J. Cereal Sci., 50 (49): 219-226. Zhao J.F, Zhang Y.H, Qian Y.L, Pan Z.H, Zhu Y.J, Zhang Y,(2016), Coincidence of variation in wheat yield and climate in northern China. Science of the Total Environment, 573: 965-973.