پهنه‌بندی مناطق مستعد کشت گیاهان دارویی در استان قم با استفاده از مدل تحلیل سلسله مراتبی (AHP)

نوع مقاله : علمی - پژوهشی

نویسندگان

گروه مهندسی منابع طبیعی، دانشکده مهندسی کشاورزی و منابع طبیعی، دانشگاه هرمزگان، بندر عباس، ایران.

چکیده

رویکرد روز افزون استفاده از گیاهان دارویی و فرآورده­های حاصل از آن، نقش این گیاهان را در چرخه اقتصاد جهانی پررنگ­تر کرده است. به­طوری­که مصرف رو به تزاید آن تنها اختصاص به کشورهای در حال توسعه نداشته، بلکه یکی از عوامل مهم بهداشتی کشورهای پیشرفته نیز محسوب می­گردد. این تحقیق با هدف پهنه­بندی مناطق مستعد کشت گونه­های گیاهی دارویی و با استفاده از مدل تصمیم­گیری چند معیاره تحلیل سلسله مراتبی (AHP) در استان قم انجام گردید. به­همین ­منظور، با غربالگری معیارها و گزینه­ها، نه معیار شامل: ارتفاع از سطح دریا، شیب زمین، دمای حداکثر مطلق سالانه، دمای حداقل مطلق سالانه، بافت خاک، عمق خاک، EC آب، دسترسی به منابع آب و کاربری اراضی و هفت گزینه شامل: آویشن باغی، اسطوخودوس، بابونه آلمانی، بادرنجبویه، به­لیمو، رازیانه و رزماری با نظرسنجی از خبرگان آشنا با گیاهان دارویی، انتخاب شد. با استفاده از مدل­ AHP، وزن هرکدام از معیارها با مقایسه زوجی بین آن­ها بر اساس اطلاعات پرسش‌نامه­ای و با نرخ ناسازگاری 01/0 و با استفاده از نرم‌افزار Expert Choice تعیین گردید. با توجه به وزن نسبی که به هرکدام از لایه­های نه­گانه در مرحله وزن­دهی در مدل AHP تعلق گرفت، در محیط نرم‌افزار GisArc در هر یک از لایه­ها، اعمال گردیده و از طریق الگوریتم Weighted overlay در جهت هم‌پوشانی کردن لایه­ها استفاده گردید و نقشه پهنه­بندی استان قم به لحاظ نواحی مستعد کشت گیاهان دارویی برای هریک از هفت گونه گیاهی دارویی مورد نظر، تهیه شد. نقشه نهایی در چهار طبقه یا کلاس محدودیت، شامل: بدون محدودیت، محدودیت کم تا متوسط، محدودیت متوسط تا زیاد و محدودیت زیاد، طبقه­­بندی گردید. نتایج نشان داد که در میان معیارهای پهنه­بندی مناطق مستعد کشت گونه­های گیاهی دارویی در استان قم، بیشترین وزن نسبی متعلق به معیار EC آب با 3/30 درصد و کمترین وزن نسبی مربوط به معیار شیب زمین با سه درصد بوده است. پس از تولید نقشه­های پهنه­بندی هم، مشخص شد که در مجموع، برای مناطق مستعد کشت هفت گونه‌ گیاهی دارویی مورد مطالعه، به­طور میانگین: 66/8 درصد مساحت استان در طبقه یک (بدون محدودیت)، 38/6 درصد در طبقه دو (محدودیت کم تا متوسط)، 71/12 درصد در طبقه سه (محدودیت متوسط تا زیاد) و 97/71 درصد در طبقه چهار (محدودیت زیاد) واقع شده است.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Zoning of areas susceptible to cultivation of twenty medicinal plant species in Qom province using analytic hierarchy process model (AHP)

نویسندگان [English]

  • Mohammah mahdi Fattahi
  • Rasool Mahdavi
  • Marzieh Rezaei
  • Yahya Esmaeilpour
Department of Natural Resources Engineering, Faculty of Agricultural and Natural Resources Engineering, Hormozgan University, Bandar Abbas, Iran.
چکیده [English]

Introduction                 
  The increasing use of medicinal plants and their products has highlighted the role of these plants in the global economic cycle. As its increasing consumption is not only allocated to developing countries, but also is one of the important health factors in developed countries. The aim of this study was to zoning areas prone to cultivation of medicinal plant species and using the Analytic Hierarchy Process (AHP) model in Qom province.
Materials and Methods
   For this study, by screening the criteria and options, 9 criteria were selected, include: (Elevation, Slope, Absolute maximum annual temperature, Absolute minimum annual temperature, Soil texture, Depth of soil, EC water, Access to water resources and Land use) and 7 options include: Thymus vulgaris, Lavandula angustifolia, Maticaria chamomilla, Melissa officinalis, Aloysia citrodora, Foeniculum vulgare and Rosmarinus officinalis. Using AHP model, the weight of each criterion was determined by pairwise comparison between them based on questionnaire information with a mismatch rate of 0.01 and using Expert Choice software. According to the weight assigned to each of the nine layers in the weighting stage in the AHP model, in the ArcGIS software environment in each of the layers, applied through the Weighted overlay algorithm and also for Operation Assurance The Raster Calculator algorithm was used to overlap the layers and the zoning map of Qom province in terms of areas prone to cultivation of medicinal plants was prepared for each of the 7 species of medicinal plants. The final map was classified into four categories or constraint classes, including: No constraints, low to medium constraints, medium to high constraints and high constraints.
Results and Discussion
  Water shortage crisis is a threat; but by changing the cultivation pattern, it can be turned into an opportunity. Due to the hot and dry climate in the region, the cultivation of medicinal plants in areas such as Qom where the environmental and climatic conditions are stressful, can be much more suitable than the cultivation of cropsfrom an economic point of view. It is also cost-effective and has more added value. On the other hand, lack of complete knowledge about the various aspects of planting, holding and harvesting of medicinal plants from a scientific and technical point of view and the lack of a stable and reliable market for selling herbal medicinal products and continuous interaction between producers and consumers are some of the problems in this sector. The results showed that among the zoning criteria, the highest weight belonged to the EC water criterion with 30.3% and the lowest weight belonged to the land slope criterion with 3%. Is. According to the results obtained from the weighting of zoning criteria, in which more than half of the weight of 9 criteria belong to 2 criteria related to water, namely EC water with 30.3% and access to water resources with 23.3%. Percentage can be attributed to the importance and special position of water (both qualitatively and quantitatively) for the cultivation of medicinal plant species in the region in question, namely Qom province, where the predominant climate is arid and desert areas. After the production of zoning maps, it was found that in total, for areas susceptible to cultivation of 7 studied medicinal plant species, on average: 8.66% of the area in the first floor (without restrictions), 6.38 Percent is located in the 2nd floor (low to medium limit), 12.71% is in the 3rd floor (medium to high limit) and 71.97% is in the 4th floor (high limit).
Conclusion
  The results showed that among the zoning criteria for areas susceptible to cultivation of medicinal plant species in Qom province, the highest weight belonged to the EC water criterion with 30.3% and the lowest weight belonged to the land slope criterion with 3%. After generating the zoning maps, it was found that in total, for areas susceptible to cultivation of 7 studied medicinal plant species, on average: 8.66% of the area in the first floor (without restrictions), 6.38 Percent is located in the 2nd floor (low to medium limit), 12.71% is in the 3rd floor (medium to high limit) and 71.97% is in the 4th floor (high limit).

کلیدواژه‌ها [English]

  • Couple comparison
  • Incompatibility rate
  • Medicinal Plants
  • Multi-criteria decision making
Abdolmohammadi, M.H., 2003. Collection and identification of medicinal plants in Qom province, Final Report of Research Plan, Agricultural Reserches, Education and Extension Organization Publications.
Aczel, J., and Saaty, T.L., 1983. Procedures for synthesizing ratio judgements. Journal of Mathematical Psychology 27: 93-102. https://doi.org/10.1016/0022-2496(83)90028-7
Aghajani, A., Bidabadi, F.S., Joolaei, R., and Keramatzadeh, A., 2013. Managing cropping patterns agricultural crops of Iran. International Journal of Agriculture and Crop Sciences 5: 596-611.
Ahmadi, K., Ebzadzadeh, H.R., Hatami, F., Hosseinpour, R., and Abdeshah, H., 2018. Agricultural census of 2016, volume 3, Ministry of Agricultural Jihad, Deputy of planning and economics, Information Technology Center and Communications. (In Persian)
Baltar, A.M., and Fontance, D.G., 2008. Use of multiobjective particle swarm optimization in water resources management. Journal of Water Resources Planning and Management 134: 257-265. DOI:10.1061/(ASCE)0733-9496(2008)134:3(257).
Beigbabayi, B., and Azadi Mobaraki, M., 2012. Uzing AHP modeling and GIS to evaluate the suitability of autumn canola in Ardabil province. Annals of Biological Researches, 3(5): 2307-2317.
Chen, H., Liu, G., Yang, Y., Ye X.F., and Shi, Z., 2010. Comprehensive evalution of tobacco ecological suitability Henan province based on GIS. Agricuture Science in China 9(4): 583-592. https://doi.org/10.1016/S1671-2927(09)60132-2.
Deanpanah, G., 2014. Survey of rural development level with TOPSIS technique (Case study: Aslanduz-Parsabad section). Journal of Geography and Planning 18(50): 175-188. https://doi.org/ 10.22059/jhgr.2017.61037
Dury, J., Garcia, F., Reynaud, A., and Bergez, J.E., 2013. Cropping-plan decision-making on irrigated crop farms: A spatio-temporal analysis. European Journal of Agronomy 50: 1-10. DOI:10.1016/j.eja.2013.04.008.
 Ebzadzadeh, H.R., Ahmadi, K., Mohammadnia, A., Shahriar, Abbasataghani, R., Abbasi, M., and Yari, S., 2018. Agricultural census of 2016, volume 2, Ministry of Agricultural Jihad, Deputy of planning and economics. Information Technology Center and Communications. http://amar.maj.ir/Portal/File/ShowFile.aspx?ID=d6a3d890-3510-4bf1-
b0ee-1377027834c1. (Persian)
Fattahi, M.M., 2008. Characteristics of Qom Province, Geographically, Natural and Historically. Zemzemeh Zendegi Publications, 400 p. (In Persian)
Ghodsipour, S.H., 2016. Hierarchical Analysis Process (AHP). Amirkabir University of Technology Publications, 222 p. (In Persian)
Gill, M.K., Kaheil, Y.H., Khalil, McKee, M., and Bastidas, L., 2006. Multiobjective particle swarm optimization for parameter estimation in hydrology. Water Resources Research 42. https://doi.org/10.1029/2005WR004528.
Javaheri, M.A., Ramrodi, M., Azgharpour, M.R., Dehmardeh, Mghaemi, A., 2016. Agroclimatic zonation for evaluating autumn sugar beet sowing feasibility in Khorasan Razavi and Khorasan-e-Jonobi provinces. Journal of Sugar Beet 31(1): 17-31. (In Persian with English Summary)
Kashfi Bonab, A.R., 2010. Comparative economic advantage of cultivation and trade of medicinal plants in Iran and its value in world markets. Journal of Business Studies 8(44): 67-78. (In Persian with English Summary)
Kazemi, H., Tahmasebi Sarvestani, Z., Kamkar, B., Shattai, S., and Sadeghi, S., 2016. Development of optimal cropping pattern for Golestan province using geographic information system (GIS). Journal of Watershed Management Research 29(1): 88-106.
Opricovic, S., and Tzeng, G.H., 2004. Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research 156: 445–455. https://doi.org/10.1016/S0377-2217(03)00020-1.
Rahman, R., and Saha, S., 2008. Remote sensing, Spatial multi criteria evaluation (SMCE) and Analytical Hierarchy process (AHP) in optimal cropping pattern planning for a food prone area. Journal of Spatial Science 53(2): 161-177. https://doi.org/10.1080/14498596.2008.9635156.
Saaty, T.L., 1980. The analytical hierarchical process: Planning, priority setting resource allocation, NewYork. Mc Graw- Hill.
Saaty, T.L., and Vargas, L.G., 2001. Models, Methods, Concepts, and Applications of the Analytic Hierarchy Process. Kluwer Academic, 160 p.
Shabestari, M.H., and Banihabib, M.E., 2015. Ranking of agricultural water demand management strategies in arid areas using AHP and M-TOPSIS hybrid model. Journal of Water in Agriculture 29(1): 101-115. (In Persian with English Summary)
Shih, H.S., Shyur, H.J., and Lee, E.S., 2007. An extension of TOPSIS for group decision making. Mathematical and Computer Modelling 45: 801-813. https://doi.org/10.1016/j.mcm.2006.03.023.
Srdjevici, B., 2004. An Object multi-criteria evaluation of water management scenarios. Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 18(1), 35-54. DOI: 10.1023/B:WARM.0000015348.88832.52.
Tavari, M., Sukhkian, M.A., and Mirnejad, S.A., 2008. Identifying and prioritizing factors affecting human resource productivity using MADM techniques (Case study: One of the jeans garments manufacturing companies in Yazd province). Industrial Management (Management Knowledge) 1(1): 71-88. (In Persian with English Summary)
Vafaeinejad, A., 2016. Cropping Pattern Optimization by Using of TOPSIS and Genetic Algorithm Based on the Capabilities of GIS. Journal of Ecohydrology 3(1): 69-82. (In Persian with English Summary). https://doi.org/10.22059/ije.2016.59191
Vaziri, A., 2019. Identification and traditional uses of some medicinal plants in Jafarabad section of Qom province, Journal of Qom University of Medical Sciences 12(3): 87-95. (In Persian with English Summary)
Wang, T.C., and Chang, T.H., 2007. Application of TOPSIS in evaluating initial training aircraft under a fuzzy environment. Expert Systems with Applications 33 (4): 870-880. DOI:10.1016/j.eswa.2006.07.003
Wang, Y., Chen, Y., and Peng, S., 2011. A GIS framework for changing cropping pattern under different climate conditions and irrigation availability scenarios. Water Resources Management. 3090-25: 3073. https://doi.org/10.1007/s11269-011-9846-6
Zarei, H., Fathi, M.R., Karimi Zarchi, M., and Azizollahil, S., 2011. The application of Fuzzy TOPSIS approach to personnel selection for Padir Company: Iran. Journal of Management Research 3(2). : https://doi.org/10.5296/jmr.v3i2.663
Zavadskas, E.K., Vilutiene, T., Turskis, Z., and Tamosaitiene, J., 2010. Contractor selection for construction works by applying SAW-G and TOPSIS Grey techniques, Journal of Business Economics and Management 11: 34-55. doi: 10.3846  /  jbem. 2010.03.
CAPTCHA Image