Оценка земель для выращивания маниоки (Manihot esculenta Crantz; Euphorbiaceae, Magnoliopsida) с использованием метода анализа иерархий, ГИС и дистанционного зондирования
https://doi.org/10.35885/1684-7318-2023-2-179-195
Аннотация
Цель настоящего исследования – оценить характеристики земель для выращивания однолетней маниоки с целью выбора пространственных свойств и параметров окружающей среды, необходимых для указания перспективных участков для выращивания маниоки. В соответствии с руководящими принципами ФАО была построена пространственная модель для оценки перспективных земель для устойчивого выращивания маниоки посредством интеграции метода AHP-GIS-Remote Sensing. Анализ земель показал, что земли с высоким потенциалом составляют 6101.1 га (8% от общей площади), они сосредоточены в средней и восточной части изучаемой территории. Эти районы имеют ограничения для выращивания маниоки из-за климатических условий: минимальная температура самого холодного месяца (P3 < 14°C), среднегодовое количество солнечных часов (P5 < 1500 ч) и ряд потенциальных факторов обеспечения качественной продукции (наиболее важные факторы – годовое количество осадков и рН почвы). Площади посевов маниоки сократились, но причина этого не зависела от физических условий окружающей среды. Возможно, на местных фермах играют важную роль ограничивающие факторы внутреннего рынка, устаревшие технологии переработки и низкая закупочная цена на сырую маниоку.
Об авторах
Т. Т. Н. Нгуен
Технический университет Ле Куи Дон
Вьетнам
Вьетнам
г. Ханой, ул. Хоанг Куок Вьет, д. 236
Т. Х. Тонг
Технический университет Ле Куи Дон
Вьетнам
Вьетнам
г. Ханой, ул. Хоанг Куок Вьет, д. 236
Список литературы
1. Adiele J. G. Growing Out of Hunger: Towards an Improved Understanding of the Water and Nutrient Limited Yield of Cassava. Doctoral Dissertation. Wageningen, Wageningen University, 2020. 150 p.
2. Adiele J. G., Schut A. G. T., van den Beuken R. O. M., Ezui K. S., Pypers P., Ano A. O., Giller K. E. A recalibrated and tested LINTUL-Cassava simulation model provides insight into the high yield potential of cassava under rainfed conditions. European Journal of Agronomy, 2021, vol. 124, pp. 126–242. https://doi.org/10.1016/j.eja.2021.126242
3. Akinwumiju A. S., Adelodun A. A., Orimoogunje O. I. Agro-Climato-Edaphic zonation of Nigeria for a cassava cultivar using GIS-Based Analysis of Data from 1961 to 2017. Scientific Reports, 2020, vol. 10, article number 1259. https://doi.org/10.1038/s41598-020-58280-4
4. Akano A. O., Dixon A. G. O., Mba C., Barrera E., Fregene M. Genetic mapping of a dominant gene conferring resistance to cassava mosaic disease. Theoretical and Applied Genetics, 2002, vol. 105, iss. 4, pp. 521–525. https://doi.org/10.1007/s00122-002-0891-7
5. Amarullah A., Indradewa D., Yudono P., Sunarminto B. H. Correlation of growth parameters with yield of two cassava varieties. Ilmu Pertanian (Agricultural Science), 2017, vol. 1, no. 3, pp. 100–104. https://doi.org/10.22146/ipas.10706
6. Anderson M. D., Rivera-Ferre M. Food system narratives to end hunger: Extractive versus regenerative. Current Opinion in Environmental Sustainability, 2021, vol. 49, pp. 18–25. https://doi.org/10.1016/j.cosust.2020.12.002
7. Boansi D. Effect of climatic and non-climatic factors on cassava yields in Togo: Agricultural policy implications. Climate, 2017, vol. 5, iss. 2, article number 28. https://doi.org/10.3390/cli5020028
8. Bravo M. R. Urbanization in the Philippines and Its Influence on Agriculture. In: M. Yokohari, A. Murakami, Y. Hara, K. Tsuchiya, eds. Sustainable Landscape Planning in Selected Urban Regions. Tokyo, Springer, 2017, pp. 97–110. https://doi.org/10.1007/978-4-431-56445-4_9
9. Burns A. E., Gleadow R. M., Zacarias A. M., Cuambe C. E., Miller R. E., Cavagnaro T. R. Variations in the chemical composition of cassava (Manihot esculenta Crantz) leaves and roots as affected by genotypic and environmental variation. Journal of Agricultural and Food Chemistry, 2012, vol. 60, iss. 19, pp. 4946–4956. https://doi.org/10.1021/jf2047288
10. Campo B. V. M., Hyman G., Bellotti A. Threats to cassava production: Known and potential geographic distribution of four key biotic constraints. Food Security, 2011, vol. 3, iss. 3, pp. 329–345. https://doi.org/10.1007/s12571-011-0141-4
11. D’haeze D., Deckers J., Raes D., Phong T. A., Loi H. V. Environmental and socio-economic impacts of institutional reforms on the agricultural sector of Vietnam: Land suitability assessment for Robusta coffee in the Dak Gan region. Agriculture, Ecosystems & Environment, 2005, vol. 105, iss. 1-2, pp. 59–76. https://doi.org/10.1016/j.agee.2004.05.009
12. Edet M. A., Tijani-Eniola H., Lagoke S. T. O., Tarawali G. Relationship of cassava growth parameters with yield, yield related components and harvest time in Ibadan, Southwestern Nigeria. Journal of Natural Sciences Research, 2015, vol. 5, iss. 9, pp. 87–92.
13. Eng J. ROC Analysis: Web-Based Calculator for ROC Curves. Baltimore, Johns Hopkins University, 2014. Available at: http://www.jrocfit.org (accessed 10 January 2023).
14. El-Sharkawy M. A. Physiological characteristics of cassava tolerance to prolonged drought in the tropics: Implications for breeding cultivars adapted to seasonally dry and semiarid environments. Brazilian Journal of Plant Physiology, 2007, vol. 19, iss. 4, pp. 257–286. https://doi.org/10.1590/S1677-04202007000400003
15. Feenstra G. W. Local food systems and sustainable communities. American Journal of Alternative Agriculture, 1997, vol. 12, iss. 1, pp. 28–36. https://doi.org/10.1017/s0889189300007165
16. Fischer G., Shah M. N., Tubiello F., Van Velhuizen H. Socio-economic and climate change impacts on agriculture: An integrated assessment, 1990–2080. Philosophical Transactions of the Royal Society B: Biological Sciences, 2005, vol. 360, iss. 1463, pp. 2067–2083. https://doi.org/10.1098/rstb.2005.1744
17. FAO Guidelines for Land-Use Planning. Rome, Food and Agriculture Organization of the United Nations, 1993.
18. General Statistics Office of Vietnam. Statistical Yearbook of Thanh Hoa Province. Statistical Publishing House, Vietnam, 2019 (in Vietnamese).
19. Ministry of Science and Published technology. ISO (TCVN) 8409:2012 by the Institute of Planning and Design of Agriculture – Ministry of Agriculture and Rural Development Editor. Directorate for Standards, Metrology and Quality appraisal, Ministry of Agriculture and Rural Development proposal, 2021.
20. Kinshella M. L. W. Consuming hunger: Experiences of cassava and development in a Coastal Tanzanian Village. Food, Culture & Society, 2015, vol. 17, iss. 3, pp. 377–393. https://doi.org/10.2752/175174414X13948130848025
21. Lamsal P., Atreya K., Ghosh M. K., Pant K. P. Effects of population, land cover change, and climatic variability on wetland resource degradation in a Ramsar listed Ghodaghodi Lake Complex, Nepal. Environmental Monitoring and Assessment, 2019, vol. 191, iss. 7, pp. 1–16. https://doi.org/10.1007/s10661-019-7514-0
22. MacCormac E. R. Review of: ‘Decision making for leaders: The analytical hierarchy process for decisions in a complex world’ by Thomas L. Saaty. The Engineering Economist, 1983, vol. 29, iss. 1, pp. 74–75. https://doi.org/10.1080/00137918308967693
23. Noerwijati K., Budiono R. Yield and yield components evaluation of cassava (Manihot esculenta Crantz) clones in different altitudes. Energy Procedia, 2015, vol. 65, pp. 155–161. https://doi.org/10.1016/j.egypro.2015.01.050
24. Okudoh V., Trois C., Workneh C., Schmidt C. The potential of cassava biomass and applicable technologies for sustainable biogas production in South Africa: A review. Renewable and Sustainable Energy Reviews, 2014, vol. 39, pp. 1035–1052. https://doi.org/10.1016/j.rser.2014.07.142
25. Papastergiadou E., Kagalou I., Stefanidis K., Retalis A., Leonardos I. Effects of anthropogenic influences on the trophic state, land uses and aquatic vegetation in a shallow Mediterranean lake: Implications for restoration. Water Resources Management, 2010, vol. 24, iss. 3, pp. 415–435. https://doi.org/10.1007/s11269-009-9453-y
26. Pereira J. M., Duckstein L. A multiple criteria decision-making approach to GIS-based land suitability evaluation. International Journal of Geographical Information Science, 1993, vol. 7, iss. 5, pp. 407–424. https://doi.org/10.1080/02693799308901971
27. Purnamasari R. A., Ahamed T., Noguchi R. Land suitability assessment for cassava production in Indonesia using GIS, remote sensing and multi-criteria analysis. Asia-Pacific Journal of Regional Science, 2019, vol. 3, iss. 1, pp. 1–32. https://doi.org/10.1007/s41685-018-0079-z
28. Rewlay-ngoen C., Papong S., Onbhuddha R., Thanomnim B. Evaluation of the environmental performance of bioethanol from cassava pulp using life cycle assessment. Journal of Cleaner Production, 2021, vol. 284, article number 124741. https://doi.org/10.1016/j.jclepro.2020.124741
29. Rouse J. W., Haas R. H., Schell J. A., Deering D. W. Monitoring Vegetation Systems in the Great Plains With ERTS. Washington, NASA special publication, 1974, vol. 351. 309 p.
30. Santisopasri V., Kurotjanawong K., Chotineeranat S., Piyachomkwan K., Sriroth K., Oates C. G. Impact of water stress on yield and quality of cassava starch. Industrial Crops and Products, 2001, vol. 13, iss. 2, pp. 115–129. https://doi.org/10.1016/S0926-6690(00)00058-3
31. Saaty T. L. Decision making with the analytic hierarchy process. International Journal of Services Sciences, 2008, vol. 1, iss. 1, pp. 83–98. https://doi.org/10.1504/IJSSci.2008.01759
32. Sharma P., Aggarwal P., Kaur A. Biofortification: A new approach to eradicate hidden hunger. Food Reviews International, 2017, vol. 33, iss. 1, pp. 1–21. https://doi.org/10.1080/87559129.2015.1137309
33. Vurro M., Bonciani B., Vannacci G. Emerging infectious diseases of crop plants in developing countries: Impact on agriculture and socio-economic consequences. Food Security, 2010, vol. 2, iss. 3, pp. 113–132. https://doi.org/10.1007/s12571-010-0062-7
34. Zemba A. A., Kefas J., Hamza A. Land suitability analysis for decision-making in cassava (Manihot Spp.) cultivation in southern part of Adamawa State, Nigeria. Global Journal of Agricultural Sciences, 2017, vol. 16, iss. 1, pp. 1–10. https://doi.org/10.4314/gjass.v16i1.1
35. Zhang J., Su Y., Wu J., Liang H. GIS based land suitability assessment for tobacco production using AHP and fuzzy set in Shandong province of China. Computers and Electronics in Agriculture, 2015, vol. 114, pp. 202–211. https://doi.org/10.1016/j.compag.2015.04.004
36. Zhu W., Lestander T. A., Örberg H., Wei M., Hedman B., Ren J., Xie G., Xiong S. Cassava stems: A new resource to increase food and fuel production. GCB-Bioenergy, 2015, vol. 7, iss. 1, pp. 72–83. https://doi.org/10.1111/gcbb.12112
Рецензия
При поддержке: Исследование выполнено при финансовой поддержке Совместного Российско-Вьетнамского Тропического научно-исследовательского и технологического центра (проект E1.4) в 2021 г.
Для цитирования:
Нгуен Т., Тонг Т. Оценка земель для выращивания маниоки (Manihot esculenta Crantz; Euphorbiaceae, Magnoliopsida) с использованием метода анализа иерархий, ГИС и дистанционного зондирования. ПОВОЛЖСКИЙ ЭКОЛОГИЧЕСКИЙ ЖУРНАЛ. 2023;(2):179-195. https://doi.org/10.35885/1684-7318-2023-2-179-195
For citation:
Nguyen T., Tong T. Assessment of lands for cassava (Manihot esculenta Crantz; Euphorbiaceae, Magnoliopsida) cultivation using the AHP-GISRemote Sensing technique. Povolzhskiy Journal of Ecology. 2023;(2):179-195. https://doi.org/10.35885/1684-7318-2023-2-179-195
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