Spatial-statistical analysis of rice, wheat and barley variability in the southern coast of the Caspian Sea

Document Type : Research Paper

Authors

1 PhD. Student, Department of Physical Geography, Faculty of Geography, University of Tehran, Tehran, Iran.

2 Professor, Department of Physical Geography, Faculty of Geography, University of Tehran, Tehran, Iran.

3 Associate Professor, Department of Physical Geography, Faculty of Geography, University of Tehran, Tehran, Iran.

4 Assistant Professor Department of Physical Geography, Faculty of Geography, University of Tehran, Tehran, Iran.

5 Assistant Professor, Department of Physical Geography, Faculty of Geography, University of Tehran, Tehran, Iran.

6 Assistant Professor, Department of Agro ecology, Environmental Sciences Research Institute, Shahid Beheshti University, G.C., Tehran, Iran.

Abstract

Climatic and regional conditions have provided a good environment for agricultural development, especially in the Caspian Sea provinces. The purpose of this study is to identify the effect of climate variables on spatial analysis of grain yield and Grain cultivation capability in the southern coast of the Caspian Sea. Then, using important functions of spatial statistics including moron index and hot spots analysis of spatial patterns of rice, wheat and barley yields on the southern coast of the Caspian Sea during the statistical period of 2000-2016 were investigated. According to the results of Moran index analysis, it was determined that the yield of rice, wheat and barley were positive and close to one in the study period, indicating the clustering of the spatial distribution of the yield of the products under study. Also, based on the results of Local Indicators of Spatial Association and the analysis of hot spots, high value values or positive spatial correlation of rice yield were mainly found in Mazandaran province and high values or positive spatial correlation of wheat yield in southern parts of Golestan province and limited parts From Mazandaran Province. For yield of barley, the most areas with high positive spontaneous autocorrelation (hot spots) are mainly confined to Babolsar and Joybar cities of Mazandaran province at confidence level of 99%, Babol in 95% confidence level and Aliabad city Located in Golestan province at a confidence level of 90%. Low value of wheat and barley yields were found in the eastern and western parts of Gilan province at 99, 95 and 90 percent confidence levels.

Keywords

References

  1. Allahyari, M.S., Keshavarz, F., Azarmi Sehsari, z., khayati, M., 2013. Factors affecting the non-acceptance of cultivating high-yielding rice cultivars among farmers in Gilan province. Agricultural Extension and Education Research.4, 99-122.
  2. Akossou, A., Attakpa, E., Fonton, N., Sinsin, B., Bosma, R., 2016. Spatial and temporal analysis of maize(Zea mays) crop yields in Benin from 1987 to 2007. Agricultural and Forest Meteorology.220, 177- 189.
  3. Asadi, M. and Karami, M., 2017. Representation of Temperature Variability in Fars Province Using Spatial Statistics. Geographical Researches Quarterly. 1, 64-75.
  4. Azizi, G., Roshani, M., 2008. Using Mann-Kendall Test to Recognize of Climate Change in Caspian Sea Southern Coasts. Physical Geography Research Quarterly. 64., 13-28.
  5. Bakhshandeh, E., Fathi, N., Pirdashti, H., Nasiri, M., 2017. Effect of weather temperature and solar radiation on grain yield and yield components of rice under different local climates in Mazandaran province. Journal of Crops Improvement. 1, 163-176.
  6. Bannayan, M., Mousavi-Baygi, M., Ashraf, B., AsadiOskuei, E., 2016.Assessment of climatic indices limiting rained wheat yield. Ecological Indicators.62, 298–305.
  7. Bay, N., Montazeri, M., Gadnomkar, A., Ataei, H., 2012. The Study of Potential of Dry Farming Wheat Cultivation in Golestan Province by Using Geographic Information System (GIS). Geographical Planning of Space Quarterly Journal.4, 19-42.
  8. Dastan, S., Yousefian, M., Soltani, A., Ajam Norouzi, H., 2018. Estimation of yield gap in local rice cultivars by using CPA and BLF methods(Case study: Mazandaran province, Sari region). Journal of Crop Production Research. 3, 255-288.
  9. Davargar, N., Zare, A., Shakori, M., Rezaei, L., Kavosi, M., Shiekh Eslam, H., Shahnazari, M., Kohneh, E., Shirinfekr, A., Bonyadi, I., Adibi, S., Moshir, E., Khodashenas, A., Shokri, H., Darighgoftar, F., Rahimi, A., Agili, A., 2015. Fertility Status of Paddy Soils in Guilan Province. Land Management Journal. 1, 1-13.
  10. Gornott, Ch. and Wechsung, F., 2016. Statistical regression models for assessing climate impacts on crop yields: A validation study for winter wheat and silage maize in Germany. Agricultural and Forest Meteorology.217, 89–100.
  11. Hajjarpoor, A., Kashiri, H., Soltani, A., Ainehband, A., Nazeri, M., Zienali, E., 2017. Determination of the optimum managements ranges in order to increasing wheat yield in Golestan province. Journal of Crops Improvement. 3, 577-590.
  12. Hataminezhad, H., Poorahmad, A., Mansourian, H., Abbas Rajaei, S., 2014. Spatial Analysis of Quality of Life Indicators in Tehran City. Human Geography Research Quarterly. 4, 29-56.
  13. Homaee, M., Sadooghi, L., Noroozi, A., Asadi Kapourchal, S.,2017. Estimating rice yield using VSM model and satellite images in Guilan province. Cereal Research. 3, 397-410.
  14. Jin, G., Li, z., Deng, X., Yang, J., Chen, D., Li, W., 2018.An analysis of spatiotemporal patterns in Chinese agricultural productivity between 2004 and 2014. Ecological Indicators.62, 1-10.
  15. Kamkar, B., Badsar, M., Soltani, A., Abdi, O., 2017. Yield gap estimation in wheat-grown fields using GIS and RS approach and SSM model (A case study: Qaresso basin, Gorgan, Iran). Cereal Research. 2, 195-215.
  16. Kazemi, H., Tahmasebi Sarvestani, Z., Kamkar, B., Shataei, S., Sadeghi, S., 2014. Agro-Ecological Zoning of Golestan Province Lands for Soybean Cultivation Using Geographical Information System (GIS). Journal of Agricultural Science and Sustainable Production. 4, 21-40.
  17. Khaledian, M., Zare, N., Pirmoradian, N., Rezaei, M., 2015. Assessment of rice yield under different irrigation treatments over a long-term weather data with CropSyst model. Water Management in Agriculture. 1, 49-56.
  18. Koocheki, A., Nassiri Mahallati, M., Mansoori, H., Moradi, R., 2016. Effect of Climate and Management Factors on Potential and Gap of Wheat Yield in Iran with Using WOFOST Model. Iranian Journal of Field Crops Research.2, 244-256.
  19. Mansoori, H., Nassiri Mahallati, M., Moradei, R., Koocheki, A., 2014. Assessing Sustainable Agriculture Development Status in Iran and Offering of Sustainability Approaches. Journal of Agricultural Science and Sustainable Production. 4, 179-197.
  20. Lucyanne Santos, A.M., Eyji Sano, E., Luis Bolfe, E., Nascimento Santos, J.F., Sales dos Santos, J., Brito Silva, F.,2019. Spatiotemporal dynamics of soybean crop in the Matopiba region, Brazil(1990–2015). Land Use Policy.80, 57-67.
  21. Mahmoudan, S., kamkar, B., abdi, O., bagherani, N., 2017. Comparison of wheat yield between common and modern management wheat cropping systems using Geographical Information System approach. Journal of Crop Production. 2, 178-198.
  22. Mirzaei, R., Nadian, M., Soltani Mohammadi, S., 2018. Application of Moran’s I Autocorrelation in Spatial-Temporal Analysis of PM2.5 Pollutant(A case Study: Tehran City). Journal of Environmental Health Engineering. 3, 197-213.
  23. Mohammadi, H., Azizi, G.H., Rabbani, F., 2017, Long-term prediction of the climate variables in northern shore of Iran on uncertainty of global climate models. Journal of Geographic Space. 56, 93-113.
  24. Mohammadi, Y., Shalalvand, M., Rezapour, K. (2018). Determining an Optimal Agronomic Cropping Pattern in Productive Units by analyzing the Regional and National Comparative Advantages. Iranian Journal of Agricultural Economics and Development Research, 49(4), 719-734
  25. Mosaedi, A., Kahe, M., 2008. The Assessing Precipitation Effects on Yield Productions of Wheat and Barley in Golestan Province. J. Agric. Sci. Natur. Resour. 4, 206-218.
  26. Parchomenko, A. and Borsky, S., 2018. Identifying phosphorus hot spots: A spatial analysis of the phosphorus balance as a result of manure application. Journal of Environmental Management.214, 137-148.
  27. Pirdashti, H., Aghaeipour, N., Zavareh, M., Asadi, H., Bahmanyar, M.A., 2018. Yield gap analysis of rice in relation to soil properties in Foumanat plain. Journal of Crop Production. 4., 159-172.
  28. Roshani, G. and Gharanjiki, A., 2015. Digital mapping of soil fertility for agricultural service centers of Golestan province using Kriging method. Journal of Agricultural Engineering. 2, 87-99.
  29. Rostaei, SH., Karim Zadeh, H., Zadvali, F., 2018. A comparative study of the use of classical statistical analysis and spatial statistics to measure the extent of urban poverty (Case study: Tabriz Metropolitan). Journal Management System. 31,153-166.
  30. Saito, K., Dieng, I., Toure, A., Somado, E., Wopereis, M., 2015. Rice yield growth analysis for African countries over 1960–2012. Global Food Security. 5, 62-69.
  31. Salami, H., Mohtashami, T. (2014). The projection model of Iran’s crop production in 2025. Iranian Journal of Agricultural Economics and Development Research, 45(4), 585-599.
  32. Shiravand, H. and Hashemi, M.N., 2016. Study the effects of climate change on sustainable national security. National Conference on passive Defense& Sustainable Development, 3th-4th October, Tehran, Iran. pp. 691- 703.
  33. Sotodeh, F. and Alijani, B., 2015. The Relationship between Spatial Distribution of Heavy Precipitation and Pressure Patterns in Guilan Province. Journal of Spatial Analysis Environmental Hazards. 1, 63-73.
  34. Zareabyaneh, H., Bayatvarkeshi, M., 2014. Statistical Analysis of Long-Term Trend of Performance, Production and Cultivated Area of 17 Field Crops Khorasan Razavi Province. Iranian Journal of Field Crops Research. 3, 403-416.
Iranian Journal of Agricultural Economics and Development Research
Volume 53, Issue 3
January 2022
Pages 627-645

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