Production Potential Prediction and Quantitative Land Suitability Evaluation for Irrigated Cultivation of Canola (Brassica napus), North of Shahrekord District

آب و خاک

Article 11, Volume 29, Issue 6, January 2015, Pages 1651-1661   

Document Type: Research Article

DOI: 10.22067/jsw.v29i6.37497

Authors

J. Givi^* ; A. Haghighi

Shahrekord University

Abstract

Introduction: Land suitability evaluation and land production potential estimation are considered as prerequisites for land use planning. In quantitative land suitability evaluation, land suitability is evaluated based on production per surface area unit. In this kind of evaluation, first, radiation thermal production potential is calculated, using different models such as FAO model. This potential is a genetical one which is not under influence of water, soil and management limitations. If soil limitations are exerted in the radiation thermal production potential, land production potential is resulted. The difference between the land production potential and the farmer yield is that the first one is not under influence of management limitation but the second one is under influence of management. Management level is determined based on management index. Canola (Brassica napus) is one of the oil crops which is cultivated in Iran and provides more than 90% of the required oil of the country. This crop is effective in the control of pests, diseases and weeds. Oil of the edible varieties of canola has good quality. After extraction of the oil, the remained meal is full of protein and is appropriate for animal nutrition. The aims of this research have been land production potential prediction and quantitative land suitability evaluation for irrigated canola in the north of Shahrekord. In the present research, for the first time, canola growth requirements were rated for different suitability classes.
Materials and Methods: The studied land with a total surface area of 25 hectares is located north of Shahrekord, in the vicinity of the previous Saman industrial district. The average annual precipitation in the studied area is 370 mm and the mean annual temperature is 13.1 OC. 19 soil profiles were dug and described. Leaf area index, harvest index and canola grain moisture percentage were measured. Farmer yield was also measured for each profile and economic data were collected. Physical and chemical analyses of the soils were done according to the standard laboratory methods. For the first time, canola growth requirements were rated for different suitability classes. In a next step, the measured land characteristics were matched with the canola growth requirements (except climatic requirements) and depending on the limitation level of the land characteristics for canola, a suitability rating was considered for each land property. By using these ratings in the second root and story formulas, soil index was calculated. Radiation-thermal production potential was calculated, using FAO model, considering temperature, solar radiation, leaf area index and harvest index limitations. Land production potential was determined by multiplication of the radiation-thermal production potential and the soil index. Margin yield was calculated by dividing total costs to the price of one kilogram of canola in the market. The limits between quantitative land suitability classes of S1 and S2, S2 and S3 and S3 and N were considered to be 75% of the radiation-thermal production potential, 140% and 90% of the marginal yield, respectively. Management index was calculated by dividing the farmer yield to the land production potential. Management index of 0.75 and 0.50 was considered respectively to be the limits between management levels of high and intermediate and intermediate and low. To evaluate the accuracy of the used methods, the correlation between the land production potential and the farmer yield was investigated.
Results and Discussion: Canola radiation-thermal production potential was calculated as 7603 kg. ha.-1; mean land production potentials, using second root and story formulas were predicted respectively, as 3214 and 2291 kg. ha.-1 and mean farmer yield was measured as 1943 kg. ha.-1. Management level was determined as high to intermediate. The marginal yield was calculated as 2025 kg. ha.-1 The results of this study showed that 59 and 6 percent of the land is marginal (S3) and moderated (S2) suitable respectively. 35 percent of them are not suitable (N). Use of the second root formula is more appropriate than story formula as far as land production potential calculation is concerned.
Conclusion: Moderate limitation of slope and carbonate content and moderate to severe limitation of gravels in the soils are the origin of a difference of 4400 to 5300 kg. ha.-1 between the radiation-thermal production potential and the land production potential. A difference of 348 to 1271 kg. ha.-1 between the land production potential and the average farmer yield is due to the high to intermediate management level. Land physical limitations and management level have caused more than 50% of the lands to have marginal suitability and 35% of them become non-suitable.

Keywords

Growth Requirements; management; Production Potential

References

1- Ashraf S. 2011. Estimating the land production potential for wheat, using GIS method. Australian Journal of Basic and Applied Sciences, 5(8): 118-122.

2- Chinene V.R.N. 1991. The Zambian land evaluation system (ZLES). Soil Use and Management, 7: 21-30.

3- Embrechts J., Poeloengan Z. and Sys C. 1988. Physical Land Evaluation: Using a parametric method applied to oilpalm plantation in north Sumatra, Indonesia. Soil Survey and Land Evaluation, 8: 111-122

4- Etedali S., Givi J. and Nouri M.R. 2012. Comparison between land production potential prediction for maize, using FAO and Wageningen models and assessment of management level for its cultivation around Shahrekord city. Journal of Water and Soil, 26 (4): 873-885. (in Persian with English abstract)

5- Fatehi Sh., Ghaderi J., and Seiedjalali A.R. 2007. Land suitability evaluation and production potential assessment for maize in Kermanshah plain. p.287. In Agriculture and Natural Resources Pardis (ed.). Proceedings of the 10th Iranian Soil Science Congress, 26-28 Aug. 2007. Agriculture and Natural Resources Pardis, Tehran University, Karaj. (in Persian)

6- Givi J. 1998. Qualitative, quantitative and economical land suitability evaluation and land production potential assessment for important field crops of the Felavarjan area, Isfahan province. Project report, Agricultural Economy and Planning Research Institute, Tehran. (in Persian )

7- Haghighi A. 2014. Qualitative land suitability evaluation and land production potential prediction for irrigated cultivation of canola in north Shahrekord district, using ALES program. M.Sc. thesis in soil science, Shahrekord University, Shahrekord. (in Persian with English abstract)

8- Khaghani R. 2009. Comparing FAO and Wageningen models for wheat production potential estimation in Harzandat area, Marand. p. 98. In Gorgan agricultural sciences and natural resources university (ed.). Proceedings of the 11th Iranian Soil Science Congress, 12-15 Jul. 2009. Gorgan Agricultural Sciences and Natural Resources University, Gorgan. (in Persian)

9- Khosraviani D. 2007. Soil survey and qualitative and quantitative land suitability evaluation for safflower cultivation in part of Sureshjan town, Chaharmahal va Bakhtiary province, using GIS. M.Sc. thesis in soil science, Shahrekord University, Shahrekord. (in Persian with English abstract)

10- Mosavati S.A. and Seiedjalali A.R. 2002. Land suitability assessment and land production potential estimation for wheat in saline soils of Golestan province. Technical publication No. 1136, Soil and Water Research Institute, Tehran. (in Persian)

11- Mozaffarian M., Nezami M., Zarrinkafsh M. and Jalali A. 2009. Land production potential estimation for irrigated wheat in south-west Tehran province. p. 444-445. In Gorgan agricultural sciences and natural resources university (ed.). Proceedings of the 11th Iranian Soil Science Congress, 12-15 Jul. 2009. Gorgan Agricultural Sciences and Natural Resources University, Gorgan. (in Persian)

12- Plant medicians of Tabriz University 2010. Available at http://www.tabrizugiyahpezeshki.blogfa.com/post-40.aspx

13- Rezai H. and Malakuti M.J. 2000. Method of oil seeds nutrient requirement supply. Part 2, optimum fertilizer use in canola plantation, technical publication No. 116, Soil and Water Research Institute, Tehran. (in Persian)

14- Rossiter D.G. 1996. A theoretical framework for land evaluation. Geoderma, 72:165-190.

15- Sohrabi A., Givi J., Malakuti M.J., Masihabadi M.H. and Seiedjalali A.R. 2003. Calculation of growth period duration and estimation of suger beet radiation-thermal production potential, using FAO model in Seilakhor plain, Lorestan. Suger beet journal, 19 (1): 67-79. (in Persian)

16- Sys C., Van Rant E. and Debaveye J. 1991. Land evaluation. Part 1, Agricultural Publications No 7. General Administration for Development Cooperation, Brussels, Belgium.

17- Tang H. 1993. Land suitability classification based on fuzzy set theory and modeling of land production potential of maize and winter wheat in different zones of China. Ph.D thesis, University of Gent. Gent, Belgium.

18- Zareeian GH.R. and Seiedjalali A.R. 2009. Quantitative land suitability evaluation and land production potential estimation for wheat in saline soils of Sarvestan plain (Fars province). p. 645-647. In Gorgan agricultural sciences and natural resources university (ed.). Proceedings of the 11th Iranian Soil Science Congress, 12-15 Jul. 2009. Gorgan Agricultural Sciences and Natural Resources University, Gorgan. (in Persian)