Estimation of Potato (Solanum tuberosum L.) Yield Gap and Determining the Contribution of Water and Nitrogen Across Khorasan Razavi Province using Modeling Approach

Articles in Press

Document Type : Research Article

Authors

• M Jahan ¹
• M Noori ¹
• H. R Khazaei ¹
• M Nasiri mahalati ¹
• K Shojaei ²
• M, H Fallah ¹

¹ Department of Agrotechnology, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran

² Agriculture and Natural Resources Research and Education Center of Khorasan Razavi, Mashhad, Iran

10.22067/jcesc.2024.90184.1355

Abstract

Introduction
The growing human population, global warming, depletion of water and soil resources, and climate change make it imperative to reconsider food production methods in agricultural systems. Improving resource use efficiency and enhancing productivity are key strategies to address these challenges. Reducing the gap between the actual yield currently achieved on farms and the yield that could be achieved using the best environmentally compatible cultivars and the best water, soil and plant management practices is a key solution to overcome the challenge of feeding the world's growing population. The first step in addressing the yield gap is to determine how much and how it is distributed.
Materials and Methods
To estimate the potato (Solanum tuberosum L.) yield gap in Khorasan Razavi province and to determine the contribution of water and nitrogen to it, two separate field experiments were conducted based on randomized complete block design (RCBD) with water and nitrogen limitation conditions for potato cultivars in the city of Quchan during the growing season of 2018-2019. The first experiment was conducted with three irrigation levels of 100, 75, and 50% water requirement, and used two potato cultivars. The second experiment was conducted with four levels of nitrogen, including 0, 50, 100, and 150 kg of pure nitrogen, and also included two potato cultivars.
Results and Discussion
The results showed that increasing nitrogen fertilizer application improved many of the evaluated characteristics of two potato varieties. However, with the increase in nitrogen use, nitrogen use efficiency (productivity) decreased. The potential yield of potatoes in different regions of Khorasan Razavi province was estimated using the DSSAT model. The data obtained from one of the field experiments, including dry matter, leaf area, phenology (developmental stages), and yield, were used to calibrate the model. After determining the potential yield and estimating the yield gap, the contribution of water and nitrogen to the yield gap was identified. Based on the protocol provided by the Global Yield Gap Atlas, the province was clustered into three regions. Region 1 (R1) includes the cities of Quchan and Fariman; Region 2 (R2) comprises Golmakan, Neyshabour, Torbat-e Hydarie, Mashhad, and Dargaz, which lie between regions 1 and 3; and Region 3 (R3) includes the cities of Torbat-e Jam, Gonabad, Khaf, Kashmar, Sabzevar, Sarakhs, and Bardaskan. The model was calibrated and validated with the data obtained from the field experiment. Long-term weather data and average actual yield were collected for each station, and the potential yield in each station was simulated using the model. Then, the difference between the potential yield and the actual yield was calculated, and the yield gap was determined for each area. Afterward, using the model, the potential yield was recalculated under water and nitrogen limitation conditions, and the contribution of water and nitrogen to the yield gap was assessed.
Conclusion
In R1, the yield gap varied between 40.5 and 57.7 ton ha^-1. The average yield gap during 10 years was estimated at 48.8 and 31.7 ton ha^-1 for R1 and R2, respectively. According to the DSSAT model's results, R3 had a lower potential yield than the other two regions. The average contribution of water and nitrogen limitations to the potato yield gap in R1 and R2 was calculated. Accordingly, in R1, the impact of water and nitrogen limitations was 12.1 and 18 ton ha^-1, and in R2, it was 10.9 and 8.3 ton ha^-1, respectively. Although narrowing the yield gap depends on the climatic conditions of each region, selecting a compatible crop variety, optimizing planting date, and adopting appropriate plant density are among the most effective crop management strategies to reduce the yield gap, regardless of climatic differences.

Keywords

• Calibration and Validation
• DSSAT
• Food security
• Potential yield
• Zoning

Main Subjects

• Crop yield

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©2025 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source.

References

1. Alva, A. K., Ren, H., Moore, A. D. (2012). Water and nitrogen management effects on biomass accumulation and partitioning in two potato cultivars. American Journal of Plant Sciences, 3, 164-170. https://doi.org/10.4236/ajps.2012.31019
2. Arora, V. K., Nath, J. C., & Singh, C. B. (2013). Analyzing potato response to irrigation and nitrogen regimes in a sub-tropical environment using SUBSTOR-Potato model. Agricultural Water Management, 124, 69-76. https://doi.org/10.1016/j.agwat.2013.03.021
3. Ayas, S. (2013). The effects of different regimes on potato (Solanum tuberosum Hermes) yield and quality characteristics under unheated greenhouse conditions. Bulgarian Journal of Agricultural Science, 19(1), 87-95.
4. Bagheri, H. R., Gharineh, M. H., & Bakhshandeh, A. (2015). Agroecological zoning and gap analysis of potato yield using SUBSTOR-Potato simulation model and geographic information system in Chaharmahal-Bakhtiari province. Ph.D. Thesis, Faculty of Agriculture, Khuzestan University of Agriculture and Natural Resources, Ahvaz, Iran.
5. Bremner, J. M., & Mulvaney, C. S. (1982). Nitrogen-total. In Methods of Soil Analysis. Chemical and microbiological properties. A. L. Page, R. H. Miller, and D. R. Keeney eds. Soil Science Society of America: Madison, WI, USA, 2, 595–624.
6. Coates, J. (2013). Build it back better: Deconstructing food security for improved measurement and action. Global Food Security, 2(3), 188-194. https://doi.org/10.1016/j.gfs.2013.05.002
7. Deguchi, T., Iwama, K., & Haverkort, A. J. (2016). Actual and potential yield levels of potato in different production systems of Japan. Potato Research, 59, 207-225. https://doi.org/10.1007/s11540-016-9322-z
8. Devaux, A., Kromann, P., & Ortiz, O. (2014). Potatoes for sustainable global food security. Potato Research, 57, 185-199. https://doi.org/10.1007/s11540-014-9265-1
9. Dobermann, A., & Cassman, K. G. (2002). Plant nutrient management for enhanced productivity in intensive grain production systems of the United States and Asia. Plant and Soil, 247, 153-175. https://doi.org/10.1023/A:1021197525875
10. Doring, T. F., Brandt, M., Heß, J., Finckh, M. R., & Saucke, H. (2005). Effects of straw mulch on soil nitrate dynamics, weeds, yield and soil erosion in organically grown potatoes. Field Crops Research, 94(2-3), 238-249. https://doi.org/10.1016/j.fcr.2005.01.006
11. Fageria, N. K., & Baligar, V. C. (2005). Enhancing nitrogen use efficiency in crop plants. Advances in Agronomy, 88, 97-185. https://doi.org/10.1016/S0065-2113(05)88004-6
12. (2017). FAOSTAT. Food and Agriculture Organization of the United Nations. Food Security, 1(1), 5-7. Available in: http://faostat.fao.org/countryprofiles.
13. (2021). Potato. FAOSTAT database for agriculture.
14. Fallah-Ghalhari, Gh., Moosavi-Baygi, M., & Habibi-Nokhandan, H. (2000). Forecasting seasonal precipitation based on synoptic patterns using adaptive neural fuzzy inference system (ANFIS). Research on Natural Geographia, 66, 121-139. (In Persian)
15. Greenwood, D. J., Neeteson, J. J., & Draycott, A. (1985). Response of potatoes to N fertilizer: Dynamic model. Plant and Soil, 85, 185-203.
16. Hall, A. J., & Richards, R. A. (2013). Prognosis for genetic improvement of yield potential and water-limited yield of major grain crops. Field Crops Research, 143, 18-33. https://doi.org/10.1016/j.fcr.2012.05.014
17. Haverkort, A. J. (2014). Yield gaps and ecological footprints of potato production systems in Chile. Potato Research, 57, 13-31. https://doi.org/10.1007/s11540-014-9250-8
18. Hochman, Z., Gobbett, D., Horan, H., & Garcia, J. N. (2016). Data rich yield gap analysis of wheat in Australia. Field Crops Research, 197, 97-106. https://doi.org/10.1016/j.fcr.2016.08.017
19. Hoogenboom, G., Wilkens, P. W., Thornton, P. K., Jones, J. W., Hunt, L. A. & Imamura, D. T. (1999). Decision support system for agrotechnology transfer v3. 5. DSSAT Version, 3, 1-36. https://doi.org/10.1007/978-94-017-3624-4_8
20. IISD Report. (2012). Food Security and Climate Change Initiative. International Institute for Sustainable Development. https://www.iisd.org/system/files/publications/food_security_agriculture_financing.pdf
21. Jaggard, K. W., Qi, A., & Ober, E. S. (2010). Possible changes to arable crop yields by 2050. Philosophical Transactions of the Royal Society B: Biological Sciences, 365(1554), 2835-2851. https://doi.org/10.1098/rstb.2010.0153
22. Kamali, Gh., & Bazgir, S. (2009). Prediction of wheat yield using agrometeorological indices in some western areas of the Iran, Journal of Agricultural Sciences and Natural Resources, 15(2), 113-121
23. Koocheki, A., Nassiri-Mahallati, M., Mansoori, H., & Moradi, R. (2017). Effect of climatic and management factors on potential and gap of wheat yield in Iran using WOFOST Model. Iranian Journal of Field Crops Research, 15(2), 244-256. (in Persian with English abstract). https://doi.org/10.22067/gsc.v15i2.54278
24. Merlos, F. A., Monzon, J. P., Mercau, J. L., Taboada, M., Andradea, F. H., Halle, A. J., Jobbagy, E., Cassman, K. G., & Grassini, P. (2015). Potential for crop production increase in Argentina through closure of existing yield gaps. Field Crops Research, 184, 145-154. https://doi.org/10.1016/j.fcr.2015.10.001
25. Metzger, M. J., & Flanagin, A. J. (2013). Credibility and trust of information in online environments: The use of cognitive heuristics. Journal of Pragmatics, 59, 210-220. https://doi.org/10.1016/j.pragma.2013.07.012
26. Ministry of Agriculture. (2022). Review of harvest level statistics and production rate of 36 years of crops. Ministry of Agricultural Jihad, Planning and Economic Deputy. Information and Communication Technology Center. https://maj.ir also in: https://agrieng.org/1401
27. Mohammadi, A., Koocheki, A., & Nassiri-Mahallati, M. (2018). Evaluation of LINTUL1-POTATO Model for simulation of development stages and potential yield of spring-sown potato (Solanum tuberosum) in Iran. Journal of Agroecology, (in Persian with English abstract).
28. Neumann, K., Verburg, P. H., Stehfest, E., & Müller, C. (2010). The yield gap of global grain production: A spatial analysis. Agricultural Systems, 103(5), 316-326. https://doi.org/10.1016/j.agsy.2010.02.004
29. Rosegrant, M. W., Koo, J., Cenacchi, N., Ringler, C., Robertson, R. D., Fisher, M., & Sabbagh, P. (2014). Food security in a world of natural resource scarcity: The role of agricultural technologies. Washington, DC: International Food Policy Research Institute (IFPRI). 250 p.https://doi.org/10.2499/9780896298477
30. Mohammadi, A. (2020). Strategies for optimal agricultural management in delayed potato cultivation. Applied Science of Potato, 3(2), 27-34. (In Persian). Available Online at: https://pem.areeo.ac.ir/article_123326_be6943fb65aad7cc09abc77063059f50.pdf
31. Shahnazari, A., Liu, F., Andersen, M. N., Jacobsen, S. E., & T Jensen, C. R. (2007). Effects of partial root-zone drying on yield, tuber size and water use efficiency in potato under field conditions. Field Crops Research, 100(1), 117-124. https://doi.org/10.1016/j.fcr.2006.05.010
32. Shock, C. C., Feibert, E. G., & Saunders, L. D. (1998). Potato yield and quality response to deficit irrigation. Horticultural Science, 33, 655-659. https://doi.org/10.21273/HORTSCI.33.4.655
33. Sobhani, A. R., & Hamidi, H. (2013). Effects of water deficit and potassium on yield and water use efficiency of potato crop in linear sprinkler irrigation method (line source). Environmental Stress in Crop Sciences, 6(1), 1-15. (in Persian with English Abstract).
34. Svubure, O., Struik, P. C., Haverkort, A. J., & Steyn, J. M. (2015). Yield gap analysis and resource footprints of Irish potato production systems in Zimbabwe. Field Crops Research, 178, 77-90. https://doi.org/10.1016/j.fcr.2015.04.002
35. Taei, J. S., Ghanbari, A., Amiri, E., Ghaffari, A., Siahsar, B., & Ayoubi, S. (2013). Agroecological zoning of wheat in the Borujen Watershed: Rianfed and irrigated wheat cropping system evaluation. Journal of Agricultural Science and Sustainable Production, 22(4), 1-12. (in Persian with English abstract). Available Online at: https://sustainagriculture.tabrizu.ac.ir/article_801.html?lang=en
36. Tavakkoli-Kakhki, H. R. (2016). Zoning and evaluation of nitrogen use efficiency and nitrogen balance for wheat and corn cropping systems of Iran by using simulation model and GIS. Ph.D. Dissertation. the Ferdowsi University of Mashhad, Mashhad, Iran. 151 pp. (In Persian with English abstract).
37. Van Bussel, L. G., Grassini, P., Van Wart, J., Wolf, J., Claessens, L., Yang, H., & van Ittersum, M. K. (2015). From field to atlas: Upscaling of location-specific yield gap estimates. Field Crops Research, 177, 98-108. https://doi.org/10.1016/j.fcr.2015.03.005
38. Van Ittersum, M. K., Cassman, K. G., Grassini, P., Wolf, J., Tittonell, P., & Hochman, Z. (2013). Yield gap analysis with local to global relevance- a review. Field Crops Research, 143, 4-17. https://doi.org/10.1016/j.fcr.2012.09.009
39. Van Wart, J., van Bussel, L. G., Wolf, J., Licker, R., Grassini, P., Nelson, A., Boogaard, H., Gerber, J., Mueller, N. D., Claessens, L., & van Ittersum, M. K. (2013). Use of agro-climatic zones to upscale simulated crop yield potential. Field Crops Research, 143, 44-55. https://doi.org/10.1016/j.fcr.2012.11.023
40. Vos, J., & Van der Putten, P. E. L. (1998). Effect of nitrogen supply on leaf growth, leaf nitrogen economy and photosynthetic capacity in potato. Field Crops Research, 59(1), 63-72. https://doi.org/10.1016/S0378-4290(98)00107-5
41. Westermann, D.T. (2005). Nutritional requirements of potatoes. American Journal of Potato Research,82, 301–307. https://doi.org/10.1007/BF02871960
42. Willmott, C. J. (1982). Some comments on the evaluation of model performance. Bulletin of the American Meteorological Society, 63(11), 1309-1313.‏
43. Zebarth, B. J., Rees, H., Tremblay, N., Fournier, P., & Leblon, B. (2002). Mapping spatial variation in potato nitrogen status using the N Sensor. In XXVI International Horticultural Congress: Toward Ecologically Sound Fertilization Strategies for Field Vegetable Production. Acta Horticultura, 627, 267-273. https://doi.org/17660/ActaHortic.2003.627.34
44. Zhang, B., Li, F. M., Huang, G., Cheng, Z. Y., & Zhang, Y. (2006). Yield performance of spring wheat improved by regulated deficit irrigation in an arid area. Agricultural Water Management, 79(1), 28-42. https://doi.org/10.1016/j.agwat.2005.02.007