Estimating the Yield Gap of Irrigated Wheat)Triticum aestivum L.( in Lorestan Province, Iran, the Modeling Approach

بوم شناسی کشاورزی

Article 11, Volume 16, Issue 2 - Serial Number 60, June 2024, Pages 403-420   

Document Type: Research Article

DOI: 10.22067/agry.2023.81319.1148

Authors

Kourosh Heidari¹; Mashallah Daneshvar^{* 1}; Sajjad Rahimi-Moghaddam¹; Aliheidar Nasrollahi²

¹Department of Production Engineering and Plant Genetic, Faculty of Agriculture, Khorramabad, Iran

²Department of Water Engineering, Faculty of Agriculture, Khorramabad, Iran

Abstract

Introduction
Removing the gap between the yield that is currently obtained by farmers and the yield that can be obtained by using the best water, soil, and crop management practices (yield gap) is the key solution to overcoming the nutritional challenge of the growing world population. Wheat has played an important role in the economy and food security of the world over the history. Considering the importance of the wheat crop in food security and human feeding, as well as the importance of Lorestan province in producing wheat crop in Iran, the current research was carried out using the modeling method in order to estimate the yield gap of irrigated wheat agro-ecosystems of Lorestan province.
Materials and Methods
The current research was conducted in 6 locations in Lorestan province, Iran (Aleshtar, Aligudarz, Borujerd, Khorramabad, Kuhdasht, and Pol-e Dokhtar). To evaluate the APSIM-wheat model for the Chamran cultivar, some independent field experiments were used under different treatments, including planting date, irrigation, and nitrogen regimes. nRMSE, d-index, and MBE indices were used to evaluate the crop model. Then, the management, soil, and climate data of the studied locations were collected. To find the most optimal sowing date, an initial simulation experiment set was performed. After obtaining the optimal sowing date for different locations, the attainable yield (85% of the potential yield) was simulated. Finally, from the difference between attainable yield and actual yield, the total yield gap for the locations was obtained. Also, the contribution of different management practices, including nitrogen, irrigation, and other reducing and limiting factors, was calculated from the total yield gap. In the current research, OriginPro software was used for all statistical analysis and drawing of figures.
Results and Discussion
The results of the model calibration showed that the APSIM-wheat model was able to simulate the days to flowing, biomass, and grain yield accurately. The normalized root mean square error for days to flowering, biomass, and grain yield was 5.13, 5.29, and 7.87%, respectively. The model validation results of the model also showed that the model simulates the grain yield well (10.3%). In the initial simulation, the best production potential (8433 kg ha^-1) was related to the October 15 sowing date. Attainable, water-limited, and nitrogen-limited yields were equal to 7179.2, 6302.7, and 4212.5 kg ha^-1 in Lorestan province. Across different locations, the water-limited yield ranged from 1.4722 to 2.7448 kg ha^-1, followed by attainable yield (from 6537.5 to 7982.7 kg ha^-1) and nitrogen-limited (from 2.2 3850 to 4414.5 kg ha^-1). The total yield gap of irrigated wheat in Lorestan province was equal to 4177.5 kg ha^-1. The results also showed that, in general, throughout the studied locations and years, the contribution of nitrogen, water, and other reducing and limiting factors in Lorestan province was equal to 69, 22, and 10% of the total yield gap. There were many changes among different locations in terms of the total yield gap in Lorestan province so it varied from 2661.8 kg ha^-1 (Pol-e Dokhtar) to 5608.4 kg ha^-1 (Aligudarz). In terms of yield gap due to water limitation, the highest amount was related to Pol-e Dokhtar (31%), and the lowest value was related to Khorramabad city (14%). For the yield gap caused by nitrogen limitation, Aligudarz had the largest share (77%), while the lowest share of this limitation was obtained for Khorramabad (59%). The maximum share of the yield gap caused by other limiting and reducing factors was also recorded in Khorramabad (27%), while its lowest value was calculated in Aligudarz and Aleshtar (without restrictions).
Conclusion
In general, the total yield gap of irrigated wheat in agro-ecosystems of Lorestan province is equal to 59%. Also, the results revealed that the largest share of the total yield gap is related to the lack of optimal application of nitrogen management (time of nitrogen application), and if the optimal management of nitrogen fertilizer is applied, the total yield gap will be significantly reduced at all studied locations in Lorestan province.
 
 

Keywords

APSIM-wheat model; Calibration and validation; Water and nitrogen management; Yield reducing and limiting factors

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