Document Type : Research Paper - Modeling
Authors
1 M.Sc. Graduated, Department of Production Engineering and Plant Genetics, Faculty of Agriculture, Khorramabad, Iran
2 Assistant Professor, Department of Production Engineering and Plant Genetics, Faculty of Agriculture, Khorramabad, Iran
3 Professor, Department of Production Engineering and Plant Genetics, Faculty of Agriculture, Khorramabad, Iran
4 Associate Professor, Department of Plant Production, Faculty of Agriculture, Saravan University, Saravan, Iran
Abstract
Introduction
Legumes are the second food source after cereals, which provide almost a quarter of protein for developing countries. Lentil is recognized as one of important legumes due to its favourable characteristics. The lintile production, like to other crops has been influenced by three factors: management, genetics, and environment. Improving crop production can be achieved by optimizing these factors. Thus, paying attention to the above-mentioned factors can reduce the severe climatic effects on crop production. Among the above-mentioned factors, management strategies e.g., optimal sowing date and using the optimal cultivar are considered to improve crop production. Initial soil moisture, which can affect crop germination, establishment and ultimately growth and yield, is another important strategy. Accordingly, the current research was conducted in order to simulate the effects of cultivar, sowing date, and initial soil moisture on lentil grian yield in different locations of Lorestan province.
Materials and Methods
The study locations were Aligudarz, Nurabad, KhorramAbad, and Kuhdasht. Simple Simulation Models-iCrop2 (SSM-iCrop2) was used to simulate the lentil growth and development. The data required to run model included climatic, soil, management, and crop data. Daily long-term climatic data including maximum and minimum temperature, rainfall, and radiation were collected from Iran Meteorological Organization. The soil data included soil depth, soil water content at wilting point, soil water content at field capacity, and saturation water content, which were obtained from different data collection in the Ministry of Agriculture and Agricultural, the Natural Resources Research and Education Centers, and soil laboratories at each location and Food and Agriculture Organization and Global yield Gap Atlas.The management data such as palnt density, tillage, rows distance, and sowing depth were obtained by local experts from the Ministry of Agriculture and Agricultural and the Natural Resources Research and Education Centers at each location. The crop data e.g., the specific genetic coefficients of each cultivar were obtained form Amiri and Deihimfard (2018). The study treatments consisted of four sowing dates (21 January, 12 February, 4 March, and 30 April), two cultivars (early-maturity and late-maturity) and four initial soil moisture (32, 36, 42, and 58 mm). The model was run for 41 years (1980-2020). Initial soil water contents and sowing dates were obtained from a preliminary simulation experiment.
Results and Discussion
Averaged across all treatments, the highest grain yield was obtained at KhorramAbad (388 kg ha-1) due to higher rainfall during the growing season. In addition, the grain yield difference among the sowing dates ranged from kg ha-1 on 30 April to 364 kg ha-1 on 21 January. The reason for the higher grain yield on 21 January sowing date was the higher cumulative rainfall season (149.3 mm vs. 99.2 mm) and the lower mean temperature (22.9 °C vs. 23.9 °C) during the growing season compared to other sowing dates. Across locations, sowing dates, and cultivars, the highest grain yield (263 kg ha-1) was simulated under initial soil moisture of 58 mm. Also, on average across sowing dates, initial soil moisture contents, and locations, the early-maturity cultivar simulated more grain yield than late-maturity cultivar (405 kg ha-1 vs. 63 kg ha-1) due to the avoidance of drought stress at the end of the growing season. Considering different interactions, on average across locations, the highest grain yield was simulated by 704 kg ha-1 in the combination of early-maturity cultivar, early sowing date (21 January), and initial soil moisture of 58 mm.
Conclusion
In general, the results indicated that the lentil grain yield varied among the various study treatments (sowing date, cultivar, and initial soil moisture) as well as different locations of Lorestan province. Lentil growers can increase the lentil production in Lorestan province and study locations by using the interaction of early planting date (21 January) ´ early-maturity cultivar (Kimia) ´ higher initial soil moisture (58 mm). It should be noted that the current research was conducted under water-limited condition and it is suggested that researchers focus on other limitimg and reducing factors in the future studies.
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