نوع مقاله : علمی پژوهشی - مدل سازی

نویسندگان

1 دانش آموخته کارشناسی ارشد، گروه مهندسی تولید و ژنتیک گیاهی، دانشکده کشاورزی، دانشگاه لرستان، خرم آباد، ایران

2 استادیار، گروه مهندسی تولید و ژنتیک گیاهی، دانشکده کشاورزی، دانشگاه لرستان، خرم آباد، ایران

3 استاد، گروه مهندسی تولید و ژنتیک گیاهی، دانشکده کشاورزی، دانشگاه لرستان، خرم آباد، ایران

4 دانشیار، گروه تولیدات گیاهی، دانشکده کشاورزی، دانشگاه سراوان، سراوان، ایران

چکیده

حبوبات پس از غلات دومین منبع غذایی در کشورهای در حال توسعه هستند و تقریبا یک چهارم نیاز پروتئین در این کشورها توسط حبوبات تامین می‌گردد. تولید عدس مانند گیاهان دیگر تحت تاثیر سه فاکتور مدیریت، ژنتیک و محیط می‌باشد. با بهینه‌سازی این عوامل می‌توان به تولید بیشتری دست پیدا کرد. بر این اساس، مطالعه حاضر به منظور شبیه‌سازی اثرات رقم، تاریخ کاشت و رطوبت اولیه خاک بر عملکرد دانه عدس در مناطق مختلف استان لرستان انجام شد. مناطق مورد بررسی شامل الیگودرز، نورآباد، خرم‌آباد و کوهدشت بودند. به منظور شبیه‌سازی رشد و نمو محصول عدس از مدل  SSM-iCrop2استفاده شد. داده‌های مورد نیاز برای اجرای مدل شامل داده‌های اقلیمی، خاکی، مدیریتی و گیاهی بودند. تیمارهای مورد بررسی شامل چهار تاریخ کاشت (9 بهمن، 23 بهمن، 13 اسفند و 30 فرودین)، دو رقم (زودرس و دیررس) و چهار آب اولیه خاک (32، 36، 42 و 58 میلی‌متر) بودند. تعداد سال‌های شبیه‌سازی برابر با 41 سال (1399-1358) بود. برای به دست آمدن آب‌های اولیه خاک و تاریخ کاشت‌ها یک آزمایش اولیه شبیه‌سازی انجام شد. نتایج نشان داد که به طور میانگین در همه‌ی تیمارهای مورد بررسی، بالاترین عملکرد دانه با 388 کیلوگرم در هکتار در منطقه خرم‌آباد به علت طول فصل رشد بیشتر بدست آمد. همچنین اختلاف ایجاد شده توسط تیمارهای تاریخ کاشت از 124 کیلوگرم در هکتار در تاریخ کاشت 30 فروردین تا 364 کیلوگرم در هکتار در تاریخ کاشت 9 بهمن بود. دلیل بالا بودن عملکرد دانه در تاریخ کاشت 9 بهمن نسبت به تاریخ کاشت‌های دیگر بیشتر بودن بارندگی تجمعی در طول فصل رشد (3/149 میلی‌متر در مقابل 2/99 میلی‌متر) و پایین‌تر بودن میانگین دما در طول فصل رشد (9/22 درجه ‌سانتی‌گراد در مقابل 9/23 درجه ‌سانتی‌گراد) بود.  به طور میانگین در همه‌ی مناطق، تاریخ‌ کاشت‌ها و ارقام مورد بررسی بیشترین عملکرد دانه (263 کیلوگرم در هکتار) در آب اولیه خاک 58 میلی‌متر شبیه‌سازی شد. همچنین به طور میانگین در همه‌ی تاریخ کاشت‌ها، آب‌های اولیه خاک و مناطق، عملکرد دانه رقم زودرس (405 کیلوگرم در هکتار) به علت اجتناب از تنش خشکی آخر فصل بیشتر از رقم دیررس (63 کیلوگرم در هکتار) بود. با در نظر گرفتن برهمکنش‌های مختلف به طور میانگین در همه‌ی مناطق، بیشترین عملکرد دانه با 704 کیلوگرم‌ در هکتار در برهمکنش رقم زودرس، تاریخ کاشت 9 بهمن و آب اولیه خاک 58 میلی‌متر شبیه‌سازی شد. به طور کلی نتایج مشخص کرد که عملکرد دانه عدس در بین تیمارها (تاریخ کاشت، رقم و آب اولیه خاک) و مناطق مختلف مورد بررسی در استان لرستان متفاوت بود. کشاورزان استان لرستان با استفاده از برهمکنش تاریخ کاشت زودهنگام (9 بهمن) × رقم زودرس (کیمیا) × آب اولیه خاک بالاتر (58 میلی‌متر) می‌توانند عملکرد دانه را افزایش دهند. باید ذکر شود که مطالعه حاضر تحت شرایط محدودیت آب انجام شده است و پیشنهاد می‌شود محققان در مطالعات آینده بر روی دیگر فاکتورهای محدودکننده و کاهنده متمرکز شوند. 

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Simulating response of lentil cultivars to sowing date and initial soil moisture in Lorestan province

نویسندگان [English]

  • Mojtaba Koohro 1
  • Sajjad Rahimi-Moghaddam 2
  • khosro Azizi 3
  • Saeid Heidari 2
  • Seyed Reza Amiri 4

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

چکیده [English]

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.

کلیدواژه‌ها [English]

  • Grain yield
  • Length of growing season
  • Rainfed conditions
  • SSM-iCrop2 model
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