پیوندهای مفید
اخبار و اعلانات
آمار
| تعداد نشریات | 158 |
| تعداد شماره‌ها | 6,232 |
| تعداد مقالات | 67,790 |
| تعداد مشاهده مقاله | 115,260,529 |
| تعداد دریافت فایل اصل مقاله | 90,002,774 |
ارزیابی تابع تولید عملکرد و اجزای عملکرد گلرنگ در شرایط کم‌آبیاری و سطوح مختلف شوری | ||
| تحقیقات آب و خاک ایران | ||
| دوره 54، شماره 9، آذر 1402، صفحه 1319-1336 اصل مقاله (2.18 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/ijswr.2023.362564.669539 | ||
| نویسندگان | ||
| مهدی مکاری* 1؛ جواد علائی2؛ امیرحسین قادری3 | ||
| 1گروه علوم و مهندسی آب، مرکز آموزش عالی کاشمر، کاشمر، ایران | ||
| 2دانشجوی دکترا آبیاری و زهکشی دانشگاه کشاورزی و منابع طبیعی گرگان | ||
| 3گروه مهندسی آب، دانشکده مهندسی آب و خاک، دانشگاه کشاورزی و منابع طبیعی گرگان، گرگان، ایران. | ||
| چکیده | ||
| به‌منظور مدیریت مصرف آب‌های شور در اراضی تحت آبیاری و هم‌چنین مقابله با بحران کمیابی منابع آبی در مناطق خشک و نیمه‌خشک، دست یافتن به توابع تولید بهینه آب-شوری-عملکرد محصولات زراعی، راه حل منطقی به نظر می‌رسد. در همین راستا پژوهشی گلخانه‌ای با سه تیمار آبیاری 100، 75 و 50 درصد نیاز آبی و چهار سطح شوری 7/0، 4، 8 و 12 دسی‌زیمنس بر متر به‌صورت فاکتوریل و در قالب طرح بلوک کامل تصادفی با سه تکرار در شهرستان کاشمر به انجام رسید. هدف از انجام پژوهش تعیین بهترین تابع تولید آب-شوری-عملکرد گیاه گلرنگ بود. توابع تولید استفاده شده در این پژوهش خطی، درجه دوم، کاب داگلاس و متعالی بودند. جهت ارزیابی دقت و کارآمدی این توابع در پیش‌بینی عملکرد و اجزای عملکرد گلرنگ، از پارامترهای آماری میانگین مطلق خطا (MAE)، ریشه میانگین مربعات خطای نرمال (NRMSE)، ضریب تبیین (R2)، کارایی مدل‌سازی (EF) و شاخص توافق (d) استفاده گردید. هم‌چنین حد آستانۀ تحمل به شوری گیاه با استفاده از مدل خطی ماس-هافمن تعیین گردید. نتایج نشان داد در بین توابع استفاده شده، تابع درجه دوم با کم‌ترین NRMSE و بیش‌ترین R2 بهترین کارایی را در پیش‌بینی عملکرد دانه و اجزای آن در شرایط توأم شوری و تنش خشکی داشت. مطابق با مدل خطی ماس-هافمن، کاهش عملکرد نسبی دانه به میزان 10 درصد در شوری 75/3 دسی‌زیمنس بر متر و کاهش 25 و 50 درصدی عملکرد دانه به‌ترتیب در شوری 75/6 و 75/11 دسی‌زیمنس بر متر اتفاق افتاد. با توجه به یافته‌های این پژوهش می‌توان تابع درجه دوم را به‌عنوان بهترین تابع تولید آب-شوری-عملکرد گلرنگ در شرایط کاشت گلدانی توصیه نمود. البته با توجه به وابستگی توابع تولید به نوع خاک، شرایط آب و هوایی و اقلیمی منطقه و روش‌های مدیریت آب در مزرعه، مطالعات جامع‌تری در خصوص معرفی بهترین تابع تولید آب-شوری-عملکرد گلرنگ در شرایط مزرعه احساس می‌گردد. | ||
| کلیدواژه‌ها | ||
| آستانه تحمل به شوری؛ تابع درجه دوم؛ تنش هم‌زمان؛ مدیریت آبیاری | ||
| عنوان مقاله [English] | ||
| Assessment of yield and yield components production function of safflower under deficit irrigation and different salinity levels | ||
| نویسندگان [English] | ||
| mahdi mokari1؛ javad alaei2؛ amirhossin ghaderi3 | ||
| 1Water Engineering Department, Kashmar Higher Education Institute, Kashmar,Iran | ||
| 2Doctoral student of irrigation and drainage of Gorgan University of Agriculture and Natural Resources | ||
| 3Department of Water Engineering, Faculty of Water and Soil Engineering, Gorgan University of Agriculture and Natural Resources, Gorgan, Iran. | ||
| چکیده [English] | ||
| In order to manage application of saline water in irrigated lands and coping with crisis of water resources scarcity in arid and semi-arid regions, it is logical to obtain the optimum yield-salinity-water production functions for crops. In this way, a greenhouse experiment with three irrigation treatments including 100, 75 and 50 percent of water requirement and four salinity levels of irrigation water including 0.7, 4, 8, and 12 dS m-1, as a factorial in the form of a completely randomized block design with three replications was conducted in Kashmar region. The objective of this study was to determine the optimum yield-water-salinity production function of safflower. The crop production functions used in this study were linear, Cobb-Douglas, quadratic and transcendental functions. For assessing the accuracy and efficiency of these functions in predicting yield and yield components of safflower, the statistics of mean absolute error, normal root mean square error, determination coefficient, efficiency function and agreement index were used. Additionally, the plant salinity resistance threshold was determined by Mass-Hoffman linear model. The results showed among the applied functions, the quadratic function the lowest NRMSE and the highest R2, had the most efficiency in predicting yield and yield components of safflower in simultaneous salinity and drought stress conditions. According to Mass-Hoffman linear model, grain yield relative reduction by 10 percent, in salinity of 3.75 dS m-1 and grain yield relative reduction by 25 and 50 percent were occurred in salinity of 6.75 and 11.75 dS m-1, respectively. According to the findings of this research it can be concluded that the quadratic equation is recommendable as the best yield-water-salinity production function of safflower in pot conditions. Since, crop production functions are dependent to soil type, weather and climate conditions and water management in the field, more comprehensive studies should be done in the field conditions for determining the best yield-water-salinity production function of safflower. | ||
| کلیدواژه‌ها [English] | ||
| Irrigation management, Quadratic function, Salinity tolerance threshold, Simultaneous stress | ||
| مراجع | ||
|
Abdzadgohari, A., Babazadeh, H., Amiri, E., & Sedghi, H. (2018). Estimation of production function in peanut cultivars on irrigation management and salinity levels. Journal of Water Irrigation Management, 7(1), 87-104 (In Persian). Anonymous. (2022). Agricultural research, education and extension organization of Razavi Khorasan Province, Agricultural research and natural resources station of Kashmar, Iran. Anonymous. (2018).Water appearance of Razavi Khorasan Province, Regional water company of Razavi Khorasan, vice president of planning, Bureau of planning and economic surveys, Statistics group, pp. 28 (In Persian). Ansari, H. (2008). Determining the index and optimal irrigation depths to maximize benefit of early maturing corn. Journal of Water and Soil, 22(2), 107-115 (In Persian). Asadi, L., Khoshravesh, M., PourGholam, M., Liaghat, A. M., & Youri, M. R. (2018). Estimation of soybean water-nitrogen production function. Iranian Journal of Soil and Water Research, 49(3), 665-672 (In Persian). Ayers, R. S., & Westcott, D. W. (1985). Water quality for agriculture. Irrigation and Drainage paper, No. 29, Rev. 1, FAO, Rome. Banakar, M. H., Amiri, H., Ranjbar, G. H., & Sarafraz Ardakani, M. R. (2020). Determination of salt tolerance threshold and effects of using saline water on grain yield and yield components of fenugreek (Trigonella foenum-graceum). Journal of Plant Process and Function, 9(39), 289-310 (In Persian). Bassil, E. S., & Kaffka, S. R. (2002). Response of safflower (Carthamus tinctorius L.) to saline soils and irrigation: I.consumptive water use. Agricultural Water Management, 45, 67-80. Cotton, oil seeds and industrial plants administration. (2014). Increase self-reliance plan in oil seeds production (Based on resistance economy). Deputy minister of agriculture, Ministry of agriculture -Jahad. Pp.143 (In Persian). Datta, K. K., Sharma, V. P., & Sharma, D. P. (1998). Estimation of a production function for wheat under saline conditions. Agricultural Water Management, 36, 85-94. Debaeke, P., & Aboudrare, A. (2004). Adaptation of crop management to water-limited environmental. European Journal of Agronomy, 21, 433-446. Dehghan, H., Mokari, M., & Abedinpour, M. (2020). Determination of water-salinity-yield production function for spinach plant. Journal of Water Research in Agriculture (Soil and Water Science), 34(1), 79-92 (In Persian). Farahbakhsh, M., Sarai Tabrizi, M., & Babazadeh, H. (2023). Determining basil production functions under simultaneous water, salinity and nitrogen stresses. Applied Water Science, 13(3), 1-12. Farahmand, A., Oustan, Sh., Jafarzadeh, A., & Aliasgharzad, N. (2012). Salinity and sodicity parameters in some salt-effected soils of Tabriz plain. Water and Soil Science, 22(1), 1-15 (In Persian). Feizi, M., Hajabbasi, M. A., & Mostafazadeh-Fard, B. (2010). Saline irrigation water management strategies for better yield of safflower (Carthamus tinctorius L.) in arid region. Australian Journal of Crop Science, 4(6), 408-414. Foster, T., & Brozovic, N. (2018). Simulating crop-water production functions using crop growth models to support water policy assessments. Ecological Economy, 152, 9-21. Fraj, M. B., Al-Dakheel, A. J., McCann, I. R., Shabbir, G. M., Rumman, G. A., & Al Gailani, A. Q. A. M. (2013). Selection of high yielding and stable safflower (Carthamus tinctorius L.) genotypes under salinity stress. Agricultural Science Research Journal, 3(9), 273-283. Hagemeyer, J. (1997). Salt. In: Plant Ecophysiology. (ed. Prasad, M. N. V.) Wiley and Sons, Inc. New York. Homaee, M., Driksen, C., & Feddes, R. A. (2002). Simulation of root water uptake, I: Non-uniform ransient salinity using different macroscopic reduction functions. Agricultural Water Management, 57, 89-109. Kamali, E., Shahmohammadi Heydari, Z., Heydari, M., & Feyzi, M. (2011). Effects of irrigation water salinity and leaching fraction on soil chemical characteristic, grain yield, yield components and cation accumulation in safflower in Esfehan. Iranian Journal of Field Crop Science, 42(1), 63-70 (In Persian). Karaca, C., Aslan, G. E., Buyuktas, D., Kurunc, A., Bastug, R., & Navarro, A. (2023). Effects of salinity stress on drip irrigated tomatoes grown under Mediterranean-type greenhouse conditions. Journal of Agronomy, 13(36), 1-18. Khoshnam, A., & Mamnoie, E. (2020). Effect of water stress and plant density on yield and yield components of safflower (Carthamus tinctorius L.) in south Kerman. Environmental Stresses in Crop Sciences, 14(1), 39-46 (In Persian). Kiani, A. R., & Abbasi, F. (2009). Assessment of the water-salinity crop production function of wheat using experimental data of the Golestan province, Iran. Irrigation and Drainage, 58, 445-455. Kikhazaleh, M., Ramroudi, M., Galavi, M., Ghanbari, S. A., & Fanaei, H. R. (2023). Effect of potassium on yield and some qualitative and physiological traits of safflower (Carthamus tinctorius L.) under drought stress conditions. Journal of Plant Nutrition, 46(10), 2380-2392. Kolsaric, O., Allu, O., & Kaya, M. D. (2005). The effects of tillage and nitrogen doses on water use efficiency, soil moisture and seed characters of safflower (Carthamus tinctorius L.) in wheat safflower rotation system. 5th International safflower Conference, Istanbul, 6-10 pp:126-131. Mass, E.V., & Hoffman, G. L. (1977). Crop salt tolerance-current assessment. Journal of Irrigation and Drainage, 103, 115-134. Mohammadi, M., Liaghat, A., & Molavi, H. (2010). Optimization of water use and determination of tomato sensitivity coefficients under combined salinity and drought stress in Karaj. Journal of Water and Soil, 24(3), 583-592 (In Persian). Mousavi Zadeh Mojarad, R. A., Feizi, M., & Ghobadinia, M. (2018). Prediction of safflower yield under different saline irrigation strategies using AquaCrop model in semi-arid regions. Australian Journal of Crop Science, 12(8), 1241-1249. Najafi Mood, M. H., Alizadeh, A., Davari, K., Kafi, M., & Shahidi, A. (2012). Determination of water-salinity production function for two cotton cultivars. Journal of Water and Soil, 26(3), 672-679 (In Persian). Omidi, A. H., Jabbari, H., & Ramezani, Z. (2021). Effects of row-spacing and plant density on seed yield and yield components of safflower cultivars under irrigated conditions. Research Achievements for Field and Horticulture Crops, 10(1), 23-32 (In Persian). Ould Ahmed, B. A., Yamamoto, T., & Inoue, M. (2007). Response of drip irrigated sorghum varieties growing in dune sand to salinity levels in irrigation water. Journal of Applied Science, 7, 1061-1066. Rashki, P., Piri, H., & Khammari, E. (2020). Determination of production function and optimal depth of irrigation of roselle under water deficit and potassium fertilizer. Journal of Water and Irrigation Management, 10(2), 189-202 (In Persian). Rashki, P., Piri, H., & Khamari, E. (2022). Determining the production function and optimal irrigation depth of Roselle in deficit irrigation conditions and using potassium fertilizer. Agricultural Water Management, 271, 107788. Royo, A., Aragues, R., Playan, E., & Ortiz, R. (2000). Salinity-grain yield response functions of barley cultivars assessed with a drip-injection irrigation system. Soil Science Society of American Journal, 64, 359-365. Salehi, M., Kafi, M., & Kiani, A. R. (2011). Water-salinity production function of Kochia in North of Golestan. Journal of Water and Soil, 25(6), 1395-1403 (In Persian). Seghatoleslami, M. J., Kafi, M., Majidi Heravan, A., Noor Mohammadi, G., & Darvish, F. (2008). Effect of drought stress at different growth stages on yield and water use efficiency of five prosomillet genotypes. Pakistan Journal of Botany, 40(4), 1427-1432. Shen, X., Wang, G., Tilahun Zeleke, K., Si, Z., & Chen, J. (2020). Crop water production functions for winter wheat with drip fertigation in the North China plain. Journal of Agronomy, Doi:10.3390/agronomy10060876. Shirmohammadi Aliakbarkhani, Z., Ansari, H., Alizadeh, A., & Kafi, M. (2014). Assessment of water-salinity production functions of forage maize in Khorasan Razavi province. Iranian Journal of Irrigation and Drainage, 7(4), 535-543 (In Persian). Tafteh, A., Babazadeh, H., Ebrahimipak, N. A., & Kaveh, F. (2013). Evaluation and improvement of crop production functions for simulation winter wheat yields with two types of yield response factor. Journal of Agricultural Science, 5(3), 111-122. Tayebi, A., Afshar, H., Farahvash, F., Masood Sinki, J., & Nezarat, S. (2012). Effect of drought stress and different planting dates on safflower yield and its components in Tabriz region. Iranian Journal of Plant Physiology, 2(3), 445-453. Volkmar, K. M., Hu, Y., & Steppuhn, H. (1997). Physiological responses of plants to salinity: a review. Canadian Journal of Plant Science, 78, 19-27. Zhang, X., Yang, H., Shukla, M. K., & Du, T. (2023). Proposing a crop-water-salt production function based on plant response to stem water potential. Agricultural Water Management, 278, 108162. | ||
|
آمار تعداد مشاهده مقاله: 147 تعداد دریافت فایل اصل مقاله: 114 |
||