دوماه نامه

نوع مقاله : مقالات پژوهشی

نویسندگان

1 دانشگاه آزاد اسلامی؛ واحد علوم وتحقیقات تهران

2 تربیت مدرس

3 دانشگاه تهران

چکیده

شوری منابع آب و خاک از چالش‌های مهم بخش کشاورزی در ایران است. در زمینه چگونگی پاسخ گیاهان به تنش‌ شوری، چند مدل‌ ریاضی وجود دارد. لیکن اغلب این مدل‌ها در شرایطی خاص کاربرد دارند. هدف از این پژوهش، برآورد آستانۀ کاهش عملکرد ریحان، مدل‌سازی واکنش گیاه ریحان به شوری و نیز ارزیابی کارآیی مدل‌های ریاضی موجود در برآورد عملکرد این گیاه بود. به همین منظور، آزمایشی با 13سطح مختلف شوری شامل شوری‌های 2/1، 8/1، 2، 2/2، 5/2، 8/2، 3، 5/3، 4، 5، 6، 8 و 10 دسی‌زیمنس بر متر انجام شد. تیمارهای شوری با استفاده از اختلاط آب رودخانه شور با آب شرب تهیه شد. به منظور کمّی کردن اثر شوری بر عملکرد محصول، از هفت مدل‌ ریاضی استفاده شد. نتایج نشان داد آستانه کاهش عملکرد ریحان نسبت به شوری خاک 25/2 دسی‌زیمنس بر متر و شیب خط کاهش عملکرد، 2/7 درصد بر دسی‌زیمنس بر متر می‌باشد. مدل ون‌گنوختن و هافمن (48) در شبیه‌سازی تابع کاهش عملکرد ریحان به شوری عصاره اشباع دقتی بیشتر نسبت به دیگر مدل‌ها داشت. به طور کلی، نتایج این پژوهش نشان داد که مدل‌های ون‌گنوختن و هافمن (48)، استپوهن و همکاران (44) و همایی و همکاران (13) برای شبیه‌سازی واکنش عملکرد ریحان به شوری عصاره اشباع خاک از دقتی مناسب برخوردارند.

کلیدواژه‌ها

عنوان مقاله [English]

Determining the Threshold Value of Basil Yield Reduction and Evaluation of Water Uptake Models under Salinity Stress Condition

نویسندگان [English]

  • M. Sarai Tabrizi 1
  • H. Babazadeh 1
  • mahdi homaee 2
  • F. Kaveh Kaveh 1
  • M. Parsinejad 3

1 Tehran Science and Research Branch, Islamic Azad University

2

3 University of Tehran

چکیده [English]

Introduction: Several mathematical models are being used for assessing the plant response to the salinity of the root zone. The salinity of the soil and water resources is a major challenge for agricultural sector in Iran. Several mathematical models have been developed for plant responses to the salinity stress. However, these models are often applicable in particular conditions. The objectives of this study were to evaluate the threshold value of Basil yield reduction, modeling Basil response to salinity and to evaluate the effectiveness of available mathematical models for the yield estimation of the Basil .
Materials and Methods: The extensive experiments were conducted with 13 natural saline water treatments including 1.2, 1.8, 2, 2.2, 2.5, 2.8, 3, 3.5, 4, 5, 6, 8, and 10 dSm-1. Water salinity treatments were prepared by mixing Shoor River water with fresh water. In order to quantify the salinity effect on Basil yield, seven mathematical models including Maas and Hoffman (1977), van Genuchten and Hoffman (1984), Dirksen and Augustijn (1988), and Homaee et al., (2002) were used. One of the relatively recent methods for soil water content measurements is theta probes instrument. Theta probes instrument consists of four probes with 60 mm long and 3 mm diameter, a water proof container (probe structure), and a cable that links input and output signals to the data logger display. The advantages that have been attributed to this method are high precision and direct and rapid measurements in the field and greenhouse. The range of measurements is not limited like tensiometer and is from saturation to wilting point. In this study, Theta probes instrument was calibrated by weighing method for exact irrigation scheduling. Relative transpiration was calculated using daily soil water content changes. A coarse sand layer with 2 centimeters thick was used to decrease evaporation from the surface soil of the pots. Quantity comparison of the used models was done by calculating statistical indices such as maximum error (ME), normalized root mean square error (nRMSE), modeling efficiency (EF), and coefficient of residual mass (CRM). At the end of the experiment, dry matter yield at the different treatments was measured and relative yield was calculated by dividing dry matter yield of treatments on dry matter yield at no stress treatment (control treatment). Leaching requirement in experimental treatments was calculated by Ayarset al., (2012) equation.
Results and Discussion: The results indicated that Basil threshold value based on soil salinity was 2.25
dSm-1 with the yield reduction of 7.2% per dSm-1. The mathematical model of van Genuchten and Hoffman (1984) had a higher precision than other models in simulating Basil yield reduction function based on saturated soil extract salinity. The overall observations revealed that van Genuchten and Hoffman (1984), Steppuhnet al., (2005) and Homaeeet al., (2002) models were accurate for simulating Basil root water uptake and yield response to saturated soil extract salinity. Considering the presented results, it seems that among math-empirical models for salinity stress conditions, model of van Genuchten and Hoffman (1984) is more accurate than Maas and Hoffman (1977), Dirksen and Augustijn (1988) and Homaeeet al., (2002a) models. The works of Green et al., (2006) and Skaggs et al., (2006) came to the same conclusion. Our work indicated that mostly statistical models have lower precision than math-empirical models. Steppuhn et al., (2005a) reported that statistical models had the higher accuracy than math-empirical model of Maas and Hoffman (1977) and among statistical models, the modified Weibull model had the best fit on measured data which is in good agreement with the results of this study.
Conclusion: The goals of this research were to evaluate Basil response to saturated soil extract salinity, to estimate threshold value of Basil crop coefficients, to obtain yield reduction gradient, and also to investigate efficiency of available math-empirical models in estimating reduction functions. The results of this study indicated that the Basil threshold value obtained based on saturated soil extract salinity was 2.25 dSm-1 and the gradient of yield reduction was 7.2% per dSm-1 according to Maas and Hoffman (1977) linear fitting. The reached general conclusion was that among the math-empirical reduction functions, the model of van Genuchten and Hoffman (1984) had the highest accuracy when compared to the models of Maas and Hoffman (1977), Dirksen and Augustijn (1988) and Homaee et al., (2002a). Therefore, it is recommended to use the van Genuchten and Hoffman (1984), Steppuhn et al., (2005), and Homaee et al., (2002) models respectively, instead of the other models in this research.

کلیدواژه‌ها [English]

  • basil
  • Root water uptake models
  • salinity
  • Threshold value
1- Ayars J.E., Corwin D.L.and Hoffman. G.J. 2012. Leaching and root zone salinity control. ASCE Manual and Report Engineering Practice No 71 Agricultural Salinity Assessment and Management (2nd Edition), ASCE Riston.Chapter 12: 371-403.
2- Ayers R.S. and Westcott D.W. 1985. Water quality for agriculture. Irrigation and Drainage paper, No. 29, Rev. 1, FAO, Rome.
3- Bressler E., and Hoffman G.J. 1986. Irrigation management for soil salinity control: Theories and tests. Soil Science Society America. Journal, 50:1552-1560.
4- Dirksen C.m and Augustijn D.C. 1988. Root water uptake function for nonuniform pressure and osmotic potentials. AgricultureAbstracts, pp. 188.
5-Ekren S., Sonmez C., Ozcakal E., KukulKurttas Y.S., Bayram E.andGurgulu H. 2012. The effect of different irrigation water levels on yield and quality characteristics of purple basil (Ocimumbasilicum L.). Agricultural Water Management, 57 (2): 111-126.
6- Esmaili E., Homaee M., and Malakouti M.J. 2005. Interactive effect of salinity and Nitrogen fertilizers on growth and composition of Sorghum. Iranian Journal of Soil and Waters Sciences 19 (1): 131-146. (in Persian with English abstract).
7- Esmaili E., Kapourchal S.A., Malakouti M.J., and Homaee M. 2008. Interactive effects of Salinity and two nitrogen fertilizers on growth and composition of sorghum. Plant Soil Environment, 54 (12): 537-546.
8- Francois L.E. 1996. Salinity effects on four sunflower hybrids. Agron Journal, 88: 215-219.
9- Hanson B.R., and Grattan S.R. 1999. Agricultural salinity and drainage.University of California, Irrigation Program, 328 pp.
10- Homaee M. 1999. Root water uptake under non-uniform transient salinity and water stress. PhD dissertation, Wageningen Agricultural University, The Netherlands, 173 pp.
11- Homaee M. 2002. Plants response to salinity.Iranian National Committee on Irrigation and Drainage (IRNCID).No. 58. (in Persian).
12- Homaee M., and Feddes R.A. 2002. Modeling the sink term under variable soil water osmotic and pressure heads. Develop Water Science, 47: 17-24.
13- Homaee M., Dirksen C., and Feddes R.A. 2002a. Simulation of root water uptake. I. Non-uniform transient salinity using different macroscopic reduction functions. Agricultural Water Management, 57: 89-109.
14- Homaee M., DirksenC., and Feddes R. A. 2002b. Simulation of root water uptake. II. Nonuniform transient water stress using different reduction functions. Agricultural Water Management, 57(2): 111-126.
15- Homaee M., Feddes R. A. and Dirksen C. 2002c. Simulation of root water uptake. III. non-uniform transient combined salinity and water stress. Agricultural Water Management, 57: 127-144.
16- Homaee M., Feddes R. A. and Dirksen C. 2002d.A macroscopic water extraction model for non-uniform transient salinity and water stress. Soil Science SocietyAmeraica Journal, 66: 1764-1772.
17- Homaee M. and Schmidhalter U. 2008. Water integration by Plants root under non-uniorm soil salinity. Irrigation Science, 27: 83-95.
18- Hosseini Y., Homaee M., Karimian N.A. and Saadat S. 2009a. Modeling of Canola response to combined salinity and nitrogen stresses. Journal of Science and Technology of Agriculture and Natural Resources (Water and Soil Science) 12 (46): 721-734. (in Persian with English abstract).
19- Hosseini Y., Homaee M., Karimian N.A., and Saadat S. 2009b. The effects of phosphorus and salinity on growth, nutrient concentrations, and water use efficiency in Canola (Brassica napus L.). Agricultural Research (Water, Soil and Plant in Agriculture) 8 (4): 1-18. (in Persian with English abstract).
20- Hosaini Y., Homaee M., Karimian N.A., and Saadat S. 2009. Modeling vegetative stage response of Canola (Brassica napus L.) to combined salinity and boron stresses. International Journal of Plant Production, 4 (3):175-186.
21- Jacobsen O.J., and Schjonning P. 1993. A laboratory calibration of time domain reflectometry for soil water measurement including effects of bulk density and texture. Journal of Hydrology, 5: 147–157.
22- Jalali V.R., Homaee M., and Mirnia S. Kh. 2008a. Modeling Canola response to salinity on vegetative growth stages. Journal of Agricultural Engineering Research 8 (4): 95-112. (In Persian with English abstract).
23- Jalali V.R., Homaee M., and Mirnia S. Kh. 2008b. Modeling Canola Response to Salinity in Productive Growth Stages. Journal of Science and Technology of Agriculture and Natural Resources (Water and Soil Science) 12 (44): 111-121. (in Persian with English abstract).
24- Jalali V. R. and Homaee M. 2010. Modeling the effect of salinity application time of root zone on yield of canola (Brassica napus L.). Journal of Crop Improvement 12 (1): 29-40. (in Persian with English abstract).
25- Jamieson P. D., Porter J. R. and Wilson D. R. 1991. A test of the computer simulation model ARC-WHEAT1 on wheat crops grown in New Zealand. Field Crops Research, 27, 337–350.
26- Kiani A.R., Mirlatifi M., Homaee M. and Cheraghi A. 2004. Effect of different irrigation regimes and salinity on wheat yield in Gorgan region. Journal of Agricultural Sciences and Natural Resources 11(1): 79-89. (in Persian with English abstract).
27- Kiani A.R., Mirlatifi M., Homaee M. and Cheraghi A. 2005a. Water use efficiency of wheat under salinity and water stress. Journal of Agricultural Engineering Research 6 (24): 47-64. (in Persian with English abstract).
28- Kiani A.R., Mirlatifi M., Homaee M. and Cheraghi A. 2005b. Determination of the best watersalinity functions for wheat production in north of Gorgan. Journal of Agricultural Engineering Research 6 (25): 1-14. (in Persian with English abstract).
29-Kiani A.R., Homaee M. and Mirlatifi M. 2006. Evaluation yield reduction functions under salinity and water stress conditions. Iranian Journal of Soil Research (Formerly Soil and Water Sciences) 20 (1): 73-83. (in Persian with English abstract).
30- Loague K., and Green R.E. 1991. Statistical and graphical methods for evaluating solute transport models: overview and application. Journal of Contaminant Hydrology, 7: 51-73.
31-Maas E.V., and Grattan S. R. 1999. Crop yields as affected by salinity. In R. W. Skaggs and J. van Schilfgaarde (eds) Agricultural Drainage. Agron.Monograph 38.ASA, CSSA, SSA, Madison, WI pp. 55–108.
32- Maas E.V., and Hoffman G. J. 1977. Crop salt tolerance-current assessment. Journal of Irrigation and Drainage Engineering(ASCE), 103 (IR2): 115-134.
33- Miller J. D. and Gaskin G. 1997. The development and application of the theta probes soil water sensor. MLURI.Technical note, 312 pp.
34- Omidbaigi R. 2009. Production and processing of medicinal plants.Astan Quds Razavi publications, No. 149, 397 pp. (in Persian).
35- Oster J. D. 1994. Irrigation with poor quality water.Agricultural Water Management,25(3):271-297.
36- Ponizovsky A.,Chudinova S. and Pachepsky Y. 1999. Performance of TDR calibration models as affected by soil texture. Journal of Hydrology, 218: 35-43.
37- Rhoades J.D. Kandiah A. and Mashali A. M. 1992. The use of saline waters for crop production. Irrigation and Drainage paper, No. 48, FAO, Rome.
38- Richards L. A. 1931. Capillary conduction of liquids in porous mediums.Physics, 1: 318-333.
39- Robinson D.A., Gardner C.M.K., and Cooper J.D. 1999. Measurement of relative permittivity in sandy soils using TDR, capacitance and theta probes: comparison, including the effects of bulk soil electrical conductivity. Journal of Hydrology, 223: 198–211.
40- Saadat S., Homaee M. and Liaghat A. M. 2005. Effect of soil solution salinity on the germination and seedling growth of sorghum plant. Iranian Journal of Soil and Waters Sciences 19 (2): 243-254. (in Persian with English abstract).
41- Sepaskhah A. R. and Beirouti Z. 2009. Effect of irrigation interval and water salinity on growth of madder (Rubiatinctorum L.).International Journal of Plant Production, 3(3):1-16.
42- Shalhevet J. 1994. Using water of marginal quality for crop production: major issues. Agricultural Water Management, 25(3):233-269.
43- Shenker M., Ben-Gal A. and ShaniU. 2003. Sweet corn response to combined nitrogen and salinity environmental stresses. Plant Soil, 256: 139-147.
44- Steppuhn H. van Genuchten M. Th. and Grieve C. M. 2005a. Crop ecology, management and quality: Root-Zone Salinity: I. Selecting a Product-Yield Index and Response Function for Crop Tolerance. Crop Science, 45(1):209-220.
45- Steppuhn H. van Genuchten M.Th. and Grieve C.M. 2005b. Crop ecology, management and quality: Root-Zone Salinity: II. Indices for Tolerance in Agricultural Crops.Crop Science,45(1):221-232.
46- van Genuchten M.Th. 1983. Analyzing crop salt tolerance data: Model description and user’s manual. UDSA, ARS, U.S. Salinity Lab. Research Report No. 120. U.S. Gov. Printing Office, Washington, DC.
47- van GenuchtenM.Th., and Gupta S.K. 1993. A reassessment of the crop tolerance response function. Journal Indian Society Soil Science, 41(4):730– 737.
48- van Genuchten M. Th. and HoffmanG. J. 1984.Analysis of crop production. In: I. Shainberg and J. Shalhevet (eds), Soil salinity under irrigation. pp. 258-271. Springer-Verlag.
49- Willmott C.J., Akleson G.S., Davis R.E., Feddema J. J., Klink K.M., Legates D.R., Odonnell J. and Rowe C. M. 1985. Statistics for the evaluation and comparison of models. Journal of Geophysics Research, 90: 8995–9005.
CAPTCHA Image