Document Type : Research Article

Authors

1 Arak University

2 Isfahan University of Technology

Abstract

Introduction: World's population growth and limited water resources and needing to more food production led to interest farmers to use nitrogen fertilizer more than soil requires and subsequently Nitrate leaching causes groundwater and environmental pollution. Therefore, researches has concentrated on improvement of nitrogen use efficiency, which numerical simulation is the effective solutions to optimize the management of water and fertilizer in the field in order to achieve the maximal yield and minimal nitrate pollution of soil, groundwater and drainage in water deficiency crisis condition. For this reason, the evaluation of new user friendly models in correct estimation of soil moisture and nitrogen content distribution and recognition of water and solutes movement in the soil and choosing the best management option for increasing productivity and economic performance and also reduction of nitrate pollution of soil and ground water source with the least limitations and high accuracy is necessary. The Eu-Rotate-N model has been developed for simulation of nitrogen use and specifically for optimization of nitrogen use in variation of vegetables in a wide range of conditions, which without the need to calibration has presented satisfactory results in many areas. So this study was conducted to evaluate the efficiency of Eu-Rate-N model in assessment of moisture and nitrogen distribution and yield under different nitrogen fertigation management for pepper plant.
Materials and Methods: Sweet pepper was planted at density of 8.33plant per m2 in a row planting method. 150kg per hectare per year of fertilizer was used during the season. Crop yield, soil water and nitrogen content were measured on a regular basis. The treatments consisted of three fertilizer level: zero (N0), the ratio of ammonium to nitrate 20:80 (N1) and 40:60 (N2), which was conducted in a completely randomized block with three replications in Isfahan. Irrigation based on daily monitoring of humidity was used with drip irrigation system. The irrigation Depth was calculated and applied with aim of replacing the water content deficiency in the root zone up to field capacity (FC) for the no water deficit treatment.
Coefficients were modified only for plant coefficients and length of each growth stage according to the area. To compare simulated data with measured data in field, indices of statistical root mean square error (RMSE), normalized root mean square error (NRMSE), coefficient of determination (r2) and index of agreement Wilmot (d) were used.
Results and Discussion: The NRMSE index for nitrate and soil water content was 11.45, 12.08, the RMSE was 0.89, 0.022, the r2 was 0.998, 0.996 and the d was 0.667, 0.66 respectively. All calculated indices for soil water and nitrate content were in the acceptable range. NRMSE index was less than 20 percent in all treatments which was indicating good ability of model in simulating soil water and nitrate content and r2 was more than 90 percent which pointed out to well process of simulation of the model. The simulation accuracy was greater at the end of the growing season. Comparing of RMSE statistical index for different depths showed that the simulation accuracy was increased by increasing depth which can be due to changes in surface evaporation and also the effect of environmental factors on surficial layers more than other layers. Generally the best simulation was related to the layer of 80 to 100 cm. And the average RMSE was 0.019 cm3 per cm3 for soil moisture content and 0.22 mg per kg for soil nitrate.In the layer of 80-100 cm the best simulation of soil moisture and nitrate content between treatments was related to N0 by the RMSE equal to 0.024 cm3 per cm3 and 0.21 mg per kg respectively and the weakest simulation was related to N3.The simulated yield in all treatments was less than its actual value. Comparison of simulations between three treatments demonstrated the usefulness of EU-Rotate N to examine the effects of management on, nitrate leaching.
Conclusions: The Eu-rotate-n model without calibration for site location was well capable of estimating soil water and nitrate content under different fertilizer management for Isfahan climatic conditions nevertheless it is suggested to use to calibrate yield functions to improve the yield simulation. Generally we can use Eu-rotate-n model for simulation of water and nitrogen content and eventually approach to integrated and optimal management in the farm in the hot, dry conditions of Isfahan.

Keywords

1- Allen R.G., Pereira L.S., Raes D., and Smith M. 1998. Crop evapotranspiration-guidelines for computing crop water requirements. Irrigation and drainage paper 56, Rome, Italy. 300 p.
2- Azhdary Kh. 2008. Simulation of Water Movement in Soil in Drip Irrigation System in Different Types of Soils. Agricultural Biotechnology, Issue 1. (in Persian with English abstract).
3- Brisson N., Gary C., Justes E., Roche R., Mary B., Ripoche D., Zimmer D., Sierra J., Bertuzzi P., Burger P., Bussiere F., Cabidoche Y.M., Cellier P., Debaeke P., Gaudillere J.P., Henault C., Maraux F., Seguin B., and Sinoquet H. 2003. An overview of the crop model STICS. European Journal of Agronomy, 18:309–332.
4- Brisson N., Mary B., Ripoche D., Jeuffroy M.H., Ruget F., Nicoullaud B., Gate P., Devienne-Barret F., Antonioletti R., Durr C., Richard G., Beaudoin N., Recous S., Tayot X., Plenet D., Cellier P., Machet J.M., Meynard J.M., and Delecolle R. 1998. STICS: a generic model for the simulation of crops and their water and nitrogen balances. I. Theory and parameterization applied to wheat and corn. Agronomie, 18, 311–346.
5- Burns I.G. 1974. A model for predicting the redistribution of salts applied to fallow soils after excess rainfall or evapotranspiration. European Journal of Soil Science, 25:165–178.
6- Casero T., Benavides A., Pay J., and Recasens I. 2004. Relationship between leaf and fruit nutrients and fruit quality attributes in Golden Smoothee using multivariate regression techniques. Journal of Plant Nutrition, 27: 313-324.
7- Cote C.M., Bristow K.L., Charleworth P.B., and Cook F.J. 2003. Analysis of soil wetting and solute transport in sub-surface trickle irrigation. Journal of Irrigation and Drainage Engineering, 22(3-4):143-156.
8- Doltra J., and Mu˜noz P. 2010. Simulation of nitrogen leaching from a fertigated crop rotation in a Mediterranean climate using the EU-Rotate N and HYDRUS-2D models. Agricultural Water Management Journal, 97:277–285.
9- Doltra J., Mu˜noz P., and Anton A. 2010. Soil and plant nitrogen dynamics of a tomato crop under different fertilization strategies. Acta Horticulturae, 852:207–214.
10- Fallahi E. and Simons B.R. 1996. Interrelations among leaf and fruit mineral nutrients and fruit quality in‘‘Delicious’’ apples. Journal of Tree Fruit Production, 1:15–25.
11- Guo R., Nendel C., Rahn C., Jiang C., and Chen Q. 2010. Tracking nitrogen losses in a greenhouse crop rotation experiment in North China using the EU-Rotate N simulation model. Environmental Pollution Journal, 158:2218–2229.
12- Hansen S., Jensen H. E., Nielsen N. E., and Svendsen H. 1991. Simulation of nitrogen dynamics and biomass production in winter-wheat using the Danish simulation-model DAISY. Fertilizer Research, 27:245–259.
13- Jackson L.E. 2000. Fates and losses of nitrogen from a nitrogen-15-labeled cover crop in an intensively managed vegetable system. Soil Science Society of America Journal, 64:1404–1412.
14- karimi z. 2008. Study the effect of mulch on drought tolerance and other quantitative and qualitative characteristics on sweet pepper varieties. msc Dissertation, Ferdowsi University of Mashhad.
15- Keller J., and Bliesner R.D. 1990. Sprinkle and Trickle Irrigation. Published by Van Nostrand Reinhold New York, p:643.
16- Khorami M., Alizadeh A., and Ansari H. 2013. Simulation of Water Movement and Moisture Redistribution under Drip Irrigation Systems Using Hydrus 2D/3D. Journal of Water and Soil, 27(4):692-702.(in Persian with English abstract).
17- Lidon A., Lado L., Berbegall F., and Ramos C. 2011. Influencia de calibracion de los parametros hidraulicos del modelo EU-Rotate N en el balance de N en el cultivo de col china. Actas de Horticultura, 61:52–58 (in Spanish).
18- Malekian R., and Gheisari M. 2012 . Sensitivity analysis of CSM-CERES-MAIZE to field capacity in simulation of nitrogen fate. Journal of water and soil resources conservation, 1(2):1-14. (in Persian with English abstract).
19- Meshkat M., Warner R.C., and Workman S.R. 1999. Modeling of evaporation reduction in drip irrigation system. Journal of Irrigation and Drainage Engineering, 125(6): 315-323.
20- Nangia V., Gowda P.H., Mulla D.J., and Sands G.R. 2008. Water quality modeling of fertilizer management impacts on nitrate losses in tile drains at the field scale. Journal of Environment Quality, 37:296–307.
21- Nendel C. 2009. Evaluation of best management practices for N fertilisation in regional field vegetable production with a small-scale simulation model. European Journal of Agronomy, 30(2):110-118.
22- Nendel C., Venezia A., Piro F., Ren T., Lillywhite R.D., and Rahn C.R. 2013. The performance of the EU-Rotate N model in predicting the growth and nitrogen uptake of rotations of field vegetable crops in a Mediterranean environment. The Journal of Agricultural Science, 151:538–555.
23- NRCS. 2004. Estimation of direct runoff from storm rainfall. In:National Engineering Handbook, Part 630,Hydrology, USDA.
24- Olasolo L., Vazquez M., Suso A., and Pardo A. 2011. Evaluacion del modelo EU-Rotate N en cultivo de patata. Actas de Horticultura, 61:52–58 (in Spanish).
25- Rahn C.R., Zhang K., Lillywhite R.D., Ramos C., De Paz J.M., Doltra J., Riley H., Fink M., Nendel C., Thorup-Kristensen K., Pedersen A., Piro F., Venezia A., Firth C., Schmutz U., Rayns F., and Strohmeyer K. 2010. A European Decision Support System, EU-Rotate_N to predict environmental and economic consequences of the management of nitrogen fertilizer in crop rotations. European Journal of Horticultural Science, 75(1): 20-32.
26- Ritchie J.T. 1998. Soil water balance and plant water stress. In: Tsuji G., Hoogenboom G., Thornton P. (Eds.) Understanding Options for Agricultural Production. Kluwer Academic Publishers. Dordrecht, p. 41–54.
27- Sadeghi A.M., Mcinnes K.J., Kissel D.E., Cabrera M.L., Koelliker J.K., and Kanemasu E.T. 1988. Mechanistic model for predicting ammonia volatilization from urea. In: Bock B.R., Kissel, D.E. (Eds.). Ammonia Volatilization from Urea Fertilizers. National Fertilizer Development Centre, Tennessee Valley Authority, Muscle Shoals, Alabama, p. 67–92.
28- Savage M.J. 1993. Statistical aspects of model validation. Presented at a workshop on the field water balance in the modeling of cropping systems, University of Pretoria, South Africa.
29- Schmitz GH., Shutze N., and Petersohn U. 2002. New strategy for optimizing water application under trickle irrigation. Journal of Irrigation and Drainage Engineering, 128(5): 287-297.
30- Seifi s. 2010. Study the Effects of plant density and pruning on yield and plant growth in two varieties of greenhouse bell pepper. MSc Dissertation, Ferdowsi University of Mashhad.
31- Shaffer M.J., Halvorson A.D., and Pierce F.J., 1991. Nitrate Leaching and Economic Analysis Package (NLEAP): model description and application. In: Follett, R.F., Keeney, D.R., Cruse, R.M. (Eds.), Managing nitrogen for Groundwater Quality and Farm Profitability. Soil Science Society of America, Madison, WI, USA, pp. 285–322.
32- Simunek J., Van Genuckten M.Th., and Sejna M. 2006. The HYDRUS Software Package for Simulating the Two- and Three-Dimensional Movement of Water, Heat, and Multiple Solutes in Variably – Saturated Media. Technical Manual.
33- Skaggs T.H., Trout T.J., Simunek J., and Shouse P.J. 2004. Comparison of HYDRUS-2D simulations of drip irrigation with experimental observations. Journal of Irrigation and Drainage Engineering, 30: 304–310.
34- Soler C.M.T., Sentelhas P.C., and Hoogenboom G. 2007. Application of the CSM-CERES-Maize model for planting date evaluation and yield forecasting for maize grown off-season in a subtropical environment. European Journal Agronomy, 27: 165-177.
35- Soto F., Gallardob M., Gimenezc C., Pe˜na-Fleitasb T., and Thompsonb R.B. 2014. Simulation of tomato growth, water and N dynamics using the EU-Rotate N model in Mediterranean greenhouses with drip irrigation and fertigation. Agricultural Water Management, 132:46–59.
36- Stöckle C.O., Donatelli M., and Nelson R., 2003. CropSyst, a cropping system simulation model. Eur. J. Agron, 18: 289–307.
37- Sun Y., Hua K., Zhangb K., Jiangc L., and Xuc Y. 2012. Simulation of nitrogen fate for greenhouse cucumber grown under different water and fertilizer management using the EU-Rotate N model. Agricultural Water Management, 112:21– 32.
38- Sфgaard H.T., Sommer S.G., Hutching H.J., Huijsmans J.F.M., Bussink D.W., and Nicholson F. 2002. Ammonia wolatilization from field-applied animal slurry-the ALFAM model. Atmospheric Environment, 36:3309–3319.
39- Tognoni F., Pardossi A., and Serra G. 1999. Strategies to match greenhouses to crop production. Acta Horticulturae, 481:451–461.
40- Willmott C.J. 1982. Some comments on the evaluation of model performance. Bulletin of the American Meteorological Society, 63(11):1309–1313.
41- Yang D.J., Zhang T.Q., Zhang K.F., Greenwood D.J., Hammond J.P., and White P.J. 2009. An easily implemented agro-hydrological procedure with dynamic root simulation for water transfer in the crop-soil system: Validation and application. Journal of Hydrology, 370:177-190.
CAPTCHA Image