Evaluation of CSM-Ceres-Maize Model for Simulating Maize Production in Northern Delta of Egypt

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There is widespread consensus that Egypt is among the developing countries that are most vulnerable to the likely negative impacts of climate change. Northern Egypt is the most threaten area under Egyptian conditions. The expected climate change
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   Life Science Journal 2013;10(4) http://www.lifesciencesite.com 3179 Evaluation of CSM-Ceres-Maize Model for Simulating Maize Production in Northern Delta of Egypt Abdrabbo M. A. A. 1,* , F. A. Hashem 1 , Maha L. Elsayed 1 , M. A. Abul-Soud 1 , A. A. Farag 1 , Maha M. Hamada 2 , and K.M. Refaie 1 1 Central Laboratory for Agricultural Climate, Agricultural Research Center, Dokki 12411, Giza- Egypt 2  Agronomy Department, Faculty of Agriculture, Ain Shams University, Cairo, Egypt abdrabbo@yahoo.com  Abstract: There is widespread consensus that Egypt is among the developing countries that are most vulnerable to the likely negative impacts of climate change. Northern Egypt is the most threaten area under Egyptian conditions. The expected climate change impacts are the driving force to investigate the suitable sowing date and irrigation requirements to face the food security needs. A field study was conducted in 2011 and 2012 at El-Bosaily farm in the Northern coast of Egypt. The main objectives of this study were to adapt maize production under expected climate change impacts via evaluating the response of the Single Cross 10 maize (  Zea mays  L.) hybrid to three different sowing dates (SD) (1 st  and mid of May and 1 st  of June) and four applied irrigation levels 0.6, 0.8, 1.0 and 1.2 of ET c  which applied by drip irrigation system. No. of leaves, leaf area index, number of days for 50 % tasseling and silking, grain yield (g/plant), average weight of 100 seeds and straw yield (g/plant) were determined beside water use efficiency. The obtained results showed that the 0.6 and 0.8 of (ET c ) irrigation treatments attributed to decline vegetative growth as well as growth yield. Nevertheless, the 1.2 irrigation treatments gave the highest grain yield and vegetative growth which was compensated the amount of water consumed. The highest yield was obtained  by the second sowing date followed by the third one. The final results show that the 0.6 irrigation level gave the highest water use efficiency; increasing irrigation water above 0.6 from ET c  led to decrease water use efficiency. The lowest value of seasonal water consumption was recorded by the first sowing date while the second date gave the highest seasonal water consumption. Calibration and validation of CERES-Maize crop simulation model using experimental datasets of years 2011 and 2012 were done successfully giving very excellent values for RMSE and d-Stat evaluation indexes. Environmental modification option of the model was used to rise maximum and minimum temperature by 1.5 o C and 3.5 o C for both seasons. Reductions in grain yield for 1.5 o C scenario arrived to -25.1 than 2011 year and -31.9% than 2012 year. Using 3.5 o C scenario caused declines in grain yield arrived to -54.8% than 2011 year and -66.2% than 2012 year. [Abdrabbo M. A., F. A. Hashem, Maha L. Elsayed, A. A. Farag, M. A. Abul-Soud, Maha M. Hamada and K.M. Refaie.  Evaluation of CSM-Ceres-Maize Model for Simulating Maize Production in Northern Delta of Egypt.    Life Sci J   2013;10(4):3179-3192]. (ISSN:1097-8135). http://www.lifesciencesite.com. 425 Keywords: Water requirement, sowing date, grain and straw yield, evapotranspiration, agro-meteorological data, crop simulation model, climate changes, and water use efficiency. 1. Introduction: Maize is one of the most important cereal crops grown principally during the summer season in Egypt. Compared to other crops, maize is more efficient in water use (Jensen, 1973) . Maize and other C4 crop species have nearly 2-fold higher water use efficiency than C3 species (Begg and Turner 1976) . The efficient use of water by modern irrigation systems is  becoming increasingly important in arid and semi-arid regions with limited water resources ( El-Hendawy et al., 2008 ). Egypt is very dependent on natural resources that are vulnerable to climate change. The Nile Delta region is considered under many studies as a homogenous agriculture region in Egypt. Whereas, the  Northern Nile Delta could be the highest vulnerable sub-region in the Nile Delta due to the combination effect of natural, human, agriculture management, and economical and political conditions. Crop yields and crop water use could be affected by climate change ( Medany and Attaher, 2009) . In environments of high light intensity and temperature, the higher water use efficiency (WUE) is due mainly to higher rates of photosynthesis by C4 crops, which results in more dry matter (DM) accumulation. However, because maize produces larger quantities of DM per acre than most other crops, soil moisture deficit can occur quickly, especially during reproductive growth. Water loss in maize fields is primarily by surface evaporation from bare soil during early vegetative growth but shifts to evapotranspiration as the tassel begins to emerge and reproductive growth begins (Howell et al  ., 1990; Yordanov  et al. , 1997; Sadler et al. , 2000) . Soil moisture deficit has been considered an economic and efficient means of utilizing drought-prone areas when appropriate management practices to reduce water losses are needed (Turner, 1991) . Shani and Dudley   Life Science Journal 2013;10(4) http://www.lifesciencesite.com 3180 (2001)   & Kijne et al.  (2003) refer to the economic grain yield divided by the volume of water consumed in the production of that yield expressed in kg grain  per cubic meter of water.   The applied water-yield relationship is more complex. At low levels of applied water, up to about 50 percent of full irrigation, yields increase more or less linearly with applied water. Beyond the point of maximum yield the yield turns downward, reflecting yield losses from anaerobic root zone conditions, disease and leaching of nutrients from excessive water use particularly in the heavy clay soil  (Vaux and Pruitt, 1983;   Norwood, 2000; Erdem et al., 2006) . Al-Kaisi and Yin (2003)  tested the effect of different water regime on maize vegetative growth and yield. They found that the differences between 0.80 ETc and 1.00 ETc treatments were not significant while the lowest plant growth and yield was obtained from 0.60 ETc treatment in the two seasons. The same authors added that the 0.80 irrigation treatment had the same or even greater WUE than 1.00 ETc and 0.60 ETc. Al-Bakeir (2003)  found that excessive water application significantly reduced N, P and K absorption of maize  plants. In addition, Al-Kaisi and Yin (2003) found that maize leaf N concentrations were reduced with increasing applied water quantity, even though N was applied with drip irrigation, leaf N concentrations with the 0.80 treatment were generally equal to or higher than the concentrations with 1.00 ETc. Killi and Altanbay (2005)  observed that seed weight was significantly affected by the sowing dates. The plants planted during the early part of the year (February-April) passed through lower temperature during early phases and completed their life cycle taking longer period, and they had higher seed weight, and the plants planted during the later section of the year, July-August, had higher temperature during the early phases and completed their life cycle rapidly, and therefore had lower seed weight. Andrade, (1995) and  Dahmardeh, (2012)  reported that seed weight decreased due to the change in sowing dates. The differences in seed weight might be due to the environmental conditions, mostly observed during the  plant life cycle ( Beiragi et al. , 2011 ). Environmental changes associated with different sowing dates (sunshine, temperature, relative humidity and etc.,) have a modifying effect on the growth and development of maize plants. Each hybrid has an optimum sowing date, and the greater the deviation from this optimum (early or late sowing), the greater the yield loss ( Berzsenyi and Lap   2001; and  Beiragi et al  .,   2011) . Sowing date was reported to affect the growth and yield of maize significantly. To date, the challenge for maize growers is finding the narrow window between sowing too early and sowing too late ( Abdrabbo et al.,  2013 ). Therefore, this study was designed to study the behavior of maize hybrid under different sowing dates and irrigation levels using drip irrigation system. CERES-Maize model is one of the Decision Support System for Agrotechnology Transfer (DSSAT) package of models ( Jones et al. , 2003 ), and it’s one of the srcinal crop models implemented in DSSAT by Jones and Kiniry (1986) . It has been chosen as one of the most used models in the field of crop simulation and one of the most efficient models that marked with: a friendly interface, more input details leads to more accurate simulation, and had open source software obtained by visiting DSSAT website (www.dssat.net) . This model has also ability to modify easily in weather data input files through an option called “environmental modification”, which facilitates drawing different future scenarios of climate change. Aim of evaluating this model was to calibrate and validate it using the experimental input data of both years 2011 and 2012, in order to be ready as a tool for future predictions of maize crop growth and yield under forecasting climate changes. 2.Material and Methods: The experiments were carried out at El- Bosaily (31 o  40' N; 30° 40' E), Protected Cultivation Experimental Farm, Central Laboratory for Agricultural Climate (CLAC), Agricultural Research Center (ARC), at Behaira Governorate, in the  Northern Coast of Egypt . Maize   (  Zea mays L .) hybrid (Single Cross 10 (SC 10)) seeds were used under this study. Data in Table (1) shows the measured climatic factors (Maximum air temperature °C  (Max. temp.), minimum air temperature  °C  (min. Temp.), average relative humidity % (Ave. RH), soil temperature °C  (Soil Temp.) and wind speed (m/sec.) during the experimental period; these data collected from automated climatic station allocated at the experimental site. The treatments comprised three sowing dates (SD)(1 st of May, mid of May and 1 st  of June of 2011 and 2012 for the first and second seasons, respectively) and four irrigation levels (0.6, 0.8, 1.0 and 1.2 of ETc). Calculations of irrigation levels were done weekly while the irrigation control done via manual valves for each experimental plot. The total amount of irrigation water was calculated by Penman method ( Penman, 1984). The potential evepotranspiration was calculated as follows: ET o  = C {W. Rn (1-w)-F (u) (Ea-Ed)}……………mm/day ET o  = Reference evapotranspiration [mm d 1 ].   C = the adjustment factor (ratio of U day to U night). Rn = Net radiation in equivalent evaporation expressed as mm/day.   Life Science Journal 2013;10(4) http://www.lifesciencesite.com 3181   W = temperature of altitude related factor. F (U) = Wind related function. Ea – ed= Vapour pressure deficit (m. bar). Ea =Saturated vapour pressure (m.bar). Ed = Mean actual vapour pressure of the air (m. bar). The second step was to obtain values of water consumptive use (ET crop ) as following (Doorenbos and Pruitt, 1977) : ET c  = ET o     K  c     L %   100/ IE.......mm / day Where ET c = ET   for crop mm/day K  c  = Crop coefficient [dimensionless]. ET o  = Reference crop evapotranspiration [mm/day]. L% = Leaching fraction (assumed 20% of total applied water). IE = Irrigation efficiency of the irrigation system in the field, (assumed 80% of the total applied water). Table (1): Average monthly climatic data of the El-Bosaily location during the two studied seasons 2011 and 2012 .   First season (2011) Month   Max. temp. Min. temp. Ave. RH Soil temp. Wind speed °C °C % °C m/sec. May 27.2 14.75 73.3 23.6 0.53 June 30.9 17.9 76.1 26.6 0.63 July 30.1 20.9 77.7 29.5 0.67 August, 31.8 23.2 82.9 30.6 0.52 September, 31.1 21.1 79.1 28.7 0.53 October 31.2 19.3 79.4 27.2 0.35 Second season (2012)   May 28.0 11.8 76.2 25.2 0.51 June 33.1 16.2 78.6 29.3 0.49 July 35.1 20.3 78.8 32.0 0.54 August, 36.0 22.6 77.4 30.9 0.47 September, 34.5 20.5 78.6 27.8 0.37 October 31.3 19.7 82.3 25.1 0.27 Each total amount of irrigation water was measured by water flow-meter for each treatment. Table (3) and Figure (1) shows the seasonal water consumption (ET crop ) for single cross 10 maize hybrid under different irrigation treatments for the three sowing dates at El-Bosaily site during the two seasons. Plants were irrigated by using drippers of 2 l/hr capacity. The chemical fertilizers were injected within irrigation water system. The experiment was designed in a split plot arrangement with three replications. Sowing dates were distributed in the main plots, and irrigation levels allocated in the sub plots. Plot area was 15 m length x 14 m width, occupying an area of 210 m 2 . Plant distances were 0.30 m apart; the distances between rows were 0.70 m. A distance of 2m was left between each two irrigation treatments as a border among the treatments.   Table (2):   Seasonal irrigation quantities for single cross 10 maize hybrid under experimental conditions for seasons 2011 and 2012. Sowing date First season (2011) Irrigation level 0.6 0.8 1.0 1.2 Average 1 st   1367 1822 2278 2734 2050 2 1464 1952 2440 2928 2196 3 d   1440 1920 2400 2880 2160   Average 1424 1898 2373 2847 Second season (2012) 1 st   1457 1942 2428 2914 2185 2 d   1517 2023 2529 3035 2276   3 1492 1990 2487 2984 2238 Average 1489 1985 2481 2978   Life Science Journal 2013;10(4) http://www.lifesciencesite.com 3182 Figure (1):   Seasonal irrigation quantities under different water levels for single cross 10 maize hybrid under experimental conditions for seasons 2011 and 2012. Table (3) shows the rates of fertilizers were added in both seasons. The total amount of phosphorus (Super  phosphate form) was applied with the soil preparation (30 kg P 2 O 5 / feddan). Fifteen kilograms of K  2 O (Potassium sulphate form) and twenty kilograms of N (Ammonium sulphate form) per feddan were applied as starter fertilizer added also with soil preparation. Remained quantity of N (Ammonium nitrate form) and K fertilizers (Potassium sulphate form) was injected into irrigation system by using venture during the season. The same fertilization schedule was added for all sowing dates and all irrigation treatments. Table (3): Applied fertilization rates for maize at summer season of 2011 and 2012.   Fertilizer application  N-P-K fertilization (kg/ feddan) P 2 O 5  K  2 O N Base fertilizers 30 15 20 Season fertilizer 0 12 126 Total fertilizers 30 27 146 Samples of ten plants of each experimental plot were taken to determine some growth parameters after 75 days from sowing, i.e. no. of leaves, leaf area index and number of days for 50 % tasseling and silking. At harvest time, the grain yield (g/plant), average weight of 100 seeds and straw yield (g/plant) were determined from each plot. The water use efficiency (WUE) was calculated according to FAO (1982)  as follows: The ratio of crop yield (Y) to the total amount of irrigation water use in the field for the growth season (IR); WUE (kg/m 3 ) = Y (kg)/IR (m 3 ). Water use efficiency and seasonal water consumption were determined after harvesting. Harvesting time was done after 120 days from sowing. Chemical properties of the experiment’s soil were analyzed before cultivation according to Chapman and Pratt (1961)  and the results are tabulated in Tables (4). The permanent wilting point (PWP) and field capacity (FC) of the trial soil were determined according to Israelsen & Hansen (1962). Plant samples were dried at 70 o C in an air forced oven for 48 h. Dried leaves and fruits were digested in H 2 SO 4  and N,P and K contents were estimated in the acid digested solution by colorimetric method (ammonium molybdate) using spectrophotometer and flame photometer ( Chapman and Pratt, 1961 ). Total nitrogen was estimated by Kjeldahl method, whereas  phosphorus was determined by spectrophotometer and  potassium by flame photometrical method according to  Chapman and Pratt (1961) . Table (4) Chemical and physical properties of the experiment’s soil analyzed before cultivation. Physical properties Sand (%) Silt (%) Clay (%) Texture F.C. (%)   W.P. (%)  pH O. M. (%) B. D. E.C. (dS m -1 ) 84.5 5.6 9.9 Sandy 17 8 7.75 0.31 1.21 1.25 Chemical properties  pH ECe (dS/m) Cations (meq /l)   Anions (meq /l)   Ca ++ Mg ++  Na + K  + Cl - CO 3-- HCO 3-   SO 4-- 7.75 1.25 2.80 2.15 6.69 0.9 4.50 - 1.90 6.14   Life Science Journal 2013;10(4) http://www.lifesciencesite.com 3183 Analysis of data was done, using SAS program for statistical analysis. The differences among means for all traits were tested for significance at 5 % level according to Waller and Duncan (1969).  All other agriculture practices of maize cultivation were done in accordance with standard recommendations for commercial growers by the Ministry of Agriculture. Field data of the grown maize experiment for both seasons were used to calibrate and validate a model specialized in crop simulation. CERES-Maize crop simulation model was the model used from DSSAT Package software ( Jones et al. , 2003 and Hoogenboom et al. , 2012 ). A latest version of the software package (DSSAT v. 4.5) was used for this simulation study. Data of season 2011 was used to calibrate the model, while data of season 2012 was used to validate the model performance. Table (5) shows genetic coefficients used in cultivar file of the model after calibration and validation processes. Evaluation of model simulation performance compared with observed values of the experiment was done using two statistical indexes, which are the Root Mean Square Error (RMSE) ( Loague and Green, 1991 ) and d-Stat index of agreement ( Willmott et al,. 1985 ). These two indications were checked several times through running the model by changes of genetic coefficient until we arrived to the optimum values  between observation and simulation, controlling that under all experimental conditions of sowing dates (SD1, 2, 3) and irrigation levels (Irr. 0.6, 0.8, 1.0, & 1.2). For future prediction, two different climate scenarios have been implemented in CERES-Maize model files in order to study the effects of future climate changes on maize plant growth and yield. Scenarios were done by adding 1.5°C and 3.5°C to maximum and minimum temperatures of the summer season of years 2011 and 2012 starting from the three different sowing dates indicated at conducted field experiments and finishing by the end of growing cycle. Table (5): Genetic coefficients used in SCIO maize cultivar file of the model after calibration and validation  processes. Cultivar Coefficinet Definition Value Single Cross 10 P1 Thermal time from seedling emergence to the end of the  juvenile phase (expressed in degree days above a base temperature of 8 o C) during which the plant is not responsive to changes in photoperiod. 190.0 P2 Extent to which development (expressed as days) is delayed for each hour increase in photoperiod above the longest photoperiod at which development proceeds at a maximum rate (which is considered to be 12.5 hours). 1.000 P5 Thermal time from silking to physiological maturity (expressed in degree days above a base temperature of 8 o C). 1000 G2 Maximum possible number of kernels per plant. 850.0 G3 Kernel filling rate during the linear grain filling stage and under optimum conditions (mg/day). 7.00 PHINT Phylochron interval; the interval in thermal time (degree days) between successive leaf tip appearances. 49.00 3.Results and Discussion: Vegetative growth and yield The effect of different irrigation levels and sowing dates on vegetative growth characteristics of maize hybrid is illustrated in Table (6). The differences among the sowing dates for SC 10 hybrid were significant; data show that second sowing date had the highest vegetative growth in terms of leaf area index followed by the third sowing date with significant difference between them. The number of leaves had a different trend; first sowing date had the highest number of leaves along with the second sowing date. The number of days to 50 % tasseling and silking shows that; the longest time for 50 % tasseling and silking was obtained by first sowing date followed by second sowing date. Regarding the effect of different irrigation treatments, data showed that increasing irrigation level up to 1.20 of ETc increased maize number of leaves, and leaf area index significantly followed by 1.00 and 0.80 treatments. The lowest vegetative growth was obtained by 0.60 irrigation level treatment during the two studied seasons. Regarding the number of days to 50 % tasseling and silking; differences between 1.2, 1.0 and 0.8 ETc   were   not significant only for numbers of days for 50 % tasseling in the 1 st  season. Regarding the interaction effect between different irrigation levels and different sowing dates, data showed that the highest values for number of
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