L. MÁRTON. Research Institute for Soil Science and Agricultural Chemistry of the Hungarian Academy of Sciences, Budapest, Hungary

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1 Cereal Research Communications 36(2), pp (2008) DOI: /CRC Impact of Rainfall, Liming, Nitrogen (N), Phosphorus (P 2 O 5 ), Potassium (K 2 O), Calcium (CaO), Magnesium (MgO) Mineral Fertilization on Triticale ( Triticosecale Wittmack) Yield in a Monoculture in Hungary L. MÁRTON Research Institute for Soil Science and Agricultural Chemistry of the Hungarian Academy of Sciences, Budapest, Hungary (Received 28 March 2007; accepted 16 November 2007) The natural climate variability may be masked by the anthropogenic made global warming, today. With a warmer climate, drought and excess rainfall conditions could become more frequent and longer lasting. The potential increase of the hazards result stresses and high costs in cereal production. For this reason a long-term study was conducted on a sandy acidic lessivated brown forest soil; WRB: Haplic Luvisol in the 44 year old Nyírlugos Field Trial (NYFT) in a Hungarian fragile agroecosystem in Nyírség region (N: , and E: ,) on triticale (x Triticosecale Wittm.) yield between 1999 and In 1962, at the trial set up the soil had the following agrochemical properties: ph (H 2 O) 5.9, ph (KCl) 4.7, hydrolytic acidity 8.4, hy1 0.3, humus 0.7%, total N 34 mg kg 1, ammonlactate (AL) soluble-p 2 O 5 43 mg kg 1, AL-K 2 O60mgkg 1 in the plowed (0 25 cm) layer. The trial consisted of 32 4 = 128 plots in randomised block design. The gross plot size was 10 5 = 50 m 2. The average fertilizer rates in kg ha 1 year 1 were nitrogen 75, phosphorus 90 (P 2 O 5 ), potassium 90 (K 2 O), calcium (CaCO 3 ) and magnesium 140 (MgCO 3 ). The groundwater table had at a depth of 2 3 m below the surface. During drought conditions the respective yield of the control areas was 25% less than for average years. The application N alone or NP and NK treatments led to yield reduction of 19.7%, while that of NPK, NPKCa, NPKMg and NPKCaMg caused an 28.3% yield drop. In the wet years the yield decreased by 22.2% on the unfertilized soils; in case of the N, NP and NK nutrition the yield dropped with an 14.1%; and the yield increased at 13.8% on NPK, NPKCa, NPKMg and NPKCaMg treated plots. Yield dropped in the very wettest year 43.1% on control soils; 39.3% of N, NP and NK loadings, and 35.8% on NPK, NPKCa, NPKMg and NPKCaMg treatments to those in the average year. The relationship between rainfall quantity during the vegetation period and N, P, K, Ca, Mg nutrition and yield was characterised by polynomial correlation (control: R = ***, N: R = ***, NP: R = ***, NK: R = ***, NPK: R = ***, NPKCa: R = ***, NPKMg: * marton@rissac.hu /$ Akadémiai Kiadó, Budapest

2 334 MÁRTON: Plant Environment R = **, NPKCaMg: R = **). However, total regression coefficients ranged from 0.43 to 0.74 in depence on the different nutrient application. Maximum yields of t. ha 1 were achieved in the rainfall range of mm. At values above and below this domain of the precipitation the grain yield reduced quadratically. So, it can be stated that both drought and excess rainfall conditions resulted dramatically significant negative effects between fertilization (N, P, K, Ca, Mg) and triticale yield. Keywords: rainfall, liming, fertilization, triticale, yield Introduction The present increase of greenhouse gases (GHG) such as carbon dioxide, methane, water vapor, ozone, nitrous oxide, sulfur hexafluoride, hydrofluorocarbons, perfluorocarbons and chlorofluorocarbons in the atmosphere (Rosenzweig and Parry 1994; Alan 1999; Easterling et al. 1999; Johnston 2000) probably will lead to significant climate changes in the 21 st century (Barrow et al. 2000; Márton 2002; Rajendra 2004; Watts 2005; Márton 2005; Rosenzweig and Iglesias 2003; Fountaine 2006). A recent consensus has emerged that among the GHG, the increase of atmospheric CO 2 concentration is of greatest concern (Márton 2002; IPCC 2004; Láng et al. 2004; Láng 2005; Márton 2006). Decades ago, researchers asked what effects climate change may have on the cereal ecology (Marschner 1995; Houghton et al. 1990; Várallyay 1992; Harnos 1993; Burman and Pochop 1994; Jan et al. 1994; Fakhri 1996; Harrison and Butterfield 1996). Today, researchers are asking how to respond to, and take advantage of the effects of climate change (Márton 2002; IPCC 2004; Láng et al. 2004; Láng 2005). Most researchers believe that higher temperature, drought and rainfall excess caused by climate change will depress on crop yield at many places in the coming decades (Voss et al. 1970; Russel and Jennifer 1991; Bullock et al. 1995; Rajendra 2004; Jolánkai 2005; Watts 2005; Márton, 2005, 2006; Pilar et al. 2006). Thus, many agricultural investigations focused on understanding the relation between mean climate change and crop production (Runge 1968; Várallyay 1992, 2005; Láng 2005; Watts 2005; Márton 2005; Rosenzweig and Iglesias 2003). Changes in weather patterns were observed throughout Europe including Hungary as early as 1850 (Rácz 1999). Till now, few investigations studied the effects of climate variability on agriculture crop yields (Wigley 1999; Németh 2004; Seth and Yeffrey 2005; Szász 2005; Várallyay 2005). However, the response of agricultural crop yield to changes in climate variability was attributed primarily to changes in the frequency of extreme climatic events (EU 2003). Triticale is a crop of worldwide importance limited research exists about the effects of climate change on this crop (Lásztity and Márton 1990). The crop is sensitive to the prevailing weather condi-

3 MÁRTON: Plant Environment 335 tions such as rainfall, and for this reason understanding the effects of anthropogenic climate change on its production is important (Márton 2006). In addition to triticale growing season parameters (e.g., soil agrochemical properties, fertilization, liming) affect the growth and yield of crop (Lobell and Asner 2003) and cause yield variations. Understanding the fertilization, liming and rainfall effects have been a continuous endeavor toward improving farming technology and management strategy to reduce the negative impacts to increase the crop yield (Kádár and Szemes 1994; Várallyay 1994; among others). Our main objective of this research it was study and clarify the precipitation amount, precipitation distribution and nitrogen (N)-, phosphorus (P 2 O 5 )-, potassium (K 2 O)-, calcium (CaO)-, and magnesium (MgO) fertilization interaction effects on a sandy acidic lessivated brown forest soil; WRB: Haplic Luvisol in the 44 year old Nyírlugos Field Trial in a Hungarian fragile agroecosystem in Nyírség region on triticale ( Triticosecale Wittm.) yield from 1999 to Furthermore, it was our intent to emphasize that the net effect of multiple environmental changes is far more important than the effect of a single factor on the crop. Materials and Methods The net-influence of rainfall (quantity, distribution) and mineral fertilization (N, P 2 O 5,K 2 O, CaO, MgO) were studied in a long term field experiment established at the Research Institute for Soil Science and Agricultural Chemistry of the Hungarian Academy of Sciences Experiment Station (RISSAC-HAS ET) in Hungary on a Haplic Luvisol (sandy acidic lessivated brown forest soil) with triticale ( Triticosecale Wittm.) indicator crop under fragile agroecological circumstances at Nyírlugos for 8 years from 1999 to The main experiment s soil agrochemical characteristics in the plowed (0 25 cm) layer are presented in Table 1. at the experimental set up in 1962 (Láng 1973). From 1980 to 2006 the experiment consisted of 32 4 = 128 plots in randomized block designs. The gross plot size has been having 10 5 = 50 m 2. The experimental treatments and combina- Table 1. The main soil agrochemical properties in the plowed (0 25 cm) layer at the experiment set up in 1962 (Brown forest soil, acid sand; WRB: Haplic Luvisol, Nyírség region Nyírlugos) Content ph HA* Hy 1 Humus Total AL** (H 2 O) (KCl) nitrogen P 2 O 5 K 2 O % 0.7 mg.kg * Hydrolytic acidity, ** ammoniumlactate (AL) soluble

4 336 MÁRTON: Plant Environment tions are shown in Table 2. The fertilizers were applied in the form of 25% calcium ammonium nitrate, 18% superphosphate, 40% potassium chloride, calcium carbonate and magnesium sulphate. The groundwater table had a depth of 2 3 m below the surface. The plant samples had taken by manually at the harvest time. Rainfall amounts (deviation in rainfall from the average over many years: dry year 10 20%, drought year 20% over, wet year %, year with excess rainfall +20% over) and other related data determined on traditional Hungarian (Harnos 1993) and Research Institute for Soil Science and Agricultural Chemistry of the Hungarian Academy of Sciences (Márton 2004) standards, and MANOVA (Multivariate Analysis of Variance) by SPSS test (SPSS Inc. 2000). Table 2. Fertilization and liming treatments in the experiments, kg ha 1 year 1 between 1962 and 2006 (Brown forest soil, acid sand; WRB: Haplic Luvisol, Nyírség region Nyírlugos) Treatment Applied kg ha 1 yr 1 Levels N P 2 O 5 K 2 O CaCO 3 MgCO Note: In the form of Ca-ammonium-nitrate, superphosphate, potassium chloride, powdered limestone and dolomite. Results and Discussion During drought conditions, in conformity with Adams et al. (1995), Rosenzweig and Tubiello (1997) and McMaster (1999) the respective yield of the control areas was 25% less than for average years (Tables 3, 4, 5). The application of N alone or of NP and NK treatments led to yield losses of 19.6%, while that of NPK, NPKCa, NPKMg or NPKCaMg caused an 28.3% drop during this type of years. In the wet years the yield decreased by 22.2% in the unfertilized plots; in case of the N, NP or NK nutrition with an 14.1%; and increased at 13.8% on NPK, NPKCa, NPKMg and NPKCaMg treatments. In the very wettest year the yield dropped 43.1% on control soils; 39.3% of N, NP or NK loadings; and 35.8% on NPK, NPKCa, NPKMg and NPKCaMg treatments to those in the average year reverse of Asbjorn et al. (2004). The relationship between rainfall quantity during the vegetation period and N, P, K, Ca and Mg nutrition and yield was characterized by polynomial correlation (control: R= ***, N: R = ***, NP: R = ***, NK: R = ***, NPK: R = ***, NPKCa: R = ***, NPKMg: R = **, NPKCaMg: R = **).

5 MÁRTON: Plant Environment 337 Table 3. Values of the crop specific drought index (CDI) for triticale ( Triticosecale Wittm.), in average*, droughty, wet and very wet years, in the 44 year old Nyírlugos Field Trial between 1998 and 2006 (Brown forest soil, acid sand; WRB: Haplic Luvisol, Nyírség region Nyírlugos) Year Period WHY SHY M MPS V HM Average Droughty Mean Wet Very wet Mean Total for mean Note: * Equivalent to the 50 year ( ) rainfall mean in Nyíregyháza-Napkor. WHF = winter half-year (Oct. Mar.), SHY = summer half-year (Apr. Sep.), M = month (Oct. Sep.), MPS = month prior to sowing (Aug.), V = vegetation period (Sep. Jul), HM = harvesting month (Jul.) Table 4. Frequency with which critical months followed each other during the winter half-year, summer half-year, month, vegetation period and in the whole year, in the 44 year old Nyírlugos Field Trial between 1998 and 2006 (Brown forest soil, acid sand; WRB: Haplic Luvisol, Nyírség region Nyírlugos) Experimental Frequency year WHY SHY M V WY (2) 1(2) 1(2) 1(2) (9) 1(9) 1(9) 1(9) ( 3) 1( 3) 1( 3) 1( 3) (5) 1(5) (9) 1(9) 1(9) Mean 1(1) 1(3) 1(2) 1(3) Note: WHF = No. of consecutive critical months during the winter half-year (Oct. Mar.), SHY = No. of consecutive critical months during the summer half-year (Apr. Sep.), M = No. of consecutive critical months during the year months (Oct. Sep.), V = No. of consecutive critical months during the vegetation period (Sep. Jul), WY = No. of consecutive critical months during the whole year (Oct. Sep.).

6 338 MÁRTON: Plant Environment Table 5. Effect of mineral fertilization and liming on triticale (x Triticosecale Wittm.) grain yield (t ha 1 ) in average*, droughty, wet and very wet years, in the 44 year old Nyírlugos Field Trial between 1998 and 2006 (Brown forest soil, acid sand; WRB: Haplic Luvisol, Nyírség region Nyírlugos) Treatment Year character Total Average Droughty Mean Wet Very wet Mean for mean Control N N N N2P N2P N2P N2K N2K N2K N2P2K N2P2K2Ca N2P2K2Mg N2P2K2Ca2Mg LSD5% Mean Note: *Equivalent to the many years mean.

7 MÁRTON: Plant Environment 339 However, the total regression coefficients ranged from 0.43 to 0.74 in dependence on the different nutrient application. Maximum yields of t ha 1 were achieved in the rainfall range of mm. At values above and below this range the grain yield reduced quadratically. To sum up we can state that rainfall, liming and mineral fertilization changes will gradually and abruptly affect the Hungarian and European triticale production today in similarly with Semenov and Porter (1995). So, the greater incidence and intensity of extreme weather events as the rainfall changes and expanded ranges of agrochemicals as the fertilizers possible lead to significant yield reductions in triticale in the nearest future. Acknowledgements This research was supported by Hungarian Academy of Sciences, H-Budapest and the Hungarian and Spanish Intergovernmental S & T Cooperation Project of E-2/04-OMFB-00112/2005 and Hungarian and Indian Intergovernmental S & T Cooperation Project of IND-3/03/2006-OMFB 00295/2006. Our thanks also go to anonymous reviewers and the editor, Prof. Dr. Zoltán Kertész, whose comments helped to improve the clarity of these manuscript. References Adams, R.M., Fleming, R.A., Chang, C.C., McCarl, B.A., Rosenzweig, C A reassessment of the economic effects of global climate change on U.S. agriculture. Climatic Change 30: Alan, W A deep antropocentric approach to environmental ethics. The Department of Environmental Science and Policy Journal 2: Asbjorn, T., Michelle, T., Bárd, R Climate Change Impacts on Agricultural Productivity in Norway. CICERO, Oslo, Norway, 34 pp. Barrow, E.M., Hulme, M., Semenov, M.A., Brooks, R.J Climate change scenarios. In: Downing, T.E., Harrison, P.A., Butterfield, R.E., Londsdale, K.G. (eds), Climate Change, Climatic Variability and Agriculture in Europe. European Commission, Brussels, 76 pp. Bullock, P., Le Houérou, E., Hoffman, M.T., Rounsevell, M.D.A., Sehgal, J., Várallyay, G Land degradation and desertification. In: Watson, R.T. Zinyowera, M.C., Moss, R.H. (eds), Climate change 1995: Impacts, adaptations and mitigation of climate change: Scientific-technical analyses. Cambridge University Press, United Kingdom and New York, Cambridge, 879 pp. Burman, R., Pochop, L.O Evaporation, evapotranspiration and climatic data. University Wyoming, Laramie, USA, 181 pp. Easterling, D.R., Evans, J.L., Groisman, Ya.P., Karl, T.R., Kunkel, K.E., Ambenje, P Observed variability and trends in extreme climate events. A brief review. Bulletin of the American Meteorological Society 81: EU (European Union) Drought costs EU farmers Euro of 11 billion. European Commission, Brussels, 2 pp. Fakhri, A.B Global climate change and agricultural production. FAO, Rome, Italy, 338 pp.

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