Campbell, C.A.

Selles, F.

Zentner, R.P.

English

University of Saskatchewan Research Archive

SPRING WHEAT RESPONSE TO NITROGEN AND WATER. F.Selles, R.P. Zentner and C.A. Campbell Agriculture Canada, Research Station Swift Current, Saskatchewan. S9H 3X2 INTRODUCTION The semiarid environment of southwestern Saskatchewan has resulted in cropping schemes with a high incidence of summerfallow. The two year fallow-wheat r6tation is preferred because it increases spring soil water reserves and stabilizes farm income (Zentner et al. 1979); however, it is also asso-ciated with high soil degradation. Consequently, it is desirable to reduce the proportion of fallow in crop rotations. Recent technological develop-ments such as reduced tillage practices, more efficient and affordable herbicides, higher yielding wheat cultivars and management practices such as snow trapping have made extended cropping systems less risky. Successful stubble cropping requires, among other things, a better tuned fertilizer strategy. In a previous study (Selles et al. 1985) it was shown that regardless of fertility level, water is the main factor determin-ing the yield of grain crops in the Brown soil zone of Saskatchewan. This fact has been recognized by the Provincial Soil Testing Laboratories of Saskatchewan and Alberta. However, the degree to which the recommended N fertilizer rates must be adjusted to reflect spring soil water and antici-pated growing season rainfall have not been clearly defined. The objective of this study was to develop production functions relat-ing the yield of hard red spring wheat (HRWS) grown on stubble to available spring soil water, growing season precipitation, soil No 3.:..N in the fall, and applied fertilizer N. MATERIALS AND METHODS Yield data from fertilizer trials carried with HRSW seeded on stubble at Swift Current from 1982 to 1986 were correlated to soil No 3-N in the first 60 em, available spring soil water in the 0-120 em depth, and May-July precipitation. The experimental plots received fertilizer N as 34-0-0 mid-row banded at seeding time at rates ranging from 0 to 100 kg/ha; fertilizer P as 11-51-0 was also applied with the seed at a rate of 20 kg/ha of P2o5• For the purposes of this study it was assumed that the crop could not distinguish between soil N and that supplied as fertilizer, nor between stored spring soil water and growing season precipitation. Thus, grain yields were regressed against total available N (soil plus fertilizer N) and and total available W (soil plus rainfall water) using a second degree polynomial of N and W. RESULTS AND DISCUSSION During the duration of the study, a wide range of environmental condi-335 tions 'ftlas encountered (Table 1). Hoisture conditions varied from the above normal precipitation during 1982 and 1986 to extreme drought during 1984 and 1985. Fall soil NO~-N in the first 60 em of soil varied from 13 to 46 kg/ha, and spring soil moisture ranged from -39 to 70 mm (soil water - PWP). Table 1. Available spring soil water, May-July precipitation, and soil test N YEAR 1982 1983 1984 1985 1986 + SPRING HATER (mm) 42 70 30 _.,39 11 JV.i.AY-JUI,Y RAINFALL (mm) 244 187 100 73 205 NO ~N o-6o em (kg/ha) 20 25 13 32 46 + Available \<Tater in 0-120 em soil depth The regression analysis j using the backward elimination procedure and no intercept indicated that the only significant terms were the interaction of the square of water with nitrogen and the square of water with the square of nitrogen. This produced the following highly significant production function (P < 0001): 2 R = 0.935 [I] The amount of total available N required for maximum yield (N is obtained by solving the first derivative of thi.s equation for N. fifXthis case N 1:11as 112 kg/ha, and was independent of the level of available water. lljflamination 2f N values ob·tained from regression equations of the form y= a + bN + eN , c:'f~ulated for each year, indicated that in ~' of the 5 years N varied between 92 and 131 kg/ha (Table 2). In the remaining year N wa~a~l6: but, here the regression was not significant. max · Table 2. Values of N obtained for individual vear regressions. max ~ 1982 1983 1984 1985 1986 115 110 -16 92 131 336 3026 2165 695 573 2091 o. 92 0.99 -.38 0.13 0.94 The yield achievable when N is not limiting (Y ) is obtained by: max Y = 0.039*W2 max (2] The magnitude of the slope of w2 is similar to that found by Staple and Lehane (1954) in their quadratic model relating grain yields with evapo-transpiration. We also developed a highly significant (P < 0.0001) relationship using a linear term for water: Yield= 0.1812*W*N- 0.000848*W*N 2 . 2 R = 0.956 [ 3] Solving this equation for N gives 107 kg/ha and an expression for Y of: max max Y = .·9. 68*W [ 4] max The slope. of the Y for this second model is similar to that reported by Staple and Lehane Ifi.~54) for their linear model, and to that reported by Campbell et al. (1987) in a recent study of crop rotation at Swift Current. This indicates that in spite of the improvements in HRSW varieties, the yield increases per unit of additional water has remained largely unchanged from that of 40 years ago. To select the most appropriate function, the predicted yields of each of the functions was regressed against the actual yields and an F test was applied to these regressions to determine whether the slope=! and inter-cept=O. Results of this test (Table 3) indicate that equation (3) was better than equation (1); thus, the discussion on this paper is based on equation (3). Table 3. F test for the slope and intercept of the actual v/s estimated yields obtained with the two models. EQUATION Y=A*W*N+B*W*N2 Regressor Intercept Slope F value 0.006 0.366 df 1/30 1/30 + Probability 0.938 0.549 .832 + Probability of having a value 0 for the intercept and 1 for the slope. Although N is of interest from a research point of view, producers are interested iWa~ rate of N that maximizes net returns (N ). This total available N level is obtained at the point on the productf~gnsurface where the the value of the additional yield obtained is equal to the cost of the last increment of fertilizer. In other words: 337 dY/dN X p,-,, Cn 1vhere Pw is the price of -.rheat Cn is the cost of nitrogen [ 5 J Although the theoretical maximum return is obtained by using equation (5), it is often desirable to include other factors such as risk. The Sas-katchewan Soil Testing Laboratory, for example, bases their recommendations on the assumption that he last dollar spent on fertilizer produces 1. 5 dollars of additional yield. In other words (using equation (3) and solving for N ) : econ N econ (0.1812 ~ (1.5 x Cn)/(nv x W))/ 0.001696 [ 6] Eauation 6 indicates that N is proportional to the nitrogen/wheat . h f econ, c~ 1'). price ratio and to t e amount o toea~ available water tig. . The usefulness of this model is that it explicitly recognizes the moisture by fertilizer interaction~ and allows the user to assign probabili~ ties chances) of being successful with stubble cropping. When this model is combined with a probability of rainfall (Fig. 2), it allows producers to obtain a better estimation of the N rates they should apply to their spring wheat crop providing the amount of plant available water in the spring and the content of the soil to 60 em in the fall are known. A small computer model has been built: using equations (3) and (6)" The model 1<1orks first asking the producer what level of risk he is able or willing to take~ this is transformed into a probability which is used to calculate the precipitation level corresponding to his risk preference using a probability of rainfall distribution such as the one presented in Fig. 2. Next the depth of moist soil in spring is entered~ which is transformed into soil available water; for example, the silty loam soil used in this study is capable of holding 172 rnm of water in 120 em depth. The soil available water and the probable rainfall are the components of total available \\later. Next, the soil test level of N (N03-N in the first 60 ern) is supplied to the program, together with the price of wheat and the cost of N. With this information, the program calculates N usii1g equation 6. The expected yield is calculated using equation ( Tf 0 "5i:nd the rate of f erti1ization is calculated by substracting the soil test N level from N • The program . - ~ . f N f '1' . . - h econ . g~ves also alternatJ.ve rates o c · ert:t 1.zat1on w:ttli t e1.r respect:tve ex~ pected yields and economic results. With this type of fertility model the guess-work of selecting a rate of fertilization for a dry, a normal, or a wet year is avoided and since this is taken care of by the producer~s capacity and preference to take risk. REFERENCES Campbell, C~A., Zentner, R.P., and Johnson, P.J. 1988. Effect of crop rota~ tion and fertilization on the quantitative relationship between spring wheat yield and moisture use in southwestern Saskatchewan. Can. J. Soil. Sci. (in press). Selles, F.~ Leyshon, A.J., and McAndrew, D. 1985. Three years of fertilizer 338 Figure 1. Economic N rates as a function of total available water and nitrogen/wheat price ratio predicted by equation 6. 100 SWIFT CURRENT C'~ .~!... >-·;; c; u-80 ~ -~ 60 0 _a:: o_ 0 >--- cu = > 40 ·- cu .C.J 0 .a c: 0 cu ... > a. (3 20 0 :IE May, June ,July 5 10 15 20 25 :IE Growing Season Rainfall (em) 30 Figure 2. Probability distribution of rainfall at Swift Current. 339 trials in the Brown soil zone. In Conservation for the Future pp. 89-99 Proc. Soils and Crops Workshop,-univ. of Saskatchewan, Saskatoon, Feb 18-19. Staple, W.J., and Lehane, J.J. 1954. Weather conditions influencing wheat yields in tanks and plots. Can. J. Agric. Sci. 34: 552-554. Zentner, R.P., Sonntag, B.H, Bole, J.B., and Pittman, U.J. 1979. An economic assessment of dryland cropping programs in the prairie provinces: expected net incomes and resource requirements. Can. Farm Econ. 14: 8-19. 340 

Spring wheat response to nitrogen and water

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Spring wheat response to nitrogen and water

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