European Journal of Agronomy 13 (2000) 225 – 244
Effect of crop rotation and fertilisation on maize and wheat
yields and yield stability in a long-term experiment
Zolta´n Berzsenyi *, Be´la Gyo
3
rffy, DangQuoc Lap
Department of Crop Production,Agricultural Research Institute of the Hungarian Academy of Sciences,Brunswick Street 2,
2462 Marton6a´sa´r, Hungary
Received 19 February 1999; received in revised form 28 October 1999; accepted 11 February 2000
Abstract
Long-term experiments are leading indicators of sustainability and serve as an early warning system to detect problems that threaten future productivity. A non-decreasing trend in yield is necessary to call a system sustainable. The stability of yield is also an important characteristic to be considered when judging the value of a cropping system relative to others. In a long-term crop rotation experiment set up in 1961 the effects of seven crop sequences and five fertilisation treatments were studied on the yields of maize (Zea mays L.) and wheat (Triticum aesti6umL.) and on yield stability. In the two-factorial split-plot experiment the main plots consisted of crop sequences, namely maize and wheat monocultures, three dicultures, one triculture and a Norfolk crop rotation (maize – spring barley – peas – wheat). Apart from the control the fertiliser treatments represented various fertilisation systems, namely organic manuring (farmyard manure or recycled crop residues supplemented with NPK) and high levels of NPK fertilisation. The long-term experiment was analysed by conventional analysis of variance procedures and stability analysis. The yields of maize and wheat were lower in all cases in a monoculture than in a crop rotation. Reductions in maize yield in a monoculture were chiefly recorded after a dry winter, particularly if the summer was also dry. The reduction in wheat yield in a monoculture could be attributed mainly to pathogenic factors stimulated by the weather. The yield-increasing effect of crop rotation was inversely proportional to the ratio of maize or wheat in the sequence and was greatest in the Norfolk rotation, followed by the alfalfa – maize – wheat triculture, the wheat – maize, the alfalfa – maize and the alfalfa – wheat rotation. Farmyard manure and the recycling of crop residues (maize stalks, wheat straw) with NPK supplementation are efficient ways of fertilising maize and wheat. Significantly higher yields were obtained at high levels of NPK fertilisation, especially in rotations where the proportion of maize or wheat was 50% or higher. The yield-increasing effect of crop sequences compared to the wheat monoculture was not affected by fertilisation. In maize crop sequences, however, fertilisation reduced the rotation effect by almost half. Further research will be required to determine the biological explanation of this phenomenon. The regression method of stability analysis shows that the stability of various crop sequences differed significantly from those of monoculture. The difference can be attributed mainly to the significant differences between the intercepts. The results show that stability analysis is a suitable method for the interpretation of the significant environment×treatment interactions observed in variance analysis models of long-term crop rotation experiments. Both the variance and regression
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* Corresponding author. Tel.: +36-22-569500; fax: +36-22-569556.
E-mail address:[email protected] (Z. Berzsenyi).
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methods of stability analysis contributed to the characterisation of the stability of the experimental treatments in various environments. © 2000 Elsevier Science B.V. All rights reserved.
Keywords:Long-term experiment; Crop rotation; Maize; Wheat; Fertilisation; Yield response; Stability analysis
1. Introduction
In recent decades the interest shown in long-term experiments has increased worldwide, since suitable indicators of sustainable agriculture (yield trends, parameters characteristic of the quality of the ecosystem), capable of serving as an early warning system, can only be obtained in such experiments (Barnett et al., 1995).
Crop sequences represent a systems approach in crop production research, enabling the available natural resources to be preserved and more effi-ciently utilised. In crop rotation experiments a monoculture is generally compared to various crop sequences. The fact that in most cases the yields of the cultivated crops are higher in crop rotation, as compared with a monoculture under identical conditions, is explained by the rotation effect. This rotation effect has been demonstrated irrespective of whether the crop rotation contains legumes or non-leguminous plants.
The benefits of crop rotation for land and water resource protection and productivity have been identified, but many of the rotation factors, pro-cesses and mechanisms responsible for increased yield and other benefits need to be better under-stood. Increased nitrogen supply is sometimes re-sponsible, but improvements in soil water availability, soil nutrient availability, soil struc-ture, soil microbial activity and weed control, decreased insect pressure and disease incidence, and the presence of phytotoxic compounds and/or growth-promoting substances originating from crop residues have also been identified as con-tributing factors (Karlen et al., 1994). Currently, no amount of chemical fertilizer or pesticide can fully compensate for crop rotation effects.
The analysis of crop rotation data is generally more complicated (due to yearly replications, cy-cles and crop orders, and correlational errors) than that of 1-year experiments. The evaluation of several decades of data series requires a specific
order of data processing and biometric analysis (annual and combined analysis of variance, trend calculations, simulation models). A detailed dis-cussion of the special problems encountered dur-ing the biometrical analysis of crop rotation experiments was given by Yates (1954). Further valuable details are found in the papers of Patter-son (1953) and Cady (1991).
The first step in the biometrical analysis of long-term crop rotation data is annual variance analysis. The aim of this preliminary analysis is to determine whether all the experimental years can be included in a single combined analysis, or whether it is necessary either to transform the data or to divide the experimental years into more or less homogeneous groups. If the variances are homogeneous on the basis of the Bartlett test, combined analysis can be carried out using the data of the various experimental years. Emphasis continues to be put on the examination of the treatment×year interaction and the analysis can be extended to cycles and series (Cady and Ma-son, 1964).
The significant treatment×environment inter-actions observed in the variance analysis of long-term experiments are difficult to interpret using traditional analysis of variance due to the com-plexity of the factors influencing the environment, but can be interpreted simply using stability anal-ysis. The treatment×environment interactions can be partitioned into variation associated with site (fixed variation) and variation associated with yearly fluctuations within a location (random variation). Treatments with less variation at a location over years are judged to be more stable (Lin and Binns, 1988). Specific cropping systems can be considered as fixed environmental effects.
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and the variance (random element) are the two main parameters describing the response pattern of a cropping system (Piepho, 1998). Different approaches to stability analyis differ in how the random term is further partitioned.
The measurement of yield stability over time involves at least three components: (1) the rela-tionship of yield with the local environment, (2) the average yield level and (3) the variability of the yield (Mead et al., 1986). Univariate stability measures are divided into two broad categories that use either variance or regression methods. The most important variance parameters are the within-treatment mean square (s2
), the coefficient of variation (CV%), the ecovalence (W2) (Wricke, 1962) and the stability variance (s2) (Shukla, 1972). The two latter parameters measure the contribution of the treatment to the treatment× environment interaction (Callaway and Francis, 1993). There are several approaches that combine the mean and variance of a system. Recently Kang (1993) developed a yield stability (YS) statistic that combines yield and stability of per-formance into a single selection criterion. It is often found that variance is related to the mean. For this reason, the square root of the variance is usually standardised by the mean, which leads to the coefficient of variance (CV%).
A common approach to stability analysis is to regress the performance of the system onto an environmental index computed as the mean of all observations in an environment. The index may be taken as a measure of the productivity of an environment. Regression techniques used to de-velop stability parameters are based on linear slope and deviation from that slope. Systems where the regression has a relatively large slope show an above-average response to improved en-vironmental conditions, as indicated by the envi-ronmental index. The regression approach was first suggested by Yates and Cochran (1938), fol-lowed later by Finlay and Wilkinson (1963) and Eberhart and Russell (1966). Piepho (1997) dis-cussed the regression method in a mixed model context. A stable system has been defined as one that changes least in response to changes in the environment. Finlay and Wilkinson (1963) sug-gested that slopes with bB1.0 indicated better
adaptation to poor environments, while genotypes with b\1.0 are best used in superior
environ-ments. A cropping system with an estimate of b equal to unity shows an average response to ronmental conditions, as measured by the envi-ronment mean. But it is not obvious why a system with an average response should be particularly stable (Dyke et al., 1995). Several statistical and biological limitations of the regression method were reported by Crossa (1990), Guertal et al. (1994) and Piepho (1998).
Alternatively, stability may be assessed in terms of the risk of a system falling below a certain level or the risk of one system being outyielded by another (Piepho, 1998). In many situations, e.g. in subsistence farming, risk considerations are more important than the concern about variability alone.
In agricultural research the analysis of yield stability has been largely confined to multienvi-ronmental trials of crop cultivars. The idea of applying methods of stability analysis to cropping systems is not novel (Willey, 1979; Mead and Riley, 1981). Hildebrand (1984), Raun et al. (1993) and Guertal et al. (1994) employed stability analysis in long-term experiments to evaluate fer-tilisation treatments. Piepho (1998) emphasizes that methods for comparing the stability of culti-vars can also be used for comparing different agronomic treatments in general, of which culti-vars are but a special case.
The aim of the present paper was (a) to evalu-ate the effect of various crop sequences and fertil-isation treatments on maize and wheat yields in comparison with maize and wheat monocultures on the basis of almost 40 years of data, and (b) to use conventional analysis of variance as well as the variance and regression methods of stability analysis to characterise the effect of experimental treatments on yield stability.
2. Materials and methods
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was a humous loam of the chernozem type with forest residues, slightly acidic in the ploughed layer, with poor supplies of available phosphorus and good supplies of potassium. The major char-acteristics of the experimental soil in different treatments are summarized in Table 1. The parti-cle size (mm) distribution (%) in the 0 – 90 cm level was: \0.25: 6 – 7; 0.25 – 0.05: 19 – 24; 0.05 – 0.01: 32 – 34; 0.01 – 0.005: 2 – 7; 0.005 – 0.001: 16 – 20; B
0.001: 13 – 21. The carbonate content was ex-tremely high below 30 cm. The N and humus contents exhibited parallel trends and the humus content was only higher than 1% to a depth of 60 cm. The quantity of clay declined with depth, being 21% in the 0 – 30 cm layer, 16% in the 30 – 60 cm layer and 13% in the 60 – 90 cm layer. The clay mineral composition was 27 – 42% illite and 21 – 38% smectite in the 0 – 90 cm layer, below which smectite became dominant.
The total precipitation for the study period (1961 – 1998) averaged 539 mm, which ranged from 386 to 760 mm. Differences in precipitation contributed to different yield responses, as shown by the various year×treatment interactions. Rain during the reproductive period of wheat and maize has traditionally been assumed to decisively influence grain yield. In the dry years the average rainfall during the vegetation period (Apr. – Sept.) was 243 mm and the total annual rainfall 474
mm, compared to 346 and 576 mm, respectively, in the wet years. There was a significant positive correlation between the grain yield of maize and the amount of precipitation during the vegetation period.
2.1. Treatments
The crop rotation experiment is a two-factorial split-plot with four replications. The main plots are the crop sequences and the subplots are the fertiliser treatments, in a randomized design. The subplot size is 7 m×7 m=49 m2
and the main plot size is 49×5 fertiliser treatments=245 m2
. The main plots consist of seven crop sequences, namely maize and wheat monocultures, three di-cultures, one triculture and a Norfolk crop rotation:
1. Maize monoculture 2. Wheat monoculture
3. 3 years alfalfa – 5 years maize 4. 3 years alfalfa – 5 years wheat 5. 2 years wheat – 2 years maize
6. 3 years alfalfa – 3 years maize – 2 years wheat 7. Maize – spring barley – peas – wheat
Each cycle of Treatments 3, 4 and 6 takes 8 years, while that of Treatments 5 and 7 takes 4 years, so the full experimental cycle is 8 years. Four complete cycles of 8 years, or eight cycles of
Table 1
Long-term effect of crop rotation and fertilisation treatments on major properties in the 0–20 cm soil layer at Martonva´sa´ra
Treatments Humus (%) pH(KCl) AL-P2O5(ppm) AL-K2O (ppm)
Crop sequences
1. Maize monoculture 2.81 d 5.91 ab 53.3 c 272.5 b
317.5 a 76.0 ab
5.79 ab
2. Wheat monoculture 3.24 ab
264.9 b 43.3 c
5.51 b 3.39 a
3. 3 years alfalfa–5 years maize
3.31 a 6.06 ab
4. 3 years alfalfa–5 years wheat 40.7 c 267.7 b
72.7 b
5. 2 years wheat–2 years maize 2.99 cd 6.33 ab 335.3 a
6.01 ab
6. 3 years alfalfa–3 years maize–2 years wheat 3.07 bc 41.2 c 255.8 b
2.96 cd 6.56 a 92.8 a 313.0 a
7. Norfolk crop rotation
Fertilisation treatments
6.23 a
A: Unfertilised control 3.05 b 25.8 d 251.2 c
309.1 a 67.3 b
6.25 a
B: Farmyard manure+NPK 3.21 a
5.93 b
C: Recycled crop residues+NPK 3.11 ab 57.7 c 283.3 b
5.89 b
3.08 b 291.9 b
D: NPK equivalent to that extracted by the crop 57.2 c
312.0 a 91.9 a
5.82 b 3.10 ab
E: NPK for high yield level
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4 years have taken place since the start of the experiment. The proportions of maize and wheat were 25.0, 37.5, 50.0, 62.5 and 100% depending on the type of crop sequence. Because of the different number of replications within the year the effects of the various crop sequences are compared with the monocultures. The various crops represent the treatments and it follows from the structure of the experiment that the plots being compared do not always contain the same crops in the same years. However, due to the long period which has passed since the experiment was set up, it is possible to compare the treatments over an adequate number of years. The subplots in the experiment represent five different fertilisation treatments:
1. Control, without fertiliser
2. 60 t ha−1 farmyard manure every 4 years+ NPK supplementation
3. 5 t ha−1
straw or 7 t ha−1
maize stalks each year+NPK supplementation
4. NPK fertiliser equivalent to that extracted by the crop
5. NPK for a yield of 15 t ha−1 maize and 10.5 t ha−1 wheat.
2.2. Analysis of 6ariance
The response of a system is governed by a systematic component (mi) and a random
compo-nent (eij). In the usual analysis of variance
(ANOVA) setting, the random component eij is
partitioned into an environmental main effect and interaction (Piepho, 1998):
yij=mi+uj+eij
where yij is the performance of the ith system in
the jth environment; mi is the mean (expected
value), i.e. the systematic effect of theith system; ujis a random environmental main effect andeijis
a random residual comprising both system× envi-ronment interaction and error.
In the rotation experiment the analysis is based on the combined evaluation of yield data from the maize and wheat monocultures and from the vari-ous crop sequences for comparable years. Thus, depending on the type of crop sequence, the com-bined analysis could be carried out for 10, 15, 18 or 23 years for maize and 8, 9, 20 or 23 years for wheat.
The analysis of variance was carried out for each experimental year and the homogeneity of error variance for the different years was studied using the Bartlett test (Sva´b, 1981). The structure of the combined analysis of variance over years was determined on the basis of Gomez and Gomez (1984). This combined variance analysis provided an overview of the magnitude of varia-tion between the experimental years, the variavaria-tion between the treatments and especially the treat-ment×year interaction.
For evaluating the effect of crop rotation and fertilisation on maize and wheat grain yield the hierarchical analysis of variance in the MSTAT-C program was used. The hierarchical analysis of variance was computed between crop rotation within fertilisation.
2.3. Stability analysis
The stability analysis of the experimental treat-ments was conducted using the variance and re-gression methods. Among the variance methods, the ecovalence index (W2) of Wricke (1962), the stability variance index (s2
) of Shukla (1972) and the yield stability index (YS) of Kang (1993) were calculated using the STABLE model elaborated by Kang and Magari (1995). The stability vari-ance index (s2) of Shukla (1972) is very closely related to the ecovalence index (W2) of Wricke (1962) (Piepho, 1998). The regression model can be written (Piepho, 1998) as
yij=mi+biuj+dij
where bi is a regression coefficient corresponding
to theith system;ujis an effect of thejth
environ-ment and dij is a random deviation from the
regression line.
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Steps to determine differences in the slope and intercept components for linear equations from the stability analysis were derived from Mead et al. (1993). The regression test for differences be-tween level regressions was used from the MSTAT-C statistical program.
The data were processed on an IBM-compatible computer using the MSTAT-C and SPSS 9.0 for Windows programs (MSTAT-C, 1991; SPSS for Windows, 1999).
3. Results
3.1. Effect of crop rotation and fertilisation on soil properties
The long-term effect of the crop rotation and fertilisation treatments on major soil properties is summarised in Table 1. The humus content was significantly the greatest in treatments 3 and 4 (where alfalfa was grown for 3 years as a previous crop to maize and wheat, respectively) and in the wheat monoculture. It was lowest in the maize monoculture. As regards the effect of fertilisation, the humus % was greatest in plots where both farmyard manure and NPK were applied. The soil pH was greatest in the Norfolk rotation and lowest in the alfalfa – maize sequence. The pH was significantly higher in control plots and in those treated with farmyard manure than in the other fertiliser treatments. The P2O5 and K2O contents of the soil were highest in the Norfolk rotation, in the wheat monoculture and in the wheat – maize diculture, and the data also provided a good reflection of the effect of the fertiliser treatment.
3.2. Analysis of 6ariance
In the combined analysis of variance over years the effects of crop sequences containing various proportions of maize and wheat were compared to the yields in maize and wheat monocultures. The main effects (year, crop sequence, fertilisa-tion) were significant in all cases at the 0.1% level, but their relative importance on the basis of MQ values varied according to the type of crop sequence.
In the case of maize – wheat diculture versus maize monoculture and maize – alfalfa diculture versus maize monoculture the greatest effect was recorded for fertilisation, followed by the year effect and the crop sequence. In the 3 years maize – 2 years wheat – 3 years alfalfa triculture versus maize monoculture, the effect of crop se-quence increased substantially, becoming similar in magnitude to that of fertilisation. When com-paring the Norfolk rotation with the maize mono-culture the effect of crop rotation became the most important, followed by fertilisation and year.
The crop rotation×year interaction was signifi-cant at the 1% and 0.1% level in the 2 years maize – 2 years wheat and the 3 years maize – 2 years wheat – 3 years alfalfa sequences, respec-tively, compared to the maize monoculture. The fertilisation×year interaction was significant at the 0.1% level for all the crop sequences. The crop sequence×fertilisation interaction was significant at the 0.1% level for all crop sequences except the maize – wheat diculture.
When comparing the 5 years wheat – 3 years alfalfa diculture with the wheat monoculture the effect of fertilisation was the most important, followed by that of crop sequence and year. In the case of wheat – maize diculture versus wheat monoculture the effect of crop sequence was the most important; on the basis of MQ values the effect of fertilisation was only two-thirds and that of the year only half that of crop sequence. In the case of 2 years wheat – 3 years alfalfa – 3 years maize triculture versus wheat monoculture the effect of crop sequence was three times that of fertilisation and almost ten times that of the year. When comparing the Norfolk rotation with the wheat monoculture the effect of crop sequence was more than seven times that of fertilisation and more than four times that of the year.
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level in the wheat – maize diculture and at the 1% level in the Norfolk rotation.
3.3. Yield response
Without fertilisation the yield in the 2 years maize – 2 years wheat diculture was 0.61 t ha−1 higher than in the maize monoculture (Table 2). Averaged over the B – E fertiliser treatments the yield difference was 0.407 t ha−1. Differences were observed in the maize yield depending on whether it was grown in the first or second year after wheat (7.392 vs. 6.665 t ha−1
).
In the 5 years maize – 3 years alfalfa sequence the yield of maize without fertilisation was 1.201 t ha−1higher than in a maize monoculture, while it was only 0.23 t ha−1 higher when a satisfactory level of fertilisation was applied (mean of treat-ments B – E) (Table 2). A detailed analysis of the data indicates that the yield of maize after alfalfa, averaged over fertiliser treatments A – E, was 0.566 t ha−1higher than that in a maize monocul-ture during the first 2 years, but only 0.408 t ha−1 higher in the 3rd – 5th years (without fertilisation the yield increase over the same periods was 1.55 and 1.28 t ha−1
, respectively).
In the 3 years maize – 2 years wheat – 3 years alfalfa triculture (Table 3) the mean yield surplus compared with the maize monoculture was 1.434 t ha−1 without fertilisation and 0.717 t ha−1 at a satisfactory nutrient supply level (mean of treat-ments B – E). The greatest maize yield surplus was obtained in the Norfolk rotation (maize – spring barley – peas – wheat), where the maize yield aver-age exceeded that achieved in the maize monocul-ture by 1.357 t ha−1 without fertilisation and by 0.787 t ha−1 in fertilised treatments (Table 3).
In the 2 years wheat – 2 years maize diculture the yield without fertilisation was 0.376 t ha−1 higher than in the wheat monoculture (Table 4). Averaged over the B – E treatments the yield dif-ference was 0.860 t ha−1. In the 5 years wheat – 3 years alfalfa diculture the wheat yield was 0.431 t ha−1 greater without fertilisation and 0.444 t ha−1 greater at adequate fertiliser levels (average of treatments B – E) than in the monoculture. There was a difference in the effect of the crop sequence, depending on which year the wheat was
grown after alfalfa. The yield surplus of wheat after alfalfa, averaged over treatments A – E, was 1.27 t ha−1 in the first year, 0.63 t ha−1 in the second year and only 0.055 t ha−1in the 3rd – 5th years compared to the wheat monoculture (the magnitude of the yield increase was similar with-out fertilisation).
In the 2 years wheat – 3 years alfalfa – 3 years maize triculture (Table 5) the average yield sur-plus compared to the wheat monoculture was 0.856 t ha−1
without fertilisation and 1.115 t ha−1
with adequate nutrient supplies (mean of treatments B – E). Differences were observed in the wheat yield depending on whether it was grown in the 1st or 2nd year after maize. In the triculture the yield of wheat after maize was 1.354 t ha−1 greater in the 1st year and 0.78 t ha−1 greater in the 2nd year than in the monoculture. The greatest wheat yield surplus was obtained in the Norfolk rotation (maize – spring barley – peas – wheat), where the wheat yield average exceeded that of the monoculture by 1.614 t ha−1 without fertilisation and by 1.554 t ha−1in fertilised plots (Table 5).
In maize crop rotations the greater rotation effect observed without fertilisation and in rota-tions including legumes could be attributed chiefly to the N effect. The increase in the yield of wheat in crop sequences, however, was similar in magni-tude in the fertilised treatments and in the non-fertilised control.
When the effect of fertilisation treatments was compared in various crop sequences, a signifi-cantly higher yield was obtained at high rates of NPK fertilisation (treatments D – E), especially in rotations where the proportion of maize or wheat was 50% or higher. Farmyard manure and the recycling of crop residues (maize stalks, wheat straw) with NPK supplementation were efficient ways of fertilising maize and wheat.
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Table 2
Stability parameters of a maize monoculture vs. maize–wheat diculture and maize monoculture vs. maize–alfalfa diculture in various fertilisation systems, 1961–1998a
Yield response (t ha−1) CV% W2 s2 YS
Fertilisation treatments Yield response (t ha−1) CV% W2 s2 YS
Maize monoculture Maize monoculture
4.492 16.9
A 4.724 17.0 30.36 2.61** 36.93 2.40**
B 6.856 4.4 3.06 0.06N.S. + 6.737 7.9 23.49 1.38** 6.875 6.6 14.76 0.72**
+
0.85N.S.
C 6.966 6.2 6.26
6.941 4.7 6.13 0.07N.S. +
D 7.256 5.5 7.37 0.36N.S. +
7.065 6.9 22.82 1.33** +
E 7.157 7.8 27.16 2.30**
0.152 LSD5% 0.161
Maize–alfalfa diculture Maize–wheat diculture
5.334 13.3 41.40 5.693 12.7 40.45 2.68**
A 3.70**
7.261 5.6 3.47 + 6.988 6.6 18.16 0.99*
B 0.02N.S.
6.984 6.8 16.91 0.89N.S. + +
C 7.458 5.0 5.04 0.14N.S.
0.35N.S. + 7.244 4.5 11.51 0.48N.S. +
7.604
D 5.9 7.20
7.322 6.0 15.40 0.78N.S. +
1.25**
E 7.541 8.6 16.40
0.190 LSD5% 0.174
aA, control; B, farmyard manure+NPK; C, recycled crop residues+NPK; D, extracted NPK equivalent; E, NPK for high yield level. CV%, coefficient of variance; W2, ecovalence;s2, stability variance; YS, yield stability;+, selected treatments.
N.S.Non-significant atP\0.05;
* Significant atP50.05;
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Table 3
Stability parameters of a maize monoculture vs. alfalfa–maize–wheat triculture and maize monoculture vs. Norfolk crop rotation in various fertilisation systems, 1961–1998a
Yield response (t ha−1) CV% W2 s2
Fertilisation treatments Yield response (t ha−1) CV% W2 s2 YS YS
Maize monoculture Maize monoculture
4.715 15.5
A 4.442 16.9 32.10 3.30** 32.44 5.48**
6.727 8.4 21.79 2.07** 7.092 5.0 1.76 0.20N.S. +
B
7.145 9.2 10.83 1.48** 0.97**
C 6.824 8.2 12.54
7.220 6.1 2.10 0.14N.S. +
D 6.982 4.0 2.33 0.25N.S. +
7.200 8.2 9.84 1.30**
+
E 7.075 7.8 19.47 1.79**
0.192 0.237
LSD5%
Norfolk crop rotation Maize–wheat–alfalfa triculture
6.072 8.8
A 5.876 9.3 10.49 1.05* 14.97 2.50**
8.199 5.4
B 7.547 4.5 5.26 0.43N.S. + 3.25 0.33N.S. +
8.208 5.8 3.62 0.40N.S. + +
C 7.594 5.2 4.62 0.35N.S. +
7.577 4.1 1.95 0.04N.S. 7.821 3.7 1.90 0.08N.S. +
D
7.576 6.0 5.36 0.72N.S. +
1.08*
E 7.757 7.6 10.69
0.260 LSD5% 0.219
aA, control; B, farmyard manure+NPK; C, recycled crop residues+NPK; D, extracted NPK equivalent; E, NPK for high yield level. CV%, coefficient of variance; W2, ecovalence;s2, stability variance; YS, yield stability;+, selected treatments.
N.S.Non-significant atP\0.05;
* Significant atP50.05;
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Table 4
Stability parameters of a wheat monoculture vs. wheat–maize diculture and wheat monoculture vs. wheat–alfalfa diculture in various fertilisation systems, 1961–1998a
Yield response (t ha−1) CV% W2 s2
Fertilisation treatments Yield response (t ha−1) CV% W2 s2 YS YS
Wheat monoculture Wheat monoculture
2.387 23.51
A 2.266 28.26 14.25 1.09** 13.80 0.89**
3.333 12.69 5.03 0.29* 3.549 13.98 6.30 0.32* B
3.740 15.84 5.22 0.24N.S. + +
0.19N.S.
C 3.492 9.80 3.92
3.812 13.73 5.22 0.24N.S. +
D 3.519 9.93 4.46 0.24N.S. +
3.939 13.65 11.32 0.70** E 3.606 8.64 7.60 0.51**
0.104 0.103
LSD5%
Wheat–alfalfa diculture Wheat–maize diculture
2.818 28.48
A 2.642 16.88 26.23 2.04** 17.42 1.17**
4.056 13.19
B 4.070 7.72 5.78 0.24N.S. + 5.17 0.24N.S. +
4.181 13.97 4.88 0.22N.S. +
C 4.421 10.94 6.87 0.34**
+
4.472 10.98 5.85 0.25N.S. 4.264 11.94 6.34 0.33N.S. +
D
4.316 11.77 5.91 0.30N.S. +
1.06**
E 4.425 15.49 15.12
0.115 LSD5% 0.104
aA, control; B, farmyard manure+NPK; C, recycled crop residues+NPK; D, extracted NPK equivalent; E, NPK for high yield level. CV%, coefficient of variance; W2, ecovalence;s2, stability variance; YS, yield stability;+, selected treatments.
N.S.Non-significant atP\0.05;
* Significant atP50.05;
Z.Berzsenyi et al./Europ.J.Agronomy13 (2000) 225 – 244 235
Table 5
Stability parameters of a wheat monoculture vs. wheat–alfalfa–maize triculture and wheat monoculture vs. Norfolk crop rotation in various fertilisation systems, 1961–1998a
Yield response CV% W2 s2 YS Yield response s2 YS
Fertilisation CV% W2
(t ha−1)
treatments (t ha−1)
Wheat monoculture Wheat monoculture
18.15
A 2.607 1.67 0.25N.S. 2.441 22.62 6.57 1.20**
B 3.771 13.50 2.81 0.52* 3.702 11.84 1.70 0.19N.S. +
9.41 1.97 0.32N.S. + 3.728
3.891 14.84
C 2.97 0.45**
9.34 1.83 0.28N.S. + 3.934
D 4.132 7.92 1.80 0.21N.S. +
8.70 4.38 0.89** 4.075
4.209 6.65
E 2.98 0.45** +
0.141 LSD5% 0.186
Norfolk crop rotation Wheat–alfalfa–maize triculture
15.77 3.21
A 3.463 0.56* 4.055 13.39 4.31 0.79**
11.31 4.14
B 4.885 0.78** 5.360 4.50 1.15 0.13N.S. +
5.59 3.92 0.73** 5.470
5.075 6.59
C 1.13 0.13N.S. +
7.23 2.66 0.43N.S. + 5.487 8.23
D 5.210 1.42 0.19N.S. +
6.49 3.05 0.52N.S. + 5.338
5.291 7.81
E 2.02 0.32N.S. +
0.159 LSD5% 0.210
aA, control; B, farmyard manure+NPK; C, recycled crop residues+NPK; D, extracted NPK equivalent; E, NPK for high yield
level. CV%, coefficient of variance;W2, ecovalence;s2, stability variance; YS, yield stability;+, selected treatments. N.S.Non-significant atP\0.05;
* Significant atP50.05;
** Significant atP50.01;*** Significant atP50.001.
Z.Berzsenyi et al./Europ.J.Agronomy13 (2000) 225 – 244
236
in the Norfolk rotation, followed by the tricul-ture, with the poorest effect for the two dicultures. At a satisfactory nutrient supply level (treatments B – E) the yield-increasing effect of crop rotations in wheat remained at a similar level while in maize it decreased significantly.
3.4. Stability analysis
Variance indices characteristic of the yield sta-bility of maize or wheat were calculated for com-parable years for crop rotation and monoculture for each fertiliser treatment (Tables 2 – 5). The highest CV% was obtained in the non-fertilised treatment (A) for both the monocultures and the crop sequences. The CV% values tended to be higher in the maize and wheat monocultures than in the crop sequences. The lowest CV% values were generally recorded in treatments B and D. The significance level and numerical size of the stability variance index (s2) express the extent to which different treatments are responsible for the interaction. It can be seen that the effect of treat-ments B and/or C and D was not usually signifi-cant. On the basis of mean yield response and
stability, the yield stability index (YS) consistently selected fertiliser treatments B, C and D as the best treatments in maize and wheat crop rota-tions. In maize monocultures comparable with the crop rotations treatment D was selected consis-tently in all cases. In wheat monocultures the yield stability index (YS) selected fertiliser ments C and D in most cases as the best treat-ments.
The regression method of stability analysis was used to evaluate interactions between fertilisation and environment in different crop rotations and monocultures. The results of theF-test for signifi-cant differences in regressions, as well as in the slope and intercept components are shown in Table 6. The regression equations characterising the stability of various crop sequences including maize differ significantly from those of the mono-cultures in fertiliser treatments A – D. On the basis of the F-test, the difference between the regres-sions can be attributed mainly to the significant differences between the intercepts. In some fer-tiliser treatments (B, C and D in the maize – wheat diculture, B and C in the maize – alfalfa diculture and A, C and D in the triculture) significant
Z.Berzsenyi et al./Europ.J.Agronomy13 (2000) 225 – 244 237
Fig. 3. Stability analysis of maize grain yield for different fertilisation treatments according to rotations vs. monoculture (1961 – 1998). A, control; B, farmyard manure+NPK; C, recycled crop residues+NPK; D, extracted NPK equivalent; E, NPK for high yield level.n, number of years. **,*** Significant atP50.01 andP50.001, respectively.
differences in slope also contributed to the differ-ences in the regression functions. According to the results of the regression analysis, the stability of the crop rotations including wheat differed signifi-cantly in all the fertiliser treatments (A – E) from that of the monoculture and this difference was due exclusively to differences in the intercepts (Table 6).
The effect of crop rotation versus monoculture and fertilisation on maize and wheat yield stabil-ity in different environments was characterised by parallel or intersecting straight lines (Figs. 3 – 6). On the whole, the unfertilised control (treatment A) differed markedly from other fertilisation treatments under high-yield conditions; the differ-ences, however, were smaller or non-existent
un-der low-yield conditions. In crop rotations the greater slope of treatment A, compared to the monoculture, can be interpreted as the rotation effect.
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Table 6
Differences in regressions, slopes and intercepts for the regression equations of various treatments in a crop rotation experiment, 1961–1998a
Difference in regressions
Comparison Difference in intercepts Difference in slopes
D E A B C D E A B C D E
B C
A
F-values† F-values† F-values†
Maize monoculture6s.
5.15* 9.98*** 11.18*** 2.64N.S. 7.84** B1 10.64** 5.55* 3.53N.S. 2.18N.S. 19.92*** 9.10** 4.60* 1.69N.S.
MW 5.38**
22.43*** 3.70N.S.
1.51N.S. B
1 3.06N.S.
3.77N.S.
4.26* 1.57N.S.
8.42**
13.86*** B1 B1
MA 4.12* 5.10* B1
5.34*
26.36*** 11.51*** 14.84*** 21.51*** 20.48*** 23.88*** 13.86*** 22.43*** 8.59** 18.77*** B1 10.80** 11.69** 1.83N.S.
MWA
6.55** 1.25N.S. 21.16*** 36.90*** 18.31*** 13.69** 2.65N.S. B1 B1 B1 B1 B1
10.79***
NF 19.41*** 8.62**
Wheat monoculture6s.
6.66* 38.55*** 49.77*** 50.61*** 21.21*** B1
20.61*** 1.82N.S.
WM 3.27* 24.93*** 25.19*** 10.33*** B1 B1 B1
4.92* 3.13N.S.
4.83* 10.47** 5.77* 8.86** 5.75* 2.07N.S. B
1 1.89N.S. B
1 B1
5.37**
WA 3.51* 3.89*
12.75** 19.00***
WAM 5.91* 8.82** 29.12*** 16.38*** 19.62*** 40.53*** 33.56*** 34.67*** B1 B1 3.06N.S. B1 1.98N.S.
46.52*** 101.96*** 59.66*** 73.56*** 60.54*** B1 B1 1.11N.S.
29.49*** B1
34.34*** B1
30.72***
NF 22.55*** 48.61***
a
MW, 2 years maize–2 years wheat; MA, 5 years maize–3 years alfalfa; MWA, 3 years maize–2 years wheat–3 years alfalfa; NF, Norfolk crop rotation; WM, 2 years wheat–2 years maize; WA, 5 years wheat–3 years alfalfa; WAM, 2 years wheat–3 years alfalfa–3 years maize. A, control; B, farmyard manure+NPK; C, recycled crop residues+NPK; D, extracted NPK equivalent; E, NPK for high yield level.
N.S.Non-significant atP\0.05;
* Significant atP50.05; ** Significant atP50.01; *** Significant atP50.001.
†
Z.Berzsenyi et al./Europ.J.Agronomy13 (2000) 225 – 244 239
similar and they showed better adaptation to poor environments.
In the maize – wheat – alfalfa triculture the sta-bility of the fertilised treatments was similar, but the yield level of treatments E and B was higher up to an environment mean of 5.8 t ha−1(Fig. 4). In the monoculture comparable with the triculture treatments C, E and D showed good adaptation to poor environment. In the Norfolk rotation the stability and yield of farmyard manure and recy-cled crop residues (treatments B and C) was the greatest in all environments, while the stability of the NPK mineral fertiliser (treatments D and E) was lower (Fig. 4). It is interesting to note that in the Norfolk rotation the yield was smallest in
treatment E in all environments. The Norfolk cropping system, with an estimate of b close to unity (treatments B – D), shows an average re-sponse to environmental conditions, as measured by the environment mean.
In the wheat – maize diculture (Fig. 5) the stabil-ity of fertiliser treatments B – E was similar, though the yield in treatment B was slightly lower. In the comparable monoculture the stability of the fertiliser treatments differed to a lower extent; above an environment mean of 3 t ha−1
the yield level was greater in treatments E and C. In the wheat – alfalfa diculture (Fig. 5) the linear func-tions characterising the stability of fertilised treat-ments (B – E) did not differ significantly. In the
Z.Berzsenyi et al./Europ.J.Agronomy13 (2000) 225 – 244
240
Fig. 5. Stability analysis of wheat grain yield for different fertilisation treatments according to rotations vs. monoculture (1961 – 1998). A, control; B, farmyard manure+NPK; C, recycled crop residues+NPK; D, extracted NPK equivalent; E, NPK for high yield level.n, number of years. **,*** Significant atP50.01 andP50.001, respectively.
relevant monoculture treatment C was more stable in a low-yielding environment, but at environment means of above 3.0 t ha−1 the yield gradually dropped to below the level of the other treatments. In the wheat – alfalfa – maize triculture (Fig. 6) treatments E and D showed an above-average response to poor environmental conditions and their yield levels exceeded those of the other treat-ments up to an environment mean of 5 t ha−1. In the monoculture comparable with the triculture treatments E and D showed an above-average response to improved environmental conditions as indicated by the environment mean. In the Norfolk rotation treatments B, C and D indicated an
above-average response in superior environments (Fig. 6). In the relevant monoculture treatment C was most stable at low environmental means, while treatments E and D produced greater yields at an environment mean of over 3 t ha−1
.
Stability analysis suggests that recycled crop residues had an increasingly greater effect in mono-culture and in a low-yielding environment (B4 t
Z.Berzsenyi et al./Europ.J.Agronomy13 (2000) 225 – 244 241
4. Discussion
The analysis of the almost 40-year data of the long-term crop rotation experiment leads to the conclusion that the yield of maize and wheat in a monoculture was always lower than in crop rota-tion. The extent of yield loss was greater in wheat than in maize. Larger yields were obtained in crop sequences after leguminous forecrops, and also after non-leguminous crops.
The yield-increasing effect of crop rotation (i.e. rotation effect) on the maize yield was inversely proportional to the ratio of maize in the sequence. Averaged over the fertiliser treatments the
yield-increasing effect was greatest in the Norfolk rota-tion, followed by the maize – wheat – alfalfa triculture, the maize – wheat and the maize – alfalfa dicultures.
Yield stability depends on yield components and other plant characteristics, such as resistance to pests and tolerance to environmental stress factors (Kang, 1998). Reductions in maize yields in a monoculture are chiefly observed after a dry winter, particularly if the summer is also dry. In a maize monoculture the yield loss can be attributed to the larger proportion of barren plants, to the lower kernel number per plant and to the smaller thousand kernel mass. In a monoculture increased
Fig. 6. Stability analysis of maize grain yield for different fertilisation treatments according to rotations vs. monoculture (1961 – 1998). A, control; B, farmyard manure+NPK; C, recycled crop residues+NPK; D, extracted NPK equivalent; E, NPK for high yield level. n, number of years. n.s.,*,**,*** Non-significant at P\0.05, significant at P50.05, P50.01 and P50.001,
Z.Berzsenyi et al./Europ.J.Agronomy13 (2000) 225 – 244
242
weed pressure also made a substantial contribu-tion to yield losses. In the 1970s and early 1980s triazine-resistant biotypes of weeds (Amaranthus retroflexus,Chenopodium album) caused the great-est problem, while in recent years the effective control of perennial weeds (Sorghum halepense) has been increasingly important. The effect of crop rotation on the maize yield was greater without fertilisation than in fertilised treatments. Riedell et al. (1998) also stated that the level of inputs provided for maize can affect the crop rotation response. In their experiments, the maize yield following soybean was 32% greater than for continuous maize with intermediate inputs, but with high input levels there was no difference between the rotation treatments.
In the maize – alfalfa diculture the rotation ef-fect was substantial without fertilisation and could be attributed primarily to the N-fixing effect of alfalfa, thus improving the N supplies. Under the given experimental conditions, where the role of soil water reserves was extremely important in the formation of maize yields, the value of alfalfa as a forecrop was considerably lower in the case of satisfactory NPK supplies. This was especially true in dry years. The rotation effect was greatest in the Norfolk rotation, which provided especially favourable conditions for the manifestation of the effect of farmyard manure and recycled crop residues.
The yield-increasing effect of the crop rotation on the wheat yield was inversely proportional to the ratio of wheat in the sequence. The greatest yield-increasing effect was observed in the Nor-folk rotation, followed by the wheat – alfalfa – maize triculture, the wheat – maize diculture and the wheat – alfalfa diculture. Maize is a good fore-crop for wheat, and this is doubly important since wheat and maize are the two major field crops in Hungarian crop production. The reduction in wheat yield in a monoculture could be attributed mainly to pathogenic factors stimulated by the weather (Gyo¨rffy, 1984). The yield depression in a wheat monoculture is smaller in dry years, but substantial in rainy years, when root diseases (take-all of wheat, caused by Gaeumannomyces graminis6ar.tritici) are more frequent. The obser-vations are in agreement with the results of Cook
(1993). His research makes clear that the detri-mental effect of crop monoculture is the direct result of root pathogens and associated poor root health. For field crops there is no viable alterna-tive to the natural soil sanitation achieved during the time allowed by crop rotation. The yield loss in the monoculture could be attributed chiefly to reductions in the number of plants and number of grains per m2. The decline in the thousand grain mass was of smaller magnitude. In a monoculture the reduction in plant number was as great as 60% on non-fertilised control plots. In this thinned plant stand weed competition made a considerable contribution to the wheat yield loss. The yield-increasing effect of crop sequences compared to the wheat monoculture was not modified by fertilisation. By contrast, in maize crop sequences fertilisation reduced the rotation effect by almost half. The discriminant analysis procedure (Wilks’ lambda and F-statistic com-puted from a Mahalanobis D2) was used to test multivariate differences between groups (crop ro-tation vs. monoculture) and to explore which fertilisation variables were most important for discriminating among groups (data not included). In maize and wheat rotations versus monocultures there were significant differences between the group centroids. In maize rotations — with the exception of the maize – wheat diculture — the crop rotations differed from the monocultures only in the unfertilised control. This means that the rotation effect can be attributed mostly to N-supplies. In wheat rotations there were signifi-cant differences between the groups in the fer-tilised treatments as well. (The wheat – maize rotation vs. monoculture differed only in the fer-tilised treatments.) The rotation effect in the wheat rotations versus monocultures was thus manifested in all fertilisation treatments. Further research will be required to determine the biologi-cal explanation of this phenomenon.
Z.Berzsenyi et al./Europ.J.Agronomy13 (2000) 225 – 244 243
maize and wheat. It can be suggested that the joint application of manure and fertiliser may provide more favourable conditions for the mani-festation of the rotation effect. The manure treat-ment represents not only inorganic nutrient additions but also the application of organic mat-ter which can be thought of as an ecological method of sustaining soil productivity. The long-term use of crop rotation or the application of supplemental C sources such as farmyard manure or additional crop residues may increase soil ag-gregate stability, microbial and earthworm activ-ity and soil water storage, and optimize the soil physical environment for crop growth (Karlen and Doran, 1993). This could be an explanation for the rotation effect of the maize – wheat dicul-ture.
Yield stability is an important characteristic when judging the value of a cropping system relative to others (Piepho, 1998). The regression method of stability analysis shows that the stabil-ity of various crop sequences differed significantly from those of the monoculture. The difference can be attributed to the significant differences between the intercepts. Because so many environment-spe-cific response differences were observed in this analysis, stability analysis may need to be consid-ered when evaluating different cropping systems. Recommendation strategies could possibly be refined by the added use of stability analysis when assessing agronomic treatment response over time. As issues of sustainability become increas-ingly important, stability analysis may assist in the understanding of yield as a function of the environment. In general, differences in environ-ment means in this experienviron-ment can be attributed largely to moisture availability. This observation could assist in identifying potential differences between crop rotations and fertiliser treatments in either dry or rainy environments.
The combined analysis of variance over years revealed the relative importance of the year, tion and fertilisation in the different crop rota-tions. When year-by-treatment interactions are detected in the conventional analysis of variance model, stability analysis provides a simple method of determining whether or not this interaction is a function of the environment. Although this can
also be achieved by partitioning the degrees of freedom in the year-by-treatment interaction from the analysis of variance model, stability analysis may provide a more direct method of assessing temporal variability in long-term experiments (Raun et al., 1993). The results show that stability analysis is a suitable method for the interpretation of the significant environment×treatment inter-actions observed in variance analysis models of long-term crop rotation experiments. Both the variance and regression methods of stability anal-ysis contributed to the characterisation of the stability of the experimental treatments in differ-ent environmdiffer-ents.
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