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  • Author or Editor: Z. Berzsenyi x
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The growth dynamics determining the yield of winter wheat depends partly on genetic determination and partly on environmental factors, including nutrient supplies. Growth and yield responses to nutrient supplies were investigated for three diverse genotypes. In the dry year of 2007 dry matter production and leaf area were influenced chiefly by N supplies, while in the more favourable year of 2008 the genotypic effect was more pronounced, and in most cases N fertiliser only led to a significant increase in yield up to a rate of 80 kg ha −1 . The maximum value of the leaf area index (LAI) was recorded at the 240 kg ha −1 N level for all three varieties in 2007 (11.5; 9.9; 8.1), while in 2008 the maximum was observed at the 160 kg ha −1 N level for Mv Toborzó and Mv Palotás (8.6 and 8.4, respectively), and only in Mv Verbunkos did LAI continue to increase up to 240 kg ha −1 N (9.8). The cumulative BMD and LAD parameters mostly exhibited much higher values in 2007 than in 2008. The maximum grain yield was achieved at 160 kg ha −1 N in 2007 and at 80 kg ha −1 N in 2008. It could be concluded from the results that the manifestation of genotypic traits was enhanced by favourable weather conditions, which also led to the better utilisation of lower rates of N fertiliser.

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The effect of sowing date, N fertilisation and genotype on the grain yield and yield stability of maize was studied between 1991 and 2006 in a long-term N fertilisation experiment set up on chernozem soil in Martonvásár, Hungary. The N treatments (0, 60, 120, 180 and 240 kg ha −1 ) represented the main plot of the three-factor, split-split-plot experiment, with the sowing date (early, optimum, late, very late) in the sub-plots and hybrids from different maturity groups in the sub-sub-plots. The highest yields were obtained for the early and optimum sowing dates (8.712 and 8.706 t ha −1 ). Compared with the optimum sowing date, a delay of ten or twenty days led to yield losses of 5% and 12.5%, respectively. In the late and very late sowings and in years with unfavourable weather conditions, yield increments were only observed up to an N rate of 60 kg ha −1 , while in the early and optimum sowings and in favourable years yield increments were significant up to 120 kg ha −1 N. Yield stability was smallest in the early and very late sowings, in the control and for high N rates, and in the early and late maturity hybrids. It can be concluded that high yields and yield stability are not mutually exclusive.

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In a long-term experiment set up in Martonvásár (N 47°21′, E 18°49′), Hungary in 1960 on a humous loam soil of the chernozem type, the effect of five crop production factors in increasing maize yields was studied in seven treatments. The factors studied were soil cultivation, fertilisation, plant density, variety and weed control. All the factors had a favourable and an unfavourable level. Yield data recorded over 42 years were evaluated using analysis of variance and stability analysis. The highest yield (8.59 t ha −1 ) was obtained when all the production factors were favourable and lowest (2.09 t ha −1 ) when these factors were unfavourable. When only one factor was unfavourable and all the other factors were favourable the following yields were obtained (t ha −1 ): soil tillage: 8.32, fertilisation: 5.21, genotype: 4.98, plant density: 6.31 weed control: 7.01. The crop production factors contributed to the increase in maize yield in the following ratios (%): fertilisation 30.6, variety 32.6, plant density 20.2, weed control 14.2, soil cultivation 2.4. The highest value of the coefficient of variation (CV%) was obtained when all the production factors were at the unfavourable level (45.7%) and when weed control or fertilisation were unfavourable (36.6% and 34.8%, respectively), while the lowest value was recorded when all the factors were favourable (19.5%). The significant treatment × year interaction could be attributed principally to treatments in which weed control, fertilisation, genotype or all the factors were unfavourable. The regression coefficient of linear regression analysis provided a satisfactory characterisation of the stability of the treatments in different environments, while the distance between the straight lines expressed the yield differences between the treatment pairs. The AMMI (Additive Main Effect and Multiplicative Interaction) model proved to be a valuable approach for understanding agronomic treatment × environment interactions and assessing the mean performance and yield stability of treatments.

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The effect of sowing date, N fertiliser rate, plant density and genotype on the yield stability of maize was analysed using 15-year data from a 5×4×5-factorial sowing date experiment, 35-year data from a two-factorial N fertilisation experiment and 25-year data from a two-factorial plant density experiment. Stability analysis on the experimental treatments was carried out using the variance and regression methods. Among the variance parameters, the ecovalence (W), the stability variance (σ²) and the yield stability (YS) were calculated. Based on the data of the sowing date experiment the optimum sowing date (Apr. 24) or sowing ten days later (May 5) were found to be the most stable due to the low, non-significant values of the variance parameters and the values close to unity for the regression coefficients (b). Although early sowing (Apr. 14) led to a significantly higher yield than late sowing, the yield stability was poorer for early sowing. In the long-term N fertilisation experiment the variance parameters indicated the least yield fluctuation at N rates of 80 and 160 kg ha-1, though the yield stability (YS) parameter for the 240 kg ha-1 N rate was also above-average. Regression analysis showed that the yield level and yield stability were the same in all environments for the 160 and 240 kg ha-1 N rates. The stability of the 80 kg ha-1 N rate was similar, but the yield level was approx. 1.3 t ha-1 lower. The yield stability of the plant density response of the maize hybrids was different in each maturity group (FAO number). The stable plant density range was broadest (50-90 thousand plants ha-1) in the FAO 200-299 group. As the vegetation period lengthened the stable plant density range narrowed and shifted towards lower plant densities (for the FAO 400-499 and FAO 500-599 maturity groups: 50-70 thousand plants ha-1). The variance and regression parameters of stability analysis both contributed to the characterisation of the stability of the genotypes and cropping systems investigated. It can be concluded from the results that high yields and yield stability are not necessarily mutually exclusive.

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In a long-term continuous maize experiment set up in 1959, the functional method of growth analysis was applied to investigate the effect of various levels of farmyard manure and mineral fertilisation on the growth of maize (Zea mays L.) and on the dynamics of the growth parameters over a 3-year period (2005–2007). The experiment involved two nutrient levels (based on the active agent equivalence principle): Level l: the NPK equivalent of 35 t ha−1 farmyard manure (FYM), applied in the form of FYM, FYM + mineral fertiliser or mineral fertiliser; Level 2: the NPK equivalent of 70 t ha−1 farmyard manure (FYM), applied in the form of FYM, FYM + mineral fertiliser or mineral fertiliser. The computerised growth analysis program elaborated by Hunt and Parsons (1974) was used to describe the effect of FYM and mineral fertiliser and to evaluate the results. This program fits functions to calculate the absolute growth rate (AGR), the relative growth rate (RGR), the net assimilation rate (NAR) and the leaf area ratio (LAR).The Hunt-Parsons program fitted a third-degree function to the dynamics of total dry matter production and second- or third-degree functions to that of the leaf area growth. The highest mean values of AGR were obtained in treatments with the higher level of mineral fertiliser alone or mineral fertiliser + FYM when the weather was favourable (2.05–2.31 g plant−1 day−1), and in treatments with the lower quantity of mineral fertiliser alone or mineral fertiliser + FYM in the case of dry weather (1.73–1.74 g plant−1 day−1). In 2005 and 2006 the absolute growth rate gave a good characterisation of the various fertiliser effects, which exhibited high values with significant differences, while in 2007 lower AGR values were obtained and no fertiliser effects were observed. In the dry year (2007) the maximum values of NAR and LAR were higher in all the treatments than in the wetter years (except at the lower rate of mineral fertiliser alone). In the case of NAR, the results obtained with the functional method of growth analysis, based on function fitting, were easier to interpret than those obtained using the classical method.It was concluded from the results that in long-term experiments the use of the functional method of growth analysis gave a more precise evaluation of the effects of fertiliser treatments and the year on the growth of maize in the vegetative growth stage and on the mean and maximum values of growth parameters.

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In a long-term maize monoculture experiment set up on the active ingredient equivalence principle, changes in the yield components were investigated over a period of three years (2005–2007) as a function of the fertiliser treatments, and the values of the growth parameters HI, LAI, NAR and CGR were calculated using the classical method of growth analysis.The results indicated that optimum N supplies and the year effect made a substantial contribution both to the grain number per ear and to the thousand-kernel weight. In the course of correlation analysis, both Pearson’s correlation coefficient and multiple regression analysis demonstrated that the grain yield was in close positive correlation with these yield components, and with the maximum value of dry matter production and the harvest index. The two yield components explained 76% of the grain yield, and the effect of thousand-kernel weight was around 3.75 times as great as that of the grain number per ear (β = 0.721 vs. 0.192). On the basis of partial correlation analysis, the maximum value of total dry matter and the thousand-kernel weight were jointly responsible for around 60% of the variance in maize grain yield. Analysis using the “Enter” method showed that the two yield components explained 62% and 59% of the grain yield in wet years (R2 2005 = 62.3%; R2 2006 = 58.8%), while in the dry year neither the thousand-kernel weight nor the grain number per ear had a significant effect on the yield (R2 2007 = 4.5%).

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The classical method of growth analysis was applied to compare the effects of farmyard manure (FYM) and mineral fertiliser on the dynamics of growth and growth parameters in maize ( Zea mays L.) over a three-year period (2005–2007) in a long-term continuous maize experiment set up using the principle of active agent equivalence in 1959. The experiment included two nutrient levels: (i) the NPK active agent equivalent of 35 t ha −1 FYM in the form of FYM, FYM + mineral fertiliser or mineral fertiliser alone; (ii) the NPK active agent equivalent of 70 t ha −1 FYM in the form of FYM, FYM + mineral fertiliser or mineral fertiliser alone. The aim was to determine the mean and maximum values of the plant growth parameters AGR, ALGR, RGR, NAR and LAR and to compare the effects of FYM and mineral fertiliser on maize growth in various years in a long-term experiment. The effect of the treatments and the year were analysed in terms of the dynamics of total dry matter production, leaf area, absolute growth rate, net assimilation rate and leaf area ratio.Both the fertiliser treatments and the year had a significant influence on the mean and maximum values of the given growth parameters during the vegetative growth stage. The rate and duration of growth (AGR and ALGR) were lowest in the unfertilised control and highest in treatments given high rates of mineral fertiliser or combined FYM and mineral fertiliser. In all the treatments the significantly lowest values of maximum NAR were observed in 2005, when the weather was average, with higher values in the drier years (2006 and 2007). The maximum values of LAR were significantly the highest in the droughty year of 2007. It could be concluded from the results that the effects of FYM and mineral fertiliser and that of the year on maize growth can be reliably evaluated with the classical method of growth analysis in long-term experiments.

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The responses of Hungarian-bred maize hybrids with different vegetation periods to sowing date, N fertiliser and plant density were studied in small-plot field experiments between 2002 and 2004. The maize grain yield was highest in the early and optimum sowing date treatments (8.563 and 8.325 t ha-1) and significantly less in the late and very late treatments (7.908 and 7.279 t ha-1). The year had a substantial effect on both the yield and the grain moisture content. In a long-term maize monoculture experiment set up in 1961, the N fertiliser responses of 6 maize hybrids with different vegetation periods were investigated. Averaged over the years 2002 and 2004 the maize grain yields in the N treatments were as follows (t ha-1): N0: 4.780, N80: 7.479, N160: 8.577, N240: 8.226. The grain yield and yield stability of maize were greatest at a N rate of 160 kg ha-1. The yield response was similar in both years, but the year had a considerable effect on the yield level. The N supplies to maize plants during the vegetation period could be well characterised using a SPAD 502 chlorophyll meter in the R3 phenological stage (18-22 days after silking). The plant density responses of maize hybrids were described by fitting a quadratic function to the data of 19-22 hybrids in the years 2002-2004. The optimum plant density averaged over the hybrids was between 67,483 and 70,161 plants ha-1. The maximum yield associated with optimum plant density was 7.978 t ha-1 in 2002, 6.60 t ha-1 in 2003 and 9.37 t ha-1 in 2004. The annual patterns of plant density responses for the maize hybrids exhibited considerable differences.

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The effect of various fertiliser treatments on the yield of maize hybrids was studied on the basis of 26 years of data obtained in a long-term bifactorial split-plot experiment set up in 1967. The seven treatments (NPK ratio 2:1:1) applied were as follows (rates per hectare): 1. Control (no fertiliser), 2. 100 kg NPK, 3. 200 kg NPK, 4. 300 kg NPK, 5. 400 kg NPK, 6. 600 kg NPK, 7. 800 kg NPK. The maize was grown with the conventional cultivation techniques in continuous cropping. The results of analyses carried out with three different methods (analysis of variance, cumulative yield analysis and regression analysis) all indicated that under the given conditions the yield of maize hybrids was highest at an NPK fertiliser rate of 200-400 kg ha -1 . The effect of fertilisation on the maize yield was significant in 21 of the 26 years. Combined analysis of variance for the years showed that the year effect (quantity of rainfall) had the greatest effect on the maize yield, but although the year effect had a fundamental effect on the yield level it did not influence the fertiliser response pattern. The fertiliser responses of the maize hybrids were described by fitting four types of functions (quadratic, square root, inverse exponential, linear-plateau) to the yield data. It was found that when selecting the best function a consideration of the regression deviations (measured yield - calculated yield) was just as important as the coefficient of determination (R 2 ). In 12 of the 26 years the fitting of the quadratic function was not significant and overestimated the fertilisation optimum. The fertiliser response curve generally has a broad maximum which is far better described by the square root function than by the quadratic. If the fertiliser response pattern includes a depressive phase, a square root function should definitely be used in place of the quadratic function. If the maximum of the response surface forms a plateau (as opposed to a maximum point) a linear-plateau function or an inverse exponential function can be recommended. In the present work the linear-plateau function gave the best results.

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The weed mass (g m −2 ) recorded in the first 15 years (1965–1979) of a long-term, bifactorial, split-plot herbicide experiment (main plots: two types of soil cultivation, subplots: 7 herbicide treatments, with two control plots) without crops indicated that the best weed control was achieved with 10 kg ha −1 rates of simazine and atrazine. These were followed by 5 kg ha −1 ametryn, 10 kg ha −1 linuron and 2+2 kg ha −1 2,4-D, all with moderate efficiency, while 5 kg ha −1 prometryn and 10 kg ha −1 monolinuron resulted in poorer weed control. Medium deep ploughing once a year in autumn reduced the weed mass by 36.5%. There was a substantial year effect, well illustrated by the annual changes in weed mass both in the herbicide treatments and in the control plots. In plots treated with simazine and atrazine there was an exponential increase in the weed mass from the 17 th year of the experiment, suggesting the multiplication of weed biotypes resistant to triazine. As a result of some herbicide treatments there was a shift in the monocot-dicot ratio.

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