J. Agronomy & Crop Science 169, 1-8 (1992) 0 1992 Paul Parey Scientific Publishers, Berlin and Hamburg ISSN 0931-2250

Contribution f rom Institute of Crop Science and Plant Breeding, University of Kid, Germany

Crop Growth Rates and Durations of Spring Barley Cultivars as Affected by Varied N Supply and Seeding Rates:b

J. LEON

Author’s address: Dr. J. LEON, Institute of Crop Science and Plant Breeding, University of Kiel, Olshausen- strafie 40, W-2300 Kiel, Germany.

With 4 figures and 2 tables

Received January 13, 1992; accepted March lli, 1992

Abstract

Beside harvest index the biomass is a component of crop yield. Biomass can be partitioned in the product of average crop growth rate (CGR) and growth duration (GD). This study was conducted to evaluate the cultivar differences of spring barley (Hordeurn vulgme L.) in CGR and GD in respect to a varied N supply and seeding rates. Ten randomly chosen two rows spring barley cultivars were tested in field studies at three levels of nitrogen fertilization (0 to 130 kg N/ha) and each three sowing rates (200 to 500 caryopses m-’) in 1986 to 1988. The field studies were conducted on a sandy loam at Hohenschulen, Northern Germany. Beginning from three and four leaf stage, respectively, to physiological maturity, plant samples were harvested on a twice-weekly basis. From fitted cubic polynomial equations the CGR and G D were calculated. Cultivars showed significant differences in GD while the observed differences in CGR were not significant. Within the tested variation of N-levels an increase of N resulted in an increase of CGR, while increasing seeding rates led to decreasing CGR. G D differences were not detected for the N-levels and seeding rates. Regarding all interactions the cultivar x year and cultivar x N x year interactions (except GD) were important. Biomass and grain yield of cultivars were correlated to G D and not to CGR.

Key words: Biomass; Hordeurn vulgare; Crop growth rate; Growth duration; Genotypic variability

Introduction Yield of cereal crops can be partitioned in at least two ways: (a) grain yield in the product of its yield components and (b) grain yield in the product of biomass and harvest index. Regard- ing the second approach it has been shown that an improvement of cereal grain yield by plant breeding has been accompanied by an increase in harvest index with little or no change in biomass (e.g. AUFHAMMER and FISCHBECK 1964, AUSTIN et al. 1980).

+ Dedicated to Professor Dr. G. Geisler.

Further improvements by increasing harvest index may be limited by an optimal harvest index for cereals (e.g. TAKEDA et al. 1987) or by a maximal harvest index. ROSIELLE and FREY (1975) showed that the harvest index had little value as a selection criterion for grain yield improvement when the harvest index was the only used information for selection. There- fore, AUSTIN et al. (1980) stated that the biomass may contribute to a further yield im- provement. Biomass can be defined as the pro- duct of average crop growth rate and growth duration and therefore the yield of cereals as the product of crop growth rate, growth dura-

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tion and harvest index (TAKEDA and FREY 1976). While an extended literature exist about cultivar and genotypic variation in vegetative growth rate and durations, studies reporting differences between cultivars or genotypes in crop growth rates (CGR) and durations (GD) have seldom been published to date and very little information is available on this topic (KARIMI and SIDDIQUE 1991).

The objective of the present study was to evaluate the cultivar differences of two rows spring barley in CGR and G D in respect to a varied N supply and seeding rates.

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Material and Methods Ten randomly chosen, two rows spring barley (Hor- deum vulgare L.) cultivars, Apex (breeder: Cebeco- Handelsraad), Arena (Schweiger), Aura (K. & J. Breun), Beate (Saaten-Ring Pfeuffer-von Riimker), Berolina (H.-U. Heege), Dorett (Schweiger), Golf (Nickerson), Harry (Weibull), Klaxon (Nickerson) and Lercbe (von Lochow-Petkus), were tested in field studies at three levels of nitrogen fertilization and each three sowing rates in 1986 to 1988. Follow- ing faba beans in the rotation, levels of N-fertiliza- tion were 0 kg N/ha (N l), 50 kg N/ha (N 2) and 100

kg N/ha (N 3) in 1986 and 1987 and following sugar beets the levels were 30,80 and 130 kg N/ha in 1988. Sowing rates were 200 (SR l), 350 (SR 2) and 500 (SR 3) caryopses per m2. The field studies were conducted on a sandy loam at Hohenschulen, the experimental station of the Institute of Crop Science and Plant Breeding near Kiel, Northern Germany. Numbers of replicates were two. Experimental de- sign was a split-plot design with N-levels as main plots and cultivar-seeding rate combinations as sub- plots. Plot sizes were 10.0 m2 (2.50 m X 4.00 m) in 1986 and 1987 and 10.8 m2 (1.80 m x 6.00 m) in 1988, respectively. Further fertilization and treat- ments were according to the local standard.

Beginning from three and four leaf stage, respec- tively, to physiological maturity, plant samples were harvested on a twice-weekly basis (usually Monday and Thursday) from predesignated sampling sites. Sample size were 0.4 m (1986, 1987) and 0.6 m (1988) of a row, respectively. From flowering to maturity the sample size was halved. At maturity plant samples of 0.6 m2 were harvested, dried and threshed. Grain yield was computed from the dry weight of the threshed caryopses. For any sample the biomass was recorded and converted into gm-'. Accumulated growing degree days (GDD) were cal- culated by summing daily degree-days. Daily de- gree-days were calculated as according to COLVILLE and FREY (1986) however using a base temperature

Fig. 1. Graphical representation of the definition of interval used to estimate growth rates and growth durations

Croo Growth Rates and Durations of SDrine Barlev Cultivars 3

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of 5 “C (LALUKKA et al. 1978, RUSSELLE et al. 1984, STRAND 1987).

As a prerequisite to analyse the growth patterns the “repeated measure analysis of variance” was ap- plied to test whether the factor steps possess parallel growth curves and whether the growth curves of the factor steps show differences in level hight (SAS 1990). With significant deviations from parallelism several mathematical models potentially are able to describe the observed growth. Since biomass de- creased after reaching a maximum polynomial or the

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Boguslawski-Schneider equation had to be used (BO- GUSLAWSKI and SCHNEIDER 1962, DARROCH and BAKER 1990). In order to compare the results with other investigations the well known cubic polyno- mial equation was applied. From the polynomial equation the growth duration (GD) and crop growth rate (CGR) was calculated. In this research the growth was considered to be complete with reaching a maximum. The interval of 10 to 90 percent of growing was used to calculate the crop growth rates and growth durations (compare Fig. 1). These analy- sis was applied to each plot.

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Fig. 2. Estimated relationships between biomass and accumulated growing degree days for three N-levels and three seeding rates 1986 to 1988. Lines represent cubic polynomial curves fit to all observed data of each N- level and seeding rate, respectively

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Results and Discussion Repeated measure analysis of variance revealed that in each year the biomass development between N-levels, between seeding rates and between cultivars were not parallel. For the interactions these non parallelism was only

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Fig. 3. Estimated relationships between biomass and accumulated growing degree days for the cultivars Apex - . - . - . -, Arena - - - -, Aura - . . - . . -, Beate '. . . . . , Berolina - - - -, Dorett - - - - - - -, Golf - . . . . - . . . . -, Harry . . . . . . ., Klaxon -, Lerche - - - - - - 1986 to 1988. Lines represent cubic polynomial curves fit to all observed data of each cultivar

found for N x cultivars in 1986 and 1987, for seeding rates x cultivars in 1988 and for N x seeding rates in 1986. Descriptive analysis of the growth patterns showed biomass decreased after having reached a maximum in all years and treatments (compare Figs. 2 and 3). In 1987, in which the interval from 900 to 1100 GDD tooked much more calender days than in 1986 and especially in 1988, the decrease was highest and in 1988 lowest. This decrease may be explained by a loss of leaves, respiration and a energy consuming translocation (WARDLAW and PORTER 1967, AUSTIN et al. 1977, CAMPBELL et al. 1983, KARIMI and SIDDIQUE 1991). Due to the observed decrease cubic polynomial equa- tions were applied to describe the growth pat- terns. While the biomass curves of the higher N-levels were always higher than the lower ones, ranking of seeding rates for biomass changed during vegetation period (Fig. 2). The lowest seeding rate firstly showed the lowest biomass and lateron the highest biomass. Ad- ditional investigations at harvest time showed that the lowest seeding rate possessed slightly higher vegetative biomass than the other seed- ing rates and that the lowest seeding rate showed the lowest number of fertil tillers/m2. Therefore, the tillers of the lowest seeding rate weighed more than tillers of higher seeding rates. It appeared that increased competion at the higher seeding rates resulted in lighter til- lers. This difference could not be compensated by more tillers.

Figure 3 gives a graphical representation of cultivar differences in biomass accumulation. Regarding GD, cultivar differences existed while for years, N-levels and seeding rates contrary to C G R no differences were observed (Table 1).

Table 1 presents the variance components for random effects and levels of significance for fixed effects for CGR, GD, biomass and grain yield. Comparing the interactions, the year x N-interaction possessed the highest variance components. However in G D the year x cul- tivar interaction was more important than the year X N-interaction. For all traits the N x cultivar, seeding rate x cultivar, year x seed- ing rate, N x seeding rate were not important. While the hight of the year x cultivar interac- tion variance components revealed an influ- ence. Regarding the three and four way in- teraction, the year x N x cultivar interaction

CroD Growth Rates and Durations of SDring Barlev Cultivars 5

Table 1 . Variance components and levels of significance of ANOVA for crop growth rates (GCR), growth duration (GD), biomass and grain DM yield of 10 spring barley cultivars tested at 3 N-levels and 3 seeding rates from 1986 to 1988 in Hohenschulen, Northern Germany

Source of variation df CGR GD Biomass Grain DM yield

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showed higher variance components except for GD. Variance components fur cultivars were lower than the respective for year x N x cultivar interaction (except for GD). Signifi- cant cultivar effects were only detected for GD and grain yield. Comparing CGR and GD, year, N and seeding rates possessed significant effects on CGR, while cultivars showed signif- icant effects in G D (Table 1). CGR and GD are components of biomass and grain yield formation. Regarding biomass and grain yield, differences existed for N-levels, seeding rates and cultivars with the exception that the cul- tivar effects were not significant for biomass.

Within the tested variation of N-levels, an increase of N resulted in an increase of CGR (Table 2). While increasing seeding rates from 200 to 500 caryopses/m* led to decreasing CGR. GD differences did not existed for the N-levels and seeding rates (Table 2). A N- effect on GD was not detected although grain filling duration was slightly prolonged by in- creasing N since this effect was compensated by an earlier flowering time of the crop stands

with higher N-supply (Data not shown). The higher N-levels and the low seeding rate, which all possessed higher CGR, led to signifi- cant higher biomass and grain yields, while a relationship between GD and biomass or grain yield could not be detected for N and seeding rates.

CGR were different between the tested years due to climatic influences. Measuring the G D in growing degree days (GDD) no differ- ences were observed between years although the lengths of the vegetation periods differed among the tested years. CGR of cultivars ranged from 0.969 (Arena) to 1.096 g GDD-h- ' (Aura) and GD of cultivars from 715 ( H a w ) to 775 GDD (Beate). Classifying CGR and GD in low, medium and high val- ues, cultivars with medium CGR and short GD (Apex, Harry, Klaxon), low CGR and medium G D (Arena), high CGR and medium G D (Aura, Berolina, Golf), high CGR and short G D (Lerche), low CGR and long GD (Beate, Dorett) existed but no cultivar with high CGR and long GD or low CGR and

6 LBON

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Fig. 4. Associations between cultivars means of crop growth rate (CGR), growth duration (GD) and yield for ten cultivars tested under 3 N-levels and 3 seeding rates from 1986 to 1988 in Hohenschulen

short GD. Due to the selection process during cultivar development possible genotypes with low CGR and short G D will probably have been discarded. Biomass and grain yield of cultivars were correlated to G D and not to CGR. The association between CGR, G D and grain yield is presented in Figure 4. The high- est yielding cultivars possessed a combination of low CGR and long G D (Beate, Dorett) and of high CGR and medium G D ( G o l f . The cultivar Golf showed that a high yielding cul- tivar needs more attributes than a combination of high CGR and medium to long G D since the cultivars Aura and Berolina with a compar- able combination of CGR and G D than Golf showed a approximately 9 % lower grain yield than Golf. This difference, however, was not significant. Classifying these ten cultivars using yield components, biomass and harvest index as traits, a cluster analysis as well as principal component analysis did not detect differences between the cultivar Golf and Beate. The additional information of CGR and G D as presented in this study revealed dis- similarities between these cultivars.

Studies presenting CGR of cultivars have rarely been published to date and vary little information is available on this topic. KARIMI and SIDDIQUE (1991) tested old and new wheat cultivars under Australian conditions. Com- pared to this study, the CGR based on GDD were lower for the wheat cultivars. This could,

be an effect on the base temperature of 0°C used by KARIMI and SIDDIQUE (1991) to estimate the GDD. KARIMI and SIDDIQUE (1991) ob- served cultivar differences in CGR at anthesis, these differences, however, were reported be- tween old and new cultivars while differences among new cultivars were not significant. Furthermore, KARIMI and SIDDIQUE (1991) found differences in time course of CGR dur- ing growth period. Relative to the old cul- tivars, the new were characterized by a greater CGR during vegetative phase and slightly low- er values after anthesis (KARIMI and SIDDIQUE 1991). Defining average CGR for an interval of 10 % to 90 % of the growth duration as done in this study these differences between cul- tivars may disappear. However, for selection purpose the average CGR offers the needed information in just one character. Since N x cultivar and seeding rates x cultivar interac- tions were not found, testing of spring barley cultivars for CGR and G D can be concentrate on a multi year analysis without N and seeding rate variation. This study revealed, that N- variation possessed a tremendeous effect on CGR while the seeding rates extended the variation of CGR only in a limited range. N x seeding rates interaction for CGR were not found. The same was true for the N and seed- ing rate effects and their interaction on GD. For modelling purpose concerning N and seeding rates, however, a detailed analysis of

CroD Growth Rates and Durations of Sorinrr Barlev Cultivars 7

Table 2. Means of crops growth rates (CGR), growth duration (GD), biomass and grain DM yield for years, N-levels, seeding rates and cultivars of spring barley grown at Hohenschulen, Northern Germany

CGR G D Biomass Grain DM yield

Year 1986 1987 1988

N-level 1 2 3

Seeding rate 1 2 3

Cultivar Apex Arena Aura Beate Berolina Dorett Golf Harry Klaxon Lerche

g GDD-’m-’ 1.113 a+ 1.130 a 0.870 b

0.795 c 1.041 b 1.277 a

1.086 a 1.034 b 0.993 c

1.034 a 0.969 a 1.096 a 1.000 a 1.062 a 0.999 a 1.072 a 1.038 a 1.049 a 1.057 a

G D D 754 a 746 a 728 a

751 a 745 a 732 a

747 a 740 a 741 a

725 ab 747 ab 739 ab 775 a 743 ab 765 ab 751 ab 715 b 734 ab 731 ab

gm-’ 637.66 a 628.18 a 625.51 a

471.97 c 629.57 b 789.81 a

646.90 a 621.66 b 622.79 b

614.94 a 605.31 a 641.31 a 673.88 a 642.99 a 634.46 a 665.96 a 578.01 a 628.16 a 619.49 a

gm-‘

376.88 a 343.02 a 373.70 a

277.75 c 363.59 b 452.27 a

374.19 a 359.77 b 359.64 b

346.92 bc 363.39 abc 361.80 abc 393.53 ab 364.06 abc 380.25 abc 398.05 a 323.98 c 360.29 abc 353.07 abc

+ Means followed by the same letter are not significantly different at P = 0.05, according to the Ryan-Einot- Gabriel-Welch multiple F-test.

changing of CGR during growth offers more information than the average CGR of a large interval.

Zusammenfassung Wachstumsraten und -dauern von Sommer- gerstensorten unter Beriicksichtigung von N-Diingung und Aussaatstarken Der Ertrag kann neben einer Aufteilung in die Ertragskomponenten auch als Produkt von Ernteindex ma1 oberirdischer Biomasse aufge- faflt werden. Die Biomasse wiederum l a k sich als Produkt von durchschnittlicher Wachs- tumsrate ma1 Wachstumsdauer darstellen. In dieser Untersuchung wurde die genetische Va- riation in der Wachstumsrate und Wachstums- dauer anhand von Sortenunterschieden bei Sommergerste unter Berucksichtigung von va- riierten N-Dungungsmengen und Aussaatstar- ken erfaflt. Zehn zufallig ausgesuchte zweizei-

lige Sommergerstensorten wurden in Freiland- versuchen unter drei N-Dungungsmengen (0 bis 130 kg N/ha) und jeweils drei Aussaatstar- ken (200 bis 500 Karyopsen mT2) von 1986 bis 1988 gepruft. Die Versuche wurden auf Ho- henschulen, einem Standort mit sandigem Lehm in Norddeutschland, durchgefuhrt. Be- ginnend von dem 3- bzw. 4-Blattstadium wur- den bis zur physiologischen Reife zweimal wo- chentlich Proben gezogen. Die Wachstumsra- ten und -dauern wurden von den Gleichungen der durchgefuhrten Polynomapproximation dritten Grades errechnet. Es bestanden signifi- kante Sortenunterschiede in den Wachstumsra- ten, wahrend fur die Wachstumsraten die be- obachteten Unterschiede nicht abgesichert werden konnten. Steigende N-Dungermengen fuhrten zu steigenden Wachstumsraten. Dem- hingegen sanken die Wachstumsraten bei stei- genden Aussaatstarken. Unterschiede in der Wachstumsdauer wurden fur die N- und Aus- saatstarkenvariation nicht festgestellt. Von den

8 LEON, Crop Growth Rates and Durations of Spring Barley Cultivars

Interaktionen waren die Sorten x Jahres- und Sorten x N x Jahres-(Ausnahrne Wachsturns- dauer)-Interaktionen bedeutend. Die Biomasse und der Karyopsenertrag der Sorten war mit der Wachstumsdauer, aber nicht mit der Wachstumsrate korreliert.

Acknowledgements The author is indebted to Mrs. B. KETELSEN for technical assistance. Financial support by the DFG (Deutsche Forschungsgemeinschaft) is gratefully acknowledged.

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