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Dependence of Grain Weight of SpringBarley Genotypes on Traits of IndividualStemsDariusz Gozdowski a , Marcin Kozak a , Manjit S. Kang b & ZdzislawWyszynski ca Department of Biometry , Warsaw Agricultural University ,Nowoursynowska 159, 02-776, Warsaw, Polandb Department of Agronomy and Environmental Management ,Louisiana State University Agricultural Center , Baton Rouge, LA,70803-2110, USAc Department of Agronomy , Warsaw Agricultural University ,Warsaw, PolandPublished online: 22 Sep 2008.

To cite this article: Dariusz Gozdowski , Marcin Kozak , Manjit S. Kang & Zdzislaw Wyszynski (2007)Dependence of Grain Weight of Spring Barley Genotypes on Traits of Individual Stems, Journal of CropImprovement, 20:1-2, 223-233, DOI: 10.1300/J411v20n01_13

To link to this article: http://dx.doi.org/10.1300/J411v20n01_13

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Dependence of Grain Weightof Spring Barley Genotypes

on Traits of Individual Stems

Dariusz GozdowskiMarcin KozakManjit S. Kang

Zdzislaw Wyszy�ski

ABSTRACT. The aim of the paper is to evaluate relationships betweensome plant traits and grain weight per spike of spring barley (Hordeumvulagre L.). Field trials were conducted in 1999, 2001, and 2002 in cen-tral Poland. Data were collected on morphological traits of individualplants of two cultivars, Rasbet and Rastik. The data were analyzed usingpath analysis. Causal relationships studied were similar for bothcultivars: grain weight per spike was determined mainly by number ofgrains per spike (path coefficient was 0.723 for Rasbet and 0.700 forRastik), whereas the effect of mean kernel weight was weaker (0.487 forRasbet and 0.510 for Rastik). The only noticeable indirect effect wasthat of spike length on grain weight per spike via number of grains perspike (0.490 for Rasbet and 0.468 for Rastik); all the indirect effects ofshoot length on grain weight per spike were negligible. We concluded

Dariusz Gozdowski and Marcin Kozak are affiliated with the Department ofBiometry, Warsaw Agricultural University, Nowoursynowska 159, 02-776 Warsaw,Poland.

Manjit S. Kang was affiliated with the Department of Agronomy and Environmen-tal Management, Louisiana State University Agricultural Center, Baton Rouge, LA70803-2110, USA.

Zdzislaw Wyszy�ski is affiliated with the Department of Agronomy, Warsaw Agri-cultural University, Warsaw, Poland.

Address correspondence to: Marcin Kozak at the above address (E-mail: nyggus@gmail.com).

Journal of Crop Improvement, Vol. 20(1/2) (#39/40) 2007Available online at http://jcrip.haworthpress.com

© 2007 by The Haworth Press, Inc. All rights reserved.doi:10.1300/J411v20n01_13 223

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that to develop new semi-dwarf and dwarf genotypes, emphasis shouldbe placed on increased number of grains, kernel weight, and spikelength. doi:10.1300/J411v20n01_13 [Article copies available for a fee fromThe Haworth Document Delivery Service: 1-800-HAWORTH. E-mail address:<docdelivery@haworthpress.com> Website: <http://www.HaworthPress.com>© 2007 by The Haworth Press, Inc. All rights reserved.]

KEYWORDS. Individual spikes, path analysis, selection, shoot length,spike length, structural equation modeling, yield components

INTRODUCTION

Formation of grain yield of barley, as well as of other cereal species,begins early in ontogenesis. Grain yield components, i.e., number ofspikes per unit area, number of grains per spike, and kernel weight de-velop sequentially during the vegetative period (Klepper et al., 1998).Cereal grain yield per unit area is completely determined by these threecomponents (Jolliffe and Courtney, 1984; Kozak, 2004); they can dif-ferentially affect yield (Akanda and Mundt, 1996; Sarawgi et al., 1997;Sinebo, 2002; García del Moral et al., 2003). In turn, formation of yieldcomponents depends on other plant traits that develop in earlierontogenetic stages. These yield-contributing traits may influence grainyield indirectly via yield components (García del Moral et al., 1991).

Many authors have investigated the effect of traits, such as shootlength, spike (or panicle) length, number of spikelets per spike, numberof tillers per plant, number of leaves, and total photosynthetic area perplant, on grain yield of various cereal species (Samonte et al., 1998;Sinebo, 2002; Sürek and Befier, 2003; Okuyama et al., 2004). Samonteet al. (1998) reported the effect of plant height on grain yield of severalrice (Oryza sativa L.) genotypes to be positive. Sinebo (2002) found inspring barley a positive effect of shoot length on grain yield. Ahmed etal. (2003) determined that the effect of spike length on grain yield of dif-ferent wheat (Triticum aestivum L.) genotypes was positive.

Information on morphological traits that affect crop yield would helpdetermine criteria for breeding of particular crop plant species. Deter-mination of traits affecting yield would help achieve better breedingprogress by focusing on these traits during selection of new genotypes(Balkema-Boomstra, 1992).

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In this paper, we investigate the process of formation of grain weightper spike of two spring barley cultivars, Rasbet (hulled grain) andRastik (hulless grain). We study grain weight (yield) per spike as a finalstage of the process of formation of shoots, spikes, and, finally, grains.

MATERIALS AND METHODS

The data originated from a field experiment conducted at the ChyliceExperimental Station of the Warsaw Agricultural University (52° 05�N, 20°32� E), in 1999, 2001, and 2002. Soils at the experiment wereclassified as Mollic Gleysols (FAO, 1998) formed of loamy sand of gla-cial origin. Soil pHKCl in the years of the experiment ranged from 5.8 to6.8.

The experiment was conducted using two cultivars, two sowingdates, and four nitrogen fertilization levels. The sowing dates were earlyand late (delayed about 3 weeks). The early sowing date was at the endof March or beginning of April, depending on weather conditions.

The two cultivars were morphologically different. Cultivar Rasbet(hulled grain) was bred and grown for brewing purposes, whereascultivar Rastik (hulless grain) was used for feed and food productionpurposes. Because of lower field germination ability of Rasbet com-pared to Rastik, Rasbet was planted at a higher density (400 grains perm2) than Rastik (350 grains per m2), to obtain optimum plant density forboth cultivars. The nitrogen doses used were 0, 30, 60, and 90 kg N perha. Doses of 30 and 60 kg N per ha were applied before sowing in theform of ammonium sulphate. The 90 kg N per ha dose was split-applied:60 kg N per ha before sowing and 30 kg N per ha during shoot elonga-tion (DC 32; Zadoks et al., 1974).

The experiment was a randomized complete-block design in a split-plot arrangement with four replications within years. Combinations ofcultivar and sowing date were the main plots (four in total), whereas ni-trogen rates were the subplots. The sub-plot area was 30 m2.

At harvest, plants were taken for measurements from a 0.22 m2 areaper plot. The following traits were measured: shoot length (from groundlevel to the beginning of spike), spike length, number of grains perspike, weight of grains per spike, and mean kernel weight. The last traitwas calculated as a quotient of grain weight per spike and number ofgrains per spike. In summary, during the three years of the experiment,15,561 shoots with spikes of cultivar Rasbet and 11,056 shoots withspikes of cultivar Rastik were harvested.

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Statistical Analysis

To investigate the relationships represented in Figure 1, we appliedthe path analysis methodology. At first, following suggestions byKozak and Kang (2006), we applied the Structural Equation Modeling(SEM) methodology (Shipley, 2002) to select the best path model(Shipley, 1997). Nevertheless, we encountered a significant problem infinding a model that: (a) would satisfy the biological knowledge of thecausal structure among variables studied (for example, we did not takeinto account models in which grain yield per spike would be a cause ofshoot length); and (b) would not be rejected by the maximum likelihoodtest. We presumed that the reason for this was large sample size, whichis thought as a possible cause of such problems because of a high levelof power that is encountered under large sample sizes (Shipley, 2002).As well, the distribution of grain yield versus its components is nevermultivariate normal, as grain yield is modeled by the multiplicativefunction of its components (Kozak, 2004). Under these circumstances,we decided to apply Wright’s path analysis (Wright, 1921; Dewey andLu, 1959) to provide a comprehensive picture of relationships studied.

Path analysis was performed for each cultivar independently. Afterpreliminary year-wise analysis of the data, we decided to pool the datafrom all three years and treatment combinations for a particular cultivar,because doing so approximately fulfilled the assumptions of path analy-sis (distribution of variables was approximately normal, so, because oflarge sample sizes for each cultivar, we accepted this distribution). Theestimated path relationships for each factor combination for a particularcultivar appeared to be similar. Therefore, for each cultivar, the analysis

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FIGURE 1. Path diagram of shoot length (X1), spike length (X2), number ofgrains per spike (X3), mean kernel weight (X4), and weight of grain per spike(Y)

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was performed across all spikes, treating them as a representative sam-ple from the population of spikes originating from various environ-ments (generated by the treatments studied and weather conditions).The path analysis was executed using R language and environment (RDevelopment Core Team, 2005).

RESULTS

Mean and coefficient of variation (CV) for shoot length were slightlygreater for Rastik than for Rasbet (Table 1). Mean spike length was alsogreater for Rastik. For both cultivars, shoot length had the smallest CVamong all traits, whereas grain weight per spike had the largest CV (Ta-ble 1). Despite the morphological differences between the two cultivars,the path coefficients, correlation coefficients, and coefficients of deter-mination of the sub-models appeared to be similar for both cultivars(Table 2; Figure 1).

Gozdowski et al. 227

TABLE 1. Mean values and standard deviations of studied traits for cultivarsRasbet and Rastik

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228 JOURNAL OF CROP IMPROVEMENT

TABLE 2. Estimates of path coefficients (p), correlation coefficient (r) and coef-ficients of determination of the sub-models (R 2) for cultivars Rasbet and Rastik(see Figure 1 for the sub-models)

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Formation of Number of Grains per Spike

Shoot length was positively correlated with spike length; the correla-tion coefficient between these traits was 0.602 for Rasbet and 0.628 forRastik. Shoot length had a positive influence on number of grains perspike, but the effect was relatively small (the path coefficient was 0.183for Rasbet and 0.213 for Rastik). Spike length was noticeably more im-portant than shoot length in the process of formation of number ofgrains per spike (the path coefficient was 0.678 for Rasbet and 0.668 forRastik). These two traits were the two major determinants of number ofgrains per spike–R2 for the model number for grains per spike versusshoot length and spike length was 64.3% for Rasbet and 67.1% forRastik.

Formation of Mean Kernel Weight

We investigated mean kernel weight as the effect of shoot length,spike length, and number of grains per spike. Spike length positively de-termined mean kernel weight in both cultivars, though the effect wasrelatively small; the path coefficient was 0.301 for cultivar Rasbet and0.257 for cultivar Rastik. Shoot length and number of grains per spikehad very weak influences on kernel weight; the corresponding path co-efficients were �0.023 (shoot length) and 0.062 (grains per spike) forcultivar Rasbet, and �0.054 (shoot length) and 0.129 (grains per spike)for cultivar Rastik. R2 for the model involving mean kernel weight ver-sus the three traits was only 11.5% for cultivar Rasbet and 11.2% forcultivar Rastik.

Formation of Grain Weight per Spike

We investigated grain weight per spike as the effect of its two compo-nents, i.e., mean number of grains per spike and mean kernel weight.This analysis enabled us to estimate a set of indirect effects of the traitsthat are at the primary level in the path diagram (Figure 1) on grainweight per spike.

Grain weight per spike of both cultivars was strongly determined byits two components (R2

y was 96.2% for Rasbet and 96.5% for Rastik).The effect of both components on grain weight per spike was positive.The larger direct effect was detected for number of grains per spike(path coefficient was 0.723 for Rasbet and 0.700 for Rastik); the effectof mean kernel weight was smaller (path coefficient was 0.487 for

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Rasbet and 0.510 for Rastik). The indirect effect of number of grains perspike on grain weight per spike via mean kernel weight was negligible(0.030 for Rasbet and 0.066 for Rastik).

Grain weight per spike was weakly determined indirectly by shootlength via number of grains per spike. This indirect effect, which is theproduct of the corresponding path, was 0.132 for Rasbet and 0.149 forRastik. The indirect effect of shoot length on grain weight per spike viamean kernel weight was negligible (�0.011 for Rasbet and �0.028 forRastik). The indirect effect of shoot length on grain weight per spike vianumber of grains per spike and then via mean kernel weight was negli-gible for both cultivars, too. Spike length had a strong indirect effect(0.490 for Rasbet and 0.468 for Rastik) on grain weight per spike vianumber of grains per spike. The indirect effect of spike length on grainweight per spike via mean kernel weight was small (path coefficientwas equal to 0.147 for Rasbet and 0.131 for Rastik). The indirect effectof spike length on grain weight per spike via number of grains per spikeand then via mean kernel weight was negligible for both cultivars(0.021 for Rasbet and 0.044 for Rastik).

DISCUSSION AND CONCLUSIONS

In previous studies, effects of yield-related traits on barley grain yieldhave been usually limited to yield components. Information on the ef-fect of other plant and canopy traits on quantity and variability of grainyield is, however, important to understand the whole process of grainyield formation and to select the traits that should be considered in de-veloping new genotypes with high yield potential (Balkema-Boomstra,1992; Grausgruber et al., 2003).

Cereal grain weight per spike is a product of number of grains perspike and mean kernel weight, and it is an important determinant ofgrain yield per unit area. Number of grains per spike is a more importantdeterminant of grain weight per spike than mean kernel weight.

Shoot length did not influence any traits studied either directly or in-directly. However, spike length had a strong positive influence on num-ber of grains per spike, and indirectly via this trait, on grain weight perspike. Longer spikes provided higher yield per spike through moregrains.

Grain weight per spike was determined positively by both its compo-nents, i.e., number of grains per spike (to a larger extent) and mean ker-

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nel weight. Mean kernel weight appeared to be determined mainly byspike length. Moreover, we did not detect any important negative ef-fects between all the traits studied and weight of grain per spike, whichis, obviously, a positive result and provides direction to barley breedersin developing new barley genotypes.

Grain weight per spike was similar for both cultivars. Apparently, thedifferences between the cultivars do not affect the relative importanceof kernel weight or grains per spike in determining grain weight perspike. Although shoot length does not influence yield, our results andpast achievements in breeding genotypes suggest that new dwarf andsemi-dwarf cultivars possess higher yield potential than do taller geno-types (Hellewell et al., 2000; Hayes et al., 2003).

Under Ethiopian conditions, Sinebo (2002) conducted a somewhatsimilar investigation, in which he studied, via path analysis, relation-ships between several yield-related traits of barley. He found a strongpositive effect of number of grains per spike on grain yield; kernelweight and plant height during vegetative growth had weaker influenceson grain yield.

Our results suggest that in developing new semi-dwarf and dwarf ge-notypes with heavy kernels, long spikes and large number of grainsshould be emphasized. Further investigations should be focused on as-certaining which plant and canopy traits determine number of spikes perunit area, and, indirectly, grain yield.

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