Trends in Animal & Veterinary Sciences Journal - Mitchell Plain Farm

J AcroCrop Sci J 2011 2(1):18-25

Journal of AcroCrop Science www.academyjournals.net

Original Article

Seeding Rate and Genotype Affect Yield and End-use Quality in Winter Wheat Qingwu XUE1*, Albert WEISS2, P. Stephen BAENZIGER2, David R. SHELTON3 1

Texas AgriLife Research at Amarillo, USA 2 University of Nebraska-Lincoln, USA 3 Wheat Marketing Center, Portland, USA

Received: 07.03.2011

Accepted: 27.03.2011

Published: 01.05.2011

Abstract Managing for high yield and good end-use quality is always a challenge for winter wheat (Triticum aestivum L.) production in the U.S. Central Great Plains because of the highly variable precipitation during growing season. The objective of this study was to investigate effect of seeding rate on biomass, yield, yield components, and end-use quality properties in three genotypes. Plants were grown at four seeding rates (16, 33, 65 and 130 kg ha-1) and two seeding dates in two growing seasons. Biomass and yield increased as seeding rate increased up to 65 kg ha-1. Higher seeding rates resulted in more spikes m-2 but less seeds spike-1. In the three genotypes, Arapahoe and NE92458 had higher yield than Karl 92 due to more seeds spike-1, particularly under dry conditions. Increasing the seeding rate increased flour yield and mixing time but reduced flour protein content. In each season, flour yield, mixing time and mixing tolerance were linearly related to protein content. As protein content increased, flour yield and mixing time decreased but mixing tolerance increased. Among the three genotypes, Karl 92 had lower flour yield but higher protein content, longer mixing time and greater mixing tolerance than Arapahoe and NE92458. The results in this study indicated that both seeding rate and genotype are important factors for determining grain yield and end-use quality properties. Protein content is a good indicator for milling and baking properties. Key words: Seeding rate, End-use quality, Genotype, Wheat *

Corresponding Author: Q.Xue, e-mail: [email protected], Phone: +1 8063545803, Fax: +1 8064535829

INTRODUCTION Wheat is a major crop in the U.S. Great Plains and grown under a wide range of environmental conditions. Management practices have played an important role to improve grain yield and maintain acceptable end-use quality under varying environmental conditions (Geleta et al., 2002; Chen et al., 2008). Many studies have documented how different management practices affect wheat grain yield such as nitrogen (N) and phosphorus fertilization, irrigation, seeding rate, seeding date, and row spacing (Blue et al., 1990; Geleta et al., 2002; Xue et al., 2006; Chen et al., 2008). Among the numerous management practices, seeding rate has long been studied since they are easily controlled by producers in most cropping systems (Kiesselbach, 1926; Paulsen, 1987; Dahlke et al., 1993; Lloveras et al., 2004; Chen et al., 2008). The optimum seeding rate varies greatly from region to region due to the variation of climatic factors, soil type, seeding date, and cultivars (Lloveras et al., 2004). In the U.S. central Great Plains, the most widely recommended seeding rate was 67 kg ha-1 (200 seed m-2)

but the basic rate can be increased by 10-50%, depending on local conditions (Paulsen, 1987). In Nebraska, the recommended seeding rate ranged from 65 to 101 kg ha-1 (190-290 seeds m-2) in eastern part of the state (Kiesselbach, 1926; Blue et al., 1990; Geleta et al., 2002) to 34-39 kg ha-1 (100-115 seeds m-2) in central areas (Stoltenberg, 1968). In the northern Great Plains, Chen et al. (2008) found that the optimum seeding rate in spring wheat was 65 kg ha-1 (215 seeds m-2), similar to the most recommend rate in the Great Plains (Paulsen, 1987). Nevertheless, adoption of the proper seeding rate for cereal crops is always important because the cost of seeds is the single largest portion of production costs. Using higher seeding rates may increase the overall input costs, but lowering the seeding rate may increase the risks for reducing yield (Spink et al., 2000). Wheat grain yield is determined by three yield components – spikes m-2, seeds spike-1 and seed weight (Donaldson et al., 2001; Guillen-Portal et al., 2006; Chen et al., 2008). There are compensatory relations among the A©ademy Journals 2011


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three yield components in response to the changes of environmental conditions and management practices (Chen et al., 2008). Higher yield at higher seeding rate is generally attributed to increased spikes m-2. However, seeds spike-1 decreases as seeding rate increases (Donaldson et al., 2001; Lloveras et al., 2004). Wheat genotypes have different abilities or plasticities to compensate for low or high seeding rate by modifying the three yield components (Lloveras et al., 2004). Ultimately, maximum grain yield results from an optimum balance of the three yield components, which are competing for fixed resources during the critical development stages (Grafius, 1972; Guillen-Portal et al., 2006). In addition to yield, grain end-use quality is another important factor affecting wheat market value. In the U.S., hard red winter wheat and spring wheat are mainly used for bread making and require acceptable milling and baking quality. Milling quality is determined by grain volume weight, seed weight, and flour yield; while baking quality is related to grain or flour protein content, and Mixograph mixing time and tolerance, water absorption, loaf volume and crumb grain and color (Finney et al., 1987). As with grain yield, wheat end-use quality properties are affected by environments, management practices and genotypes (Peterson et al., 1992; Baenziger et al., 2001; Pierre et al., 2008). When managing for end-use quality, selecting proper seeding rate and genotypes can be important for producers to maximize the market values. Although the effect of seeding rate on yield and agronomic performance in wheat has been studied for long time, few studies investigated the effect of seeding rate on grain end-use quality. Currently, data from literature are inconsistent for the seeding rate effect on end-use quality parameters. For example, Geleta et al. (2001) showed that decreasing seeding rate reduced flour yield and mixing time but increased protein content and mixing tolerance. Otteson et al. (2008) showed that seeding rate did not affect any of the end-use quality parameters in spring wheat, and the major factor affecting milling and baking quality is genotype. Chen et al. (2008) showed that seeding rate did not affect grain protein in a relatively wet year but increasing seeding rate reduced protein content in a dry year in spring wheat. Since grain protein content is a primary component in determining milling and baking quality, many studies have been focused on this parameter in wheat (Woolfolk et al., 2002; Guttieri et al., 2005; Chen et al., 2008; Otteson et al., 2008; Pierre et al., 2008). The question remains that whether protein content can be used to predict other milling and baking quality parameters such as flour yield, mixing time and mixing tolerance (Budak et al., 2003). Currently, the relationships between protein content and other milling and baking quality parameters (e.g., flour yield, mixing time and mixing tolerance) have not been well understood (Graybosch et al., 1996; Budak et al., 2003). In the U.S. Central Great Plains, managing for high yield as well as good end-use quality is always a challenge

for winter wheat production because of the highly variable precipitation and temperature during growing season (Peterson et al., 1992; Graybosch et al., 1995). We conducted a field experiment in three winter wheat genotypes under four environments (two years and two seeding dates) in the Central Great Plains. The objective was to investigate the effect of seeding rate on biomass, grain yield, and milling and baking quality properties.

MATERIALS AND METHODS A 2-year field experiment was conducted at the Havelock Farm, Department of Agronomy and Horticulture, University of Nebraska-Lincoln (40o 51’ N, 96o 36’ W, elevation 347 m), during the 1996-97 (1997) and 1997-98 (1998) growing seasons under rainfed conditions. Three semi-dwarf, hard red winter wheat genotypes (Arapahoe, Karl 92, and NE92458) were used in the experiment. Arapahoe and Karl 92 were popular cultivars and NE92458 was an advanced experimental line at the time of the experiment. Arapahoe is photoperiod sensitive, while Karl 92 and NE92458 are photoperiod insensitive. NE92458 has superior winter hardiness. The soil at the experimental site was a Butler silt loam (fine, montmorillonitic, mesic Abruptic Agriaquoll; USDA taxonomy). Two seeding dates, normal seeding (SD1) and late seeding (SD2) were 4 Oct. and 15 Oct. 1996, respectively, in the 1997 season and 1 Oct and 15 Oct. 1997, respectively, in the 1998 season. The experiment design within each seeding date was a randomized complete block design with three replications. A factorial treatment design was used at four seeding rates (16, 33, 65 and 130 kg ha-1) and three genotypes. These seeding rates represented the 0.25, 0.5, 1 and 2 times the normal seeding rate for eastern Nebraska. The field plots were 1.2 m wide and 2.4 m long with 0.30 m row spacing. There were 4 rows in each plot in an eastwest row direction. These plots were surrounded by other wheat plots extending at least 50 m in all directions. The research fields were prepared with standard production practices, such as land preparation, and fertilizer and herbicide applications. In addition, the plots were sprayed with the fungicide Tilt (1-[2-(2,4dichlorophenyl)-4-propyl-1,3-dioxland-2-yl]methyl-1H1,2,4 triozole: Novartis, Greensboro, NC) at heading in each season. After maturity, plant aboveground biomass was determined by harvesting either one 40 cm section or two 20 cm sections in the middle rows of each plot. Grain yield was measured by harvesting the middle of two rows in 1997 and all four rows in 1998. Among the three yield components, the number of spikes m-2 was determined by counting spikes in the biomass samples after maturity in both seasons. In 1997, seed weight (mg seed -1) was determined by counting and weighing 250 seeds after harvest, and seeds spike-1 was calculated using grain yield, seed weight and spikes m-2. In 1998, spikes from the biomass samples were threshed and seed weight per spike 19

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was measured. The number of seeds spike-1 was determined by counting seeds from ten randomly selected spikes. Then, seed weight (mg seed-1) was calculated based on seeds spike-1 and seed weight per spike. The grain end-use quality parameters, including flour yield, protein content, and Mixograph (National Manufacturing Co., Lincoln, NE) mixing time and tolerance, were measured following the methods detailed by Baenziger et al. (2001), Geleta et al. (2002) and Fufa et al. (2005). Briefly, a 40 g grain sample from each plot was tempered to a moisture basis of 152 g H2O kg-1 grain for 18-20 h prior to milling. The sample was then milled in a Quadrumat Jr. mill (C.W. Branbender Instruments Inc., South Hackensack, NJ). Flour was separated from bran with a standard shaker (Strand Shaker Co., Minneapolis, MN) at 225 rpm for 90 s with a U.S.A. standard testing sieve No. 70 and the flour was weighed. Flour yield was expressed as grams of flour per 100 g of grain. Flour protein content 140 g H2O kg-1 flour moisture basis, was determined by the Udy dye binding (Udy dye Method 46-14A) (AACC, 1995). Flour mixing characteristics were evaluated on a 10 g flour sample using a Mixograph according to the Approved Method 54-40 (AACC, 1995) with a constant water absorption of 610 g H2O kg-1 flour. Mixing time was determined as the time in minutes to maximum Mixograph curve height. Mixing tolerance was rated based on the comparison against a standard curve in the Nebraska Wheat Laboratory using a scale from 0 to 7. The higher number indicates a greater tolerance of dough to overmixing (Approved Methods 54-40, AACC, 1995; Geleta etal., 2001; Fufa et al., 2005). End-use quality of wheat flours with a mixing time > 3 min and a mixing tolerance over 3 are considered acceptable (Baenziger et al., 2001; Geleta et al., 2002; Fufa et al., 2005).

(P = 0.05) test. In addition, regression analysis was used to determine relationships between flour protein content and other quality parameters (flour yield, mixing time and mixing tolerance).

RESULTS AND DISCUSSION Environmental conditions There was a large variation in environmental conditions in the two growing seasons (Table 1). In the 1997 season, air temperature was lower than the 30-year average in most months. The 1998 season was warmer as compared to the 30-year average during the period from December to May except for March. In most months, except March and June, the mean air temperature in 1998 was higher than that in 1997 (Table 1). The 1998 season had more precipitation (650 mm) than the 30-year average (459 mm), while the 1997 season had much less precipitation (388 mm). The large differences in precipitation between the 1997 and the 1998 seasons occurred during the grain filling period (MayJune). The cumulative precipitation in May and June was 135 mm in 1997 and 292 mm in 1998 as compared to 245 mm for the 30-year average (Table 1). The wheat plants experienced water stress from the middle to late grain filling in 1997. In general, plants in 1998 were growing under high soil moisture conditions and no significant water stress was found during grain filling (Xue et al., 2004a). Biomass, yield, and yield components The variation of biomass, yield, and yield components was mainly from all the main effects of environment, seeding rate, and genotype, and interactions of environment by seeding rate and environment by genotype. The interaction of seeding rate and genotype was generally not significant (P>0.05) (Table 2). Among the four environments, biomass and yield ranged from 9012 to 15351 kg ha-1 and from 2833 to 3673 kg ha-1, respectively. For both years, plants at the late seeding date (SD2) had lower biomass and yield than those at the normal seeding date (SD1). In 1997, biomass and yield at SD2 were 17% and 23% lower than those at SD1.

Data analysis was performed using SAS (SAS Institute, 2008). Analysis of variance (ANOVA) was conducted using general linear model (GLM) procedures to test environment, seeding rate, and genotype main effects, and their interactions. In addition, ANOVA was also conducted in each environment for seeding rate and genotype effects, and their interaction. Means were separated using the LSD

Table 1. Monthly mean air temperature (Tair) and total monthly precipitation (Precip) during 1997 and 1998 growing seasons, and 30-year mean (1969-1998). Month 1997 1998 30-year mean Tair Precip Tair Precip Tair Precip (oC) (mm) (oC) (mm) (oC) (mm) October 11.8 17 12.5 85 12.9 44 November 0.8 88 2.3 59 3.9 23 December -4.5 6 -1.1 18 -2.6 21 January -6.1 9 -3.2 33 -5.3 12 February -1.0 23 2.6 18 -2.7 24 March 6.0 20 1.1 86 3.1 37 April 7.6 90 10.9 59 10.7 54 May 14.4 60 19.4 145 16.7 95 June 22.9 75 21.4 147 21.8 150 Mean/Total 5.7 388 7.3 650 6.5 459

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Table 2. Analysis of variance for biomass, yield, yield components, and end-use quality parameters in three wheat genotypes grown in four environments in 1997 and 1998 seasons. Source DF Biomass Yield Spikes Seeds Seed Flour Protein Mixing Mixing m-2 spike-1 weight yield content time tolerance -----(kg ha-1)----(mg) -----(g kg-1)----(min) (0-7) Environment (EV) 3 *** *** *** *** *** *** *** *** *** Seeding rate (SR) 3 *** *** *** *** *** *** *** *** * Linear 1 *** *** *** *** *** *** *** *** ** Quadratic 1 NS *** NS *** NS ** NS NS NS Genotype (G) 2 NS *** *** *** *** *** *** *** *** EV x SR 9 *** ** *** *** ** NS ** ** NS EV x G 6 NS ** NS ** NS *** * *** ** SR x G 6 NS NS NS NS * NS NS NS NS EV x SR x G 18 NS NS NS NS NS NS NS * NS *, **, *** Significant at the 0.05, 0.01, and 0.001 probability levels, respectively.

In 1998, biomass at SD2 was 41% lower but yield was 6% lower as compared to SD1. Yield did not differ in two years at SD1. Dry environment during grain filling resulted in lowest yield at SD2 in 1997 (Table 3). Consistent to previous studies, high biomass and yield require early or normal seeding date (Blue et al., 1990; Dahlke et al., 1993; Donaldson et al., 2001). In the Pacific Northwest, Donaldson et al. (2001) showed that biomass decreased linearly and reduced about 30% per month as seeding was delayed from August to October. In the three yield components, the response of spikes m-2 to environment was similar to biomass, and plants at SD1 produced more spikes than those at SD2. The more spikes in plants at SD1 were related to more early growth and earlier tillering initiation. In general, the tiller initiation started earlier in normal seeding plants than in late seeding ones (Xue et al., unpublished data), and normal seeding plants had more main stem leaves than late seeding plants (normally 2-3 leaves, Xue et al., 2004b). The differences in seeds spike-1 among the four environments were mainly related to year and plants in 1997 had fewer seeds spike-1 than those in 1998. In 1997, late seeding also resulted in fewer seeds spike-1. The variation of seed weight among the four environments was less than that of spikes m-2 and seeds spike-1. However, plants at SD2 had greater seed weight than those at SD1 (Table 3).

Table 4. Effect of seeding rate on wheat biomass, yield, and yield components in four environments. Seed rate Biomass Grain Spikes Seeds Seed kg ha-1 yield m-2 spike-1 weight ---(kg ha-1)--(mg) † SD1-1997 16 13561a‡ 3055b 638.4b 19.2a 28.12a 33 12939a 3741a 629.9b 24.6a 26.96d 65 13418a 3957a 645.8b 25.6a 27.97b 130 14563a 3939a 845.5a 17.8a 27.77c SD1-1998 16 12189b 2765b 499.8c 33.3a 31.49a 33 15461a 3488a 738.3b 30.1b 26.91b 65 17160a 3949a 809.6b 28.5b 27.73b 130 16594a 3770a 1007.9a 23.0c 24.69b SD2-1997 16 11760a 2044c 535.7b 13.8c 28.99a 33 10989a 2707b 597.8b 16.9bc 28.58b 65 10943a 3314a 482.9b 24.4a 28.84b 130 11574a 3322a 686.8a 19.6b 28.01c SD2-1998 16 7685b 2022c 363.7d 31.7a 31.63a 33 8836b 3423b 468.7c 28.6b 29.71a 65 9832a 3974a 597.6b 23.3c 32.54a 130 9695a 3727ab 676.2a 21.9c 29.45a

Table 3. Biomass, grain yield, and yield components across seeding rates and genotypes in four environments. Environ- Biomass Grain Spikes Seeds ment yield m-2 spike-1 ----- (kg ha-1)----SD11997† 13622b‡ 3673a 691.6b 21.7b SD11998 15351a 3493a 763.9a 28.7a SD21997 11317c 2833c 575.8c 18.5c SD21998 9012d 3287b 526.5c 26.4a

In 1998, biomass increased as seeding rate increased up to 65 kg ha-1. However, seeding rate did not affect biomass in 1997, even plants in the lowest seeding rate produced relatively high biomass. The greater biomass at the lower seeding rates (16 and 33 kg ha-1) could be a result of strong tillering in the spring of 1997 due to the cooler temperature from March to early May. For all four environments, yield increased as seeding rate increased up to 65 kg ha-1 and doubling this rate did not further increase yield. Although increasing seeding rate increased yield on both SD1 and SD2, yield was reduced more at lower seeding rates when the seeding date was delayed from SD1 to SD2 (Table 4). In general, higher seeding rate was required as seeding was delayed from optimum seeding date (Blue et al., 1990; Dahlke et al., 1993).

†

†

SD1 = normal seeding date; SD2 = later seeding date. Means followed by the same letter in the same column within each environment were not significantly different based on LSD test at 0.05 probability level. ‡

averaged Seed weight (mg) 27.71b 27.70b 28.60b 30.83a

SD1 = normal seeding date; SD2 = later seeding date. Means followed by the same letter in the same column were not significantly different based on LSD test at 0.05 probability level. ‡

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Seeding rate affected all the three yield components (Table 4). For the two seeding dates in 1997, spikes m-2 did not increase until to the highest seeding rate, while lower seeds spike-1 were found at either the lowest or highest seeding rate in SD2. However, spikes m-2 increased and seeds spike-1 decreased linearly as seeding rate increased for both seeding dates in 1998. Across four environments, seed weight was the highest at the lowest seeding rate (16 kg ha-1) but the lowest at the highest seeding rate (130 kg ha-1) (Table 4). Apparently, strong competition among individual plants reduced seed weight at the highest seeding rate (Geleta et al., 2001). Among the three genotypes, the difference in biomass was only found in 1998 at SD2. However, the yield differences were found in all four environments (Table 5). Yields for Arapahoe and NE92458 were similar in 1998 but Arapahoe yielded more than NE92458 at SD2 in 1997. Karl 92 had the lowest yield even under favorable conditions in 1998 and generally yielded 13-18% less than Arapahoe and NE92458. Under the relatively dry conditions observed in 1997, Arapahoe had the highest yield and Karl 92 had the lowest, and the yield difference between the two genotypes was as large as 21%. The lower yield in Karl 92 could be related to being more sensitive to environmental stress than Arapahoe. Previously, it was found that Arapahoe maintained higher photosynthesis than Karl 92 during grain filling (Xue et al., 2004a).

Table 5. Biomass, yield, and yield components among genotypes in four environments. Cultivar Biomass Grain Spikes Seeds yield m-2 spike-1 -1 ----(kg ha )---SD1-1997† Arapahoe 13436a‡ 4061a 669.6b 25.8a Karl 92 13959a 3201b 822.8a 13.2b NE92458 13499a 3757a 572.6b 26.6a

In the three yield components, the major differences among the genotypes were seeds spike-1 and seed weight. Across the four environments, the genotypic difference in spikes m-2 was only found at SD1 in 1997, and Karl 92 plants produced more spikes m-2 than Arapahoe and NE92458. Consistently across environments, Arapahoe and NE92458 had more seeds spike-1 than Karl 92. In particular, Karl 92 had much less seeds spike-1 than Arapahoe and NE92458 in 1997 when water stress occurred during grain filling. In contrast, Arapahoe performed well and had higher yield by maintaining more seeds spike-1 under dry conditions in 1997. However, Karl 92 had higher seed weight than the other two genotypes, regardless of the environment (Table 5).

three Seed weight (mg) 26.53b 30.46a 26.13b

SD1-1998 Arapahoe Karl 92 NE92458

15413a 15324a 15317a

3643a 3025b 3811a

760.7a 804.5a 726.4a

28.5b 25.3c 32.3a

26.75b 30.06a 26.31b


11504a 11009a 11438a

3207a 2506b 2760b

570.9a 602.1a 554.3a

21.3a 13.3b 20.5a

27.73b 31.15a 26.94c


9684a 8628b 8724ab

3278ab 3016b 3565a

542.1a 531.8a 505.8a

26.3b 23.6c 29.3a

29.85b 34.0a 28.65b

†


End-use quality parameters Flour yield, protein content, mixing time and mixing tolerance were all affected by the main effects of environment, seeding rate, and genotype, and their interactions. The interaction of seeding rate and genotype was not significant for all the four quality parameters (Table 2). The mean flour yield, protein content, mixing time and mixing tolerance averaged across seeding rates and genotypes in four environments are shown in Table 6. Among the environments, flour yield was the lowest at SD2 in 1998 (600 g kg-1) but the highest at SD2 in 1997 (667 g kg-1). Grains in 1997 generally had higher flour yield than in 1998. Flour protein content ranged from 117 to 139 g kg 1 across the four environments and was the lowest at SD1 in 1998. Unlike biomass and grain yield, flour yield and protein content were not consistently related to seeding date. For example, plants at SD2 had higher flour yield but lower protein content at those at SD1 in 1997. In contrast, plants at SD2 had lower flour yield and higher protein content in 1998 (Table 6). Although mixing time and mixing tolerance varied with environment, their values generally were greater than 4, which are preferred baking quality. Based on Baenziger et al. (2001), higher mixing time (>3 min, preferably >4 min), mixing tolerance (>3, preferably >4) and protein content (>12%) are preferred baking quality properties. Therefore, grains harvested in the four environments generally have preferred baking quality properties. Table 6. Flour yield, protein content, mixing time and mixing tolerance averaged across seeding rates and genotypes in four environments. Environment Flour Protein Mixing Mixing yield content time tolerance ------(g kg-1)-----(min) (0-7) † SD1-1997 652.5b‡ 138.5a 4.8a 5.2a SD1-1998 623.2c 117.1c 4.7ab 4.1b SD2-1997 667.2a 132.7b 4.6b 4.3b SD2-1998 599.7d 129.8b 4.1c 5.0a †


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Seeding rate affected flour yield in three of four environments (Figure 1A). Increasing seeding rate increased flour yield up to 65 kg ha -1, which is consistent with the results from Gelata et al. (2001). However, Otteson et al. (2008) did not find the seeding rate effect on flour yield in spring wheat. Nevertheless, the variation in flour yield as affected by seeding date and seeding rate was generally less than 5%. Consistently across environments, flour protein content decreased linearly as seeding rate increased. In particular, the difference in protein content between the lowest and highest seeding rates was as high as 20 g kg-1 in 1997 (Figure 1B). The seeding rate effect on protein content was consistent with previous studies in winter wheat (Geleta et al., 2001) and spring wheat (Chen et al., 2008). The lower protein content at higher seeding

rates could be explained by the strong competition among plants for N since no additional N fertilizers were applied to any of the seeding rate treatments in this study, which is similar to Geleta et al. (2001). Therefore, more N fertilizers may be required at higher seeding rates in order to increase grain protein content in this management practice. This was particularly true for 1998 when there was no water stress during grain filling. In contrast to protein content, mixing time increased as seeding rate increased (Figure 1C). Although the seeding rate effect on mixing tolerance was observed in two environments, flours had lower mixing tolerance at higher seeding rates (65 and 130 kg ha-1) as compared to lower seeding rates (16 and 33 kg ha -1) (Figure 1D).

700

6.0 Contrast

* ***

650

*** *** * ***

NS

***

600

5.5 5.0 4.5

4.0 550

SD1-1997

SD1-1998

SD2-1997

SD2-1998

3.5

(C)

(A)

Mixing time (min)

Flour yield (g kg-1)

Contrast

3.0

500 160

6.0

150

Contrast

5.5

NS

140

Contrast

130

***

120

*** *

110

*

5.0 4.5

NS

***

4.0

Mixing tolerance (0-7)

Protein content (g kg -1)

(B)

3.5

(D) 100

3.0 40 60 80 100 120 140 160 0 20 40 60 80 100 120 140 160 Seeding rate (kg ha -1) Seeding rate (kg ha -1) Figure 1. Seeding rate effect on flour yield (A), protein content (B), mixing time (C) and mixing tolerance (D) in four environments (vertical bars are standard error of mean). SD1: normal seeding date; SD2: late seeding date; NS: not significant, P>0.05; *, **, ***: significant at P