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a Field Crop Dev. Cent., Alberta Agric., Food, and Rural Dev., 5030 50th St., Lacombe, AB T4L 1W8 Canada
b Semiarid Prairie Agric. Res. Cent., Agric. and Agri-Food Canada, Box 1030, Swift Current, SK S9H 3X2 Canada
c Agron. Unit, Alberta Agric., Food, and Rural Development, 905 O.S. Longman Building, Edmonton, AB T6H 4P2 Canada
Corresponding author (patricia.juskiw{at}gov.ab.ca)
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONREFERENCES |
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Abbreviations: B&W, Banerjee and Wienhues • g x e, genotype x environment interaction • GDD, growing degree days • LAI, leaf area index • LAImax, maximum leaf area index
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONREFERENCES |
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Phenology is the development of a plant through successive growth stages. It is important for understanding biomass partitioning and stress assessment. Several growth-staging systems have been developed for cereals and Landes and Porter (1989) compared 23 of them. Commonly-used scales to describe plant growth, such as BBCH (Lancashire et al., 1991) and that of Haun (1973), are based on the external appearance of the plant. Other scales, such as that of Banerjee and Wienhues [B&W] (1965), describe apical growth.
Although scales based on external appearance and apical growth can be very precise, the relationships between them are not always clear, and depending on why stages are being measured, the selection of an appropriate scale is important (Landes and Porter, 1989). As well, the relationship of scales to environmental factors, temperature, photoperiod, and time are not always well understood. However, Rickman and Klepper (1995) developed an elegantly simple model relating the phenological development of the apex with the external development of the plant and thermal time. They illustrated the full-season synchronous initiation and development of all vegetative and reproductive parts of the plant as a function of average temperature sums. However, it may be that a nonlinear relationship that accounts for temperature and daylength effects on growth, such as the beta function described by Jame et al. (1998), may better explain the relationship of growth to GDD.
The phyllochron is the interval, either on a calendar or thermal unit basis, between the emergence of successive leaves (Rickman and Klepper, 1995). For spring barley at a given temperature, the emergence of new leaves was found by Cao and Moss (1989a) to be a linear function of time, and differences in the rate of appearance were found between temperatures and genotypes. For spring barley as well, the emergence of new leaves at a given daylength was found by Cao and Moss (1989b) to be a linear function of time, and differences were observed between daylengths and genotypes. Cao and Moss (1989c) also pointed out that although phyllochrons for spring barley varied among genotypes and combinations of temperature and daylength, they increased as either temperature or daylength increased. Kirby (1995) reported that the rate of leaf appearance was set early in the life cycle. Frank and Bauer (1995) noted that the phyllochron has been widely accepted by crop modelers for predicting plant development and by producers for determining the timing of management practices such as irrigation, fertilizer, and pesticide applications.
Studies relating the morphological stages of barley to thermal time have been made in Alaska (Dofing, 1992; Dofing and Karlsson, 1993; Sharratt, 1999), Australia (López-Castañeda and Richards, 1994), North Dakota (Bauer et al., 1993), Quebec (Ma and Smith, 1992), Spain (Garcia del Moral et al., 1991), Syria (van Oosterom and Acevedo, 1992), and under growth room conditions (Frank and Bauer, 1997). Phyllochrons for spring barley have been determined in Alaska (Dofing and Karlsson, 1993; Sharratt, 1999), Alberta (Jedel and Helm, 1994b), North Dakota (Frank and Bauer, 1995), and Syria (van Oosterom and Acevedo, 1992). Leaf development rates in barley have been studied by Cao and Moss (1989a)(1989b). Final leaf numbers in barley have been determined in Alaska (Dofing, 1992), Alberta (Jedel and Helm, 1994a), Australia (López-Castañeda and Richards, 1994), Britain (Gallagher, 1979), North Dakota (Bauer et al., 1993), Quebec (Ma and Smith, 1992), and Syria (van Oosterom and Acevedo, 1992). Variation found in the literature of values (GDD) for phenological traits are, in part, due to differences in when the measurements started (sowing vs. emergence). As well, they may reflect location differences in temperatures and daylengths (Jame et al., 1998). As Cao and Moss (1986b) found that the phyllochron decreased as daylength increased, so the smaller phyllochrons found in Alaska vs. those in Syria could be explained on the basis of daylength differences. The variation found in the literature illustrates why it is important that data be collected specifically for the development and validation of a barley crop model in the environment where it will be used unless all of the variability can be accounted for by coefficients and equations.
The objective of the research reported in this paper was to study the phenological development of several barley cultivars grown under field conditions. These data, in conjunction with biomass data that will be reported later, were used to develop and validate a crop model for barley (SPARC-Barley, developed by Y. Jame), especially for use in the Alberta portion of the Great Plains.
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MATERIALS AND METHODS |
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Plot size from 1993 to 1995 was eight 6.10-m-long rows with 0.14-m row spacing. Plots were trimmed to six 2.74-m-long rows with 0.14-m row spacing before final harvest. Plot size in 1996 at all three sites was eight 4.57-m-long rows with 0.14-m row spacing. Plots were twinned, two plots of the same treatment, so that biomass samples over the growing season were taken from one plot and LAIs, phenological stages, and the yield at final harvest were taken from the adjacent plot. Plots were trimmed to six 2.52-m-long rows with 0.14-m row spacing before final harvest.
Plots were seeded using a belt-type seeder in 1993 on 11 May at Botha, 14 May at Lacombe, and 12 May at Olds; in 1994 on 9 May at Botha, 5 May at Lacombe, and 12 May at Olds; in 1995 on 9 May at Botha, 9 May at Lacombe, and 11 May at Olds; and in 1996 on 21 May at Botha, 13 May at Lacombe, and 17 May at Olds. Seeds were treated with 2 mL kg-1 Vitavax single solution [a.i. carbathiin (5,6-dihydro-2-methyl-N-phenyl-1,4-oxathiin-3-carboxamide)]. The seeding rate was approximately 200 seeds m-2 based on kernel weights. The seeding depth was approximately 0.04 m.
Fertilizer applications were based on soil tests done in the fall of the year previous to seeding; 112 kg ha-1 of a premix blend of ammonium phosphate (NH4H2PO4) and potassium chloride (KCL) was incorporated with the seed. Weeds were controlled by hand weeding and the application of herbicides. In 1993 at Lacombe, Lorsban [a.i. chlorpyrifos (O,O-diethyl O-(3,5,6-trichloro-2-pyridinyl) phosphorothioate)] was applied at 1200 mL ha-1 to control cutworms.
The five barley cultivars used in these tests were `Brier', `Duel', Manley, Tukwa and `Seebe'. Brier, Duel, and Tukwa are six-row cultivars while Manley and Seebe are two-row cultivars. Duel and Manley are malt types while the others are classed as feeds. Tukwa and Duel mature 1 d earlier than the cultivar Harrington while Brier is similar maturing and Manley and Seebe mature 3 to 4 d later (AAFRD, 1997). Brier, Duel, and Seebe are tall cultivars at 83, 90, and 84 cm, respectively, while Manley is a standard-height cultivar at 78 cm and Tukwa is a semidwarf cultivar at 72 cm (AAFRD, 1997). Seebe has good resistance to scald [Rhyncosporium secalis (Oud.) J. Davis], which is generally the most prevalent leaf disease in Alberta, while Brier and Tukwa have intermediate resistance and Duel and Manley are susceptible (AAFRD, 1997). Tukwa and Brier have intermediate resistance to the spot form of net blotch (Pyrenophora teres f. maculata Drechs.), also a common leaf disease in Alberta, while the other three cultivars are susceptible (AAFRD, 1997).
Weather Measurements
Weather data were collected from on-site weather stations located within 2 km of the plots. Minimum, maximum, and mean temperatures were collected daily along with solar radiation and precipitation data using a LI-1000 DataLogger (LI-COR, Lincoln, NE) at all location-years except Olds in 1993 when a Campbell system [Campbell Scientific (Canada) Corp. Edmonton, AB] was used. When data were missing, missing values were replaced by data obtained from Agriculture and Agri-Food Canada for the Lacombe site (approximately 3 km from the site); Olds College for the Olds site (approximately 5 km from the site); and the Conservation and Development Branch of Alberta Agriculture, Food, and Rural Development for the Botha site (approximately 25 km from the site). Growing Degree Days were calculated as the accumulation of daily mean temperatures
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Soil Measurements
In 1993 and 1994, soils were sampled in the fall previous to planting to determine nutrient status. Before seeding and after harvest in 1994, soils were sampled using a hand corer to determine moisture content to depths of 30 or 45 cm. Soil nutrient analyses were done by Norwest Labs, Edmonton, AB.
In 1995 and 1996, deep soil core samples were collected before seeding and after harvest to depths of 0.9 to 1.5 m. Deep core samples were analyzed for moisture, N, and bulk densities. Organic matter, sand, silt, and clay content were determined on a selected subsample. Phosphorous, K, pH, and electroconductivity were determined for the 0- to 15-cm depth. Soil nutrient analyses were done by Soil and Crop Diagnostic Centre, Edmonton, AB.
Plant Measurements
Phenological stages were monitored throughout the growing season and based on 50% of the plot at each stage: emergence (the first true leaf visible, BBCH 10); Apex 1 (the first node 0.01 m or above the soil surface, BBCH 30); flag leaf emerged (the ligules of the flag leaf visible, BBCH 39); flag leaf fully elongated (fully elongated flag leaf, no BBCH stage); anthesis (the central florets of the head having shed their pollen, BBCH 61); heading (heads fully emerged from the leaf sheath of the flag leaf, BBCH 55); peduncle fully elongated (the last internode or peduncle fully elongated, no BBCH stage); milk (kernels with milky endosperms, BBCH 75); soft dough (kernels with soft, doughy endosperms, BBCH 85); physiological maturity (loss of green color from the peduncle, corresponding to approximately 30% kernel moisture content, BBCH 87). Emergence was determined as GDD from sowing while all other stages were determined as GDD from emergence.
To assess early development, dissections were made in 1994 and 1995 to determine the apical development of the main culm. Stages were assigned according to the scale of B&W (1965). Leaf numbers were counted on the main culm before dissections.
Leaf counts based on the Haun (1973) scale were made once a week from emergence to flag leaf on the main culm. Five plants were selected per plot by tagging shortly after emergence. Using fine multicolored wire, tillers were distinguished from the main culm. We marked the fifth leaf of the main culm by cutting approximately 1 cm from the end of the leaf to give a blunt end that was easily visible as the stem elongated and lower leaves senesced. These data were regressed against GDD, and the slope was taken as the phyllochron in GDD. Final leaf numbers were determined as the number of leaves on the main culm. Leaf areas were measured three to five times throughout the growing season using a LI-COR LAI-2000 Plant Canopy Analyzer (LI-COR, Lincoln, NE). Due to lodging at Olds in 1995, LAIs could not be measured using this method.
Statistical Analysis
The experimental design was a randomized complete block with five cultivars and four replicates at each location. Analyses were conducted using PROC GLM of SAS (SAS Inst., 1988). Locations and cultivars were treated as fixed effects while years and times of measurements were treated as random effects. Errors appropriate to mixed models were used to test for the significance of the effects (Steel and Torrie, 1980). Phyllochrons were determined as the slope of the linear equations of weekly leaf numbers regressed against GDD accumulated since emergence using PROC GLM of SAS (SAS Inst., 1988). For the B&W data, stage was regressed as a linear function of GDD from emergence to sampling date using PROC GLM. Leaf numbers at sampling for B&W staging were also regressed against GDD at sampling to predict the leaf number at double ridge (B&W 4) and glume initials (B&W 7). Quadratic equations were fitted to the LAI data by year, location, and cultivar to determine maximum LAI (LAImax) and time of LAImax in GDD.
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RESULTS AND DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONREFERENCES |
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During the time from double ridge to glume initials, spikelet number is being set. Environmental factors during this time will affect this yield component. Therefore, stresses such as those due to herbicide application, drought, or frost during this period may adversely affect yield due to effects on spikelet number and viability (ovary and anther development). Leaf numbers were estimated to range from 2.8 to 4.2 during the stage from double ridge to glume initials (Table 4), a time coincident with herbicide application. Jedel and Helm (1994b) had reported earlier that double ridge occurred at the two- to three-leaf stage for a different group of spring barley cultivars grown in Alberta.
Apex 1
At this stage, internode elongation has pushed the apical meristem above the soil surface. Before this stage, resources allocated to the growth of aboveground structures are going to leaf and apical development while after this stage, resources are split between leaf, apical, and stem development. Location, year x location, cultivar, and year x cultivar effects on this trait were significant (Table 1). Manley remained the earliest cultivar attaining this stage, having the lowest GDD requirement from emergence to Apex 1 while Tukwa had the greatest GDD requirements to reach Apex 1 (Table 3). The range in GDD from emergence to Apex 1 was from 410 to 601 (Table 2), which was slightly longer than the 405 GDD reported by Bauer et al. (1993) for barley grown in North Dakota.
Flag Leaf Emergence
The flag leaf is the last leaf to emerge, and once it is fully elongated, resources allocated to the growth of aboveground structures will go only to completing stem elongation and apical development. At the flag leaf emergence stage, the last leaf of the main culm was now visible. While Brier and Duel had greater GDD requirements to emerge than the other cultivars and Tukwa had a greater GDD requirement to reach Apex 1, these three cultivars were the earliest to reach flag leaf emergence (Table 3). Both Manley and Seebe were late in reaching flag leaf emergence. While the year x location effect was significant, there was no significant g x e interaction. Therefore, this trait should be easier to predict than other traits were g x e was present (Table 1).
Flag Leaf Fully Elongated
When the flag leaf is fully elongated, resources allocated to the growth of aboveground structures no longer need to be partitioned to leaf growth. The six-row cultivars had a lower GDD requirement to reach this stage than the two-row cultivars (Table 3). The range in GDD from emergence to flag leaf fully elongated was from 646 to 864 (Table 2), which was longer than the 528 GDD reported by Bauer et al. (1993) for barley grown in North Dakota. As for flag leaf emergence, no g x e effects were noted for this trait.
Anthesis
Anthesis in barley generally occurs while the spike is still in the boot—usually only one-fourth to three-fourths of the spike is emerged. At this stage, apical development has been completed. Resources allocated to aboveground structures will now go to completing stem elongation and kernel formation. Stem elongation will often cease when stresses occur during this stage, as kernel fill seems to have precedence, and spikes may not completely emerge from the boot. While the year x location x cultivar interaction effect for GDD to anthesis was significant (Table 1), Brier required markedly less GDD to reach anthesis than all of the other cultivars except Tukwa (Table 3) in all environments (data not shown). Manley and Seebe, the two-row cultivars, had the greatest GDD requirements to reach anthesis (Table 3). Duel had the greatest GDD requirement to move from flag leaf fully elongated to anthesis. Jedel and Helm (1994a) also found that days to anthesis were longer for two-rowed cultivars than for six-rowed cultivars. The range in GDD from emergence to anthesis was from 705 to 966, which was greater than the 669 GDD reported by Bauer et al. (1993) for barley grown in North Dakota.
Heads Fully Emerged
When heads do not fully emerge from the boot, stresses may be occurring that are delaying or stopping the completion of stem elongation. However, even in the drought years (Fig. 1), these cultivars tended to have complete head emergence. This trait was complexly influenced by years, locations, and cultivars (Table 1) and so may be difficult to predict. The six-row cultivars generally had a lower GDD requirement to complete head emergence than the two-row cultivars (Table 3). Seebe was late but had a significantly lower GDD to complete heading than Manley in 4 of 12 location-years (data not shown). Seebe may have been more stress-tolerant than Manley, and therefore was able to complete head emergence earlier. The range in GDD from emergence to heads fully emerged was from 756 to 1109 with an average of 916 (Table 2), which was slightly greater than the average of 834 found by Bauer et al. (1993) for spring barley grown in North Dakota.
Peduncle Fully Elongated
Full elongation of the peduncle marks the completion of stem elongation. After this stage, resources allocated to aboveground structures will be going to maintenance and kernel fill. This trait was significantly affected by the interaction of year x location x genotype (Table 1), so it may be difficult to predict. The six-row cultivars had a lower GDD requirement to reach peduncle fully elongated than the two-row cultivars (Table 3).
Kernels at Milk Stage
From anthesis to milk stage, the kernels are in their lag phase of development as the cellular and structural components of the embryo and endosperm are being laid down. At the milk stage, the kernels begin to rapidly increase in size as starch is accumulated. While the six-row cultivars had a lower GDD requirement to reach milk than the two-row cultivars (Table 3), this was a complex trait with significant g x e effects (Table 1).
Kernels at Soft Dough Stage
Soft dough is a very important stage in barley when it is going to be used for greenfeed or be ensiled. The prediction of this stage to optimize quality and biomass is important to producers. The six-row cultivars had similar GDD requirements to reach soft dough while the two-row cultivars had greater requirements (Table 3). This was a complex trait with significant g x e effects (Table 1).
Physiological Maturity
At physiological maturity, remobilization of resources to the head for kernel fill has been completed. The two-row cultivars had the greatest GDD requirements to reach physiological maturity (Table 3). Manley and Seebe are known to be late-maturing cultivars, and therefore are not representative of all two-row barley cultivars in their phenological development. Jedel and Helm (1994a) found that two-rowed cultivars had similar days to physiological maturity as six-rowed cultivars. The range in GDD from emergence to physiological maturity was 1268 to 1702 (Table 2), which was greater than the 976 to 1200 GDD reported by Sharratt (1999) for barley grown in Alaska but less than the 1642 to 1925 GDD reported by López-Castañeda and Richards (1994) for barley grown in Australia.
Leaf Growth
Phyllochrons
The phyllochron is prone to error because temperature and daylength are known to affect the leaf appearance rate. Jame et al. (1998) have proposed a beta function to better estimate the leaf appearance rate. However, all of the linear regressions of the leaf number as a function of GDD for our tests were significant (P < 0.001) with r2 values >0.90. The good fit to a linear model was due, in part, to the long days (>16 h) at all locations during leaf growth that would be near the peak of the daylength response found by Jame et al. (1998).
Brier and Duel had the lowest GDD requirement, or the shortest phyllochrons (Table 3). Therefore, although these cultivars emerged after Manley, they required fewer heat units to complete their life cycle. Manley had the longest phyllochron, which was significantly greater than that of Seebe (Table 3). So although Manley initiated leaf development earlier as indicated by GDD to emergence and Apex 1, it ended up being the latest-maturing cultivar studied due to greater GDD requirements for leaf development. However, if the phyllochrons are calculated from the data for the B&W samplings (Table 4), Manley had one of the shorter phyllochrons during this early period of growth. This variability in phyllochrons would support the use of the nonlinear technique of Jame et al. (1998) for the determination of leaf appearance rates. Long phyllochrons for two-row cultivars is not the norm; Frank and Bauer (1995) found that the two-rowed cultivar Bowman had the shortest phyllochron of the cultivars they studied.
Average phyllochron was 69.1 GDD with a range of 43 to 108 (Table 2), which was longer than the mean of 64.5 GDD found by Dofing and Karlsson (1993) for barley grown in Alaska and shorter than the mean of 77.2 GDD found by Frank and Bauer (1995) for barley grown in North Dakota. The range was greater than the range of 60 to 80 GDD found by Sharratt (1999) for barley grown in Alaska or the range of 88 to 104 GDD found by van Oosterom and Acevedo (1992) for barley grown in Syria.
The time from sowing to emergence was about two phyllochrons, which would be consistent with one phyllochron for the development of the coleoptile and one phyllochron for the first true leaf. Again, the early emergence of Manley would not be in relationship to its phyllochron based on the whole season, but it would be consistent with its phyllochron based on early season growth as indicated by the B&W samplings.
Final Leaf Number
Manley had the lowest final leaf number (Table 3), which is consistent with earlier initiation of double ridge (Table 4). Although the location x year x cultivar effect was significant (Table 1), variability for final leaf number within a location-year-cultivar was relatively small (data not shown). The final leaf number of the main culm of barley in these tests was 9.0 when averaged over years, locations, and cultivars (Table 2). While cultivar differences were observed, none were significantly different than the mean of 9.0 (Table 3). This final leaf number is similar to those reported by Gallagher (1979) for barley grown in Britain and to those reported by Ma and Smith (1992) for barley grown in Quebec. It is higher than the reports of Dofing (1992) and Dofing and Karlsson (1993) for barley grown in Alaska, Jedel and Helm (1994b) for barley grown in Alberta, López-Castañeda and Richards (1994) for barley grown in Australia, and Bauer et al. (1993) for barley grown in North Dakota. However this final leaf number is less than that reported by van Oosterom and Acevedo (1992) for barley grown in Syria. The semidwarf Tukwa had a similar leaf number to the other cultivars (Table 3), so although Tukwa was early maturing, this early maturity was not due to a reduction in leaf number or a short phyllochron; instead, it must have been due to accelerated postanthesis growth. The GDD required to reach flag leaf emergence (mean 681) was slightly more than that required to produce 9.0 leaves with an average phyllochron of 69 GDD leaf-1. These types of disparities must be accounted for in a crop model, and they support a nonlinear relationship between the leaf appearance rate and GDD as proposed by Jame et al. (1998).
Leaf Area Indices
Once the leaves and stems are fully elongated, LAI would be expected to be maximized. The estimations of LAImax on a GDD basis were later than peduncle fully elongated and usually occurred near the milk stage (Tables 3 and 6). This lateness may be due to the development of secondary tillers lagging behind the main culm. As well, the demand for carbohydrates concurrent with kernel fill causes remobilization demands that result in senescence. The prediction of LAImax is important for green-feed and silage production because there is a loss of leaf material that is important to the quality of these feeds after this time. As for other traits, LAImax usually occurred earlier in Brier, Duel, and Tukwa than in Seebe or Manley (Table 6). The predicted range in LAImax from 3.21 to 6.39 depended on location and cultivar. Under Australian conditions, LAImax for barley was found to be 5.3 by López-Castañeda and Richards (1994). For barley, LAImax occurred at about 900 GDD under Australian conditions, while under Alberta conditions, we found it occurred at about 1040 GDD. The semidwarf Tukwa had a similar LAImax to the other cultivars, as would be expected because it had similar leaf numbers. Despite its lower leaf number, Manley had a higher LAImax than Duel or Brier. The production of secondary tillers, which is higher in two-row cultivars than in six-row cultivars (Jedel and Helm, 1994a), must compensate for low main culm leaf numbers.
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CONCLUSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONREFERENCES |
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As well, the barley crop model needs to address the complexity of kernel development occurring concurrently with the completion of stem elongation and the differences among cultivars in their ability to complete stem elongation under stress conditions. Use of the phyllochrons determined in this study for a crop model could be erroneous if the relationship of leaf count to GDD was not linear, and estimation of LAImax could be inaccurate if the relationship of LAI to GDD was not quadratic (nonsignificant regressions noted in Table 6). The relationship of GDD to flag leaf emergence and full elongation were the only traits where g x e effects were not evident, so these stages should be easier to incorporate into the model than more complex traits where g x e was evident. The data collected can be used to relate stages to GDD, leaf number, and apical development.
The year x location interaction was significant for all of the traits measured, underscoring the importance of site-specific data for model development. Each environment offered a complex setting of different temperatures, radiation, precipitation, and soil conditions. As well, there were different stress conditions from location-year to location-year for which the model would have to be able to predict cultivar responses.
The purpose of measuring or calculating of 12 growth stages and the phyllochron was to develop a model for barley that can accurately predict the stages of importance for the distribution of biomass for growth and maintenance. The model must accurately predict across a wide range of environmental conditions for the cultivar being grown for producers to accept using crop models to time harvest and applications of pesticides, fertilizers, and irrigation water. These data collected for the development and validation of a crop growth model help us to understand more fully the phenological development of the barley crop in the Alberta portion of the Great Plains.
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ACKNOWLEDGMENTS |
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Received for publication March 24, 2000.
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONREFERENCES |
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