| | Acknowledgments | Abstract | Introduction | Objectives | Materials and methods | Results and discussion | Conclusions
Acknowledgments
Our thanks to the Alberta Agricultural Research Institute and the Alberta Barley Commission for their financial support of this research. Also thanks to: the Field Crop Development Centre staff for their technical assistance; Dr. Brian Rossnagel, Crop Development Centre, University of Saskatchewan, for supplying seed from the Hulless Barley Cooperative Tests; Dr. Feral Temelli, Department of Agricultural, Food and Nutritional Sciences, University of Alberta, for the laboratory analysis; Dr. Richard Beames, University of British Columbia, who originally took part in the study but was unable to continue, for his help in the development of the project.
Abstract
Since it was first released in the late 1980's, hulless barley has become an economical quality alternative for feeding pigs. However, variability has been observed in the feeding quality. It has long been known that environment plays a large role in determining grain protein content; is there an equal effect upon the digestibility of the protein and energy in the pig? This study was undertaken to determine whether this variability in protein and energy digestibility in a pig, and total energy and protein content of the grain was due to the effects of the genetics (the variety) or the environment (climate, weather, and production practices).
In this study, the genetic or varietal factor was found to be the primary effect influencing end-use quality. This was mainly due to the presence of the hulled variety and, to a lesser extent, the waxy starch types that had lower feeding value. The effect of the year on quality was greater than the location effect despite the great differences in soil type, fertility, rainfall and yield between locations. The data did support the premise that those environments or years that promote yield also promote feed quality. For the producer, this means that if a good variety is chosen and good growing conditions are present which result in high yield, then the better the feed quality will be. It also indicates that as we develop new higher yielding varieties that can adapt to environmental stresses we can expect to see the feed quality of the grain increase as well.
The greatest expense and difficulty in selecting for nutritional quality is the cost and time it takes to obtain results from animal testing. It would be of benefit to the feed industry as well as the scientific community to develop a quick, easy method to determine feed value. Near Infrared Reflectance Spectroscopy (NIRS) technology is quick and easy. The fact that this study used a large number of samples from a three-year span and from several locations gave us an ideal situation to develop calibrations for NIRS. The NIRS can be used in the future to replace the pig in digestibility studies. The results were very good, giving very high correlations between the NIRS, the pig and the laboratory. These results indicate that in the near future, the grain producer and the hog producer will be able to rapidly determine the value of the grain on a quality basis. This will eliminate the need to over balance rations which promotes waste and higher costs of production. These results have given the plant breeder a new tool for screening for genetic differences in protein and energy digestibility for pigs.
Introduction
With the development of hulless barley in the late 1980's it became essential for plant breeders to determine the quality of this barley to meet the needs of potential new markets in animal feed and human food. Plant breeders discovered many years ago that environment plays a big role in the resulting quality of the grain. However, it was also assumed that differences between cultivars grown at the same location were due to the genetics of the plant. If the quality characteristic is influenced by genetic control factors then it follows that a breeder should be able to enhance that quality factor. If the main effect on the quality factor is due to environment then breeding will have very little influence.
Some of our early studies with feed quality of cereals gave mixed results when samples were used from different environments (years and locations). Breeders were concerned that if they could not obtain repeatable results, hulless barley would not be an economically viable crop. With the development of 'Condor' in 1998, consistent results were obtained for digestible energy and protein content in hogs. These results gave the first indication that environmental stability in feed quality factors are possible and that the probability to increase feed quality by genetics was significant.
This project was developed to determine the Genetic by Environmental effects on the feed quality factors of hulless barley. Once we began the project we recognized that this data base would be applicable to several different extensions including some food quality factors as reported by Temelli and Helm (1999) and the development of Near Infrared Reflectance Spectroscopy (NIRS) calibrations that could be used to screen genetic material for quality.
Objectives
The main objective of this study was to determine the effects of environment and genetics on the crude protein (CP), protein digestibility (PD), gross energy (GE), energy digestibility (ED), digestible energy content (DEC) and starch content in existing cultivars and advanced breeding lines of hulless barley grown in western Canada. These results will then be used to improve the PD and DEC of new hulless barley cultivars.
As we began to gather the results we found that there was a great deal more that could be done with the samples and data than were described in the original project plan. Temelli and Helm (1999) used the same samples to determine the non-starch polysaccharide content, and the samples were also used to develop NIRS calibrations. These data will become the corner stone of several new projects to develop commercial and research NIRS technology for a wide array of grain quality factors for food, feed and malt barley.
Due to the expanded nature of this project, that included AARI project #96M023 reported separately by Temelli and Helm (1999), this report will cover the main objective of the study in Part I. The NIRS part of the study, which arose from the original study and addresses the use of the results to enhance the breeding for quality, will be reported in Part II.
Materials and Methods
Selection and handling of barley
Samples of barley were collected from ten hulless barley test plots in Alberta, Saskatchewan, and Manitoba during the 1993, 1994 and 1995 seasons (Figure 1).
Figure 1. General soil zone map of Alberta, Saskatchewan and Manitoba showing the approximate growing locations for the study.
These tests included the check cultivars Condor, CDC Richard, Falcon and Harrington as well as up to a maximum of 10 advanced lines of the Hulless Barley Cooperative Test [Prairie Registration Recommending Committee for Grain (PRRCG, 1993, 1994, 1995)]. Wherever possible, the same genotypes were used each year; however since lines are routinely dropped from the test on a yearly basis, we were not able to ensure that all lines were tested in all three years. Also, we were not able to ensure samples were from the same locations each year due to uncontrollable factors that wiped out sites. Therefore, in 1994 there were only 9 sites tested; while in 1995 sites were increased to 11 to provide a total of three hundred samples.
Data on yield, test weight (TW), kernel weight (KW), plant height, lodging, disease, and all other data normally taken on the Hulless Cooperative Test were recorded and published in the Annual Reports of the PRRCG (PRRCG, 1993, 1994, 1995). A 1 kg composite sample of each line was sent to the Field Crop Development Centre at Lacombe where it was prepared for quality testing.
Analysis of barley
Test weight and kernel weight was analyzed by Alberta Agriculture, Field Crop Development Centre. Soluble and insoluble non-starch polysaccharides, total dietary fibre, starch and beta-glucans were determined and reported by Temelli and Helm (1999). The CP, PD, GE, ED, and DEC were determined by Dr. W. Sauer at the University of Alberta, Animal Science Department using the pig as a test animal. For interests sake, the starch data of Temelli and Helm (1999) is also reported here.
Measurements with pigs - mobile nylon bag study
In this experiment nine barrows (30 kg initial weight) were used which were surgically fitted with T-cannulas in the duodenum. The cannulas were exteriorized on the right side of the pig through the 11th or 12th intercostal space, at the level of the costo-chondral junction. The pigs were housed individually in stainless steel metabolic crates and allowed a 3-week period to recuperate and regain their normal appetites. During the experiment the pigs were fed a standard grower diet formulated to meet or exceed National Research Council (NRC, 1988, 1998) standards for all nutrients and energy. Each pig received 800 g of diet twice daily at 0800 h and 1600 h. Water was available at all times. Environmental temperature was maintained at 23°C. Nylon bags, measuring approximately 25 x 40 mm, prepared from monofilament nylon with a pore size of 48 m were used. The bags were sealed on three sides using heat and reinforced by sewing. A 1 g sample of finely ground feed (1.0 mm mesh) was placed into each nylon bag and the open end was heat-sealed. The bags were grouped into blocks of 18 and placed in a beaker containing 500 ml of a solution made up of deionized water, 0.01 N HCl and purified pepsin powder (2 g pepsin/L; 377.41 IU/g). The beaker was placed in a 37°C water bath and agitated at a rate of 90 oscillation/min. The bags were then removed from the beaker, washed with deionized water and frozen (-20°C) until required. The frozen bags were thawed in a water bath at 37°C for 5 min. The thawed bags were inserted into the duodenal cannulae of one of the pigs during a 5 min period when the pig was eating. Four bags were inserted into each pig during both the morning and evening meals. Only bags that were recovered in feces within 72 hours were used for analysis. The bags were freeze-dried and the contents analyzed for gross energy and nitrogen. A more detailed description of the mobile nylon bag technique was provided by Sauer et al. (1989). Crude protein (%N x 6.25) was determined with a Leco FP-428 Nitrogen Analyzer (Leco Corporation, St. Joseph, MI, USA). Gross energy was determined using a Parr 1241 Adiabatic Bomb Calorimeter (Parr Instruments, Moline, IL, USA).
Analysis of test results
Ten barley varieties grown at ten different locations over a period of three years resulted in 300 samples. However, in 1994 both Irricana and Lethbridge sites were wiped out so Goodale was added for 1994 and 1995 in order to maintain 300 samples. As well in 1995, HB313, HB316 and HB803 were not in the Cooperative Hulless Barley Test so HB104, HB325, and HB608 were added to the test. Therefore, the test was unbalanced for both location and variety (genotype). All chemical analysis was conducted in duplicate for each sample. Analysis of variance was performed using the General Linear Model procedure of SAS Statistical software Version 6 (SAS, 1989). The model consisted of the main effects of Genotype (G), Location (L) and Year (Y) as well as their interaction effects (G x L, G x Y and L x Y). In addition, correlation analysis was carried out to determine Pearson correlation coefficients and to evaluate the significance of correlation between various components.
Near Infrared Reflectance Spectroscopy
An additional study was added to this project to more fully utilize the results of the expensive animal and laboratory testing. These results are reported in Part II of this report. The authors found that this opportunity to determine the potential to use NIRS for determining feed quality across genetics and environment was at least as important as the original project (refer to Barley Development Council, Annual Reports 1995, 1996, 1997, 1998). We have therefore included this as part of the project but reported it in a separate section.
Results and Discussion
Composition analysis
Means, standard deviation and range for all the variables studied are presented in Table 1. The range of the chemical constituents are also depicted in Figures 2 and 3, where the values for Harrington (the hulled check) are indicated for comparison with the hulless varieties.
Table 1. Barley composition (%, w/w, dry matter basis): Means, standard deviation and range for the traits studied.
| Variable | No. of
Samples | Mean | Standard
Deviation | Minimum | Maximum |
| Yield | 278 | 4962.21 | 1571.30 | 1711.00 | 10233.00 |
| Test Weight | 268 | 71.86 | 5.65 | 55.00 | 83.00 |
| Kernel Weight | 278 | 38.13 | 4.87 | 20.30 | 48.40 |
| Crude Protein | 295 | 13.10 | 2.16 | 8.10 | 17.70 |
| Gross Energy | 294 | 4017.73 | 103.26 | 2677.30 | 4236.60 |
| Protein Digestibility | 294 | 76.93 | 6.66 | 51.60 | 89.90 |
| Energy Digestibility | 293 | 84.85 | 4.53 | 68.00 | 92.10 |
| Digestible Energy Content | 293 | 3407.47 | 215.32 | 1845.75 | 3741.80 |
| Starch | 298 | 61.68 | 3.87 | 50.36 | 72.09 |
Figure 2. Range of constituent values for hulless barley cultivars. Mean values for Harrington are indicated for comparison.
Figure 3. Range of constituent values for hulless barley cultivars. Mean values for Harrington are indicated for comparison.
Analysis of variance
Cultivar (genotype) was significant for all characteristics except GE and yield when all samples were included in the analysis (Table 2a). However, if the Harrington sample (hulled barley) was removed, GE was significant (P </= 0.01) and the PD and DEC became non-significant (Tables 2a and 2b). Temelli and Helm (1999) reported that Insoluble Fibre (IF) and Total Fibre (TF) differences were also primarily due to the difference between hulled and hulless barley with little difference between the hulless barley cultivars. This indicates that the hull has an effect upon GE, PD, DEC, IF and TF as well as Pentosans (Temelli and Helm, 1999 ). Harrington also increased the significance of ED, yield, test weight (TW), and kernel weight (KW) .
Harrington also had a big effect upon some of the interactions (Temelli and Helm, 1999). In this test it affected the Y x G interaction of all the quality traits but had no effect upon the interaction effects of Y x L or L x G.
Table 2a. Analysis of variance results for data set, including Harrington. (Ten cultivars grown at 10 locations from 1993 to 1995)
| Quality Characteristic | Genotype (G) | Location (L) | Year (Y) | G x L | G x Y | L x Y |
| Crude Protein | *** | ** | * | ns | * | *** |
| Gross Energy | ns | ns | ns | ns | ns | *** |
| Protein Digestibility | *** | ns | *** | ns | * | *** |
| Energy Digestibility | *** | ns | ** | ns | ** | *** |
| Digestible Energy Content | *** | ns | ** | ns | *** | *** |
| Starch | *** | ns | * | * | ns | *** |
| Yield | ns | * | ns | ** | *** | *** |
| Test weight | *** | ns | ns | * | * | *** |
| Kernel weight | *** | * | ns | * | *** | *** |
| ns | - not significant |
| * | - P </= 0.05 |
| ** | - P </= 0.01 |
| *** | - P </= 0.001 |
Table 2b. Analysis of variance results for data set, excluding Harrington.
| Quality Characteristic | Genotype (G) | Location (L) | Year (Y) | G x L | G x Y | L x Y |
| Crude Protein | (**) | (*) | * | ns | (ns) | *** |
| Gross Energy | (**) | (*) | ns | ns | ns | *** |
| Protein Digestibility | (ns) | ns | *** | ns | (ns) | *** |
| Energy Digestibility | (*) | ns | (*) | ns | (ns) | *** |
| Digestible Energy Content | (ns) | ns | ** | ns | (*) | *** |
| Starch | *** | (*) | (ns) | * | ns | *** |
| Yield | -- | -- | -- | -- | -- | -- |
| Test weight | -- | -- | -- | -- | -- | -- |
| Kernel weight | -- | -- | -- | -- | -- | -- |
| ns | - not significant |
| * | - P </= 0.05 |
| ** | - P </= 0.01 |
| *** | - P </= 0.001 |
( ) - indicates a change in the level of significance (compared to those in Table 2a) due to exclusion of Harrington
These results were expected as they confirm earlier results of yield trials by the authors as well as trials by F. Aherne (1989, personal communication) which showed the negative effect of hull content on ED and PD. There were no special measures taken to ensure that all hulless barley samples in this test had the same hull content, however all samples had a relatively low percentage of hulls as indicated by the average DEC of over 3400 kcal kg-¹.
The results also indicate that there was little difference between hulless cultivars for PD and DEC, but significant differences for CP, GE, ED, and starch (Table 2b).
Agronomic traits
Yield (mean = 4962.21 kg ha-¹ ± 1571.03, range 1711 - 10,233), Test Weight (TW) (mean = 71.86 kg hl-¹ ± 5.645, range 57 - 83, Kernel Weight (KW) (mean = 38.13 g ± 4.87, range 20.3 - 48.4).
These data were reported by Temelli and Helm (1999) but are also relevant to these discussions.
There was no significant difference between genotypes for yield; however, the TW and KW did show significant differences (Table 2a). Year effect was not significant for any of the agronomic measurements. Location effect was significant (P</=0.05) for yield and KW. There was significance for all interactions. In spite of the fact that genotypes did not differ significantly in yield, the waxy endosperm barleys (HB313 and HB803) were the lowest yielding, while Falcon and Harrington yielded the highest. The highest yielding sites were Olds (7118 kg ha-¹), Calmar (7072 kg ha-¹) and Lacombe (6049 kg ha-¹), while the lowest yielding sites were Irricana (3674 kg ha-¹), Glenlea (3793 kg ha-¹) and Beaverlodge (3836 kg ha-¹). The yield differences were related to fertility, moisture and disease conditions. Most of the interactions can also be related to climatic and disease effects over years and locations.
The TW and KW data were missing for several additional locations in 1993 and 1994. While year and location effects were primarily due to climatic and disease factors, the genotype effects were compounded by type, with differences between two-row and six-row, hulled and hulless as well as the waxy starch type. Test weight was also most probably influenced by the level of adhering hulls on the hulless barleys, as we did not take extraordinary precautions to ensure that every sample was completely free of hulls.
Quality traits
Crude Protein (mean 13.10 % ± 2.16 %, range 8.1 - 17.7 %)
Genotype (P </= 0.001), Location (P </= 0.01), Year (P </= 0.05), Genotype x Year (P </= 0.05) (Harrington included only) and Location x Year (P </= 0.001) effects were significant (Tables 2a and 2b). Barley grown in 1993 had a higher protein content than barley grown in 1994 and 1995. The sites giving the highest CP content were Calmar (14.96%), Lacombe (14.90%), Lethbridge (14.18%) and Olds (14.18%); the lowest protein sites were Goodale (10.12%), Irricana (10.72%) and Beaverlodge (11.73%). On average, HB803 (14.56%), a waxy starch barley, had the highest protein content while Harrington, the hulled barley, had the lowest protein content (11.72%).
Protein content was negatively correlated with starch, TW and KW, and positively correlated with GE, PD, DEC and yield (Table 3).
Starch (mean = 61.68 % ± 3.87 %, range 50.36 - 72.04 %)
Genotype (P </= 0.001), Location (P </= 0.05) (Harrington excluded only), Year (P </= 0.05) (Harrington included only), Genotype x Location (P </= 0.05) and Location x Year (P </= 0.001) effects were significant (Tables 2a and 2b). On average, the highest starch cultivars were HB325 (64.48 %) and HB608 (63.43 %); the lowest were HB803 (56.54 %) and Harrington (57.88 %). Goodale and Beaverlodge, which were low protein sites, had the highest starch levels at 65.83 % and 68.64 %, respectively; the lowest starch levels were found at Olds (59.28 %) and Calmar (60.11 %), both among the high protein sites.
Starch content was negatively correlated with CP, GE and PD (Table 3). Only the TW, KW and ED were positively correlated with starch content. Digestible energy content was negatively correlated with starch content, but it was not significant.
Table 3. Correlation analysis results, Harrington excluded.
| Variable | Year | Crude Protein | Gross Energy | Protein Digest. | Energy Digest. | Digest. Energy Content | Starch | Yield | Test Weight | Kernel Weight |
| Year |  | -0.304 | ns | -0.543 | 0.303 | 0.282 | 0.352 | ns | 0.149 | 0.126 |
| Crude Protein | *** | | 0.639 | 0.555 | ns | 0.202 | -0.630 | 0.150 | -0.171 | -0.288 |
| Gross Energy | ns | *** | | 0.231 | ns | 0.478 | -0.450 | 0.389 | -0.224 | -0.208 |
| Protein Digest. | *** | *** | *** | | 0.391 | .453 | -0.371 | ns | ns | ns |
| Energy Digest. | *** | ns | ns | *** | | 0.906 | 0.166 | ns | 0.139 | 0.169 |
| Dig. Energy Cont. | *** | *** | *** | *** | *** | | ns | 0.215 | ns | ns |
| Starch | *** | *** | *** | *** | ** | ns | | ns | 0.171 | 0.180 |
| Yield | ns | * | *** | ns | ns | *** | ns | | ns | ns |
| Test weight | * | ** | *** | ns | * | ns | ** | ns | | 0.292 |
| Kernel weight | * | *** | ** | ns | ** | ns | ** | ns | *** | |
The level of significance of each correlation is presented in the section below the diagonal and the Pearson correlation coefficients are given in the section above the diagonal for those combinations with a significant correlation.
Significance levels:
| ns | - not significant |
| * | - P </= 0.05 |
| ** | - P </= 0.01 |
| *** | - P </= 0.001 |
Gross Energy (mean = 4017.73 Kcal ± 103.26 Kcal, range 2677.3 - 4235.6)
There was no significance for anything but Location x Year (P </= 0.001) (Table 2a); however, if Harrington was removed from the analysis then Genotype (P </= 0.01) and Location (P </= 0.05) showed significance (Table 2b). This indicates that there was a difference between the hulless lines. Harrington was very variable with a range of 2677.3 Kcal to 4117 Kcal.
Gross energy was positively correlated with CP, PD, DEC and yield (Table 3).
Protein Digestibility (mean = 76.93 % ± 6.66 %, range 51.6 - 89.9 %)
Harrington was significantly lower in protein digestibility than the hulless cultivars. Therefore, Genotype was significant (P </= 0.001) when Harrington was included in the calculation, but not significant when it was removed from the analysis (Tables 2a and 2b). This indicates that there were no differences between hulless cultivars for PD in the pig. There was a significant Year effect (P </= 0.001). The highest PD was 81.36% in 1993. The average PD was 75.86% in 1994 and 73.60% in 1995. There was more variation in PD in 1994 (SD=6.2%) and 1995 (SD=7.3%) than in 1993 (SD=4.0%).
Protein digestibility was positively correlated with CP, GE, ED and DEC (Table 3) and negatively correlated with starch and fibre (Temelli and Helm, 1999).
Energy Digestibility (mean = 84.85 % ± 4.53 %, range 68.0 - 92.1 %)
Harrington was the lowest in ED with an average of 75.5 %. This influenced the level of significance for Genotype which was P </= 0.001 when Harrington was included and P </= 0.05 when excluded (Tables 2a and 2b). Year effect was also significant (P </= 0.01) as was the interaction of Genotype x Year (P </= 0.01). When Harrington was removed from the analysis the G x Y interaction was not significant. The range between hulless was 4.03 % in 1993, 4.0 % in 1994 and 3.01 % in 1995.
Energy digestibility was positively correlated to PD, DEC, starch, TW and KW (Table 3).
Digestible Energy Content (mean = 3407.47 kcal kg-¹ ± 215.32 kcal kg-¹, range 1847.75 - 3741.8 kcal kg-¹)
Digestible energy content is the most important measurement and is used for calculating energy levels in the ration. Since both GE and ED are used to calculate DEC, they all respond the same. The significance for Genotype (P </= 0.001), Year (P </= 0.01), and Genotype x Year (P </= 0.001) were reduced when Harrington was removed from the analysis (Tables 2a and 2b). This indicates that there was little difference between hulless cultivars and that year differences were significant.
Digestible energy content was positively correlated to CP, GE, PD, ED and yield (Table 3).
Fibre, lipids, beta-glucans, pentosans, ash, soluble fibre, insoluble fibre and total dietary fibre were reported by Temelli and Helm (1999). However, they did not report the interactions of these with feed quality for the pig.
Pentosans were negatively correlated with CP (Temelli and Helm, 1999), PD, lipid, beta-glucan and soluble fibre and positively correlated with ED, DEC, insoluble fibre and total fibre (Table 4).
Beta-glucan content was negatively correlated with ED, DEC, pentosans and starch (Temelli and Helm, 1999); there was positive correlation with CP (Temelli and Helm, 1999), GE, lipid, soluble fibre and total fibre.
Soluble fibre was negatively correlated to ED, DEC, pentosan, insoluble fibre and starch (Temelli and Helm, 1999). Insoluble fibre showed a negative correlation with PD; total dietary fibre was negatively correlated to DEC and PD. It is evident that fibre content is related to hull content and that all forms of fibre have an influence on both energy and protein utilization by the pig.
The other interesting association was that lipid content was positively correlated with GE, but there was negative correlation with ED. The higher energy that was obtained from the lipids was canceled by lower digestibility. As a result, DEC was not affected.
Table 4. Correlation analysis results, Harrington excluded.
| Variable | Gross Energy | Protein Digest. | Energy Digest. | Digest. Energy Content | Pentosan | Beta-glucan | Soluble Fibre | Insoluble Fibre | Total Fibre | Lipid |
| Gross Energy | | 0.231 | ns | 0.478 | ns | 0.170 | ns | ns | ns | 0.274 |
| Protein Digest. | *** | | 0.391 | 0.453 | -0.203 | ns | ns | -0.259 | -0.174 | ns |
| Energy Digest. | ns | *** | | 0.906 | 0.274 | -0.234 | -0.152 | ns | ns | -0.215 |
| Dig. Energy Cont. | *** | *** | *** | | 0.275 | -0.134 | -0.129 | ns | -0.132 | ns |
| Pentosan | ns | *** | *** | *** | | -0.131 | -0.141 | 0.299 | 0.187 | -0.150 |
| Beta-glucan | ** | ns | *** | * | * | | 0.669 | ns | 0.305 | 0.308 |
| Soluble Fibre | ns | ns | * | * | * | *** | | -0.150 | 0.439 | 0.127 |
| Insoluble Fibre | ns | *** | ns | ns | *** | ns | * | | 0.822 | -0.170 |
| Total Fibre | ns | ** | ns | * | ** | *** | *** | *** | | ns |
| Lipid | *** | ns | *** | ns | * | *** | * | ** | ns | |
The level of significance of each correlation is presented in the section below the diagonal and the Pearson correlation coefficients are given in the section above the diagonal for those combinations with a significant correlation.
Significance levels:
| ns | - not significant |
| * | - P </= 0.05 |
| ** | - P </= 0.01 |
| *** | - P </= 0.001 |
Conclusions
This study raised several new questions while answering some of the old questions. As expected there was a greater difference between years than between locations and genotypes for most of the quality factors examined. The differences between genotypes were primarily due to the hulled versus hulless lines, with little difference between hulless lines except for protein, energy, lipid, beta-glucan, starch, ash, soluble fibre and total fibre. Most of the differences in protein, starch and beta-glucan were due to the waxy starch cultivars which were higher in protein, lower in starch and higher in beta-glucan content.
The level of fibre seemed to have the largest effect on DEC and protein for the pig. The level of fibre influenced ED to the greatest extent, but PD was also affected. These results are not unexpected as these confirm earlier results from the authors and Aherne (1989, personal communication).
One of the unexpected results was the effect of lipids on ED. Increased lipid content increased GE, but the percent of energy that was digested was reduced so that DEC in the pig was not affected. What we cannot determine from this experiment is if the digestibility of the lipid was due to its significant association with beta-glucan and insoluble fibre. It is reported that these have an effect upon blood cholesterol (Pick et al., 1998) as well as the rate of conversion of starch to sugars in the blood (Newman et al., 1989a and 1989b).
Yield was not negatively correlated with any of the characteristics measured except ash (Temelli and Helm, 1999). There was a positive correlation with DEC, GE and CP. This indicates that we can expect that further increases in yield can be made without any detrimental effects upon feed quality. It also indicates that the sites with the highest yield (and therefore the lowest stress factors that limit yield) produce barleys with the best feeding values. Growing hulless cultivars in stress environments where the genotype is not well adapted will lower the feed quality of the cultivar. Therefore, these results for certain cultivars may differ if that cultivar is grown where it is not meant to be grown.
Since this research was started in 1993, a large number of new cultivars have been released with improved yields. As new cultivars are developed we expect to see yields and quality increase in the high yielding environments of Alberta.
J.H. Helm1, P.E. Juskiw1, L. Oatway1 and W.C. Sauer2
1 Alberta Agriculture, Food & Rural Development, Field Crop Development Centre, Lacombe, AB
2 University of Alberta, Department of Agricultural, Food and Nutritional Science
Helm, J.H., P.E. Juskiw, L. Oatway, and W.C. Sauer. 2000. Genetic and Environmental Effects on the Feed Quality of Hulless Barley. Final Report, Farming for the Future Project #94M616 (http://www.aari.ab.ca/index.cfm) and Alberta Barley Commission Project #60-057 (http://www.albertabarley.com/). |
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