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a Dep. 436, AP9A/2, Abbott Laboratories, 100 Abbott Park Road, Abbott Park, IL 60064-6124
b Dep. of Agronomy, Univ. of Wisconsin-Madison, 1575 Linden Dr., Madison, WI 53706-1597
c Dep. of Plant Pathology, Univ. of Wisconsin-Madison, 1630 Linden Dr., Madison, WI 53706-1598
Corresponding author (mdcasler{at}facstaff.wisc.edu)
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ABSTRACT |
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 TOPNOTES ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
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Abbreviations: ADF, acid detergent fiber • ADL, acid detergent lignin • CW, cell wall • NDF, neutral detergent fiber • NIRS, near-infrared reflectance spectroscopy • WSC, water soluble carbohydrate
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INTRODUCTION |
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TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
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Genetic modification of NDF in forages has been reported. In reed canarygrass (Phalaris arundinacea L.), one cycle of bidirectional selection for NDF and forage yield created the following groups: low NDF–low yield, low NDF–high yield, mean NDF–mean yield, high NDF–low yield, and high NDF–high yield (Surprenant et al., 1988). At both reproductive and vegetative stages, the two low-NDF groups, on average, had lower NDF and acid detergent fiber (ADF) than the two high-NDF groups, although the difference in NDF at reproductive stage was attributed to the difference in maturity. At reproductive stage, the low-NDF groups also had lower yield per plant than the high-NDF groups; at the vegetative stage, their difference in yield was not significant.
In smooth bromegrass (Bromus inermis Leyss.), one cycle of divergent selection for NDF produced a low-NDF synthetic and a high-NDF synthetic (Carpenter and Casler, 1990). The low-NDF synthetic was lower in NDF and ADF than the high-NDF synthetic, but the two synthetics were not significantly different in sward dry matter yield or acid detergent lignin (ADL). Most recently, Casler (1999) reported on the evaluation of selection cycles from six recurrent selection methods for reducing NDF in smooth bromegrass. Three of these methods completed three cycles; the other three methods completed two cycles. The response to the selection was significant at the vegetative and/or reproductive stage for five of the six methods. The least effective method in that study was uniparental mass selection at heading stage using wet-laboratory analysis for NDF determination. The three selection cycles selected by that method as well as the base population of the selection were independently evaluated in this study with more replications and at more sites.
Cell walls, especially when highly lignified, could serve as preexisting structural defenses against microorganisms which are incapable of producing the appropriate degradative enzymes (Ride, 1983). Therefore, it is conceivable that genetic modification of NDF, of which lignin is a part, could change the reaction of plants to pathogens. Water soluble carbohydrates (WSC) make up the largest share of noncell-wall carbohydrates. Breese and Davies (1970) reported that successful divergent selection for WSC in perennial ryegrass (Lolium perenne L.) for three generations resulted in higher susceptibility to crown rust infection (caused by Puccinia coronata Corda) for the families with high WSC. Webb et al. (1996) reported that plants selected for low ADL in alfalfa (Medicago sativa L.) showed greater susceptibility to alfalfa rust (caused by Uromyces striatus J. Schröt.) and spring blackstem (caused by Phoma medicaginis Malbr. & Roum. in Roum.) in the field than those selected for high ADL, although a further experiment in the greenhouse found little or no relationship between ADL and the reaction of alfalfa to the rust pathogen. It was our concern that selection for low NDF might have increased susceptibility of smooth bromegrass to diseases.
On the other hand, selection for disease resistance has been shown to alter NDF in some cases further raising the concern that NDF and disease resistance could be genetically correlated. In intermediate wheatgrass [Thinopyrum intermedium (Host) Barkworth and D.R. Dewey], strains resistant to foliar diseases had lower NDF than those susceptible when diseases were present (Karn et al., 1989). In orchardgrass (Dactylis glomerata L.), three cycles of selection for resistance to purple leaf spot (caused by Stagonospora arenaria Sacc.) did not change NDF, even though the third cycle was later in maturity than the original cycle (Oberheim et al., 1987). In alfalfa, the cultivar Saranac, which was susceptible to anthracnose (caused by Colletotrichum trifolii Bain), and the cultivar Saranac AR, which was selected from Saranac for resistance to anthracnose, were compared for NDF in the greenhouse with and without inoculation with Colletotrichum trifolii (Lenssen et al., 1991). Saranac AR was lower than or similar to Saranac in NDF in stems or leaves. In addition, the difference between the two cultivars was not consistent in the two treatments or in different plant tissues.
The relationship between cell wall traits and disease reaction goes beyond genetic correlations. Forage plants with leaf diseases could have different NDF, ADL, and yield than healthy plants of the same genotypes. In a greenhouse study on intermediate wheatgrass, plants infected with Cochliobolus sativus (Ito and Kurib.) Drechsl. ex Dastur had higher NDF than healthy plants of the same strains (Karn and Krupinsky, 1983). In two greenhouse trials on orchardgrass, leaves of inoculated plants had higher ADL (permanganate method) than the leaves of the uninoculated plants (Sherwood and Berg, 1991). In a field study on alfalfa, crude fiber of fungicide-protected plots was similar to that of unprotected plots while dry matter yield of fungicide-protected plots was higher than or similar to that of unprotected plots depending on which fungicide was used (Summers and McClellan, 1975). In a field study on pearl millet [Pennisetum americanum (L.) Leeke] and its rust (Puccinia substriata Ellis and Barth. var. indica Ramachar and Cummins), fungicide-protected and urediniospore-inoculated plots had similar dry matter yield for two resistant cultivars while fungicide-protected plots yielded better than inoculated plots for two susceptible cultivars (Wilson et al., 1991). In a greenhouse study on red clover (Trifolium pratense L.), plants inoculated with Stemphylium sarciniforme (Cav.) Wiltsh. had 20 to 30% lower dry matter yield than uninoculated plants (Berg and Leath, 1996).
The objectives of this study were (i) to evaluate divergent selection for NDF in smooth bromegrass for direct response in NDF and correlated responses in disease resistance and other traits, (ii) to determine whether these responses change at different disease potentials, and (iii) to ascertain how plants at different disease potentials differ in cell wall traits and dry matter yield.
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MATERIALS AND METHODS |
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TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
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Evaluation in the Field
The five cycles, C-3 to C+1, were evaluated at three locations: Arlington Agricultural Research Station, Arlington, WI; West Madison Agricultural Research Station, Verona, WI (both Plano silt loam [fine-silty, mixed, mesic Typic Argiudolls]); and Agrecol Corp., Sun Prairie, WI (Houghton muck [Euic, mesic Typic Medisaprists]). A split-plot design was used at each location with disease potential (high or low) as the whole plot factor and selection cycle as the subplot factor. The whole plot factor was arranged in four randomized complete blocks at each location, but some plots were lost because of flooding at Sun Prairie, resulting in incomplete data at that location. Each subplot had two rows of 10 plants each. Centers of two adjacent plants were spaced at 0.91 m.
All selection cycles were seeded in June of 1994 in the greenhouse, and the seedlings were transplanted to the field in August of 1994. To create different disease potentials, we selected Cochliobolus sativus, a cause of leaf blight on smooth bromegrass, as a pathogen. The isolates of C. sativus used for inoculation were isolated from the diseased leaves of smooth bromegrass at the Arlington Agricultural Research Station in 1993 and were cultured on potato dextrose agar to produce conidia. Before transplanting, plants at the high disease potential were sprayed using a hand sprayer until runoff with a conidial suspension of C. sativus (5.7 x 104 conidia per mL sterilized distilled water, with two drops of Tween 20 added per 100 mL). Then the inoculated plants were kept in a humidity chamber for 24 h before being transplanted 4 to 8 d later. At the time of transplanting, all inoculated plants expressed moderate to severe disease symptoms. Additional inoculum was not delivered to plants once they were established in the field. The plants at the low disease potential were sprayed with sterilized distilled water (two drops of Tween 20 added per 100 mL) in place of conidial suspension before being placed in a humidity chamber and transplanted to the field. In addition, the plants at the low disease potential were sprayed with 0.9 to 2.2 kg a.i. ha-1 mancozeb (zinc ion and manganese ethylene-bisdithiocarbamate) one to two times for each growth-harvest cycle to reduce disease occurrence. The plants were fertilized with 100 kg N ha-1 2 wk after being transplanted.
Yield data were collected in June, August, and October of 1995 and 1996. Forages were harvested by subplot with a small-plot harvester, and fresh forage yield was measured for each subplot. The plots at Sun Prairie were not harvested at the third harvest in 1996 due to inadvertent plot damage. One or two handfuls of forage were taken from the harvester for each subplot and air-dried at 55°C to provide the dry matter percentage of the fresh forage. Dry matter yield for each subplot was calculated from the fresh forage yield and the dry matter percentage of the sample from the harvester, and then divided by the number of live plants in the subplot to convert to dry matter yield per plant for a subplot. Plants were fertilized at the rate of 56 kg N ha-1 in the spring and after spring and summer harvests. Weeds were controlled by a combination of hand weeding and application of 1.12 kg a.i. ha-1 alachlor [2-chloro-N-(2,6-diethylphenyl)-N-(methoxymethyl)acetamide] and 0.56 kg a.i. bromoxynil [3,5-dibromo-4-hydroxybenzonitrile] in the spring.
Disease severity was assessed for the second and third harvests in 1995 and all three harvests in 1996. One to two weeks before harvesting forage for yield, each plant was scored visually for the percentage of the foliage diseased on the scale of 0 to 10: 0 = less than 1% of all leaf tissues diseased, 1 = 1 to 10%, 2 = 11 to 20%, 3 = 21 to 30%, 4 = 31 to 40%, 5 = 41 to 50%, 6 = 51 to 60%, 7 = 61 to 70%, 8 = 71 to 80%, 9 = 81 to 90%, and 10 = 91 to 100%. The average of all plants in a subplot was used to represent the disease severity of that subplot. Further, the average disease severity of a subplot was transformed to a 0 to 2 log scale for statistical analysis by the formula 
to correct for unequal variances on the original scale, where x is a value on the original scale and y is the transformed value on the log scale. No attempt was made to distinguish different diseases in disease assessment, although three diseases were predominant: leaf blight caused by C. sativus, brown leafspot caused by P. bromi, and rust caused by Puccinia coronata Corda (Delgado, 1998). Plants of all selection cycles at both disease potentials at all three locations survived well throughout the experiment, thus no survival data were taken.
Frequency of heading prior to harvest was scored as 0 to 2 according to the number of tillers with fully emerged panicles: if none, score = 0; if 1 to 5, score = 1; if more than 5, score = 2. The scores of all plants for a subplot were averaged to give a variable, which we call heading index. It was taken for the second and third harvests in 1995 and all three harvests in 1996. Heading index was a measure of the number of emerged heads at the time of assessment for a subplot, combining variation in relative maturity with variation in number of tillers per plant.
Cell Wall Traits Determination
A forage sample was taken for each subplot by bulking one to two tillers from each plant in the subplot. For the spring harvest, this was done when most plants were at fully headed growth stage. For the summer and fall harvests, it was done when at least 20% of the plants were heading. The samples were air-dried at 55°C, ground through a 1-mm screen in a Wiley-type mill, and reground through a 1-mm screen in a cyclone mill. All 600 samples were scanned by a NIRS (near-infrared reflectance spectroscopy) monochromator (Model 6500, NIRSystems/Perstorp Corp., Silver Spring, MD). A calibration set of 103 samples was selected by means of the NIRS software for the monochromator (Infrasoft International, 1995). Neutral detergent fiber, ADF, and ADL of the calibration samples, all on a dry-matter basis, were determined by sequential analysis on 0.5-g samples in duplicate (Robertson and Van Soest, 1981). To improve the precision of ADL, all samples were analyzed for ADF and ADL again on 0.5-g samples in duplicate, skipping the NDF step. Acid detergent fiber determined without the NDF step was, on average, 12 g kg-1 DM higher than ADF determined with the NDF step. However, the correlation coefficients between the four ADF determinations were all very high, in the range of 0.97 to 0.99. On the other hand, acid detergent lignin determined without the NDF step was, on average, 5.6 g kg-1 DM higher than ADL determined with the NDF step, but the correlation coefficients between the four ADL determinations were relatively low, in the range of 0.35 to 0.51, suggesting the need for multiple measurements. The averages of all determinations for each trait were used to develop the prediction equations for NDF, ADF, and ADL by the NIRS software of Infrasoft International (1995). The R2 for the prediction equations were 0.99, 0.99, and 0.73 for NDF, ADF, and ADL, respectively. The standard errors of cross-validation for NDF, ADF, and ADL were 6.51, 3.94, and 2.03 g kg-1 DM, respectively. Neutral detergent fiber, ADF, and ADL of all samples were predicted by the prediction equations. Hemicellulose and cellulose were calculated as NDF - ADF and ADF - ADL, respectively. Further, hemicellulose, cellulose, and lignin were divided by NDF to give cell wall hemicellulose (CW-hemicellulose), cell wall cellulose (CW-cellulose), and cell wall lignin (CW-lignin), respectively. Morrison (1980) reported that the Van Soest detergent system underestimates the hemicellulose and overestimates the cellulose. For this reason, CW-hemicellulose and CW-cellulose were used only for the comparison of samples. Such a comparison is valid under the assumption that the bias of the estimates on hemicellulose and cellulose is consistent across all samples in a block, which is likely to be true for comparisons made within one species at a single stage of maturity.
Statistical Analyses
The experiment was a split-plot design replicated across three locations. For dry matter yield and all cell wall traits, each subplot had repeated measurements at three harvests in each of two consecutive years. Each of these traits was fitted to the following linear model:
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For disease severity and heading index, there were no measurements for the spring of 1995. Thus, repeated measurements for each subplot did not have a balanced combination of harvests and years. To avoid an unbalanced model, repeated measurements in the two harvests in 1995 and the three harvests in 1996 were treated as levels of one factor termed assessment, instead of as combinations of years and harvests. The linear model is
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For the calculation of genetic gain per cycle averaged over all cycles (C-3 to C+1), we assigned C+1 a cycle number 2.6 (rounded up from 2.595) to account for the fact that C+1 was selected by a higher selection intensity than C-1, C-2, and C-3 and was selected by biparental mass selection instead of uniparental mass selection. Thus the cycle numbers for C-3 to C+1 were -3, -2, -1, 0, and 2.6, as if C+1 had been selected by the scheme that was used in selection for low NDF. These cycle numbers were derived under the assumption of random-mating equilibrium at each cycle and constant phenotypic and additive variances (
2P and 2A) throughout the recurrent selection. The derivation was in six steps: (i) calculate the selection intensity (i) from the proportion of plants selected for each cycle (Burrows, 1972); (ii) compute the expected genetic gain (
g) over the previous cycle for cycles C-1, C-2, and C-3 using formula 
, or for cycle C+1, using 
(note that these formulas are the same for both diploid [Empig et al., 1981] and autotetraploid [Rowe and Hill, 1984]); (iii) set the genotypic mean of C0 at an arbitrary value, say 0; (iv) add cumulatively the expected genetic gains to obtain the expected genotypic mean of each cycle; (v) divide the expected genotypic mean of each cycle by 
to cancel from all terms; (vi) multiply the expected genotypic mean of each cycle by a common constant so that cycle C-3 has a value of -3. The assumption underlying the above derivation implied that the response to the recurrent selection was linear. A linear contrast was constructed from these cycle numbers to test the linear response to the recurrent selection. The contrast coefficients were the cycle numbers subtracted by their average.
Inbreeding coefficients were calculated for all cycles assuming that the inheritance was disomic, that every plant in a population had the same chance to be pollinated by any plant in the population, and that the plants of C0 had an inbreeding coefficient of zero and were unrelated to each other (Han and Casler, 1999). The inbreeding coefficients calculated under the assumptions are (from C-3 to C+1): 0.0107, 0.0061, 0.0015, 0.0000, 0.0500. The pattern of inheritance in smooth bromegrass can be disomic or tetrasomic (Armstrong, 1981). If the inheritance were tetrasomic, we suspect that the inbreeding coefficient would be lower for all selected cycles. A linear contrast was constructed from the inbreeding coefficients by subtracting their average from each of them. This contrast tests whether cycles are linear for a trait with respect to their inbreeding coefficients.
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RESULTS AND DISCUSSION |
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TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
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There are two possible explanations for the result that high disease severity was associated with high ADL and high CW-lignin. First, our measurements of acid detergent lignin and CW-lignin included chitin from fungal cell walls, and there was a larger amount of pathogenic fungi in the plants at the higher disease severity. Second, the diseased tissues had additional lignification in the cell walls. This implies that lignification was involved in plant response to the disease, but not necessarily in plant resistance response to the disease. The result on NDF disagrees with Summers and McClellan (1975), who found that fungicide-protected alfalfa plots were similar to unprotected plots for crude fiber. The association between high disease severity and high NDF, ADL, and CW-lignin suggests that diseases could reduce forage nutritional quality.
None of the significant differences in disease severity between the two disease potentials was associated with a significant difference in dry matter yield (Table 3). This result partially agrees with Summers and McClellan (1975), who found that plots protected by one fungicide yielded more than the unprotected plots while plots protected by another two fungicides were similar in yield to the unprotected plots. The result disagrees with Wilson et al. (1991), who found in pearl millet that fungicide-protected plants had higher dry matter yield if the cultivars were susceptible to the diseases.
The interaction between disease potential and selection cycle was not significant for any trait measured, indicating that the relative differences among cycles in these traits were not affected by disease potentials, i.e., the responses in these traits to divergent selection for NDF were not affected by disease severities.
Direct Response to Selection for NDF
Selection for NDF was effective in both high- and low-NDF directions, as indicated by the overall linear response to selection (P < 0.001), the linear response in the low-NDF direction (P < 0.001), and the difference (P < 0.001) between the high-NDF cycle (C+1) and the base population (C0) (Table 4). Averaged over the two disease potentials and all harvests in 2 yr, the third cycle from selection for low NDF (C-3) was 1.9% lower than the base population C0 (525.3 vs. 535.5 g kg-1 DM, P < 0.001), and the first cycle from the selection for high NDF (C+1) was 2.1% higher than the base population C0 (546.6 vs. 535.5 g kg-1 DM, P < 0.001). Even though cycle x year interaction was significant 
, the relative NDF levels of cycles were fairly consistent over the 2 yr. Cycle x harvest interaction, however, was statistically significant (P < 0.001) as well as large in magnitude.
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Correlated Responses in Other Cell Wall Traits
The correlated response in ADF to selection for NDF almost mirrored the response in NDF (Table 4; Fig. 1 A, B). On average, C-3 was 3.4% lower than C0 in ADF (272.2 vs. 281.9 g kg-1 DM, P < 0.001) and C+1 was 2.4% higher than C0 in ADF (288.7 vs. 281.9 g kg-1 DM, P < 0.001). The relative ADF levels of cycles were consistent over the 2 yr, as indicated by the nonsignificant cycle x year interaction. Similar to the response in NDF, the response in ADF was more appreciable in the spring than in the summer or the fall, but linear response to selection was significant for all three seasons (Table 4).
The correlated response in ADL was only evident in the spring harvest (Table 4; Fig. 1 C): C-3 was 5.5% lower than C0 (29.31 vs. 31.03 g kg-1 DM, P < 0.001) although C+1 was similar to C0 (31.29 vs. 31.03 g kg-1 DM, P > 0.05). The linear response in ADL was not significant for the summer or the fall harvests, possibly because selection for NDF was based on forage samples in the spring.
The correlated response in CW-hemicellulose was in the opposite direction of NDF (Table 4, Fig. 2 A) while the correlated response in CW-cellulose was in the same direction of NDF (Table 4, Fig. 2 B). In selection for low NDF, CW-hemicellulose increased 2.7 g kg-1 NDF per cycle (P < 0.01) while CW-cellulose decreased by 2.6 g kg-1 NDF per cycle (P < 0.01). In selection for high NDF, cycle C+1 was 2.8 g kg-1 NDF lower (P < 0.05) in CW-hemicellulose and 2.7 g kg-1 NDF higher (P < 0.05) in CW-cellulose than the base population C0. The pattern of responses in CW-hemicellulose and CW-cellulose to selection for NDF was consistent across all harvests (Table 4, Fig. 2 A, B). For CW-lignin, there was no correlated response in the spring harvest (Table 4). In the summer and fall harvests, CW-lignin responded in the opposite direction of NDF, increasing 0.3 and 0.4 g kg-1 NDF per cycle (both P < 0.01), respectively, as NDF was reduced (Fig. 2 C).
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There were no literature reports, to our knowledge, on the correlated responses in cell wall composition due to selection for NDF, as evaluation of populations from selection for NDF generally did not include cell-wall based traits (Surprenant et al., 1988; Carpenter and Casler, 1990; Buendgen et al., 1990; Casler, 1999). This pattern of a reduction in NDF leading to an increase in CW-hemicellulose and a decrease in CW-cellulose suggests that in the base population of this experiment (WB-RP1), NDF concentration is negatively correlated with CW-hemicellulose and positively correlated with CW-cellulose. Even though this pattern may or may not hold for all populations in all forage species, the composition of NDF should be investigated following selection for NDF concentration, because changes in NDF composition may affect NDF digestibility.
Correlated Response in Dry Matter Yield and Inbreeding Depression
Linear response in dry matter yield to selection for NDF was significant (P < 0.001) for the low-NDF direction when averaged over all harvests in the 2 yr (Table 4). Dry matter yield was lower for cycles with lower NDF, dropping from 200 g plant-1 in C0 to 180 g plant-1 in C-3 (P < 0.001); however, if C+1 is included, the positive linear response in yield to selection for NDF cannot be detected. From Fig. 1 D, it is obvious that C+1 did not follow the trend we found in the low-NDF direction. We have already described that the linear response in NDF extended to both the low-NDF and the high-NDF directions. If we recall that C+1 had the highest inbreeding coefficient of all cycles, the most reasonable explanation to low yield in C+1 is inbreeding depression. However, the contrast testing the linear trend of cycles with respect to inbreeding coefficients was not significant 
even though the overall test for differences among cycles was significant 
, suggesting that inbreeding alone cannot explain all the variation in yield of cycles. In the low-NDF direction, a likely explanation is that inbreeding depression and genetic correlation between NDF and yield acted synergistically to cause the yield to go down. In the high-NDF direction, the explanation is that inbreeding depression and genetic correlation between NDF and yield were counteractive.
In reed canarygrass, Surprenant et al. (1988) found that the low-NDF groups had lower yield per plant than the high-NDF groups in the spring, but did not differ from the high-NDF groups in the summer or the fall. In smooth bromegrass, Carpenter and Casler (1990) did not find a significant difference in sward dry matter yield between low- and high-NDF synthetics. Both Surprenant et al. (1988) and Carpenter and Casler (1990) compared low- and high-NDF populations at similar inbreeding levels, thus their results were not affected by inbreeding. From this study, it appears that both inbreeding and genetic correlation between NDF and dry matter yield contributed to the differences among cycles from recurrent selection for NDF, the trend being that either reduced NDF or increased inbreeding could cause reduced yield.
Correlated Response in Disease Resistance
There was no evidence that selection for low NDF modified disease reaction, as the linear response in the low-NDF direction was nonsignificant (Table 5). The disease severities of C-3 and C0 were not significantly different (Fig. 3
A, B) for any of the five assessments. Plants of C+1 expressed severe symptoms in the summer and the fall of 1995, causing the contrast testing overall linear response to selection for NDF to be significant for those two harvests in 1995 (P < 0.05 and P < 0.001, respectively). We had suspected that low CW-lignin might be responsible for the high disease severity of C+1 in the summer and fall harvests of 1995 because C+1 had significantly lower (P < 0.05) CW-lignin than all other cycles for those two assessments (data not shown). Yet C+1 also had significantly lower (P < 0.05) CW-lignin than all other cycles for the summer and fall harvests of 1996 (data not shown), for which we did not observe a significantly higher disease severity on C+1. Interestingly, C+1 happened to be the cycle with the highest inbreeding coefficient.
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Correlated Response in Heading Index
Heading index of cycles for the spring harvest of 1996 (Fig. 3 D) suggested that selection for low NDF resulted in low heading index. The contrast testing linear response in heading index to selection for NDF indicated the same (Table 5, P < 0.001). Surprenant et al. (1988) attributed the change in NDF at reproductive stage (spring harvest) to change in growth stage while Carpenter and Casler (1990) found no variation for maturity in their base population of selection.
The trend of heading index for the summer and fall harvests was quite different from that for the spring harvest. It appears that the association between lower NDF and lower heading index held for C+1, C0, and C-1 while the higher inbreeding coefficient of C-2 and C-3 was associated with more heads (Fig. 3 C, D).
Smooth bromegrass has little genetic variation for timing of reproductive maturity in the spring, probably due to its photoperiod sensitivity. Carpenter and Casler (1990) found no variation for maturity in their base population of selection. However, the result of this study, which used a different base population from Carpenter and Casler (1990), suggests that there is some variation in either growth stage or number of heads per se in smooth bromegrass, and selection for low NDF could lead to either late maturity or reduced number of heads for the spring harvest. Given that forage plants at a more advanced growth stage are usually higher in NDF, a change in growth stage possibly contributed to the change in NDF among selection cycles. We would not attribute all the change in NDF in the spring harvest to change in growth stage because the "match" between the curve of heading index over cycles and the curve (line) of NDF over cycles does not warrant it. In reed canarygrass, Surprenant et al. (1988) did attribute the change in NDF for spring harvest to a change in growth stage. Further study is needed to determine whether the direct response in spring harvest to recurrent selection for NDF is partially due to change in growth stage.
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CONCLUSIONS |
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TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
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ACKNOWLEDGMENTS |
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NOTES |
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TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
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Received for publication November 23, 1999.
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TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
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