Optimal spatial and temporal measurement repetition
for reducing environmental variation of berry
traits in grape breeding
Akihiko Sato
*, Masahiko Yamada, Hiroshi Iwanami,
Nobuyuki Hirakawa
1Persimmon and Grape Research Center, National Institute of Fruit Tree Science, Ministry of Agriculture, Forestry and Fisheries, Akitsu, Hiroshima, 729-2494 Japan
Accepted 8 November 1999
Abstract
Environmental variance components were estimated for berry ripening time (BRT), berry weight (BW), soluble solids concentration (SSC), titratable acidity (TA), and deformation at the ®rst major peak (DFP) and maximum force (MF) in penetration tests of berry ¯esh in grapes (Vitis viniferaL. and V. labruscana Bailey). The variance among berries within clusters was largest among environmental variance components for BW, SSC, DFP and MF. The variance among clusters within vines was smaller than the variance among berries within clusters for all traits. The sum of the variance among years and the variance associated with the genotypeyear interaction was generally larger than that among vines within genotypes. Consequently, increasing the number of yearly repetitions was more ef®cient than increasing vine replications in evaluating the genetic potential in breeding.#2000 Elsevier Science B.V. All rights reserved.
Keywords: Vitis vinifera;Vitis labruscana; Fruit breeding; Environmental variation
1. Introduction
Fruit breeding requires testing of many seedlings to increase the probability of selecting superior genotypes. However, the number of seedlings used in fruit tree
*Corresponding author. Tel.:
81-846-45-1260; fax:81-846-45-5370.
E-mail address: satoaki@akt.affrc.go.jp (A. Sato)
1Present address: Fukuoka Agricultural Research Center, Chikushino, Fukuoka, 818-0011 Japan.
breeding is restricted compared to annual crop breeding, because perennial fruit crops occupy a large area and have a long juvenile phase. Early evaluation and selection allow an ef®cient use of testing facilities, and enable breeders to test a large number of seedlings in a given period.
Most commercially important traits of grapes, such as berry ripening time (BRT), berry weight (BW), soluble solids concentration (SSC), titratable acidity (TA), and berry ¯esh texture are quantitative, and ¯uctuate depending on environmental factors. Therefore, it is important for grape breeders to obtain information on the contribution of genetic and environmental factors to phenotypic expression as reported for other fruit crops (Hansche and Brooks, 1965; Hansche and Beres, 1966; Machida and Kozaki, 1975; Kester et al., 1977; Yamada et al., 1993).
Increasing the number of vine replications, yearly repetitions, cluster and berry samples, increase the precision of discriminating genetic properties. Repeating measurements too much, however, decreases the number of offspring evaluated in a given period. Estimates of genetic and environmental variance components for traits provide information on the optimal sample size, yearly repetition, and vine replication. Estimated values of environmental variance components have been utilized to predict accurately the proportion of genotypes exceeding a critical value in an offspring population (Yamada et al., 1994a,b, 1995, 1997; Yamada and Yamane, 1997).
Generally, adding more locations, years, or both have been reported to be more ef®cient for estimating genetic properties than adding replications (Rasmusson and Lambert, 1961; Kaltsikes, 1970; Sekioka and Lauer, 1970; Patterson et al., 1977; Shorter and Norman, 1983; Swallow and Wehner, 1989). Yamada et al. (1993) reported that a broad-sense heritability for fruit ripening time, fruit weight, and SSC in Japanese persimmon (Diospyros kakiThunb.) was increased more by adding yearly repetition than adding tree replication.
Nesbitt and Kirk (1972) also showed that adding plot replication was more ef®cient than increasing the plot size to estimate the yield of muscadine grape. The variance component among vines within genotypes was generally larger than that within vines for SSC in grape (Rankine et al., 1962; Wolpert et al., 1980; Hagiwara et al., 1987). However, no information on the year effect, genotype year interaction, and vineyear interaction was provided in grapes.
A grape breeding project has been carried out at the Persimmon and Grape Research Center (PGRC) of the National Institute of Fruit Tree Science (NIFTS), Akitsu, Hiroshima, Japan, since 1968. Environmental variance normally ¯uctuate, depending on location, climate, and cultural management. Therefore, it is important to obtain information on the environmental variances under our cultural management and climate condition at Akitsu. The objectives of this study were: (1) to estimate environmental variance components speci®c to grape breeding at Akitsu and (2) to determine the effect of adding yearly repetition
and adding vine replication for reducing the environmental variation of six berry traits in grapes.
2. Materials and methods
This study was conducted at the PGRC of the NIFTS, using genotypes of seven diploid (`July Muscat', `Hiro Humburg', `Italia', `North Red', `Buffalo', `Steuben', and `Muscat Bailey A'), and two tetraploid (`Ryuho' and `Fujiminori)' cultivars ofV. viniferaL. andV. labruscanaBailey. The genotypes evaluated were used as cross-parents in a grape breeding program at the PGRC. Current-scion of these genotypes were grafted onto `Teleki 5BB' rootstock in May or June of 1992. Two vines per genotype were planted randomly into an offspring population grown in the same way in a test ®eld in June 1992, at 0.63.2 m spacing. Four year-old plants were evaluated for berry traits in 1995. Berry traits were evaluated for 2 years (1995 and 1996).
Four clusters were sampled per vine, using two vines for each of nine genotypes. Each cluster on a vine was harvested at its respective BRT. BRT was judged when berries had fully ripened and reached the best eating quality, and was rated on a scale of 1±8; a rating of 1 (late July), 2 (early August), 3 (mid-August), 4 (late (mid-August), 5 (early September), 6 (mid-September), 7 (late September), and 8 (early October). BW, SSC, TA, and the deformation at the ®rst major peak (DFP) and the maximum force (MF) as the textural properties in the berry penetration test (Sato et al., 1997) were also evaluated. SSC and TA were determined with a calibrated refractometer (model N1; Atago, Tokyo, Japan) and continuous titrator (model BK-D; Mitamura Riken Kogyo, Tokyo, Japan), respectively. TA was expressed as grams of tartaric acid in 100 ml of juice.
There are high correlation coef®cients between the sensory rating of dif®culty of breakdown in mastication and DFP, and between the sensory ¯esh ®rmness and MF (Sato et al., 1997). To measure DFP and MF, an 8 mm thick ¯esh section was cut longitudinally from each berry and was subjected to a penetration test. The sample was mounted on the stage of the rheometer (model NRM-2010J-CW; Fudoh, Tokyo, Japan). A 3 mm diameter plunger was used at a penetrating rate of 50.0 mm minÿ1 according to Sato et al. (1997). The force for compression and the distance from the surface of the sample was recorded as the force± deformation curve to an X±Y recorder. The value of DFP and MF were obtained from the force-deformation curve.
Smirnov one sample test, and approached a normal distribution for all traits. Therefore, the model of ANOVA was assumed to be applicable to the data.
The model adopted here to express the phenotypic value is Pijklmmgi
vijcijkmbijklmym(gy)im(vy)ijm, wherePijklmis the phenotypic value of thelth berry of thekth cluster of thejth vine of theith genotype in themth year,m
the overall mean,gia random effect contributed by theith genotype,vija random effect of thejth vine of theith genotype,yma random effect of themth year,cijkm a random effect ofkth cluster of thejth vine of theith genotype in themth year,
bijklma random effect of thelth berry of thekth cluster of thejth vine of theith genotype in themth year, (gy)imthe interaction betweenith genotype and themth year, and (vy)ijmthe interaction between thejth vine of theith genotype and the
mth year.
The ANOVA provided the variance associated with genotype (s2g) among vines
within genotypes (s2v), among clusters within vines (s2c), among berries within
clusters (s2b), among years (s2y), the genotypeyear interaction (s2gy), and the
vineyear interaction (s2vy). The sum of these variance components was
regarded as the total variance (s2T). The total environmental variance (s2E) can be
expressed as s2Es2y=ys2gy=ys2v=vs2vy= yv s2c= yvc s2b= yvcb,
where y is the number of yearly repetitions, v the number of vine replications per genotype,cthe number of cluster samples per year and vine,bthe number of berries sampled per cluster, respectively.
3. Results and discussion
The mean performance of the evaluated genotypes was 5.2 for BRT, 6.4 g for BW, 20.3% for SSC, 0.48g100 mlÿ1 for TA, 4.0910ÿ3m for DFP, and 0.75 N for MF, respectively (Table 2).
Table 1
Expected mean squares in analysis of variance using nine genotypes with two vines per genotype for 2 years
Source of variation DF Expected mean squares
Genotype 8 s2b3s2c12s2vy24s2gy24s2v48s2g
Year 1 s2b3s2c12s2vy24s2gy216s2y
Genotypeyear 8 s2b3sc212s2vy24s2gy
Among vines within genotypes 9 s2b3s2c12s2vy24s2v
Vineyear 9 s2b3s2c12s2vy
Among clusters within vines 108 s2b3s2c
Among berries within clusters 288 s2b
Grape cultivars evaluated and their performance in berry traits
Species Cultivars BRT BW (g) SSC (%) TA (g100 mlÿ1) Texture
DFP10ÿ3m MF (N)
V. vinifera July Muscat 4.0 ab 5.2 b 20.7 bc 0.32 a 2.18 a 0.861 cd
Hiro Humburg 5.5 bc 5.1 b 22.3 c 0.36 ab 2.90 b 0.547 ab Italia 5.8 cd 8.1 c 19.3 ab 0.45 a±c 1.76 a 0.555 ab
V. labruscana North Red 4.0 a 4.5 b 20.4 bc 0.46 a±c 4.51 c 0.441 a
Buffalo 4.5 ab 3.5 a 22.3 c 0.65 e 6.10 d 1.047 cd Steuben 5.6 bc 4.6 b 20.3 bc 0.50 b±e 5.97 d 0.838 c Muscat Bailey A 6.9 d 4.2 ab 20.5 bc 0.64 de 5.40 cd 1.269 d Ryuho 5.3 bc 9.5 c l8.0 a 0.56 c±e 5.04 cd 0.699 bc Fujiminori 5.0 a±c 13.0 d 18.7 ab 0.39 a±c 2.92 b 0.494 a
Mean 5.2 6.4 20.3 0.48 4.09 0.750
a
The abbreviations used for the column heading have already been de®ned in text.
b
Mean separation within columns by LSD test atP< 0.05. The log-transformed values were used in ANOVA for BW, DFP and MF. LSD was calculated as 1:96
2
p
sE, wheres2Es2y=2s2gy=2sv2=2s2vy=4s2c=16s2b=48.
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Table 3
Mean square for six berry traits evaluated using nine genotypes with two vines per genotype for 2 yearsa Source of variation Mean squares (MS)b
BRT10 BW102 SSC TA102 DFP102 MF102 Genotype 422.61**b 168.86** 102.66* 67.03** 191.75** 117.23** Year 222.32* 17.43* 35.31NS 5.92NS 20.78NS 36.18NS Genotypeyear 40.70* 3.15NS 19.88NS 6.93NS 5.46NS 13.67* Among vines within genotypes 30.21NS 3.88NS 14.23NS 9.42NS 1.77NS 6.34NS Vineyear 10.23** 2.51** 6.84** 4.54** 1.96NS 3.83* Among clusters within vines 0.71** 0.74** 1.80** 0.72** 1.55NS 1.66NS
Among berries within clusters 0.44 0.40 0.60 0.29 1.12 1.75
aThe abbreviations used for the column heading have already been de®ned in text. BW, DFP and MF were log-transformed. b
NS, * and ** referred to nonsigni®cant, signi®cant at P< 0.05 and 0.01, respectively, using F-test. F-value for the effect of genotype was calculated asF(MS for genotypeMS for vineyear)/(MS for among vinesMS for genotypeyear), according to Snedecor and Cochran (1972).
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The result of ANOVA showed that the effect of genotype was signi®cant at
P< 0.05 for SSC and atP< 0.01 for the other traits (Table 3). The effect of the vines within genotypes was nonsigni®cant for all traits.
The contribution of the environmental variance components to the total variance varied with the traits (Table 4). For BRT, the variances associated with year and vine (s2y; s2gy;s2vands2vy) were larger than s2c ands2b. For BW, as the
environmental variance components were generally small, it was easy to identify the genetic property. The variance among berries within clusters was the largest among the environmental variance components for all traits with the exception of BRT. Especially, the s2b of DFP and MF were very large, indicating that
increasing the number of berries evaluated per cluster increases the measurement accuracy effectively.
The cost and time to increase berry and cluster samples are generally smaller than yearly repetitions or vine replications. So, ®rst choice of grape breeders should be to measure more berries by increasing cluster or berry samples. Yearly repetitions or vine replications, however, take much cost or time. So, comparison between yearly repetitions and vine replications should be considered primarily. To compare the in¯uence of adding yearly repetitions and adding vine replications on the decrease of the s2E, the ratio of s2v= s2ys2gy shows the
ef®ciency of the two factors in decreasing the s2E, because the s2vy; s2c and s2b
decrease equally both by adding years and vine replications. Our results showed that the ratio was <1 for each trait except TA, in which the year effect could not be detected. Moreover, the year effect was signi®cant at P< 0.05 for BRT and BW, and the genotypeyear interaction was signi®cant for BRT and MF. F
-Table 4
Estimates of variance components and their percentage to the total variance obtained from the analysis of variance for berry traits using nine genotypes with two vines per genotype for 2 yearsa Variance
components
BRT10 BW102 SSC TA102 DFP102 MF102
s2g 7.54(63.9%) 3.42(80.7%) 1.57(40.1%) 1.15(52.3%) 3.00(66.5%) 2.11(45.4%) s2y 0.84(7.1%) 0.07(1.7%) 0.07(1.8%) 0
b
(0%) 0.07(1.6%) 0.10(2.2%)
s2gy 1.27(10.8%) 0.03(0.7%) 0.54(13.9%) 0.10(4.5%) 0.15(3.3%) 0.41(8.8%) s2v 0.83(7.1%) 0.06(1.4%) 0.31(7.9%) 0.20(9.1%) 0b(0%) 0.10(2.2%) s2vy 0.79(6.7%) 0.15(3.5%) 0.42(10.7%) 0.32(14.5%) 0.03(0.7%) 0.18(3.9%) s2c 0.09(0.8%) 0.11(2.6%) 0.40(10.2%) 0.14(6.4%) 0.14(3.1%) 0b(0%) s2b 0.44(3.6%) 0.40(9.4%) 0.60(15.4%) 0.29(13.2%) 1.12(24.8%) 1.75(37.5%) s2T 11.80(100%) 4.24(100%) 3.91(100%) 2.20(100%) 4.51(100%) 4.65(100%)
a
The abbreviations used for the column heading have already been de®ned in text. BW, DFP and MF were log-transformed.
value of the genotypeyear interaction was near the value atP0.05 for SSC and DFP. On the other hand, the effect of the vines within genotypes was nonsigni®cant for all traits. These results suggested that temporal variance components were larger than the component associated with vines, and that adding yearly repetitions is more ef®cient than adding vine replications in reducing the environmental variance.
The total number of offspring accommodated in a given ®eld space and evaluated in a given period decreases more by adding replications than by adding yearly repetitions unless the seedlings bear fruit and are evaluated in the ®rst year of planting (Yamada et al., 1993). Suppose r is the number of plants accommodated in a selection ®eld, and Ya is the number of years that selection can be continued in the selection ®eld in a breeding program, then the total number of offspring (N) that can be tested during the period is rYa. At the PGRC, the plants of offspring are raised by making softwood grafting of 2-month-old seedlings onto rootstock, and after a few months they are planted in a breeding ®eld; those grapevines bear fruit in the second to fourth year after planting. SupposeYis the number of years that measurements are repeated,Vthe number of vines per offspring genotype, and T the total number of genotypes accommodated in the ®eld over years. When the plants ®rst bear fruit in the second year of planting, TN/[(1Y)V]; the equation indicates that T
decrease more by adding vine replications than by adding yearly repetitions. Thus, adding vine replications is less ef®cient than adding yearly repetitions. Breeders should not add vine replications but add yearly repetitions in terms of reducing environmental variation and maximizing the total number of genotypes tested in a given period.
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