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Relationships between yield components in first cropping year and average yield of short-day strawberries over two main seasons
Scientia Horticulturae 118 (2008) 14–19
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Relationships between yield components in first cropping year and average yield of short-day strawberries over two main seasons D.B. Shokaeva * All-Russian Research Institute of Horticultural Breeding, Zhilina 3-17, 302530 Orel, Russia
A R T I C L E I N F O
A B S T R A C T
Article history: Received 7 January 2008 Received in revised form 2 April 2008 Accepted 19 May 2008
Fruit productivity of the garden strawberry, Fragaria ananassa Duch., is a result of interrelationship of yield components contributing to it directly or indirectly. The main aim of the investigation was to find out whether there exists any general regularity, connecting relationships between main yield components in first cropping year to average yield of two main seasons. Two successive studies which primarily included 23 genotypes, differing in yield components and productivity, each, were planted in field conditions in spring 1999 and in spring 2000, respectively, and used for data collection to explore the material obtained in them. Four key yield components and average yields were measured in both cropping years, after which all possible ratios between the components were calculated to find out: first, the relationships to be influential on average yield of the two main seasons; second, type of the probable yield dependence upon the ratios; and, third, their values leading to high yields. Two ratios between the key yield components in first season, i.e.: inflorescence number per plant to branch crown number per plant, named ratio 1, and fruit weight (g) to flower count per inflorescence, named ratio 2, have been found to be related to average yield. An irregular surface, with a single peak falling approximately in its centre, describes average yield dependence upon the ratios. Values of the two ratios falling in the range of 1.0–1.6 each, provided that they are close, have enabled plants to produce high yields cumulatively over two first years. The paper highlights the most important differences in plant behaviour and yield dynamics of strawberry genotypes, depending on combinations of the ratios in first year, discerning those, which have been particularly advantageous to obtain very high yields, and are influenced by negative environmental factors least of all. Based on the findings, a method of predicting of average yield has been developed. Following this, usefulness of the method and possibilities of its using in strawberry breeding and variety trial are discussed. ß 2008 Elsevier B.V. All rights reserved.
Keywords: Fragaria ananassa Marketable yield Ratios between yield components
1. Introduction Yield of the cultivated strawberry, Fragaria ananassa Duch., like that of any other crop, is a cumulative result of various yield components influencing it directly or indirectly. Many plant characters and indices are of concern, however, when cultivars are grown as individual plants, particularly important yield components are: branch crown number per plant, inflorescence (truss) number per plant, flower (fruit) number per inflorescence and mean fruit weight. All the components except for the former contribute to yield directly. Branch crown number, although being not contributing to yield directly, is the key index of plant development, decisive for the other component characters and,
* Tel.: +7 4862 45 9235. E-mail address: [email protected]. 0304-4238/$ – see front matter ß 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.scienta.2008.05.021
consequently, for yield (Lacey, 1973; Webb et al., 1974; Baumann et al., 1993; Shokaeva, 2005a). These components have been reported to be intercorrelated, often negatively, and can interact compensatively (Swartz et al., 1985; Cross and Burgess, 1998; Daugaard, 1999; Shokaeva, 2006, pp. 68–76). Numerous studies using various cultivars were undertaken to explore correlations between yield and individual components and to determine their contribution to the-same-year yield in different locations. It has been found that yield is usually highly correlated with truss number per plant, while mean fruit weight and flower number per truss influence yield either weakly or indirectly, nevertheless all the components are very important (Hondelmann, 1965; Guttridge and Anderson, 1973; Lacey, 1973; Webb et al., 1974; Strik and Proctor, 1988; Baumann et al., 1993; Shokaeva, 2005b). The main aim of the research is to find out whether there is any general regularity, connecting relationships between main yield components in first cropping year to average yield of two main
D.B. Shokaeva / Scientia Horticulturae 118 (2008) 14–19
seasons. The intermediate objectives of the investigation are following: to measure the most important yield components in genotypes differing in productivity; to calculate ratios between them and to reveal those in first cropping year, which are influential on both first-year and average (of two first seasons of fruiting) yields; to find out whether there is any regular connection of the ratios to average yield; and, if there is, to trace the character of the probable relationship to make known the values of the ratios that may lead to high yields. 2. Material studied, methods and conditions of vegetative periods Two analogous field trials planted in spring 1999 and in spring 2000, respectively, which primarily included 23 strawberry genotypes each, were used to measure yield components and marketable yields during two full cropping seasons and to collect data needed. However, for some reasons two cultivars and one line were further excluded from the analysis of the data obtained in study 2. Fifteen genotypes (nine cultivars and six lines) were present in both experiments and, thus, estimated twice. These genotypes were: ‘Elsanta’, ‘Gariguette’, ‘Senga Sengana’, ‘Senga Tigaiga’, ‘Tago’, ‘Tantallon’, ‘Tenira’, ‘Toro’, ‘Zolushka of Kuban’, ‘Or 171-15-5’, ‘Or 913-7-140’, ‘Or 965-7-1’, ‘Or 967-5-29’, ‘Or 967-749’ and ‘Or 968-9-58’. Also, ‘Or 967-5-89’ was planted in both trials, but the data obtained in this line were omitted when analysing study 2. Additionally to them, the first trial included ‘Pandora’, ‘Redgauntlet’, ‘Vesnyanka’, ‘Voskhod’, ‘Vystavochnaya’, ‘Or 967-5-89’, ‘Or 975-12-62’ and ‘Or 968-8-94, while ‘Bylinnaya’, ‘Dukat’, ‘Elista’, ‘Saint Williams’, ‘Sudarushka’, ‘Yuzhanka’ and ‘Zenith’ were added to the second one. However, the data on ‘Bylinnaya’ and ‘Saint Williams’ have not been used in the research. As the investigation did not pursue the aim of estimation of individual strawberry genotypes, it did not matter, which genotypes would be used in it—cultivars or lines. A task of great concern was including patterns of cropping that could represent the existing diversity of the garden strawberries. The genotypes of choice were examined in preliminary studies, developed different habits, had different terms of fruit maturing and produced cumulative yields gradually ranging from very high to low. Additionally to that, three indices were taken into account: branch crown count per plant by first cropping year, inflorescence-tobranch crown ratio and flower count per plant. The genotypes with various combinations of the indices were available in the studies. One should say that from time to time several high-yielding cultivars and lines developed similar plant structure and had comparable indices, although they could vary and differentiate in different studies. As they are particularly important for fruit production, when it was possible and expedient, a couple of genotypes having similar indices were included. At the same time, a limited set of genotypes is able to represent the entire diversity only to a certain extent. To widen the representation, one genotype within each abovementioned couple, if they produced comparable yields, in experiment 2 was substituted for another, similar by traits and indices. Comparison of several genotypes with similar indices would allow answering the question whether a relation of the ratios to yield, which could be found in study 1, does exist, or the finding was occasional and happened thanks to the cultivar choice. Planting in different years could give the possibility to verify whether findings of the preceding study remained valid under somewhat different conditions or they were a matter of case, conditioned by the circumstances. At the same time, inclusion of the same genotypes in both studies and planting them in different years could allow tracing the influence of weather conditions on plant development and yield height. In addition, some combina-
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tions of indices are rare, and the genotypes that develop such plant structures are problematic to be substituted. A fully randomized design with three complete sets of the genotypes was used in both trials. Each genotype was repeated once in each block, being represented with 30 plants planted on spaced beds. The distance between beds was 80 cm. Plants on a bed were spaced 25 cm apart. The arrangement resulted in a planting density of 50,000 plants ha 1. The blocks were equipped with sprinkler irrigation. Plants were deblossomed in the planting years; runners emerged during both planting year and first fruiting seasons were regularly removed. Data from experiment 1 were collected in 2000 and 2001, and those obtained in experiment 2—in 2001 and 2002. Branch crowns, trusses and flowers were counted for each replicate of each cultivar/line, using ten typical plants in succession. Thereafter, mean values of the yield components, i.e. branch crown number per plant, inflorescence number per plant, flower number per inflorescence and also mean fruit weight in g, were calculated for both first and second fruiting years. Fruit were harvested two times a week throughout fruiting periods. All marketable berries were counted and weighed at each harvest for each plot. First-year, second-year and average marketable yields (marketable fruit are berries not less than 18 mm wide in the maximum diameter) were computed in t per ha. Mean fruit weights and yields were computed for the whole plots. Using values of the yield components, all possible ratios between them were computed for each replicate of each genotype to search for their connection to yield. Also, absolute sum of these four components (irrespective of measure units) was calculated for each genotype to find out its minimum that would be high enough to enable plants to produce high cumulative yield over two seasons, as yield has been found to be correlated with the index (Shokaeva, 2004a). In view of the fact that environmental conditions influence plant growth and development, sum of effective temperatures (above +5 8C) during three important periods of vegetation, i.e. (1) period of plant growth, flowering and fruit growth (from the beginning of growth to the end of May), (2) period of fruiting and runnering (June and July), (3) flower bud differentiation period (from the beginning of August to the end of vegetation), and also over the whole vegetative seasons were calculated (Table 1). Late spring frosts occurred in 2000 and in 2001. In 2000, air temperature falls of up to 5.5 8C and 5.0 8C took place on 8 May and 15 May, respectively. In 2001, late spring frosts happened on 9, 16 and 22 May ( 2.0 8C). Conditions of overwintering were favourable in all the winter seasons, and practically no freezeinduced injuries to plants were observed after them. In general, the Central Russia’s summer is rather hot and dry, while autumn seasons are usually short and cool. Statistical analyses have been performed using Methods of SAS Institute (USA, 1989). Duncan’s test has been used for determination of LSD between means at P = 0.05. Graphs representing average and maximum yield responses to two coefficients of
Table 1 Sums of effective temperatures (above +5 8C) over three important periods of vegetative seasons and over the whole seasons in the years of studying (1999– 2002) Period of plant development
Year 1999
Plant growth, flowering and fruit growth Fruit maturing and runnering Flower bud differentiation Whole vegetative season
2000
2001
2002
356.5
387.8
344.4
205.1
934.5 627.7 1918.7
747.8 667.5 1803.1
782.3 642.3 1769.0
858.2 – 2171.0
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Table 2 Ranges of the mean values of: four main yield components in first cropping year depending on genotype, two ratios between them, first-year, second-year and average yields in study 1 (2000–2001) Yield components and indices
Range
LSD05
(1) Branch crown number per plant (2) Inflorescence number per plant (3) Flower number per inflorescence (4) Fruit weight (g) Ratio 1 (2:1) Ratio 2 (4:3) First-year marketable yield (t per ha) Second-year marketable yield (t per ha) Average marketable yield (t per ha)
2.1–4.8 2.2–6.9 5.3–12.0 5.4–12.4 0.96–1.83 0.98–1.81 4.5–14.3 7.3–23.7 6.7–16.9
1.1 1.4 3.1 2.3 0.16 0.20 3.1 4.2 2.6
relationships between yield components have been performed using Axum 5.0 Software (MathSoft, Inc., USA, 1996). 3. Results The weather conditions of the planting year vegetative period in study 1 favoured growth and development of ‘maiden’ plants. However, in both first and second cropping years, late spring frosts caused injuries to flowers, particularly heavy in 2000, when all the genotypes except for the late-season ones experienced serious flower losses (data not shown). The most vulnerable flowers of ‘Redgauntlet’, ‘Elsanta’, ‘Gariguette’, ‘Tantallon’ and some others were injured rather severely in both seasons. The cultivars and lines studied significantly differed by the main yield components. Their values in the first cropping season represented different levels, gradually ranging from rather low to high (Table 2). All possible ratios between the components were calculated for each cultivar/line to distinguish the most important ones connected to yield, and to establish particularly favourable combinations of ratio values, on which top first-year, second-year and average of the two years yields could be based. Computation of average yields and exploration of their reference to the ratios between yield components which were measured and recorded in the first year of fruiting, have led to the finding that only two ratios appeared to be important and influential on average marketable yield: inflorescence number per plant to branch crown number per plant (2:1) and mean fruit weight to flower number per inflorescence (4:3). Ranges of the values found for these ratios, designated as ratio 1 and ratio 2, respectively, turned out to be similar (Table 2). Sum of the four components was not less than 24.5 for all the genotypes, reaching the maximum of 30.9. Correlation analysis revealed existence of a highly significant correlation between average yield and sum of the four components calculated for the first year (r = 0.68 at P 0.01). However, it was found that the two ratios between the two pairs of the components played an evidently more important role in cumulative (average) yield compared with the components themselves and their sum. The cultivars and lines that had close sum values, but different ratios might produce yields which were greatly different from each other, and vice versa. At the same time, the values of the ratios that led to high yields in the first year of fruiting were different from those that allowed achievement of high cumulative yields over the two first seasons. Top yields in the first year were obtained when either both ratios had relatively high values (more than 1.3), or one ratio (the first one) had a very high value, while the other was comparatively low (data not shown). Combinations of the ratios that were a guide to high average (cumulative) marketable yields noticeably varied, being at the same time rather specific. Genotypes with values of both ratios falling in the range from 1.1 to 1.6, had advantages over the others (Fig. 1). Although the
Fig. 1. Average (of two first years) yield response to two ratios between two pairs of main yield components measured in first fruiting year (data collected in 2000– 2001); the ratios are: 2:1—inflorescence number per plant to branch crown number per plant, 4:3—mean fruit weight (g) to flower count per inflorescence.
values did not ensure a top yield in any cultivar/line that had them, they were an indispensable condition of high two-year commercial productivity. Furthermore, the highest yield levels were characteristic of the genotypes that had approximately equal or at least relatively close values of both coefficients. The absolute maximum belonged to ‘Or 965-7-1’ the two ratios of which were 1.38 and 1.31, respectively, while sum of the main components amounted to 26.2. The genotypes that showed any ratio outside of the limits mentioned above produced lower yields on average. Very low values of both ratios in the first year, as well as any combination of values, where one of them was very high, whereas the other was very low (especially the second one), led to particularly low cumulative yields. Combinations of very high values of both ratios were absent. Lower values within the optimum ranges were distinctive of the genotypes that produced much higher marketable yields in the second-year compared to the first season. None of the genotypes studied belonged to the top-yielding groups in both years of fruiting. The same components were also measured in the second cropping season. Ratios between them varied much more extensively than those in the first year, and had a clearly weaker relation to yield, although the highest yields were also obtained when the two coefficients were not too low and the difference between them not particularly substantial (data not shown). The vegetative seasons during studying in experiment 2 seemed to be more favourable than those in the preceding study. The late spring frosts that happened in 2001 caused almost no injury to flowers, because plants of early to mid-season genotypes flowered 1–2 weeks earlier compared with the same two-year cultivars and lines in study 1, and the first frost impact happened when flowering of most mid-season genotypes was progressing to finish. Thus, the plants avoided significant flower losses, while most midlate and all the late-season genotypes began full flowering after the frosts passed. In spring 2002 no temperature falls below 0 8C occurred. In this experiment, plants of most cultivars and lines ripening in early to mid-season terms had formed by the first cropping year somewhat more branch crowns per plant compared with the same genotypes in study 1. For instance, plants of ‘Gariguette’ developed 4.2 vs. 2.6 branch crowns per plant in the previous study, ‘Tantallon’ produced 3.6 vs. 3.1 branch crowns, ‘Or 965-7-1’ and ‘Or 967-7-49’ had 5.3 vs. 3.9 and 4.0 vs. 3.4 branch crowns, respectively. Conversely, some mid-late and late-season genotypes, especially those with a large vegetative sink in first cropping year, developed noticeably fewer branch crowns: ‘Elsanta’
D.B. Shokaeva / Scientia Horticulturae 118 (2008) 14–19
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Table 3 Ranges of the mean values of: four main yield components in first cropping year depending on genotype, two ratios between them, first-year, second-year and average yields in study 2 (2001–2002) Yield components and indices
Range
LSD05
(1) Branch crown number per plant (2) Inflorescence number per plant (3) Flower number per inflorescence (4) Fruit weight (g) Ratio 1 (2:1) Ratio 2 (4:3) First-year marketable yield (t per ha) Second-year marketable yield (t per ha) Average marketable yield (t per ha)
2.0–6.2 2.1–9.0 6.0–10.3 5.8–11.4 0.91–1.59 0.86–1.87 4.1–15.3 7.8–24.5 7.0–16.8
1.0 1.2 1.9 2.1 0.14 0.21 1.3 1.5 1.3
produced only 2.1 vs. 2.4 branch crowns formed a year earlier in the first trial, ‘Or 171-15-5’ did 3.3 vs. 4.1 branch crowns, ‘Or 9675-29’ and ‘Or 968-9-58’ formed 3.1 vs. 3.8 and 2.1 vs. 2.6 branch crowns per plant, respectively. Establishment of ‘Bylinnaya’ (1.3 branch crowns), ‘Saint Williams’ (1.6 branch crowns) and ‘Or 9675-89’ (1.5 branch crowns) in the study was particularly poor. It subsequently resulted in extremely low both sums of the main yield components (they even have not reached 18.0) and cumulative yields (lower than 5.5 t per ha), which fell out of the set and looked inconsistent with the term ‘cultivar’. The data obtained using the genotypes were afterwards excluded from analysis to equalize the minimum indices in both studies, first of all yield minima. In consequence of this values of the main components in the first season ranged in this experiment to some extent differently compared with those in the study planted in 1999 (Table 3). This resulted in a narrower range of ratio 1, while ratio 2, conversely, ranged slightly broader. However, the genotypes, which were included in this trial repeatedly, had both component and ratio values comparable with those in the first study, or not particularly different from them. The principal differences that took place in study 2 were following: first, somewhat smaller fruit produced by most early to mid-season cultivars and lines and, second, more (in early to mid-season and some mid-late genotypes) or fewer (in mid-late and late-season genotypes) branch crowns and inflorescences per plant. The maximum value of flower number per inflorescence was lower in study 2, which could be to some extent connected with absence of ‘Or 975-12-62’. The highest mean value of the index in the preceding study distinguished this mid-season line. However, most early and mid-season genotypes initiated fewer flowers per truss in study 2. Sum of the four components varied from 20.4 to 30.5 depending on genotype, whereas its minimum value in the first study was 24.5. Average yield was correlated with the sum approximately as strongly as in study 1 (r = 0.73 at P 0.01). In this study, nine of 15 genotypes that were present in both trials produced higher average yields. The differences were particularly apparent in ‘Elsanta’ that produced 14.1 vs. 12.9 t per ha in the previous study, ‘Senga Sengana’ (12.8 vs. 9.8 t per ha), ‘Tantallon’ (14.3 vs. 10.8 t per ha), ‘Zolushka of Kuban’ (13.5 vs. 11.9 t per ha) and ‘Or 171-15-5’ (14.5 vs. 12.0 t per ha). Maximum yield values at most combinations of the ratios between components were higher than in study 1, sometimes by 2.5– 3.0 t per ha, but the absolute maximum was approximately the same, and belonged to the same line (Table 3). However, the peak on a response surface could not have been as prominent as that in study 1. A number of cultivars and one line, having different combinations of ratios, produced yields nearly reaching the maximum value. ‘Dukat’ plants of which were characterized with the ratios of 1.22 and 1.29, respectively, produced 15.5 t fruit -
Fig. 2. Maximum (average of two years) yield response to two ratios between main yield components measured in first fruiting year (data collected in 2001–2002); the ratios are: 2:1—inflorescence number per plant to branch crown number per plant, 4:3—mean fruit weight (g) to flower count per inflorescence.
per ha. The average yield of ‘Elsanta’ that had the ratios 1.08 and 1.04, was 15.1 t per ha. Two replicates of ‘Senga Tigaiga’ (the indices were 1.33, 1.31 and 15.3 t per ha for the first one and 1.35, 1.29 and 16.0 t per ha for the second one), ‘Tantallon’ (1.59, 1.56 and 15.5 t per ha) and ‘Or 171-15-5’ (the indices were 1.29, 1.56 and 15.5 t per ha on average) were also among those high-yielding genotypes. However, drawing of a graph, similar to that obtained using the data collected in study 1, turned out to be complicated because of lack of data in the area of high values of the ratios between components, particularly of ratio 1. Plants of early ripening and mid-season genotypes produced more both branch crowns and trusses, but truss numbers per branch crown in most cases turned out to be lower. Also, there was a gap in the area of relatively low values of ratio 1, as the cultivars/lines with a large vegetative sink produced fewer branch crowns and particularly inflorescences per plant compared with usual because of cool June temperatures in the year 2000. Additionally to that, most genotypes with low ratios had low sums of the components, which made them beyond compare with the genotypes that had high sums at the same ratio values in study 1. In this experiment where there were no harmful impacts of late spring frosts, average yields exceeding 15.0 t per ha occurred only in the genotypes with sum values varying within the range of 24.4–29.1, provided that the two ratios between components were close by value and ranged from 1.0 to 1.6 each like those in study 1 (Fig. 2). The response surface, reflecting changing of a maximum value of average yield depending on the ratios, resembled a convex halfsphere. However, the maximum value declined more quickly with increasing of ratio 1, particularly in combination with low values of ratio 2. In this study, increasing of the latter index, as well as decreasing of both ratios, beginning from the limits of the optimum area that still could ensure top yields, up- and downwards, respectively, led to more gradual yield decreasing compared with its dynamics in the preceding study. 4. Discussion Researchers, working with strawberry cultivars in different conditions, have occasionally observed rank reversals in yield height in second cropping year in comparison with first season (Hondelmann, 1965; Baumann et al., 1993; Shokaeva, 2005b). The results, obtained in the two studies where none of the cultivars and lines belonged to the group of top-yielding genotypes in both seasons, have been fully consistent with the findings reported by the authors, and proved the peculiarity of cropping, distinctive of
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the crop. Any strawberry genotype usually demonstrates its own habit and similar behaviour in the same location, encoded genetically and conditioned environmentally (Gooding et al., 1975; Hortynski, 1979; Shaw, 1989; Hortynski et al., 1994; Lopez-Medina et al., 2001; Shokaeva, 2007). When observing the fifteen genotypes that were present in both field trials where there was a possibility to examine plants of the same cultivars and lines in somewhat different conditions, one could see patterns of such behaviour (Shokaeva, 2005a). In one experiment, late spring frosts caused flower injuries to most genotypes, which were particularly harmful for cultivars with especially susceptible flowers, such as ‘Elsanta’, ‘Gariguette’, ‘Redgauntlet’ and ‘Tantallon’ (Shokaeva, 2002), while plants in the other study experienced practically no impact of negative temperatures during flowering and developed as appropriate. The loss in flowers in study 1 subsequently resulted in inevitable yield losses that turned out to be particularly considerable in cumulatively low-yielding genotypes (Shokaeva, 2005a). Such genotypes either produced misbalanced sets of the main yield components with distant ratios between them or had low component values, their sum and very low ratios within the two pairs. The cultivars and lines, typically high-yielding over the two first cropping seasons, had close ratios between the components, values of which were situated within the ranges of 1.1–1.6 each. They have been found to be possessed of the ability to compensate a considerable part of flower and yield losses in either first or second cropping year. Higher mean weights of fruit, produced by most genotypes in the first cropping year and by some genotypes in the second season in this study in comparison with study 2, have been evidence of compensative activity of the cultivars and lines. The parity of the absolute yield maxima in the studies has shown that the ratios ranging approximately from 1.2 to 1.5 in first year are most advantageous for strawberry growers, as genotypes having them are able to bring yield losses to a minimum, while this ability noticeably, although gradually, declined with ratios growing distant from the optima. This is the most logical and well founded explanation of that apparent peak on the surface that describes average yield dynamics depending on the relationships within the two pairs of yield components. One should add that some short-day cultivars in study 1, such as ‘Elsanta’, ‘Gariguette’, ‘Redgauntlet’ and ‘Tantallon’, having lost noticeable flower quantities in both years of fruiting because of spring frost impacts, which resulted in significantly lower yields compared with those in study 2 (Shokaeva, 2005a) and preliminary studies (Shokaeva, unpubl. data), revealed an ever bearing phenomenon (Shokaeva, 2002). The phenomenon manifested itself in producing solitary fruits in July and August. None of the low-yielding genotypes, which also experienced flower and yield losses like them, demonstrated such a repeated fruiting. It was observed only in the cultivars, the two ratios of which fell in the range of 1.0–1.6, being more or less close by value, and which produced high or at least relatively high yields over the two cropping years. Judging overall, this mechanism of yield loss compensation is likely to occur only in the genotypes that are high-yielding in favourable conditions. In study 2, differences between high- and low-yielding genotypes probably could have been less perceptible unless the thermal factor had had a substantial effect on plant branching. The analysis of plant development peculiarities in connection with sums of effective temperatures over the important periods of vegetation showed clear correlations between them (Shokaeva, 2005a). Plant establishment of early ripening, early to mid-season and mid-season genotypes, which turned out to be superior to that in the preceding study, was conditioned by warmer spring temperatures in the planting year, whereas June and July were unusually cool, much cooler than the same months in 1999, which was the main reason of under-
development of some mid-late and late-season cultivars and lines with a large vegetative sink and deeper dormancy of axillary buds. The latter had formed fewer branch crowns by the first cropping year, failed to develop branching in the next season to achieve plant structure as appropriate and, consequently, produced lower marketable yields cumulatively over the two cropping years. Only plants of ‘Senga Sengana’ and ‘Tenira’, despite maturing in lateseason terms, formed even more branch crowns in this trial compared with the previous study. Judging overall, dormancy of the axillary buds of the cultivars is easier to be broken, and branching of the plants was favoured by the very warm spring temperatures (Shokaeva, 2005a, 2006). The substantial loss in flowers, which occurred in experiment 1, and subsequent compensative efforts of plants resulted in development of larger berries in most cultivars and lines, particularly in the first cropping year (Shokaeva, 2005a). Conversely, absence of any serious frost impact during flowering in experiment 2 led to somewhat smaller on average marketable fruit produced by most genotypes studied. Additionally to this, the slightly higher sum of effective temperatures over the flower bud differentiation period in the year 2000 compared with that in 1999 was likely to contribute to initiation of bigger quantities of flower buds. However, the enhanced plant branching of the majority of early ripening and mid-season cultivars and lines in the planting year in study 2 was a probable guide to lower values of ratio 1, despite more inflorescences produced per plant, because some branch crowns were poorly developed. At the same time, fewer branch crowns in some mid-late and late-season genotypes with a large vegetative sink restricted initiation of inflorescences to markedly fewer ones per plant compared with study 1, which also conditioned lower values of ratio 1 (this explains why the maximum value of the index was noticeably lower in this study) and, along with it, much lower sums of the four main yield components. In the end plants were doomed to produce yields significantly inferior to those obtained from the same genotypes in the preceding study. Absence of genotypes with very high values of both ratios is easy to be explained. Numerous inflorescences per plant, in principle, are inconsistent with large marketable berries in the garden strawberry, particularly when plants form only a few branch crowns and flowers per truss, which is the very precondition of such an improbable combination. Plants that produce many trusses per branch crown develop medium-sized fruit in the best case. Even if the first berries are large, fruit following them grow smaller, and the difference in size may be huge. As a result, either ratio 2 turns out to be significantly lower than ratio 1, or such a genotype produces an extremely low marketable yield, numerous culls and, therefore, is of no value for commercial growing. All the results have been evidence that the two ratios between the components exhibit a certain degree of balance between them and are of great concern for resultant productivity of strawberry genotypes. The nearer values of the ratios to optima are the higher yield may be obtained over two first cropping years. Furthermore, judging by plant behaviour in different conditions, unfavourable temperatures, including late spring frosts, become more influential on cumulative yield with increasing misbalance between the components. This rather thoroughly elucidates why only a few genotypes, as a rule of thumb, having well-balanced sets of yield components, succeed to be steadily high-yielding unless plants are heavily injured. Low-yielding cultivars and lines almost always produce low yields. However, some cultivars which usually produce intermediate yields, from time to time happen to be rather productive (Shokaeva, unpubl. data). This means that environmental conditions in that particular season appeared to be
D.B. Shokaeva / Scientia Horticulturae 118 (2008) 14–19
more than ever favourable for the plants, which enabled them to produce a higher yield, or, in other words, this cultivar can be higher yielding in more favourable conditions, different from those where it is grown, which are likely not particularly suitable for it. The findings of this research may be to a great extent used for prediction of further plant behaviour and average yield as early as in the first cropping year. A method, based on them, has been developed at the All-Russian Research Institute of Horticultural Breeding (Shokaeva, 2004b). This, for instance, may be used for evaluation of seedlings, as a breeder often has a limited time to assess them, usually within a vegetative season. Measuring of the main yield components and calculation of the ratios between them allow obtaining additional estimates of such hybrids, which, along with yields obtained in the season of evaluation, could assist in selecting lines promising to be high-yielding cumulatively over main cropping years. It may be especially useful when first-year yield is not particularly high, which often occurs in the genotypes that produce significantly higher second-year yields and in the end demonstrate very high cumulative productivity over the two seasons. 5. Conclusion Average marketable yield over two first years of fruiting has been primarily influenced by interrelationship of four chief yield components in first cropping year, exhibiting particular dependence upon two ratios between them, i.e. inflorescence number per plant to branch crown number per plant (ratio 1) and mean fruit weight to flower number per inflorescence (ratio 2). When their values were close, and each ratio fell in the range from 1.0 to 1.6, the genotype could produce very high yield cumulatively. Higher ratio values within the ranges are characteristic of the genotypes top yielding in first cropping year, whereas a genotype with lower ratios may be expected to produce outstanding yield in second season. Such genotypes have been notable for high capabilities to compensate flower and yield losses. Both ratios falling in the middle of the ranges have been particularly advantageous, being a guide to the highest yields to be influenced by negative environmental factors, such as late spring frosts and lack of effective temperatures, least of all. Conversely, one or both ratios outside of the limits, as well as the ratios distant by value lead to significantly lower yields. The graph, describing average yield response to the ratios, has a peak, falling in the point of intersection of the most preferable values of the ratios, which was especially prominent when plants experienced flower losses because of late spring frosts in comparison with growing under favourable weather conditions. The surface, showing changing of a maximum value of average yields depending on the ratios, resembles a convex half-sphere which, however, declines more quickly with
19
increasing ratio 1, particularly in combination with low values of ratio 2. The findings have been of use to be employed in predicting of average yield during or after first cropping season, which could be especially useful for evaluation of seedlings. References Baumann, T.E., Eaton, G.W., Spaner, D., 1993. Yield components of day-neutral and short-day strawberry varieties on raised beds in British Columbia. HortScience 28, 891–894. Cross, J.V., Burgess, C.M., 1998. Strawberry fruit yield and quality responses to flower bud removal: a simulation of damage by strawberry blossom weevil (Anthonomus rubi). J. Hort. Sci. Biotechnol. 73, 676–680. Daugaard, H., 1999. The effect of flower removal on the yield and vegetative growth of A+ frigo plants of strawberry (Fragaria ananassa Duch). Sci. Hort. 82, 153– 157. Gooding, H.J., Jennings, D.L., Topham, P.B., 1975. A genotype—environment experiment on strawberries in Scotland. Heredity 34, 105–115. Guttridge, C.G., Anderson, H.M., 1973. The relationship between plant size and fruitfulness in strawberry in Scotland. Hort. Res. 13, 125–135. Hondelmann, W., 1965. Untersuchungen zur Ertragszu¨chtung bei der Gartenerdbeere (Fragaria ananassa Duch.). Pflanzenzu¨chtung 54, 46–60. Hortynski, J.A., 1979. Correlation and path analysis in strawberry seedlings (Fragaria ananassa Duch.). Genet. Polonica 20, 549–566. Hortynski, J.A., Liniewicz, K., Hulewicz, T., 1994. Influence of some atmospheric factors affecting yield and single fruit weight in strawberry. J. Hort. Sci. 69, 89– 95. Lacey, C.N.D., 1973. Phenotypic correlations between vegetative characters and yield components in strawberry. Euphytica 22, 546–554. Lopez-Medina, J., Vazquez, E., Medina, J.J., Dominguez, F., Lopez-Aranda, J.M., Bartual, R., Flores, F., 2001. Genotype environment interaction for planting date and plant density effects on yield characters of strawberry. J. Hort. Sci. Biotech. 76, 564–568. Shaw, D.V., 1989. Variation among heritability estimates for strawberries obtained by offspring-parent regression with relatives raised in separate environments. Euphytica 44, 157–162. Shokaeva, D.B., 2002. A consequent of late spring frosts impact on strawberry cultivars. Sadovodstvo I Vinogradarstvo 5, 11–12 (In Russian). Shokaeva, D., 2004a. Factors influencing marketable yield and berry size in shortday strawberry varieties in two fruiting seasons. J. Fruit. Ornam. Plant Res. 12, 159–166. Shokaeva, D.B., 2004b. A method of predicting of average yield in strawberry cultivars. RUS Patent No. 2228604 (In Russian). Shokaeva, D., 2005a. The influence of plant development peculiarities and environmental conditions on fruiting and yield height of differing short-day strawberry genotypes. In: Libek, A., Kaufmane, E., Sasnauskas, A. (Eds.), Environmentally Friendly Fruit Growing, 222. Fruit Science, pp. 117–123. Shokaeva, D.B., 2005b. About interdependency of the main productivity components in different strawberry cultivars. Selskokhozyaistvennaya Biologiya 5, 43–51 (In Russian, with English abstract). Shokaeva, D.B., 2006. Principles of fruiting of short-day strawberries. Cartouche, Orel. Shokaeva, D., 2007. Important features of strawberry genotypes and peculiarities of inheritance. Sodininkyste˙ ir darzˇininkyste˙ 26, 102–114. Strik, B.C., Proctor, J.T.A., 1988. Yield component analysis of strawberry genotypes differing in productivity. J. Am. Soc. Hort. Sci. 113, 124–129. Swartz, H.J., Popenoe, J., Fiola, J.A., 1985. Yield component analysis of the 1984 Maryland-USDA replicated trials. Adv. Strawberry Prod. 4, 45–52. Webb, R.A., Purves, J.V., White, B.A., Ellis, R., 1974. A critical path analysis of fruit production in strawberry. Sci. Hort. 2, 175–184.
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Relationships between yield components in first cropping year and average yield of short-day strawberries over two main seasons D.B. Shokaeva * All-Russian Research Institute of Horticultural Breeding, Zhilina 3-17, 302530 Orel, Russia
A R T I C L E I N F O
A B S T R A C T
Article history: Received 7 January 2008 Received in revised form 2 April 2008 Accepted 19 May 2008
Fruit productivity of the garden strawberry, Fragaria ananassa Duch., is a result of interrelationship of yield components contributing to it directly or indirectly. The main aim of the investigation was to find out whether there exists any general regularity, connecting relationships between main yield components in first cropping year to average yield of two main seasons. Two successive studies which primarily included 23 genotypes, differing in yield components and productivity, each, were planted in field conditions in spring 1999 and in spring 2000, respectively, and used for data collection to explore the material obtained in them. Four key yield components and average yields were measured in both cropping years, after which all possible ratios between the components were calculated to find out: first, the relationships to be influential on average yield of the two main seasons; second, type of the probable yield dependence upon the ratios; and, third, their values leading to high yields. Two ratios between the key yield components in first season, i.e.: inflorescence number per plant to branch crown number per plant, named ratio 1, and fruit weight (g) to flower count per inflorescence, named ratio 2, have been found to be related to average yield. An irregular surface, with a single peak falling approximately in its centre, describes average yield dependence upon the ratios. Values of the two ratios falling in the range of 1.0–1.6 each, provided that they are close, have enabled plants to produce high yields cumulatively over two first years. The paper highlights the most important differences in plant behaviour and yield dynamics of strawberry genotypes, depending on combinations of the ratios in first year, discerning those, which have been particularly advantageous to obtain very high yields, and are influenced by negative environmental factors least of all. Based on the findings, a method of predicting of average yield has been developed. Following this, usefulness of the method and possibilities of its using in strawberry breeding and variety trial are discussed. ß 2008 Elsevier B.V. All rights reserved.
Keywords: Fragaria ananassa Marketable yield Ratios between yield components
1. Introduction Yield of the cultivated strawberry, Fragaria ananassa Duch., like that of any other crop, is a cumulative result of various yield components influencing it directly or indirectly. Many plant characters and indices are of concern, however, when cultivars are grown as individual plants, particularly important yield components are: branch crown number per plant, inflorescence (truss) number per plant, flower (fruit) number per inflorescence and mean fruit weight. All the components except for the former contribute to yield directly. Branch crown number, although being not contributing to yield directly, is the key index of plant development, decisive for the other component characters and,
* Tel.: +7 4862 45 9235. E-mail address: [email protected]. 0304-4238/$ – see front matter ß 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.scienta.2008.05.021
consequently, for yield (Lacey, 1973; Webb et al., 1974; Baumann et al., 1993; Shokaeva, 2005a). These components have been reported to be intercorrelated, often negatively, and can interact compensatively (Swartz et al., 1985; Cross and Burgess, 1998; Daugaard, 1999; Shokaeva, 2006, pp. 68–76). Numerous studies using various cultivars were undertaken to explore correlations between yield and individual components and to determine their contribution to the-same-year yield in different locations. It has been found that yield is usually highly correlated with truss number per plant, while mean fruit weight and flower number per truss influence yield either weakly or indirectly, nevertheless all the components are very important (Hondelmann, 1965; Guttridge and Anderson, 1973; Lacey, 1973; Webb et al., 1974; Strik and Proctor, 1988; Baumann et al., 1993; Shokaeva, 2005b). The main aim of the research is to find out whether there is any general regularity, connecting relationships between main yield components in first cropping year to average yield of two main
D.B. Shokaeva / Scientia Horticulturae 118 (2008) 14–19
seasons. The intermediate objectives of the investigation are following: to measure the most important yield components in genotypes differing in productivity; to calculate ratios between them and to reveal those in first cropping year, which are influential on both first-year and average (of two first seasons of fruiting) yields; to find out whether there is any regular connection of the ratios to average yield; and, if there is, to trace the character of the probable relationship to make known the values of the ratios that may lead to high yields. 2. Material studied, methods and conditions of vegetative periods Two analogous field trials planted in spring 1999 and in spring 2000, respectively, which primarily included 23 strawberry genotypes each, were used to measure yield components and marketable yields during two full cropping seasons and to collect data needed. However, for some reasons two cultivars and one line were further excluded from the analysis of the data obtained in study 2. Fifteen genotypes (nine cultivars and six lines) were present in both experiments and, thus, estimated twice. These genotypes were: ‘Elsanta’, ‘Gariguette’, ‘Senga Sengana’, ‘Senga Tigaiga’, ‘Tago’, ‘Tantallon’, ‘Tenira’, ‘Toro’, ‘Zolushka of Kuban’, ‘Or 171-15-5’, ‘Or 913-7-140’, ‘Or 965-7-1’, ‘Or 967-5-29’, ‘Or 967-749’ and ‘Or 968-9-58’. Also, ‘Or 967-5-89’ was planted in both trials, but the data obtained in this line were omitted when analysing study 2. Additionally to them, the first trial included ‘Pandora’, ‘Redgauntlet’, ‘Vesnyanka’, ‘Voskhod’, ‘Vystavochnaya’, ‘Or 967-5-89’, ‘Or 975-12-62’ and ‘Or 968-8-94, while ‘Bylinnaya’, ‘Dukat’, ‘Elista’, ‘Saint Williams’, ‘Sudarushka’, ‘Yuzhanka’ and ‘Zenith’ were added to the second one. However, the data on ‘Bylinnaya’ and ‘Saint Williams’ have not been used in the research. As the investigation did not pursue the aim of estimation of individual strawberry genotypes, it did not matter, which genotypes would be used in it—cultivars or lines. A task of great concern was including patterns of cropping that could represent the existing diversity of the garden strawberries. The genotypes of choice were examined in preliminary studies, developed different habits, had different terms of fruit maturing and produced cumulative yields gradually ranging from very high to low. Additionally to that, three indices were taken into account: branch crown count per plant by first cropping year, inflorescence-tobranch crown ratio and flower count per plant. The genotypes with various combinations of the indices were available in the studies. One should say that from time to time several high-yielding cultivars and lines developed similar plant structure and had comparable indices, although they could vary and differentiate in different studies. As they are particularly important for fruit production, when it was possible and expedient, a couple of genotypes having similar indices were included. At the same time, a limited set of genotypes is able to represent the entire diversity only to a certain extent. To widen the representation, one genotype within each abovementioned couple, if they produced comparable yields, in experiment 2 was substituted for another, similar by traits and indices. Comparison of several genotypes with similar indices would allow answering the question whether a relation of the ratios to yield, which could be found in study 1, does exist, or the finding was occasional and happened thanks to the cultivar choice. Planting in different years could give the possibility to verify whether findings of the preceding study remained valid under somewhat different conditions or they were a matter of case, conditioned by the circumstances. At the same time, inclusion of the same genotypes in both studies and planting them in different years could allow tracing the influence of weather conditions on plant development and yield height. In addition, some combina-
15
tions of indices are rare, and the genotypes that develop such plant structures are problematic to be substituted. A fully randomized design with three complete sets of the genotypes was used in both trials. Each genotype was repeated once in each block, being represented with 30 plants planted on spaced beds. The distance between beds was 80 cm. Plants on a bed were spaced 25 cm apart. The arrangement resulted in a planting density of 50,000 plants ha 1. The blocks were equipped with sprinkler irrigation. Plants were deblossomed in the planting years; runners emerged during both planting year and first fruiting seasons were regularly removed. Data from experiment 1 were collected in 2000 and 2001, and those obtained in experiment 2—in 2001 and 2002. Branch crowns, trusses and flowers were counted for each replicate of each cultivar/line, using ten typical plants in succession. Thereafter, mean values of the yield components, i.e. branch crown number per plant, inflorescence number per plant, flower number per inflorescence and also mean fruit weight in g, were calculated for both first and second fruiting years. Fruit were harvested two times a week throughout fruiting periods. All marketable berries were counted and weighed at each harvest for each plot. First-year, second-year and average marketable yields (marketable fruit are berries not less than 18 mm wide in the maximum diameter) were computed in t per ha. Mean fruit weights and yields were computed for the whole plots. Using values of the yield components, all possible ratios between them were computed for each replicate of each genotype to search for their connection to yield. Also, absolute sum of these four components (irrespective of measure units) was calculated for each genotype to find out its minimum that would be high enough to enable plants to produce high cumulative yield over two seasons, as yield has been found to be correlated with the index (Shokaeva, 2004a). In view of the fact that environmental conditions influence plant growth and development, sum of effective temperatures (above +5 8C) during three important periods of vegetation, i.e. (1) period of plant growth, flowering and fruit growth (from the beginning of growth to the end of May), (2) period of fruiting and runnering (June and July), (3) flower bud differentiation period (from the beginning of August to the end of vegetation), and also over the whole vegetative seasons were calculated (Table 1). Late spring frosts occurred in 2000 and in 2001. In 2000, air temperature falls of up to 5.5 8C and 5.0 8C took place on 8 May and 15 May, respectively. In 2001, late spring frosts happened on 9, 16 and 22 May ( 2.0 8C). Conditions of overwintering were favourable in all the winter seasons, and practically no freezeinduced injuries to plants were observed after them. In general, the Central Russia’s summer is rather hot and dry, while autumn seasons are usually short and cool. Statistical analyses have been performed using Methods of SAS Institute (USA, 1989). Duncan’s test has been used for determination of LSD between means at P = 0.05. Graphs representing average and maximum yield responses to two coefficients of
Table 1 Sums of effective temperatures (above +5 8C) over three important periods of vegetative seasons and over the whole seasons in the years of studying (1999– 2002) Period of plant development
Year 1999
Plant growth, flowering and fruit growth Fruit maturing and runnering Flower bud differentiation Whole vegetative season
2000
2001
2002
356.5
387.8
344.4
205.1
934.5 627.7 1918.7
747.8 667.5 1803.1
782.3 642.3 1769.0
858.2 – 2171.0
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D.B. Shokaeva / Scientia Horticulturae 118 (2008) 14–19
Table 2 Ranges of the mean values of: four main yield components in first cropping year depending on genotype, two ratios between them, first-year, second-year and average yields in study 1 (2000–2001) Yield components and indices
Range
LSD05
(1) Branch crown number per plant (2) Inflorescence number per plant (3) Flower number per inflorescence (4) Fruit weight (g) Ratio 1 (2:1) Ratio 2 (4:3) First-year marketable yield (t per ha) Second-year marketable yield (t per ha) Average marketable yield (t per ha)
2.1–4.8 2.2–6.9 5.3–12.0 5.4–12.4 0.96–1.83 0.98–1.81 4.5–14.3 7.3–23.7 6.7–16.9
1.1 1.4 3.1 2.3 0.16 0.20 3.1 4.2 2.6
relationships between yield components have been performed using Axum 5.0 Software (MathSoft, Inc., USA, 1996). 3. Results The weather conditions of the planting year vegetative period in study 1 favoured growth and development of ‘maiden’ plants. However, in both first and second cropping years, late spring frosts caused injuries to flowers, particularly heavy in 2000, when all the genotypes except for the late-season ones experienced serious flower losses (data not shown). The most vulnerable flowers of ‘Redgauntlet’, ‘Elsanta’, ‘Gariguette’, ‘Tantallon’ and some others were injured rather severely in both seasons. The cultivars and lines studied significantly differed by the main yield components. Their values in the first cropping season represented different levels, gradually ranging from rather low to high (Table 2). All possible ratios between the components were calculated for each cultivar/line to distinguish the most important ones connected to yield, and to establish particularly favourable combinations of ratio values, on which top first-year, second-year and average of the two years yields could be based. Computation of average yields and exploration of their reference to the ratios between yield components which were measured and recorded in the first year of fruiting, have led to the finding that only two ratios appeared to be important and influential on average marketable yield: inflorescence number per plant to branch crown number per plant (2:1) and mean fruit weight to flower number per inflorescence (4:3). Ranges of the values found for these ratios, designated as ratio 1 and ratio 2, respectively, turned out to be similar (Table 2). Sum of the four components was not less than 24.5 for all the genotypes, reaching the maximum of 30.9. Correlation analysis revealed existence of a highly significant correlation between average yield and sum of the four components calculated for the first year (r = 0.68 at P 0.01). However, it was found that the two ratios between the two pairs of the components played an evidently more important role in cumulative (average) yield compared with the components themselves and their sum. The cultivars and lines that had close sum values, but different ratios might produce yields which were greatly different from each other, and vice versa. At the same time, the values of the ratios that led to high yields in the first year of fruiting were different from those that allowed achievement of high cumulative yields over the two first seasons. Top yields in the first year were obtained when either both ratios had relatively high values (more than 1.3), or one ratio (the first one) had a very high value, while the other was comparatively low (data not shown). Combinations of the ratios that were a guide to high average (cumulative) marketable yields noticeably varied, being at the same time rather specific. Genotypes with values of both ratios falling in the range from 1.1 to 1.6, had advantages over the others (Fig. 1). Although the
Fig. 1. Average (of two first years) yield response to two ratios between two pairs of main yield components measured in first fruiting year (data collected in 2000– 2001); the ratios are: 2:1—inflorescence number per plant to branch crown number per plant, 4:3—mean fruit weight (g) to flower count per inflorescence.
values did not ensure a top yield in any cultivar/line that had them, they were an indispensable condition of high two-year commercial productivity. Furthermore, the highest yield levels were characteristic of the genotypes that had approximately equal or at least relatively close values of both coefficients. The absolute maximum belonged to ‘Or 965-7-1’ the two ratios of which were 1.38 and 1.31, respectively, while sum of the main components amounted to 26.2. The genotypes that showed any ratio outside of the limits mentioned above produced lower yields on average. Very low values of both ratios in the first year, as well as any combination of values, where one of them was very high, whereas the other was very low (especially the second one), led to particularly low cumulative yields. Combinations of very high values of both ratios were absent. Lower values within the optimum ranges were distinctive of the genotypes that produced much higher marketable yields in the second-year compared to the first season. None of the genotypes studied belonged to the top-yielding groups in both years of fruiting. The same components were also measured in the second cropping season. Ratios between them varied much more extensively than those in the first year, and had a clearly weaker relation to yield, although the highest yields were also obtained when the two coefficients were not too low and the difference between them not particularly substantial (data not shown). The vegetative seasons during studying in experiment 2 seemed to be more favourable than those in the preceding study. The late spring frosts that happened in 2001 caused almost no injury to flowers, because plants of early to mid-season genotypes flowered 1–2 weeks earlier compared with the same two-year cultivars and lines in study 1, and the first frost impact happened when flowering of most mid-season genotypes was progressing to finish. Thus, the plants avoided significant flower losses, while most midlate and all the late-season genotypes began full flowering after the frosts passed. In spring 2002 no temperature falls below 0 8C occurred. In this experiment, plants of most cultivars and lines ripening in early to mid-season terms had formed by the first cropping year somewhat more branch crowns per plant compared with the same genotypes in study 1. For instance, plants of ‘Gariguette’ developed 4.2 vs. 2.6 branch crowns per plant in the previous study, ‘Tantallon’ produced 3.6 vs. 3.1 branch crowns, ‘Or 965-7-1’ and ‘Or 967-7-49’ had 5.3 vs. 3.9 and 4.0 vs. 3.4 branch crowns, respectively. Conversely, some mid-late and late-season genotypes, especially those with a large vegetative sink in first cropping year, developed noticeably fewer branch crowns: ‘Elsanta’
D.B. Shokaeva / Scientia Horticulturae 118 (2008) 14–19
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Table 3 Ranges of the mean values of: four main yield components in first cropping year depending on genotype, two ratios between them, first-year, second-year and average yields in study 2 (2001–2002) Yield components and indices
Range
LSD05
(1) Branch crown number per plant (2) Inflorescence number per plant (3) Flower number per inflorescence (4) Fruit weight (g) Ratio 1 (2:1) Ratio 2 (4:3) First-year marketable yield (t per ha) Second-year marketable yield (t per ha) Average marketable yield (t per ha)
2.0–6.2 2.1–9.0 6.0–10.3 5.8–11.4 0.91–1.59 0.86–1.87 4.1–15.3 7.8–24.5 7.0–16.8
1.0 1.2 1.9 2.1 0.14 0.21 1.3 1.5 1.3
produced only 2.1 vs. 2.4 branch crowns formed a year earlier in the first trial, ‘Or 171-15-5’ did 3.3 vs. 4.1 branch crowns, ‘Or 9675-29’ and ‘Or 968-9-58’ formed 3.1 vs. 3.8 and 2.1 vs. 2.6 branch crowns per plant, respectively. Establishment of ‘Bylinnaya’ (1.3 branch crowns), ‘Saint Williams’ (1.6 branch crowns) and ‘Or 9675-89’ (1.5 branch crowns) in the study was particularly poor. It subsequently resulted in extremely low both sums of the main yield components (they even have not reached 18.0) and cumulative yields (lower than 5.5 t per ha), which fell out of the set and looked inconsistent with the term ‘cultivar’. The data obtained using the genotypes were afterwards excluded from analysis to equalize the minimum indices in both studies, first of all yield minima. In consequence of this values of the main components in the first season ranged in this experiment to some extent differently compared with those in the study planted in 1999 (Table 3). This resulted in a narrower range of ratio 1, while ratio 2, conversely, ranged slightly broader. However, the genotypes, which were included in this trial repeatedly, had both component and ratio values comparable with those in the first study, or not particularly different from them. The principal differences that took place in study 2 were following: first, somewhat smaller fruit produced by most early to mid-season cultivars and lines and, second, more (in early to mid-season and some mid-late genotypes) or fewer (in mid-late and late-season genotypes) branch crowns and inflorescences per plant. The maximum value of flower number per inflorescence was lower in study 2, which could be to some extent connected with absence of ‘Or 975-12-62’. The highest mean value of the index in the preceding study distinguished this mid-season line. However, most early and mid-season genotypes initiated fewer flowers per truss in study 2. Sum of the four components varied from 20.4 to 30.5 depending on genotype, whereas its minimum value in the first study was 24.5. Average yield was correlated with the sum approximately as strongly as in study 1 (r = 0.73 at P 0.01). In this study, nine of 15 genotypes that were present in both trials produced higher average yields. The differences were particularly apparent in ‘Elsanta’ that produced 14.1 vs. 12.9 t per ha in the previous study, ‘Senga Sengana’ (12.8 vs. 9.8 t per ha), ‘Tantallon’ (14.3 vs. 10.8 t per ha), ‘Zolushka of Kuban’ (13.5 vs. 11.9 t per ha) and ‘Or 171-15-5’ (14.5 vs. 12.0 t per ha). Maximum yield values at most combinations of the ratios between components were higher than in study 1, sometimes by 2.5– 3.0 t per ha, but the absolute maximum was approximately the same, and belonged to the same line (Table 3). However, the peak on a response surface could not have been as prominent as that in study 1. A number of cultivars and one line, having different combinations of ratios, produced yields nearly reaching the maximum value. ‘Dukat’ plants of which were characterized with the ratios of 1.22 and 1.29, respectively, produced 15.5 t fruit -
Fig. 2. Maximum (average of two years) yield response to two ratios between main yield components measured in first fruiting year (data collected in 2001–2002); the ratios are: 2:1—inflorescence number per plant to branch crown number per plant, 4:3—mean fruit weight (g) to flower count per inflorescence.
per ha. The average yield of ‘Elsanta’ that had the ratios 1.08 and 1.04, was 15.1 t per ha. Two replicates of ‘Senga Tigaiga’ (the indices were 1.33, 1.31 and 15.3 t per ha for the first one and 1.35, 1.29 and 16.0 t per ha for the second one), ‘Tantallon’ (1.59, 1.56 and 15.5 t per ha) and ‘Or 171-15-5’ (the indices were 1.29, 1.56 and 15.5 t per ha on average) were also among those high-yielding genotypes. However, drawing of a graph, similar to that obtained using the data collected in study 1, turned out to be complicated because of lack of data in the area of high values of the ratios between components, particularly of ratio 1. Plants of early ripening and mid-season genotypes produced more both branch crowns and trusses, but truss numbers per branch crown in most cases turned out to be lower. Also, there was a gap in the area of relatively low values of ratio 1, as the cultivars/lines with a large vegetative sink produced fewer branch crowns and particularly inflorescences per plant compared with usual because of cool June temperatures in the year 2000. Additionally to that, most genotypes with low ratios had low sums of the components, which made them beyond compare with the genotypes that had high sums at the same ratio values in study 1. In this experiment where there were no harmful impacts of late spring frosts, average yields exceeding 15.0 t per ha occurred only in the genotypes with sum values varying within the range of 24.4–29.1, provided that the two ratios between components were close by value and ranged from 1.0 to 1.6 each like those in study 1 (Fig. 2). The response surface, reflecting changing of a maximum value of average yield depending on the ratios, resembled a convex halfsphere. However, the maximum value declined more quickly with increasing of ratio 1, particularly in combination with low values of ratio 2. In this study, increasing of the latter index, as well as decreasing of both ratios, beginning from the limits of the optimum area that still could ensure top yields, up- and downwards, respectively, led to more gradual yield decreasing compared with its dynamics in the preceding study. 4. Discussion Researchers, working with strawberry cultivars in different conditions, have occasionally observed rank reversals in yield height in second cropping year in comparison with first season (Hondelmann, 1965; Baumann et al., 1993; Shokaeva, 2005b). The results, obtained in the two studies where none of the cultivars and lines belonged to the group of top-yielding genotypes in both seasons, have been fully consistent with the findings reported by the authors, and proved the peculiarity of cropping, distinctive of
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the crop. Any strawberry genotype usually demonstrates its own habit and similar behaviour in the same location, encoded genetically and conditioned environmentally (Gooding et al., 1975; Hortynski, 1979; Shaw, 1989; Hortynski et al., 1994; Lopez-Medina et al., 2001; Shokaeva, 2007). When observing the fifteen genotypes that were present in both field trials where there was a possibility to examine plants of the same cultivars and lines in somewhat different conditions, one could see patterns of such behaviour (Shokaeva, 2005a). In one experiment, late spring frosts caused flower injuries to most genotypes, which were particularly harmful for cultivars with especially susceptible flowers, such as ‘Elsanta’, ‘Gariguette’, ‘Redgauntlet’ and ‘Tantallon’ (Shokaeva, 2002), while plants in the other study experienced practically no impact of negative temperatures during flowering and developed as appropriate. The loss in flowers in study 1 subsequently resulted in inevitable yield losses that turned out to be particularly considerable in cumulatively low-yielding genotypes (Shokaeva, 2005a). Such genotypes either produced misbalanced sets of the main yield components with distant ratios between them or had low component values, their sum and very low ratios within the two pairs. The cultivars and lines, typically high-yielding over the two first cropping seasons, had close ratios between the components, values of which were situated within the ranges of 1.1–1.6 each. They have been found to be possessed of the ability to compensate a considerable part of flower and yield losses in either first or second cropping year. Higher mean weights of fruit, produced by most genotypes in the first cropping year and by some genotypes in the second season in this study in comparison with study 2, have been evidence of compensative activity of the cultivars and lines. The parity of the absolute yield maxima in the studies has shown that the ratios ranging approximately from 1.2 to 1.5 in first year are most advantageous for strawberry growers, as genotypes having them are able to bring yield losses to a minimum, while this ability noticeably, although gradually, declined with ratios growing distant from the optima. This is the most logical and well founded explanation of that apparent peak on the surface that describes average yield dynamics depending on the relationships within the two pairs of yield components. One should add that some short-day cultivars in study 1, such as ‘Elsanta’, ‘Gariguette’, ‘Redgauntlet’ and ‘Tantallon’, having lost noticeable flower quantities in both years of fruiting because of spring frost impacts, which resulted in significantly lower yields compared with those in study 2 (Shokaeva, 2005a) and preliminary studies (Shokaeva, unpubl. data), revealed an ever bearing phenomenon (Shokaeva, 2002). The phenomenon manifested itself in producing solitary fruits in July and August. None of the low-yielding genotypes, which also experienced flower and yield losses like them, demonstrated such a repeated fruiting. It was observed only in the cultivars, the two ratios of which fell in the range of 1.0–1.6, being more or less close by value, and which produced high or at least relatively high yields over the two cropping years. Judging overall, this mechanism of yield loss compensation is likely to occur only in the genotypes that are high-yielding in favourable conditions. In study 2, differences between high- and low-yielding genotypes probably could have been less perceptible unless the thermal factor had had a substantial effect on plant branching. The analysis of plant development peculiarities in connection with sums of effective temperatures over the important periods of vegetation showed clear correlations between them (Shokaeva, 2005a). Plant establishment of early ripening, early to mid-season and mid-season genotypes, which turned out to be superior to that in the preceding study, was conditioned by warmer spring temperatures in the planting year, whereas June and July were unusually cool, much cooler than the same months in 1999, which was the main reason of under-
development of some mid-late and late-season cultivars and lines with a large vegetative sink and deeper dormancy of axillary buds. The latter had formed fewer branch crowns by the first cropping year, failed to develop branching in the next season to achieve plant structure as appropriate and, consequently, produced lower marketable yields cumulatively over the two cropping years. Only plants of ‘Senga Sengana’ and ‘Tenira’, despite maturing in lateseason terms, formed even more branch crowns in this trial compared with the previous study. Judging overall, dormancy of the axillary buds of the cultivars is easier to be broken, and branching of the plants was favoured by the very warm spring temperatures (Shokaeva, 2005a, 2006). The substantial loss in flowers, which occurred in experiment 1, and subsequent compensative efforts of plants resulted in development of larger berries in most cultivars and lines, particularly in the first cropping year (Shokaeva, 2005a). Conversely, absence of any serious frost impact during flowering in experiment 2 led to somewhat smaller on average marketable fruit produced by most genotypes studied. Additionally to this, the slightly higher sum of effective temperatures over the flower bud differentiation period in the year 2000 compared with that in 1999 was likely to contribute to initiation of bigger quantities of flower buds. However, the enhanced plant branching of the majority of early ripening and mid-season cultivars and lines in the planting year in study 2 was a probable guide to lower values of ratio 1, despite more inflorescences produced per plant, because some branch crowns were poorly developed. At the same time, fewer branch crowns in some mid-late and late-season genotypes with a large vegetative sink restricted initiation of inflorescences to markedly fewer ones per plant compared with study 1, which also conditioned lower values of ratio 1 (this explains why the maximum value of the index was noticeably lower in this study) and, along with it, much lower sums of the four main yield components. In the end plants were doomed to produce yields significantly inferior to those obtained from the same genotypes in the preceding study. Absence of genotypes with very high values of both ratios is easy to be explained. Numerous inflorescences per plant, in principle, are inconsistent with large marketable berries in the garden strawberry, particularly when plants form only a few branch crowns and flowers per truss, which is the very precondition of such an improbable combination. Plants that produce many trusses per branch crown develop medium-sized fruit in the best case. Even if the first berries are large, fruit following them grow smaller, and the difference in size may be huge. As a result, either ratio 2 turns out to be significantly lower than ratio 1, or such a genotype produces an extremely low marketable yield, numerous culls and, therefore, is of no value for commercial growing. All the results have been evidence that the two ratios between the components exhibit a certain degree of balance between them and are of great concern for resultant productivity of strawberry genotypes. The nearer values of the ratios to optima are the higher yield may be obtained over two first cropping years. Furthermore, judging by plant behaviour in different conditions, unfavourable temperatures, including late spring frosts, become more influential on cumulative yield with increasing misbalance between the components. This rather thoroughly elucidates why only a few genotypes, as a rule of thumb, having well-balanced sets of yield components, succeed to be steadily high-yielding unless plants are heavily injured. Low-yielding cultivars and lines almost always produce low yields. However, some cultivars which usually produce intermediate yields, from time to time happen to be rather productive (Shokaeva, unpubl. data). This means that environmental conditions in that particular season appeared to be
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more than ever favourable for the plants, which enabled them to produce a higher yield, or, in other words, this cultivar can be higher yielding in more favourable conditions, different from those where it is grown, which are likely not particularly suitable for it. The findings of this research may be to a great extent used for prediction of further plant behaviour and average yield as early as in the first cropping year. A method, based on them, has been developed at the All-Russian Research Institute of Horticultural Breeding (Shokaeva, 2004b). This, for instance, may be used for evaluation of seedlings, as a breeder often has a limited time to assess them, usually within a vegetative season. Measuring of the main yield components and calculation of the ratios between them allow obtaining additional estimates of such hybrids, which, along with yields obtained in the season of evaluation, could assist in selecting lines promising to be high-yielding cumulatively over main cropping years. It may be especially useful when first-year yield is not particularly high, which often occurs in the genotypes that produce significantly higher second-year yields and in the end demonstrate very high cumulative productivity over the two seasons. 5. Conclusion Average marketable yield over two first years of fruiting has been primarily influenced by interrelationship of four chief yield components in first cropping year, exhibiting particular dependence upon two ratios between them, i.e. inflorescence number per plant to branch crown number per plant (ratio 1) and mean fruit weight to flower number per inflorescence (ratio 2). When their values were close, and each ratio fell in the range from 1.0 to 1.6, the genotype could produce very high yield cumulatively. Higher ratio values within the ranges are characteristic of the genotypes top yielding in first cropping year, whereas a genotype with lower ratios may be expected to produce outstanding yield in second season. Such genotypes have been notable for high capabilities to compensate flower and yield losses. Both ratios falling in the middle of the ranges have been particularly advantageous, being a guide to the highest yields to be influenced by negative environmental factors, such as late spring frosts and lack of effective temperatures, least of all. Conversely, one or both ratios outside of the limits, as well as the ratios distant by value lead to significantly lower yields. The graph, describing average yield response to the ratios, has a peak, falling in the point of intersection of the most preferable values of the ratios, which was especially prominent when plants experienced flower losses because of late spring frosts in comparison with growing under favourable weather conditions. The surface, showing changing of a maximum value of average yields depending on the ratios, resembles a convex half-sphere which, however, declines more quickly with
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increasing ratio 1, particularly in combination with low values of ratio 2. The findings have been of use to be employed in predicting of average yield during or after first cropping season, which could be especially useful for evaluation of seedlings. References Baumann, T.E., Eaton, G.W., Spaner, D., 1993. Yield components of day-neutral and short-day strawberry varieties on raised beds in British Columbia. HortScience 28, 891–894. Cross, J.V., Burgess, C.M., 1998. Strawberry fruit yield and quality responses to flower bud removal: a simulation of damage by strawberry blossom weevil (Anthonomus rubi). J. Hort. Sci. Biotechnol. 73, 676–680. Daugaard, H., 1999. The effect of flower removal on the yield and vegetative growth of A+ frigo plants of strawberry (Fragaria ananassa Duch). Sci. Hort. 82, 153– 157. Gooding, H.J., Jennings, D.L., Topham, P.B., 1975. A genotype—environment experiment on strawberries in Scotland. Heredity 34, 105–115. Guttridge, C.G., Anderson, H.M., 1973. The relationship between plant size and fruitfulness in strawberry in Scotland. Hort. Res. 13, 125–135. Hondelmann, W., 1965. Untersuchungen zur Ertragszu¨chtung bei der Gartenerdbeere (Fragaria ananassa Duch.). Pflanzenzu¨chtung 54, 46–60. Hortynski, J.A., 1979. Correlation and path analysis in strawberry seedlings (Fragaria ananassa Duch.). Genet. Polonica 20, 549–566. Hortynski, J.A., Liniewicz, K., Hulewicz, T., 1994. Influence of some atmospheric factors affecting yield and single fruit weight in strawberry. J. Hort. Sci. 69, 89– 95. Lacey, C.N.D., 1973. Phenotypic correlations between vegetative characters and yield components in strawberry. Euphytica 22, 546–554. Lopez-Medina, J., Vazquez, E., Medina, J.J., Dominguez, F., Lopez-Aranda, J.M., Bartual, R., Flores, F., 2001. Genotype environment interaction for planting date and plant density effects on yield characters of strawberry. J. Hort. Sci. Biotech. 76, 564–568. Shaw, D.V., 1989. Variation among heritability estimates for strawberries obtained by offspring-parent regression with relatives raised in separate environments. Euphytica 44, 157–162. Shokaeva, D.B., 2002. A consequent of late spring frosts impact on strawberry cultivars. Sadovodstvo I Vinogradarstvo 5, 11–12 (In Russian). Shokaeva, D., 2004a. Factors influencing marketable yield and berry size in shortday strawberry varieties in two fruiting seasons. J. Fruit. Ornam. Plant Res. 12, 159–166. Shokaeva, D.B., 2004b. A method of predicting of average yield in strawberry cultivars. RUS Patent No. 2228604 (In Russian). Shokaeva, D., 2005a. The influence of plant development peculiarities and environmental conditions on fruiting and yield height of differing short-day strawberry genotypes. In: Libek, A., Kaufmane, E., Sasnauskas, A. (Eds.), Environmentally Friendly Fruit Growing, 222. Fruit Science, pp. 117–123. Shokaeva, D.B., 2005b. About interdependency of the main productivity components in different strawberry cultivars. Selskokhozyaistvennaya Biologiya 5, 43–51 (In Russian, with English abstract). Shokaeva, D.B., 2006. Principles of fruiting of short-day strawberries. Cartouche, Orel. Shokaeva, D., 2007. Important features of strawberry genotypes and peculiarities of inheritance. Sodininkyste˙ ir darzˇininkyste˙ 26, 102–114. Strik, B.C., Proctor, J.T.A., 1988. Yield component analysis of strawberry genotypes differing in productivity. J. Am. Soc. Hort. Sci. 113, 124–129. Swartz, H.J., Popenoe, J., Fiola, J.A., 1985. Yield component analysis of the 1984 Maryland-USDA replicated trials. Adv. Strawberry Prod. 4, 45–52. Webb, R.A., Purves, J.V., White, B.A., Ellis, R., 1974. A critical path analysis of fruit production in strawberry. Sci. Hort. 2, 175–184.