Next Article in Journal
Ecological and Geographical Structure of the Plant Cover of the East Asian Boreal–Nemoral Ecotone (the Lower Amur Region, Far East Russia)
Next Article in Special Issue
Fingerprinting of Plum (Prunus domestica) Genotypes in Lithuania Using SSR Markers
Previous Article in Journal
Molecular Characterization and Efficacy Evaluation of Transgenic Maize Harboring cry2Ab-vip3A-cp4epsps for Insect Resistance and Herbicide Tolerance
Previous Article in Special Issue
Habitat Characteristics and Mineral Nutrition Status of Rubus chamaemorus L. in Latvia
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Plants
Volume 12
Issue 3
10.3390/plants12030614
plants-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Performance of Sweet Cherry Cultivars and Advanced Selections on Gisela 5 Rootstock in Young Orchards

by
Juozas Lanauskas
1,*,
Darius Kviklys
1,2,
Nobertas Uselis
1 and
Vidmantas Stanys
1
1
Institute of Horticulture, Lithuanian Research Centre for Agriculture and Forestry, Kauno Str. 30, LT-54333 Kaunas, Lithuania
2
Department of Horticulture, Norwegian Institute of Bioeconomy Research—NIBIO Ullensvang, Ullensvangvegen 1005, NO-5781 Lofthus, Norway
*
Author to whom correspondence should be addressed.
Plants 2023, 12(3), 614; https://doi.org/10.3390/plants12030614
Submission received: 19 December 2022 / Revised: 13 January 2023 / Accepted: 27 January 2023 / Published: 30 January 2023
(This article belongs to the Special Issue Selected Papers from the 3rd International Conference on Scientific Actualities and Innovations in Horticulture (SAIH2022))
Browse Figure
Review Reports Versions Notes

Abstract

:
Six sweet cherry cultivars and two advanced selections of Gisela 5 rootstock were tested in 2015–2021 at the Institute of Horticulture, Lithuanian Research Centre for Agriculture and Forestry. Fruit trees were planted at distances of 4.5 × 2.5 m and trained as spindles. Orchard floor management included frequently mown grass in alleyways with herbicide strips along tree rows. Cultivars ‘Mindaugė’ and ‘Irema BS’ were the most vigorous at the end of the seventh leaf. Their trunk diameter achieved 11.6 cm. The ‘Merchant’ cultivar had the smallest trunk diameter—9.3 cm. The average yield in 2018–2021 ranged from 2.75 t/ha for ‘Vega’ to 8.73 t/ha for ‘Regina’. Cultivars ‘Regina’, ‘Sunburst’, ‘Irema BS’ and ‘Merchant’ had the highest cumulative yield efficiency of 0.440–0.503 kg/cm2 with respect to the trunk cross-section area (TCSA). The least productive cultivar ‘Vega’ produced fruits of the highest average weight—9.9 g. Fruits of ‘Regina’ and ‘Sunburst’ were large as well—8.8–9.1 g. ‘Irema BS’ fruits had the highest soluble solids content (SSC)—20.2%. The lowest SSC was recorded in ‘Merchant’ and ‘Sunburst’ fruits—14.7–15.8%. The yield of advanced selection, No. 102, equaled to the yield of cv. ‘Regina’. No. 102 had a high fruit weight, and fruits were distinguished by attractiveness and taste.

1. Introduction

Global sweet cherry production exhibited slight increasing tendencies in recent years [1] and reached about 2.5 million tons per year [2]. Northeastern European countries are far from being the top producers of sweet cherries. In Lithuania, cherry orchards comprise only about 4% of the total plot under fruit and berry plants [3]. Sweet cherry is mainly grown by amateur growers, and they are very rarely planted in commercial orchards. Growing sweet cherry is more complicated in more severe climatic conditions. Low winter temperatures may damage flower buds or the entire fruit tree [4,5]. Recently, winters have become milder due to climate change, but fluctuations in temperatures create other challenges for fruit trees. Spring frosts also introduce a particular risk for early blooming sweet cherry trees [6].
In northern regions, the selection of optimal sites for orchard establishment and proper cultivar choice is crucial for successful sweet cherry growing. In Norway, sweet cherries can be grown up to 60° N latitude in areas with suitable local climatic conditions [7]. Lithuania is located between 53.53° and 56.27° N latitudes and has a coastline with the Baltic Sea, which softens winters mainly in the coastal area. For successful fruit production, sites of higher locations and with more favorable microclimates are also significant [8].
The focus of breeding new sweet cherry cultivars is on fruit quality, high and stable fruit set and tolerance to biotic and abiotic stress [9]. Recently, the weight of fruits available on the market reached 10 grams or more [10]. The fruit market has become global, but fruit growers face various challenges related to the specifics of a particular area. Fruit tree winter hardiness and tolerance to spring frost are of great importance in northern climates. Eighteen cultivars of sweet cherries were created in Lithuania from 1986 to 2022 [11]. The fruit weight of the first Lithuanian cultivars is 4–5.5 g [12,13] and does not meet the expectations of modern markets. Thus, efforts are being made to breed cultivars with large, tasty fruits during different ripening times [14]. Newly developed cultivars such as ‘Germa’, ‘Lukė’, ‘Irema BS’, ‘Pagunda’ and some others are characterized by better fruit quality indicators and sufficiently good adaptability to local climatic conditions [11]. Sweet cherry breeding programs are also being developed in Latvia and Estonia—countries located to the north of Lithuania [15,16]. Breeding and cultivar evaluation is a routine process in expanding the knowledge and capabilities of sweet cherry growing [17,18,19,20]. Cultivars originated in neighboring countries, Western and South Europe, USA, Canada, Ukraine and Russia are mainly found in Lithuanian orchards. Promising cultivars for testing usually are selected based on the experience of other researchers or personal observations.
Vigorous trees on Prunus mahaleb L. and P. avium L. seedlings are still used in sweet cherry production in Lithuania [21]. It is appropriate to conduct research with dwarf fruit trees used in modern orchards [22]. Gisela 5 usually meets these requirements [23,24,25]. It also proved to be suitable as growth limiting and yield-efficient rootstock in northern conditions [26,27,28]. Gisela series rootstocks are highly adaptable and can be found globally [29]. There is information that Gisela 5 rootstock in northern regions performs even better than in southern ones [30].
The study aims to investigate the main characteristics of fruit tree growth, productivity and fruit quality of sweet cherry cultivars and advanced selections grafted on dwarf rootstock Gisela 5.

2. Results

According to sweet cherry trunk diameters after 7 years of growth, ‘Mindaugė’ and ‘Vega’, also No. 102, were the most vigorous cultivars (Figure 1). Cv. ‘Merchant’ and No. 6 exhibited the weakest growth.
Sweet cherry trees began to flower in the second year after planting. The most abundant flowering was recorded for cv. ‘Regina’, and the lowest was recorded for ‘Irema BS’ with (Table 1). The fruit trees flowered less in the third leaf, but ‘Regina’ remained the most abundant flowering cultivar. Since 2018, flowering has become more abundant and stable. In different years, the cultivars that bloomed the most were ‘Regina’, ‘Sunburst’, ‘Mindaugė’, ‘Irema BS’, and No. 6. Fruit trees bloomed in 2020 in a particularly abundant manner. In the following year, the fruit trees of most cultivars bloomed less, especially ‘Vega’, due to unfavorable weather conditions during winter and early spring (Table 1). Low temperatures damaged flowers or even flower buds. The ‘Vega’ cultivar and ‘Sunburst’ and ‘Merchant’ were the most affected. (Table 2). Cvs. ‘Regina’, ‘Irema BS’ and No. 6 exhibited the best flower survival.
In the first two years, the yield was very low and was not recorded. From the fourth year onwards, the yield was determined. In 2018, ‘Mindaugė’ fruit trees were the most productive, and ‘Merchant’ trees were the least productive (Table 3). The latter cultivar produced the most abundant yield in the next year, while ‘Regina’ produced the lowest yield. In the sixth leaf (2020), ‘Regina’ and No. 102 produced the highest yields, and ‘Vega’ produced the lowest. The year 2020 was characterized by the most abundant harvest during the entire period of research. ‘Irema BS’ was the most productive, and ‘Vega’ produced the lowest yield. However, the average yield was about twice lower in the next year. On average, cvs. ‘Regina’, ‘Irema BS’, and No. 102 produced the highest average yield during the study period, and ‘Vega’ was the least productive.
There were no statistical differences in yield efficiency among cultivars in 2018 (Table 4). Cv. ‘Merchant’ was the most, and ‘Regina’ exhibited the least yield efficient in 2019. In 2020, when the highest yield was recorded, the yield efficiency of most tested cultivars was similar—0.206–0.261 kg/cm2. ‘Regina’ showed the highest yield efficiency, and ‘Vega’ and ‘Mindaugė’ showed the lowest. The latter cultivar was the most yield-efficient in the last year of the experiment. ‘Vega’ fruit trees grew vigorously, produced a small yield and had the lowest cumulative yield efficiency. Cv. ‘Regina’ trees were the most yield-efficient followed by ‘Sunburst’, ‘Irema BS’ and ‘Merchant’.
Average fruit weight varied among cultivars and within the years. Fruits of cv. ‘Regina’ had the highest weight during the first harvest (Table 5), while fruits of ‘Mindaugė’ and ‘Irema BS’ were the smallest. From the second harvest onwards, cv. ‘Vega’ had the largest fruits. ‘Irema BS’ fruits in 2021 were the smallest during the study. According to the average data, the smallest fruits had Lithuanian cultivars and advanced selections, with the exception of No. 102. The least productive cv. ‘Vega’ had the largest fruits, followed by ‘Sunburst’ and ‘Regina’.
Fruit soluble solid content (SSC) varied from 11.7% in ‘Merchant’ fruits (2020) to 21.7% in ‘Irema BS’ fruits (2019) (Table 6). SSC in the fruits of the latter cultivar was steadily high throughout the study period and reached an average value of 20.2%. The lowest average SSC was recorded in ‘Merchant’ and ‘Sunburst’ fruits: 14.7 and 15.8%, respectively. A particularly low SSC was observed in 2020 when the fruit yield was the highest.
‘Merchant’, ‘Sunburst’, ‘Regina’ and advanced selection No. 102 fruits were the most attractive (Table 7). No. 6 fruits had a poorer appearance. ‘Sunburst’, ‘Mindaugė’, ‘Regina’ and No. 102 fruits were the most delicious, and ‘Irema BS’, ‘Merchant’, ‘Vega’ and No. 6 fruits were somewhat less tasty. ‘Sunburst’, ‘Regina’ and No. 102 fruits achieved the highest overall rating.

3. Discussion

The growth of fruit trees is determined by cultivar and rootstock [31,32]. Even with the same rootstock, fruit trees of different cultivars have different growth vigor [23,33]. The weaker growth of fruit trees is an advantage, especially in the case of sweet cherries. Based on our research, the most significant effort will be needed to limit the growth of ‘Mindaugė’, ‘Vega’ and advanced selection No. 102 fruit trees.
The early or late beginning of cropping can be determined by the genetic characteristics of the cultivar [34], but vigorous sweet cherry trees on Mazzard or mahaleb rootstocks often do not flower significantly until the sixth or seventh leaf [35]. Usually, dwarf rootstocks significantly increase fruit tree precocity [31,36]. In our experiment, sweet cherry trees on Gisela 5 began flowering already in the 2nd year. Similar studies reported the early onset of flowering fruit trees on Gisela 5 rootstock [37,38]. According to the flowering abundance, cv. ‘Regina’ was the most precocious. Despite the observation that all cultivars of fruit trees bloomed less in the next year, cv. ‘Regina’ exhibited the most abundant flowering.
During the first two years, the fruit set was relatively low, and yields were not recorded. A more significant harvest was achieved in the 4th year after planting. The yield of the ‘Merchant’ cultivar was the lowest, while ‘Mindaugė’ yielded almost twice as many—4.69 t/ha. In later years, the most productive cultivars were ‘Merchant’, ‘Regina’ and advanced selection No. 102. The highest yields were recorded in 2020. ‘Regina’ and No. 102 produced a yield that was slightly higher than 20 t/ha. Weather conditions during the winter–early spring period in 2019–2020 were the most favorable during the study’s period. Average monthly air temperatures were higher than perennial ones, and the minimum temperature was recorded in early spring when it fell only to 10.7 °C. Frosts falling down to −2.9 °C at the beginning of flowering could slightly damage earlier flowering cultivars. The next winter (2020–2021) was characterized by low average and minimum temperatures in January and February. Moreover, a large fluctuation in temperature was recorded in the January–March period. Long-term warming in the second half of winter break dormancy and subsequent cooling even with not very low temperatures, may damage plants. Salazar-Gutiérrez et al. [39] reported that hardiness is highly dependent on fluctuations in temperature. This phenomenon mostly affected ‘Sunburst’, ‘Merchant’ and especially ‘Vega’ cultivars. Damage to the flower buds of the latter cultivar was rated with 4.0 points, and the yield was almost lost. Cultivar ‘Mindaugė’ produced the largest yield after the unfavorable winter–early spring period, although some of its flowers were also damaged. The frost resistance of sweet cherry flower buds and flowers is a complex phenomenon. This is influenced by the critical values of temperatures and their change over a relatively long period.
According to Salazar-Gutierrez et al. [39], sweet cherry cold hardiness increases from late fall to mid-January and is later followed by deacclimation. The possible level of damage is very dependent on the stage of flower bud development, and warm conditions increase flower vulnerability while low temperatures decrease that condition. Another study established that flower bud damage during spring frosts depended on their stage of development [28]. Flower buds subjected to frost at an earlier stage are more susceptible. Sweet cherry flowering phenophases are advanced by warm weather prior to the onset of phenophase [40]. Therefore, the risk of frost will remain with climate change, causing variable yields.
The yield efficiency indicator describes the ratio of fruit tree yield and growth. Higher yield efficiencies indicate that the fruit tree produces more fruit rather than vegetative parts. As the weaker fruit tree grows and produces more fruit, its yield efficiency becomes higher. The low yield efficiency recorded for cv. ‘Vega’ was caused by vigorous tree growth and low yield. The most yield-efficient fruit trees were the fruit trees of cv. ‘Regina’ followed by ‘Sunburst’, ‘Irema BS’ and ‘Merchant’. In the study by Gjamovski et al. [10], ‘Regina’ had about twice higher cumulative yield efficiencies than ‘Sunburst’ at the fifth leaf.
It is genetically determined that sweet cherry fruit weights can vary greatly. In the fresh fruit market, cherries weighing at least 10 grams are preferred [41]. In our experiment, only cv. ‘Vega’ produced fruits of a similar size, but the yield of this cultivar was low. Fruit size is affected by crop load [42], so the fruit would likely be smaller at the higher crop level. ‘Sunburst’ and ‘Regina’ fruits weighed about 9 g. The average fruit weight of Lithuanian cultivars was almost 7 g, and only an advanced selection of No. 102 produced fruits weighing 7.6 g. In addition to genetics, fruit size is determined by local ecological conditions and the technological factors of orchard management. According to different studies, the weight of ‘Regina’ fruits when grown on Gisela 5 rootstock ranged from 8.3 [10] to 11.5 g [43] in different locations. The weight of fruits grown in northern countries is usually lower. Preference is given to fruit tree winter hardiness, and a fruit weight of 6–9 g is considered to be acceptable [15].
Another important indicator of fruit quality is the soluble solid content (SSC). It ranged from 14.7% in ‘Merchant’ to 20.2% in ‘Irema BS’ fruits. Many factors influence SSC, and its range is wide enough in sweet cherries. It may vary between 11 and 25 °Brix [44]. There is different information regarding the lower limits of the SSC range. According to Vangdal [45], in order to be of acceptable quality, sweet cherries in Norway should contain at least 14.2% of soluble solids. American consumers prefer ‘Brooks’ and ‘Bing’ fruits with an SSC of not less than 16.0% [46]. The lowest SSC in our study was found in the year of the most abundant yield. High crop loads may have certain negative effects on fruit SSCs [47], and reducing the crop load results in an increase in SSC [48].
Sweet cherries are mainly used for fresh consumption, so the attractiveness and flavor of fruits are very important characteristics. Almost all tested cultivars received high sensory ratings. The exception was No 6, which was rated significantly worse. Meanwhile, another advanced selection No 102 was rated equally to the best commercial cultivars. A relationship between fruit flavor and SSC is often discussed. Some studies show a positive relationship between these indicators [49,50]. Crisosto et al. [51] reported interesting data that reflected no differences in SSC and fruit flavor perception between trained panelists, but consumers preferred fruits with higher SSCs. A curvilinear relationship between SSC’s impact on flavor was established [52], which suggests that lower SSC values may limit flavor acceptance and high ones are not determinative. Relatively low SSC values in 2020 did not reflect negatively on the sensory evaluation of fruits. On the other hand, a high SSC in ‘Regina’ fruits did not produce a high taste score.
Cvs. ‘Sunburst’, ‘Regina’ ‘Vega’ and ‘Merchant’ should be the most valuable from a consumer’s point of view due to the good quality of the fruit. The high yield of fruit trees is also important for fruit growers. ‘Regina’ and ‘Sunburst’ performed best at a young age. The advanced selection No. 102 produced a yield equal to that of the ‘Regina’ cultivar. The average fruit weight of No. 102 was the highest among all studied Lithuanian cultivars and was equal to ‘Merchant’ fruits. The fruits of No. 102 were attractive with good flavor and were rated similarly to those of ‘Regina’, ‘Sunburst’ ‘Merchant’ or ‘Vega’. ‘Regina’, ‘Sunburst’ and No. 102 performed best both in terms of productivity and fruit quality.

4. Materials and Methods

4.1. Planting Material and Orchard Maintenance

Sweet cherry cultivars and advanced selections of different ripening times were selected (Table 8). There was a preference toward large fruit size and dark fruit color (only ‘Vega’ fruits are colored red-yellow).
Fruit trees on the Gisela 5 rootstock were planted in the spring of 2015, spacing them at distances of 4.5 × 2.5 m. Trees were trained as spindles, and orchard floor management included frequently mown grass in the alleyways with herbicide strips along tree rows. Ammonium nitrate and potassium sulphate were applied to herbicide strips in spring annually since the third leaf. The N50K80 rate was used.

4.2. Site and Meteorological Conditions

The field experiment was carried out in 2015–2021 at the Institute of Horticulture, Lithuanian Research Centre for Agriculture and Forestry (55°60′ N, 23°48′ E).
The soil at the experiment place was Epicalcari–Endohypogleic cambisol, containing 245 mg/kg of P2O5, 196 mg/kg of K2O, and 2.9% of humus, with a pH(1MKCl) of 7.2.
The minimum air temperature in February and March 2018 was −23.3 and −21.0 °C, respectively (Table 9). No frosts were recorded during flowering. The minimum temperature of −20.1 °C in the winter of 2018–2019 was recorded in January. On May 4–8 2019, spring frosts down to −3.2 °C occurred during the flowering of sweet cherry trees. The winter of 2019–2020 was mild. The lowest temperature of −10.7 °C was recorded in early spring. At the beginning of flowering, frosts down to −2.9 °C occurred on April 26. Low temperatures were recorded in January and February 2021, reaching −27.7 and −24.9 °C, respectively. A considerable fluctuation in temperatures was recorded in the January–March period. In 2021, fruit trees bloomed late (on 8–24 of May), and there were no frosts during the flowering period. Temperature extremes of the winter–spring period were not reached during the research period.

4.3. Observations and Measurements

Trunk diameter measurements were performed in autumn at 25 cm above the graft union. Fruit tree flowering abundance was recorded at full bloom and scored on a 0–5 score scale, where “0” means the lowest and “5” means the highest value. In 2021, flower damage induced by unfavorable temperatures during the winter period was evaluated on a 0–5 score scale, where “0” means the lowest and “5” means the most significant damage. The yield was recorded for the entire experimental plot and recalculated to t/ha. Annual yield efficiency was expressed as the ratio of fruit yield per tree (kg) and tree trunk cross-section area (TCSA, cm2). The cumulative yield efficiency was calculated as a sum of annual efficiencies. The average fruit weight (g) was determined on a representative sample of 100 fruits per experimental plot. The soluble solid content (SSC, % Brix) was established with a digital refractometer (ATAGO 101, Atago Co., Ltd., Tokyo, Japan) on juice extracted from a random sample of 20 fruits. Sensory fruit quality was examined at harvest by 7 trained panelists. Fruit appearance, flavor and overall rating were expressed on a 1–5 score scale, where 1 indicates the lowest quality and 5 is the highest. Sensory fruit quality evaluation was performed in 2018 and 2020.

4.4. Experiment Design and Statistical Analysis

The field experiment was arranged in four replications with randomly arranged cultivars, and each experimental plot included 3 fruit trees. Experimental data were subjected to a one-way analysis of variance (ANOVA), and their means were compared using Duncan’s multiple range test. Differences were considered to be significant at p ≤ 0.05.

Author Contributions

Conceptualization, J.L. and V.S.; methodology, J.L.; software, D.K.; investigation, J.L. and N.U.; resources, D.K. and V.S.; data curation, J.L.; writing—original draft preparation, J.L.; writing—review and editing, J.L. and D.K.; visualization, J.L.; supervision, V.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Bujdosó, G.; Hrotko, K. Cherry production. In Cherries: Botany, Production and Uses; Quero-García, J., Iezzoni, A., Pulawska, J., Lang, G., Eds.; CABI: Wallingford, UK, 2017; pp. 1–13. [Google Scholar]
  2. FAOSTAT. Available online: https://www.fao.org/faostat/en/#data/QCL (accessed on 26 October 2022).
  3. Petrauskaitė-Senkevič, L. Fruit and berries. In Agriculture and Food Sector in Lithuania; Melnikienė, R., Ed.; Lithuanian Institute of Agrarian Economics: Vilnius, Lithuania, 2020; pp. 163–172. Available online: https://www.laei.lt/?mt=leidiniai&straipsnis=1817&metai=2020 (accessed on 26 October 2022). (In Lithuanian)
  4. Caprio, J.M.; Quamme, H.A. Influence of weather on apricot peach and sweet cherry production in the Okanagan Valley of British Columbia. Can. J. Plant Sci. 2006, 86, 259–267. [Google Scholar] [CrossRef]
  5. Szewczuk, A.; Gudarowska, E.; Dereń, D. The estimation of frost damage of some peach and sweet cherry cultivars after winter 2005/2006. J. Fruit Ornam. Plant Res. 2007, 15, 55–63. [Google Scholar]
  6. Demirsoy, H.; Demirsoy, L.; Lang, G.A. Research on spring frost damage in cherries. Hort. Sci. 2022, 49, 89–94. [Google Scholar] [CrossRef]
  7. Meland, M.; Maas, F.M.; Jørgensen, Å. Sweet cherry production in controlled environment. Acta Hortic. 2019, 1235, 353–358. [Google Scholar] [CrossRef]
  8. Koumanov, K.S.; Long, L.E. Site preparation and orchard infrastructure. In Cherries: Botany, Production and Uses; Quero-García, J., Iezzoni, A., Pulawska, J., Lang, G., Eds.; CABI: Wallingford, UK, 2017; pp. 223–243. [Google Scholar]
  9. Schuster, M.; Grafe, C.; Wolfram, B.; Schmidt, H. Cultivars resulting from cherry breeding in Germany. Erwerbs-Obstbau 2014, 56, 67–72. [Google Scholar] [CrossRef]
  10. Gjamovski, V.; Kiptijanovski, M.; Arsov, T. Evaluation of some cherry varieties grafted on Gisela 5 rootstock. Turk. J. Agric. For. 2016, 40, 737–745. [Google Scholar] [CrossRef]
  11. Stanys, V. Stone fruits. In Plant Breeding in Lithuania at the Turn of the Centuries; Ruzgas, V., Stanys, V., Eds.; Lithuanian Research Centre for Agriculture and Forestry: Kaunas, Lithuania, 2022; pp. 196–202. ISBN 9786094510052. (In Lithuanian) [Google Scholar]
  12. Bieniek, A.; Kawecki, Z.; Kopytowski, J.; Zielenkiewicz, J. Yielding and fruit quality of Lithuanian sweet cherry cultivars grown under the climatic and soil conditions of Warmia. Folia Hortic. 2011, 23, 101–106. [Google Scholar] [CrossRef] [Green Version]
  13. Lanauskas, J.; Kviklys, D.; Uselis, N.; Viškelis, P.; Kviklienė, N.; Buskienė, L. Rootstock effect on the performance of sweet cherry (Prunus avium) cv. ‘Vytėnų rožinė’. Zemdirbyste 2014, 101, 85–90. [Google Scholar] [CrossRef] [Green Version]
  14. Sasnauskas, A.; Bendokas, V.; Karklelienė, R.; Juskeviciene, D.; Šikšnianas, T.; Gelvonauskien, D.; Rugienius, R.; Baniulis, D.; Sikorskaite, S.; Mazeikiene, I.; et al. Breeding Trends of Fruit and Vegetable Crops for Organic Production in Lithuania. Horticulturae 2016, 3, 1. [Google Scholar] [CrossRef] [Green Version]
  15. Ruisa, S.; Krasnova, I. Assessment of sweet cherry cultivars and selections in Latvia. Acta Hortic. 2013, 976, 161–166. [Google Scholar] [CrossRef]
  16. Jänes, H.; Ardel, P.; Kersti, K.; Kelt, K.; Kikas, A. Some biological properties and fruit quality parameters of new sweet cherry cultivars and perspective selections. Agron. Res. 2010, 8, 583–588. [Google Scholar]
  17. Sansavini, S.; Lugli, S. Sweet cherry breeding programs in Europe and Asia. Acta Hortic. 2008, 795, 41–58. [Google Scholar] [CrossRef] [Green Version]
  18. Quero-García, J.; Schuster, M.; López-Ortega, G.; Charlot, G. Sweet cherry varieties and improvement. In Cherries: Botany, Production and Uses; Quero-García, J., Iezzoni, A., Pulawska, J., Lang, G., Eds.; CABI: Wallingford, UK, 2017; pp. 60–94. [Google Scholar]
  19. Dondini, L.; Lugli, S.; Sansavini, S. Cherry breeding: Sweet cherry (Prunus avium L.) and sour cherry (Prunus cerasus L.). In Advances in Plant Breeding Strategies: Fruits; Al-Khayri, J., Jain, S., Johnson, D., Eds.; Springer: Cham, Switzerland, 2018; pp. 31–88. [Google Scholar]
  20. Blažek, J.; Zelený, L.; Suran, P. Sweet cherry research world overview 2015–2017. Hort. Sci. 2022, 49, 121–146. [Google Scholar] [CrossRef]
  21. Lanauskas, J.; Uselis, N.; Kviklys, D.; Kviklienė, N.; Buskienė, L. Rootstock effect on the performance of sweet cherry cv. Lapins. Hort. Sci. 2012, 39, 55–60. [Google Scholar] [CrossRef]
  22. Musacchi, S.; Gagliardi, F.; Serra, S. New training systems for high-density planting of sweet cherry. HortScience 2015, 50, 59–67. [Google Scholar] [CrossRef]
  23. Akçay, M.E.; Fidancı, A.; Burak, M. Growth and yield of some sweet cherry cultivars grafted on ‘Gisela® 5’ rootstock. Acta Hortic. 2008, 795, 277–282. [Google Scholar] [CrossRef]
  24. Kolev, K.; Dzhuvinov, V. Evaluation of nine sweet cherry cultivars on ‘Gisela® 5’ rootstock. Acta Hortic. 2008, 795, 373–378. [Google Scholar] [CrossRef]
  25. Usenik, V.; Fajt, N. Sweet cherry cultivar testing in Slovenia. Acta Hortic. 2019, 1235, 265–270. [Google Scholar] [CrossRef]
  26. Rubauskis, E.; Skrivele, M.; Ruisa, S.; Feldmane, D. Effect of Crown Restriction on the Growth and Productivity of Sweet Cherries. Proc. Latv. Acad. Sci. B Nat. Exact Appl. Sci. 2013, 67, 151. [Google Scholar] [CrossRef] [Green Version]
  27. Rubauskis, E.; Skrīvele, M.; Ruisa, S.; Feldmane, D. Growth and yield of two sweet cherry cultivars on vegetatively propagated rootstocks. Acta Hortic. 2014, 1058, 657–661. [Google Scholar] [CrossRef]
  28. Dekena, D.; Lepsis, J.; Laugale, V.; Feldmane, D. Preliminary results of sweet cherry rootstock evaluation for cultivar ‘Arthur’. Acta Hortic. 2022, 1346, 709–716. [Google Scholar] [CrossRef]
  29. Bujdosó, G.; Hrotkó, K. Cultivars and rootstocks in the cherry producing countries. Acta Hortic. 2019, 1235, 207–212. [Google Scholar] [CrossRef]
  30. Sansavini, S.; Lugli, S. New rootstocks for intensive sweet cherry plantations. Acta Hortic. 2014, 1020, 411–434. [Google Scholar] [CrossRef]
  31. Pal, M.D.; Mitre, I.; Asănică, A.C.; Sestraș, A.F.; Peticilă, A.G.; Mitre, V. The influence of rootstock on the growth and fructification of cherry cultivars in a high density cultivation system. Not. Bot. Horti Agrobot. Cluj-Napoca 2017, 45, 451. [Google Scholar] [CrossRef] [Green Version]
  32. Milić, B.; Kalajdžić, J.; Keserović, Z.; Magazin, N.; Ognjanov, V.; Miodragović, M.; Popara, G. Early performance of four sweet cherry cultivars grafted on Gisela 5 and Colt rootstocks in a high density growing system. Acta Sci. Pol. Hortorum Cultus 2019, 18, 99–108. [Google Scholar] [CrossRef]
  33. Franken-Bembenek, S. Gisela 5 (148/2)—Dwarfing rootstock for sweet cherries. Acta Hortic. 1998, 468, 279–284. [Google Scholar] [CrossRef]
  34. Blazek, J. Precocity and productivity in some sweet cherry crosses. Acta Hortic. 1985, 169, 105–114. [Google Scholar] [CrossRef]
  35. Lang, G. Precocious, dwarfing, and productive—How will new cherry rootstocks impact the sweet cherry industry? HortTechnology 2000, 10, 719–725. [Google Scholar] [CrossRef]
  36. Usenik, V.; Fajt, N.; Ătampar, F. Effects of rootstocks and training system on growth, precocity and productivity of sweet cherry. J. Hortic. Sci. Biotechnol. 2006, 81, 153–157. [Google Scholar] [CrossRef]
  37. Whiting, M.; Lang, G.; Ophardt, D. Rootstock and training system affect sweet cherry growth, Yield and Fruit Quality. HortScience 2005, 40, 582–586. [Google Scholar] [CrossRef] [Green Version]
  38. Ağlar, E.; Kenan, Y. Influence of rootstocks (Gisela 5, Gisela 6, MaxMa, SL 64) on performance of ‘0900 Ziraat’ sweet cherry. J. Basic Appl. Sci. 2014, 10, 60–66. [Google Scholar] [CrossRef] [Green Version]
  39. Salazar-Gutiérrez, M.R.; Chaves, B.; Anothai, J.; Whiting, M.; Hoogenboom, G. Variation in cold hardiness of sweet cherry flower buds through different phenological stages. Sci. Hortic. 2014, 172, 161–167. [Google Scholar] [CrossRef]
  40. Usenik, V.; Stampar, F. The Effect of environmental temperature on sweet cherry phenology. Eur. J. Hortic. Sci. 2011, 76, 1–5. [Google Scholar]
  41. Szilágyi, S.; Horváth-Kupi, T.; Desiderio, F.; Bekefi, Z. Evaluation of sweet cherry (Prunus avium L.) cultivars for fruit size by FW_G2a QTL analysis and phenotypic characterization. Sci. Hortic. 2022, 292, 110656. [Google Scholar] [CrossRef]
  42. Bennewitz, E.; Sanhueza, S.; Elorriaga, A. Effect of different crop load management strategies on fruit production and quality of sweet cherries (Prunus avium L.) ‘Lapins’ in Central Chile. J. Fruit Ornam. Plant Res. 2010, 18, 51–57. [Google Scholar]
  43. Szpadzik, E.; Krupa, T.; Niemiec, W.; Jadczuk-Tobjasz, E. Yielding and fruit quality of selected sweet cherry (Prunus avium) cultivars in the conditions of Central Poland. Acta Sci. Pol. Hortorum Cultus 2019, 18, 117–126. [Google Scholar] [CrossRef]
  44. Silva, V.; Pereira, S.; Vilela, A.; Bacelar, E.; Guedes, F.; Ribeiro, C.; Silva, A.P.; Gonçalves, B. Preliminary insights in sensory profile of Ssweet cherries. Foods 2021, 10, 612. [Google Scholar] [CrossRef] [PubMed]
  45. Vangdal, E. Quality criteria for fruit for fresh consumption. Acta Agric. Scand. B Soil Plant Sci. 1985, 35, 41–47. [Google Scholar] [CrossRef]
  46. Crisosto, C.H.; Crisosto, G.M.; Metheney, P. Consumer acceptance of ‘Brooks’ and ‘Bing’ cherries is mainly dependent on fruit SSC and visual skin color. Postharvest Biol. Technol. 2003, 28, 159–167. [Google Scholar] [CrossRef]
  47. Carvalho, M.L.; Dias, C.; Barrisca, C.; Branca, M.; De Melo-Abreu, J.P. Crop load effect on productivity and quality parameters of sweet cherry (Prunus avium L.). Acta Hortic. 2012, 932, 187–193. [Google Scholar] [CrossRef]
  48. Rutkowski, K.; Łysiak, G.P. Thinning methods to regulate sweet cherry crops—A Review. Appl. Sci. 2022, 12, 1280. [Google Scholar] [CrossRef]
  49. Guyer, D.E.; Sinha, N.K.; Chang, T.S.; Cash, J.N. Physicochemical and sensory characteristics of selected Michigan sweet cherry (Prunus avium L.) cultivars. J. Food Qual. 1993, 16, 355–370. [Google Scholar] [CrossRef]
  50. Dever, M.C.; MacDonald, R.A.; Cliff, M.A.; Lane, W.D. Sensory evaluation of sweet cherry. HortScience 1996, 31, 150–153. [Google Scholar] [CrossRef]
  51. Crisosto, C.H.; Crisosto, G.M.; Ritenour, M.A. Testing the reliability of skin color as an indicator of quality for early season ‘Brooks’ (Prunus avium L.) cherry. Postharvest Biol. Technol. 2002, 24, 147–154. [Google Scholar] [CrossRef]
  52. Kappel, F.; Fisher-Fleming, B.; Hogue, E.J. Fruit characteristics and sensory attributes of an ideal sweet cherry. Hortscience 1996, 31, 443–446. [Google Scholar] [CrossRef] [Green Version]
  53. Patzak, J.; Henychová, A.; Paprštein, F.; Sedlak, J. Evaluation of genetic variability within sweet cherry (Prunus avium L.) genetic resources by molecular SSR markers. Acta Sci. Pol. Hortorum Cultus 2019, 18, 157–165. [Google Scholar] [CrossRef]
  54. Lithuanian Hydrometeorological Service. Available online: http://www.meteo.lt/en/ (accessed on 15 November 2022).
Plants 12 00614 g001 550
Figure 1. Sweet cherry tree trunk diameter in autumn 2021 in cm. Values marked with different letters are statistically different (p ≤ 0.05).
Figure 1. Sweet cherry tree trunk diameter in autumn 2021 in cm. Values marked with different letters are statistically different (p ≤ 0.05).
Plants 12 00614 g001
Table
Table 1. Sweet cherry flowering abundance (0–5 score scale). Values marked with different letters are statistically different within the columns (p ≤ 0.05).
Table 1. Sweet cherry flowering abundance (0–5 score scale). Values marked with different letters are statistically different within the columns (p ≤ 0.05).
Cultivar201620172018201920202021
‘Mindaugė’ 2.0 bc0.1 a3.8 b4.4 bc5.0 b4.4 cd
‘Irema BS’0.3 a0.3 ab3.8 b3.9 a5.0 b5.0 d
No 6 2.1 bc1.4 bc3.5 ab4.1 ab4.5 a3.2 b
No 1022.3 bc0.8 b3.6 ab4.8 c5.0 b3.9 c
‘Merchant’1.7 b0.2 a3.3 a4.1 ab4.7 ab4.0 cd
‘Sunburst’1.7 b0.0 a3.4 a4.4 bc5.0 b3.7 bc
‘Regina’ 3.4 c2.3 c4.2 c4.7 bc4.9 b5.0 d
‘Vega’1.8 b0.0 a3.8 b4.2 ab5.0 b1.8 a
Table
Table 2. Sweet cherry flower damage after winter 2021 (0–5 score scale). Values marked with different letters are statistically different within the columns (p ≤ 0.05).
Table 2. Sweet cherry flower damage after winter 2021 (0–5 score scale). Values marked with different letters are statistically different within the columns (p ≤ 0.05).
‘Mindaugė’ 1.1 b
‘Irema BS’0.5 ab
No 6 0.5 ab
No 1021.0 b
‘Merchant’1.8 c
‘Sunburst’2.2 c
‘Regina’ 0.0 a
‘Vega’4.0 d
Table
Table 3. Sweet cherry fruit yields (t/ha). Values marked with different letters are statistically different within the columns (p ≤ 0.05).
Table 3. Sweet cherry fruit yields (t/ha). Values marked with different letters are statistically different within the columns (p ≤ 0.05).
Cultivar2018201920202021Average
‘Mindaugė’ 4.69 c2.14 abcd9.77 b12.36 e7.24 c
‘Irema BS’3.58 abc2.79 abcd16.68 c8.98 d8.01 cd
No. 6 3.51 abc2.69 abcd12.76 b5.59 b6.14 bc
No. 1022.48 ab3.12 dc21.20 d6.80 bc8.40 cd
‘Merchant’2.42 a3.33 d12.21 b5.06 b5.76 b
‘Sunburst’3.54 abc3.05 bcd16.25 bc5.61 b7.11 bc
‘Regina’ 2.99 abc1.69 a22.16 d8.07 cd8.73 d
‘Vega’2.88 abc1.90 ab5.85 a0.37 a2.75 a
Table
Table 4. Sweet cherry yield efficiency (kg/cm2 TCSA). Values marked with different letters are statistically different within the columns (p ≤ 0.05); ns—non-significant.
Table 4. Sweet cherry yield efficiency (kg/cm2 TCSA). Values marked with different letters are statistically different within the columns (p ≤ 0.05); ns—non-significant.
Cultivar2018201920202021Cumulative
‘Mindaugė’ 0.0810.030 ab0.114 a0.135 e0.359 b
‘Irema BS’0.0710.044 ab0.224 bc0.109 d0.448 cd
No. 6 0.0780.049 b0.206 b0.082 bc0.415 c
No. 1020.0450.041 ab0.252 bc0.072 b0.409 bc
‘Merchant’0.0630.071 c0.224 bc0.083 bc0.440 cd
‘Sunburst’0.0800.057 bc0.261 bcd0.081 bc0.478 cd
‘Regina’ 0.0600.026 a0.315 d0.102 cd0.503 d
‘Vega’0.0590.031 ab0.079 a0.004 a0.173 a
ns
Table
Table 5. The average sweet cherry fruit weight (g). Values marked with different small letters are statistically different within the columns and with the capitals—in the row (p ≤ 0.05).
Table 5. The average sweet cherry fruit weight (g). Values marked with different small letters are statistically different within the columns and with the capitals—in the row (p ≤ 0.05).
Cultivar2018201920202021Average
‘Mindaugė’ 6.1 a7.1 ab7.8 ab6.5 b6.9 a
‘Irema BS’6.5 ab7.2 b7.2 ab5.7 a6.7 a
No. 6 7.0 b6.6 a6.9 a6.2 ab6.7 a
No. 1027.4 b8.3 cd7.5 ab7.2 b7.6 b
‘Merchant’8.1 c8.1 c8.0 b8.0 c8.0 b
‘Sunburst’8.9 d10.2 e8.1 b9.2 d9.1 c
‘Regina’ 9.5 e9.6 d8.9 b7.2 b8.8 c
‘Vega’7.5 b11.6 f10.2 c10.4 e9.9 d
Average7.6 A8.6 C8.1 B7.6 A8.0
Table
Table 6. Soluble solid content of sweet cherry fruits (%). Values marked with different small letters are statistically different within the columns and with the capitals—in the row (p ≤ 0.05).
Table 6. Soluble solid content of sweet cherry fruits (%). Values marked with different small letters are statistically different within the columns and with the capitals—in the row (p ≤ 0.05).
Cultivar2018201920202021Average
‘Mindaugė’19.0 b20.4 c15.7 c15.2 a17.6 d
‘Irema BS’20.3 c21.7 d19.4 d19.5 c20.2 f
No 6 20.8 c19.8 c15.6 c18.3 bc18.6 e
No 10219.2 b20.2 c13.6 b14.0 a16.8 c
‘Merchant’16.7 a16.0 a11.7 a14.3 a14.7 a
‘Sunburst’17.0 a18.4 b12.3 a15.3 a15.8 b
‘Regina’ 17.9 ab18.5 b15.5 c17.0 b17.2 cd
‘Vega’17.2 a21.0 cd14.5 bc18.7 c17.8 d
Average18.5 C19.5 D14.8 A16.5 B17.3
Table
Table 7. Sensory evaluation of sweet cherry fruits (1–5 score scale), and average data of 2018 and 2020. Values marked with different letters are statistically different within the columns (p ≤ 0.05).
Table 7. Sensory evaluation of sweet cherry fruits (1–5 score scale), and average data of 2018 and 2020. Values marked with different letters are statistically different within the columns (p ≤ 0.05).
CultivarAppearanceFlavourOverall Rating
‘Mindaugė’ 4.5 ab4.6 ab4.5 ab
‘Irema BS’4.5 ab4.4 a4.5 ab
No 6 4.4 a4.4 a4.4 a
No 1024.7 b4.6 ab4.7 b
‘Merchant’4.7 b4.5 a4.6 ab
‘Sunburst’4.7 b4.7 b4.7 b
‘Regina’ 4.7 b4.6 ab4.7 b
‘Vega’4.6 ab4.5 a4.6 ab
Table
Table 8. Genetic resources [11,53]. OP—open pollination.
Table 8. Genetic resources [11,53]. OP—open pollination.
CultivarFruit RipeningOriginPedigree
‘Mindaugė’ midseasonLithuania‘Severnaya’ × ‘Jurgita’
‘Irema BS’lateLithuaniaNo 1106 × ‘Sam’
No. 6 midseasonLithuaniaunknown
No. 102midseasonLithuania‘Ulster’ × OP
‘Merchant’earlyGreat Britain‘Merton Glory’ × OP
‘Sunburst’midseasonCanada‘Van’ × ‘Stella’
‘Regina’ lateGermany‘Schneiders’ × ‘Rube’
‘Vega’midseasonCanada‘Bing’ × ‘Victor’
Table
Table 9. Air temperature in the winter–spring period. Records of the iMETOS® (Pessl Instruments GmbH, Weiz, Austria) meteorological station in Babtai and Lithuanian Hydrometeorological Service [54] (* Galerija—Meteo.lt; ** Extreme phenomena—Meteo.lt).
Table 9. Air temperature in the winter–spring period. Records of the iMETOS® (Pessl Instruments GmbH, Weiz, Austria) meteorological station in Babtai and Lithuanian Hydrometeorological Service [54] (* Galerija—Meteo.lt; ** Extreme phenomena—Meteo.lt).
Temperature, °CDecemberJanuaryFebruaryMarchAprilMay
2017–2018
Average1.3−1.4−5.6−0.410.416.8
Minimum−4.2−17.2−23.3−21.0−1.52.1
Maximum8.47.73.29.027.431.6
2018–2019
Average−0.3−3.61.63.48.211.7
Minimum−13.6−20.1−8.8−5.6−4.2−3.2
Maximum5.65.210.313.926.128.5
2019–2020
Average2.62.92.53.66.810.4
Minimum−7.3−3.9−7.0−10.7−5.2−2.2
Maximum10.37.510.717.721.622.9
2020–2021
Average0.8−3.6−5.91.96.011.5
Minimum−9.4−27.7−24.9−11.2−3.8−1.8
Maximum6.35.013.616.721.026.2
Perennial (1991–2020) average and extreme phenomena
Average *−1.2−3.0−2.41.27.613.0
Minimum **−34.0−40.5−42.9−37.5−23.0−6.8
Maximum **15.612.616.521.831.034.0
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Lanauskas, J.; Kviklys, D.; Uselis, N.; Stanys, V. Performance of Sweet Cherry Cultivars and Advanced Selections on Gisela 5 Rootstock in Young Orchards. Plants 2023, 12, 614. https://doi.org/10.3390/plants12030614

AMA Style

Lanauskas J, Kviklys D, Uselis N, Stanys V. Performance of Sweet Cherry Cultivars and Advanced Selections on Gisela 5 Rootstock in Young Orchards. Plants. 2023; 12(3):614. https://doi.org/10.3390/plants12030614

Chicago/Turabian Style

Lanauskas, Juozas, Darius Kviklys, Nobertas Uselis, and Vidmantas Stanys. 2023. "Performance of Sweet Cherry Cultivars and Advanced Selections on Gisela 5 Rootstock in Young Orchards" Plants 12, no. 3: 614. https://doi.org/10.3390/plants12030614

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop