Cultivar-specific responses of sweet cherry flowering to rising temperatures during dormancy
Introduction
Phenology in temperate fruit trees, as in other woody perennials, is mainly regulated by the seasonal fluctuation of temperature and in many species also by photoperiod (Cooke et al., 2012; Singh et al., 2017). Temperate trees enter dormancy during autumn-winter and resume active growth in spring. They then experience a relatively rapid succession of phenological development stages, which culminates in flowering several weeks later (Rohde and Bhalerao, 2007). Recent temperature changes caused by global warming are affecting tree phenology and flowering, with reported changes including both advances and delays, depending on the species and geographical area (Shi et al., 2017). In fruit tree species, such changes may directly affect fruit production and yield, which depend on processes occurring around flowering time, such as pollination, fertilization and fruit set (Hedhly et al., 2009). Despite the importance of dormancy physiology, understanding how temperature regulates phenology in temperate fruit trees remains a challenge.
Fruit tree species and cultivars present specific temperature requirements that must be met for them to overcome dormancy and resume growth in spring (Castède et al., 2014). First, during endodormancy, trees require chill, i.e. exposure to low temperatures, which allows them to overcome endodormancy and recover the capacity to grow. Subsequently, during ecodormancy, also known as the forcing period, trees need mild or warm temperatures to initiate budbreak and eventually bloom (Lang et al., 1987; Rohde and Bhalerao, 2007). The chilling and forcing periods have traditionally been determined experimentally, based on shoots collected during the winter after different periods of chill exposure in the field (Fadón and Rodrigo, 2018). Dormancy is considered broken when flower buds have increased significantly in weight and show resumption of phenological development after a period of exposure to warm conditions in a growth chamber (Bennett, 1949; Brown and Kotob, 1957). As an alternative to experiments, several statistical approaches have been developed to estimate the chilling and forcing periods by relating flowering dates to temperature records (Alonso et al., 2005; Ashcroft et al., 1977; Richardson et al., 1974; Tabuenca, 1972; Tabuenca and Herrero, 1966). Among these attempts, Partial Least Squares (PLS) regression has emerged as particularly promising, since it can be applied even when the number of independent variables (daily temperatures, 365 data points per year) substantially exceeds the number of dependent variables (one flowering date per cultivar and year; (Luedeling and Gassner, 2012). This method identifies the days of the season during which relatively low temperatures are associated with early flowering dates (chilling period). It also marks days when relatively high temperatures are linked to early flowering (forcing period).
After establishing the chilling and forcing periods with either the experimental or the statistical method, temperature dynamics during both periods can be analyzed to determine the temperature requirements of particular cultivars. The Chilling Hours model (Hutchins, 1932, as cited by Weinberger, 1950), the Utah model (Richardson et al., 1974), and the Dynamic model (Erez et al., 1990; Fishman et al., 1987) are the most commonly used models for chill quantification (Luedeling and Brown, 2011). Heat accumulation is usually quantified with the Growing Degree Hours model (Richardson et al., 1975). These models, which need hourly temperature data from autumn to bloom, have been extensively used to predict the phenology of numerous species of temperate fruit trees under a wide range of climates (Fadón et al., 2020b; Luedeling and Brown, 2011). However, they were originally developed for particular peach cultivars under specific climate conditions: the Utah model was developed under cold and snowy winter conditions (Richardson et al., 1974), and the Dynamic model was developed in the warm Mediterranean climate of Israel (Erez et al., 1990; Fishman et al., 1987).
Sweet cherry has seen a substantial increase in demand in recent years, with cherries produced near the margin of the production season, or even in the off-season, fetching particularly high prices (Bujdosó and Hrotko, 2017). This has prompted the extension of the traditional growing areas to warmer or cooler regions (Kappel et al., 2012). However, many attempts to introduce particularly early or late cultivars have not been successful, in part because of insufficient knowledge of the cultivars’ agroclimatic requirements, which has led to introductions of poorly suited cultivars that displayed irregular phenology and erratic productivity. In addition to the long-standing difficulties in introducing new cultivars, in the current age of climate change, even the performance of traditional sweet cherry cultivars under the novel climate conditions that are expected can no longer be forecast with certainty (Wenden et al., 2017).
Temperature requirements are only known for a few commercial sweet cherry cultivars, and except for some recent efforts, many of these estimates were published more than 25 years ago (Alburquerque et al., 2008; Campoy et al., 2019; Cortés and Gratacós, 2008; Kuden and Imrak, 2012; Tabuenca, 1983; reviewed in Fadón et al., 2020b). Whether these estimates are valid under current and, in particular, future climatic conditions is currently unclear, and for most currently grown cultivars, no information at all is available. Estimates that exist were obtained by growth observations of shoots under forcing conditions during the winter (Bennett, 1949; Brown and Kotob, 1957). This methodology identifies the minimum chill exposure that is necessary for buds to grow when moved to warm conditions. In other fruit tree species, recent studies have successfully applied PLS regression analysis to estimate temperature requirements of a number of cultivars (Benmoussa et al., 2017a, 2017b; Díez-Palet et al., 2019). PLS regression analysis delineates the periods during which relatively low or high temperatures advance flowering.
In the present analysis, we investigated the effects of chill and heat accumulation on flowering in 20 sweet cherry cultivars from North America grown in Zaragoza (Spain), including some of the world's most widely grown cultivars. First, we delineated the temperature response phases and established the temperature requirements of each cultivar by using Partial Least Squares (PLS) regression to correlate a 20-year phenology record (1991–2001; 2009–2019) with daily chill and heat accumulation. We then explored the effects of temperature variation during these phases to elucidate how flowering dates responded to the decline in chill accumulation that has been caused by climate change.
Section snippets
Plant material and phenology monitoring
We evaluated flowering dates of 20 sweet cherry cultivars from a cultivar collection at the Centro de Investigación y Tecnología Agroalimentaria de Aragón (CITA) in Zaragoza (Spain), at 41°44′30″N, 0°47′00″W and 220 m above sea level. The orchard was managed according to standard horticultural practices. The cultivars we studied originated from breeding programs in the United States and Canada (Table 1). The collection includes some of the most widely grown cultivars in the United States
Flowering dates
Bloom dates of the sweet cherry cultivars we analyzed ranged between mid-March and mid-April (Fig. 1). The earliest flowering date was 12th March (in 2017) for 'Sandom Rose', and the latest was 16th April (in 2016) for 'Lambert' (Fig. 1), with 35 days between them.
In general, the flowering dates showed a delay between 1 and 5 days during the years 2009–2019 in comparison with the period between 1991–2001 (Fig. 1). Linear regressions of flowering dates over time showed positive slopes (i.e.
Chill and heat requirements for flowering
In this work, we determined the temperature requirements of 20 sweet cherry cultivars, for most of which (13) no previous data were available (Fadón et al., 2020b). This is the first time that a statistical method has been used with a large number of cultivars of sweet cherry, since only the temperature requirements of ‘Schneiders späte Knorpelkirsche’ had previously been calculated with this methodology (Luedeling et al., 2013). So far, PLS regression has been used to calculate the temperature
Conclusion
Flowering dates in sweet cherry and other deciduous trees are determined by temperatures in the seven or eight months that precede bloom. Within this time span, rising temperatures during winter resulted in a reduction in chill and heat accumulation in Zaragoza. These developments provide an explanation for the long-term trend towards delayed flowering, since flowering dates are driven by temperature conditions during the chilling and forcing phases for most of the sweet cherry cultivars in
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
We are deeply thankful to Rosa Fustero for recording the blooming dates of cherry trees; and to Eduardo Fernandez for his support in data processing.
Financial support has been provided by PRIMA, a program supported under H2020, the European Union's Framework programme for research and innovation ("AdaMedOr" project; grant number 01DH20012 of the German Federal Ministry of Education and Research; grant number PCI2020-111966/AEI/10.13039/501100011033 of Agencia Estatal de Investigación);
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