Predicting Flower Phenology and Viability of Highbush Blueberry

To maximize yield of pollination-dependent agricultural crops, farmers must ensure that sufficient pollinators are present when flowers are open and viable. We characterized and compared the lower development threshold temperature, bloom phenology, and flower viability of five common cultivars of highbush blueberry (Vaccinium corymbosum L.) to enable prediction of when flowers would be available for pollination. Threshold temperatures of all cultivars were found to be very similar and range between 7 and 8 8C. Logistic regression was used to characterize bloom phenology for all cultivars under field and greenhouse conditions. Bloom phenology under greenhouse conditions was delayed ’100 growing degree-days when compared with field conditions. Average flower viability was determined daily from first flower opening until 5 days after flower opening for each cultivar. Results indicated declining flower viability with increasing flower age with most flowers unsuitable for pollination more than 4 days after opening. Implications of these results for planning pollination of highbush blueberry fields are discussed. A wide variety of variables, both genetic and environmental in origin, are known to influence plant growth and development. In agricultural systems, light intensity, air quality, soil nutrients, moisture, and air and soil temperature are particularly important environmental factors (Pessarakli, 2002). Monitoring environmental conditions can be crucial for farmers wishing to implement management practices at specific stages of crop development. For example, the phenological development of pollination-dependent agricultural crops is important to farmers seeking to maximize yield. Many farmers depend on rented honeybee hives for pollination (Delaplane and Mayer, 2000; James and Pitts-Singer, 2008). It is important for these managed pollinators to be introduced into agricultural crops only after flowering has begun to ensure pollination of the crop of interest as opposed to alternative foraging resources such as wildflowers (Free, 1993). The ability to predict timing of crop flowering can improve placement of managed bee colonies near fields at the optimal time for pollination and also aid in maximizing crop yield. Accurate prediction of biological events is fundamental to planting at an appropriate time, protecting crops from pests and inclement weather conditions, ensuring sufficient pollination, and planning the eventual harvest of crops (Bailey, 1947; Wielgolaski, 1999). The ability to predict important components of flower development such as flower opening and viability after anthesis would be useful for growers of crops dependent on insect-mediated pollination. If a crop requires cross-pollination, as is the case for many fruit crops (McGregor, 1976), it is also important to know the phenology of each participant cultivar to ensure that reproductively compatible varieties within the same area are in bloom at the same time. Finally, knowledge of the period of time during which flowers remain viable for pollination enables sufficient bee colonies to be purchased or rented to achieve the concentration of bees required for full crop pollination and yield potential. For a large majority of fruit crop species, temperature and consequent heat accumulation are the most influential environmental factors that control development (Rathcke and Lacey, 1985; Schaffer and Anderson, 1994) and these are commonly monitored by farmers in early spring. One method of measuring heat accumulation incorporates both time and temperature into a unit called a growing degree-day (GDD), described in detail by Baskerville and Emin (1969). Because GDDs are calculated using a species-specific value for the critical lower threshold temperature below which plant development does not occur (base temperature), these heat units are universally functional and therefore allow bloom phenology to be predicted in many regions across a range of environments. The prediction of crop bloom based on GDD has been used in the past to predict bloom in almond [Prunus dultis (Mill) D.A. Webb] (DeGrandi-Hoffman et al., 1996; Rattigan and Hill, 1986), apple [Malus 3 sylvestris (L.) Mill. Var. domestica (Borkh.) Mansf.] (Anstey, 1966; DeGrandi-Hoffman et al., 1987), tomato [Lycopersicon esculentum Mill.] (Zalom and Wilson, 1999), apricot (Prunus armeniaca L.), cherry (Prunus avium L.), peach [Prunus persica (L.) Batsch], pear (Pyrus communis L.) (Anstey, 1966), and sunflower (Helianthus anuus L.) (Goyne et al., 1977), but this has not been accomplished for highbush blueberry [Vaccinium corymbosum (L.)]. Similarly, few studies have focused on the duration of flower viability in modern blueberry cultivars. An early study of ‘Rubel’ suggested that viability is greatest 1 to 2 d after flower opening (Merrill, 1936); however, this cultivar has been planted less frequently in recent years. In 1964, Moore documented that ‘Bluecrop’ flowers were receptive to pollen up to 5 d after flower opening under greenhouse conditions, whereas fruit set and seed number both decreased if the flower was pollinated more than 4 d after opening. Moore (1964) also investigated flower viability under field conditions for ‘Coville’ and ‘Blueray’. His results indicate significant differences in flower viability for these cultivars, with flowers of ‘Blueray’ receptive to pollination for a longer period of time than those of ‘Coville’. Rabbiteye blueberry (Vaccinium virgatum Ait. syn. V. ashei Reade) flowers are viable up to 5 d after anthesis (Brevis and NeSmith, 2006). Additional data for highbush blueberry phenology and flower viability can be incorporated into mathematical models that predict bloom dependent on accumulated GDDs. Such decision support tools would provide highbush blueberry growers with a means to predict the dynamics of flower opening and flower viability using forecasted weather conditions. It would also allow for pollination strategies and management practices to be adapted depending on the projected length of blueberry bloom. This study characterized and compared the bloom phenology of five common cultivars of highbush blueberry with respect to temperature accumulation. This was accomplished by first measuring bloom phenology as a function of temperature so that a lower threshold base temperature could be determined. Base temperatures were then used to calculate accumulated GDDs and relate that temperature accumulation to the bloom phenology of bushes grown under greenhouse and field conditions. In addition, flower viability was examined in each of the five cultivars under greenhouse and field conditions to determine the relationship between flower age and viability within and among cultivars. Received for publication 7 May 2012. Accepted for publication 23 July 2012. This research was funded by a MSU Plant Science Program Fellowship to A.K.K. and by the Michigan State University Rackham Foundation. We thank Kyle Ringwald for excellent technical assistance. We also thank Jim Miller, Jim Hancock, Scott Swinton, and members of the Berry Crops Entomology laboratory at Michigan State University for reviewing earlier versions of the manuscript. Thanks to John Wise and the staff at Trevor Nichols Research Center for technical support and to the Southwest Michigan Research and Extension Center, MBG Marketing, Jawor Bros. Blueberries, Inc., DeGrandchamp Farms, and Cornerstone Ag LLC for access to their blueberry fields. To whom reprint requests should be addressed; e-mail [email protected]. HORTSCIENCE VOL. 47(9) SEPTEMBER 2012 1291 Materials and Methods Highbush blueberry plants. Five commonly planted cultivars of northern highbush blueberry, V. corymbosum, were chosen to represent a range of early to late harvest periods. The cultivars used for all experiments were Duke, Bluecrop, Jersey, Elliott, and Liberty. Base temperature, phenology, and flower viability experiments were conducted in growth chambers in 2010–11, under greenhouse conditions in 2009 and 2011 and in Michigan highbush blueberry fields in 2009–11, respectively. Bushes used for growth chamber and greenhouse experiments were purchased from a local nursery in midwinter of each year. All plants were 2 years old, in 3.8-L pots, and remained in cold storage (1 to 2 C) until removed for experimentation. In growth chamber experiments, plants were maintained at a 16:8 light to dark photoperiod. Mature bushes used for field experiments were selected within commercial fields that received similar levels of maintenance and were all located in the main blueberry production region of southwest Michigan, in Ottawa, Allegan, Van Buren, and Berrien Counties. Base temperature of five highbush blueberry cultivars. Five sets of five plants, one from each cultivar, were removed from cold storage and one set was placed in each of five growth chambers set at constant temperatures of either 13, 17, 20, 23, or 26 C. Temperatures were chosen to span the range typically encountered during the period of blueberry bloom in the main regions where this crop is grown. The position of bushes was randomized in each chamber and light levels were recorded once a week using a field scout quantum meter (Spectrum Technologies, Inc., Plainfield, IL) to ensure consistency. Plants were allowed to progress from dormancy through flower bloom. Newly opened flowers were counted every 1 to 2 d and marked with a permanent marker to avoid duplicate counts. Each progression through bloom constituted one replicate, and three to five replicates were conducted for each cultivar/temperature pairing. Only three replicates were completed for the lowest temperature (13 C) as the bloom period was significantly extended. Development rate was calculated as the inverse of the time elapsed between the start of bloom and 50% total bloom. Results were then plotted as temperature vs. development rate for each of five replicates. A one-way analysis of covariance compared the relationship of temperature and development rate for complete replicates (those including at least four temperature3 development rate pairings) among the cultivars (PROC GLM; SAS Institute Inc., Cary, NC) using the development rate as the independent variable. The dependent variable was the temperature and the covariate was the experimental replicate. For each of the five cultivars, base temperature was calculated as the x-intercept of the best fit regression line. Highbush blueberry bloom phenology under greenhouse conditions. Ten potted highbush blueberry plants of each of the five cultivars were maintained at greenhouse temperatures of 15 ± 5 C. Temperature data were recorded using two HOBO pendant temperature loggers (Onset Corporation, Bourne, MA) suspended at plant height in the greenhouse. To account for differences in base temperature among cultivars, air temperature data and individual cultivar base temperatures determined in the experiment described above were used to calculate accumulated GDD values. Accumulated GDD was measured from the time plants were removed from cold storage and placed in the greenhouse. Numbers of newly opened flowers were counted daily on each bush and marked with a permanent marker to avoid duplicate counts. Highbush blueberry bloom phenology under field conditions. To observe highbush blueberry bloom under field conditions, three separate blueberry plantings in southwest Michigan were sampled during the 2009 and 2010 field seasons. Sites were chosen based on the availability of the five cultivars of interest being planted in close proximity. In 2009, the three sites sampled were located at the Southwest Michigan Research and Extension Center in Benton Harbor, the Michigan Blueberry Growers Association (MBG) headquarters in Grand Junction, and the Trevor Nichols Research Complex in Fennville. In 2010, the three sites sampled were located at the MBG headquarters in Grand Junction, Cornerstone Ag. in Lacota, and DeGrandchamp Farms in South Haven. Each site was equipped with a HOBO Weather Station (Onset Corporation) that monitored on-site temperature conditions 1.5 m aboveground level. To determine the progression of flower bloom as a function of temperature, bushes from each of the five cultivars were monitored for flower opening throughout the period of bloom while simultaneously collecting air temperature data at the three individual sites. At each site, 12 flower clusters in each of three plots per cultivar were flagged and monitored for flower opening (a total of 36 clusters per cultivar). For each plot, four flower clusters were flagged near the apical tip of a shoot, another four were flagged along the middle of a shoot, and the final four were flagged near the base of a shoot. Newly opened flowers from selected clusters were counted two to three times a week and marked with a permanent marker to keep track of which flowers had opened recently. Flagged flower clusters were observed throughout the entire period of bloom. Again, individual cultivar base temperatures determined previously were used to calculate accumulated GDD values, beginning on 1 Jan. of each year. For all bloom phenology experiments, the relationship between percent total bloom and accumulated GDD for each cultivar was first analyzed using linear regression. No significant linear relationships were identified for either the original or transformed data taken from the greenhouse or field. The data were then plotted as percent total bloom vs. accumulated GDD for each cultivar to distinguish possible non-linear relationships. Gaussian, gamma, and logistic nonlinear regression analyses were performed and parameters were compared among these non-linear curve types (PROC NLIN; SAS Institute Inc.). Although variations of each of these regressions fit the majority of phenology curves, only the logistic function was able to describe the relationships between percent total bloom (%TB) and accumulated GDDs for each of the 15 individual curves. The PROC NLIN function was used to fit the following general logistic function to each curve: