Advertisement
ASHS 2024 Annual Conference

 

Evaluating Various Colors of Persistent Luminescent Powders on Rose Cut Flowers

Authors:
Abby Pace Department of Horticulture and Landscape Architecture, Oklahoma State University, 358 Ag Hall, Stillwater, OK 74078-6027, USA

Search for other papers by Abby Pace in
This Site
Google Scholar
Close
,
Bruce L. Dunn Department of Horticulture and Landscape Architecture, Oklahoma State University, 358 Ag Hall, Stillwater, OK 74078-6027, USA

Search for other papers by Bruce L. Dunn in
This Site
Google Scholar
Close
, and
Charles Fontanier Department of Horticulture and Landscape Architecture, Oklahoma State University, 358 Ag Hall, Stillwater, OK 74078-6027, USA

Search for other papers by Charles Fontanier in
This Site
Google Scholar
Close

Abstract

Rose cut flowers are popular in everyday bouquets or for special occasions, and tinting of the flowers by means of color addition increases the flowers economical value and aesthetic appeal. This study evaluated red and white luminescent rose cut flowers, which was achieved by applying six persistent luminescent powders. Solutions of each color were prepared by mixing 6 g of powder and 240 ml of deionized water and sprayed four times around the flower head plus a control. Images were taken of the flowers before ultraviolet blacklight exposure and after exposure to be later analyzed with ImageJ software. Daily measurements were taken including vase weight, average floral diameter, and visual deterioration based on scale of 1 to 4. Overall measurements included mean brightness; red, green, and blue measured values; dominant wavelengths of emitted color; flower diameter change rate; relative water percent; solution uptake rate; and vase solution uptake rate. For luminescent brightness mean without ultraviolet, white rose with blue powder had the greatest value. For luminescent brightness after ultraviolet exposure, white rose with green powder had the greatest value. With ultraviolet exposure, white roses with green powder had the greatest value followed by blue, orange, and white. Red powder on white and red roses experienced little to no luminescence before or after ultraviolet exposure. Mean and mode varied in their calculated dominant wavelengths; therefore, it is recommended to use mean values because more similarities in matching of the powder color and the calculated dominant wavelength were reported. Ultimately, white roses are preferred because they seemed to have greater health and luminescence compared with red roses, and green and blue powder would be recommended for luminescent application for brightness.

Roses are a part of the genus Rosa L., which is composed of more than 140 species (Synge 1971). The wholesale value of cut roses produced in the United States was valued at $12 million in 2020 (US Department of Agriculture 2021). The flowers offer beautification and aesthetic merit, which contributes to the overall commercial and economical value of the plant (Önder et al. 2022). Furthermore, floral purchases are greatest during the holidays as illustrated by the sales during Christmas and Hanukkah amounting to $2.28 billion and Valentine’s Day and Mother’s Day at $1.9 billion (Silady 2019). Value addition techniques, such as color tinting, contribute to economic growth in the floriculture market by increasing the flowers’ value 5 to 10 times the original market value (Mekala et al. 2012). Tinting allows for visual enhancement in florals that are otherwise lacking in color and, therefore, visual appeal (Sowmeya et al. 2017).

One value addition technique to consider is the use of persistent luminescent powders, which offer a colored luminescence to the flowers in a dark environment. Luminescence, specifically photoluminescence, is when light is emitted by a given substance from an electronically excited state as exacted by an external source (Jaque and Vertrone 2012). Persistent luminescent is light emission that exists after excitation (Chiatti et al. 2021). Photoluminescent materials that offer afterglow can absorb ultraviolet and visible lights and can release that energy at a certain wavelength within darkness (Gao et al. 2009). Afterglow is when a material emits light in the various spectral regions and the continuous emission time can vary from seconds to hours even after the photons have been excited by an external source (Li et al. 2016). Photoluminescent materials have trapping mechanisms that capture the energy from ultraviolet light for subsequent release in the form of afterglow (Van der Heggen et al. 2022). Strontium aluminate phosphors are common materials used to create high-quality photoluminescence and color emission (Swathi et al. 2023). Various colored luminescent powders are achieved by altering the preparation and the chemical makeup of doped strontium aluminate phosphors with europium and dysprosium for example (Haranath et al. 2003; Khattab et al. 2018; Peng et al. 2022). Red luminescence can be obtained by the excitation of CaS:Eu2+, Tm3+ phosphor, and persistent luminescence is observed in the 400 to 600 nm wavelengths (Tamura et al. 2020). Furthermore, white powder can be achieved by tridoped Gd3Ga5O12 with Pr3+, Tb3+, Eu3+, and a cool-white luminescence is achieved by combining Pr3+ and Tb3+ luminescent centers in the GGG: Pr3+, Tb3+, Eu3+ phosphors (Ueda et al. 2020). Strontium aluminate phosphors are common materials used to create high-quality photoluminescence and color emission (Swathi et al. 2023). Various colored luminescent powders are achieved by altering the preparation and the chemical makeup of strontium aluminate phosphors doped with the europium and dysprosium (Haranath et al. 2003; Khattab et al. 2018; Peng et al. 2022).

Image and other color software programs can be used to analyze color of an image in terms of brightness and color emission. ImageJ is an imaging analysis program in the public domain that has been used in a multitude of studies to analyze and quantify variables within pictures (Abràmoff et al. 2004). ImageJ can measure brightness of an image by reporting the mean gray value, which is the number of gray values of the pixels divided by the number of pixels (Rasband and Ferreira 2012). Red, green, and blue values represent color in imaging systems and other colors are formed by diversifying different pixel values of these primary colors (Strock 2021). The dominant wavelength of the emitted color is calculated using color matching mathematical functions curated by the Commission Internationale de l’Eclairage (CIE) in 1931 from the modal RGB values reported using ImageJ (Strock et al. 2019; Wang et al. 2021). The CIE Calculator can be used to convert across independent color spaces, including RGB color spaces, to CIE representations to determine spectrum wavelengths (Lindbloom 2012).

Various studies have researched and incorporated luminescence in root tissues, leaves and fruits, ceramic surfaces, fabrics, and information encryption (Defrianto et al. 2022; Gao et al. 2009; Khattab et al. 2018; Strock et al. 2019; Swathi et al. 2023). The persistent luminescence of cut flowers has recently been reported using green luminescence by means of glow-in-the-dark spray paint and highlighters (Pace et al. 2022b) and blue luminescence by dip and spray of using a blue glow-in-the-dark powder in a water-based solution (Pace et al. 2022a). Both studies were limited to white carnation flowers and solely tested green and blue colored luminescence. This current study aims to evaluate multiple persistent luminescent powders by quantifying the brightness of the powders, to determine the dominant wavelength of the emitted colors, and to evaluate the response of red and white roses to the powders.

Materials and Methods

Plant material.

Red and white rose (Rosa sp.) cut flowers were received from Bear Creek Farms (Stillwater, OK, USA) on 6 May 2022 from a cooler set at 3.3 °C. The stems were then kept in a cooler at the Greenhouse Learning Center at Oklahoma State University at 4.4 °C (Stillwater, OK, USA). On 9 May 2022, the stems were cut to 40 cm at a 45° angle with leaves removed from the lower 10 cm of the stem. The stems were then placed into fluted glass bud vases, one flower per vase, filled with 240 ml deionized water and 2 g of floral preservative (Syndicate Sales Inc., Kokoma, IN, USA).

Experimental setting and treatments.

Vases were kept in a climate-controlled room at a consistent temperature of 21.1 °C and fluorescent lighting. On 9 May 2022, treatments of 6 g of white, red (juice red), green, orange (orange-red), and blue (blue-purple) photoluminescent pigment (UniGlow Products LLC, Worthington, IN, USA) were mixed with 240 ml of deionized water to be sprayed four times around the flower at stage 4 of opening (Gao et al. 2016) using a standard spray bottle with the nozzle open one revolution from close (Groundwork Misting Sprayer, Tractor Supply Company, Brentwood, TN, USA). Uniglow Products LLC (n.d.) states that their “Ultra and standard pigment consists of europium and dysprosium doped strontium aluminate” except for their red and pink powders, which are zinc-sulfide based. They characterize their ultra and standard pigments as “Materials are non-toxic, non-radioactive and contain no phosphorus, lead, or any other hazardous chemicals.” Regarding the prestige glow series, which are the pigments used in this study, no information about chemical composition is given except it is a “Quality photoluminescent pigment that is free of formaldehyde and ECO friendly.” A control was added that did not receive any powder treatments.

Data collection.

Measurements were taken daily on vase weight (without flower), average flower diameter (average of two perpendicular measurements with a ruler), and visual deterioration. The vase and vase solution were weighed without the flower and the consecutive variability in weight represents the water loss of that flower as the weight of the bottle remained constant, and in preliminary studies water loss to evaporation was negligible. Visual deterioration was evaluated on a rating score (average daily rating per day) of 1 to 4 for deterioration (1 = no sign of deterioration; 2 = some wilting and color change; 3 = wilting and darkening in color more throughout the flower; 4 = complete shriveled and discolored, petals fallen off, or flower head is bent at the pedicel). For quantification of brightness, images were taken of flowers in darkness using a camera on a smartphone (iPhone 13; Apple, Cupertino, CA, USA). Two images of each flower were collected, one before black-light exposure (flower mean without ultraviolet) and another taken with a 365-nm black light on (Sunlite Industrial Corp., El Monte, CA, USA) and reported as flower mean with ultraviolet. Photos were analyzed for brightness using ImageJ (Rasband 1997–2018) version 1.53j to measure the mean brightness of grayscale values between 0 and 255 of the outlined luminescent flower (Bednarkiewicz et al. 2020). The luminescent colored glow was analyzed using a macro code to determine RGB values (Strock 2021) and the CIE Color Calculator (Lindbloom 2012) to determine the dominant wavelengths of the colored luminescence the flowers were emitting. All photo thresholders were set to the triangle method. Standard mean values of the powders were determined using 6 g of each powder on 92 brightness white copy paper (TRU RED, Framingham, MA, USA) and mixed in 240 ml deionized water in a clear plastic tumbler cup (WebstraurantStore, Lititz, PA, USA) and analyzed by the same procedures previously stated. Images were taken before and after ultraviolet exposure and the dominant wavelengths were analyzed using a minimum threshold method. The experiment was concluded on 19 May 2022 once the majority of the flowers had a deterioration rating of 4.

Calculation on water relations.

Relative fresh water percent (water and vase weight/weight of water and vase day 1) * 100, water uptake rate (daily weight of water and vase/weight of water and vase on day 1), vase solution uptake rate [(previous day water and vase weight) – (current day water and vase weight)]/(water and vase weight day 1), and flower diameter change rate (flower diameter average/flower diameter) * 100 were performed (Lou et al. 2021).

Statistical analysis.

Statistical analysis was performed using SAS/STAT software (Version 9.4; SAS Institute, Cary, NC). Each treatment was applied to a set of three stems and was replicated four times, resulting in 12 vases per treatment per flower color for a total of 144 vases. The vases were arranged in a completely randomized design. Tests of significance were reported at the 0.05, 0.01, and 0.001 level. The data were analyzed using generalized linear mixed models methods. Tukey multiple comparison methods were used to separate the means.

Results and Discussion

A significant day × treatment effect was observed for relative fresh weight percent, solution uptake rate, vase solution uptake rate, luminescence mean without ultraviolet exposure, and luminescence mean with ultraviolet exposure (Table 1). On day 1 for luminescence mean without ultraviolet exposure, white rose treated with blue powder had the greatest value but was only different from white rose with white and orange powder (Fig. 1). On day 2, white rose with blue powder had the greatest value and was greater than white rose with white and orange powder and red rose with white, green, and blue powder. On day 8, red rose treated with orange powder had the smallest value and was different from white rose with white, red, and blue powder and red rose with red powder. For luminescence mean with ultraviolet exposure, white rose with green powder application was greatest and only different from red rose with red powder on day 3 (Fig. 2). On day 6, white rose with green powder was the greatest and different from red and white rose with red powder. For luminescent mean without ultraviolet exposure, white rose with blue powder not only had the greatest values but also visually was the only powder to luminesce before exposure. For luminescence with ultraviolet exposure, white rose with green powder had the greatest luminescent value and white roses with blue powder had the second greatest luminescent value for most of the days. White rose with orange and white powder luminesced but not as bright and was not as consistent among the roses compared with green and blue powder. Red powder was the only one to visually show little to no luminescence before and after ultraviolet exposure as illustrated in both figures (Figs. 1 and 2).

Table 1.

Analysis of variance for flower characteristics, water relations, and brightness after application of persistent luminescent powders of cut-flower roses at the Greenhouse Learning Center (Stillwater, OK, USA) in 2022.

Table 1.
Fig. 1.
Fig. 1.

Treatment × day interaction effect for the flower mean brightness without ultraviolet charge of roses using 6 g of persistent luminescent powder of various colors. The significant difference among treatments on a specific day is represented by an asterisk. rr = red rose; wr = white rose.

Citation: HortScience 58, 11; 10.21273/HORTSCI17282-23

Fig. 2.
Fig. 2.

Treatment × day interaction effect for the flower mean brightness with ultraviolet charge of roses using 6 g of persistent luminescent powder of different colors. The significant difference among treatments on a specific day is represented by an asterisk. rr = red rose; wr = white rose.

Citation: HortScience 58, 11; 10.21273/HORTSCI17282-23

Overall, the white roses had greater luminescent values than the red roses. It can be reasoned that the white roses greater luminescent values over red roses are due to different colored objects have varying capacities to absorb and or reflect different colored wavelengths. An object with a dark background will absorb different wavelengths of light energy and an individual is unable to see the colors reflected, whereas white or lighter backgrounds will reflect most of the wavelengths that is being applied and an individual is able to see the colored wavelength (Straley 2004). Due to the inherent differences in chemical properties of the chemical powders, the spray treatments varied in their intensities and glow durations. It is assumed that because some powder treatments have a weaker composition, they will have lower brightness intensity values when applied at the same rate as all the other powder treatments. It would then be suggested to use greater rates for those chemicals with a weaker composition to account for the lower intensity values expressed when using the same rate across all powder treatments. The effects of increased rates on overall floral health is unknown so should be tested on a few flowers first. The study performed by Shi et al. (2018) had similar findings, as their red emitting phosphors were inferior to their green and blue phosphors, and the different mixtures created by tuning the three emissive colors resulted in an interaction of impact and energy transfer. The study performed by Ksharti and Khare (2014) stated that afterglow luminescence is dependent on the crystal structure of the phosphor, suggesting how materials are synthesized can have a significant effect on the luminescence lifetime. Techno Glow Inc. (Ennis, TX) another company that sells glow powders, reported their powders chemical composition and brightness intensities, further demonstrating the relationship of glow intensity and brightness with the powder’s chemical makeup (Glow in the Dark Powder, 2023). They reported that their green glow-in-the-dark and ultraviolet powder of 50 µm composed of Ultra Glow propriety strontium aluminate, europium, and dysprosium formula after 60 min had an intensity of 207 mcd/m2, whereas their blue powder of 50 µm nonencapsulated pigment, composed after 60 min, had an intensity of 42 mcd/m2. Their invisible orange glow-in-the-dark and ultraviolet powder of 35-µm pigment is an off-white powder based composed of yttrium oxide and after 60 min had an intensity of 11 mcd/m2, and white powder of 35 µm and composed of strontium calcium aluminate oxysulfide europium did not have the glow intensity and duration stated on their website but is similar to the values of the orange powder as they both have a size of 35 µm. Lastly, their red glow-in-the-dark powder of 35 µm and composed of calcium sulfide is the weakest intensity of 1 mcd/m2 after 60 min. Jiang et al. (2020) determined how the grayscale value range of 0 to 255 corresponds to luminance values given in cd/m2 with a grayscale value of 0 correlates to 0.16 cd/m2 and the grayscale value of 255 corelates to 4000 cd/m2 or higher. The pigments used in this study and other similar products contain inorganic ingredients and the powders are unable to degrade naturally, and it is recommended that wastes involving these pigments should be managed and disposed of as hazardous waste.

For relative fresh weight percent, red rose with red and blue powder were the greatest on day 8 and different from white rose with green powder (Fig. 3). On day 9, red roses with white, red, blue, and no powder were greater than white rose with green powder, while white roses with red powder were different from red roses with red and blue powder. Solution uptake rate was greatest for red rose applied with red and blue powder and was different from white rose with green powder on day 8 (Fig. 4). On day 9, red rose treated with white, red, blue, and no powder application were all greater values and different from red rose with green powder, whereas red roses with red and blue powder were greater than white roses with red powder. Relative fresh weight and solution uptake rate had similar interactions, which could be expected because both the calculations compare the water relations of said day back to the first day of the study. Suong et al. (2019) also reported similar fresh weight percent and solution uptake rate water relations for ‘Dolcetto’ rose in that both trends included an increase followed by a decrease for the rest of the study.

Fig. 3.
Fig. 3.

Treatment × day interaction effect for relative fresh weight (%) of roses using 6 g of persistent luminescent powder of different colors. The significant difference among treatments on a specific day is represented by an asterisk. rr = red rose; wr = white rose.

Citation: HortScience 58, 11; 10.21273/HORTSCI17282-23

Fig. 4.
Fig. 4.

Treatment × day interaction effect for overall solution uptake rate (%) of roses using 6 g of persistent luminescent powder of different colors. The significant difference among treatments on a specific day is represented by an asterisk. rr = red rose; wr = white rose.

Citation: HortScience 58, 11; 10.21273/HORTSCI17282-23

Vase solution uptake rate was greatest for white rose with red, green, and blue powder and were only different from red rose with blue powder on day 5 (Fig. 5). Red rose with blue powder had a plant in which the water weight remained the same between days 4 and 5 and thus causing a very small, calculated value that influenced a decline in trend. White rose treated with red, green, and blue powders had the greatest values and were different from red rose with no powder on day 7. On day 8, white rose with red, green, blue, white, and orange were all greater than red rose with no powder. White rose green powder had the greatest value and was different from red rose with no powder application, which had the smallest value on day 9. Other studies reported similar trends for water relations. Regarding relative fresh weight percent, Jiping et al. (2009) researching gerbera (Gerbera jamesonii L.) and Çelikel et al. (2011) focusing on cut strap wattle (Acacia holosericea Cunn. ex G. Don), reported trends of consistent decreases as also noted in this current study’s fresh weight percent figures. For vase solution uptake rate, Jiping et al. (2009) studying gerberas and Ahmad et al. (2011) researching roses, reported a cyclic trend of having an increase and decrease which is similar to this current study’s vase solution uptake rate’s figure.

Fig. 5.
Fig. 5.

Treatment × day interaction effect for vase solution uptake rate of roses using 6 g of persistent luminescent powder of different colors. The significant difference among treatments on a specific day is represented by an asterisk. rr = red rose; wr = white rose.

Citation: HortScience 58, 11; 10.21273/HORTSCI17282-23

Overall, regarding relative fresh weight and solution uptake rate, red rose with red and blue powder were consistently greater than white rose with green powder. For vase uptake, white rose with red, green, and blue powder consistently had greater values than red rose with no powder. Toward the end of the study, the red roses had the greatest rate values when comparing back to day 1 for solution uptake rate and greater percentages for relative fresh weight. Relative fresh weight values of red rose revealed greater percentages from greater dividends from the calculation as the water uptake had a small difference in water uptake amounts when comparing the measurements of said day with day 1. For solution uptake rate, red flowers had little variability in water uptake amounts when comparing the measurements of said day with day 1. Furthermore, of vase solution uptake rate, white flowers had larger variability resulting in significant interactions in water uptake amounts at days 5, 7, 8, and 9 compared with the previous day. Red roses had smaller variability in the uptake of water when comparing back to day 1, causing greater rate and percentage values of the relative fresh weight percent and water uptake rate, and the white roses difference compared with day 1 was greater than the red rose water relations. Ultimately, the white roses had the largest variability in water uptake amounts of its flowers when comparing the water uptake between the days. The differences in water relations among the white and red roses can be reasoned as the white roses were in better health than the red roses rather than it being a powder treatment effect. Gebremedhin’s (2020) findings are in agreement with those of this study in that treatment effects did not significantly influence the vase solution uptake rate and relative fresh weight percent among cut rose ‘Red Sky’ and ‘Blizzard’. Although Tsegaw et al. (2011) reported ‘Red Calypso’ rose exhibited greater solution uptake than ‘Akito’ and reasoned that effects were due to treatment effects and not that some cultivars experienced more water stress than others due to environmental conditions.

Treatment main effects were significant for floral diameter, floral diameter change rate, and quality ratings (Table 2). White rose with blue powder had the greatest value for floral diameter and was different from white rose with no powder and all powder colors with red rose. No significant differences were seen between powder colors and among red roses. Red rose with white powder had the greatest floral diameter change rate value at 165.0% and was greater than all other treatments except for red roses with orange powder.

Table 2.

The treatment main effects on flower characteristics, water relations, and brightness after application of persistent luminescent powders of cut-flower roses at the Greenhouse Learning Center (Stillwater, OK, USA) in 2022.

Table 2.

Generally, for floral diameter change rates, red roses with and without powder treatment had greater values than white roses except for red rose blue powder. This can be explained by cultivar differences because red roses had a large difference due to an increase in diameter of a said day when compared with that flower’s diameter of day 1 and thus larger dividends which increases the analysis estimation of that treatment of flower. White roses had a larger floral diameter value overall. Therefore, a smaller floral diameter in white rose without powder and red roses may have been due to greater variability in flower buds being open or still tight due to floral health (Table 2). Van Doorn et al. (1991) reported that inhibition of flower opening is correlated with a decrease in water potential. Furthermore, Chamani et al. (2005) stated that inhibition of flower opening is associated with shortened vase life, which supports the relationship of this current study between the greater quality ratings of the red rose and the red rose overall health being connected to its smaller floral diameters.

For quality rating measurements (Table 2), red rose with blue powder had the greatest quality rating at 2.6 and was different from white rose with white, red, blue, and no powder and red rose with no powder. Our findings were supported by Tsegaw et al. (2011), whose study found that ‘Akito’ and ‘Viva’ rose cultivars lasted significantly longer (14.6 and 14.4 d) than the ‘Red Calypso’ rose cultivar (13.6 d).

Day main effects were significant for floral diameter, floral diameter change rate, and quality ratings (Table 3). The floral diameter was greatest on day 9 but was different on days 1, 2, and 3. The floral diameter change rate was greatest on day 6 and not different on days 5, 7, 8, and 9. The study conducted by Teklić et al. (2003) reported a continuous decrease in floral diameter over the course of their temperature study for each rose and carnation cultivar. In other studies, Pace et al. (2022a, 2022b) and Kumari et al. (2018) suggest the decrease in floral diameter mid way through the useful life of the flower is due to the treatment effects of color tinting. Reasoning as to why this study’s results did not match those of previous work (Pace et al. 2022a, 2022b) is that cultivar differences had a more significant influence on the roses than the powders, whereas the color treatments did have significant influence on the flowers in previous studies. For quality ratings, day 9 was the greatest but was not different from day 8, which would be expected for ratings to increase over time.

Table 3.

The day main effects on flower characteristics, water relations, and brightness after application of persistent luminescent powders of cut-flower roses at the Greenhouse Learning Center (Stillwater, OK, USA) in 2022.

Table 3.

Quality rating references visual deterioration; however, other quality factors that were not considered are that some treatments were visible and had an odor. Under fluorescent lighting, the powders on the white roses were not obvious but did look like white crystals and almost salt like for all the colors except blue, which appeared as purple droplets on the white petals. Under the same fluorescent lighting, the powders were more visible on the red roses as either white salt-like crystals or white water droplets for all colors except the blue powder, which left faint purple water droplets after spray application. The red powder, due to nitrous oxide being used in its chemical makeup, had a strong and unpleasant odor that lasted at most 3 to 4 d.

On paper, orange had the greatest brightness before ultraviolet and white had the greatest brightness values after ultraviolet (Table 4). Red had the highest brightness before ultraviolet but had the lowest brightness values after ultraviolet when mixed with tap water (Table 5). Machado et al. (2023) reported that powders made with sulfur have low resistance to water and, when in contact with water, the luminescence is suppressed. All powder brightness values increased after ultraviolet exposure on paper and in water, except red, which declined after ultraviolet exposure (Tables 4 and 5). No glow was visual for blue powder before ultraviolet exposure on both paper and mixed in with water (Tables 4 and 5). Brightness values after ultraviolet decreased when placed in water for white, red, and green, whereas orange brightness values remained relatively stable, and blue brightness values increased. The degradation occurs for powders composed of strontium aluminate phosphors doped with Eu2+ and Dy3+, which are chemically unstable in the presence of water and to enhance resistance, encapsulation is often used (Zhu et al. 2009). According to Uniglow’s product website, white, green, juice red, orange, and purple blue (blue) are not encapsulated (Uniglow Products LLC). The calculated dominant wavelengths were similar among all powders before and after ultraviolet except green, which had a wavelength color of green before ultraviolet exposure and a cyan wavelength after ultraviolet. Dominant wavelength colors were consistently reported when on paper and in water except white, for which on paper, the calculated wavelength was yellow and the wavelength when in water was measured to be green. Wavelength colors for green powder before ultraviolet and blue powder after ultraviolet were the only powders where the measured emitted wavelength color matched the powder color. In contrast, powder colors red and orange in all reported measured wavelengths of orange and yellow, respectively, and green after ultraviolet on paper and in water reported a wavelength of cyan resulting in the three powder colors’ measured wavelength range ranking below the powders identified color range according to Nassau (2023). Thermo Fisher Scientific (n.d.) explained that an excited fluorescent molecule emits a lower energy light than the light energy it absorbs; therefore, there is a color spectrum shift between the color of light absorbed and the color of light that is emitted.

Table 4.

The standard mean brightness and color values of the luminescent glow of the persistent luminescent powders on white copy paper (TRU RED, Framingham, MA, USA) background at the Greenhouse Learning Center (Stillwater, OK, USA) in 2022.

Table 4.
Table 5.

The standard mean brightness and color values of the luminescent glow of the persistent luminescent powders mixed in tap water in clear plastic cups at the Greenhouse Learning Center (Stillwater, OK, USA) in 2022.

Table 5.

For calculated wavelength based on mode, green and blue color values matched the identified color powder for white roses with green powder having a green dominant wavelength and white roses with blue powder having a blue dominant wavelength (Table 6). This is also illustrated with the standards of green powder before ultraviolet and blue powder after ultraviolet exposure (Tables 4 and 5). The identified powder color and calculated dominant wavelength did not match for white roses with white and orange powder and red roses with white, green, and blue powders, the calculated wavelengths was cyan; red roses with orange powder also did not match the identified powder color because the calculated wavelength was green. Calculated wavelength based on mean RGB color values matched the identified color powder of blue for white and red rose (Table 7). The calculated wavelength of the standard of blue powder also matched its identified powder color after ultraviolet exposure (Tables 4 and 5). Dominant wavelength and the powder color identification did not match for orange, green, and white powders. For orange and green powders, the calculated dominant wavelength was similar to the powder color as the orange powder wavelength was calculated as yellow for both white and red roses and green powder wavelength was calculated as cyan for both white and red roses. The standards of orange powders calculated wavelength were also yellow when on paper and mixed in water and green powder’s calculated wavelength was cyan after ultraviolet exposure (Tables 4 and 5). White powder was the only treatment in which the wavelength did not match the identified powder color nor did it match across white or red roses. Smaller numbers could be explained by the white balance of the camera. When using an auto white balance from image to image, the camera’s white balance could potentially change slightly from image to image. To have a consistent white balance, consider using a color correction card with color standards including white as white balance standard and incorporating an image analysis software to correct the white balance of images such as OpenCV. A study conducted by Dergachov et al. (2019) was able to create a new algorithm to correct color balance of webcams by featuring high color correction accuracy and function of OpenCV library and Python software.

Table 6.

The mode color values of the luminescent glow of the flowers after application of persistent luminescent powders of cut-flower roses at the Greenhouse Learning Center (Stillwater, OK, USA) in 2022.

Table 6.
Table 7.

The mean color values of the luminescent glow of the flowers after application of persistent luminescent powders of cut-flower roses at the Greenhouse Learning Center (Stillwater, OK, USA) in 2022.

Table 7.

A more likely reason for the smaller RGB numbers and why some of the colors do not match exactly is that despite using an automated threshold to outline the flower, black pixels were still included in the section of the outline or on the edge of the outline of the flower in the image that was analyzed. If black pixels are present, the mode and mean values for color data could be skewed thus producing smaller RGB values. Ahmad et al. (1999) reported similar findings of the intense black color of Soybean mosaic potyvirus (black) would decrease the average RGB values to closer to a value of 0.

By looking at the red, green, and blue channels individually and as distinct channels, ImageJ software is ignoring the relationships between the channels, the combinations, and proportions of these channels that contribute to the overall smaller calculated dominant wavelength values being emitted in the image. Further research should consider looking into methods to address the interrelationships of the RGB channels for better calculation of a more representative dominant color wavelength. In addition, studies could consider analyzing the images in other color spaces such as L*a*b* and HSB to calculate a dominant wavelength based on those spatial values. García-Mateos et al. (2015) identified other color spaces such as RGB, XYZ, L*a*b*, L*u*v*, and HSV and with each of these spaces comes with various ways to represent a color by different number of channels, deciding what channels to use, and the size of histograms.

Conclusions

Overall, white roses with green and blue powder are recommended over other powder color treatments and red roses based on luminescent qualities. Regarding reporting dominant wavelength, the use of mean values is recommended because it showed greater similarity in matching the powder color and the calculated dominant wavelength. Future studies should implement a protocol to ensure consistent health among flowers and use other methods for correcting white balance, segmentation of black pixels, other color spaces, rates of application to increase luminescence of colored powders, and further analysis into the differentiation of mode and mean values.

References Cited

  • Abràmoff MD, Magalhães PJ, Ram SJ. 2004. Image processing with ImageJ. Biophotonics Intl. https://imagej.nih.gov/ij/docs/pdfs/Image_Processing_with_ImageJ.pdf.

  • Ahmad I, Joyce DC, Faragher JD. 2011. Physical stem-end treatment effects on cut rose and acacia vase life and water relations. Postharvest Biol Technol. 59:258264. https://doi.org/10.1016/j.postharvbio.2010.11.001.

    • Search Google Scholar
    • Export Citation
  • Ahmad IS, Reid JF, Paulsen MR, Sinclair JB. 1999. Color classifier for symptomatic soybean seeds using image processing. Plant Dis. 83:320327.

    • Search Google Scholar
    • Export Citation
  • Bednarkiewicz A, Carlos LD, Jaque D, Marciniak L. 2020. Standardizing luminescence nanothermometry for biomedical applications. Nanoscale. 12:1440514421.

    • Search Google Scholar
    • Export Citation
  • Çelikel FG, Joyce DC, Faragher JD. 2011. Inhibitors of oxidative enzymes affect water uptake and vase life of cut Acacia holosericea and Chamelaucium uncinatum stems. Postharvest Biol Technol. 60:149157. https://doi.org/10.1016/j.Postharvbio.2010.12.009.

    • Search Google Scholar
    • Export Citation
  • Chamani AK, Joyce DC, Irving DE, Zamani ZA, Mostofi Y, Kafi M. 2005. Ethylene and anti-ethylene treatment effects on cut ‘First Red’ rose. J Appl Hortic. 1:37.

    • Search Google Scholar
    • Export Citation
  • Chiatti C, Fabiani C, Pisello AL. 2021. Long persistent luminescence: A road map toward promising future developments in energy and environmental science. Annu Rev Mater Res. 51:409433. https://doi.org/10.1146/annurev-matsci-091520-011838.

    • Search Google Scholar
    • Export Citation
  • Defrianto D, Shiddiq M, Malik U, Asyana V, Soerbakti Y. 2022. Fluorescence spectrum analysis on leaf and fruit using the ImageJ software application. Sin Tech Comm J. 3:16.

    • Search Google Scholar
    • Export Citation
  • Dergachov K, Krasnov L , Cheliadin O, Plakhotnyi O. 2019. Web-cameras stereo pairs color correction method and its practical implementation. Adv Info System. 3(1):2942. https://doi.org/10.20998/2522-9052.2019.1.06.

    • Search Google Scholar
    • Export Citation
  • Gao F, Xiong Z, Xue H, Liu Y. 2009. Improved performance of strontium aluminate luminous coating on the ceramic surface. J Phys Conf Ser. 152:012082. https://doi.org/10.1088/1742-6596/152/1/012082.

    • Search Google Scholar
    • Export Citation
  • Gao Y, Liu C, Li X, Xu H, Liang Y, Ma N, Fei Z, Gao J, Jiang CZ, Ma C. 2016. Transcriptome profiling of petal abscission zone and functional analysis of an Aux/IAA Family gene RhIAA16 involved in petal shedding in rose. Front. Plant Sci. 7:1375.

    • Search Google Scholar
    • Export Citation
  • García-Mateos G, Hernández-Hernández JL, Escarabajal-Henarejos D, Jaén-Terrones S, Molina-Martínez JM. 2015. Study and comparison of color models for automatic image analysis in irrigation management applications. Agr Water Manage. 151:158166. https://doi.org/10.1016/j.agwat.2014.08.010.

    • Search Google Scholar
    • Export Citation
  • Gebremedhin H. 2020. Effects of aluminum sulphate, ethanol, sucrose and their combination on the longevity and physiological properties of rose (Rosa hybrida L.) cut flowers. J Hortic Res. 28:2938. https://doi.org/10.2478/johr-2020-0013.

    • Search Google Scholar
    • Export Citation
  • Haranath D, Shanker V, Chander H, Sharma P. 2003. Tuning of emission colours in strontium aluminate long persisting phosphor. J Phys D Appl Phys. 36:22442248. https://doi.org/10.1088/0022-3727/36/18/012.

    • Search Google Scholar
    • Export Citation
  • Jaque D, Vetrone F. 2012. Luminescence nanothermometry. Nanoscale. 4:43014326. https://doi.org/10.1039/C2NR30764B.

  • Jiang Y, Liu Z, Li Y, Lian Y, Liao N, Li Z, Zhao Z. 2020. A digital grayscale generation equipment for image display standardization. Appl Sci (Basel). 10:2297. https://doi.org/10.3390/app10072297.

    • Search Google Scholar
    • Export Citation
  • Jiping L, He S, Zhang Z, Cao J, Lv P, He S, Cheng G, Joyce DC. 2009. Nano-silver pulse treatments inhibit stem-end bacteria on cut gerbera cv. Ruikou flowers. Postharvest Biol Technol. 54:5962. https://doi.org/10.1016/j.postharvbio.2009.05.004.

    • Search Google Scholar
    • Export Citation
  • Khattab TA, Rehan M, Hamouda T. 2018. Smart textile framework: Photochromic and fluorescent cellulosic fabric printed by strontium aluminate pigment. Carbohydr Polym. 195:143152. https://doi.org/10.1016/j.carbpol.2018.04.084.

    • Search Google Scholar
    • Export Citation
  • Kshatri DS, Khare A. 2014. Comparative study of optical and structural properties of micro- and nanocrystalline SrAl2O4:Eu2+, Dy3+ phosphors. J Lumin. 155:257268.

    • Search Google Scholar
    • Export Citation
  • Kumari S, Deepika BR, Sarika K, Deb P. 2018. Value addition of tuberose (Polianthes tuberosa L.) cv. Calcutta Double cut flower by colouring with edible dyes. Chem Sci Rev. Lett. 7:158164.

    • Search Google Scholar
    • Export Citation
  • Li Y, Gecevicius M, Qiu J. 2016. Long persistent phosphors—from fundamentals to applications. Chem Soc Rev. 45:20902136. https://doi.org/10.1039/c5cs00582e.

    • Search Google Scholar
    • Export Citation
  • Lindbloom B. 2012. CIE color calculator. http://www.brucelindbloom.com.

  • Lou X, Anwar M, Wang Y, Zhang H, Ding J. 2021. Impact of inorganic salts on vaselife and postharvest qualities of the cut flower of perpetual carnation. Braz J Biol. 81:228236. https://doi.org/10.1590/1519-6984.221502.

    • Search Google Scholar
    • Export Citation
  • Machado RCL, Fonseca KT, Teixeira VC, Catalani LH, Rodrigues LCV. 2023. Development of a red persistent luminescent composite: Electrospun nanofiber polymer coating prevents emission quenching by water. Mater Today Commun. 35:105965. https://doi.org/10.1016/j.mtcomm.

    • Search Google Scholar
    • Export Citation
  • Mekala P, Ganga M, Jawaharlal M. 2012. Artificial coloring of tuberose flowers for value addition. South Indian Hortic. 60:216223.

  • Nassau K. 2023. Colour. Encyclopaedia Britannica. https://www.britannica.com/science/color. [accessed 6 Sep 2023].

  • Önder S, Tonguç M, Erbaş S, Önder D, Mutlucan M. 2022. Investigation of phenological, primary and secondary metabolites changes during flower developmental of Rosa damascena. Plant Physiol Biochem. 192:2034. https://doi.org/10.1016/j.plaphy.

    • Search Google Scholar
    • Export Citation
  • Pace A, Dunn BL, Fontanier C. 2022a. Blue phosphorescence of standard cut flower carnation. HortScience. 57:13341335. https://doi.org/10.21273/HORTSCI16737-22.

    • Search Google Scholar
    • Export Citation
  • Pace A, Dunn BL, Fontanier C, Goad C, Singh H. 2022b. Cut flower carnation photoluminescence: Potential new value-added product. HortScience. 57:491496. https://doi.org/10.21273/HORTSCI16402-21.

    • Search Google Scholar
    • Export Citation
  • Peng H, Xie G, Cao Y, Zhang L, Yan X, Zhang X, Miao S, Tao Y, Li H, Zheng C, Huang W, Chen R. 2022. On-demand modulating afterglow color of water-soluble polymers through phosphorescence fret for multicolor security printing. Sci Adv. 8. https://doi.org/10.1126/sciadv.abk2925.

    • Search Google Scholar
    • Export Citation
  • Rasband WS. 1997–2018. ImageJ. US National Institutes of Health, Bethesda, MD, USA. https://imagej.nih.gov/ij/.

  • Rasband W, Ferreira T. 2012. ImageJ user guide—IJ 1.46R. US National Institutes of Health, Bethesda, MD, USA. https://imagej.nih.gov/ij/docs/guide/.

  • Shi C, Zhu Y, Zhu G, Shen Z, Ge M. 2018. Phototunable full-color emission of dynamic luminescent materials. J Mater Chem. 6:95529560. https://doi.org/10.1039/C8TC02955E.

    • Search Google Scholar
    • Export Citation
  • Silady A. 2019. The economics of flowers. SmartAsset. https://smartasset.com/insights/the-economics-of-flowers. [accessed 5 Sep 2023].

  • Sowmeya S, Kumaresan S, Priya L. 2017. Effect of multi colours in tinting techniques in cut flowers (rose and carnation). Chem Sci Rev. Lett. 6:22502253.

    • Search Google Scholar
    • Export Citation
  • Straley JP. 2004. Online physics for teachers, the light course. University of Kentucky. http://www.pa.uky.edu/sciworks/ intro.htm. [accessed 5 Sep 2023].

  • Strock CF. 2021. protocol for extracting basic color metrics from Images in ImageJ/Fiji. Zenodo. https://zenodo.org/record/5595203#.Y8xgQuzMLt1.

    • Search Google Scholar
    • Export Citation
  • Strock CF, Schneider HM, Galindo-Castañeda T, Hall BT, Van Gansbeke B, Mather DE, Roth MG, Chilvers MI, Guo X, Brown K, Lynch JP. 2019. Laser ablation tomography for visualization of root colonization by edaphic organisms. J Expt Bot. 70:53275342. https://doi.org/10.1093/jxb/erz271.

    • Search Google Scholar
    • Export Citation
  • Suong T, Ha T, Lim JH, In BC. 2019. Extension of the vase life of cut roses by both improving water relations and repressing ethylene responses. Hortic Sci Technol. 37(1):6577. https://doi.org/10.12972/kjhst.20190007.

    • Search Google Scholar
    • Export Citation
  • Swathi BN, Radha Krushna BR, Hariprasad SA, Srikanth C, Subramanian B, Daruka Prasad B, Nagabhushana H. 2023. Designing vivid green Sr9Al6O18:Er3+ phosphor for information encryption and nUV excitable cool-white LED applications. J Lumin. 257:119618. https://doi.org/10.1016/j.jlumin.2022.119618.

    • Search Google Scholar
    • Export Citation
  • Synge PM. 1971. The dictionary of rose in color, p 191. Madison Square Press, New York, NY, USA.

  • Tamura Y, Okuno T, Suda Y, Nanai Y. 2020. Red persistent luminescence excited by visible light in CaS:Eu2+,Tm3+. J Phys D Appl Phys. 53:155101. https://doi.org/10.1088/1361-6463/ab6d1c.

    • Search Google Scholar
    • Export Citation
  • Techno Glow Inc. 2023. Glow in the dark powder. https://www.technoglowproducts.com/glow-in-the-dark-powder/. [accessed 5 Sep 2023].

  • Teklić T, Parađiković N, Vukadinović V. 2003. The influence of temperature on flower opening, vase life and transpiration of cut roses and carnations. Acta Hortic. 624:405411. https://doi.org/10.17660/ActaHortic.2003.624.57.

    • Search Google Scholar
    • Export Citation
  • Tsegaw T, Tilahun S, Humphries G. 2011. Influence of pulsing biocides and preservative solution treatment on the vase life of cut rose (Rosa hybrida L.) varieties. Sci Technol Arts Res J. 2:115.

    • Search Google Scholar
    • Export Citation
  • Ueda J, Miyano S, Xu J, Dorenbos P, Tanabe S. 2020. Development of white persistent phosphors by manipulating lanthanide ions in gadolinium gallium garnets. Adv Photonics. 2:2000102. https://doi.org/10.1002/adpr.202000102.

    • Search Google Scholar
    • Export Citation
  • US Department of Agriculture. 2021. Floriculture crops 2020 summary. USDA Economics, Statistics and Market Information System. https://usda.library.cornell.edu/?locale=en. [accessed 5 Sep 2023].

  • Van der Heggen D, Joos JJ, Feng A, Fritz V, Delgado T, Gartmann N, Walfort B, Rytz D, Hagemann H, Poelman D, Viana B, Smet PF. 2022. Persistent luminescence in strontium aluminate: A roadmap to a brighter future. Adv Funct Mater. 32:2208809. https://doi.org/10.1002/adfm.202208809.

    • Search Google Scholar
    • Export Citation
  • Van Doorn WG, De Stigter HCM, De Witte Y, Boekestein A. 1991. Micro-organisms at the cut surface and xylem vessels of rose stems: A scanning electron microscope study. J Appl Bacteriol. 70:3439.

    • Search Google Scholar
    • Export Citation
  • Wang R, Ruan G, Sun Y, Zhao D, Yu H, Zhang C, Li L, Liu J. 2021. A full-wavelength coverage colorimetric sensor depending on polymer-carbon nanodots from blue to red for visual detection of nitrite via smartphone. Dyes Pigments. 191:109383. https://doi.org/10.1016/j.dyepig.2021.109383.

    • Search Google Scholar
    • Export Citation
  • Zhu Y, Zeng J, Li W, Liu Y. 2009. Encapsulation of strontium aluminate phosphors to enhance water resistance and luminescence. Appl Surf Sci. 255:75807585. https://doi.org/10.1016/j.apsusc.2009.04.031.

    • Search Google Scholar
    • Export Citation
  • Fig. 1.

    Treatment × day interaction effect for the flower mean brightness without ultraviolet charge of roses using 6 g of persistent luminescent powder of various colors. The significant difference among treatments on a specific day is represented by an asterisk. rr = red rose; wr = white rose.

  • Fig. 2.

    Treatment × day interaction effect for the flower mean brightness with ultraviolet charge of roses using 6 g of persistent luminescent powder of different colors. The significant difference among treatments on a specific day is represented by an asterisk. rr = red rose; wr = white rose.

  • Fig. 3.

    Treatment × day interaction effect for relative fresh weight (%) of roses using 6 g of persistent luminescent powder of different colors. The significant difference among treatments on a specific day is represented by an asterisk. rr = red rose; wr = white rose.

  • Fig. 4.

    Treatment × day interaction effect for overall solution uptake rate (%) of roses using 6 g of persistent luminescent powder of different colors. The significant difference among treatments on a specific day is represented by an asterisk. rr = red rose; wr = white rose.

  • Fig. 5.

    Treatment × day interaction effect for vase solution uptake rate of roses using 6 g of persistent luminescent powder of different colors. The significant difference among treatments on a specific day is represented by an asterisk. rr = red rose; wr = white rose.

  • Abràmoff MD, Magalhães PJ, Ram SJ. 2004. Image processing with ImageJ. Biophotonics Intl. https://imagej.nih.gov/ij/docs/pdfs/Image_Processing_with_ImageJ.pdf.

  • Ahmad I, Joyce DC, Faragher JD. 2011. Physical stem-end treatment effects on cut rose and acacia vase life and water relations. Postharvest Biol Technol. 59:258264. https://doi.org/10.1016/j.postharvbio.2010.11.001.

    • Search Google Scholar
    • Export Citation
  • Ahmad IS, Reid JF, Paulsen MR, Sinclair JB. 1999. Color classifier for symptomatic soybean seeds using image processing. Plant Dis. 83:320327.

    • Search Google Scholar
    • Export Citation
  • Bednarkiewicz A, Carlos LD, Jaque D, Marciniak L. 2020. Standardizing luminescence nanothermometry for biomedical applications. Nanoscale. 12:1440514421.

    • Search Google Scholar
    • Export Citation
  • Çelikel FG, Joyce DC, Faragher JD. 2011. Inhibitors of oxidative enzymes affect water uptake and vase life of cut Acacia holosericea and Chamelaucium uncinatum stems. Postharvest Biol Technol. 60:149157. https://doi.org/10.1016/j.Postharvbio.2010.12.009.

    • Search Google Scholar
    • Export Citation
  • Chamani AK, Joyce DC, Irving DE, Zamani ZA, Mostofi Y, Kafi M. 2005. Ethylene and anti-ethylene treatment effects on cut ‘First Red’ rose. J Appl Hortic. 1:37.

    • Search Google Scholar
    • Export Citation
  • Chiatti C, Fabiani C, Pisello AL. 2021. Long persistent luminescence: A road map toward promising future developments in energy and environmental science. Annu Rev Mater Res. 51:409433. https://doi.org/10.1146/annurev-matsci-091520-011838.

    • Search Google Scholar
    • Export Citation
  • Defrianto D, Shiddiq M, Malik U, Asyana V, Soerbakti Y. 2022. Fluorescence spectrum analysis on leaf and fruit using the ImageJ software application. Sin Tech Comm J. 3:16.

    • Search Google Scholar
    • Export Citation
  • Dergachov K, Krasnov L , Cheliadin O, Plakhotnyi O. 2019. Web-cameras stereo pairs color correction method and its practical implementation. Adv Info System. 3(1):2942. https://doi.org/10.20998/2522-9052.2019.1.06.

    • Search Google Scholar
    • Export Citation
  • Gao F, Xiong Z, Xue H, Liu Y. 2009. Improved performance of strontium aluminate luminous coating on the ceramic surface. J Phys Conf Ser. 152:012082. https://doi.org/10.1088/1742-6596/152/1/012082.

    • Search Google Scholar
    • Export Citation
  • Gao Y, Liu C, Li X, Xu H, Liang Y, Ma N, Fei Z, Gao J, Jiang CZ, Ma C. 2016. Transcriptome profiling of petal abscission zone and functional analysis of an Aux/IAA Family gene RhIAA16 involved in petal shedding in rose. Front. Plant Sci. 7:1375.

    • Search Google Scholar
    • Export Citation
  • García-Mateos G, Hernández-Hernández JL, Escarabajal-Henarejos D, Jaén-Terrones S, Molina-Martínez JM. 2015. Study and comparison of color models for automatic image analysis in irrigation management applications. Agr Water Manage. 151:158166. https://doi.org/10.1016/j.agwat.2014.08.010.

    • Search Google Scholar
    • Export Citation
  • Gebremedhin H. 2020. Effects of aluminum sulphate, ethanol, sucrose and their combination on the longevity and physiological properties of rose (Rosa hybrida L.) cut flowers. J Hortic Res. 28:2938. https://doi.org/10.2478/johr-2020-0013.

    • Search Google Scholar
    • Export Citation
  • Haranath D, Shanker V, Chander H, Sharma P. 2003. Tuning of emission colours in strontium aluminate long persisting phosphor. J Phys D Appl Phys. 36:22442248. https://doi.org/10.1088/0022-3727/36/18/012.

    • Search Google Scholar
    • Export Citation
  • Jaque D, Vetrone F. 2012. Luminescence nanothermometry. Nanoscale. 4:43014326. https://doi.org/10.1039/C2NR30764B.

  • Jiang Y, Liu Z, Li Y, Lian Y, Liao N, Li Z, Zhao Z. 2020. A digital grayscale generation equipment for image display standardization. Appl Sci (Basel). 10:2297. https://doi.org/10.3390/app10072297.

    • Search Google Scholar
    • Export Citation
  • Jiping L, He S, Zhang Z, Cao J, Lv P, He S, Cheng G, Joyce DC. 2009. Nano-silver pulse treatments inhibit stem-end bacteria on cut gerbera cv. Ruikou flowers. Postharvest Biol Technol. 54:5962. https://doi.org/10.1016/j.postharvbio.2009.05.004.

    • Search Google Scholar
    • Export Citation
  • Khattab TA, Rehan M, Hamouda T. 2018. Smart textile framework: Photochromic and fluorescent cellulosic fabric printed by strontium aluminate pigment. Carbohydr Polym. 195:143152. https://doi.org/10.1016/j.carbpol.2018.04.084.

    • Search Google Scholar
    • Export Citation
  • Kshatri DS, Khare A. 2014. Comparative study of optical and structural properties of micro- and nanocrystalline SrAl2O4:Eu2+, Dy3+ phosphors. J Lumin. 155:257268.

    • Search Google Scholar
    • Export Citation
  • Kumari S, Deepika BR, Sarika K, Deb P. 2018. Value addition of tuberose (Polianthes tuberosa L.) cv. Calcutta Double cut flower by colouring with edible dyes. Chem Sci Rev. Lett. 7:158164.

    • Search Google Scholar
    • Export Citation
  • Li Y, Gecevicius M, Qiu J. 2016. Long persistent phosphors—from fundamentals to applications. Chem Soc Rev. 45:20902136. https://doi.org/10.1039/c5cs00582e.

    • Search Google Scholar
    • Export Citation
  • Lindbloom B. 2012. CIE color calculator. http://www.brucelindbloom.com.

  • Lou X, Anwar M, Wang Y, Zhang H, Ding J. 2021. Impact of inorganic salts on vaselife and postharvest qualities of the cut flower of perpetual carnation. Braz J Biol. 81:228236. https://doi.org/10.1590/1519-6984.221502.

    • Search Google Scholar
    • Export Citation
  • Machado RCL, Fonseca KT, Teixeira VC, Catalani LH, Rodrigues LCV. 2023. Development of a red persistent luminescent composite: Electrospun nanofiber polymer coating prevents emission quenching by water. Mater Today Commun. 35:105965. https://doi.org/10.1016/j.mtcomm.

    • Search Google Scholar
    • Export Citation
  • Mekala P, Ganga M, Jawaharlal M. 2012. Artificial coloring of tuberose flowers for value addition. South Indian Hortic. 60:216223.

  • Nassau K. 2023. Colour. Encyclopaedia Britannica. https://www.britannica.com/science/color. [accessed 6 Sep 2023].

  • Önder S, Tonguç M, Erbaş S, Önder D, Mutlucan M. 2022. Investigation of phenological, primary and secondary metabolites changes during flower developmental of Rosa damascena. Plant Physiol Biochem. 192:2034. https://doi.org/10.1016/j.plaphy.

    • Search Google Scholar
    • Export Citation
  • Pace A, Dunn BL, Fontanier C. 2022a. Blue phosphorescence of standard cut flower carnation. HortScience. 57:13341335. https://doi.org/10.21273/HORTSCI16737-22.

    • Search Google Scholar
    • Export Citation
  • Pace A, Dunn BL, Fontanier C, Goad C, Singh H. 2022b. Cut flower carnation photoluminescence: Potential new value-added product. HortScience. 57:491496. https://doi.org/10.21273/HORTSCI16402-21.

    • Search Google Scholar
    • Export Citation
  • Peng H, Xie G, Cao Y, Zhang L, Yan X, Zhang X, Miao S, Tao Y, Li H, Zheng C, Huang W, Chen R. 2022. On-demand modulating afterglow color of water-soluble polymers through phosphorescence fret for multicolor security printing. Sci Adv. 8. https://doi.org/10.1126/sciadv.abk2925.

    • Search Google Scholar
    • Export Citation
  • Rasband WS. 1997–2018. ImageJ. US National Institutes of Health, Bethesda, MD, USA. https://imagej.nih.gov/ij/.

  • Rasband W, Ferreira T. 2012. ImageJ user guide—IJ 1.46R. US National Institutes of Health, Bethesda, MD, USA. https://imagej.nih.gov/ij/docs/guide/.

  • Shi C, Zhu Y, Zhu G, Shen Z, Ge M. 2018. Phototunable full-color emission of dynamic luminescent materials. J Mater Chem. 6:95529560. https://doi.org/10.1039/C8TC02955E.

    • Search Google Scholar
    • Export Citation
  • Silady A. 2019. The economics of flowers. SmartAsset. https://smartasset.com/insights/the-economics-of-flowers. [accessed 5 Sep 2023].

  • Sowmeya S, Kumaresan S, Priya L. 2017. Effect of multi colours in tinting techniques in cut flowers (rose and carnation). Chem Sci Rev. Lett. 6:22502253.

    • Search Google Scholar
    • Export Citation
  • Straley JP. 2004. Online physics for teachers, the light course. University of Kentucky. http://www.pa.uky.edu/sciworks/ intro.htm. [accessed 5 Sep 2023].

  • Strock CF. 2021. protocol for extracting basic color metrics from Images in ImageJ/Fiji. Zenodo. https://zenodo.org/record/5595203#.Y8xgQuzMLt1.

    • Search Google Scholar
    • Export Citation
  • Strock CF, Schneider HM, Galindo-Castañeda T, Hall BT, Van Gansbeke B, Mather DE, Roth MG, Chilvers MI, Guo X, Brown K, Lynch JP. 2019. Laser ablation tomography for visualization of root colonization by edaphic organisms. J Expt Bot. 70:53275342. https://doi.org/10.1093/jxb/erz271.

    • Search Google Scholar
    • Export Citation
  • Suong T, Ha T, Lim JH, In BC. 2019. Extension of the vase life of cut roses by both improving water relations and repressing ethylene responses. Hortic Sci Technol. 37(1):6577. https://doi.org/10.12972/kjhst.20190007.

    • Search Google Scholar
    • Export Citation
  • Swathi BN, Radha Krushna BR, Hariprasad SA, Srikanth C, Subramanian B, Daruka Prasad B, Nagabhushana H. 2023. Designing vivid green Sr9Al6O18:Er3+ phosphor for information encryption and nUV excitable cool-white LED applications. J Lumin. 257:119618. https://doi.org/10.1016/j.jlumin.2022.119618.

    • Search Google Scholar
    • Export Citation
  • Synge PM. 1971. The dictionary of rose in color, p 191. Madison Square Press, New York, NY, USA.

  • Tamura Y, Okuno T, Suda Y, Nanai Y. 2020. Red persistent luminescence excited by visible light in CaS:Eu2+,Tm3+. J Phys D Appl Phys. 53:155101. https://doi.org/10.1088/1361-6463/ab6d1c.

    • Search Google Scholar
    • Export Citation
  • Techno Glow Inc. 2023. Glow in the dark powder. https://www.technoglowproducts.com/glow-in-the-dark-powder/. [accessed 5 Sep 2023].

  • Teklić T, Parađiković N, Vukadinović V. 2003. The influence of temperature on flower opening, vase life and transpiration of cut roses and carnations. Acta Hortic. 624:405411. https://doi.org/10.17660/ActaHortic.2003.624.57.

    • Search Google Scholar
    • Export Citation
  • Tsegaw T, Tilahun S, Humphries G. 2011. Influence of pulsing biocides and preservative solution treatment on the vase life of cut rose (Rosa hybrida L.) varieties. Sci Technol Arts Res J. 2:115.

    • Search Google Scholar
    • Export Citation
  • Ueda J, Miyano S, Xu J, Dorenbos P, Tanabe S. 2020. Development of white persistent phosphors by manipulating lanthanide ions in gadolinium gallium garnets. Adv Photonics. 2:2000102. https://doi.org/10.1002/adpr.202000102.

    • Search Google Scholar
    • Export Citation
  • US Department of Agriculture. 2021. Floriculture crops 2020 summary. USDA Economics, Statistics and Market Information System. https://usda.library.cornell.edu/?locale=en. [accessed 5 Sep 2023].

  • Van der Heggen D, Joos JJ, Feng A, Fritz V, Delgado T, Gartmann N, Walfort B, Rytz D, Hagemann H, Poelman D, Viana B, Smet PF. 2022. Persistent luminescence in strontium aluminate: A roadmap to a brighter future. Adv Funct Mater. 32:2208809. https://doi.org/10.1002/adfm.202208809.

    • Search Google Scholar
    • Export Citation
  • Van Doorn WG, De Stigter HCM, De Witte Y, Boekestein A. 1991. Micro-organisms at the cut surface and xylem vessels of rose stems: A scanning electron microscope study. J Appl Bacteriol. 70:3439.

    • Search Google Scholar
    • Export Citation
  • Wang R, Ruan G, Sun Y, Zhao D, Yu H, Zhang C, Li L, Liu J. 2021. A full-wavelength coverage colorimetric sensor depending on polymer-carbon nanodots from blue to red for visual detection of nitrite via smartphone. Dyes Pigments. 191:109383. https://doi.org/10.1016/j.dyepig.2021.109383.

    • Search Google Scholar
    • Export Citation
  • Zhu Y, Zeng J, Li W, Liu Y. 2009. Encapsulation of strontium aluminate phosphors to enhance water resistance and luminescence. Appl Surf Sci. 255:75807585. https://doi.org/10.1016/j.apsusc.2009.04.031.

    • Search Google Scholar
    • Export Citation
Abby Pace Department of Horticulture and Landscape Architecture, Oklahoma State University, 358 Ag Hall, Stillwater, OK 74078-6027, USA

Search for other papers by Abby Pace in
Google Scholar
Close
,
Bruce L. Dunn Department of Horticulture and Landscape Architecture, Oklahoma State University, 358 Ag Hall, Stillwater, OK 74078-6027, USA

Search for other papers by Bruce L. Dunn in
Google Scholar
Close
, and
Charles Fontanier Department of Horticulture and Landscape Architecture, Oklahoma State University, 358 Ag Hall, Stillwater, OK 74078-6027, USA

Search for other papers by Charles Fontanier in
Google Scholar
Close

Contributor Notes

B.L.D. is the corresponding author. E-mail: bruce.dunn@okstate.edu.

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 367 367 48
PDF Downloads 213 213 33
Save