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Article

Nectar Characteristics and Honey Production Potential of Five Rapeseed Cultivars and Two Wildflower Species in South Korea

by
Sung-Joon Na
*,
Young-Ki Kim
and
Ji-Min Park
Department of Forest Bioresources, National Institute of Forest Science, Suwon 16631, Republic of Korea
*
Author to whom correspondence should be addressed.
Plants 2024, 13(3), 419; https://doi.org/10.3390/plants13030419
Submission received: 14 November 2023 / Revised: 26 January 2024 / Accepted: 29 January 2024 / Published: 31 January 2024
(This article belongs to the Section Phytochemistry)
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Abstract

:
The growing beekeeping industry in South Korea has led to the establishment of new honey plant complexes. However, studies on honey production from each species are limited. This study aimed to assess the honey production potential of various Brassica napus cultivars and two wildflower species. The nectar characteristics of B. napus varied significantly among the cultivars. Absolute sugar concentrations differed among the cultivars, but sugar composition ratios were similar. In contrast, the amino acid content remained relatively uniform regarding percentage values, irrespective of the absolute concentrations. Estimations of honey potential production per hectare (kg/ha) resulted in the following ranking among cultivars: ‘JM7003’ (107.1) > ‘YS’ (73.0) > ‘JM7001’ (63.7) > ‘TL’ (52.7) > ‘TM’ (42.4). The nectar volume of Pseudolysimachion rotundum var. subintegrum and Leonurus japonicus increased during the flowering stage. P. rotundum var. subintegrum was sucrose-rich and L. japonicus was sucrose-dominant. Both species predominantly contained phenylalanine, P. rotundum var. subintegrum had glutamine as the second most abundant amino acid, and L. japonicus had tyrosine. The honey production potential was 152.4 kg/ha for P. rotundum var. subintegrum and 151.3 kg/ha for L. japonicus. These findings provide a basis for identifying food resources for pollinators and selecting plant species to establish honey plant complexes.

1. Introduction

1.1. Ecological Significance and Economic Implications of Honey Plants

Honey and various bee products have advantages attributed to their potential positive effects on human health. As a result, honey has been utilized for nutritional and therapeutic purposes since ancient times [1,2,3]. The viability of the apiculture industry depends on factors including the bee species, environmental conditions, and botanical origin [4]. Flowering plants provide food resources, such as nectar and pollen, to honeybees, and, reciprocally, honeybees assist in the pollination of these flowering plants, aiding their reproduction and survival [5]. This symbiotic relationship forms the basis of the apiculture industry, which includes beekeeping products and vital crop pollination services. Therefore, the maintenance and expansion of flowering plants are crucial for the sustainable development of the apiculture industry. This ensures an adequate supply of food for honeybees, allowing them to pollinate entomophilous plants and continue facilitating crop production [6]. Preserving and increasing the diversity and abundance of flowering plants is vital for maintaining ecological balance and supporting the health and reproduction of pollinators such as honeybees [7,8]. Consequently, this contributes to the long-term sustainability of the apiculture industry.
Diverse and abundant nectar plants have a positive effect on the population growth of plants and insects [9,10]. Conversely, the scarcity of nectar plant resources has led to a reduction in honeybee product yield and a decline in wild pollinators [11,12]. Recently, there have been decreases in both the diversity and abundance of pollinators worldwide [13,14,15,16]. Multiple factors, such as global climate change, altered land use, pesticides, diseases, and insufficient nutrition, contribute to the decline [17,18,19,20,21,22,23,24,25]. With the increasing recognition of the ecological contributions of floral resources, various methods have been proposed to expand floral resources and enhance service functions across agricultural ecosystems [26,27,28].
According to statistics from the Ministry of Agriculture, Food, and Rural Affairs (MAFRA), South Korea, the beekeeping industry has been consistently growing, with the number of beekeeping farms increasing from 19,000 in 2011 to 29,000 in 2020, a 152% growth over the past decade. The number of bee colonies increased by 175% during the same period. However, despite this quantitative growth, the average annual natural honey production decreased from 25,000 tons in 2007–2011 to 13,000 tons in 2016–2020 [29]. This situation is the result of a complex interplay of various factors, including the nationwide synchronized flowering plants due to climate change. However, a scarcity of floral resources has been identified as the primary cause. Currently, in South Korea, efforts are being made to promote the development of the beekeeping industry and increase the income of beekeeping farms. The “Beekeeping Industry Promotion and Support Act” was enacted in 2020 to protect and distribute honey plants. Large-scale honey plant complexes are being established in various regions with financial support from the government. Article 2 of the Enforcement Rules encourages the cultivation of honey plants by specifying a range of honey plants, including 25 woody and 15 herbaceous plant species. However, studies on the apicultural aspects of honey plant valuation, including nectar secretion, honey production potential, and sugar and amino acid contents of each honey plant, are lacking.
Not all flowering plants are equally important to the apiculture industry. Each plant differs in nectar production capacity and sugar composition, both quantitatively and qualitatively [30]. Moreover, the proportion of secreted nectar utilized by honeybees varies among these honey plants. Recently, studies have been conducted to estimate honey production per unit area by considering growth characteristics, flowering quantity, and nectar characteristics (nectar volume and sugar content) for each honey plant species [30,31,32]. These studies provide valuable information for establishing honey plant complexes based on plants with superior honey productivity at the regional and national levels [26]. Importantly, the evaluation of plants for the establishment of honey plant complexes at the regional or national levels must be conducted using consistent methods.
Sugars and amino acids in nectar are essential energy sources for honey production and bee colony development. Therefore, the sugar and amino acid profiles of plants are valuable factors that explain the relationship between pollinators and their source plants [33,34]. The composition of nectar varies depending on the plant taxa [30,32], environmental conditions in which the plant grows [35], floral sexual phases [36], and flower position within inflorescences [37]. The quality and composition ratio of sugars in nectar, as well as the absolute amount per flower, can significantly influence the appeal of plants to pollinators. The profitability of flowers is a key determining factor in the selection of plants that bees visit to obtain food [38]. However, the quantity of sugars and amino acids in the floral nectar from specific plants can contribute to ‘flower constancy’ or ‘pollinator constancy’ [39]. Amino acids are important attractors that determine plant visits by pollinators [40,41] and are key nutrients for many consumers [42,43]. Amino acids activate specific taste chemoreceptors and stimulate or inhibit sensory cell responses [44,45,46]. Thus, they attract pollinators and protect plants from herbivores [47,48]. Specific amino acid concentrations provide information to insects regarding the intensity of nectar taste [48], and pollinators prefer nectar with a specific amino acid composition [49]. Therefore, a better understanding of host plants is crucial for bee production, as well as sustainable bee management. These findings are likely to provide a basis to identify food resources for pollinators and select plant species to establish honey plant complexes.
There are approximately 625 species of honey plants in Korea, including herbaceous and woody plants [50]. The plant species tested in this study, Brassica napus L. (rapeseed), Pseudolysimachion rotundum var. subintegrum T. Yamaz (mountain spike speedwell), and Leonurus japonicus Houtt. (motherwort), are included in this list and have been used as honey plants for a long time. However, quantitative evaluations of honey plant value have not been conducted, and only honeybee foraging behavior has been observed. Therefore, this study aimed to elucidate the value of honey plants for five recommended varieties of B. napus in Korea, P. rotundum var. subintegrum, and L. japonicus, which have not yet been globally studied for their honey plant characteristics. Accordingly, we applied a consistent methodology to determine nectar secretion, the sugar content and composition, and the quantitative and qualitative compositions of amino acids. In addition, we estimated the potential honey production per plant per hectare by considering plant growth characteristics.

1.2. Research Plants: Utilization and Significance

B. napus is a crucial crop in temperate regions and ranks as one of the four major global oil crops, along with soybeans and peanuts [51,52]. It accounts for approximately 13–16% of global vegetable oil production [53]. In addition to its use in edible oils, B. napus is utilized for producing high-quality animal feed and biodiesel [54]. Because of its abundant flowering in early spring, B. napus is a valuable food resource for various insects until other plants start blooming after winter. While approximately 70% are known to be self-fertile or autogamous [55], visits from pollinating insects still provide benefits by increasing the seed yield [56,57]. B. napus flowers develop two pairs of nectaries: the lateral (inner) and median (outer) pairs. It was believed that median nectaries did not produce nectar. However, subsequent studies have revealed that nectar is produced in the median nectaries and that anatomical differences are associated with differences in nectar production [55]. Moreover, Davis et al. [58] reported that nectar produced from lateral nectaries had a higher quantity and showed a higher glucose/fructose ratio (1.0–1.2) compared to those from median nectaries (0.2–0.9). The differing nectar production capabilities of nectaries led most bees to visit the lateral nectaries when foraging on B. napus flowers [59]. Bee activity for collecting nectar and pollen appears to be greater in the afternoon (12:00–2:00 p.m.) than in the morning [57].
P. rotundum var. subintegrum was previously categorized as belonging to the genus Veronica. However, based on molecular phylogenetic studies, it is now classified within the genus Pseudolysimachion [60,61,62]. P. rotundum var. subintegrum thrives naturally throughout Korea because of its excellent ecological adaptability [63]. Its popularity as an ornamental plant is attributed to being perennial; it has long blooming periods and is easy to maintain [64]. Currently, the detailed pharmacological effects specific to P. rotundum var. subintegrum have not been extensively documented. However, considering that extracts from many species within the Plantaginaceae family exhibit various pharmacological actions, including antioxidant, anticancer, antimicrobial, and anti-inflammatory activities, it is anticipated that P. rotundum var. subintegrum could become a valuable crop in the future [65,66,67,68].
L. japonicus is a perennial herb belonging to the Lamiaceae family and is widely distributed in East Asia, including Korea, China, and Thailand. It typically blooms from July to August. It has traditionally used to treat gynecological and obstetrical diseases, as indicated by its name, and is beneficial to women [69]. More than 280 secondary metabolites have been isolated from this plant, showing various activities, such as anticoagulant [70], antibacterial [71,72], antiplatelet aggregation [73,74,75], vasodilation [76], angiogenesis [77], and effects on uterine smooth muscle [78].

2. Results

2.1. Comparison among B. napus Cultivars

2.1.1. Flowering and Growth Characteristics

The flowering periods of the five cultivars of B. napus sown on the same date varied slightly (Table 1). ‘JM7003’ bloomed the earliest, starting on 25 May and flowering for a total of 20 days until June 13. ‘YS’ flowered from 27 May to 13 June, whereas ‘TM’, ‘YL’, and ‘JM7001’ all began flowering on May 30 and concluded flowering by June 16. ‘JM7001’ finished flowering on June 20. Plant height was tallest in ‘JM7003’ at 73.1 cm, followed by ‘JM7001’ (65.3 cm), ‘TL’ (60.7 cm), ‘TM’ (54.7 cm), and ‘YS’ (53.4 cm) in descending order. The number of flowers per plant was the highest in ‘JM7003’ at 65.3, followed by ‘JM7001’ with 43.7 flowers per plant. ‘TL’, ‘TM’, and ‘YS’ had 27.2 to 33.2 flowers per main stem, with the maximum and minimum numbers differing approximately twofold. Plant density per unit area (m2/plants) was relatively high for ‘YS’ and ‘JM7001’ and relatively low for ‘TM’ and ‘TL’, and no statistically significant difference was observed between the cultivars. These data were used to quantify potential honey production per unit area.

2.1.2. Nectar Secretion and Sugar Composition

The secreted nectar volume per flower over the lifespan (1 day) was the highest in ‘JM7003’ (1.54 μL/flower), followed by ‘YS’ (1.08 μL/flower), ‘JM7001’ (1.04 μL/flower), ‘TL’ (0.81 μL/flower), and ‘TM’ (0.73 μL/flower) in descending order (p = 0.005).
The free sugar content differed significantly among the cultivars for all constituents (sucrose, glucose, and fructose). The total sugar content was highest in ‘TM’ (1349.4 μg/μL) and lowest in the ‘JM7003’ (641.0 μg/μL). Overall, ‘TM’, ‘TL’, and ‘YS’ exhibited higher sugar contents per unit volume, whereas ‘JM7001’ and ‘JM7003’ showed slightly lower sugar contents per unit volume. These results were consistent in the sugar components as well, with the ‘JM7003’ and ‘JM7001’ having lower quantitative amounts of sucrose, glucose, and fructose compared to the other cultivars (Table 2).
The floral nectar of B. napus consists primarily of glucose and fructose, with sucrose constituting a very low proportion, ranging from 1.2% to 1.9% of the total sugar content. Glucose accounted for 47.6–49.5% of the total sugar content, while fructose constituted 48.9–50.7% of the sugar composition. Notably, the sugar composition was more uniform than the absolute quantities. Sucrose and glucose compositions showed no differences among the cultivars. Regarding fructose, the ‘JM7003’ had the highest content at 50.7%, whereas the ‘JM7001’ had the lowest content at 48.9%, but the difference was marginal.
The sucrose to hexose ratio (SH ratio) showed a slight difference, with ‘TM’ at 0.019 and ‘TL’ at 0.012. The fructose to glucose ratio (FG ratio) varied among cultivars, with ‘JM7001’ at 1.013 and ‘JM7003’ at 0.939, but the differences were not statistically significant (Figure 1).

2.1.3. Amino Acid Content

In B. napus nectar, 20 different amino acids were identified, and significant variability was observed in their absolute concentrations. In quantitative terms, ‘YS’ had the highest content at 7.91 mg/L, followed by ‘TM’ (5.01 mg/L), ‘JM7001’ (2.99 mg/L), ‘TL’ (2.36 mg/L), ‘JM7003’ (1.82 mg/L), showing significant differences among the cultivars (Figure 2A). Among all cultivars, glutamine had the highest absolute concentration, and considerable variability was observed for both glutamine and histidine. The glutamine absolute value for ‘YS’ was 3.2 mg/L, which was over four times higher than that of ‘JM7003’ (0.7 mg/L) and ‘TL’ (0.8 mg/L). The second most abundant amino acid in all cultivars was histidine, with a difference of approximately sevenfold between ‘YS’ and ‘JM7003’.
The amino acid composition ratio showed that glutamine (34.4–40.0%) and histidine (11.6–19.2%) were the most abundant in all cultivars (Figure 2B). On average, proline (5.6–9.2%), glutamic acid (4.1–6.6%), and asparagine (3.6–6.0%) had relatively high composition ratios, with variations in rank among the cultivars. For example, proline was the third most abundant in ‘JM7003’, ‘JM7001’, and ‘TL’, but in ‘TM’, asparagine had a higher proportion, and in ‘YS’, glutamic acid was more abundant than proline. The amino acids constituting more than 5% of the nectar composition were proline in both ‘JM7003’ (8.8%) and ‘JM7001’ (6.6%) and glutamic acid (6.3%) in ‘YS’. Additionally, in ‘TM’, asparagine (6.0%) and proline (5.6%) were present in concentrations exceeding 5%. For ‘TL’, proline (9.2%), glutamic acid (5.8%), and asparagine (5.2%) were present in concentrations exceeding 5%. Serine was present in all cultivars at a concentration of over 3% (3.7–4.9%), whereas the amino acids with a less than 1% composition were glycine (0.5–0.7%), tryptophan (0.5–0.8%), and methionine (0.1–0.3%). Histidine, isoleucine, leucine, threonine, tryptophan, valine, asparagine, glutamic acid, glutamine, serine, and tyrosine exhibited statistically significant differences in composition ratios among the cultivars (p < 0.05).
The average essential amino acid content in the floral nectar of the five B. napus cultivars was 33.5%. ‘JM7003’ had the lowest content at 30.3%, whereas the other four cultivars showed similar contents ranging from 33.3% to 35.6%.

2.1.4. Estimated Honey Production

The nectar sugar content per flower, calculated as the product of nectar volume and free sugar content, was highest in ‘YS’ at 1.24 mg/flower, followed by ‘TM’ and ‘JM7003’ at 0.96 mg/flower, ‘TL’ at 0.95 mg/flower, and ‘JM7001’ with the lowest content at 0.80 mg/flower. Despite noticeable differences, no statistically significant differences were observed among the cultivars (Table 3).
However, by estimating the potential honey production per plant by multiplying the nectar sugar content per flower and the number of flowers per plant, the honey production was highest in ‘JM7003’ at 72.0 mg per plant among the five cultivars. ‘YS’ and ‘JM7001’ followed at 45.3 and 40.2 mg, respectively. ‘TL’ and ‘TM’ had honey potentials of 36.3 and 29.9 mg, respectively. Furthermore, by calculating the potential honey production per hectare using the number of plants per hectare, ‘JM7003’ exhibited excellent honey productivity at 107.1 kg/ha, followed by ‘YS’ at 73.0 kg. The estimated honey production per hectare for ‘JM7001’ and ‘TL’ were 63.7 and 52.7 kg, respectively. ‘TM’ showed the lowest honey production at 42.4 kg.

2.2. Two Wildflowers

2.2.1. Flowering and Growth Characteristics

The flowering and growth characteristics of P. rotundum var. subintegrum and L. japonicus are presented in Table 4. The flowering period of P. rotundum var. subintegrum lasted for 41 days, from July 19 to August 30. The average plant height was 83 cm, and the average number of flowers per plant was 3422. Motherwort flowered for 32 days from August 2 to September 2. The average plant height was 124.8 cm, with an average of 2894 flowers per plant. The planting spacing was 30 × 25 cm, resulting in a plant density of 17.5 plants/m2 for both species per unit area.

2.2.2. Nectar Secretion Characteristics

Nectar volume was measured on each day of flowering because the two species of wildflowers flowered for two days (Table 5). The nectar secretion per flower of P. rotundum var. subintegrum was 0.07 μL on the first day of flowering and increased to 0.30 μL on the second day of flowering, showing an accumulation of nectar as flowering progressed (p = 0.0099). The free sugar content per unit volume of nectar slightly decreased as flowering progressed, with 828.7 μg/μL on the first day and 767.9 μg/μL on the second day. On the first day of flowering, the absolute quantities of sucrose were 407.9 μg/μL and glucose and fructose were 197.7 and 232.2 μg/μL, respectively. On the second day of flowering, the composition of nectar sugars was as follows: sucrose was 310.2 μg/μL, glucose was 211.2 μg/μL, and fructose was 246.5 μg/μL. The free sugar content per flower, calculated using nectar secretion and the free sugar content per unit volume, was 0.06 mg on the first day of flowering and significantly increased to 0.22 mg on the second day of flowering (p = 0.0015).
The nectar volume per flower of L. japonicus was 0.16 μL on the first day of flowering and increased to 0.33 μL on the second day of flowering, showing a significant difference between the flowering days (p = 0.0057). The free sugar content per unit volume was 775.4 μg/μL on the first day and 816.3 μg/μL on the second day, with no significant difference. On the first day of flowering, sucrose was 624.7 μg/μL, glucose was 71.8 μg/μL, and fructose was 78.9 μg/μL. On the second day of flowering, sucrose was 631.1 μg/μL, whereas glucose and fructose were 88.9 and 96.3 μg/μL, respectively. The free sugar content per flower was 0.12 and 0.26 mg on the first and second days of flowering, respectively, indicating a higher value on the second day (p = 0.0106).

2.2.3. Sugar Content and Composition

The sugar content in P. rotundum var. subintegrum showed that sucrose was the most abundant sugar, followed by fructose and glucose, on both the first day of flowering (p = 0.0052) and the second day of flowering (p = 0.0006). As flowering progressed, the proportion of sucrose decreased (first day of flowering, 50.5%; second day of flowering, 40.0%), whereas the amounts of glucose and fructose slightly increased. The glucose content increased from 23.2% on the first day of flowering to 27.8% on the second day, whereas the fructose content increased from 26.2% on the first day to 32.2% on the second day. Therefore, the sucrose-to-hexose (glucose + fructose) ratio decreased from 1.1 on the first day of flowering to 0.7 on the second day. The fructose-to-glucose ratio increased from 1.1 on the first day of flowering to 1.2 on the second day, indicating a higher proportion of glucose (Figure 3).
Similarly, the nectar sugar composition in L. japonicus showed that sucrose was the predominant sugar on all flowering days (p < 0.0001), with glucose and fructose constituting approximately 10% of the sugars. Changes in sugar content per flowering day indicated a reduction in sucrose from 80.5% on the first day to 77.5% on the second day, whereas glucose and fructose contents increased by approximately 1.5%. Consequently, the sucrose-to-hexose ratio decreased from 4.1 on the first day to 3.5 on the second day, while the fructose-to-glucose ratio remained constant at 1.1, reflecting a proportional increase in glucose and fructose.

2.2.4. Amino Acid Content

The floral nectar of P. rotundum var. subintegrum contained twenty amino acids (Figure 4). The absolute quantity of total amino acids decreased by 93.8 mg/L from 341.1 mg/L on the first day of flowering to 247.4 mg/L on the second day as flowering progressed. The content of the nine essential amino acids was an average of 230.5 mg/L, with 270.9 mg/L on the first day of flowering and 190.2 mg/L on the second day of flowering. Notably, there were increases in valine (+0.45 mg/L), isoleucine (+0.15 mg/L), leucine (+0.11 mg/L), and arginine (+0.02 mg/L), despite this overall decrease. Phenylalanine was overwhelmingly abundant among all amino acids (73.4%), and this decrease was pronounced. Specifically, it decreased significantly from 186.1 mg/L on the first day of flowering to 75.0 mg/L on the second day, indicating a reduction of 80.9 mg/L. However, when expressed as a percentage, the rate of decrease was minimal at −1.16%. The total content of 11 non-essential amino acids in quantity decreased by 13.1 mg/L from 70.2 mg/L on the first day of flowering to 57.1 mg/L on the second day as flowering progressed. However, the proportion of the overall amino acids increased from 20.6% on the first day of flowering to 23.2% on the second day of flowering. Although the proportions were small, proline (−0.16%), tyrosine (−0.07%), and taurine (−0.05%) decreased in their respective proportions. The remaining 19 amino acids accounted for 0.02–1.59% of the total content, which was very low.
The floral nectar of L. japonicus contained twenty-two amino acids (Figure 5). The total absolute quantity decreased from 112.8 mg/L on the first day of flowering to 90.0 mg/L on the second day, a reduction of 22.8 mg/L (−20.2%). The decrease in phenylalanine levels was particularly notable as flowering progressed. Additionally, apart from lysine, asparagine, tryptophan, GABA, and other amino acids increased on the second day of flowering compared with the first day. The proportion of the 10 essential amino acids was 81.4% (day 1: 84.3%; day 2: 78.5%), with phenylalanine being the most abundant (first day: 80.8%; second day: 73.7%). Among the 13 non-essential amino acids, tyrosine was the most abundant, slightly increasing in composition from 8.3% on the first day to 12.0% on the second day of flowering. The remaining 20 amino acids were present in very small amounts, ranging from 0.01–0.59%. Ornithine and taurine were not detected on the first day of flowering but were found in trace amounts on the second day of flowering.

2.2.5. Estimated Honey Production

Based on the sugar content per flower and number of flowers per plant in P. rotundum var. subintegrum, it is estimated that approximately 870.6 mg of honey can be produced per plant. In addition, assuming that 175,000 plants are cultivated per hectare, it is estimated that approximately 152.4 kg of honey can be produced (Table 6).
Using the sugar content of 0.22 mg per flower and the total number of flowers per plant (2894 flowers) for L. japonicus, the potential honey production per plant was estimated to be 846.6 g. Extrapolating this to a planting density of 175,000 plants per hectare, the estimated honey production per hectare is 151.3 kg.

3. Discussion

3.1. Estimation of Honey Production

Significant variability was observed in the nectar volumes and absolute sugar concentrations among the different B. napus cultivars. Among the five B. napus cultivars, ‘JM7003’ recorded the highest nectar volume (1.54 μL), which was more than twice that of ‘TM’ (0.73 μL). Such significant variability has been reported in other studies. Bertazzini and Forlani [79] reported nectar volumes ranging from 0.2 μL to 0.75 μL among 44 cultivars, whereas Pierre et al. [80] documented volumes ranging from 0.7 μL to 5.9 μL among 71 genotypes. An important consideration is that the volume and concentration of nectar can vary depending on the temperature and relative humidity at the time of nectar collection [81,82]. For example, under high-temperature and low-relative humidity conditions, the moisture content of nectar decreases, reducing the absolute quantity and increasing the concentration. Conversely, under low-temperature and high-relative humidity conditions, the absolute quantity of nectar increases, lowering the nectar concentration. Therefore, when assessing honey production among species or cultivars, it is essential to consider the quantity of nectar per flower as well as various factors such as the nectar content per unit volume and the number of flowers per plant [30,32]. In this study, ‘JM7003’ had the highest nectar volume, but it had a lower free sugar content per unit volume compared to ‘YS’, which had the highest sugar content per flower (Table 3). In contrast, ‘TM’ had the lowest nectar volume, but it had the highest sugar content per unit volume, resulting in ‘TM’ having the same sugar content per flower as ‘JM7003’ (Table 2 and Table 3). However, ‘YS’, with the highest sugar content per flower, exhibited a lower number of flowers per plant, lowering overall honey production per plant compared to ‘JM7003’. Conversely, ‘JM7001’, despite having the lowest sugar content per flower, demonstrated a higher honey production per plant compared to ‘TM’ and ‘TL’ due to its higher flower count. Furthermore, it is important to consider the per hectare plant count because the currently measured flower number per plant reflects the planting density. In conclusion, among the B. napus cultivars developed in Korea, ‘JM7003’ exhibited the highest honey potential production (107.1 kg), followed by ‘YS’ (73.0 kg), ‘JM7001’ (63.7 kg), ‘TL’ (52.7 kg), and ‘TM’ (42.4 kg) in descending order.
Utilizing indigenous plants with high regional adaptability is advantageous for establishing and maintaining honey plant complexes in various regions and countries. P. rotundum var. subintegrum and L. japonicus demonstrate superior honey production potential compared to B. napus, which is widely used in many countries (Table 5). Additionally, these plants offer promising valuable medicinal resources (as mentioned in the Introduction). This study is the only investigation of nectar characteristics and honey production in P. rotundum var. subintegrum and L. japonicus. Nectar secretion in P. rotundum var. subintegrum varied significantly between the first and second days of flowering, with 0.07 μL on the first day and 0.30 μL on the second day. A similar trend was observed in L. japonicus. Considering that our nectar collection time was 4:00 p.m., it is evident that more nectar was secreted on the second day of flowering, irrespective of nectar reabsorption [83]. Therefore, to accurately measure nectar volume using centrifugation, collecting the cumulative nectar over the entire flower lifespan is necessary. However, the estimated range of honey production per hectare, based on the minimum and maximum native plant counts, was broad for P. rotundum var. subintegrum, ranging from 92 to 244 kg, and for L. japonicus, ranging from 69 to 235 kg. The existence of variability implies the possibility of breeding to increase honey production by selecting individuals with abundant flowering numbers. The medicinal use of L. japonicus can be categorized into two methods: harvesting before flowering during early summer and utilizing the fruits in autumn [84]. If a management approach is adopted in which honey is harvested in summer (July) and fruits are collected in autumn (October), the economic value (land productivity) per unit area may increase.
The results of this study are expected to provide valuable information in terms of offering more food resources to pollinators, as well as selecting plant species to establish honey plant complexes aimed at increasing honey production. However, it is expected that actual honey production will be lower than the estimated honey production potential in this study, as a significant portion of nectar is typically used for brood rearing and sustaining bee colonies [30].

3.2. Sugar Composition

The sugars in the floral nectar mainly comprise sucrose, glucose, and fructose. In some plants, small amounts of mannose, arabinose, xylose, galactose, sorbitol, maltose, and melibiose are occasionally included [79,85,86]. The sugar concentration and quality of the floral nectar are closely related to the type and frequency of pollinators [85,87]. The preference of various pollinators for these specific plants affects seed production and crop yield of the plant [88].
The sugar composition of honey is categorized as sucrose-dominant (over 1.0; sucrose 51–100%), sucrose-rich (0.5–1.0; 34–50%), hexose-rich (0.1–0.5; 10–33%), and hexose-dominant (below 1.0; 0–9%) based on the sucrose-to-hexose ratio [86,89]. In this study, all B. napus cultivars belonged to the hexose-dominant category (0.012–0.019) (Figure 1), which was consistent with previous studies [55,58,79,80,90,91].
The SH ratio of the floral nectar changed daily during blooming (Figure 3). On the first day of flowering in P. rotundum var. subintegrum, floral nectar was categorized as sucrose-dominant (1.1), whereas on the second day of flowering, it became sucrose-rich (0.7). In the case of L. japonicus, the nectar on all flowering days was sucrose-dominant, but the value decreased from 4.1 to 3.5. The increase in hexoses in the secreted nectar over time can be explained by the hydrolysis of sucrose by invertase [92], where glucose and fructose are typically present in a 1:1 ratio [93]. However, a difference existed in the sugar conversion rates between the two plants. On the first day of blooming, the sucrose content in P. rotundum var. subintegrum rapidly decreased from 50% to 40%, whereas in L. japonicus, it decreased by only 3%, from 80.5% to 77.5%. This indicates that the rate of sugar conversion is not the same for all plants. It can vary depending on sugar metabolism pathways and secretion processes occurring in the nectaries. This can also be a result of the presence or speed of catalytic reactions by transglucosidases and transfructosidases located in nectaries [79,94]. However, further research on this topic is required.
Honeybees show a preference for floral nectar, a blend of various sugars (sucrose, glucose, and fructose), to nectar composed only of sucrose [95,96]. However, in terms of a single sugar content, there was a tendency of sucrose > glucose > maltose > fructose [97]. Furthermore, the preference of long- or short-tongued bees and other pollinators may vary based on the sugar content [98,99,100,101,102,103,104]. However, the types of pollinators visiting plants that secrete nectar are not solely based on the sugar composition. Different types of pollinators visit plants with similar sugar compositions; however, different types of pollinators are observed [105,106,107,108].
In this study, although there were no collected data, observations were made that Apis mellifera visits were mostly observed in B. napus, where hexoses were overwhelmingly abundant in the nectar. Although sucrose was dominant, both glucose and fructose were present in high proportions in P. rotundum var. subintegrum and L. japonicus, resulting in diverse insect visits and making it difficult to pinpoint specific insects that lead to pollination.
Generally, floral nectar contains sugars that are essential for the survival of pollinators, along with small amounts of amino acids and secondary metabolites. The quantity and sugar composition of secreted nectar vary across species [109,110,111]. In addition, nectar contains secondary compounds such as alkaloids, phenolic substances, and iridoid glycosides, which can either increase or decrease the frequency and duration of pollinator visits [112,113]. Therefore, the type and frequency of pollinators visiting flowers can vary depending on the qualitative and quantitative composition of floral nectar, the quality and content of pollen [114], the presence and function of toxins [115,116], and the food resource characteristics provided to insects. Furthermore, the type and frequency of pollinators visiting flowers can vary based on the distance between plants and beehives, competition with other insects, and the influence of the bee colony’s intrinsic needs. Therefore, comprehensive research is required to thoroughly investigate these aspects.

3.3. Amino Acid Content

Amino acids play a crucial role in determining the taste of nectar and influencing pollinator visits [117]. The composition of amino acids, both in type and quantity, varies among different plant species and even within the same species [118,119]. The uptake of variety amino acids has been noted to positively influence the lifespan and fecundity of bees [120], with positive effects on memory and learning abilities [121]. In the present study, both rapeseed and mountain spike speedwell contained 20 amino acids each, whereas motherwort contained 22 amino acids, suggesting a diverse supply of amino acids to pollinators.
The amino acid contents among the different B. napus genotypes showed significant differences. However, when expressed as relative percentages, they still exhibited statistically distinct yet more consistent relative values (Figure 2). A similar trend was observed for sugar contents among the different genotypes (Table 2 and Figure 1). Regarding these findings, Bertazzini and Forlani [79] reported that all genotypes shared a mechanism that controls the reciprocal ratios of sugar and amino acid compositions. All rapeseed cultivars exhibited high proportions of glutamine (34.8–40.0%; avg. 37.5%) and histidine (11.6–19.2%; avg. 17.2%). Additionally, proline (3.2–8.8%; avg. 6.7%), glutamic acid (3.9–5.8%; avg. 5.2%), asparagine (3.6–6.0%; avg. 4.6%), and serine (3.7–4.9%; avg. 4.2%) exhibited relatively high compositions (Figure 2). This is consistent with the results of a previous study that investigated the amino acid compositions of 44 different genotypes of B. napus var. oleifera [79].
de Groot [122] reported 10 essential amino acids for bees that cannot be synthesized within their bodies and must necessarily be obtained from food sources. In this study, the essential amino acid contents in five B. napus cultivars ranged from 30.3% to 35.6%, with non-essential amino acids (64.4–69.7%) being the most abundant. However, B. napus is recognized as an attractive plant for bees because it can obtain additional necessary amino acids and proteins from the nectar of rapeseed flowers. Bees obtain a nutritionally balanced amino acid profile by foraging for nectar and pollen from rapeseed flowers [79,123]. However, other studies have suggested a more complex relationship between the amino acid content of nectar and bee preferences. The nutritional balance of essential amino acids and carbohydrates preferred by adult worker honey bees varies with age. Forager bees tend to prefer nectar with a higher carbohydrate content than essential amino acid content [34].
Proline, the third most abundant amino acid in rapeseed nectar, is one of the most preferred amino acids by honeybees [124,125,126,127]. This amino acid is believed to stimulate labellar salt receptor cells, allowing bees to perceive taste [48,128,129]. Proline is a crucial energy source for honeybee flight [125,130,131], which is rapidly metabolized during the oxidation process and releases significant amounts of ATP [132,133,134,135,136]. These characteristics of proline confer significant advantages to honeybees that travel long distances to forage [79]. This can be considered a co-evolutionary strategy by which plants produce proline-rich nectar to increase their foraging success rates [127]. Additionally, proline is a component of antimicrobial peptides present in Apis mellifera hemolymph, aiding in the removal of bacteria without damaging cell membranes [137]. Therefore, proline is a crucial amino acid providing innate immunity for honey bees [138,139,140].
Serine is also part of a serine protease enzyme involved in the immune processes of A. mellifera and plays a role in protecting insects from harmful microorganisms and xenobiotics [141,142]. B. napus nectar contains a significant amount of serine, approximately 4% (ranking sixth in overall abundance), and it is relatively abundant in P. rotundum var. subintegrum and L. japonicus at approximately 2%. Typically, honeybees tend to avoid nectar with a high serine content [125,126,127]. Honeybee respond negatively to glycine, leucine, valine, threonine, alanine, aspartic acid, and methionine [41]. Glutamic acid, which constitutes approximately 5% of B. napus nectar, is an essential donor of amide groups (glutamine and asparagine), which are crucial for the production of purine nucleotides and serotonin [143,144]. Glutamic acid and hydroxyproline are the primary determinants of the qualitative variation in amino acid composition within B. napus nectar and serve as major sources of nitrogen, carbon, and energy for insects [133,145,146]. Furthermore, this amino acid, along with aspartic acid (2.0–2.8%; avg. 2.4%) and lysine (2.1–3.2%; avg. 2.7%), reduces oxidative stress in A. mellifera larvae and adults [147,148].
This study is the first to describe the amino acid profiles of the nectar of P. rotundum var. subintegrum and L. japonicus. Phenylalanine, constituting over 70% of the nectar of P. rotundum var. subintegrum and L. japonicus (present in B. napus nectar from the five cultivars at around 1%), along with proline, stimulates chemosensors in forager bees, directing their focus towards collecting nectar. Hendriksma et al. [126] reported that phenylalanine showed a stronger preference than other amino acids in their analysis of amino acid preference in bees. Bees were observed to find phenylalanine highly attractive to such an extent that they would forgo 84 units of sucrose to collect 1 unit of phenylalanine. In addition, Petanidou et al. [41] found that phenylalanine was the most abundant amino acid and preferred by flower visitors. In various studies, phenylalanine has been identified as a phagostimulant that attracts honeybees to flowers, and its presence, along with tryptophan and alanine, enhances the foraging preference of honeybees [126,149]. These amino acids are crucial for pollination ecology [150]. In our study, the tryptophan content in B. napus nectar was approximately 0.5–0.8% (average 0.7%), while it was approximately 0.5% in P. rotundum var. subintegrum and 1.9% in L. japonicus. Alanine was found to be present in canola at a level of 2.4–3.1%, whereas in P. rotundum var. subintegrum and L. japonicus, it was approximately 0.9% and 0.8%, respectively (Figure 2, Figure 4 and Figure 5).
The floral nectar of P. rotundum var. subintegrum and L. japonicus contained taurine and ornithine (Figure 4 and Figure 5). These amino acids, classified as non-protein amino acids (NPAAs), are relatively uncommon in floral nectars, but have been found in other plants as well [151,152,153,154]. Taurine is estimated to be involved in the development of flight muscles in winged insects. GABA works synergistically with taurine to suppress excessive and potentially disruptive states of excitation under stressful conditions [43].

4. Materials and Methods

4.1. Plant Material

This study utilized five cultivars of B. napus, which were developed by the National Institute of Crop Science, Rural Development Administration in South Korea. The seeds used in the research were provided by the aforementioned institute. Seeds of five B. napus cultivars were sown on 14 April 2022, in an experimental field located in Suwon, South Korea. B. napus used in this study is recommended for cultivation in South Korea. ‘Youngsan’ (‘YS’), ‘Tammi’ (‘TM’), and ‘Tamla’ (‘TL’) are developed for increased seed yield. ‘Jungmo 7001’ (‘JM 7001’) and ‘Jungmo 7003’ (‘JM 7003’) are ornamental cultivars, with ‘Jungmo 7001’ known for its large flowers and ‘Jungmo 7003’ having distinctive white flowers (Figure 6A) [155,156]. Sowing was carried out at a rate of 2 kg per 100 m2 according to the recommended cultivation practices in Korea.
P. rotundum var. subintegrum and L. japonicus were sown on 1 April 2022, after which they were transplanted at intervals of 25 × 30 cm to approximately 10 cm tall plants (Figure 6B,C). Flower counts were obtained by conducting a comprehensive survey of 50 randomly selected plants of each plant species. The number of plants per square meter (m2) was counted and converted to plants per hectare (ha), resulting in an estimate of potential honey production per hectare.

4.2. Measure of Nectar Volumes

To measure the secreted nectar volume, we selected ten healthy plant individuals with robust growth. We removed all flowers that had already bloomed and covered the entire plant with pollination bags to prevent any loss of nectar due to visits from honeybees and other insect pollinators. For plants with a 2-day flower lifespan, such as P. rotundum var. subintegrum and L. japonicus, we collected nectar by distinguishing the flowering time using a method involving marking flowers that had bloomed one day after the installation of pollination bags (at 2:00 p.m.) [111]. For B. napus plants with a one-day flowering period, we collected nectar on the same day as the installation of pollination bags at 5:00 p.m. Nectar collection from B. napus plants was conducted on June 3 for the ‘JM7003’ variety, which had the earliest flowering, and on June 10 for the remaining four varieties. P. rotundum var. subintegrum and L. japonicus were examined on August 18, respectively.
More than 50 flowers were harvested from each species and variety and placed into sterilized 50 mL centrifugal tubes equipped with a flower mesh (pore size 0.3 mm). The tubes were centrifuged at 4000 rpm for 4 min [157,158]. The collected nectar was quantified using a 50 μL micro-syringe (Hamilton Co., Reno, NV, USA). Subsequently, it was purified by adding an 80% ethanol solution at a 10-fold dilution, followed by filtration through a 0.45 μM pore centrifuge filter (Millipore, Billerica, MA, USA) to remove pollen and other impurities. Finally, the collected nectar was stored at −20 °C until further analysis of the sugar and amino acid contents.

4.3. Analysis of Sugar Contents

The free sugar content was analyzed using HPLC (Dionex Ultimate 3000; Dionex, Sunnyvale, CA, USA). Deionized water served as the mobile phase, flowing at a rate of 0.5 mL/min, and the oven temperature was set at 80 °C. Detection was carried out using a Shodex Ri-101 (Showa Denko, New York, NY, USA) in combination with an Aminex 87P column (300 × 7.8 mm, Bio-Rad, Hercules, CA, USA). The free sugar content was determined by the standard external method utilizing integral meter measurements, and high purity (99.5%) sucrose, glucose, and fructose (Sigma Aldrich, St. Louis, MO, USA) were employed as standards.

4.4. Analysis of Amino Acid Contents

The amino acids in the collected nectar samples were analyzed using OPA (O-phthalaldehyde)-FMOC (fluorenylmethyl chloroformate) derivatization. The samples were prepared by sequential mixing with borate buffer, OPA/mercaptopropionic acid (MPA), and FMOC reagent. Subsequently, analysis was conducted using HPLC 1200 series (Agilent Technologies, Santa Clara, CA, USA). The mobile phase consisted of two solutions: A solution containing 10 mM Na2HPO4 and 10 mM Na2B4O7·10H2O with a pH of 8.2, and B solution, which was a mixture of water/acetonitrile/methanol in a 10:45:45 ratio. The gradient conditions were set to change from an initial 100:0 (v/v, %) of solution A to solution B at 26–28 min, followed by 0:100 at 28–30.5 min, and maintained at 100:0 after 30.5 min. The flow rate was set to 1.5 mL/min, and an injection volume of 1 mL was used. The INNO C-18 column (150 mm × 4.6 mm, 5 μm; Youngjin Biochrom Co., Ltd., Seongnam, Republic of Korea) was maintained at a temperature of 40 °C. The UV detector was set at 338 nm, and the OPA derivative was analyzed at an emission wavelength of 450 nm and an excitation wavelength of 340 nm using a fluorescence detector. For the FMOC derivative, the emission and excitation wavelengths were set to 305 and 266 nm, respectively.

4.5. Honey Production Potential

The estimation of honey production and yield was calculated using the following formula, considering the surveyed nectar secretion (μL/flower), free sugar content per unit (μg/μL), number of flowers (ea/plant), and the honey potential [159]. In the final step, to enable standardization between species, we considered plant density based on crop density and calculated the population density per hectare, ultimately estimating the potential honey production per hectare (kg/ha).
Honey production (mg/plant) = nectar sugar content (mg/flower) 1 × number of flowers (ea/plant) × honey potential (1.15) 2
  • 1 Nectar sugar content (mg/flower) = nectar volume (μL/flower) × free sugar content (μg/μL) × 0.001 (for unit conversion: μg to mg)
  • 2 Honey potential = sugar content: honey = 85:100.
Honey yield (kg/ha) = honey production (mg/plant) × number of plants (ea/ha) × 0.000001 (for unit conversion: mg to kg).

4.6. Statistics

Statistical analyses were performed, including one-way analysis of variance (ANOVA) and Duncan’s multiple range test, using the integrated statistical software package SAS 8.2 (SAS Institute, Cary, NC, USA) with a significance level of 0.05. These analyses covered various aspects, including growth, nectar volume, sugar concentration (sucrose, glucose, and fructose contents), and the concentrations of individual amino acids. Additionally, a T-test was conducted to compare the nectar volume and free sugar content between different flowering dates.

5. Conclusions

This study investigated the honey production potential of various B. napus cultivars and two wildflower species. Significant variability was observed in the quantity and sugar concentration of nectar produced per flower among B. napus cultivars. In the comparison of B. napus cultivars, ‘JM7003’ exhibited the highest honey production potential, followed by ‘YS’, ‘JM7001’, ‘TL’, and ‘TM’. Utilizing cultivars with high regional adaptability could be advantageous for establishing honey plant complexes. P. rotundum var. subintegrum and L. japonicus showed superior honey production potential compared to B. napus, suggesting their potential use in future honey plant complexes. The study results, examining the composition and changes in nectar components, sugar content, and amino acid content, are expected to provide valuable information for selecting honey plant species to increase food resources for pollinators and boost honey production. However, it is anticipated that actual honey production may be lower than the estimated potential due to bees using a significant portion of honey for brood rearing and hive maintenance. Finally, the diversity in amino acid composition across different honey plant species implies the potential to attract various types of pollinators and enhance honey production.

Author Contributions

S.-J.N., project administration, designed study, methodology, investigation, data analysis, draft writing, graphic design, formal analysis, statistical analysis, writing—review and editing, collecting references; Y.-K.K., methodology, investigation, planned and performed the experiments, writing—review and editing; J.-M.P., planned and performed the experiments; data curation; writing—review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by the National Institute of Forest Science [Project No. FG0403-2023-01-2023].

Data Availability Statement

Data are contained within the article.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Ioniță-Mîndrican, C.-B.; Mititelu, M.; Musuc, A.M.; Oprea, E.; Ziani, K.; Neacșu, S.M.; Grigore, N.D.; Negrei, C.; Dumitrescu, D.-E.; Mireșan, H.; et al. Honey and other Beekeeping products intake among the Romanian population and their therapeutic Use. Appl. Sci. 2022, 12, 9649. [Google Scholar] [CrossRef]
  2. Abd Rashid, N.; Mohammed, S.N.F.; Syed Abd Halim, S.A.; Ghafar, N.A.; Abdul Jalil, N.A. Therapeutic Potential of Honey and Propolis on Ocular Disease. Pharmaceuticals 2022, 15, 1419. [Google Scholar] [CrossRef]
  3. Bungau, S.G.; Popa, V.-C. Between religion and science: Some aspects: Concerning illness and healing in antiquity. Transylv. Rev. 2015, 26, 3–19. Available online: https://www.researchgate.net/publication/286442576 (accessed on 19 September 2023).
  4. Durazzo, A.; Lucarini, M.; Plutino, M.; Lucini, L.; Aromolo, R.; Martinelli, E.; Souto, E.B.; Santini, A.; Pignatti, G. Bee Products: A Representation of Biodiversity, Sustainability, and Health. Life 2021, 11, 970. [Google Scholar] [CrossRef]
  5. Morse, R.A.; Calderone, N.W. The value of honey bees as pollinators of US crops in 2000. Bee Cult. 2000, 128, 1–15. Available online: http://www.beeculture.com/beeculture/pollination2000 (accessed on 19 September 2023).
  6. Papa, G.; Maier, R.; Durazzo, A.; Lucarini, M.; Karabagias, I.K.; Plutino, M.; Bianchetto, E.; Aromolo, R.; Pignatti, G.; Ambrogio, A.; et al. The Honey Bee Apis mellifera: An Insect at the Interface between Human and Ecosystem Health. Biology 2022, 11, 233. [Google Scholar] [CrossRef] [PubMed]
  7. Isbell, F.; Adler, P.R.; Eisenhauer, N.; Fornara, D.; Kimmel, K.; Kremen, C.; Letourneau, D.K.; Liebman, M.; Polley, H.W.; Quijas, S.; et al. Benefits of increasing plant diversity in sustainable agroecosystems. J. Ecol. 2017, 105, 871–879. [Google Scholar] [CrossRef]
  8. Sutter, L.; Jeanneret, P.; Bartual, A.M.; Bocci, G.; Albrecht, M. Enhancing plant diversity in agricultural landscapes promotes both rare bees and dominant crop-pollinating bees through complementary increase in key floral resources. J. Appl. Ecol. 2017, 54, 1856–1864. [Google Scholar] [CrossRef]
  9. Futuyma, D.J.; Mitter, C. Insect-plant interactions: The evolution of component communities. Philos. Trans. R. Soc. Lond. B 1996, 351, 1361–1366. [Google Scholar] [CrossRef]
  10. Sharma, G.; Malthanar, P.A.; Mathur, V.; Notes, A. Insect-plant interactions: A multilayered relationship. Ann. Entomol. Soc. Am. 2021, 114, 1–16. [Google Scholar] [CrossRef]
  11. Baude, M.; Kunin, W.E.; Boatman, N.D.; Conyers, S.; Davies, N.; Gillespie, M.A.K.; Morton, R.D.; Smart, S.M.; Memmott, J. Historical nectar assessment reveals the fall and rise of floral resources in Britain. Nature 2016, 530, 85–88. [Google Scholar] [CrossRef]
  12. Reilly, J.R.; Artz, D.R.; Biddinger, D.; Bobiwash, K.; Boyle, N.K.; Brittain, C.; Brokaw, J.; Campbell, J.W.; Daniels, J.; Elle, E.; et al. Crop production in the USA is frequently limited by a lack of pollinators. Proc. R. Soc. B 2020, 287, 1931. [Google Scholar] [CrossRef]
  13. Neumann, P.; Carreck, N.L. Honey bee colony losses. J. Apic. Res. 2010, 49, 1–6. [Google Scholar] [CrossRef]
  14. Potts, S.G.; Roberts, S.P.M.; Dean, R.; Marris, G.; Brown, M.A.; Jones, R.; Neumann, P.; Settele, J. Declines of managed honey bees and beekeepers in Europe. J. Apic. Res. 2010, 49, 15–22. [Google Scholar] [CrossRef]
  15. Morawetz, L.; Köglberger, H.; Griesbacher, A.; Derakhshifar, I.; Crailsheim, K.; Brodschneider, R.; Moosbeckhofer, R. Health status of honey bee colonies (Apis mellifera) and disease-related risk factors for colony losses in Austria. PLoS ONE 2019, 14, e0219293. [Google Scholar] [CrossRef] [PubMed]
  16. López-Uribe, M.M.; Ricigliano, V.A.; Simone-Finstrom, M. Defining pollinator health: A holistic approach based on ecological, genetic, and physiological factors. Annu. Rev. Anim. Biosci. 2020, 8, 269–294. [Google Scholar] [CrossRef] [PubMed]
  17. Memmott, J.; Craze, P.G.; Waser, N.M.; Price, M.V. Global warming and the disruption of plant–pollinator interactions. Ecol. Lett. 2007, 10, 710–717. [Google Scholar] [CrossRef] [PubMed]
  18. Flores, J.M.; Gil-Lebrero, S.; Gámiz, V.; Rodríguez, M.I.; Ortiz, M.A.; Quiles, F.J. Effect of the climate change on honey bee colonies in a temperate Mediterranean zone assessed through remote hive weight monitoring system in conjunction with exhaustive colonies assessment. Sci. Total Environ. 2019, 653, 1111–1119. [Google Scholar] [CrossRef] [PubMed]
  19. Clermont, A.; Eickermann, M.; Kraus, F.; Hoffmann, L.; Beyer, M. Correlations between land covers and honey bee colony losses in a country with industrialized and rural regions. Sci. Total Environ. 2015, 532, 1–13. [Google Scholar] [CrossRef]
  20. Goulson, D.; Nicholls, E.; Botías, C.; Rotheray, E.L. Bee declines driven by combined stress from parasites, pesticides, and lack of flowers. Science 2015, 347, 1255957. [Google Scholar] [CrossRef]
  21. Potts, S.G.; Biesmeijer, J.C.; Kremen, C.; Neumann, P.; Schweiger, O.; Kunin, W.E. Global pollinator declines: Trends, impacts and drivers. Trends Ecol. Evol. 2010, 25, 345–353. [Google Scholar] [CrossRef]
  22. Favaro, R.; Bauer, L.M.; Rossi, M.; D’Ambrosio, L.; Bucher, E.; Angeli, S. Botanical origin of pesticide residues in pollen loads collected by honeybees during and after apple bloom. Front. Physiol. 2019, 10, 1069. [Google Scholar] [CrossRef] [PubMed]
  23. de Miranda, J.R.; Genersch, E. Deformed wing virus. J. Invertebr. Pathol. 2010, 103, S48–S61. [Google Scholar] [CrossRef] [PubMed]
  24. Smith, K.M.; Loh, E.H.; Rostal, M.K.; Zambrana-Torrelio, C.M.; Mendiola, L.; Daszak, P. Pathogens, pests, and economics: Drivers of honey bee colony declines and losses. EcoHealth 2013, 10, 434–445. [Google Scholar] [CrossRef] [PubMed]
  25. Fairbrother, A.; Purdy, J.; Anderson, T.; Fell, R. Risks of neonicotinoid insecticides to honeybees. Environ. Toxicol. Chem. 2014, 33, 719–731. [Google Scholar] [CrossRef] [PubMed]
  26. Decourtye, A.; Mader, E.; Desneux, N. Landscape enhancement of floral resources for honey bees in agro-ecosystems. Apidologie 2010, 41, 264–277. [Google Scholar] [CrossRef]
  27. Wratten, S.D.; Gillespie, M.; Decourtye, A.; Mader, E.; Desneux, N. Pollinator habitat enhancement: Benefits to other ecosystem services. Agric. Ecosyst. Environ. 2012, 159, 112–122. [Google Scholar] [CrossRef]
  28. Proesmans, W.; Bonte, D.; Smagghe, G.; Meeus, I.; Decocq, G.; Spicher, F.; Kolb, A.; Lemke, I.; Diekmann, M.; Bruun, H.H.; et al. Small forest patches as pollinator habitat: Oases in an agricultural desert? Landsc. Ecol. 2019, 34, 487–501. [Google Scholar] [CrossRef]
  29. Other Livestock Statistics. Available online: https://www.mafra.go.kr/bbs/home/798/567228/artclView.do?layout=unknown (accessed on 18 December 2023).
  30. Adgaba, N.; Al-Ghamdi, A.; Tadesse, Y.; Getachew, A.; Awad, A.M.; Ansari, M.J.; Owayss, A.A.; Mohammed, S.E.A.; Alqarni, A.S. Nectar secretion dynamics and honey production potentials of some major honey plants in Saudi Arabia. Saudi J. Biol. Sci. 2017, 24, 180–191. [Google Scholar] [CrossRef]
  31. Bareke, T.; Addi, A.; Wakjira, K.; Kumsa, T. Dynamics of nectar secretion, honey production potential and colony carrying capacity of Coffea arabica L., Rubiaceae. J. Agric. Environ. Int. 2021, 115, 125–138. [Google Scholar] [CrossRef]
  32. Kim, Y.K. A Study on the Valuation of Honey Plants by Investigating the Nectar Characteristics. Ph.D. Thesis, Kangwon National University, Kangwon, Republic of Korea, 2022. [Google Scholar]
  33. Simcock, N.K.; Gray, H.E.; Wright, G.A. Single amino acids in sucrose rewards modulate feeding and associative learning in the honeybee. J. Insect Physiol. 2014, 69, 41–48. [Google Scholar] [CrossRef]
  34. Paoli, P.P.; Donley, D.; Stabler, D.; Saseendranath, A.; Nicolson, S.W.; Simpson, S.J.; Wright, G.A. Nutritional balance of essential amino acids and carbohydrates of the adult worker honeybee depends on age. Amino Acids 2014, 46, 1449–1458. [Google Scholar] [CrossRef] [PubMed]
  35. Herrera, C.M.; Pérez, R.; Alonso, C. Extreme intraplant variation in nectar sugar composition in an insect-pollinated perennial herb. Am. J. Bot. 2006, 93, 575–581. [Google Scholar] [CrossRef] [PubMed]
  36. Antoñ, S.; Denisow, B. Nectar production and carbohydrate composition across floral sexual phases: Contrasting patterns in two protandrous Aconitum species (Delphinieae, Ranunculaceae). Flora 2014, 209, 464–470. [Google Scholar] [CrossRef]
  37. Lu, N.-N.; Li, X.-H.; Li, L.; Zhao, Z.-G. Variation of nectar production in relation to plant characteristics in protandrous Aconitum gymnandrum. J. Plant Ecol. 2015, 8, 122–129. [Google Scholar] [CrossRef]
  38. Waddington, K.D. Honey bee foraging profitability and round dance correlates. J. Comp. Physiol. 1982, 148, 297–301. [Google Scholar] [CrossRef]
  39. Grüter, C.; Ratnieks, F.L.W. Flower constancy in insect pollinators: Adaptive foraging behaviour or cognitive limitation? Commun. Integr. Biol. 2011, 4, 633–636. [Google Scholar] [CrossRef] [PubMed]
  40. Baker, H.G.; Baker, I. The occurrence and significance of amino acids in floral nectar. Plant Syst. Evol. 1986, 151, 175–186. [Google Scholar] [CrossRef]
  41. Petanidou, T.; Van Laere, A.; Ellis, W.N.; Smets, E. What shapes amino acid and sugar composition in Mediterranean floral nectars? Oikos 2006, 115, 155–169. [Google Scholar] [CrossRef]
  42. Nicolson, S.W.; Thornburg, R.W. Nectar chemistry. In Nectaries and Nectar; Nicolson, S.W., Nepi, M., Pacini, E., Eds.; Springer: Dordrecht, The Netherlands, 2007; pp. 215–264. [Google Scholar]
  43. Nepi, M. Beyond nectar sweetness: The hidden ecological role of non-protein amino acids in nectar. J. Ecol. 2014, 102, 108–115. [Google Scholar] [CrossRef]
  44. Haydak, M.H. Honey bee nutrition. Annu. Rev. Entomol. 1970, 15, 143–156. [Google Scholar] [CrossRef]
  45. Shiraishi, A.; Kuwabara, M. The effects of amino acids on the labellar hair chemosensory cells of the fly. J. Gen. Physiol. 1970, 56, 768–782. [Google Scholar] [CrossRef] [PubMed]
  46. Dadd, R.H. Insect nutrition: Current developments and metabolic implications. Annu. Rev. Entomol. 1973, 18, 381–420. [Google Scholar] [CrossRef] [PubMed]
  47. Poulis, B.A.D.; O’Leary, S.J.B.; Haddow, J.D.; von Aderkas, P. Identification of proteins present in the Douglas fir ovular secretion: An insight into conifer pollen selection and development. Int. J. Plant Sci. 2005, 166, 733–739. [Google Scholar] [CrossRef]
  48. Gardener, M.C.; Gillman, M.P. The taste of nectar—A neglected area of pollination ecology. Oikos 2002, 98, 552–557. [Google Scholar] [CrossRef]
  49. Tamm, S.; Gass, C.L. Energy intake rates and nectar concentration preferences by hummingbirds. Oecologia 1986, 70, 20–23. [Google Scholar] [CrossRef]
  50. Jang, J.W. A Study on Honey Plants in Korea—The Kind of Honey Plants in Korea and Around a Former Scanning Electron Microscope Form Structure of the Pollen. Ph.D. Thesis, Daegu University, Daegu, Republic of Korea, 2008. [Google Scholar]
  51. Škorić, D.; Jocić, S.; Sakac, Z.; Lećić, N. Genetic possibilities for altering sunflower oil quality to obtain novel oils. Can. J. Physiol. Pharmacol. 2008, 86, 215–221. [Google Scholar] [CrossRef]
  52. Enkegaard, A.; Kryger, P.; Boelt, B. Determinants of nectar production in oilseed rape. J. Apic. Res. 2016, 55, 89–99. [Google Scholar] [CrossRef]
  53. Wang, B.; Wu, Z.; Li, Z.; Zhang, Q.; Hu, J.; Xiao, Y.; Cai, D.; Wu, J.; King, G.J.; Li, H.; et al. Dissection of the genetic architecture of three seed-quality traits and consequences for breeding in Brassica napus. Plant Biotechnol. J. 2018, 16, 1336–1348. [Google Scholar] [CrossRef]
  54. Marles, M.S.; Gruber, M.Y. Histochemical characterisation of unextractable seed coat pigments and quantification of extractable lignin in the Brassicaceae. J. Sci. Food Agric. 2004, 84, 251–262. [Google Scholar] [CrossRef]
  55. Farkas, Á.; Zajácz, E. Nectar production for the Hungarian honey industry. Eur. J. Plant Sci. Biotechnol. 2007, 1, 125–151. Available online: https://www.researchgate.net/publication/228856362 (accessed on 21 September 2023).
  56. Shubharani, R.; Roopa, P.; Sivaram, V. Pollen morphology of selected bee forage plants. Glob. J. Bio-Sci. Biotechnol. 2013, 2, 82–90. Available online: https://www.academia.edu/download/31906096/GJBB_-_Shubha_et_al.pdf (accessed on 21 September 2023).
  57. Khan, K.A.; Ghramh, H.A. Pollen source preferences and pollination efficacy of honey bee, Apis mellifera (Apidae: Hymenoptera) on Brassica napus crop. J. King Saud Univ. Sci. 2021, 33, 101487. [Google Scholar] [CrossRef]
  58. Davis, A.R.; Sawhney, V.K.; Fowke, L.C.; Low, N.H. Floral nectar secretion and ploidy in Brassica rapa and B. napus (Brassicaceae). I. Nectary size and nectar carbohydrate production and composition. Apidologie 1994, 25, 602–614. [Google Scholar] [CrossRef]
  59. Free, J.B.; Nuttall, P.M. The pollination of oilseed rape (Brassica napus) and the behaviour of bees on the crop. J. Agric. Sci. 1968, 71, 91–94. [Google Scholar] [CrossRef]
  60. Albach, D.C.; Chase, M.W. Paraphyly of Veronica (Veroniceae; Scrophulariaceae): Evidence from the internal transcribed spacer (ITS) sequences of nuclear ribosomal DNA. J. Plant Res. 2001, 114, 9–18. [Google Scholar] [CrossRef]
  61. Luo, J.; Gong, Q.; Zhou, M.; Liu, Q.; Cheng, R.; Ge, Y. Complete chloroplast genome of the medicinal herb Veronicastrum axillare (Sieb. et Zucc.) Yamazaki and the phylogenetic relationship analysis within the tribe Veroniceae. Mitochondrial DNA Part B 2022, 7, 783–785. [Google Scholar] [CrossRef]
  62. Ding, S.X.; Jiang, H.; Tian, J.; Ren, J.; Mutie, F.M.; Waswa, E.N.; Hu, G.W.; Wang, Q.F. Veronicastrum Wulingense (Plantaginaceae), a New Species from Southwestern Hubei, China. Bot. Stud. 2023, 64, 3. [Google Scholar] [CrossRef]
  63. Albach, D.C.; Meudt, H.M.; Oxelman, B. Piecing together the “new” Plantaginaceae. Am. J. Bot. 2005, 92, 297–315. [Google Scholar] [CrossRef]
  64. Hawke, R.G. Comparative studies of Veronica and Veronicastrum. Plant Eval. Notes 2010, 33, 1–8. Available online: https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=3473917bbc02e2e9afd4964f54dd5ebddf38ef97 (accessed on 21 September 2023).
  65. Gao, W.; Zhang, R.; Jia, W.; Zhang, J.; Takaishi, Y.; Duan, H. Immunosuppressive diterpenes from Veronicastrum sibiricum. Chem. Pharm. Bull. 2004, 52, 136–137. [Google Scholar] [CrossRef]
  66. Kim, M.I.; Kim, C.Y. Four new acylated iridoid glycosides from the aerial part of Veronicastrum sibiricum and their antioxidant response element-inducing activity. Chem. Biodivers. 2018, 15, e1700447. [Google Scholar] [CrossRef]
  67. Wang, Z.; Liang, L.; Jie, M.; Wei, G. Anti-inflammation, analgesic and hemostatic effects of Veronicastrum sibiricum. Herald Med. 2017, 12, 489–492. Available online: https://pesquisa.bvsalud.org/portal/resource/pt/wpr-512344 (accessed on 21 September 2023).
  68. Yin, L.; Han, H.; Zheng, X.; Wang, G.; Li, Y.; Wang, W. Flavonoids analysis and antioxidant, antimicrobial, and anti-inflammatory activities of crude and purified extracts from Veronicastrum latifolium. Ind. Crops Prod. 2019, 137, 652–661. [Google Scholar] [CrossRef]
  69. Peng, C. Chinese Genuine Medicinal Materials; Chinese Press of Traditional Chinese Medicine: Beijing, China, 2011; pp. 4187–4188. [Google Scholar]
  70. Peng, F.; Xiong, L.; Zhao, X.M. A bicyclic diterpenoid with a new 15,16-dinorlabdane carbon skeleton from Leonurus japonicus and its coagulant bioactivity. Molecules 2013, 18, 13904–13909. [Google Scholar] [CrossRef] [PubMed]
  71. Xiong, L.; Peng, C.; Zhou, Q.M.; Wan, F.; Xie, X.F.; Guo, L.; Li, X.H.; He, C.J.; Dai, O. Chemical composition and antibacterial activity of essential oils from different parts of Leonurus japonicus Houtt. Molecules 2013, 18, 963–973. [Google Scholar] [CrossRef] [PubMed]
  72. Xiong, L.; Zhou, Q.M.; Zou, Y.K.; Chen, M.H.; Guo, L.; Hu, G.Y.; Liu, Z.H.; Peng, C. Leonuketal, a spiroketal diterpenoid from Leonurus japonicus. Org. Lett. 2015, 17, 6238–6241. [Google Scholar] [CrossRef]
  73. Yang, H.; Zhou, Q.M.; Peng, C.; Liu, L.S.; Xie, X.F.; Xiong, L.; Liu, Z.H. Coumarins from Leonurus japonicus and their anti-platelet aggregative activity. China J. Chin. Mater. Med. 2014, 39, 4356–4359. [Google Scholar]
  74. Zhou, Q.M.; Peng, C.; Yang, H.; Liu, L.S.; Yang, Y.T.; Xie, X.F.; Guo, L.; Liu, Z.H.; Xiong, L. Steroids from the aerial parts of Leonurus japonicus. Phytochem. Lett. 2015, 12, 287–290. [Google Scholar] [CrossRef]
  75. Peng, Y.; Zheng, C.; Wang, Y.N.; Dai, O. Novel labdane diterpenoids from the aerial parts of Leonurus japonicus. Phytochem. Lett. 2017, 20, 45–48. [Google Scholar] [CrossRef]
  76. Xiong, L.; Zhou, Q.M.; Peng, C.; Xie, X.F.; Liu, L.S.; Guo, L.; He, Y.C.; Yang, L.; Liu, Z.H. Bis-spirolabdane diterpenoids from Leonurus japonicus and their anti-platelet aggregative activity. Fitoterapia 2015, 100, 1–6. [Google Scholar] [CrossRef] [PubMed]
  77. He, Y.L.; Shi, J.Y.; Peng, C.; Hu, L.J.; Liu, J.; Zhou, Q.M.; Guo, L.; Xiong, L. Angiogenic effect of motherwort (Leonurus japonicus) alkaloids and toxicity of motherwort essential oil on zebrafish embryos. Fitoterapia 2018, 128, 36–42. [Google Scholar] [CrossRef] [PubMed]
  78. Liu, J.; Peng, C.; Zhou, Q.M.; Guo, L.; Liu, Z.H.; Xiong, L. Alkaloids and flavonoid glycosides from the aerial parts of Leonurus japonicus and their opposite effects on uterine smooth muscle. Phytochemistry 2018, 145, 128–136. [Google Scholar] [CrossRef] [PubMed]
  79. Bertazzini, M.; Forlani, G. Intraspecific variability of floral nectar volume and composition in rapeseed (Brassica napus L. var. oleifera). Front. Plant Sci. 2016, 7, 288. [Google Scholar] [CrossRef] [PubMed]
  80. Pierre, J.; Mesquida, J.; Marilleau, R.; Pham-Delègue, M.H.; Renard, M. Nectar secretion in winter oilseed rape, Brassica napus—Quantitative and qualitative variability among 71 genotypes. Plant Breed. 1999, 118, 471–476. [Google Scholar] [CrossRef]
  81. Mohr, N.A.; Jay, S.C. Nectar production of selected cultivars of Brassica campestris L. and Brassica napus L. J. Apic. Res. 1990, 29, 95–100. [Google Scholar] [CrossRef]
  82. Jakobsen, H.B.; Kristjansson, K. Influence of temperature and floret age on nectar secretion in Trifolium repens L. Ann. Bot. 1994, 74, 327–334. [Google Scholar] [CrossRef]
  83. Búrquez, A.; Corbet, S.A. Dynamics of production and exploitation of nectar: Lessons from Impatiens glandulifera Royle. In Nectary Biology; Dattsons: Nagpur, India, 1998; pp. 130–152. [Google Scholar]
  84. Li, Y.; Chen, Z.; Feng, Z.; Yang, Y.; Jiang, J.; Zhang, P. Hepatoprotective glycosides from Leonurus japonicus Houtt. Carbohydr. Res. 2012, 348, 42–46. [Google Scholar] [CrossRef]
  85. Wolff, D. Nectar sugar composition and volumes of 47 species of Gentianales from a southern Ecuadorian montane forest. Ann. Bot. 2006, 97, 767–777. [Google Scholar] [CrossRef]
  86. Petanidou, T. Sugars in Mediterranean floral nectars: An ecological and evolutionary approach. J. Chem. Ecol. 2005, 31, 1065–1088. [Google Scholar] [CrossRef]
  87. Chalcoff, V.R.; Aizen, M.A.; Galetto, L. Nectar concentration and composition of 26 species from the temperate forest of South America. Ann. Bot. 2006, 97, 413–421. [Google Scholar] [CrossRef]
  88. Abrol, D.P.; Shankar, U. Pollination in oil crops: Recent advances and future strategies. In Technological Innovations in Major World Oil Crops; Springer: New York, NY, USA, 2012; Volume 2, pp. 221–267. [Google Scholar] [CrossRef]
  89. Nepi, M. Nectary structure and ultrastructure. In Nectaries and Nectar; Nicolson, S.W., Nepi, M., Pacini, E., Eds.; Springer: Dordrecht, The Netherlands, 2007; pp. 129–166. [Google Scholar]
  90. Kevan, P.G.; Lee, H.; Shuel, R.W. Sugar ratios in nectars of varieties of canola (Brassica napus). J. Apic. Res. 1991, 30, 99–102. [Google Scholar] [CrossRef]
  91. Westcott, L.; Nelson, D. Canola pollination: An update. Bee World 2001, 82, 115–129. [Google Scholar] [CrossRef]
  92. Ruhlmann, J.M.; Kram, B.W.; Carter, C.J. CELL WALL INVERTASE 4 is required for nectar production in Arabidopsis. J. Exp. Bot. 2010, 61, 395–404. [Google Scholar] [CrossRef] [PubMed]
  93. Lohaus, G.; Schwerdtfeger, M. Comparison of sugars, iridoid glycosides and amino acids in nectar and phloem sap of Maurandya barclayana, Lophospermum erubescens, and Brassica napus. PLoS ONE 2014, 9, e87689. [Google Scholar] [CrossRef] [PubMed]
  94. Heil, M. Nectar: Generation, regulation and ecological functions. Trends Plant Sci. 2011, 16, 191–200. [Google Scholar] [CrossRef] [PubMed]
  95. Afik, O.; Dag, A.; Kerem, Z.; Shafir, S. Analyses of avocado (Persea americana) nectar properties and their perception by honey bees (Apis mellifera). J. Chem. Ecol. 2006, 32, 1949–1963. [Google Scholar] [CrossRef]
  96. Schmidt, K.; Orosz-Kovács, Z.S.; Farkas, Á. The effect of blossom structure and nectar composition of some raspberry and blackberry cultivars on the behaviour of pollinators. J. Plant Reprod. Biol. 2008, 1, 1–6. Available online: https://scholar.google.com/scholar_lookup?title=The+effect+of+blossom+structure+and+nectar+composition+of+some+raspberry+and+blackberry+cultivars+on+the+behaviour+of+pollinators&author=Schmidt,+K.&author=Orosz-Kov%C3%A1cs,+Z.S.&author=Farkas,+%C3%81.&publication_year=2008&journal=J.+Plant+Reprod.+Biol.&volume=1&pages=1%E2%80%936 (accessed on 21 September 2023).
  97. Wykes, G.R. The preferences of honey bees for solutions of various sugars which occur in nectar. J. Exp. Biol. 1952, 29, 511–519. [Google Scholar] [CrossRef]
  98. Baker, H.G.; Baker, I. Floral nectar sugars constituents in relation to pollinator type. In Handbook of Experimental Pollination Biology; Jones, C.E., Little, R.J., Eds.; Van Nostrand Reinhold Co.: New York, NY, USA, 1983; pp. 117–141. [Google Scholar]
  99. Elisens, W.J.; Freeman, C.E. Floral nectar sugar composition and pollinator type among new world genera in tribe Antirrhineae (Scrophulariaceae). Am. J. Bot. 1988, 75, 971–978. [Google Scholar] [CrossRef]
  100. van Wyk, B.E. Nectar sugar composition in southern African Papilionoideae (Fabaceae). Biochem. Syst. Ecol. 1993, 21, 271–277. [Google Scholar] [CrossRef]
  101. Baker, H.G.; Baker, I.; Hodges, S.A. Sugar composition of nectars and fruits consumed by birds and bats in the tropics deciduous forests. Biotropica 1998, 30, 559–586. [Google Scholar] [CrossRef]
  102. Galetto, L.; Bernardello, G. Sugar nectar composition in angiosperms from Chaco and Patagonia (Argentina): An animal visitor’s matter? Plant Syst. Evol. 2003, 238, 69–86. [Google Scholar] [CrossRef]
  103. Nicolson, S.W.; Fleming, P.A. Nectar as food for birds: The physiological consequences of drinking dilute sugar solutions. Plant Syst. Evol. 2003, 238, 139–153. [Google Scholar] [CrossRef]
  104. Dupont, Y.L.; Hansen, D.M.; Rasmussen, J.T.; Olesen, J.M. Evolutionary changes in nectar sugar composition associated with switches between bird and insect pollination: The Canarian bird-flower element revisited. Funct. Ecol. 2004, 18, 670–676. [Google Scholar] [CrossRef]
  105. van Wyk, B.E.; Whitehead, C.S.; Glen, H.F.; Hardy, D.S.; van Jaarsveld, E.J.; Smith, G.F. Nectar sugar composition in the subfamily Alooideae (Asphodelaceae). Biochem. Syst. Ecol. 1993, 21, 249–253. [Google Scholar] [CrossRef]
  106. Galetto, L.; Bernardello, G.; Sosa, C.A. The relationship between floral nectar composition and visitors in Lycium (Solanaceae) from Argentina and Chile: What does it reflect? Flora 1998, 193, 303–314. [Google Scholar] [CrossRef]
  107. Kingston, A.B.; Mc Quillan, P.B. Are pollination syndromes useful predictors of floral visitors in Tasmania? Austral Ecol. 2000, 25, 600–609. [Google Scholar] [CrossRef]
  108. Perret, M.; Chautems, A.; Spichiger, R.; Peixoto, M.; Savolainen, V. Nectar sugar composition in relation to pollination syndromes in Sinningieae (Gesneriaceae). Ann. Bot. 2001, 87, 267–273. [Google Scholar] [CrossRef]
  109. Wolff, D.; Witt, T.; Jürgens, A.; Gottsberger, G. Nectar dynamics and reproductive success in Saponaria officinalis (Caryophyllaceae) in southern Germany. Flora 2006, 201, 353–364. [Google Scholar] [CrossRef]
  110. Cavalcante, M.C.; Galetto, L.; Maués, M.M.; Pacheco Filho, A.J.S.; Bomfim, I.G.A.; Freitas, B.M. Nectar production dynamics and daily pattern of pollinator visits in Brazil nut (Bertholletia excelsa Bonpl.) plantations in Central Amazon: Implications for fruit production. Apidologie 2018, 49, 505–516. [Google Scholar] [CrossRef]
  111. Broyles, S.B.; Stoj, K.R. Patterns of nectar production in Asclepias curassavica (Apocynaceae). J. Poll. Ecol. 2019, 25, 78–88. [Google Scholar] [CrossRef]
  112. Irwin, R.E.; Adler, L.S. Nectar secondary compounds affect self-pollen transfer: Implications for female and male reproduction. Ecology 2008, 89, 2207–2217. [Google Scholar] [CrossRef] [PubMed]
  113. Kessler, D.; Bhattacharya, S.; Diezel, C.; Rothe, E.; Gase, K.; Schöttner, M.; Baldwin, I.T. Unpredictability of nectar nicotine promotes outcrossing by hummingbirds in Nicotiana attenuata. Plant J. 2012, 71, 529–538. [Google Scholar] [CrossRef]
  114. Leonhardt, S.D.; Blüthgen, N. The same, but different: Pollen foraging in honeybee and bumblebee colonies. Apidologie 2012, 43, 449–464. [Google Scholar] [CrossRef]
  115. Stephenson, A.G. Iridoid glycosides in the nectar of Catalpa speciosa are unpalatable to nectar thieves. J. Chem. Ecol. 1982, 8, 1025–1034. [Google Scholar] [CrossRef]
  116. Adler, L.S. The ecological significance of toxic nectar. Oikos 2000, 91, 409–420. [Google Scholar] [CrossRef]
  117. Pacini, E.; Nepi, M. Nectar production and presentation. In Nectaries and Nectar; Springer: Dordrecht, The Netherlands, 2007; pp. 167–214. [Google Scholar]
  118. Gottsberger, G.; Schrauwen, J.; Linskens, H.F. Amino acids and sugars in nectar, and their putative evolutionary significance. Plant Syst. Evol. 1984, 145, 55–77. [Google Scholar] [CrossRef]
  119. Gardener, M.C.; Gillman, M.P. Analyzing variability in nectar amino acids: Composition is less variable than concentration. J. Chem. Ecol. 2001, 27, 2545–2558. [Google Scholar] [CrossRef]
  120. Mevi-Schütz, J.; Erhardt, A. Amino acids in nectar enhance butterfly fecundity: A long-awaited link. Am. Nat. 2005, 165, 411–419. [Google Scholar] [CrossRef] [PubMed]
  121. Chalisova, N.I.; Kamyshev, N.G.; Lopatina, N.G.; Kontsevaya, E.A.; Urtieva, S.A.; Urtieva, T.A. Effect of encoded amino acids on associative learning of honey bee: Apis mellifera. J. Evol. Biochem. Physiol. 2011, 47, 607–610. [Google Scholar] [CrossRef]
  122. de Groot, A.P. Protein and amino acid requirements of the honey bee (Apis mellifera L.). Physiol. Comp. Oecol. 1953, 3, 197–285. Available online: https://lccn.loc.gov/54030108 (accessed on 5 October 2023).
  123. Somerville, D.C. Nutritional Value of Bee Collected Pollens; RIRDC Publication No. 01/047; New South Wales Agriculture: Canberra, Australia, 2001.
  124. McGregor, S.E. Insect Pollination of Cultivated Crop Plants; Agricultural Research Service; U.S. Government Publishing Office: Washington, DC, USA, 1976; 411p.
  125. Bertazzini, M.; Medrzycki, P.; Bortolotti, L.; Maistrello, L.; Forlani, G. Amino acid content and nectar choice by forager honeybees (Apis mellifera L.). Amino Acids 2010, 39, 315–318. [Google Scholar] [CrossRef] [PubMed]
  126. Hendriksma, H.P.; Oxman, K.L.; Shafir, S. Amino acid and carbohydrate tradeoffs by honey bee nectar foragers and their implications for plant–pollinator interactions. J. Insect Physiol. 2014, 69, 56–64. [Google Scholar] [CrossRef]
  127. Biancucci, M.; Mattioli, R.; Forlani, G.; Funck, D.; Costantino, P.; Trovato, M. Role of proline and GABA in sexual reproduction of angiosperms. Front. Plant Sci. 2015, 6, 680. [Google Scholar] [CrossRef]
  128. Hansen, K.; Wacht, S.; Seebauer, H.; Schnuch, M. New aspects of chemoreception in flies. Ann. N. Y. Acad. Sci. 1998, 855, 143–147. [Google Scholar] [CrossRef]
  129. Wacht, S.; Lunau, K.; Hansen, K. Chemosensory control of pollen ingestion in the hoverfly Eristalis tenax by labellar taste hairs. J. Comp. Physiol. A 2000, 186, 193–203. [Google Scholar] [CrossRef]
  130. Micheu, S.; Crailsheim, K.; Leonhard, B. Importance of proline and other amino acids during honeybee flight (Apis mellifera carnica POLLMANN). Amino Acids 2000, 18, 157–175. [Google Scholar] [CrossRef]
  131. Carter, C.; Shafir, S.; Yehonatan, L.; Palmer, R.G.; Thornburg, R. A novel role for proline in plant floral nectars. Naturwissenschaften 2006, 93, 72–79. [Google Scholar] [CrossRef]
  132. Alm, J.; Ohnmeiss, T.E.; Lanza, J.; Vriesenga, L. Preference of cabbage white butterflies and honey bees for nectar that contains amino acids. Oecologia 1990, 84, 53–57. [Google Scholar] [CrossRef]
  133. Verbruggen, N.; Hua, X.J.; May, M.; Van Montagu, M. Environmental and developmental signals modulate proline homeostasis: Evidence for a negative transcriptional regulator. Proc. Natl. Acad. Sci. USA 1996, 93, 8787–8791. [Google Scholar] [CrossRef]
  134. Kaczorowski, R.L.; Gardener, M.C.; Holtsford, T.P. Nectar traits in Nicotiana section alatae (Solanaceae) in relation to floral traits, pollinators, and mating system. Am. J. Bot. 2005, 92, 1270–1283. [Google Scholar] [CrossRef] [PubMed]
  135. Nicolson, S.W.; Nepi, M.; Pacini, E. Nectar consumers. In Nectaries and Nectar; Nicolson, S.W., Ed.; Springer: Dordrecht, The Netherlands, 2007; pp. 312–322. [Google Scholar]
  136. Nepi, M.; von Aderkas, P.; Wagner, R.; Mugnaini, S.; Coulter, A.; Pacini, E. Nectar and pollination drops: How different are they? Ann. Bot. 2009, 104, 205–219. [Google Scholar] [CrossRef]
  137. Otvos, L.; Insug, O.; Rogers, M.E.; Consolvo, P.J.; Condie, B.A.; Lovas, S.; Bulet, P.; Blaszczyk-Thurin, M. Interaction between heat shock proteins and antimicrobial peptides. Biochemistry 2000, 39, 14150–14159. [Google Scholar] [CrossRef]
  138. Rolland, J.L.; Abdelouahab, M.; Dupont, J.; Lefevre, F.; Bachère, E.; Romestand, B. Stylicins, a new family of antimicrobial peptides from the Pacific blue shrimp Litopenaeus stylirostris. Mol. Immunol. 2010, 47, 1269–1277. [Google Scholar] [CrossRef]
  139. Avitabile, C.; D’Andrea, L.D.; Romanelli, A. Circular dichroism studies on the interactions of antimicrobial peptides with bacterial cells. Sci. Rep. 2014, 4, 4293. [Google Scholar] [CrossRef] [PubMed]
  140. De Souza Cândido, E.; e Silva Cardoso, M.H.; Sousa, D.A.; Viana, J.C.; de Oliveira-Júnior, N.G.; Miranda, V.; Franco, O.L. The use of versatile plant antimicrobial peptides in agribusiness and human health. Peptides 2014, 55, 65–78. [Google Scholar] [CrossRef] [PubMed]
  141. Ligoxygakis, P.; Pelte, N.; Hoffmann, J.A.; Reichhart, J.M. Activation of Drosophila Toll during fungal infection by a blood serine protease. Science 2002, 297, 114–116. [Google Scholar] [CrossRef] [PubMed]
  142. Vannette, R.L.; Mohamed, A.; Johnson, B.R. Forager bees (Apis mellifera) highly express immune and detoxification genes in tissues associated with nectar processing. Sci. Rep. 2015, 5, 16224. [Google Scholar] [CrossRef] [PubMed]
  143. Hrassnigg, N.; Leonhard, B.; Crailsheim, K. Free amino acids in the haemolymph of honey bee queens (Apis mellifera L.). Amino Acids 2003, 24, 205–212. [Google Scholar] [CrossRef] [PubMed]
  144. Qiu, X.M.; Sun, Y.Y.; Ye, X.Y.; Li, Z.G. Signaling role of glutamate in plants. Front. Plant Sci. 2020, 10, 1743. [Google Scholar] [CrossRef] [PubMed]
  145. Lanza, J.; Smith, G.C.; Sack, S.; Cash, A. Variation in nectar volume and composition of Impatiens capensis at the individual, plant, and population levels. Oecologia 1995, 102, 113–119. [Google Scholar] [CrossRef]
  146. Chapman, R.F. The Insects: Structure and Function; Cambridge University Press: New York, NY, USA, 2012. [Google Scholar]
  147. Anraku, M.; Shintomo, R.; Taguchi, K.; Kragh-Hansen, U.; Kai, T.; Maruyama, T.; Otagiri, M. Amino acids of importance for the antioxidant activity of human serum albumin as revealed by recombinant mutants and genetic variants. Life Sci. 2015, 134, 36–41. [Google Scholar] [CrossRef] [PubMed]
  148. Duan, J.; Yin, J.; Ren, W.; Liu, T.; Cui, Z.; Huang, X.; Wu, L.; Kim, S.W.; Liu, G.; Wu, X.; et al. Dietary supplementation with L-glutamate and L-aspartate alleviates oxidative stress in weaned piglets challenged with hydrogen peroxide. Amino Acids 2016, 48, 53–64. [Google Scholar] [CrossRef] [PubMed]
  149. Chatt, E.C.; Von Aderkas, P.; Carter, C.J.; Smith, D.; Elliott, M.; Nikolau, B.J. Sex-dependent variation of pumpkin (Cucurbita maxima cv. Big Max) nectar and nectaries as determined by proteomics and metabolomics. Front. Plant Sci. 2018, 9, 860. [Google Scholar] [CrossRef]
  150. Inouye, D.W.; Waller, G.D. Responses of honeybees (Apis mellifera) to amino acid solutions mimicking floral nectars. Ecology 1984, 65, 618–625. [Google Scholar] [CrossRef]
  151. Gardener, M.C.; Gillman, M.P. The effects of soil fertilizer on amino acids in the floral nectar of corncockle, Agrostemma githago (Caryophyllaceae). Oikos 2021, 92, 101–106. [Google Scholar] [CrossRef]
  152. Nepi, M.; Soligo, C.; Nocentini, D.; Abate, M.; Guarnieri, M.; Cai, G.; Bini, L.; Puglia, M.; Bianchi, L.; Pacini, E. Amino acids and protein profile in floral nectar: Much more than a simple reward. Flora 2012, 207, 475–481. [Google Scholar] [CrossRef]
  153. Nocentini, D.; Pacini, E.; Guarnieri, M.; Nepi, M. Flower morphology, nectar traits and pollinators of Cerinthe major (Boraginaceae-Lithospermeae). Flora 2012, 207, 186–196. [Google Scholar] [CrossRef]
  154. Baker, H.G. Non-sugar chemical constituents of nectar. Apidologie 1977, 8, 349–356. Available online: https://www.apidologie.org/articles/apido/pdf/1977/04/Apidologie_0044-8435_1977_8_4_ART0005.pdf (accessed on 27 January 2024). [CrossRef]
  155. Kim, K.S.; Jang, Y.S.; Lee, Y.H.; Kim, C.W.; Choi, K.H.; Kang, D.S.; Kim, S.T.; Choi, I.H. A rapeseed intermediate parent ‘Jungmo 7001’ with wide adaptable and large flower. Korean J. Breed. Sci. 2014, 46, 302–306. [Google Scholar] [CrossRef]
  156. Kim, K.S.; Jang, Y.S.; Lee, Y.H.; Choi, K.H.; Shin, J.H.; Lee, K.B. A new rapeseed variety ‘Jungmo 7003’ with white flower, early flowering and disease resistance. Korean J. Breed. Sci. 2016, 48, 339–343. [Google Scholar] [CrossRef]
  157. Swanson, C.A.; Shuel, R.W. The centrifuge method for measuring nectar yield. Plant Physiol. 1950, 25, 513–520. [Google Scholar] [CrossRef] [PubMed]
  158. Armstrong, D.P.; Paton, D.C. Methods for measuring amounts of energy available from banksia inflorescences. Austral Ecol. 1990, 15, 291–297. [Google Scholar] [CrossRef]
  159. Petanidou, T. Introducing plants for bee-keeping at any cost?—Assessment of Phacelia tanacetifolia as nectar source plant under xeric Mediterranean conditions. Plant Syst. Evol. 2023, 238, 155–168. [Google Scholar] [CrossRef]
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Figure 1. Sugar composition in the floral nectar of five B. napus cultivars. Data were subjected to one-way ANOVA with post hoc comparisons using Duncan’s multiple range test at the 5% level. Different letters in each column indicate statistical differences, and n.s. means non-significance.
Figure 1. Sugar composition in the floral nectar of five B. napus cultivars. Data were subjected to one-way ANOVA with post hoc comparisons using Duncan’s multiple range test at the 5% level. Different letters in each column indicate statistical differences, and n.s. means non-significance.
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Plants 13 00419 g002
Figure 2. Amino acid contents of five B. napus cultivars. Results are expressed as either absolute concentrations (A) or the composition of the total amino acid content (B). Data were subjected to one-way ANOVA with post hoc comparisons using Duncan’s multiple range test at the 5% level. * and ** indicate significant differences between cultivars at p < 0.05 and <0.01, respectively.
Figure 2. Amino acid contents of five B. napus cultivars. Results are expressed as either absolute concentrations (A) or the composition of the total amino acid content (B). Data were subjected to one-way ANOVA with post hoc comparisons using Duncan’s multiple range test at the 5% level. * and ** indicate significant differences between cultivars at p < 0.05 and <0.01, respectively.
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Plants 13 00419 g003
Figure 3. Sugar composition in collected floral nectar from P. rotundum var. subintegrum (A) and L. japonicus (B). Data were subjected to one-way ANOVA with post hoc comparisons using Duncan’s multiple range test at the 5% level. Different letters in each column indicate statistical differences.
Figure 3. Sugar composition in collected floral nectar from P. rotundum var. subintegrum (A) and L. japonicus (B). Data were subjected to one-way ANOVA with post hoc comparisons using Duncan’s multiple range test at the 5% level. Different letters in each column indicate statistical differences.
Plants 13 00419 g003
Plants 13 00419 g004
Figure 4. Amino acid contents as absolute concentrations (A) and composition as percent values of the total amino acid content (B) of P. rotundum var. subintegrum. Explanations: Arg—arginine, His—histidine, Iso—isoleucine, Leu—leucine, Lys—lysine, Phe—phenylalanine, Thr—threonine, Try—tryptophan, Val—valine, Ala—alanine, Asp—asparagine, Asa—aspartic acid, Gla—glutamic acid, Glt—glutamine, Gly—glycine, Pro—proline, Ser—serine, Tyr—tyrosine, Tau—taurine.
Figure 4. Amino acid contents as absolute concentrations (A) and composition as percent values of the total amino acid content (B) of P. rotundum var. subintegrum. Explanations: Arg—arginine, His—histidine, Iso—isoleucine, Leu—leucine, Lys—lysine, Phe—phenylalanine, Thr—threonine, Try—tryptophan, Val—valine, Ala—alanine, Asp—asparagine, Asa—aspartic acid, Gla—glutamic acid, Glt—glutamine, Gly—glycine, Pro—proline, Ser—serine, Tyr—tyrosine, Tau—taurine.
Plants 13 00419 g004
Plants 13 00419 g005
Figure 5. Amino acid contents as absolute concentrations (A) and composition as percent values of the total amino acid content (B) of L. japonicus. Explanations: Arg—arginine, His—histidine, Iso—isoleucine, Leu—leucine, Lys—lysine, Met—methionine, Phe—phenylalanine, Thr—threonine, Try—tryptophan, Val—valine, Ala—alanine, Asp—asparagine, Asa—aspartic acid, Gla—glutamic acid, Glt—glutamine, Gly—glycine, Pro—proline, Ser—serine, Tyr—tyrosine, Tau—taurine, Orn—ornithine.
Figure 5. Amino acid contents as absolute concentrations (A) and composition as percent values of the total amino acid content (B) of L. japonicus. Explanations: Arg—arginine, His—histidine, Iso—isoleucine, Leu—leucine, Lys—lysine, Met—methionine, Phe—phenylalanine, Thr—threonine, Try—tryptophan, Val—valine, Ala—alanine, Asp—asparagine, Asa—aspartic acid, Gla—glutamic acid, Glt—glutamine, Gly—glycine, Pro—proline, Ser—serine, Tyr—tyrosine, Tau—taurine, Orn—ornithine.
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Plants 13 00419 g006
Figure 6. Flower and inflorescence shapes of B. napus ((A), ‘Jungmo 7003’), P. rotundum var. subintegrum (B), and L. japonicus (C).
Figure 6. Flower and inflorescence shapes of B. napus ((A), ‘Jungmo 7003’), P. rotundum var. subintegrum (B), and L. japonicus (C).
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Table 1. Results of the survey on flower characteristics and plant density.
Table 1. Results of the survey on flower characteristics and plant density.
CultivarsFlowering
Period		Height (cm)No. of Flowers (ea/plant)Plant Density
(m2/plant)
MeanRange
‘JM7003’5/25–6/1373.1 ± 13.7 a65.3 ± 8.7 a49–77148.8 ± 39.9 n.s.
‘YS’5/27–6/1353.4 ± 7.9 d31.8 ± 7.2 c21–42161.0 ± 31.2
‘TM’5/30–6/1654.7 ± 10.3 cd27.2 ± 5.3 c16–34142.0 ± 27.4
‘TL’5/30–6/1660.7 ± 9.4 bc33.2 ± 10.2 c23–49145.3 ± 9.2
‘JM7001’5/30–6/2065.3 ± 11.0 b43.7 ± 5.9 b36–56158.7 ± 20.1
p-value-<0.0001<0.0001-0.8829
Data represent the means ± SD. Data were subjected to one-way ANOVA with post hoc comparisons using Duncan’s multiple range test at the 5% significance level. Different letters in each column indicate statistical differences, and n.s. indicates non-significance.
Table 2. Nectar secretion and sugar characteristics of five B. napus cultivars.
Table 2. Nectar secretion and sugar characteristics of five B. napus cultivars.
CultivarsNectar Volume
(μL/flower)		Free Sugar Content (μg/μL)
SucroseGlucoseFructoseTotal
‘JM7003’1.54 ± 0.33 a10.1 ± 2.3 c307.5 ± 58.9 c325.3 ± 60.7 c641.0 ± 118.7 c
‘YS’1.08 ± 0.21 b19.3 ± 6.6 ab564.3 ± 122.0 ab563.2 ± 122.0 ab1146.8 ± 248.6 ab
‘TM’0.73 ± 0.18 b25.0 ± 5.0 a656.8 ± 200.6 a667.7 ± 181.0 a1349.4 ± 381.3 a
‘TL’0.81 ± 0.23 b13.5 ± 2.3 bc575.2 ± 132.2 ab585.7 ± 135.5 a1174.4 ± 269.8 ab
‘JM7001’1.04 ± 0.18 b12.3 ± 4.2 c388.8 ± 133.1 bc384.1 ± 132.2 bc785.25 ± 269.4 bc
p-value0.00050.00040.00620.00460.0048
Data represent the means ± SD. Data were subjected to one-way ANOVA with post hoc comparisons using Duncan’s multiple range test at the 5% significance level. Different letters in each column indicate significant differences between the groups.
Table 3. Estimation of honey production considering the nectar and flowering characteristics of five B. napus cultivars.
Table 3. Estimation of honey production considering the nectar and flowering characteristics of five B. napus cultivars.
Honey Potential‘JM7003’‘YS’‘TM’‘TL’‘JM7001’
Nectar sugar content 10.96 ± 0.021.24 ± 0.320.96 ± 0.240.95 ± 0.310.80 ± 0.20
Honey production per plant 272.0 (54–85)45.3 (30–60)29.9 (18–37)36.3 (25–54)40.2 (33–52)
Honey yield per hectare 3107.1 (81–141)73.0 (54–89)42.4 (36–54)52.7 (51–57)63.7 (56–72)
Data represent the means ± SD, and range data are given in parentheses. 1 Nectar sugar content (mg/flower) = nectar volume (μL/flower) × free sugar content (μg/μL) × 0.001 (for unit conversion: μg to mg). 2 Honey production (mg/plant) = nectar sugar content (mg/flower) × number of flowers per plant (ea/plant) × honey potential (1.15). 3 Honey yield (kg/ha) = honey production (mg/plant) × number of plants per hectare (ea/ha) × 0.000001 (for unit conversion: mg to kg). Nectar volume and the free sugar content can be found in Table 2. The number of flowers and the number of plants per hectare can be found in Table 1.
Table 4. Results of the survey on the growth and flower characteristics of P. rotundum var. subintegrum and L. japonicus.
Table 4. Results of the survey on the growth and flower characteristics of P. rotundum var. subintegrum and L. japonicus.
CharacteristicP. rotundum var. subintegrumL. japonicus
Flowering period19 July–30 August2 August–2 September
Plant height (cm)83.0 ± 13.6124.8 ± 27.8
Number of flowers (ea/plant)3422 ± 370 (2064–5490)2894 ± 318 (1320–4490)
Planting density (m2/plant)17.5; 30 × 25 cm17.5; 30 × 25 cm
Data represent the means ± SD, and range data are given in parentheses.
Table 5. Nectar volume, free sugar content and nectar sugar content of P. rotundum var. subintegrum and L. japonicus.
Table 5. Nectar volume, free sugar content and nectar sugar content of P. rotundum var. subintegrum and L. japonicus.
Nectar CharacteristicsFlowering Timet-Test
First DaySecond Day
P. rotundum var. subintegrum
 Nectar volume (μL/flower)0.07 ± 0.010.30 ± 0.09p = 0.0114
 Free sugar content (μg/μL)828.7 ± 266.2767.9 ± 206.8n.s.
  - Sucrose407.9 ± 116.5310.2 ± 103.0n.s.
  - Glucose197.7 ± 86.0211.2 ± 45.8n.s.
  - Fructose232.2 ± 93.8246.5 ± 59.9n.s.
 Nectar sugar content (mg/flower) *0.06 ± 0.030.22 ± 0.02p = 0.0015
L. japonicus
 Nectar volume (μL/flower)0.16 ± 0.050.33 ± 0.01p = 0.0057
 Free sugar content (μg/μL)775.4 ± 88.6816.3 ± 139.4n.s.
  - Sucrose624.7 ± 73.8631.1 ± 95.1n.s.
  - Glucose71.8 ± 8.588.9 ± 21.3n.s.
  - Fructose78.9 ± 7.896.3 ± 23.5n.s.
 Nectar sugar content (mg/flower) *0.12 ± 0.040.26 ± 0.03p = 0.0106
Data represent the means ± SD. T-test between flowering times, significant at p = 0.05. n.s. indicates non-significance. * Nectar sugar content (mg/flower) = nectar volume (μL/flower) × free sugar content (μg/μL) × 0.001 (for unit conversion: μg to mg).
Table 6. Estimation of honey production considering the nectar and flowering characteristics of P. rotundum var. subintegrum and L. japonicus.
Table 6. Estimation of honey production considering the nectar and flowering characteristics of P. rotundum var. subintegrum and L. japonicus.
Honey PotentialP. rotundum var. subintegrumL. japonicus
Honey production per plant 1870.6 (525–1397)864.6 (394–1341)
Honey yield per hectare 2152.4 (92–244)151.3 (69–235)
Range data are given in parentheses. 1 Honey production (mg/plant) = nectar sugar content (mg/flower) × flower number per plant (ea/plant) × honey potential (1.15). 2 Honey yield (kg/ha) = honey production (mg/plant) × number of plants per hectare (ea/ha) × 0.000001 (for unit conversion: mg to kg). Nectar sugar content per flower can be found in Table 5. The number of flowers (ea/plant) and the number of plants per hectare (m2/plant) can be found in Table 4.
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Na, S.-J.; Kim, Y.-K.; Park, J.-M. Nectar Characteristics and Honey Production Potential of Five Rapeseed Cultivars and Two Wildflower Species in South Korea. Plants 2024, 13, 419. https://doi.org/10.3390/plants13030419

AMA Style

Na S-J, Kim Y-K, Park J-M. Nectar Characteristics and Honey Production Potential of Five Rapeseed Cultivars and Two Wildflower Species in South Korea. Plants. 2024; 13(3):419. https://doi.org/10.3390/plants13030419

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Na, Sung-Joon, Young-Ki Kim, and Ji-Min Park. 2024. "Nectar Characteristics and Honey Production Potential of Five Rapeseed Cultivars and Two Wildflower Species in South Korea" Plants 13, no. 3: 419. https://doi.org/10.3390/plants13030419

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