be more associated to cheerfulness. In addition, trait cheerfulness is related to a greater coping with and recovery from negative emotions (see Papousek and Schulter, 2010; Ruch and Hofmann, 2012), which has also been associated with cognitive flexibility processes (Malooly et al., 2013). In a recent study (López-Benítez et al., under review), it has been found that people with high versus low trait cheerfulness frequently use reappraisal strategies in their daily lives. However, they did not have a better ability to apply reappraisal strategies for down- regulating negative emotions. In this sense, if our task is testing cognitive flexibility as ability rather than a general use of it, it could be thought that the frequent use of reappraisal strategies is not enough to also have a greater cognitive flexibility. In any case, future studies are needed to test these hypotheses.

The present pattern of results could be influenced by the sample size. To solve this limitation, we carried out an omnibus analysis with data from Study 1 (N = 49), Study 2 (N = 48), and our unpublished study (N = 46), with a total of 72 high trait cheerfulness participants and 71 low trait cheerfulness participants. Only trials that appeared in all studies were selected, that is, trials where there was not a prior preparation to the task, given that the preparation condition was presented in some studies but not in others. The mixed ANOVA with Task Change (Different vs. Same) as within participants variable and Group (High Trait Cheerfulness vs. Low Trait Cheerfulness) and Study as between participants variables showed a complete absence of Group × Task Change interaction, F(1,137) = 0.07, p = 0.791, η 2 = 0.00.

In order to see whether this absence of evidence could be taken as evidence for absence of modulation of group over the task-switching costs, a Bayesian approach was used. This procedure assesses how much support we could obtain for the null hypothesis through the Bayes Factor (BF10), which represents how strongly a result supports our hypothesis (i.e., lower task-switching cost for high trait cheerfulness people, or Group × Task Change interaction, H1) over the null hypothesis (i.e., no Group × Task Change interaction). Three ranges of values for BF10 are commonly accepted to interpret the output: (a) evidence of the absence of an effect (from 0 up to 0.33); (b) inconclusive evidence (from 0.33 up to 3); (c) evidence of an effect (from 3 and up). The Bayesian analysis was carried out with JASP Team (2017). Our results indicated, again reflecting that taskswitching cost did not depend on trait cheerfulness, substantial evidence for a null effect (BF10 = 0.186, for the Group × Task Change interaction or a t-test comparing the two groups on the task-switching cost).

A tentative explanation of the present results is related to the subject of this research and the demands required by the task itself. Cheerfulness is a positive affective predisposition associated with sense of humor (Ruch and Köhler, 2007). It is therefore related to the manifestation, enhancement, and maintenance of positive emotions, along with a lower manifestation of negative emotions and a higher resilience to them (Zweyer et al., 2004; Papousek and Schulter, 2010). This endows it with qualities that are very closely linked to processes of an emotional nature, such as induction processes, regulation, and emotional intelligence (e.g., Ruch, 1997; Yip and Martin, 2006), and processes more related to social interaction and empathy (e.g., Ruch and Köhler, 2007; Beermann and Ruch, 2009). From this viewpoint, given the affective, humoristic, communicative, expressive, and social characteristics that compound trait cheerfulness, it might be possible that trait cheerfulness has a higher predictive power and play a relevant role in tasks that involve processes of this nature, compared to cognitive tasks which do not include elements typical of humoristic, emotional, or social stimulation. Further research needs to be carried out in this field to clarify these ideas.

In addition, and although this was not our main goal, in Study 1 and in the preparation part of Study 2 we observed that, compared to individuals with low trait cheerfulness, those with high trait cheerfulness showed a higher effect of attribute repetition between two consecutive trials (e.g., Hommel, 2004). They also showed a tendency toward a higher effect of preparation when presented with a cue anticipating the demand in a trial that immediately followed (e.g., Kiesel et al., 2010) that was even higher in the expressed emotion recognition task (Study 1).

To our knowledge, no studies have explored the modulation of the effects of attribute repetition by predisposition to affective states (or affective states themselves). However, if our findings are confirmed, it may be possible to explain them in terms of the broaden-and-build theory (Fredrickson, 2001). According to this approach, positive states often lead to a more holistic processing of the context, thus expanding the attention focus (see, for example, Johnson et al., 2010). Taking into account that trait cheerfulness is a predisposition toward positive affective states, it could be inferred that individuals with high trait cheerfulness are defined by a more global processing style. In this sense, even if all participants were to benefit from attribute repetition between consecutive trials and from a cue anticipating the next demand, it would be possible to theorize that, due to their more global mindset configuration, individuals with high trait cheerfulness benefit more from these facilitation effects, having the information on the demand to carry out more active in their short-term memory, which would improve their immediate response, particularly in the expressed emotion recognition task (Study 1), which is considered more complicated (e.g., Egner et al., 2008; Ochsner et al., 2009).

Another possible explanation is derived from affective induction contexts. In a recent study, López-Benítez et al. (in press) have found that, compared to low trait cheerfulness people, individuals characterized by high trait cheerfulness experienced a larger affective state change as a consequence of watching amusing and sad stimuli. The authors interpreted this finding as larger affective sensitivity or permeability to the environment, thus promoting some psychological, social, and physical benefits in high trait cheerfulness individuals (e.g., Yip and Martin, 2006; Carretero-Dios et al., 2014; Delgado-Domínguez et al., 2016). In this sense, it is possible that the presentation of a cue to anticipate the task might be a powerful element to capture and focus high cheerfulness people's attention, promoting a better permeability (larger preparation effects) to it. Moreover, this fact also would explain, at least partially, the larger attribute repetition effect for high trait cheerfulness individuals that was only significant when a cue that prepares to a subsequent demand was displayed.

Therefore, from this point of view, it might be possible that high trait cheerfulness individuals have a higher receptivity to process useful and relevant nuances and contextual cues, which could help them to a better adaptation to the environment. In any case, future studies should replicate and extend these findings in order to understand the role of trait cheerfulness on these phenomena.

Notwithstanding the importance of the results, our study had some limitations. First, as pointed out above, participants in our studies were selected according to their trait cheerfulness scores. Ruch et al. (1996, 1997) suggest that the temperamental basis of sense of humor have two manifestations, as traits and as states, which are closely related to one another. Clear dissociations have been observed between traits and states, which have differential modulation effects on attentional processes in other areas such as anxiety (Pacheco-Unguetti et al., 2010). In addition, and following Fredrickson's (2001) theoretical proposal, a positive affective induction rather than a positive trait might have a greater impact in aspects such as cognitive resources. Therefore, it would be interesting to verify whether the induction of state cheerfulness, as opposed to the selection of participants with high trait cheerfulness, would have the same effects as those caused by trait cheerfulness or if, on the other hand, participants' state at the time of the task is a more powerful predictive factor to explain cognitive flexibility. Moreover, further research is needed to assess whether other elements of sense of humor are relevant for making predictions on this type of processes. For example, taking into account that the task used here might put participants in a telic state of mind, that is, more goal oriented (Apter and Smith, 1977) and assuming that seriousness is described from a cognitive, attitudinal, and reflexive perspective, trait or, even more importantly, state seriousness may modulate to a greater extent the effect of these processes, which have a more cognitive nature. Additionally, based on studies that have found a relationship between negative affective states and a poorer performance in multitasking conditions, which require high cognitive flexibility (Morgan and D'Mello, 2016), it could be inferred that bad mood, through its affective properties, may also modulate cognitive flexibility, leading to a lower task-switching cost.

Second, taking into account that trait cheerfulness is linked to personality characteristics that may affect the performance on tasks that require cognitive flexibility (e.g., Compton, 2000; Jensen-Campbell et al., 2002), they should be incorporated in future studies together with related variables such as, for example, optimism, to observe their differential weight in cognitive tasks compared to trait cheerfulness.

#### REFERENCES

Finally, assuming the conceptualization of the cheerfulness construct (for a review, see Ruch and Hofmann, 2012), it might be more interesting to analyze the modulation of emotional induction processes by cheerfulness, in its trait and state manifestation, in the presence not only of positive but also of negative emotions. It would also be interesting to explore its possible relationship with emotion regulation strategies, which are involved in these processes with the goal of modifying the affective response experienced by an individual.

In short, two studies were conducted in this research to verify whether individuals with high trait cheerfulness, compared to those with low trait cheerfulness, showed higher cognitive flexibility, manifested as a lower task-switching cost. The results did not confirm this scenario. This is important taking into account that a relation between this cheerfulness and cognitive flexibility can be predicted from the literature on both humor and cheerfulness. Nevertheless, individuals with high versus low trait cheerfulness showed higher effects of attribute repetition and task preparation. Therefore, although replication of this finding seems necessary, it suggests a new path of exploration. The higher permeability to contextual cues of high cheerfulness individuals shown in the current and previous studies (López-Benítez et al., in press) could underlay a better adaptation to the environment that calls for future research. In addition, new studies should analyze whether these effects can be generalized to other cognitive processes such as creativity while exploring the modulation of affective processes by cheerfulness.

### AUTHOR CONTRIBUTIONS

Conceived and designed the experiments: RL-B, JL, AA, HC-D. Performed the experiments: RL-B. Analyzed the data: RL-B, JL, AA, HC-D. Interpreted the data and drafted the manuscript: RL-B, JL, AA, HC-D. All authors read and accepted the final manuscript submitted for publication.

### FUNDING

This research is part of the doctoral dissertation by RL-B, and it was supported by the Spanish Ministerio de Educación, Cultura, y Deporte with a predoctoral grant (FPU-AP2012- 1806) and with the Spanish grants of PSI2014-52764-P, from Ministerio de Economía, Industria, y Competitividad (MINECO), and PSI2013-45567P from Dirección General de Investigación Científica y Técnica-Ministerio de Educación y Ciencia (DGICYT-MEC).

trait version of the State-Trait-Cheerfulness-Inventory. Pers. Individ. Dif. 68, 77–82. doi: 10.1016/j.paid.2014.03.045

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2017 López-Benítez, Carretero-Dios, Acosta and Lupiáñez. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Are Clowns Good for Everyone? The Influence of Trait Cheerfulness on Emotional Reactions to a Hospital Clown Intervention

#### Sarah Auerbach\*

Personality and Assessment, Department of Psychology, University of Zurich, Zürich, Switzerland

Trait cheerfulness predicts individual differences in experiences and behavioral responses in various humor experiments and settings. The present study is the first to investigate whether trait cheerfulness also influences the impact of a hospital clown intervention on the emotional state of patients. Forty-two adults received a clown visit in a rehabilitation center and rated their emotional state and trait cheerfulness afterward. Facial expressions of patients during the clown visit were coded with the Facial Action Coding System. Looking at the total sample, the hospital clown intervention elicited more frequent facial expressions of genuine enjoyment (Duchenne smiles) than other smiles (Non-Duchenne smiles), and more Duchenne smiles went along with more perceived funniness, a higher level of global positive feelings and transcendence. This supports the notion that overall, hospital clown interventions are beneficial for patients. However, when considering individual differences in the receptiveness to humor, results confirmed that high trait cheerful patients showed more Duchenne smiles than low trait cheerful patients (with no difference in Non-Duchenne smiles), and reported a higher level of positive emotions than low trait cheerful individuals. In summary, although hospital clown interventions on average successfully raise the patients' level of positive emotions, not all patients in hospitals are equally susceptible to respond to humor with amusement, and thus do not equally benefit from a hospital clown intervention. Implications for research and practitioners are discussed.

Keywords: trait cheerfulness, Facial Action Coding System, Duchenne smile, hospital clown, amusement, transcendence

### INTRODUCTION

Whereas in some situations all people behave more or less in the same way, in other situations, individual differences co-determine people's actions and reactions. Research in the field of positive psychology has shown that in situations designed to promote happiness and well-being, the fit between a person's personality and the type of activity is in part responsible for its success (Schueller, 2012; Senf and Liau, 2013). The present study focuses on hospital clown interventions1 , which aim at bringing positive experiences to ailing patients. Hospital clown interventions have

#### Edited by:

René T. Proyer, Martin Luther University of Halle-Wittenberg, Germany and University of Zurich, Switzerland

#### Reviewed by:

William Larry Ventis, College of William & Mary, United States Alberto Dionigi, Federazione Nazionale Clown Dottori (FNC), Italy

> \*Correspondence: Sarah Auerbach<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Personality and Social Psychology, a section of the journal Frontiers in Psychology

Received: 24 August 2017 Accepted: 27 October 2017 Published: 13 November 2017

#### Citation:

Auerbach S (2017) Are Clowns Good for Everyone? The Influence of Trait Cheerfulness on Emotional Reactions to a Hospital Clown Intervention. Front. Psychol. 8:1973. doi: 10.3389/fpsyg.2017.01973

1Also referred to as clown therapy, clown visit, medical clowning, or clown care.

been described to "represent a particular way of using humor in order to promote people's well-being" (Dionigi et al., 2012, p. 1). The idea goes back to Freud (1960), who described humor as a tool that allows the individual to face adversity. In a situation normally associated with negative emotions (such as a hospital stay), humor can help the individual to cope with the situation by providing an alternative perspective on the situation. Although the art of clowning does not solely consist of humor (e.g., Peacock, 2009), humor has frequently been characterized as the main component of hospital clowning (Dionigi et al., 2012), and thus hospital clown interventions have been defined as humorous interventions2 (Ruch and Hofmann, 2017).

Although to date, hospital clown interventions are widely used in hospitals, nursing homes and other care facilities, and research has shown some positive effects for patients (see Effects of Hospital Clown Interventions on Individuals), no study has investigated whether these humorous interventions are beneficial for all recipients, or whether some groups of individuals benefit more than others (only age or gender differences were tested so far; e.g., Fernandes and Arriaga, 2010; Vagnoli et al., 2010). Hence, no research is available on whether individual differences influence the effects of a hospital clown intervention on the emotional reactions of patients.

### Individual Differences in Emotional Reactions to Humor

Research on personality and humor demonstrates that people habitually differ in the way they cognitively evaluate humorous stimuli (Ruch and Hehl, 2007), use and communicate humor in everyday life (Craik et al., 1996; Fox et al., 2016), and emotionally respond to humor (Ruch, 2007; Platt et al., 2013; Ruch et al., 2015). The predominant emotional reaction to humor was labeled exhilaration3 (or amusement), which in classifications of emotions is defined as a facet of joy (Ruch, 1993). One personality trait in particular, trait cheerfulness, has been studied in a variety of humor experiments and settings as a stable disposition for cheerful mood states and the easiness with which amusement is induced. Trait cheerfulness is characterized by a prevalence of cheerful mood, a low threshold for smiling and laughter, a composed view of adverse life circumstances, a broad range of active elicitors of cheerfulness and smiling and laughter, and a generally cheerful interaction style (Ruch et al., 1996). Together with trait seriousness and trait bad mood, it forms the temperamental basis for the sense of humor (Ruch and Carrell, 1998). Trait cheerfulness can be classified into the higher-order dimension of extraversion (Carretero-Dios et al., 2014), but has a higher specificity in predicting the intensity of amusement in response to humor than extraversion (Ruch, 1997). Ruch et al. (2011) postulated five relationships between trait cheerfulness and a cheerful state: high trait cheerful individuals have a lower threshold, a higher intensity, a longer duration, a higher robustness of cheerful mood (even when facing adversity), and a faster mood recovery (after a mood alteration to the negative) than low trait cheerful individuals. These postulates were tested in various experiments and contexts using subjective as well as objective methods, such as the observation of facial signs, to infer on the emotional state (for an overview see Ruch and Hofmann, 2012).

The universal facial expression of enjoyable emotions is smiling (Ekman, 2003). Research has repeatedly shown that there are different types of smiles, but especially one type (Duchenne smile) is a valid indicator of genuine enjoyment (Ekman et al., 1990; Sauter et al., 2013). It is characterized by the joint and timely corresponding contraction of the zygomatic major muscle (pulling the lip corners up) and the lateral part of the orbicularis oculi muscle (contracting the region around the eye producing crow's feet). Other types of smiles occur in situations without genuinely felt enjoyment (Non-Duchenne smiles). These types of smiles are present, for example, when individuals mask a negative emotional state (masking smile) or smile when nothing much is felt (phony smile) but individuals attempt to appear as if positive emotions are felt (Ekman and Friesen, 1982; Harris and Alvarado, 2005). The different types of smiles can be assessed with an objective and reliable technique for coding observable facial actions, the Facial Action Coding System (FACS; Ekman et al., 2002a), which enables coding the frequency, intensity, timing, duration, laterality and symmetry of 44 different action units. In a series of studies the FACS was used as an objective measure of amusement to demonstrate the influence of trait cheerfulness on the emotional reaction to humorous stimuli. For example, during an interaction with a clowning experimenter, individuals high in trait cheerfulness showed more frequent, more intense and longer lasting signs of facial amusement (Duchenne smiling and laughter4 ) than individuals low in trait cheerfulness (Ruch, 1997). When high trait cheerful individuals saw their own distorted photographs as a surprise, they showed more frequent Duchenne smiling and laughter than low trait cheerful individuals (Beermann and Ruch, 2011). When a virtual companion was present during a funny film, high trait cheerful individuals had higher frequencies of Duchenne laughter than low trait cheerful individuals (Hofmann et al., 2015).

### Effects of Hospital Clown Interventions on Individuals

To date, a few studies have evaluated hospital clown interventions and have consequently shown that hospital clown interventions can have a beneficial effect on patients (mostly children). For example, studies found a reduction of preoperative anxiety and worries in children undergoing medical procedures when interacting with a clown pair compared to a control group without a clown visit (e.g., Golan et al., 2009; Fernandes and Arriaga, 2010; Vagnoli et al., 2010). Regarding changes in positive states after interacting with hospital clowns, one

2Ruch and Hofmann (2017) argue that there are different types of humor interventions (such as self-administered individual humor interventions stemming from a positive psychology tradition, humor training programs to strengthen an individuals' level of the sense of humor, or hospital clown interventions).

3Exhilaration has been defined as the main emotional response to humor and denotes either the process of making cheerful or the temporary rise and fall of a cheerful state. To exhilarate in this sense means to make cheerful, or to amuse (Ruch, 1993).

4Duchenne laughter typically occurs at higher levels of reported amusement, while Duchenne smiling occurs at lower levels of reported amusement (Ruch, 1993).

study found an increase in self-rated positive affect in children (Fernandes and Arriaga, 2010), and another study found an increase in self- and parent reported well-being (Pinquart et al., 2011).

Only two studies have examined the positive emotions elicited by hospital clowns in individuals in more detail. Auerbach et al. (2014) developed and tested the 29 Clown Emotion List (CLEM-29), which is a collection of single adjectives and short phrases, but can be reduced to four factors: amusement, transcendence, unease and arousal. The factor of amusement merges a variety of positive humor-related states including a calmer cheerfulness and a more aroused hilarity. Transcendence was defined according to its non-religious connotation as the feeling of being uplifted and surpassing the ordinary. It includes positive feelings induced by clowns such as feeling privileged, appreciated, connected to the clown and elevated. The negative factor of unease consisted of negative feelings induced by clowns (e.g., threatened, fearful, confused). Ratings of the factor of arousal relate to different states of arousal, in which positive loadings (touched and speechless) refer to a calm state, that is, low arousal, whereas negative loadings (overexcited and schadenfreude) refer to a more heightened arousal. Studies that used the CLEM-29 showed that individuals watching videos of (Auerbach et al., 2014) and patients interacting with (Auerbach et al., 2016) a hospital clown reported a higher level of amusement compared to individuals who watched or experienced a nurse intervention. Furthermore, in both samples a combination of amusement and transcendence best predicted the total amount of positive affect after a hospital clown intervention. The authors concluded that a hospital clown intervention induces not only the typical humor reaction in recipients (amusement), but also adds a unique quality to the clown-patient interaction (transcendence).

In summary, previous research has provided evidence that hospital clown interventions are a suitable method to enhance the emotional state of individuals. The studies used subjective assessment tools, either self-reports or external reports of the key variables. So, the next step in a comprehensive evaluation of hospital clown interventions is to validate the subjectively assessed state of patients during the clown intervention by including observable signs of non-verbal behavior. Research (e.g., Ruch and Hofmann, 2012) has shown that humorous stimuli successfully generate facial amusement in various experiments if the subjects experience amusement (objective and subjective markers of amusement are typically moderately related; Ruch, 1995). Platt et al. (2013) showed that of the 16 enjoyable emotions proposed by Ekman (2003), amusement was one facet of joy that went along with both Duchenne smiles and Duchenne laughter. It is assumed that amusement will be the enjoyable emotion most elicited by hospital clown interventions, going along with Duchenne smiles and laughter.

Another still unnoted issue in evaluations of hospital clown interventions is the personality influence. Taking into account the trait cheerfulness model and its empirical evidence (Ruch and Hofmann, 2012), it can be assumed that high trait cheerful individuals benefit more from the intervention (i.e., more positive emotions) than low trait cheerful individuals.

### Aims and Hypotheses

The present study aims to contribute to a better understanding of hospital clown interventions in three ways: the investigation of patient's facial signs of enjoyment during an interaction with a hospital clown, its relationship to their subjective states, and the replication of the theory of trait cheerfulness as predictor of the emotional reaction of patients to humorous stimuli. The first hypothesis is that the hospital clown intervention on average elicits Duchenne smiles more often than Non-Duchenne smiles. The second hypothesis is that higher frequencies of Duchenne smiles are associated with higher levels of a positive experience, and lower levels of a negative one, whereas higher frequencies of Non-Duchenne smiles are associated with lower levels of positive experiences, and higher levels of negative ones. The third hypothesis is that high trait cheerful individuals show more Duchenne smiles and less Non-Duchenne smiles, and simultaneously report higher levels of positive emotions than low trait cheerful individuals.

### MATERIALS AND METHODS

### Sample

The sample consisted of N = 42 adult German speaking patients from a physical rehabilitation center (81% male), and was a convenient sample. Patients suffered from paraplegia, amputations, or other multiple injuries. The age of patients ranged from 19 to 75 years (M = 45.36, SD = 16.56). Inclusion criteria were age 18 or older, voluntary participation, not bedridden, and being cognitively and physically able to participate in the study. Patients were filmed during the study, and videos of a subsample of 26 patients could be used for coding facial actions.

#### Instruments

The standard trait version of the State-Trait-Cheerfulness Inventory (STCI-T < 60 >; Ruch et al., 1996) consists of 60 items to reliably and validly assess trait cheerfulness, trait seriousness and trait bad mood. To compose the trait cheerfulness scale in the current study, eight items were selected representing the facets of a low threshold for smiling and laughter and a generally cheerful interaction style (hilarity5 ; e.g., "I am a merry person"). The answer format is a four-point Likert-scale ranging from 1 (strongly disagree) to 4 (strongly agree) and Cronbachs alpha was 0.87.

The 29 Clown Emotion List (CLEM-29; Auerbach et al., 2014) is a list of 29 adjectives and short phrases assessing emotional states in the context of clowning. Participants rate their current state on a 7-point Likert scale ranging from 1 (=not at all) to 7 (=very strongly). As the sample size in the present study is too small to test the hypotheses with all single ratings, factor scores were used instead (transcendence, uneasiness, amusement, and arousal; the procedure is described in detail in Auerbach

5The present study addresses emotional reactions to clowns, which are a trigger of hilarity. Hence, only items representing facets of hilarity were selected to compose trait cheerfulness.

et al., 2016), which are sensitive enough to capture changes in clown-induced emotional states (Auerbach et al., 2014).

The Hospital Study Evaluation Form (HSEF; Auerbach et al., 2016) contains 22 single ratings, of which seven ratings concern the stay in the care facility (HSEF-General; e.g., quality of meals, care) and the evaluation of the hospital clown intervention (HSEF-Current; e.g., global positive and negative feelings during the situation). The answer format is a 7-point Likert scale. A second set of 15 single ratings (HSEF-Preferences), which are related to patients' general preferences for clowns, was given to patients at the end of the study (e.g., general liking of clowns; 5-point Likert scale).

### Procedure

Prior to the study, the local ethics committee approved the study. Consent forms were handed out before and after the experiment. The core of the current study was a surprise visit from a hospital clown pair. The study took place in a separate room in the rehabilitation center, and the procedure was highly standardized. Patients were recruited with the cover story that they were going to participate in an evaluation of patient satisfaction in hospitals. They were also told that a staff member would conduct a routine assessment, which they were to evaluate afterward. Two patients participated in each trial. Patients first filled out the HSEF-General, followed by a baseline assessment of emotional states (CLEM-29, HSEF-Current). Afterward, the clown intervention of a predetermined length took place (Min = 4.00, Max = 8.85, M = 6.65, SD = 1.17). It consisted of a semi-standardized performance of a hospital clown pair (one male clown with 17 years of experience, and one female clown with 16 years of experience), aiming at the induction of a positive emotional state in the patients. The same clowns performed in all trials, and used the same roles, clothes and make-up. They worked according to a script and did the same performance (same punchlines) in every trial. They were instructed to limit the length of the interaction to about 5–8 min. Both wore a red nose. The male clown carried a ukulele, wore a Doctor-like jacket. The female clown wore a yellow dirndl dress with yellow socks, a pink blouse.  The clown pair behaved like Auguste and Whiteface: the female clown was more dominant, slightly aggressive, bossy and pompous, while the male clown was the foolish, clumsy and more sensitive partner. After the clowns left the room, patients filled out the state measures (CLEM-29, HSEF-Current). Patients subsequently were debriefed about the real aim of the study (to investigate emotional reactions to hospital clowns) and asked not to disclose the use of clowns to other patients until the study was completed. For the last step of the study, they filled out the trait measures (STCI-T < 60 >, HSEF-Preferences).

Full color, digital format films with a close-up view of the patients' face were recorded. To be able to code the same clownpatient interactions for all subjects, ten standardized scenes occurring in all trials (about 10–20 s long) were extracted, each containing a studied punch line produced by the clowns followed by the reaction of patients. A certified FACS coder6 coded the resulting 260 observations (26 patients with 10 scenes each) with the help of the FACS (Ekman et al., 2002a). A Duchenne smile was defined as a symmetric and timely coincidental movement of the orbicularis oculi muscle around the eye (AU6) and zygomatic major muscle at the corners of the mouth (AU12). It could be accompanied by a tightening of the eyelids (AU7) and mouth opening (AU25, AU26, AU27), but no other action unit7 (Ekman and Friesen, 1982). The Non-Duchenne smile was defined as AU12 alone, or AU12 plus further action units that are associated with negative feelings (Ekman et al., 2002b). Laughter vocalizations were coded using one of four codes: "single unvoiced (ch)," "single voiced (ha)," "multiple unvoiced (ch ch ch)," or "multiple voiced (ha, ha, ha)."

## RESULTS

Three scores were built for use in the analyses. As they were sum scores over ten different standardized scenes during the interaction between the clowns and a patient, Cronbach's alpha was calculated for each score as a measure of the homogeneity of behaviors during the ten scenes. A frequency score for enjoyment smiles was built by summing up all Duchenne smiles in ten scenes, which showed high internal consistency (α = 0.80). A frequency score for Non-Duchenne smiles was built by summing up all Non-Duchenne smiles in the same ten scenes (α = 0.58). The Non-Duchenne smile category was more heterogeneous than the Duchenne smile one, as it comprised different types of Non-Duchenne smiles. A laughter score was built by summing up all four types of laughter vocalizations in ten standardized scenes (α = 0.75). All variables used in the analyses were normally distributed.

### Frequency of Different Types of Smiles

Patients on average smiled 8.92 times (SD = 3.76) during the 10 scenes. The percentage of Duchenne smiles among all smiles was 76.29%. The minimum was zero Duchenne smiles; the maximum was 16 (M = 6.81, SD = 3.74). The minimum of Non-Duchenne smiles was zero; the maximum was eight (M = 2.12, SD = 2.01). Patients on average laughed 3.58 times during the ten scenes (SD = 4.14) with a maximum of 15 laughter vocalizations. Thirty percent of patients did not produce any laughter vocalizations during the selected scenes.

### Relationship between Subjective and Objective Assessment

Negative affect after the clown visit was very low (M = 1.73, SD = 1.32), and positive affect was high (M = 5.12, SD = 1.5;

6The coder proved high reliability (agreement index = 0.78) scoring video material from real interactions in the FACS final test.

7 In few cases, high intensity combinations of AU12 and AU6 (intensity scores of D-E on a scale from A – E) during apex were accompanied by nose wrinkling (AU9) and/or eyebrow-lowering frowning (AU4). Following Hofmann (2014), these smiles were classified as high intensity Duchenne smiles. In the offset of the AU12, few patients pulled down their lip corners (AU15) or slightly pressed their lips together (AU24). There was no time overlap with the apexes of the AU12 and thus they were seen as regulatory mechanism (Ekman et al., 2002b).

scale from 1 to 7). Patients enjoyed participating in the study to a high extent (M = 4.24, SD = 0.77; scale from 1 to 5), and 81.5% stated that they felt better after the clown visit. The frequency of Duchenne smiles was positively correlated with funniness of the clown visit (r = 0.57, p < 0.01), global positive feelings (r = 0.46, p < 0.01), transcendence (r = 0.40, p < 0.05) and the joy of participating in the study (r = 0.43, p < 0.05), and negatively correlated with global negative feelings after the clown visit (r = −0.38, p < 0.05). The frequency of Non-Duchenne smiles was negatively correlated with the joy of participating in the study (r = −0.62, p < 0.01), transcendence (r = −0.59, p < 0.01), feeling better after the clown visit (r = −0.33), and positively correlated to unease (r = 0.34, both marginally not significant, p = 0.06). Laughter vocalizations were positively correlated with Duchenne smiles (r = 0.37, p < 0.05), transcendence (r = 0.46, p < 0.05), amusement (r = 0.44, p < 0.05), funniness of the clown visit (r = 0.46, p < 0.01), and feeling better after the clown visit (r = 0.41, p < 0.05).

### The Influence of Trait Cheerfulness

Next, it was tested whether high trait cheerful individuals had higher levels of positive emotions during the clown intervention than low trait cheerful individuals. To build two groups of equal sizes, ten patients with the lowest scores were allocated to group 1 (low trait cheerful), and ten patients with the highest scores to group 2 (high trait cheerful). A 2 × 2 repeated measures ANOVA with trait cheerfulness (high vs. low) and type of smile (Duchenne smile vs. Non-Duchenne smile) was computed for the frequency of smiling. Results are displayed in **Figure 1**.

Patients showed more Duchenne smiles than Non-Duchenne smiles, F(1,18) = 31.58, p < 0.001, η 2 p = 0.64, and high trait cheerful individuals smiled more frequently than low trait cheerful individuals, F(1,18) = 6.90, p < 0.05, η 2 p = 0.28. The interaction just failed to be significant, F(1,18) = 2.84, p = 0.11. However, there was a numerical trend toward higher levels of Duchenne smiles in the high trait cheerful group (M = 8.60, SD = 2.32) than in the low trait cheerful group (M = 5.30, SD = 3.13). An independent samples t-test confirmed that the two groups significantly differed in their frequency of Duchenne smiles, t(18) = −2.68, p < 0.05. No difference was found for Non-Duchenne smiles, t(18) = −0.30, p = 0.77.

Individuals high in trait cheerfulness reported higher positive feelings, t(31) = −2.35, p < 0.05, higher funniness ratings of the clowns, t(31) = −2.82, p < 0.01, higher levels of transcendence (marginally not significant), t(28) = −1.75, p = 0.09, and a lower level of unease, t(28) = 3.09, p < 0.01, than individuals low in trait cheerfulness. The two groups did not differ in their general preference for clown performances, t(31) = −1.54, p = 0.14, and laughter, t(18) = −0.70, p = 0.49.

### DISCUSSION

Humor interventions have been used frequently in research to increase happiness and lower depression in various settings and samples, including hospital clown interventions (for an

overview see Ruch and Hofmann, 2017). One consistent finding stemming from humor research is that individuals habitually differ in their readiness to react with amusement to humorous stimuli (Ruch and Hofmann, 2012). However, this has never been tested in patients receiving a hospital clown visit. Hence, the present study was the first to investigate individual differences in the emotional state of patients in response to a hospital clown intervention, and to use the FACS as a comprehensive, reliable technique for the objective assessment of the patient's emotions. This made it possible to distinguish between Duchenne smiles (genuine expressions of enjoyment) and other smiles in patients during clown-patient interactions.

First, the results confirmed that both types of smiles can occur during a humorous intervention (Harris and Alvarado, 2005), but eight out of ten smiles were Duchenne smiles, which is associated (and was positively correlated) with a positive emotional state (Ekman, 2003). In the present study, the facial expression of enjoyment was not only highly related to funniness ratings of the hospital clown performance indicating amusement (which replicated findings from humor research; Ruch, 1995, 1997), but also positively related to the felt level of transcendence in patients (extending humor research). Hence, the present study complements the work of other researchers and practitioners who stress that hospital clown interventions are not eliciting amusement, but contribute to the elicitation of other positive experiences. Patch Adams, one of the pioneers of hospital clowning, described the work of hospital clowns as a combination of humor and love (Adams, 2002). Kontos et al. (2017) found that clowns working with elderly care residents apply a mixture of humor and empathy. Linge (2012) interviewed children after a hospital clown intervention and concluded that a close connection between the clown and the recipients (magical attachment) is a core component of a (successful) clownpatient interaction. Hospital clown interventions apparently elicit feelings that go beyond the typical humor response, such as feelings of connection, liberation, appreciation or playfulness. In this sense, the present research validates studies

using self-report measures (Auerbach et al., 2014, 2016), and strengthens the widespread assumption of practitioners and clown organizations (see Dionigi et al., 2012) that on average hospital clown interventions successfully create positive experiences and emotions for patients in need of care.

Second, another important, yet unanswered question was whether a hospital clown intervention is successful in eliciting a positive emotional state in all patients, or whether some groups of patients benefit more from the intervention than other groups. Derived from the theory of the temperamental basis of the sense of humor (Ruch et al., 1996), a trait could be identified that has been shown to be an important predictor for the emotional reaction to humorous stimuli repeatedly – trait cheerfulness (e.g., Ruch, 1997; Hofmann et al., 2015). The present study gives further validation to trait cheerfulness as predictor of positive emotions by demonstrating that a hospital clown intervention does not lead to high levels of amusement in all cases. Hence, not all patients benefit equally from the clown intervention. Clowns working in the field should always bear in mind that some patients do not want to be involved in a humorous and playful interaction, look for signs of refusal, and act accordingly. At the same time, the results can also be a justification for practitioners on a 'bad day' (e.g., in case their performance does not lead to the intended success, i.e., the patients do not smile or laugh). In fact, in many clown organizations hospital clown training includes interpersonal skills, the sensitization of the clowns to the current state of patients, and the appropriate handling of uncertainty and refusal (Dionigi et al., 2012), which seems even more important given the results presented here.

The present study has some limitations. First, only one clown pair was used. A next step could be to study possible interactions between high and low trait cheerful individuals and different kinds of clowns with different techniques (clownperson fit). The clown pair used in this study had a rather playful, interactive, hilarity-based style, while other clowns work in a more sensitive, insightful and composed way (Hofmann et al., 2014). Also, cultural differences in humor and clowning have not been studied here. Second, the sample was rather small and very heterogeneous with a wide age range and few females, which was due to the convenience sampling method. Also, only one physical rehabilitation center was included. Future research should collect larger samples more representative of hospitalized adult patients in different settings. Third, the situation was somewhat artificial – as patients were overtly filmed during the intervention – and the intervention was highly standardized, and other than in real life the subjects were committed to take part in the study. Results presented here might underestimate the true relationships between the behavior, subjective experience and personality of individuals. A next study should also aim to differentiate the different types of Non-Duchenne smiles and have a look at their correlations with different emotional states, while subjects are unobtrusively filmed. A recent study suggests that in spontaneous and unobserved situations, the emotional state of Schadenfreude goes along with the Duchenne smile, whereas in social situations (such as the openly filmed hospital clown intervention), subjects try to mask or suppress the expression of Schadenfreude (Hofmann and Ruch, 2015). It would be interesting to study the different types of smiles during a natural unobserved clown-patient interaction and during a social, observed situation, such as the one used in the present study. Fourth, although the main aim was to standardize the interactions between the clown pair and the patients, it is safe to say that not all trials were executed in exact the same manner. The clowns were instructed to perform as standardized as possible, but also as realistic as possible, meaning that in case the subject tried to interrupt the clown pair, they should not ignore him or her but react in a natural way before continuing with the scripted performance. After all, it was a real interaction between the clowns and the patients in a natural setting, and therefore not perfectly standardized. However, for the analyses only those scenes were chosen that occurred in every interaction in the same manner (same punchline), and thus the biasing effect on the results is expected to be rather small.

Despite the limitations, the results promote the use of hospital clown interventions for the enhancement of a positive emotional state in patients in need of care, but also point out the relevance of accounting for individual differences in recipients of the interventions. It is much to be hoped that this will stimulate future studies in that other researchers also combine objective and subjective assessment methods to get a clearer picture of the variety and uniqueness of emotional responses of patients during a hospital clown intervention. Furthermore, this knowledge can be used by organizations that train clowns to raise the awareness of signs that help explaining the success and failure of hospital clown interventions in their work in hospitals to prevent unwanted side effects such as the induction of negative emotions and rejection. Research demonstrates that emotional expressivity may be a reliable sign of cooperative tendency in humans (Schug et al., 2010), indicating that clowns should watch out for facial signs of emotions in patients to find out whether they want to cooperate (and thus join the game). These days, many clown organizations already include a sensitive, careful and responsible approach in the interaction with patients in their curriculum, emphasizing to always pay attention to the emotional impact of their visit to patients (Dionigi et al., 2012). Clown organizations could go one step further and specifically include the recognition and interpretation of facial expressions of individuals into their training programs.

### ETHICS STATEMENT

This study was carried out in accordance with the recommendations of "Swiss Psychological Association"; and the Ethics Committee of the Department of Psychology, University of Zurich, with written informed consent from all subjects. All subjects gave written informed consent in accordance with the Declaration of Helsinki.

### AUTHOR CONTRIBUTIONS

fpsyg-08-01973 November 9, 2017 Time: 16:43 # 7

SA conceived and designed the work and was also involved in data collection, data analysis and interpretation, drafting the article, critical revision of the article, and final approval of the published version.

### FUNDING

This publication benefited from the support of the Red Noses Clowndoctors International Organization. The author is grateful

### REFERENCES

to the Red Noses Clowndoctors International for their financial assistance.

### ACKNOWLEDGMENTS

The author would like to thank Prof. Dr. Willibald Ruch, Dr. Tracey Platt, Dr. Jennifer Hofmann for helpful comments on a prior version of the manuscript. She would also like to thank the clowns of the Red Noses Clowndoctors International Organization for participating in the study, and Annette Fehling for assisting in the data collection.

Vagnoli, L., Caprilli, S., and Messeri, A. (2010). Parental presence, clowns or sedative premedication to treat preoperative anxiety in children: what could be the most promising option? Pediatr. Anesth. 20, 937–943. doi: 10.1111/j.1460- 9592.2010.03403.x

**Conflict of Interest Statement:** The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The author and handling Editor declared their shared affiliation, and the handling Editor states that the process nevertheless met the standards of a fair and objective review.

Copyright © 2017 Auerbach. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.


*2.3. Astaxanthin Impaired the Phenotypic Maturation of LPS-Induced DCs*

Maturation is the key step in the DC-mediated regulation of immune responses. To investigate whether astaxanthin modulated the DC maturation, the expression levels of MHCII and costimulatory molecules in DCs were analyzed by FCM. With LPS treatment alone, the expressions of MHCII, CD40, CD80, and CD86 were markedly upregulated, whereas they were down-regulated remarkably with the treatment of astaxanthin (Figure 4). These data suggested that astaxanthin diminished LPS-activated DC phenotypic maturation and compromised the immunostimulation of the activated DCs.

**Figure 4.** Astaxanthin suppressed the expression of phenotypic markers by LPS-stimulated DCs in vitro. After stimulation for 24 h with astaxanthin or plus 100 ng/mL LPS, the expressions of phenotypic markers on DCs, including MHCII (**A**,**E**), CD40 (**B**,**F**), CD80 (**C**,**G**), and CD86 (**D**,**H**), were analyzed by FCM. Data shown are the means ± s.d. of three replicates and are representative of three independent experiments. Statistical significance is assessed by one-way ANOVA analysis to compare the results between different groups. \*\* *p* < 0.01.

#### *2.4. Astaxanthin Increased the Endocytosis Capability of LPS-Induced DCs*

In response to inflammatory stimuli, DCs trigger the process of maturation; downregulation of endocytosis is a hallmark of maturation [34]. To investigate whether astaxanthin modulated the endocytosis of DCs, the fluorescent marker dextran was used. As shown in Figure 5A,B, LPS alone significantly decreased the endocytosis capability of DCs compared to the untreated control, while astaxanthin enhanced the uptake of dextran in LPS-induced DCs. Moreover, confocal laser scanning microscopy (CLSM) images displayed the amount of Alexa Fluor 647-dextran existing in the body of LPS-induced DCs and was enhanced after the treatment of astaxanthin (Figure 5C). These results suggested that astaxanthin significantly increased the endocytosis capability of LPS-induced DCs.

**Figure 5.** Astaxanthin enhanced the endocytosis ability of DCs after LPS treatment in vitro. After stimulation for 24 h with astaxanthin or plus 100 ng/mL LPS, the treated DCs were incubated with 1 mg/mL FITC-Dextran (**A**,**B**) or Alexa Fluor 647-Dextran (**C**) at 37 ◦C for 30 min. After incubation, the cells were washed three times with cold PBS and analyzed by FCM (**A**) or were observed by using confocal laser scanning microscopy (CLSM). Parallel experiments were performed at 4 ◦C to determine the nonspecific binding. The data shown are the means ± s.d. of three replicates and are representative of three independent experiments. (**C**) Dextran (Alexa Fluor 647; red) and Nuclei (4 ,6-diamidino-2-phenylindole (DAPI); blue). The results are from one representative experiment of three performed. Bars: 10 μm. Statistical significance is assessed by one-way ANOVA analysis to compare the results between different groups. \*\* *p* < 0.01.


*3.4. Extraction and Isolation*

The fermented rice substrate was mechanically fragmented after incubation, and then extracted with petroleum ether (PE) to remove the low-polarity chemical constituents. The remaining culture was extracted thoroughly with EtOAc, which was filtered and evaporated under reduced pressure to give EtOAc extract (75.5 g).

The EtOAc extract was fractionated by Si gel VLC (vacuum liquid chromatography), using solvents of increasing polarity (PE-EtOAc, 20:1 to 1:1, and then CH2Cl2-MeOH, 20:1 to 1:1) to yield nine fractions (Frs. 1−9). Fr. 5 (6.6 g) was further separated by CC (Column Chromatography) over Lobar LiChroprep RP-18 with a MeOH-H2O gradient (from 1:9 to 10:0) to yield 10 subfractions (Frs. 5.1−5.10). Fr. 5.4 (453.8 mg) was subjected to CC on Si gel eluting with a CH2Cl2-MeOH gradient (from 500:1 to 200:1) to yield compounds **6** (187.6 mg) and **7** (15.5 mg). Fr. 6 (29.2 g) was repeatedly subjected to Si gel VLC and then fractionated by solvents of increasing polarity from CH2Cl2 to acetone to yield

four subfractions (Frs. 6.1−6.4) based on HPLC and TLC analysis. Purification of Fr. 6.1 (6.2 g) by CC over Lobar LiChroprep RP-18 with a MeOH-H2O gradient (from 1:9 to 10:0) yielded 10 subfractions (Frs. 6.1.1−6.1.10). Fr. 6.1.1 (14.3 mg) was recrystallized from mixed solvents (MeOH-H2O, 10:1) to give **3** (6.7 mg). Fr. 6.1.2 (53.7 mg) was purified by prep-TLC and CC on Sephadex LH-20 (MeOH) to obtain **10** (34.1 mg). Fr. 6.1.3 (44.8 mg) was also recrystallized from MeOH to give **9** (21.9 mg). Fr. 6.1.4 (79.2 mg) was applied to semi-preparative HPLC (Elite ODS-BP column, 10 μm; 20 × 250 mm; 70% MeOH-H2O, 16 mL/min) to afford **4** (18.3 mg, *t*R 29.6 min). Fr. 6.1. 5 (207.3 mg) was subjected to repeated CC on silica gel (CH2Cl2-MeOH, 140:1) and purified by prep-TLC and CC on Sephadex LH-20 (MeOH) to give **5** (9.4 mg). Fr. 6.2 (6.0 g) was split by CC over Lobar LiChroprep RP-18, silica gel, and Sephadex LH-20 to yield **2** (12.5 mg). Fr. 6.3 (6.5 g) was subjected to CC over Lobar LiChroprep RP-18, eluted with a MeOH-H2O gradient (from 1:9 to 10:0) to yield 10 subfractions (Frs. 6.3.1−6.3.10). Fr. 6.3.1 (32.1 mg) was recrystallized from mixed solvents (MeOH-H2O, 10:1) to afford **8** (13.7 mg).


**3. Progress in improving nutritional quality**

allow further manipulation of the nutrient loading pathway without affecting other traits of importance [31, 32]. Thereof, the selected omics technological platforms would bring about data outputs that would allow the establishment of a good balance in the expression of selected traits of interest in desired grain compartments [33]. The integration of these technologies would allow researchers to identify novel genes or pathways that could be activated to improve the bioavailability of desired nutritional components in wheat. This chapter aims to highlight the progress and challenges encountered in attempts to improve nutritional quality in wheat in order to recommend strategies that could be deployed to improve nutritional quality in a more sustainable and efficient way. The most important research question that needs to be addressed is, what is the source or origin of the total grain nutrient content of minerals or phenolic acids found in different grain compartments? Thus, there is still a need to conduct a quantitative assessment of the total mineral nutrient use efficiency and the type of mineral used for plant

Wheat, grown in many parts of the world, is a major contributor to food security in that it is a staple food in other countries [1]. It has three main grain compartments such as the bran, endosperm and the germ. The wheat grain as a whole houses a series of nutritional health beneficial components ranging from macronutrients, micronutrients, vitamins, phenolic compounds and other components at different levels across various grain compartments [2]. The wheat grain is also a major contributor to the daily dietary intake required by individuals due to its regular consumption in various forms. Thus, regular consumption of essential nutrients at adequate levels could largely contribute to the reduction of nutrient deficiency-related ailments such as anaemia, growth and development problems, cardiovascular diseases, cancer,

Intriguingly, the endosperm region is the most edible part of the grain reported to contain less contents of Fe and Zn than the outer layers that are removed upon milling [18, 34]. Several efforts to establish the biofortification of wheat have been undertaken and some major challenges have been experienced. Little or no progress has been made to characterize the key biological process involved in the accumulation and bioavailability enhancement of Fe, Zn,

Wheat has a complex genome and the complete genome sequence is not available yet. This makes it challenging to identify and understand the function of many genes in wheat, thereby making it difficult to characterize and manipulate complex traits of interest for the development of improved varieties. Further characterization of some traits is still needed for a continued contribution to better understand various gene networks/pathways and their role within the wheat genome to allow rapid development of improved cultivars with desirable traits of interest for a continued contribution to food and nutrition security. There are various wheat genetic resources ranging from landraces to wild relatives that may carry various genes of interest due to their genetic diversity [1, 35, 36]. Genetic resources have been utilized for crop improvement efforts in cases where information regarding a complex trait is not readily known, the informa-

tion may then be inferred from closely related species with known biology [1].

metabolism and seed production.

348 Wheat Improvement, Management and Utilization

diabetes, neurological disorders, etc. [7].

vitamins and phenolic acids in this grain compartment [14].

**2. Wheat**

The improvement of nutritional quality entails a series of processes to ensure that the nutrients are bioavailable upon consumption. The major process requires a genotypic and phenotypic characterization of key biological processes or pathways that are involved in the assimilation, accumulation, biosynthesis, translocation and remobilization of desired nutritional quality components such as Fe, Zn, vitamins and phenolic acids in the wheat grain [12, 15, 37–39]. The ultimate process involves the application of biofortification, which is the most sustainable approach that can reach the nutritional requirements of the global community in a cost-effective manner. However, the application of biofortification requires rudimentary information regarding the crop's genetic and phenotypic profile across different environments. Substantial progress has been made in attempts to improve nutritional quality in wheat. This includes the deployment of several strategies that involve the application of conventional, technological and transgenic approaches [14, 40].

Conventional-based approaches involve the use of basic genetic and agronomic practices, such as agronomic biofortification, soil+foliar application and genetic biofortification, which involves germplasm screening to reveal the genetic variation for grain Fe and Zn levels across different wheat genotypes grown in different environments [21]. Progress has been made to establish genetic variation of Fe and Zn across various wheat species. Along the process, an important quantitative trait locus (QTL) *Gpc-B1* from wild emmer wheat (*Triticum turgidum* ssp. *dicoccoides*) was discovered and mapped on chromosome arm 6BS [41]. The gene of this locus was then cloned and effectively improved Zn, Fe and protein concentrations by 12%, 18% and 38%, respectively [19]. The *Xuhw89* marker is linked to the *Gpc-B1* locus with a 0.1 cM genetic distance and can be used to identify and select lines with improved levels of selected micronutrients in the wheat grain [42]. In addition, several efforts have also been made to establish the genetic variation in the levels of phenolic compounds in some wheat species.

Technological-based approaches involve the application of advanced high-throughput analytical technologies such as ribonucleic acid sequencing (RNAseq), ribonucleic acid interference (RNAi), genomics, transcriptomics and metabolomics to discover and characterize candidate genes that could be used to improve nutritional quality. This may also include genome editing-based approaches such as the CRISPR Cas9 approach, which has recently been used in wheat [20]. Transgenic-based approaches mainly involve the application of genetic modification to improve nutrient accumulation in the wheat grain. Some minimal progress has been made with the application of transgenic approaches in attempts to improve nutritional quality [43, 44].

Several applications have been deployed to improve nutritional quality in wheat; some applications were successful but not sustainable and others were not successful [12, 13, 28]. Technological applications have also been deployed for wheat improvement. This includes success in increasing the bioavailability of Fe and Zn and decreasing the antinutrients such as phytic acid and polyphenols, which inhibit Fe absorption thereby reducing Fe bioavailability. However, a series of strategies to improve the bioavailability of micronutrients and phenolic acids have been deployed, this includes agronomic biofortification and the use of nutritional enhancers [27, 28, 38]. Micronutrients and phenolic acids have also been reported to be present at high concentrations in the outer layers of the seed and in the wheat germ region than in the endosperm region [18, 34].

Nonetheless, there are challenges with the biofortification of wheat with other nutritional components. This is mainly due to an incomplete understanding of pathways involved in the translocation of desirable nutritional components into desired wheat grain compartments such as the endosperm. In addition, the bioavailability of micronutrients such as Fe is reduced due to its interaction with other anti-nutritional components such as phytic acid or the food matrix, which constitutes other nutritional or anti-nutritional wheat grain components [43, 45, 46]. Moreover, the wheat endosperm region was also reported to lack transporters that are essential for the translocation Fe into the endosperm region [14, 47]. little or no research has been conducted to manipulate the transporter proteins to translocate more Fe into the wheat grain. Little or no studies were conducted on the translocation of phenolic acids into the wheat endosperm, and there is less information regarding the translocation or transporters involved in the translocation of phenolic compound and vitamins into the endosperm region.

A number of attempts to address the above-mentioned challenges were undertaken through the application of various conventional, technological and transgenic approaches. Much progress has been made in attempts to understand key processes involved in the assimilation, translocation and biosynthesis of micronutrients into the wheat grain [12–15, 48]. However, there is still a great need to utilize selected omics technologies to further improve our understanding on processes involved in optimising the accumulation of essential nutrients in the wheat grain.

#### **3.1. Establishing genetic variation**

The establishment of genetic variation entails screening various wheat genotypes grown across different environments for their levels of total Fe, Zn, vitamins and phenolic acids found in the wheat grain with the aid of analytical instruments [49–51]. Most or all studies on genetic variation in grain Fe and Zn concentration reported on the total grain Fe and Zn concentration obtained in wholemeal flour. Little or no reports are available on establishing the genetic variation in grain Fe and Zn concentration in white flour. However, the Agricultural Research Council-Small Grain Institute of South Africa has reported some preliminary data on the levels of Fe and Zn found in white flour among some modern commercial wheat genotypes, which showed some degree of genetic variation at a local conference in 2016 (unpublished data).

Velu et al. [28] reported substantial progress made on screening more than 7800 wheat genotypes for their variation in Zn concentration in bread wheat, durum wheat, wheat landraces and their wild relatives from several studies conducted since 1983 until 2012. The studies from the paper revealed some genotypes that had the highest grain Zn concentration reaching as far as 142 mg/kg, whereas other wheat genotypes especially the improved adapted wheat genotypes showed little variation in grain Zn [28]. Amiri et al. [52] also reported the genetic variation for grain's protein, Fe and Zn concentration among 80 irrigated bread wheat genotypes, which showed some level of genetic variation. Gorafi et al. [53] also reported the assessment of genetic variation in grain Fe and Zn concentrations in more than 40 synthetic hexaploid wheat lines and conducted further development of the wheat lines for use as genetic resources. Thus, various wheat genotypes showed a significant genetic variation in wheat grain Fe and Zn content. Consequently, wheat genotypes that contain the highest levels of Fe and Zn could be selected as donors to improve the levels of Fe and Zn in recurrent parents who have lower levels of Fe and Zn. However, it is imperative to ensure that important traits, such as grain yield, protein content, disease resistance and other agronomic traits, are not compromised upon the development of varieties with improved nutritional quality.

Genetic variation was reported in phenolic acid content of various wheat genotypes [54–56]. Thus, some progress has been made to selectively breed for genotypes with the highest phenolic acid content. However, more studies are needed to further confirm the genetic variation that exists in phenolic acids among different wheat genotypes through germplasm screening of other wheat genotypes including wild relatives and landraces.

Little or no research has been reported on the establishment of genetic variation on the concentration of vitamins, manganese, magnesium, copper, potassium, as well as concentrations of other anti-nutritional components found in the wheat grain. Nonetheless, [49, 50, 57] provided a report on the levels of tocol (vitamin E) content found in various wheat genotypes. However, more studies are needed in this field.

The establishment of genetic variation in minerals has led to the improvement of several wheat germplasms. The selected genotypes were used to improve the levels of Zn by more than twofold in other instances [28]. However, there are some drawbacks with conventional breeding, in that it may take several years to develop a new variety with improved nutritional quality. In addition, only the total grain Fe and Zn can be increased. Therefore, breeders have no control on improving the levels of selected nutrients into desired grain compartments.

### **3.2. Grain nutrient content**

ent at high concentrations in the outer layers of the seed and in the wheat germ region than in

Nonetheless, there are challenges with the biofortification of wheat with other nutritional components. This is mainly due to an incomplete understanding of pathways involved in the translocation of desirable nutritional components into desired wheat grain compartments such as the endosperm. In addition, the bioavailability of micronutrients such as Fe is reduced due to its interaction with other anti-nutritional components such as phytic acid or the food matrix, which constitutes other nutritional or anti-nutritional wheat grain components [43, 45, 46]. Moreover, the wheat endosperm region was also reported to lack transporters that are essential for the translocation Fe into the endosperm region [14, 47]. little or no research has been conducted to manipulate the transporter proteins to translocate more Fe into the wheat grain. Little or no studies were conducted on the translocation of phenolic acids into the wheat endosperm, and there is less information regarding the translocation or transporters involved in the translocation of phenolic compound and vitamins into the endosperm region. A number of attempts to address the above-mentioned challenges were undertaken through the application of various conventional, technological and transgenic approaches. Much progress has been made in attempts to understand key processes involved in the assimilation, translocation and biosynthesis of micronutrients into the wheat grain [12–15, 48]. However, there is still a great need to utilize selected omics technologies to further improve our understanding on processes involved in optimising the accumulation of essential nutrients in the

The establishment of genetic variation entails screening various wheat genotypes grown across different environments for their levels of total Fe, Zn, vitamins and phenolic acids found in the wheat grain with the aid of analytical instruments [49–51]. Most or all studies on genetic variation in grain Fe and Zn concentration reported on the total grain Fe and Zn concentration obtained in wholemeal flour. Little or no reports are available on establishing the genetic variation in grain Fe and Zn concentration in white flour. However, the Agricultural Research Council-Small Grain Institute of South Africa has reported some preliminary data on the levels of Fe and Zn found in white flour among some modern commercial wheat genotypes, which showed some degree of genetic variation at a local conference in 2016 (unpub-

Velu et al. [28] reported substantial progress made on screening more than 7800 wheat genotypes for their variation in Zn concentration in bread wheat, durum wheat, wheat landraces and their wild relatives from several studies conducted since 1983 until 2012. The studies from the paper revealed some genotypes that had the highest grain Zn concentration reaching as far as 142 mg/kg, whereas other wheat genotypes especially the improved adapted wheat genotypes showed little variation in grain Zn [28]. Amiri et al. [52] also reported the genetic variation for grain's protein, Fe and Zn concentration among 80 irrigated bread wheat genotypes, which showed some level of genetic variation. Gorafi et al. [53] also reported the assessment of genetic variation in grain Fe and Zn concentrations in more than 40 syn-

the endosperm region [18, 34].

350 Wheat Improvement, Management and Utilization

wheat grain.

lished data).

**3.1. Establishing genetic variation**

Wheat grain houses a number of nutritional components ranging from macronutrients, micronutrients, vitamins, amino acids, arabinoxylans and various other nutritional components [2]. These components vary in quantity due to the manner in which they are incorporated into different grain compartments upon seed formation. Thus, increasing the quantity of selected nutritional component might result in a decrease in other constituents [21, 43]. Hence, it would be ideal to optimize the production of desirable nutrients in a manner that could result in the reduction of non-targeted wheat grain components. However, this would be a major challenge in that some or most traits in certain organisms are quantitative and the expression of a selected trait could depend on the expression of more than one gene, thereby resulting in minimal expression or production of a desired nutritional component.

Starch, protein and cell wall polysaccharides (dietary fibre) are the major grain nutritional components that account for about 90% of the dry weight and minerals, vitamins, lipids, phenolic compounds and terpenoids are among the minor grain nutritional constituents found in wheat. A major component of the endosperm comprises about 80% of starch and about 10% of other constituents, including minerals and some phytochemicals, which are mostly concentrated in the wheat bran area [58].

The levels of minerals in several wheat varieties particularly Fe and Zn have been reported to be declined over more than five decades due to their dilution with starch [2]. Nonetheless, substantial progress has been made in improving the total grain nutrient content with micronutrients such as Fe and Zn. The second HarvestPlus Yield Trial has managed to improve the levels of 50 wheat lines through biofortification with a total grain Zn content, which was 75–150% more than the control lines used for the trial [28, 59]. Hidalgo and Brandolini [60] reported that the wheat bran region of some einkorn accessions and some bread wheat genotype had the highest levels of total tocols, including α–tocopherol and β-tocopherol, in a study that screened the distribution of tocols across different grain compartments.

Agronomic biofortification, a traditional biofortification approach, which involves direct micronutrient uptake from the soil that gets remobilised into the grain, has been applied in wheat to improve the levels of Fe and Zn. Much progress has been made in the application of this strategy for the biofortification of wheat with grain Zn. This was done through the application of Zn fertilizers using the soil and foliar application method, which can result in about threefold increase in the total grain Zn concentration [21]. Several studies that involved the use of radioactive Fe and Zn were carried out to evaluate ways to gain better understanding of the remobilisation of selected minerals [19, 32, 61]. The studies largely contributed to depicting the manner in which micronutrients are translocated into seeds from various tissues. Feil et al. [62] reported that environmental conditions, particularly soil composition, largely influence the total micronutrient concentration of wheat grain. Thus, agronomic biofortification can facilitate nutrient uptake and ultimately improve the total grain Zn content. However, this process is mainly dependent on the availability of minerals in the soil or through provision from the fertilizer, thereby making it an unsustainable approach to utilize in improving nutritional quality.

#### *3.2.1. Nutrient translocation into grain*

There are genes that contribute to the translocation of minerals, mainly Fe and Zn into the wheat grain. Nutrient uptake and translocation or remobilization are complex processes that are involved in seed nutrient loading to make up the total grain nutrient content [12, 15, 21]. The two major processes involved in nutrient uptake and translocation and/or remobilization are mainly dedicated for plant metabolism and seed production. In the case of plant metabolism, nutrients would be taken up, translocated or remobilized to specific tissues in response to growth and developmental requirements, including mineral deficiencies. Whereas in the case of seed production, the source of the total nutrient content found in the seed remains unknown because nutrient loading in the seed has been attributed to multiple processes including senescence and direct translocation with the aid of transporters [19, 32]. The process of moving micronutrients from the soil into the seeds is a complex process, which still requires further characterization. Waters and Sankaran [15] provided a review uncovering several processes involved in the improvement of seed mineral biofortification on various species, including wheat, and made a recommendation that the simultaneous enhancement mineral uptake from roots to shoots and ultimately remobilization into seeds would result in successful seed mineral biofortification.

Nutrient remobilization through senescence was reported to be more efficient in cases where the plant carries a Gpc-B1 locus derived from *T. dicoccoides* [21]. Wherein, Distelfeld et al. [42] showed that recombinant substitution lines (RSLs) carrying the *dicoccoides* Gpb-B1 allele had 12%, 18% and 38% more Zn, Fe and grain protein content (GPC), respectively, than (RSLs) carrying a Gpc-B1 locus acquired from durum wheat. Thus, there is a great need to distinguish whether the nutrients that are accumulated in the grain are excess nutrients that were committed for plant development in the leaves, which are translocated into the wheat grain upon senescence or whether they are accumulated and translocated into the wheat grain during different growth developmental stages. Consequently, there is a great need to trace the origin of nutrients found in different grain compartments.

#### *3.2.2. Transgenic approaches*

The levels of minerals in several wheat varieties particularly Fe and Zn have been reported to be declined over more than five decades due to their dilution with starch [2]. Nonetheless, substantial progress has been made in improving the total grain nutrient content with micronutrients such as Fe and Zn. The second HarvestPlus Yield Trial has managed to improve the levels of 50 wheat lines through biofortification with a total grain Zn content, which was 75–150% more than the control lines used for the trial [28, 59]. Hidalgo and Brandolini [60] reported that the wheat bran region of some einkorn accessions and some bread wheat genotype had the highest levels of total tocols, including α–tocopherol and β-tocopherol, in a study

Agronomic biofortification, a traditional biofortification approach, which involves direct micronutrient uptake from the soil that gets remobilised into the grain, has been applied in wheat to improve the levels of Fe and Zn. Much progress has been made in the application of this strategy for the biofortification of wheat with grain Zn. This was done through the application of Zn fertilizers using the soil and foliar application method, which can result in about threefold increase in the total grain Zn concentration [21]. Several studies that involved the use of radioactive Fe and Zn were carried out to evaluate ways to gain better understanding of the remobilisation of selected minerals [19, 32, 61]. The studies largely contributed to depicting the manner in which micronutrients are translocated into seeds from various tissues. Feil et al. [62] reported that environmental conditions, particularly soil composition, largely influence the total micronutrient concentration of wheat grain. Thus, agronomic biofortification can facilitate nutrient uptake and ultimately improve the total grain Zn content. However, this process is mainly dependent on the availability of minerals in the soil or through provision from the fertilizer, thereby making it an unsustainable approach to utilize in improving

There are genes that contribute to the translocation of minerals, mainly Fe and Zn into the wheat grain. Nutrient uptake and translocation or remobilization are complex processes that are involved in seed nutrient loading to make up the total grain nutrient content [12, 15, 21]. The two major processes involved in nutrient uptake and translocation and/or remobilization are mainly dedicated for plant metabolism and seed production. In the case of plant metabolism, nutrients would be taken up, translocated or remobilized to specific tissues in response to growth and developmental requirements, including mineral deficiencies. Whereas in the case of seed production, the source of the total nutrient content found in the seed remains unknown because nutrient loading in the seed has been attributed to multiple processes including senescence and direct translocation with the aid of transporters [19, 32]. The process of moving micronutrients from the soil into the seeds is a complex process, which still requires further characterization. Waters and Sankaran [15] provided a review uncovering several processes involved in the improvement of seed mineral biofortification on various species, including wheat, and made a recommendation that the simultaneous enhancement mineral uptake from roots to shoots and ultimately remobilization into seeds would result in

that screened the distribution of tocols across different grain compartments.

nutritional quality.

*3.2.1. Nutrient translocation into grain*

352 Wheat Improvement, Management and Utilization

successful seed mineral biofortification.

A transgenic approach that could enhance the Fe concentration in edible plant part is the overexpression of ferritin, an Fe-rich soybean (*Phaseolus vulgaris*) storage protein [63, 64], which completely degrades phytate in seeds. Ferritin is considered a more bioavailable storage form and is abundant in the endosperm amyloplasts, the widely consumed grain compartment [65]. Ferritin genes of soybean were introduced and used to produce transgenic rice lines, and the concentrations of Fe were doubled with the highest Fe level in the transgenic lines [63]. Recombinant soybean ferritin gene also increased seed Fe concentration in rice, under the control of an endosperm-specific promoter [66, 67].

However, ferritin overexpression possesses a disadvantage in transgenic crops as the accumulation of Fe might depend greatly on the soil composition, for example, transgenic tobacco (*Nicotiana tabacum*) continuously overexpresses ferritin under a 35S-GUS promoter [68] and Fe deficiency was widespread in the crop. Metals, such as cadmium, lead and nickel, which are toxic for human health, were found rich in ferritin-overexpressing tobacco plants, when grown in one of the tested soil [68]. Consequently, Fe accumulation within ferritin results in an iron deficiency in these transgenic tobacco plants [68]. Iron deficiency expresses ferrous Fe root transporters, which also uptake cadmium, thereby promoting cadmium accumulation in plants [69–74].

#### **3.3. Candidate genes for nutritional quality enhancement**

Nutrient biosynthesis and accumulation in the seed involves multiple complex processes. Phenolic acids are mainly synthesized from phenylalanine, a major precursor molecule for the phenlypropanoid biosynthetic pathway [39, 75, 76]. The biosynthesis of phenolic acids is mainly governed by several genes, which encode enzymes to carry out biochemical reactions involved in the production of selected phenolic acids. However, little or no information is known on the process that is involved in the loading of specific phenolic acids into different grain compartments. Micronutrient accumulation in the wheat grain is mainly dependent on the availability of soil mineral nutrients, which are taken up from the roots and then translocated to different plant compartments. In this process, a series of genes and active transport protein families are activated to facilitate in the nutrient translocation and remobilization process. The total quantity of micronutrients found in different grain compartments depend on environmental circumstances and the growth stage in which micronutrients are taken up, translocated or remobilized from different plant tissues. Thus, it would depend on the nutrient soil status and the stage at which the selected nutrients are taken up. Nonetheless, there is little or no research on the characterization of the origin and starting concentration of the nutritional component attributed to specific concentrations obtained in specific grain compartments.

#### *3.3.1. Genes involved in micronutrient accumulation*

Waters and Sankaran [15] reported genes implicated in the uptake of Fe mainly. No gene(s) that are involved in Fe uptake have been reported for wheat. Thus, there is still a need to characterize and identify genes involved in the uptake of Fe from soil to the seeds in wheat. Furthermore, [70, 77, 78] provided a comprehensive overview of genes and pathways involved mainly in Fe uptake from roots to other plant compartments. Waters et al. [61] conducted a more comprehensive investigation on the role of the *NAM-B1* gene, which affects Fe and Zn in wheat.

*Gpc-B1* locus from *Triticum dicoccoides* was mapped and found to enhance Zn and Fe concentrations and encoded a NAC transcription factor that was found responsible to accelerate senescence. Senescence, the programmed degradation of cell constituents makes nutrients available for remobilization from leaves to developing seeds [19, 42]. Kohl et al. [79] reported that some NAC transcription factors were upregulated in the glumes at 14 days after anthesis and were obviously associated with developmental senescence. During senescence, proteases are rapidly activated to degrade leaf proteins into amino acids [80]. Serine proteases are the most important family of proteases participating in nitrogen remobilization (NR) during grain filling, acting as major regulators and executors in wheat and barley [81].

In wheat and barley, the specific NAC and WRKY transcription factors, in combination with hormones (abscisic acid and jasmonic acid), have been shown to be involved in the regulation of transition between early grain filling and developmental senescence [79, 82, 83]. Zhao et al. [84] identified a novel NAC1-type transcription factor, TaNAC-S, in wheat, with gene expression located primarily in the leaf/sheath tissues. Overexpression of TaNAC-S in transgenic wheat plants resulted in delayed leaf senescence, which led not only to increased GPC but also to increased grain yields; thus, this result further verified the improved NR from vegetative organs to growing grain in transgenic lines [84].

#### *3.3.2. Genes involved in phenolic acid accumulation*

Very little research has been conducted on the accumulation of phenolic acids. Ma et al. [39] reported five key enzymes, namely phenylalanine ammonia lyase (PAL), coumaric acid 3-hydrolase (C3 H), cinnamic acid 4-hydrolase (C<sup>4</sup> H), 4-coumarate CoA ligase (4CL) and caffeic acid/5-hydroxyferulic acid O-methlytransferase (COMT), which are essential for the biosynthesis of phenolic acids. Ma et al. [39] also characterized gene expression patterns of nine candidate genes associated with phenolic acid biosynthesis during early and late grain filling stages, the most crucial growth stage in polyphenol accumulation [85, 86]. The study revealed that seven genes (*TaPAL1*, *TaPAL2, Ta4CL1, Ta4CL2, TaCOMT1, TaCOMT2* and *TaC3H2*) are highly expressed during the early stages of grain development among white, red and purple wheat. However, *TaC3H1* was the single gene that was expressed only during the later stage of grain development. Finally, five genes (*TaC4H, TaPAL1, TaPAL2, Ta4CL2 and TaCOMT1*) showed higher expressions in both early and later grain developmental stages [39]. Hence, there is still a need to conduct studies to further characterize the process of phenolic acid accumulation in seeds.

on environmental circumstances and the growth stage in which micronutrients are taken up, translocated or remobilized from different plant tissues. Thus, it would depend on the nutrient soil status and the stage at which the selected nutrients are taken up. Nonetheless, there is little or no research on the characterization of the origin and starting concentration of the nutritional component attributed to specific concentrations obtained in specific grain compartments.

Waters and Sankaran [15] reported genes implicated in the uptake of Fe mainly. No gene(s) that are involved in Fe uptake have been reported for wheat. Thus, there is still a need to characterize and identify genes involved in the uptake of Fe from soil to the seeds in wheat. Furthermore, [70, 77, 78] provided a comprehensive overview of genes and pathways involved mainly in Fe uptake from roots to other plant compartments. Waters et al. [61] conducted a more comprehensive investigation on the role of the *NAM-B1* gene, which affects Fe and Zn in wheat.

*Gpc-B1* locus from *Triticum dicoccoides* was mapped and found to enhance Zn and Fe concentrations and encoded a NAC transcription factor that was found responsible to accelerate senescence. Senescence, the programmed degradation of cell constituents makes nutrients available for remobilization from leaves to developing seeds [19, 42]. Kohl et al. [79] reported that some NAC transcription factors were upregulated in the glumes at 14 days after anthesis and were obviously associated with developmental senescence. During senescence, proteases are rapidly activated to degrade leaf proteins into amino acids [80]. Serine proteases are the most important family of proteases participating in nitrogen remobilization (NR) during

In wheat and barley, the specific NAC and WRKY transcription factors, in combination with hormones (abscisic acid and jasmonic acid), have been shown to be involved in the regulation of transition between early grain filling and developmental senescence [79, 82, 83]. Zhao et al. [84] identified a novel NAC1-type transcription factor, TaNAC-S, in wheat, with gene expression located primarily in the leaf/sheath tissues. Overexpression of TaNAC-S in transgenic wheat plants resulted in delayed leaf senescence, which led not only to increased GPC but also to increased grain yields; thus, this result further verified the improved NR from vegeta-

Very little research has been conducted on the accumulation of phenolic acids. Ma et al. [39] reported five key enzymes, namely phenylalanine ammonia lyase (PAL), coumaric acid

feic acid/5-hydroxyferulic acid O-methlytransferase (COMT), which are essential for the biosynthesis of phenolic acids. Ma et al. [39] also characterized gene expression patterns of nine candidate genes associated with phenolic acid biosynthesis during early and late grain filling stages, the most crucial growth stage in polyphenol accumulation [85, 86]. The study revealed that seven genes (*TaPAL1*, *TaPAL2, Ta4CL1, Ta4CL2, TaCOMT1, TaCOMT2* and *TaC3H2*) are highly expressed during the early stages of grain development among white, red and purple wheat. However, *TaC3H1* was the single gene that was expressed only during the later stage

H), 4-coumarate CoA ligase (4CL) and caf-

grain filling, acting as major regulators and executors in wheat and barley [81].

*3.3.1. Genes involved in micronutrient accumulation*

354 Wheat Improvement, Management and Utilization

tive organs to growing grain in transgenic lines [84].

H), cinnamic acid 4-hydrolase (C<sup>4</sup>

*3.3.2. Genes involved in phenolic acid accumulation*

3-hydrolase (C3