The relationship between thermophysiology, endocrinology and behaviour in female giant pandas

Abstract

The breeding of giant pandas is attracting great attention as it concerns population stability. Due to the lag in hormone testing, it is impossible to assess the oestrus state of female giant pandas efficiently and concisely via hormone monitoring accompanied by separate empirical behaviour. Here, 6 female giant pandas were selected to monitor the oestrus period. Infrared thermography was utilized to measure eye temperature. Simultaneously, urinary hormone levels and behaviours were recorded daily. Subjects in oestrus exhibited significant differences in eye temperature, hormone levels and behaviours compared with those in their in non-oestrus. Specifically, the average eye temperature in oestrus was significantly higher than that in non-oestrus. The eye temperature of giant pandas began to rise from the pre-oestrus phase, reached a maximum in the oestrus peak phase and began to decline after mating, but was still higher than the average temperature in non-oestrus. There were significant correlations among eye temperature, hormone levels and behaviours. The main physiological changes in female giant pandas in thermophysiology, endocrinology and behaviour can be used to assess the shift in oestrus. Our study breaches the limitations of traditional methods and provides a robust and reliable method to judge the oestrus of captive female giant pandas.

Introduction

Screening for the appropriate oestrus period plays a crucial role in reproductive success. In recent decades, the oestrus peak phase of female giant pandas has been inferred from behaviour observations and the frequency of the call^1,2. Behaviour assessment is an effective method of distinguishing oestrus³. However, some subjects present a peak phase of very short duration, only for 1–2 h, and the typical behaviours during the peak phase are difficult to observe³. By contrast, few female giant pandas present typical oestrus behaviours, including scent marking, bleating and chirping. Due to the lack of research subjects, the small amount of data, the deviation of research results and individual differences, it is hard to establish a reliable behaviour evaluation standard⁴. Nevertheless, ambiguous behaviour observation and untimely hormone monitoring impedes a rapid response to the oestrus period in female giant pandas, which can significantly reduce their successful mating rate. Consequently, a precise, reliable and non-contact method is needed for the mating and breeding of giant pandas.

The determination of hormones can be performed via urine from female giant pandas during oestrus, especially during the oestrus peak phase. This process requires multiple collections of urine throughout the day to prevent missing the most appropriate time window for mating. The accuracy of hormone measurement depends on the quality of laboratories and personnel⁵. Furthermore, it requires a long collection, transport and experimental time. According to the physiology of menstruation in mammals, body temperature changes are mainly regulated by oestrogen and progesterone, where the rise in the luteal phase and the drop in the follicular phase are closely associated with hormonal levels⁶. The body temperature of animals usually increases significantly during oestrus. For example, Wang et al.⁷ measured the surface temperature of the key body parts in sows, and found that the body temperature of sows during 9–16 days of pregnancy was significantly lower than that during oestrus, and the vulva and buttocks temperature of sows during oestrus significantly increased⁷. Vicentini et al.⁸ combined hormone to monitor the changes of surface and core body temperature during the oestrus in Gyr heifers, and found that decreasing progesterone levels in the pre-oestrus phase were associated with a decline in body temperature, while increasing oestrogen levels during estrus corresponded to a rise in body temperature⁸. Thus, temperature is an important indicator of the menstrual cycle.

Recently, infrared thermography has been applied to animal reproduction studies, because it offers the advantages of a non-contact, non-invasive fast method; ease of capture; no stress response and real-time monitoring. This technology can be used to monitor changes in the body surface temperature of animals in real time and provide an important basis for thermal insulation ability, stress response, and disease diagnosis. For example, McCafferty et al.⁹ measured body temperature of the barn owl with infrared thermography, and found that the eye temperature of the barn owls during resting state and the wing surface temperature during flight were significantly higher than those of other body parts⁹. Edgar et al.¹⁰ found that within 20 min of stress induction, the comb temperature of the chickens rapidly decreased by 2 °C, while the eye temperature initially dropped before rising significantly above the baseline, and the head temperature also increased beyond the baseline¹⁰. Amezcua et al.¹¹ employed infrared thermography to continuously monitor lower limb temperature of pregnant sows, demonstrating its effectiveness in detecting lameness and providing an objective tool for health assessment¹¹. It has also been applied to assisted breeding in other animals (e.g., elephants, rhinoceros)¹². Furthermore, Durrant et al.¹³ used infrared thermography combined with ultrasound to monitor the pregnancies of two female giant pandas, confirming that infrared thermography can accurately determine pregnancy in giant pandas¹³.

To our best knowledge, there are few studies focusing on the application of infrared thermography in captive giant pandas. Here, the eye temperature of female giant pandas was measured via infrared thermography, while the behaviours observed and hormones in the urine were also monitored to explore oestrus accurately in female giant pandas, from non-oestrus to the final oestrus period.

Methods

Experimental animal selection and research were approved by the Institutional Animal Care and Use Committee (IACUC) of the Chengdu Research Base of Giant Panda Breeding (No. 2018023) and were conducted in strict accordance with the ARRIVE guidelines. Prior to the collection of data, permission was obtained from the Chengdu Research Base of Giant Panda Breeding in the Sichuan Province, China. All methods were performed in accordance with the relevant guidelines and regulations.

The Chengdu Research Base of Giant Panda Breeding is located in Chengdu, Sichuan Province, China. This area belongs to the subtropical humid monsoon climate zone, namely a mild climate with an annual average temperature of 16.2 °C, an annual average humidity of 81%, abundant rainfall and little sunshine. Six female giant pandas were selected as the subjects, when they were under the oestrus and mating periods in January–March 2024.

In this study, to ensure the scientific rigor and reliability of the results, age and reproductive history were considered in subject selection. The subjects were adult female giant pandas (6–20 years old) with multiple oestrus and parturition histories, selected to ensure an even age distribution across the sample.

Definition of oestrus behaviours

The main behaviours of female giant pandas during oestrus were comprised of activity: walking and running; feeding: eating bamboo, bamboo shoots, corn bun, apple, water, honey and other food; rest: keeping still or sleeping in various postures, eyes closed or not closed; scent marking: rubbing scent glands (located near the tail) on trees or rocks to mark territory or attract mates; bleating: usually in a softer, higher tone, similar to the sheep’s call; chirping: crisp, high and short tones, similar to a bird’s call¹⁴.

Thermophysiological, endocrinological and behavioural data collection

According to the specific anatomic structure of the eyeball, the blood vessels are distributed at the posterior of the lens, which may maintain general thermal energy. Therefore, it may play a buffering role against external factors, for example, by maintaining a stable temperature¹⁵. Compared with the surface temperature on the nose and fur, the eye temperature is closest to the rectal temperature and less affected by the environmental temperature and humidity¹⁶. In our previous work, it was also found that environmental temperature and humidity had no significant effect on eye temperature, as shown in the supplementary information (Figure S1 and Table S1). Moreover, given the specific animal welfare restrictions that non-contact and non-invasive methods be used to measure dynamic thermal changes, the eye presents absolute advantages as it can accurately reflect the animal’s body temperature¹⁷.

Thermophysiological measurement

Thermophysiological data were collected on 6 subjects from 8:00 to 9:00 because the subjects may go out to play at other times. The emissivity of the FLIR 540 portable infrared thermal imager was set to 0.98. The portable infrared thermal imager was used to collect thermophysiological data from subjects via a focused sampling method. Each one was collected over 5 days during the non-oestrus. After the animals entered oestrus, we began to collect data every day until 3 days after mating. We focused on collecting infrared thermal imaging videos of the subjects’ faces, taking the infrared thermal imaging picture at the appropriate time, namely the panda’s face exposed on the image with largest proportion. With the safety ensured, the data collection distance was kept as close as possible to the subjects, typically around 1 m and at most 2 m. Finally, the highest temperature on the surface was extracted as the eye temperature of the individual on that day. The data collection process was carried out indoors, without wind or direct sunlight and without restricting the subjects’ behaviour, to ensure the lowest stress response and environmental variation. The temperature and humidity in the cage were also recorded; see details of the workflow in Fig. 1.

Behavioural measurement

Behavioural observations were conducted from 8:30 to 10:30 and 14:00 to 16:00. By using a SONY camera, 4 h of behavioural video and audio data per day for each individual were captured for further analysis. Each one was collected for 5 days during the non-oestrus. After the animal entered oestrus, we began to collect data every day until 3 days after mating. No restrictive behaviours were set during the period; see details of the workflow in Fig. 1.

Endocrinologial measurement

From the end of the previous year to the next year, the breeders collected urine from the subjects between 7:00 and 8:00. Urine collection was performed once a week before oestrus, once a day during oestrus and 2–3 times a day during the oestrus peak. See details of the workflow in Fig. 1. Further, the concentrations of urinary oestrogen and progesterone were quantified using single-antibody competitive enzyme immunoassays (EIA). The used antibodies and steroid-3 3-(O-carboxymethyl) oxime horseradish peroxidase (3CMO-HRP) conjugates for oestrogen and progesterone were provided by C. Munro (Clinical Endocrinology Laboratory, University of California, Davis, CA, USA).

Fig. 1 [Images not available. See PDF.]

Workflow for thermophysiological, endocrinological and behavioural data collection in female giant pandas.

Thermophysiological data processing

Thermal images were captured and analysed by use of the rainbow palette. This palette comprises dark- and light-coloured bars, indicating temperatures from cooler (dark blue) to warmer (white). The other colours indicate the intermediate temperatures. The program FIRL Tools V5.6.1 (FLIR Systems, Inc., USA) was used to extract the target temperature at the focal point and to calculate the average temperature, minimum temperature and maximum temperature of the measurement area⁸. The maximum temperature of each area was adopted in data analysis, according to the lowest variances in infrared thermography¹⁸. The extracted eye temperature was corrected by the formula to eliminate the influence of distance on temperature measurement¹⁹. Temperature measurement was conducted indoors, to ensure less solar radiation, temperature radiation from living subjects, wind force and atmospheric temperature.

Behavioural data processing

This study used manual observation methods to quantitatively analyze the behaviour of female giant pandas. Researchers first conducted frame-by-frame visual inspection of animal behaviour videos, employing both event recording (for behaviour frequency) and duration recording (for behaviour percentage). Before the behavior data extraction, the reliability analysis of the observer was carried out. Although all behavioral data were extracted by a single observer, the within-observer reliability analysis was performed²⁰. The results showed that the observer’s criteria for defining the oestrus behavior was reliable (p < 0.01).

Statistics

Prior to data analysis, the Kolmogorov-Smirnov test was used to test the normality and homogeneity of variance of the data. Normally distributed data were expressed as mean and standard deviation; otherwise, the data were expressed as quartiles (Q25, Q75). An independent-samples t-test was used to compare differences in eye temperature, oestrogen and progesterone between non-oestrus and oestrus subjects. Moreover, multivariate analysis of variance was used to determine whether eye temperature was affected by state. One-way analysis of variance was used to compare whether there were differences in eye temperature in different phases. Due to skew distribution of behavioural data, the Mann-Whitney U test was used to compare the differences in behaviour between the non-oestrus and oestrus subjects. Finally, Spearman correlation analysis was performed to determine the relationships among thermophysiological, endocrinological, and behavioural changes in the subjects from non-oestrus to the end of oestrus. p-value less than 0.05 were deemed significant.

Results

Endocrine

The study can be divided into the non-oestrus and oestrus periods, according to prior knowledge and the breeder’s experience. The oestrus period was divided into three phases, the pre-oestrus phase (oestrogen gradually rise to a peak), the oestrus peak phase (oestrogen suddenly drops after a peak) and the post-oestrus phase (after mating, oestrogen returns to normal and progesterone begin to rise) due to the menstrual cycle²⁰. There were significant differences in oestrogen and progesterone between non-oestrus and oestrus in subjects (p < 0.01). Oestrogen in the oestrus was significantly higher than that in non-oestrus, and progesterone was significantly lower than that in non-oestrus, see Table 1.

Table 1. Endocrine comparison between non-oestrus and oestrus in female giant pandas. Statistical significance is denoted as *p < 0.05, **p < 0.01.

Hormone	Non-oestrus (N = 6) (ng/mg Cr)	Oestrus (N = 6) (ng/mg Cr)	t	p
Oestrogen	4.136 ± 1.736	55.020 ± 37.251	−11.810	< 0.001**
Progesterone	21.480 ± 10.202	9.715 ± 7.451	7.387	< 0.001**

Behaviour

Behaviours, including the frequency of scent marking, bleating, chirping and the percentage of time spent on activity, rest and feeding, presented significant differences in subjects between non-oestrus and the oestrus (p < 0.05). During the oestrus period, the frequency of scent marking, bleating, chirping and activity time increased significantly, while rest and feeding time decreased significantly, see Table 2.

Table 2. Behaviour difference between non-oestrus and oestrus in female giant pandas. Statistical significance is denoted as *p < 0.05, **p < 0.01.

Behaviours		Non-oestrus (N = 6) [M (Q25, Q75)]	Oestrus (N = 6) [M (Q25, Q75)]	Z	p
Frequency	Scent marking	0(0,1)	3(0,11)	3.678	0.001**
	Bleating	0(0,0)	30(0,175)	5.511	0.001**
	Chirping	0(0,0)	0(0,22)	3.808	0.001**
Percentage	Activity	0.13(0.01,0.36)	0.45(0.30,0.68)	4.920	0.001**
	Rest	0.43(0.37,0.54)	0.36(0.10,0.50)	−2.164	0.030*
	Feeding	0.32(0.21,0.40)	0.06(0.02,0.13)	−5.478	0.001**

*p < 0.05 significant difference; **p < 0.01 extremely significant difference.

During the non-oestrus period, the subjects rarely presented bleating and chirping behaviour and performed only few scent markings. In contrast, during the oestrus period, the frequency of scent marking, bleating and chirping significantly increased accordingly, approaching a peak in the oestrus peak phase and continuing until post-oestrus phase. As oestrus progressed, the activity level of the subjects gradually increased but decreased at the oestrus peak phase, and began to recover after mating. The time spent on rest of the subjects showed an opposite trend against the activity trajectory. The feeding behaviour decreased gradually with oestrus progression, indicating that their appetites reached the lowest level during the oestrus peak phase and recovered slightly in the post-oestrus phase, see Fig. 2.

Fig. 2 [Images not available. See PDF.]

Behavioral changes across different phases in female giant pandas. Error bars represent mean ± standard deviation (SD).

Overall, significant behavioral differences were observed in female giant pandas between the non-oestrus and oestrus, with oestrus linked to increased scent marking, bleating, chirping, and activity, but reduced rest and feeding, while non-oestrous exhibited minimal behaviors.

Thermophysiology

To determine the effects of oestrus state (oestrus or non-oestrus) and the behavioural state (feeding, rest or activity) against temperature dynamic changes, multivariate analysis of variance was used to distinguish the impact on the eye temperature. These findings disclosed that the oestrus state presented a significant effect (F = 99.323, df = 1, p = 0.001), no significant effect was found on the behavioural state (F = 0.422, df = 2, p = 0.657), and there was no interaction effect of oestrus and behaviour on temperature changes (F = 1.061, df = 2, p = 0.350); for details see Fig. 3.

Fig. 3 [Images not available. See PDF.]

The effect of oestrus state and the behavioural state against the eye temperature changes in female giant pandas. Error bars represent mean ± standard deviation (SD).

Eye temperature presented a significant difference between non-oestrus and oestrus in subjects. The average eye temperature in oestrus was significantly higher than that in non-oestrus (36.596 ± 0.545 vs. 35.645 ± 0.356, t = −10.763, df = 104, p < 0.01). From the average eye temperature in non-oestrus and the three phases of oestrus, the eye temperature of subjects began to rise from the pre-oestrus phase, and the highest temperature appeared in the oestrus peak phase. After mating, it began to decline (Fig. 4).

To display the eye temperature dynamic changes among the non-oestrus and the three phases of oestrus, one-way analysis of variance was used to distinguish the differences, while the Bonferroni post hoc test was used to compare the specific difference between any two phases. Particularly, the eye temperature in non-oestrus was significantly different from that in the three phases of oestrus (p < 0.01), and that in post-oestrus was also significantly different from those in the pre-oestrus and oestrus peak phases (p < 0.01, Fig. 4).

Fig. 4 [Images not available. See PDF.]

The eye temperature changes across different phases in female giant pandas. Error bars represent mean ± standard deviation (SD). Statistical significance is denoted as *p < 0.05, **p < 0.01.

Relationship between thermophysiology, endocrinology and behaviours

Eye temperature had a significant positive correlation with oestrogen (r = 0.762, p < 0.01), and a significant negative correlation with progesterone (r = −0.559, p < 0.01), see Fig. 5. Except for rest, there was a significant correlation between the eye temperature and other oestrus behaviours (p < 0.01). Oestrogen was significantly correlated with all oestrus behaviours except rest (p < 0.01) and progesterone was significantly correlated with all oestrus behaviours (p < 0.01).

Fig. 5 [Images not available. See PDF.]

Relationships between thermophysiology, endocrine, and behaviours in female giant pandas. Statistical significance is denoted as *p < 0.05, **p < 0.01. ET, eye temperature; EC, oestrogen; PG, progesterone.

Discussion

To obtain a comprehensive understanding of reproduction in giant pandas, eye temperature, urinary hormone levels, and behaviour patterns were measured and observed. The findings indicated that the subjects in oestrus exhibited significant differences in eye temperature, hormone levels and behaviour compared with those in non-oestrus. Notably, the average eye temperature during oestrus was significantly higher than that in non-oestrus. The eye temperature in oestrus incresaed from the pre-oestrus phase, peaked at the oestrus peak phase, and decreased after mating. Finally, a significant correlation was found among eye temperature, hormone levels and behaviour.

Endocrine

Monitoring the changes in urinary oestrogen and progesterone of subjects during the oestrus period has long been regarded as a reliable and accurate method to identify their oestrus state^{22, 23–24}. Li et al.²⁵ reported that the urinary oestrogen of subjects in oestrus was significantly higher than that in non-oestrus, gradually decreasing in the post-oestrus phase and returning to the non-oestrus level, while progesterone were found to increase significantly following the post-oestrus phase²⁵, which is consistent with the results of this study. High levels of oestrogen promote endometrial thickening and the secretion of luteinizing hormone, thereby triggering ovulation²⁶. Excessive progesterone will inhibit the ovulation process²⁷. These findings indicate that changes in oestrogen and progesterone levels are important characteristics of reproductive physiology during oestrus in subjects.

Behaviour

The behaviours of subjects during the oestrus period included scent marking, bleating, chirping, activity, rest and feeding. These are usually observed with high frequency in the oestrus period¹⁴. The results of subjects in oestrus exhibited a series of typical behavioural characteristics. For example, there was a significantly increased tendency in behaviours, including scent marking, bleating and chirping, along with a marked rise in overall activity levels. Conversely, feeding and rest behaviours were significantly reduced during oestrus. The increase in oestrus behaviour is mainly to attract the opposite sex and facilitate mating. For example, the behaviour of scent marking may not only help release sex pheromones but also attract male individuals by scent marking²⁸. Furthermore, during the oestrus period, the subjects may frequently emit bleating and chirping sounds. These vocalizations are considered to be non-aggressive and attract the appropriate mates in the oestrus period⁴. Decreased appetite and increased activity levels are the dominant manifestations in the pre-oestrus period. As the oestrus intensity deepens, this phenomenon becomes more pronounced^29,30.

Thermophysiology

There was a significant difference between non-oestrus and oestrus in subjects, and the average eye temperature in oestrus was significantly higher than that in non-oestrus, which is consistent with the previous work of Chen et al.³¹. This phenomenon has also been similarly supported in studies of other kinds of animals. For example, Wang et al.⁷ studied sows and found that the eye temperature in oestrus was significantly higher than that in the weaned phase, with the average temperature increasing from 36.40 °C to 37.23 °C, and the difference was highly significant⁷. Vicentini et al.⁸ also found that eye temperature of cows in oestrus began to rise significantly 24 h before oestrus and remained high during oestrus⁸. Wang et al.³² found that the highest, lowest and average temperatures of the eyes of dairy cows increased after entering the oestrus period, and the increase in the highest temperature was the most obvious, increasing by 1–2 °C³².

Endocrine and behaviour

The hormone levels of subjects in oestrus were strongly associated with their oestrus behaviour³⁰. The urinary oestrogen levels were consistent with the onset, development and decline of oestrus behaviour²⁵. The findings indicated that the oestrus behaviours of female giant pandas, such as scent marking, bleating, chirping and activity, were positively correlated with oestrogen levels. Similarly, Lindburg et al.², showed a strong positive correlation between the scent marking and bleating behaviours of female giant pandas and their oestrogen levels³³. The changes in oestrogen levels were temporally correlated with oestrus behaviour, but the continued expression of oestrus behaviours is not entirely dependent on continued high levels of oestrogen, indicating that the relationship between hormones and oestrus behaviours was not directly causal, and hormones may trigger the following behaviours rather than maintain them³³.

Behaviour and thermophysiology

Our study showed a significant correlation between oestrus behaviour and the eye temperature of subjects. The elevation in body temperature observed during oestrus in animals may be attributed to the increase in oestrus behaviour³⁴. However, when the subjects were limited to a certain range, after entering oestrus, the body temperature also rose significantly³⁵. Therefore, other factors contribute to the increase in body temperature.

Endocrine and thermophysiology

The reproductive hormones of female animals significantly influence both the core and the surface body temperature³⁶. The changes in body temperature during the oestrus period may be related to changes in hormone levels³⁷. Bertoni et al.³⁸ studied dairy cows and monitored the temperature changes in their eyes and vulva via infrared thermography. The involvement of oestrogen and progesterone led to an increase in the local surface temperature³⁸. Ruediger et al.³⁷ reported that the oestrogen level in the blood of cows was positively correlated, while the progesterone level was negatively correlated with the eye temperature³⁷. This conclusion is consistent with ours. Talukder et al.³⁹ observed that the body temperature of dairy cows was significantly higher on the day before ovulation than two days before ovulation. Although there were no significant changes in progesterone during this period, it may be related to a significant increase in oestrogen³⁹. Therefore, changes in the subjects’ eye temperature may be more reflective of intrinsic physiological states rather than direct behavioural expression.

Conclusion

The main physiological changes in eye temperature, endocrinology and behaviour can be used to assess oestrus state in female giant pandas, and they can provide reliable evidence for decision making in breeding and reproduction.

Limitation

The frequency of body temperature sampling may present a selection bias during measurement, and in further studies the sampling frequency per day needs to be increased to determine the precise mating time of the female giant panda.

Acknowledgements

We thank the wildlife Conservation Department of the National Forestry and Grassland Administration of P.R. China and the medical sound database from Chengdu Medical College (http://ama.cmc.edu.cn) for the support of this research.We extend our heartfelt thanks to breeders at Chengdu Research Base of Giant Panda Breeding for their diligent and attentive care of the pandas.

Author contributions

Author contribution: CP designed and constructed the general concept; GCF, HMN, LG and MY performed the field observation and collected data; GCF and LG analyzed data and drafted the manuscript with XF, CP and WW supervised all project. HAQ revised the charts and figures. All authors read and approved the final manuscript.

Funding

This research is supported by Sichuan Science and Technology Program (2023NSFSC1926, 2022NSFSC0020), the Chengdu Research Base of Giant Panda Breeding [NO. CAZG2025C04, 202503KY0004], National Natural Science Foundation of China [NO. 32270552]; National Key R&D Program of China (NO.2023YFE0108400); Key Discipline Project at the School of Public Health, Chengdu Medical College (No. 21).

Data availability

The datasets generated and/or analysed during the current study are not publicly available due ongoing research utilizing the same dataset but are available from the corresponding author on reasonable request.

Declarations

Competing interests

The authors declare no competing interests.

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

1. McGeehan, L et al. Hormonal and behavioral correlates of estrus in captive giant pandas. Zoo Biol.; 2002; 21, pp. 449-466.1:CAS:528:DC%2BD38XovFWhtrc%3D [DOI: https://dx.doi.org/10.1002/zoo.10047]

2. Lindburg, DG; Czekala, NM; Swaisgood, RR. Hormonal and behavioral relationships during estrus in the giant panda. Zoo Biol.; 2001; 20, 6 pp. 537-543.1:CAS:528:DC%2BD38XislSnsr4%3D [DOI: https://dx.doi.org/10.1002/zoo.10027]

3. Deng, SQ; Chen, M. Study on special estrus behavior and identification method of giant panda. J. Southwest. Agricultural Univ.; 1997; 19, pp. 386-388.

4. Yang, B et al. Discussion and prospect on estrus and ovulation monitoring methods of captive female giant pandas. Sichuan J. Zool.; 2022; 41, 3 pp. 348-360. [DOI: https://dx.doi.org/10.11984/j.issn.1000-7083.20210282]

5. Deng, T et al. Application of immunoassay technology in reproductive research of captive giant pandas. Chin. J. Wildl.; 2013; 34, 3. [DOI: https://dx.doi.org/10.3969/j.issn.1000-0127.2013.05.017]

6. Baker, F. C., Siboza, F. & Fuller, A. Temperature regulation in women: effects of the menstrual cycle. Temperature. 1–37. https://doi.org/10.1080/23328940.2020.1735927 (2020).

7. Wang, CY et al. Non-contact temperature measurement for identification of typical physiological States in sows. J. Agricultural Eng.; 2022; 38, 20 pp. 149-155.1:CAS:528:DC%2BB2MXhvFSku7rP [DOI: https://dx.doi.org/10.11975/j.issn.1002-6819.2022.20.017]

8. Vicentini, R et al. Infrared thermography reveals surface body temperature changes during proestrus and estrus reproductive phases in Gyr heifers (Bos Taurus indicus). J. Therm. Biol; 2020; 92, 102662. [DOI: https://dx.doi.org/10.1016/j.jtherbio.2020.102662] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/32888565]

9. McCafferty, D; Moncrieff, J; Taylor, I; Boddie, GF. The use of IR thermography to measure the radiative temperature and heat loss of a barn Owl (Tyto alba). J. Therm. Biol; 1998; 23, 5 pp. 311-318. [DOI: https://dx.doi.org/10.1016/S0306-4565(98)00022-9]

10. Edgar, JL; Nicol, CJ; Pugh, CA; Paul, ES. Surface temperature changes in response to handling in domestic chickens. Physiol. Behav.; 2013; 119, pp. 195-200.1:CAS:528:DC%2BC3sXhtFKlu7vL [DOI: https://dx.doi.org/10.1016/j.physbeh.2013.06.020] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/23816981]

11. Amezcua, R; Walsh, S; Luimes, PH; Robert, M. Infrared thermography to evaluate lameness in pregnant sows. Can. Veterinary J.; 2014; 55, 3 pp. 268-272.

12. Hilsberg-Merz, S. Infrared thermography in zoo and wild animals. Zoo Wild Anim. Med. 20–32. https://doi.org/10.1016/B978-141604047-7.50006-3 (2008).

13. Durrant, BS; Ravida, N; Spady, T; Cheng, A. New technologies for the study of carnivore reproduction. Theriogenology; 2006; 66, 6–7 pp. 1729-1736.1:CAS:528:DC%2BD28Xps1Oiuro%3D [DOI: https://dx.doi.org/10.1016/j.theriogenology.2006.02.046] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/16713619]

14. Chen, L; Li, G. Observation of estrus behavior in captive female giant pandas in Wolong. J. China West. Normal Univ. (Natural Sciences); 2006; 27, 1 pp. 79-81.1:CAS:528:DC%2BD28XmtVSms7g%3D [DOI: https://dx.doi.org/10.3969/j.issn.1673-5072.2006.01.017]

15. Standring, S. Gray’s Anatomy 42nd ed. 711–727 (Elsevier, 2020).

16. He, JC; Zhang, X; Li, SQ; Gan, QF. Effects of ambient temperature and humidity as well as measurement sites on infrared thermography temperature in dairy cows. J. Zhejiang Univ. (Agriculture Life Sciences); 2020; 46, 4 pp. 500-508.

17. Yuan, B., Gong, P. & Xie, L. A calibration method for measuring eye temperature based on infrared thermal imager. CN109419495A (2025).

18. Stewart, M et al. Non-invasive measurement of stress in dairy cows using infrared thermography. Physiol. Behav.; 2007; 92, 3 pp. 520-525.1:CAS:528:DC%2BD2sXhtF2htr3L [DOI: https://dx.doi.org/10.1016/j.physbeh.2007.04.034] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/17555778]

19. Zhang, JH; Zhang, XJ. Study on the influence of test distance on infrared thermography temperature measurement of Tan sheep and error correction. Ningxia J. Agric. Forestry Sci. Technol.; 2023; 64, 12 pp. 54-57.

20. Bateson, M. & Martin, P. Measuring Behaviour: An Introductory Guide. 91–111 (Cambridge university press, 2021).

21. Zhang, H. M. & Wang, P. Y. In Research on Giant Panda Reproduction. 45–75 (eds Zhang, H. M.) (China Forestry Publishing House, 2003).

22. Zeng, GQ et al. Research on giant panda reproductive biology I: changes in serum and urine levels of luteinizing hormone, progesterone, and 17β-estradiol during estrus in giant pandas. Curr. Zool.; 1990; 36, 1 pp. 66-72.

23. Shen, JN et al. Study on the changes of reproductive hormones in urine of Qinling giant pandas during breeding season. Chin. J. Wildl.; 2020; 41, 4 pp. 868-872. [DOI: https://dx.doi.org/10.19711/j.cnki.issn2310-1490.2020.04.003]

24. Peng, S. Y. et al. Changes in urinary sex hormones during estrus and pregnancy in female giant pandas. Chin. J. Zool. (2), 25–28. https://doi.org/10.13859/j.cjz.1993.02.009 (1993).

25. Li, FD et al. Changes in urinary 17β-estradiol and progesterone levels during estrus in female giant pandas and their relationship with mating. Acta Theriol. Sinica; 1993; 13, 3 pp. 166-171.1993AcApS.13.166L [DOI: https://dx.doi.org/10.16829/j.slxb.1993.03.002]

26. Bosch, E et al. Reduced FSH and LH action: implications for medically assisted reproduction. Hum. Reprod.; 2021; 36, 6 pp. 1469-1480.1:CAS:528:DC%2BB38XhslOms7jN [DOI: https://dx.doi.org/10.1093/humrep/deab065] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/33792685][PubMedCentral: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8129594]

27. Zhang, BB et al. MiR-140-3p promotes follicle granulosa cell proliferation and steroid hormone synthesis via targeting AMH in chickens. Theriogenology; 2023; 202, pp. 84-92.1:CAS:528:DC%2BB3sXlsF2gur8%3D [DOI: https://dx.doi.org/10.1016/j.theriogenology.2023.03.010] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/36933285]

28. Xu, L. Observation of diurnal behavioral rhythms in captive giant pandas. New. Farmers; 2023; 4, pp. 123-125.

29. Yang, SL; Li, M; Zhou, Q; Wei, RP; Li, D. Observation of estrus behavior and analysis of related indicators in female giant pandas. Sichuan J. Zool.; 2007; 26, 3 pp. 664-668.

30. Liu, M. Estrus identification of two captive female giant pandas in Chengdu. Contemp. Anim. Husb.; 2016; 10, 30 pp. 37-38.

31. Chen, YS et al. Preliminary study on reproductive biology of giant pandas. Acta Theriol. Sinica; 1985; 5, 3 pp. 233-239.1985AcApS..5.224C4211601 [DOI: https://dx.doi.org/10.16829/j.slxb.1985.03.015]

32. Wang, Z et al. A non-contact cow estrus monitoring method based on the thermal infrared images of cows. Agriculture; 2023; 13, 2 385. [DOI: https://dx.doi.org/10.3390/agriculture13020385]

33. Lindburg, DG; Czekala, NM; Swaisgood, RR. Hormonal and behavioral relationships during estrus in the giant panda. Zoo Biol.; 2001; 20, 6 pp. 537-543.1:CAS:528:DC%2BD38XislSnsr4%3D [DOI: https://dx.doi.org/10.1002/zoo.10027]

34. Walton, JS; King, GJ. Indicators of estrus in Holstein cows housed in tie stalls. J. Dairy Sci.; 1986; 69, 11 pp. 2966-2973.1:STN:280:DyaL2s7htVWgsg%3D%3D [DOI: https://dx.doi.org/10.3168/jds.S0022-0302(86)80754-8] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/3805470]

35. Suthar, VS; Burfeind, O; Patel, JS; Dhami, AJ; Heuwieser, W. Body temperature around induced estrus in dairy cows. J. Dairy Sci.; 2011; 94, 5 pp. 2368-2373.1:CAS:528:DC%2BC3MXnvFCgsL8%3D [DOI: https://dx.doi.org/10.3168/jds.2010-3858] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/21524526]

36. Charkoudian, N; Hart, ECJ; Barnes, JN; Joyner, MJ. Autonomic control of body temperature and blood pressure: influences of female sex hormones. Clin. Auton. Res.; 2017; 27, 3 pp. 149-155. [DOI: https://dx.doi.org/10.1007/s10286-017-0420-z] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/28488202]

37. De Ruediger, FR et al. Effect of estrous cycle phase on vulvar, orbital area and muzzle surface temperatures as determined using digital infrared thermography in Buffalo. Anim. Reprod. Sci.; 2018; 197, pp. 154-161. [DOI: https://dx.doi.org/10.1016/j.anireprosci.2018.08.0] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/30143282]

38. Bertoni, A et al. Scientific findings related to changes in vascular microcirculation using infrared thermography in the river Buffalo. J. Anim. Behav. Biometeorol.; 2020; 8, 4 pp. 288-297. [DOI: https://dx.doi.org/10.31893/jabb.20038]

39. Talukder, S et al. Infrared technology for estrus detection and as a predictor of time of ovulation in dairy cows in a pasture-based system. Theriogenology; 2014; 81, 7 pp. 925-935.1:STN:280:DC%2BC2cvntFGrsA%3D%3D [DOI: https://dx.doi.org/10.1016/j.theriogenology.2014.0] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/24560547]