The giant panda (Ailuropoda melanoleuca) is classified as a carnivore, yet subsists on a diet comprised almost exclusively of bamboo. Wild and captive giant pandas use highly selective foraging behaviors for processing and consuming bamboo. These behaviors are for the first time quantified in captive giant pandas over a 5-year period of time showing highly specific seasonal trends. Giant panda feeding behavior was recorded using live video observations of two giant pandas housed at the Memphis Zoo from November 2003 to June 2008. Leaf was the primary plant part consumed from June to December, whereas culm was consumed primarily from February to May, with both bears displaying similar seasonal shifts in plant part consumption. From May to June, leaf consumption increased significantly (P-values<0.001); from June to August, leaf consumption remained high and stable. From December to March, leaf consumption decreased significantly (P-values<0.001). Specific behaviors for bamboo leaf and culm consumption were also observed. Both bears formed wads of leaves before ingestion while feeding on leaf, but the male employed this feeding behavior more often than the female (54 and 33%, respectively). Both bears used similar culm-stripping behavior (26 and 25%), used to remove the outer layer and isolate the pith for consumption. This study indicates that unique seasonal foraging behaviors observed in wild pandas are also apparent in captive animals in relation to plant part selectivity and feeding behaviors.

Giant panda (Ailuropoda melanoleuca) monitoring and research often require accurate estimates of population size and density. However, obtaining these estimates has been challenging. Innovative technologies, such as fecal near infrared reflectance spectroscopy (FNIRS), may be used to differentiate between sex, age class, and reproductive status as has been shown for several other species. The objective of this study was to determine if FNIRS could be similarly used for giant panda physiological discriminations. Based on samples from captive animals in four U.S. zoos, FNIRS calibrations correctly identified 78% of samples from adult males, 81% from adult females, 85% from adults, 89% from juveniles, 75% from pregnant and 70% from non-pregnant females. However, diet had an impact on the success of the calibrations. When diet was controlled for plant part such that “leaf only” feces were evaluated, FNIRS calibrations correctly identified 93% of samples from adult males and 95% from adult females. These data show that FNIRS has the potential to differentiate between the sex, age class, and reproductive status in the giant panda and may be applicable for surveying wild populations.

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Giant pandas ( Ailuropoda melanoleuca) are specialist feeders, dependent upon bamboo as their main dietary resource. Due to the difficulty of many captive facilities to meet the natural qualitative diet changes in bamboo species and plant parts consumed seasonally by giant pandas, it is important to understand the nutritional quality of this forage and the differences among plant parts for improved husbandry. Near infrared (NIR) reflectance spectroscopy has been used as a tool to measure forage quality for both domestic and free-ranging species. The objective of this study was to determine the capability of NIR spectroscopy to: (1) discriminate between bamboo parts, (2) discriminate between bamboo species and (3) to predict the nutrient composition of bamboo. All bamboo samples were received from the Memphis Zoo Bamboo Farm (Memphis, TN, USA), dried at 60°C and ground to pass through a 1 mm screen before analysis. Discrimination between a total of 722 branch, culm and leaf samples resulted in an R2 of 0.88 and SECV of 0.18. Spectra from a total of 756 samples of four different species were used to create a discriminant equation among bamboo species. This resulted in an R2 of 0.47 and SECV of 0.29. Validation sets were correctly predicted at the following rates: (part) branch 94%, culm 100% and leaf 100%; (species) Phyllostachys aurea 10%, P. aureosulcata 98%, P. glauca 80% and Pseudosasa japonica 73%. Calibration equations for crude protein (CP), neutral detergent fibre (NDF), acid detergent fibre (ADF) and organic matter (OM) were created using all bamboo samples. For each nutritional constituent, the calibration R2 values exceeded 0.96. The average SEP across all constituents was 0.21% for CP, 2.35% for NDF, 3.62% for ADF, 0.84% for DM and 0.25% for OM. NIR spectroscopy was used to predict nutrient characteristics and discriminate between bamboo plant parts and species. The inability to discriminate among bamboo species is most likely due to a close physiological similarity between at least two of the species. Results suggest that NIR spectroscopy can be used to analyse bamboo forage quality which may have applications to captive giant panda husbandry.

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