Next generation sequencing methods allow species identification from environmental samples, including faecal material and thus facilitate the investigation of diet and the interdependencies between predator and prey. PCR-based methods, employing a range of meta-barcodes have been widely used, but suffer from biases and limitations. Capture-based methods may reduce these biases as well as provide a means for assessing multiple barcodes and meta-barcodes simultaneously, including novel taxa-specific nuclear markers to maximise species identification. The robustness and accuracy of these methods will be tested using a range of captive animals, where the diet is known. This method will allow investigation of diet in a specialist herbivore, the giant panda (Ailuropoda melanoleuca). Giant panda feed almost exclusively on bamboo, yet their diet may contain hidden complexities, with over 60 bamboo species are reportedly eaten, plus occasional consumption of other plants and even animals. Many bamboo species are difficult to distinguish, especially following digestion, restricting our understanding of the precise bamboo species giant pandas rely on. Standard ‘universal’ plant barcodes have limited resolution in bamboo due to low rates of molecular evolution, and even whole chloroplast sequencing shows limited differences. Using existing genomic data from bamboos and other grasses to develop nuclear DNA species diagnostic markers that can be incorporated into a capture-based approach, we will be able to increase the reliability of bamboo identification in the diet. In addition, information from standard ‘universal’ meta-barcodes will also be incorporated to provide a complete overview of both bamboo and non-bamboo species consumed by giant panda.