The application of near-infrared spectroscopy to predict composition, gross energy yield, and methane production of natural forages on the Qinghai–Tibet Plateau

Background: Yak (Poephagus grunniens) production on the Qinghai–Tibet Plateau is influenced heavily by the quality of the natural forage, which can vary significantly in both quality and quantity. Therefore, timely and accurate monitoring of forage variables is essential for optimizing livestock production in this region. Methods: This study investigated the use of near-infrared spectroscopy (NIRS) as a tool for estimating the composition and quality of natural forage. A total of 301 natural forage samples were collected, and their spectral data were acquired using NIRS. Conventional methods were used to measure the forage composition, and predictive models were developed based on the spectral data. Results: Our findings indicate that NIRS can accurately predict the contents of crude protein, acid detergent fiber, and neutral detergent fiber. However, it demonstrated less accuracy in predicting dry matter digestibility, gross energy yield, and methane production. Conclusions: The application of NIRS for assessing the nutritional composition of forages on the Qinghai–Tibet Plateau is a key advancement for the livestock industry. Understanding forage nutrition enables informed feeding strategies and improvement of livestock production. Future research should refine predictive models to ensure sustainable forage management and enhance livestock productivity in this unique ecological environment.