Italian ryegrass (IRG) has become a vital forage crop due to its increasing cultivation area and its role in enhancing forage self-sufficiency. However, its production is susceptible to environmental factors such as climate change and drought, necessitating precise yield prediction technologies. This study aimed to assess the growth characteristics of IRG and predict dry matter yield (DMY) using vegetation indices derived from unmanned aerial vehicle (UAV)-based remote sensing. The Green Leaf Index (GLI), normalized difference vegetation index (NDVI), normalized difference red edge (NDRE), and optimized soil-adjusted vegetation index (OSAVI) were employed to develop DMY estimation models. Among the indices, GLI demonstrated the highest correlation with DMY (R² = 0.971). The results revealed that GLI-based UAV observations can serve as reliable tools for estimating forage yield under varying environmental conditions. Additionally, post-winter vegetation coverage in the study area was assessed using GLI, and 54% coverage was observed in March 2023. This study assesses that UAV-based remote sensing can provide high-precision predictions of crop yield, thus contributing to the stabilization of forage production under climate variability.

Ⅰ. INTRODUCTION
Ⅱ. MATERIALS AND METHODS
    1. Study site and plant material
    2. Soil environmental data collection
    3. Soil composition and chemical analysis
    4. UAV data acquisition and hyperspectralpost-processing
    5. Vegetation cover analysis
    6. Plant growth and nutritional analysis
    7. Statistical analysis
Ⅲ. RESULTS AND DISCUSSION
    1. Soil environmental data and composition analysis
    2. Chemical composition analysis
    3. Correlation analysis between growth parameter andobservation data
    4. Development of DMY estimation models
Ⅳ. CONCLUSIONS
Ⅴ. ACKNOWLEDGEMENTS
Ⅵ. REFERENCES

• Seung Hak Yang(National Institute of Animal Science, RDA, Cheonan 31000, Korea) Corresponding author
• Jeong Sung Jung(National Institute of Animal Science, RDA, Cheonan 31000, Korea)
• Ki Choon Choi(National Institute of Animal Science, RDA, Cheonan 31000, Korea)