Research on Enhancing the Yield and Quality of Oat Forage: Optimization of Nitrogen and Organic Fertilizer Management Strategies

In the context of the increasingly serious issues of resource waste, soil degradation, and environmental pollution caused by excessive nitrogen fertilizer application worldwide, this study conducted a two-year field experiment in Qinghai Province to explore suitable nitrogen fertilizer management strategies for the region. Ten fertilization levels were set, incorporating varying ratios of conventional nitrogen fertilizer and organic fertilizer, as well as the proportion of base fertilizer and topdressing. The focus was on monitoring the forage yield, quality, and related physiological indicators of oats during the flowering and milk stages. The use of correlation analysis and the multi-criteria decision-making model TOPSIS was applied for comprehensive data evaluation to determine the optimal fertilization strategy. After systematic data collection and analysis, the results showed that when 75% conventional nitrogen fertilizer was combined with 4500 kg<middle dot>hm-2 of organic fertilizer (F4), the oat yield during the milking stage reached its peak at 14,722.48 kg<middle dot>hm-2. Additionally, the yield effect was optimal (13,677.34 kg<middle dot>hm-2) when using 30% base fertilizer and 70% jointing fertilizer (D2). Regarding nutritional quality, the fertilization strategy combining 75% conventional nitrogen fertilizer with 4500 kg<middle dot>hm-2 of organic fertilizer, along with 30% base fertilizer and 70% jointing fertilizer (F4D2), significantly reduced the content of acid detergent fiber (ADF), neutral detergent fiber (NDF), and coarse fiber (CF) in oats, while increasing the content of EE (crude fat) and CP (crude protein). This significantly improved the nutritional value of oats. Correlation analysis further revealed the positive effect of fertilization amount and fertilization period on oat yield, as well as a negative correlation with fiber content. Finally, through comprehensive evaluation using the multi-criteria decision-making model TOPSIS, we verified the superiority of the fertilization strategy.