In order to investigate the cutting mechanical characteristics of Caragana korshinskii (C.k.) branches and explore the optimal combination of cutting parameters to support the subsequent equipment development, this paper explores the relationship between branch diameter D, average cutting speed v, wedge angle β, slip cutting angle α, cutting height h, cutting gap t, moisture content M and peak cutting force by using a homemade swing-cut branch cutting test bench with peak cutting force of branches as the target value under unsupported and supported cutting methods, respectively, through single-factor tests. Based on the single-factor test, v, β, α and t were selected as the test factors, and a multi-factor test was conducted with the peak cutting force as the target. Test result: The best combination of unsupported cutting in the range of multi-factor test is v for 3.315 m·s⁻¹, β for 20°, α for 20°, when the peak cutting force is 95.690 N. Supported cutting multi-factor test range to get the best combination of v for 3.36 m·s⁻¹, β for 20°, α for 20°, t for 1.38 mm, when the peak cutting force is 53.082 N. The errors of the predicted peak cutting force and the measured peak cutting force of the obtained model were 1.3% and 3.9%, respectively, which prove that the cutting parameters were optimized reliably. This research can provide a theoretical basis for subsequent development the C.k. harvesting equipment.

To solve the problems of poor sawing surface quality, severe blade wear and high power consumption caused by unreasonable working parameters in the process of Caragana korshinskii (C.K.) stumping, this study explored the effects of branch diameter (D), sawing speed $\left(v_c\right)$, feeding speed $\left(v_f\right)$, cutting inclination (α), number of circular saw teeth (T) and moisture content (M) on sawing power consumption (P) and sawing surface quality (A) through a single-factor test using a homemade branch sawing bench. Based on the Box–Behnken design principle, a multi-factor test was carried out based on a single-factor test with $v_c$,$v_f$, α and T as influencing factors and with P and A as targets, establishing a regression model. The test results show that the sawing power consumption (P) increases with increasing D, decreases with increasing M, and decreases first and then increases with increasing $v_c$, $v_f$, α and T; the sawing surface quality (A) increases first and then decreases with increasing D, increases with increasing M, and first increases and then decreases with increasing $v_c$, $v_f$, α and T. The optimum combination of parameters for the regression model was obtained with $v_c$ of 45.24 m/s, $v_f$ of 0.34 m/s, α of 10° and T of 100, which resulted in the P of 177.46 J and A of 85.87%. The errors between the predicted and actual values of P and A are 3.1% and 6%, respectively. The study can provide information to support the development of subsequent C.K. stubble equipment.