Paper Title
Effects of Noise on Mulching Oil Palm Fronds using Tractor Mounted Mulcher Blades

Abstract
Pruning and subsequent field upkeep generates oil palm fronds wastes in oil palm plantation. Burning of unwanted biomass and other waste material is apparently the cheapest and fastest method of waste disposal. This activity causes excessive release of CO2 to the atmosphere and contribute to climate change and global warming. Zero burning technique was found to be financially and economically superior to the burn method. Mulching of oil palm fronds as the best alternative using the existing blade affects the operators in terms of vibration. Three different blades were designed using Solid Works, produced and compared among the blades to select the best blade with less vibration effect on tractor operator. Measured vibration in tractor was conducted by putting Sensor VM 24 vibration meter in steering wheel of tractor by tying adaptor and clip in steering wheel tractor and putting sensor vibration meter in the adaptor. Data acquisition were done at the Universiti Putra Malaysia oil palm plantation under the same operating conditions by four blades with different lifting angles (60o, 90o, 120o, and 150o), two tractorPTO speeds (540 and 1000 rpm) and three tractorforward speeds (1, 3, and 5 km/h). The statistical analysis based on ANOVA test of significance was in Completely Randomized Blocked Design (CRBD) - model andshowed significance at (P<0.05). Tukey's Studentized Range (HSD) testshowed significant differencebetween the means (P<0.05). The results show that minimum vibration was given by the blade with 90o lifting angle at tractor forward speeds of 1 and 3 km/h and tractor PTO speeds of 540 and 1000 rpm with mean values of 0.47 and 0.50 Hz respectively. Multiple regression were used in describing the relationships between blade lifting angles, tractor forward speed and tractor PTO speed to predict a model equation for vibration. Coefficient of determination (R2) on the vibration shows that the linear and quadratic regression coefficient of vibration are highly significant P= 0.0001 and the R2 = 0.3766 and 0.377 respectively. The models are weak and not fit to predict vibration. Keywords - Oil Palm Fronds, Mulching, Mulcher, Blades Lifting Angles, Noise