TESTING OF TURMERIC SLICER FOR POTATO SLICING

R. P. Murumkar, P. A. Borkar, S. M. Bhoyar, P. K. Rathod and A. R. Dorkar. All India Coordianted Resarch Project on Post Harvest Engineering and Technology, Dr. Panjabrao Deshmukh Krishi Vidyapeeth, Akola (M.S.) ...................................................................................................................... Manuscript Info Abstract ......................... ........................................................................ Manuscript History

Testing of turmeric slicer for slicing of potato:-Tests were carried out to evaluate the performance of the developed turmeric slicing/cutting machine for slicing of potato. Potatoes were purchased from local market of Akola. Before testing machine, physical properties of potato were measured. The clearance between casing plate and fixed cutting stainless steel blade was adjusted to get slices of desired thickness. The potatoes and ginger were fed through hopper into the machine at constant feed rate of 200 and 100 kg/h. The fed material is thrown forcefully by three stainless steel (SS) blades fixed to the hollow rotating drum by centrifugal action against the stationary SS cutting blade and get sliced/cut into desired thickness. The slicing was longitudinal. Whole slices and damaged slices were separated and weighed. The cutting efficiency was assumed to be affected by rotor speed (S) and slice thickness (T). The experimental design of independent parameters are shown in Table 1. This table shows the coded and decoded independent variables and their levels. Per cent Damage (PD):-WD Per cent damage = ---------x 100 W Response surface methodology was applied to the experimental data, using Design expert version 9 (Statease Inc. Minneapolis USA Trial version 2015). Sixteen trials were performed as enumerated in Table 2. Table 2:-Experimental layout for two variables and five levels response surface analysis for potato slicing. As per 2 variable 5 level model, 16 trials were performed as enumerated in Table 3 for obtaining the slicing efficiency and per cent damage responses for each treatment. All these trials were conducted with 500 g sample size and data for slicing efficiency and per cent damage was reported. To avoid bias, 16 runs were performed in a random order. The decision for the range and centre points of the variables was taken through preliminary trials as described by Pokharkar (1994)

Results and Discussion:-
Potato slicing:-Physical properties:-Some physical properties of potatoes used for study are given in Table 3. The average of 10 observations are given. Testing of turmeric slicer for slicing of potatoes:-Effect of input parameters on slicing efficiency for potato:-The slicing efficiency was observed to be ranging from 84.72 to 95.27% depending upon the slicing treatments. The minimum slicing efficiency was found for treatment having the combination of rotor speed of 500 rpm, slice thickness of 3.5 mm. The maximum slicing efficiency was observed in case of treatment having the combination of rotor speed of 350 rpm, slice thickness of 2.5 mm.
The analysis of variance (ANOVA) was made for the experimental data and the significance of rotor speed and slice thickness as well as their interactions on slicing efficiency was analyzed. The response surface quadratic model was fitted to the experimental data and statistical significance of linear, interaction and quadratic effects were analyzed for slicing efficiency response (Table 4). It revealed that the model was highly significant at 1 % level of significance. The results showed that among linear effects, slice thickness had significant effect on slicing efficiency (P<0.01) at 1 % level of significance followed by rotor speed. Quadratic effect of rotor speed had significant effect on slicing efficiency (P<0.01) at 1 % level of significance. The existence of quadratic terms of rotor speed indicates the curvy linear nature of response surface. It indicates that increasing the value of variable initially increases the response up to certain level of variable however further increase in the level of variable decreases the value of response.
The quadratic response surface model data indicated the results as significant. The lack of fit was found to be non significant which indicates that the developed model was adequate for predicting the response. The coefficient of determination (R 2 ) was 0.9620 for slicing treatment which indicated that the model could fit the data for slicing activity very well for all the two variables, i.e. of rotor speed and slice thickness. The linear terms of both the parameters showed effect on slicing efficiency however the interaction terms were showing non-significant effect. The quadratic terms of rotor speed only showed significant effect. The equation in terms of actual factors can be used to make predictions about the response forgiven levels of each factor. Here, the levels should be specified in the original units for each factor. This equation should not be used to determine the relative impact of each factor because the coefficients are scaled to accommodate the units of each factor and the intercept is not at the center of the design space.
The effect of rotor speed and slice thickness on slicing efficiency is as shown in Fig. 1. It could be observed that with increase in rotor speed, the slicing efficiency increased at a particular rotor speed and then decreased. It was observed that the slicing efficiency was found maximum at 2 mm slice thickness and as the slice thickness increased the slicing efficiency decreased. The results regarding percent damage by using various slicing parameters are given in Table 5.   Table 5, it revealed that the percent damage was observed to be ranging from 4.72 to 15.27 % depending upon the slicing treatments. The minimum percent damage was found for treatment having the combination of rotor speed 350 rpm, slice thickness 2 mm. The maximum percent damage was observed in case of treatment having the combination of rotor speed 500 rpm, slice thickness 3.5 mm. The ANOVA in Table6 revealed that the model was highly significant at 5 % level of significance. The results showed that among linear effects, slice thickness had significant effect on percent damage (P<0.05) at 5 % level of significance followed by rotor speed. All the interaction and quadratic effects of rotor speed were found significant for percent damage.
The lack of fit was non significant which indicates that the developed model was adequate for predicting the response. The coefficient of determination (R 2 ) was 0.9774 for slicing which indicated that the model could fit the data very well for all the variables. The equation in terms of actual factors can be used to make predictions about the response for given levels of each factor. Here, the levels should be specified in the original units for each factor. This equation should not be used to determine the relative impact of each factor because the coefficients are scaled to accommodate the units of each factor and the intercept is not at the center of the design space.

Effect of rotor speed and slice thickness on percent damage:-
The effect of rotor speed and slice thickness on percent damage was determined as shown in Fig. 2. The percent damage was found decreasing as the rotor speed increased to some extent and then the damage was found increasing at higher rotor speed. The percent damage was found increased significantly as the thickness of slice increased.
707 Fig. 2:-Effect of rotor speed and slice thickness on percent damage. The optimization criteria for different process variables and responses for slicing efficiency are given in Table 7. Optimization of slicing treatment variables:-Software Design Expert version 9.0.3.1 was used for the optimization of responses. A stationary point at which the slope of the response surface was zero in all the direction was calculated by partially differentiating the model with respect to each variable, equating these derivatives to zero and simultaneously solving the resulting equations. The optimum values for different variables and their predicted responses thus obtained are given in Table 8 as well as Fig. 3. The optimum values of different variables for slicing were found within the range considered in the study.

Verification of the Model for slicing of potato:-
The performance of this model was also verified by conducting an experiment for the validation. In order to validate the optimum conditions of slicing treatment variables, the experiments were conducted at optimum input parameters derived conditions. The average values of three experiments are given in Table 9. The observed values of slicing efficiency and percent damage were found to be 94.69 % and 4.58%. It could reveal that the experimental values were very close to the predicted values which confirmed the optimum conditions (Table 9).  (Fig. 3) indicated the range of optimum values of process variables.

Conclusion:-
The performance of developed turmeric slicer was found to be satisfactory for slicing of potato with 94.69 % slicing efficiency and it was found techno economically feasible for an entrepreneur.