Optimization of preparation process of nanometer rabbit bone meal by ball milling

Abstract: Rabbit meat as a kind of green and healthy meat, contains a lot of nutrients. With the increase of the yield of rabbit meat, rabbit bone and other rabbit meat processing by-products are increasing. Rabbit bone has high nutritional value like other livestock and poultry bone, but it is mostly used for primary processing, such as animal feed, and it has a low rate of deep processing utilization, which results in a great waste of resources. So it is very necessary for us to find a new form of utilization for it. Generally speaking, the smaller the particle size, the greater the porosity and specific surface area, and the better the surface adsorption capacity, solubility and dispersion. In addition, if the particle size is reduced to the nanometer scale, it is likely to produce some characteristics which are different from that of conventional particles, such as small size effect, surface effect and catalysis effect. Therefore, in this study, the response surface method was used to find the best preparation technology of the nanometer rabbit bone meal. The spines, ribs and legs of 70-day-age Ira rabbits were used as raw materials (the ratio of total mass of spines and ribs to mass of legs was 4:1), and multiple treatments were adopted to process these bones, such as high pressure cooking, protease hydrolysis, colloid mill grinding, vacuum freeze drying, standard sieve sieving, and ball milling; the method of dynamic light scattering was used to measure the average particle size and the particle dispersion index (PDI) of rabbit bone meal. On the basis of single factor tests, the response surface method was employed to optimize the preparing parameters of nanometer rabbit bone meal, and the quadratic regression equation was established to find the best processing conditions. The results illustrated that the optional preparation conditions were as follows: Ball-milling speed was 558 r/min, ball-milling time was 4.7 h, and ball-material ratio was 3.66:1. Three validation tests were carried out under these conditions, and the results showed that the actual verification value of the average particle size of nanometer rabbit bone meal was (502.5±11.7) nm, the actual verification value of the PDI of nanometer rabbit bone meal was 0.497±0.021, and the relative errors between the predicted values and measured values were less than 5%, which indicated that the regression model was reliable and had practical value in the deep processing of rabbit bone. The results provide a reference for the follow-up study of deep processing of rabbit bone and other livestock poultry bone.