Application of the Taguchi method in poultry science: estimation of thein vitrooptimum intrinsic phytase activity of rye, wheat and barley

Free and immobilized Aspergillus oryzae SBS50 producing protease-resistant and thermostable phytase

Optimization for enhanced phytase production by Aspergillus oryzae SBS50 in submerged fermentation was investigated using Taguchi design. In first step design, starch, beef extract, magnesium sulphate, ferrous sulphate and Tween 80 were identified as significant factors affecting phytase production. These significant factors were further optimized at four different levels using a second Taguchi design and were observed that 1% starch, 2% beef extact, 3% Tween 80, 0.1% magnesium sulphate and 0.225% ferrous sulphate supported maximum phytase production (47,432 U/L). The use of Taguchi designed experiments resulted in 14.9-fold enhancement in phytase production compared to the medium optimized by 'one variable at a time' approach. Furthermore, 4% agar immobilized conidiospores of A. oryzae supported high phytase production compared with free cells and other matrices. Agar-immobilized conidiospores resulted in sustained phytase production up to eight repeated batch cycles followed by a decrease in enzyme titres.

Optimisation of broiler chicken responses from 0 to 7 d of age to dietary leucine, isoleucine and valine using Taguchi and mathematical methods

Three experiments were conducted to evaluate the applicability of the Taguchi method (TM) and optimisation algorithms to optimise the branch chain amino acids (BCAA) requirements in 0 to 7 d broiler chicks. In the first experiment, the standardised digestible (SID) amino acids and apparent metabolisable energy (AME) values of maize, wheat and soya bean meal were evaluated. In the second experiment, three factors including leucine (Leu), isoleucine (Ile) and valine (Val), each at 4 levels, were selected, and an orthogonal array layout of L16 (4(3)) using TM was performed. After data collection, optimisation of average daily gain (ADG) and feed conversion ratio (FCR) were obtained using TM. The multiobjective genetic algorithm (MOGA) and random search algorithm (RSA) were also applied to predict the optimal combination of BCAA for broiler performance. In the third experiment, a growth study was conducted to evaluate the applicability of obtained optimum BCAA requirements data by TM, MOGA and RSA, and results were compared with those of birds fed with a diet formulated according to Ross 308 recommendations. In the second experiment, the TM resulted in 13.45 g/kg SID Leu, 8.5 g/kg SID Ile and 10.45 g/kg SID Val as optimum level for maximum ADG (21.57 g/bird/d) and minimum FCR (1.11 g feed/g gain) in 0- to 7-d-old broiler chickens. MOGA predicted the following combinations: SID Leu = 14.8, SID Ile = 9.1 and SID Val = 10.3 for maximum ADG (22.05) and minimum FCR (1.11). The optimisation using RSA predicted Leu = 16.0, Ile = 9.5 and Val = 10.2 for maximum ADG (22.67), and Leu = 15.5, Ile = 9.0 and Val = 10.4 to achieve minimum FCR (1.08). The validation experiment confirmed that TM, MOGA and RSA yielded optimum determination of dietary amino acid requirements and improved ADG and FCR as compared to Aviagen recommendations. However, based on the live animal validation trial, MOGA and RSA overpredicted the optimum requirement as compared to TM. In general, the results of these studies showed that the TM may be used to optimise nutrient requirements for poultry.