Modelling the lag time and growth rate of Aspergillus section Nigri IOC 4573 in mango nectar as a function of temperature and pH

被引:16
作者
Silva, A. R. [1 ]
Sant'Ana, A. S. [2 ]
Massaguer, P. R. [1 ,3 ]
机构
[1] Univ Campinas UNICAMP, Dept Food Sci, Fac Food Engn FEA, Campinas, SP, Brazil
[2] Univ Sao Paulo, Dept Food & Expt Nutr, Fac Pharmaceut Sci FCF, Sao Paulo, Brazil
[3] Univ Estadual Campinas, Dept Chem Proc, Fac Chem Engn, Campinas, SP, Brazil
关键词
Arrhenius-Davey model; Aspergillus section Nigri; fruit juices; mango nectar; modelling; polynomial model; predictive mycology; spoilage; HEAT-RESISTANT FUNGI; ALICYCLOBACILLUS-ACIDOTERRESTRIS; WATER ACTIVITY; PENICILLIUM-EXPANSUM; EXPERIMENTAL-DESIGN; PREDICTIVE MODEL; RADIAL GROWTH; FRUIT JUICES; APPLE JUICE; FOOD;
D O I
10.1111/j.1365-2672.2010.04803.x
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Aims: To assess the behaviour of Aspergillus section Nigri IOC 4573 in mango nectar as affected by temperature and pH. Methods and Results: A central composite design (22 + 2*2 + 3) was used to estimate the influence of temperature (17 center dot 2-22 center dot 8 degrees C) and pH (3 center dot 28-4 center dot 7) on A. section Nigri growth (lambda, lag time; mu, growth rate). Secondary models (polynomial and Arrhenius-Davey) describing the effects of temperature and pH on lambda and mu were constructed. A decrease in temperature from 22 center dot 8 degrees C to 17 center dot 2 degrees C resulted in an a 16-fold increase in lambda. The increase in temperature from 20 degrees C to 22 center dot 8 degrees C at pH = 4 center dot 0 led to a fourfold increase in mu. The polynomial model was the best in fitting the data and the pH (linear), temperature (linear and quadratic terms) significantly influenced lambda. For mu, there was a significant influence by the pH (linear), temperature and pH (quadratic terms). Conclusions: The storage of mango nectar at < 15 degrees C and reduced pH could completely inhibit the growth of A. section Nigri. Significance and Impact of the Study: This is the first study to show how storage temperature and seasonal variability (pH) between harvests may affect mould growth in mango nectar.
引用
收藏
页码:1105 / 1116
页数:12
相关论文
共 64 条
[1]   Bioactive compounds and antioxidant potential of mango peel extract [J].
Ajila, C. M. ;
Naidu, K. A. ;
Bhat, S. G. ;
Rao, Uts. Prasada .
FOOD CHEMISTRY, 2007, 105 (03) :982-988
[2]   The hurdle effect of mild heat and two tropical spice extracts on the growth of three fungi in fruit juices [J].
Akpomedaye, DE ;
Ejechi, BO .
FOOD RESEARCH INTERNATIONAL, 1998, 31 (05) :339-341
[3]  
Anonymous, 2003, Compr Rev Food Sci F, V2, P46, DOI DOI 10.1111/J.1541-4337.2003.TB00051.X
[4]   Validating and comparing predictive models [J].
Baranyi, J ;
Pin, C ;
Ross, T .
INTERNATIONAL JOURNAL OF FOOD MICROBIOLOGY, 1999, 48 (03) :159-166
[5]   MATHEMATICS OF PREDICTIVE FOOD MICROBIOLOGY [J].
BARANYI, J ;
ROBERTS, TA .
INTERNATIONAL JOURNAL OF FOOD MICROBIOLOGY, 1995, 26 (02) :199-218
[6]   Modelling mould spoilage in cold-filled ready-to-drink beverages by Aspergillus niger and Penicillium spinulosum [J].
Battey, AS ;
Duffy, S ;
Schaffner, DW .
FOOD MICROBIOLOGY, 2001, 18 (05) :521-529
[7]   Estimating the bacterial lag time: which model, which precision? [J].
Baty, F ;
Delignette-Muller, ML .
INTERNATIONAL JOURNAL OF FOOD MICROBIOLOGY, 2004, 91 (03) :261-277
[8]   Quality of the fruits and pulp of Uba mango [J].
Benevides, Selene Daiha ;
Ramos, Afonso Mota ;
Stringheta, Paulo Cesar ;
Castro, Vanessa Cristina .
CIENCIA E TECNOLOGIA DE ALIMENTOS, 2008, 28 (03) :571-578
[9]  
Beuchat L. R., 2001, COMPENDIUM METHODS M, V3, P217
[10]   Response surface methodology (RSM) as a tool for optimization in analytical chemistry [J].
Bezerra, Marcos Almeida ;
Santelli, Ricardo Erthal ;
Oliveira, Eliane Padua ;
Villar, Leonardo Silveira ;
Escaleira, Luciane Amlia .
TALANTA, 2008, 76 (05) :965-977