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4. Special issue on 10th international conference of predictive modelling in foods: Towards a new paradigm in predictive microbiology. Pérez-Rodríguez F; Carrasco E; Pradhan AK; Sant'Ana AS; Valdramidis VP; Valero A Int J Food Microbiol; 2019 Feb; 291():65-66. PubMed ID: 30463031 [No Abstract] [Full Text] [Related]
5. Towards a novel class of predictive microbial growth models. Van Impe JF; Poschet F; Geeraerd AH; Vereecken KM Int J Food Microbiol; 2005 Apr; 100(1-3):97-105. PubMed ID: 15854696 [TBL] [Abstract][Full Text] [Related]
6. The future of predictive microbiology: strategic research, innovative applications and great expectations. McMeekin T; Bowman J; McQuestin O; Mellefont L; Ross T; Tamplin M Int J Food Microbiol; 2008 Nov; 128(1):2-9. PubMed ID: 18703250 [TBL] [Abstract][Full Text] [Related]
7. Application of predictive modelling techniques in industry: from food design up to risk assessment. Membré JM; Lambert RJ Int J Food Microbiol; 2008 Nov; 128(1):10-5. PubMed ID: 18701182 [TBL] [Abstract][Full Text] [Related]
9. Development of predictive modelling approaches for surface temperature and associated microbiological inactivation during hot dry air decontamination. Valdramidis VP; Belaubre N; Zuniga R; Foster AM; Havet M; Geeraerd AH; Swain MJ; Bernaerts K; Van Impe JF; Kondjoyan A Int J Food Microbiol; 2005 Apr; 100(1-3):261-74. PubMed ID: 15854711 [TBL] [Abstract][Full Text] [Related]
10. The "Sym'Previus" software, a tool to support decisions to the foodstuff safety. Leporq B; Membré JM; Dervin C; Buche P; Guyonnet JP Int J Food Microbiol; 2005 Apr; 100(1-3):231-7. PubMed ID: 15854708 [TBL] [Abstract][Full Text] [Related]
11. Integrative modelling for sustainable water allocation: editorial notes on the special issue. Schreider SY J Environ Manage; 2005 Dec; 77(4):267-8. PubMed ID: 16288824 [No Abstract] [Full Text] [Related]
12. [Experimental design and data handling in food microbiology]. Carbonell EA Microbiologia; 1993 Feb; 9 Spec No():104-8. PubMed ID: 8484911 [TBL] [Abstract][Full Text] [Related]
13. Current trends in predictive modelling of microbial lag phenomena. Swinnen IA; Bernaerts K; Dens EJ; Geeraerd AH; Van Impe JF Meded Rijksuniv Gent Fak Landbouwkd Toegep Biol Wet; 2001; 66(3b):495-502. PubMed ID: 15954644 [TBL] [Abstract][Full Text] [Related]
14. Modelling the variability of lag times and the first generation times of single cells of E. coli. Métris A; Le Marc Y; Elfwing A; Ballagi A; Baranyi J Int J Food Microbiol; 2005 Apr; 100(1-3):13-9. PubMed ID: 15854688 [TBL] [Abstract][Full Text] [Related]
15. Predictive modelling of growth, survival and inactivation of pathogenic and spoilage organisms in foods. Roberts TA Microbiologia; 1993 Feb; 9 Spec No():93-5. PubMed ID: 8484921 [No Abstract] [Full Text] [Related]
16. [Multichannel device for monitoring the quality of food products]. Khastsaev BD Med Tekh; 1996; (6):42-4. PubMed ID: 9053714 [No Abstract] [Full Text] [Related]
17. [Principles of monitoring food products by impedance Bactometer]. Khastsaev BD Med Tekh; 1996; (5):41-3. PubMed ID: 8992188 [No Abstract] [Full Text] [Related]
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20. Optimal experiment design for cardinal values estimation: guidelines for data collection. Bernaerts K; Gysemans KP; Nhan Minh T; Van Impe JF Int J Food Microbiol; 2005 Apr; 100(1-3):153-65. PubMed ID: 15854701 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]