Knowledge based diagnosis of inoculum properties and sterilization time in lactic acid fermentation

Siimes, T.; Nakajima, Mikio; Yada, Hideo; Asama, Hajime; Nagamune, Teruyuki; Linko, Pekka; Endo, Itaru

doi:10.1007/bf02447474

Cited by 6 publications

(1 citation statement)

References 11 publications

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“…Therefore, some hypothetically relevant inoculum properties are not included in the model (Atkinson and Mavituna, 1991). A regression or classification model can be obtained in order to detect inoculum qualities that are most related to high fermentation productivity (Atkinson and Mavituna, 1991;Siimes et al, 1992). When a poor-quality inoculum is detected it should not be used to inoculate the production tank.…”

Section: Introductionmentioning

confidence: 99%

Multiblock PLS analysis of an industrial pharmaceutical process

Lopes

Menezes

Westerhuis

et al. 2002

Biotech & Bioengineering

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The performance of an industrial pharmaceutical process (production of an active pharmaceutical ingredient by fermentation, API) was modeled by multiblock partial least squares (MBPLS). The most important process stages are inoculum production and API production fermentation. Thirty batches (runs) were produced according to an experimental planning. Rather than merging all these data into a single block of independent variables (as in ordinary PLS), four data blocks were used separately (manipulated and quality variables for each process stage). With the multiblock approach it was possible to calculate weights and scores for each independent block. It was found that the inoculum quality variables were highly correlated with API production for nominal fermentations. For the nonnominal fermentations, the manipulations of the fermentation stage explained the amount of API obtained (especially the pH and biomass concentration). Based on the above process analysis it was possible to select a smaller set of variables with which a new model was built. The amount of variance predicted of the final API concentration (cross-validation) for this model was 82.4%. The advantage of the multiblock model over the standard PLS model is that the contributions of the two main process stages to the API volumetric productivity were determined.

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Section: Introductionmentioning

confidence: 99%

Multiblock PLS analysis of an industrial pharmaceutical process

Lopes

Menezes

Westerhuis

et al. 2002

Biotech & Bioengineering

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Real‐time fuzzy‐knowledge‐based control of Baker's yeast production

Siimes¹,

Linko²,

Numers

et al. 1995

Biotech & Bioengineering

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A real-time fuzzy-knowledge-based system for fault diagnosis and control of bioprocesses was constructed using the object-oriented programming environment Small-talk/V Mac. The basic system was implemented in a Macintosh Quadra 900 computer and built to function connected on line to the process computer. Fuzzy logic was employed in handling uncertainties both in the knowledge and in measurements. The fuzzy sets defined for the process variables could be changed on-line according to process dynamics. Process knowledge was implemented in a graphical two-level hierachical knowledge base. In on-line process control the system first recognizes the current process phase on the basis of top-level rules in the knowledge-base. Then, according to the results of process diagnosis based on measurement data, the appropriate control strategy is subsequently inferred making use of the lower level rules describing the process during the phase in question. (c) 1995 John Wiley & Sons, Inc.

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