In a batch reactor, how does the specific growth rate μ typically behave over the course of the fermentation (from lag through stationary phases)?
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AIt remains strictly constant throughout the entire process
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BIt increases exponentially without bound
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CIt changes during the fermentation as conditions evolve
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DIt is highest during the stationary phase
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EIt instantly drops to zero after inoculation
Answer
Correct Answer: It changes during the fermentation as conditions evolve
Explanation
Introduction / Context:Batch cultures are closed systems: nutrients deplete, products accumulate, and pH or dissolved oxygen can drift. The specific growth rate μ therefore varies across lag, exponential, deceleration, and stationary phases. This question tests the basic temporal profile of μ in batch operation.
Given Data / Assumptions:
- No feed or bleed; volume is constant (ignoring evaporation, gas exchange).
- Substrate and oxygen are finite; products and acids/ethanol may accumulate.
- Physiology adapts from inoculation to stationary phase.
Concept / Approach:In lag, μ ≈ 0 while cells adapt. In exponential phase, μ ≈ μ_max if nutrients and O2 are abundant. As limitations and inhibition set in, μ declines. Finally, in stationary phase, net μ approaches 0 as growth balances death or ceases due to depletion/stress.
Step-by-Step Solution:
Lag: enzyme synthesis/adaptation; μ ~ 0.Exponential: μ approaches μ_max.Deceleration: μ falls as S or O2 limit and P accumulates.Stationary: μ ~ 0 (net).Verification / Alternative check:Typical growth curves of OD or dry cell weight show sigmoidal behavior consistent with changing μ.
Why Other Options Are Wrong:
- Constant μ: only holds during a portion of exponential growth.
- Unbounded exponential: violates resource limits.
- Highest in stationary: contradictory by definition.
- Instant drop to zero after inoculation: ignores exponential phase.
Common Pitfalls:Assuming a single μ fits the whole batch when modeling long runs.
Final Answer:It changes during the fermentation as conditions evolve.