Merge pull request #10 from ControlledMold/koji-temp-curve

Adding new Koji temperature post

Author: CamDavidsonPilon

_posts/2020-06-09-microbe-miso-yeast-algae.md

@@ -21,9 +21,17 @@ I had grown some kveik yeast for another, canceled project, so I decanted and pa
 
 I tried to flocculate them, but wasn't able to for some reason². So I instead took a "boil-the-ocean" approach and literally boiled the water away until I had a salty slurry (similar to my outcome [here](https://controlledmold.com/algae-as-a-plant-based-anchovy-flavour/)), about ~100mL. I added them to a bowl, along with ~200g of fresh barley koji and some salt (the algae media had lots of salt in it, so I didn't know how much additional salt to add. I added it "to taste"). Transferred it to a jar, and used the snap-lid plus some plastic lids to add pressure onto the miso. The initial taste was nice: an umami-rich, salty, fish/seaweed flavour. I'll update this post as I taste it over the next few weeks & months.
 
-
-![day 0 of product](/assets/images/microbe_miso/endsidebyside.jpg){: .center}
+![day 0 of product](/assets/images/microbe_miso/IMG_0331.jpeg){: .center}
 *Day 0 of yeast + algae miso*
+### 6 months later
+I didn't touch this miso much over the next 6 months. After opening it, it had a very unique taste: earthy, very sweet, and rich. It tasted like algae, but in a far and distinct way - hard to put my finger on it. Overall, a really tasty miso! 
+
+
+![day 180 of product](/assets/images/microbe_miso/endsidebyside.jpg){: .center}
+*Day 180 of yeast + algae miso*
+
+
+
 
 ¹ There wasn't a good reason to hydrolyze. I just did it for fun.
 

_posts/2020-11-25-building-a-bioreactor-part-3-tracking-growth-rates-in-real-time.md

@@ -48,7 +48,7 @@ $$\text{OD}_t = \text{OD}_0 \exp{(r_t\cdot t)}$$
 
  Note the subscript $t$ on the growth rate, $r$. This makes biological sense. Individuals cells, due to variation, will start to reproduce at different times, leading to an increasing population growth rate. Eventually, the growth rate will level off as all cells are actively reproducing (and, given a long enough time, the growth rate will creep up due to evolution). Now that we have a better mathematical model of our population, how can we estimate $r_t$?
 
-To solve this, we will use a Kalman Filter. A Kalman Filter is a algorithm used for *estimating* a *time-varying process* that contains an internal *dynamical system*. Let's break that down: *estimating* is the act of taking in noisy measurements and producing a more accurate result; *time-varying process* is an object that changes over time (in our case: both optical density and growth rate change over time); *dynamical system* is a model to describe the relationship between our variables: optical density and growth rate. I'd love to go into detail about how a Kalman Filter works, but for a computation-first-mathematics-second resource, I suggest the book I used: [Kalman and Bayesian Filters in Python](https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python). 
+To solve this, we will use a Kalman Filter. A Kalman Filter is an algorithm used for *estimating* a *time-varying process* that contains an internal *dynamical system*. Let's break that down: *estimating* is the act of taking in noisy measurements and producing a more accurate result; *time-varying process* is an object that changes over time (in our case: both optical density and growth rate change over time); *dynamical system* is a model to describe the relationship between our variables: optical density and growth rate. I'd love to go into detail about how a Kalman Filter works, but for a computation-first-mathematics-second resource, I suggest the book I used: [Kalman and Bayesian Filters in Python](https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python). 
 
 To start, we'll write down the variables we wish to estimate (these are called our state variables):