Beersmith 3 ph tool

[Silver_Is_Money]

i believe your software uses the same math whatever as bs3 hence why your so adamant that the software youve never tried is correct. im gonna give it a try and see if its also broken in the same way. ill report in the new thread and not reply to you here anymore. cheers

Beliefs and intuition make for very poor science.

Please be sure to select your base malts proper DI_pH range before attempting to compare MME to any programs that lack this vital feature.

 

[Silver_Is_Money]

i agree 100% brunwater works great and not to bother fixing something thats not broken. see you in the other thread. cheers

Martin has just recently reported having fixed it due to its having previously been broken. And he has modified it over the years, so just as for MME, the current release does not give quite the same output as for previous releases (as someone else is currently actively discussing on another thread). For you to presume that it has never been broken is rather naive.

OTOH, I see MME as a product in need of constant improvement, and I have been responding to improving it on a regular basis, but I would never imply that it may not similarly be discovered to be broken in some way within any of its releases. I will only work to make it better in regard to such feedback. But valid feedback must clearly be objective and unbiased, and not tainted with confirmation bias, or given from the perspective of one who bears a chip on his shoulder.

 

[Blazinlow86]

Martin has just recently reported having fixed it due to its having previously been broken. And he has modified it over the years, so just as for MME, the current release does not give quite the same output as for previous releases (as someone else is currently actively discussing on another thread). For you to presume that it has never been broken is rather naive.

i agree 100% brunwater works great and its even better to hear there still making improvments to this day. see you in the other thread. cheers

 

[Blazinlow86]

can a mod lock this now with the conclusion being **if** your having bs3 recommending too much acid that changing it 125% seems to be working for now. we are (myself included) beating a dead horse lol. cheers

 

[Bassman2003]

For the record. most of my APA talked about on this thread was with Rahr pale malt.

 

[Silver_Is_Money]

For the record. most of my APA talked about on this thread was with Rahr pale malt.

It would be interesting to see if BS3's accuracy increases greatly (minus the application of the 125% lactic acid strength kludge) with a switch to Munton's Maris Otter pale malt from Rahr pale malt. Rahr malt is often suspect of being rather on the acidic (low DI_pH) side. A.J. deLange has measured Munton's Maris Otter at as high as 5.84 DI_pH, and Kai Troester once measured it at 5.77 DI_pH.

Note: Per A.J., the Crisp brand of Maris Otter pale malt is more acidic than the Munton's brand.

 

[Big Monk]

Any discussion about Beersmith's pH tool should really be a discussion about Riffe's MpH calculator. That's what is being used behind the scenes.

 

[Silver_Is_Money]

Any discussion about Beersmith's pH tool should really be a discussion about Riffe's MpH calculator. That's what is being used behind the scenes.

And given the source, that should make it about as accurate as they come. But does it allow for the handling of differences in base malt DI_pH values?

 

[ajdelange]

Yes, and buffering values too but, if I understand what he is doing based on his description of it in his paper it won't accept data on the non-linearity of malt nor account for the non linearities of added acids nor that of bicarbonate (added or from alkalinity). It is simple to improve it so that it does and still not require an iterative solution. How to do that is described in a post in https://www.homebrewtalk.com/forum/...gnificance-of-mash-ph-estimates.654492/page-2

 

[Blazinlow86]

I asked this in another ph thread. I'm wondering if the reason so many have issues with bs3s tool is possibly the timing there taking there ph readings? It sounds like the model used is well recognized and should be pretty accurate. If brunwater/brewers friend/Mme etc all recommend within say .5ml of acid of each other there HAS to be a simple answer why beersmith recommends appx 3.5ml more than all the other software. Is anyone aware of a step by step tutorial on how the beersmith tool should be used? The threads I've read in regards to inaccurate ph with Brad responding have only stated why the ph tool software was chosen and he suggests that it's only a estimate (which I agree) and to add acid during the mash if it's off. It's just so far off from all the others that there has to be something we're missing and arguably having to add acid during the mash isn't really ideal (for that matter if bs is the odd man out the ph would be too low ) please understand. This is not a troll post. I really want to figure this out so I can use beersmith 3 exclusively. Cheers


P.s sorry for all the bad press Brad. I love your software but can't get the ph sorted out. I'm not trying to be a ass.

 

[dmr]

I asked this in another ph thread. I'm wondering if the reason so many have issues with bs3s tool is possibly the timing there taking there ph readings? It sounds like the model used is well recognized and should be pretty accurate. If brunwater/brewers friend/Mme etc all recommend within say .5ml of acid of each other there HAS to be a simple answer why beersmith recommends appx 3.5ml more than all the other software. Is anyone aware of a step by step tutorial on how the beersmith tool should be used? The threads I've read in regards to inaccurate ph with Brad responding have only stated why the ph tool software was chosen and he suggests that it's only a estimate (which I agree) and to add acid during the mash if it's off. It's just so far off from all the others that there has to be something we're missing and arguably having to add acid during the mash isn't really ideal (for that matter if bs is the odd man out the ph would be too low ) please understand. This is not a troll post. I really want to figure this out so I can use beersmith 3 exclusively. Cheers


P.s sorry for all the bad press Brad. I love your software but can't get the ph sorted out. I'm not trying to be a ass.

@Blazinlow86, I just found this thread. I believe I can shed some light on your observations.

The mash pH estimates used in Beer Smith (at least v2, if not also v3) are based on a couple of papers I wrote in 2013, which can be found on my blog (listed below in my signature). The papers report on my analysis of Kai Troesters work that he wrote up in his 2009 paper "The Effect of Brewing Water and Grist Composition on the pH of the Mash." I wrote these papers mostly for myself in an attempt to understand mash chemistry, which I was beginning to study at the time.

While I believe my analysis of Kai's data to be accurate, it did not go far enough in that I never tested it against real-world homebrewer mashes.

Personally, I used these equations to come up with my own pH calculator, MpH (v. 3.0 at present). Sometime in the past Brad Smith contacted me to ask if he could use my work to incorporate such calculations in bs. I said yes, and so that is where we are with all of that.

Here is the bottom line on the errors in acid additions: equation (6) in my second paper (... Mash pH II...) appears to overestimate the buffering capacity of a typical grist. Hence, the amount of acid required to hit a target pH is overestimated.

Consistent with your (and others) observations, recent preliminary analysis (of actual mash pH measurements) by me indicates the buffering capacity is overestimated by a factor of about 1.65. Thus the observation that changing concentration from 88% to about 140% -- 150% in the bs software (more-or-less) fixes this issue when working with bs.

Towards the end of nailing all of this down, I urge you to add your own data to the thread I recently started -- https://www.homebrewtalk.com/forum/threads/wanted-mash-ph-measurements.661544/ . As you can see there, I have asked that actual mash pH data be posted so that anyone interested in mash pH developing software has a chance of making it accurate.

Just in case you might be interested, I am currently updating MpH (although I have no idea when it will be ready for prime time). The underlying mathematical model will be entirely new (for MpH); it will be based on the water-chemistry ideas that A.J. deLange has discusses at length on this forum.

Cheers!

 

[ajdelange]

@Blazinlow86
Consistent with your (and others) observations, recent preliminary analysis (of actual mash pH measurements) by me indicates the buffering capacity is overestimated by a factor of about 1.65.

After correcting for this what sort of buffering numbers are you coming up with?

 

[Pappers_]

Thanks for the update, @dmr . I am following the other thread, also.

 

[Blazinlow86]

Thanks for the input. I've found using 70% of bs3 recommations seems to work pretty well. Cheers

 

[dmr]

After correcting for this what sort of buffering numbers are you coming up with?

A question that gets right to the heart of things. Good!

Let me explain my overall procedure before I throw out any numbers. Anyone that has read my recent paper (with Mick Spencer -- ... Mash pH III ...) will know that we (i) made some measurements on distilled-water mash pH values and relative buffering capacities of a number of malts and flaked grains and (ii) we collated all the data we could find on these two quantities. Perhaps the most important thing we found was that there are significant systematic differences (I won't call them errors, as I do not think these differences exactly rise to the level of errors) among each researcher when it came to the buffering capacities of Briess Caramel Malts. In the paper we discuss various possibilities for the differences, but that is not important here. What is important is that we were able to do a good job of normalizing the buffering capacities of these malts by applying a single multiplicative factor to the data from each researcher. Confirmation that such systematic difference existed was the result that the adjusted buffering capacities of dark roasted malts fell much more in line among the researchers, even though the data from these malts were not used in the normalization process. BTW, we assumed a normalizing factor of 1.00 for the A.J. deLange data. The other multiplicative factors varied substantially -- from 0.86 (Walts data) to 1.62 (data of Kai Troester).

The importance of these findings are twofold. First, it is difficult, if not impossible, to assign an absolute buffering-capacity to a given malt, as the measured value appears to depend upon (as of yet unknown) differences in measuring techniques. Second, one cannot really know what the appropriate multiplicative factor is in a homebrew setting unless one has actual homebrew-setting data (thus the thread I recently started). Indeed, the exact multiplicative factor might very well be somewhat different from homebrewer to homebrewer.

Along these lines I'll mention that Kai Troester's data in his (in)famous 2009 paper show that crushed grains have an effective buffering capacity that is significantly less that that of pulverized grains.

With all that said, I currently find (based on the homebrewing data that has been posted on the recent thread) that a multiplicative factor of about 0.6 applied to the normalized values in the tables in my recent paper give the overall best agreement with the measured data. So for example, this would give an average buffering capacity of 27.3 for malt in the Pils/Lager/2-Row category. [BTW, my current comparison uses all of the water-chemistry science that you, Mr. deLange, have been arguing for in the forums for quite sometime. Charge must be conserved! I do choose, though, to assume a linear model of buffering (as described in my paper).]

I will say that I have identified one potential pitfall to assuming that a normalization factor is the whole story: perhaps there is a significant difference in distilled-water pH between pulverized and crush grain. I hope that Mick Spencer and I can experimentally address this.

Lastly, I'll say that all science is based on observation (clearly this is the physicist in me speaking here). To argue the benefits of any one mash-pH calculator over another without comparison to actual data (as is rife in this beer science forum) is folly at best. It can be amusing, though.

So there we go. A.J., if you have issue or questions with any of this, I'd certainly like to hear your thoughts. I'm more than happy to engage in a scientific discussion. Cheers!

 

[Big Monk]

Lastly, I'll say that all science is based on observation (clearly this is the physicist in me speaking here). To argue the benefits of any one mash-pH calculator over another without comparison to actual data (as is rife in this beer science forum) is folly at best. It can be amusing, though.

This is the key takeaway.

One of the reasons I’ve latched onto the charge conservation method is because the basis is very sound. Finding the right way to apply it in a user interface is a work in progress but I’m putting my chips down on the model I believe in.

 

[Silver_Is_Money]

A question that gets right to the heart of things. Good!

Let me explain my overall procedure before I throw out any numbers. Anyone that has read my recent paper (with Mick Spencer -- ... Mash pH III ...) will know that we (i) made some measurements on distilled-water mash pH values and relative buffering capacities of a number of malts and flaked grains and (ii) we collated all the data we could find on these two quantities. Perhaps the most important thing we found was that there are significant systematic differences (I won't call them errors, as I do not think these differences exactly rise to the level of errors) among each researcher when it came to the buffering capacities of Briess Caramel Malts. In the paper we discuss various possibilities for the differences, but that is not important here. What is important is that we were able to do a good job of normalizing the buffering capacities of these malts by applying a single multiplicative factor to the data from each researcher. Confirmation that such systematic difference existed was the result that the adjusted buffering capacities of dark roasted malts fell much more in line among the researchers, even though the data from these malts were not used in the normalization process. BTW, we assumed a normalizing factor of 1.00 for the A.J. deLange data. The other multiplicative factors varied substantially -- from 0.86 (Walts data) to 1.62 (data of Kai Troester).

The importance of these findings are twofold. First, it is difficult, if not impossible, to assign an absolute buffering-capacity to a given malt, as the measured value appears to depend upon (as of yet unknown) differences in measuring techniques. Second, one cannot really know what the appropriate multiplicative factor is in a homebrew setting unless one has actual homebrew-setting data (thus the thread I recently started). Indeed, the exact multiplicative factor might very well be somewhat different from homebrewer to homebrewer.

Along these lines I'll mention that Kai Troester's data in his (in)famous 2009 paper show that crushed grains have an effective buffering capacity that is significantly less that that of pulverized grains.

With all that said, I currently find (based on the homebrewing data that has been posted on the recent thread) that a multiplicative factor of about 0.6 applied to the normalized values in the tables in my recent paper give the overall best agreement with the measured data. So for example, this would give an average buffering capacity of 27.3 for malt in the Pils/Lager/2-Row category. [BTW, my current comparison uses all of the water-chemistry science that you, Mr. deLange, have been arguing for in the forums for quite sometime. Charge must be conserved! I do choose, though, to assume a linear model of buffering (as described in my paper).]

I will say that I have identified one potential pitfall to assuming that a normalization factor is the whole story: perhaps there is a significant difference in distilled-water pH between pulverized and crush grain. I hope that Mick Spencer and I can experimentally address this.

Lastly, I'll say that all science is based on observation (clearly this is the physicist in me speaking here). To argue the benefits of any one mash-pH calculator over another without comparison to actual data (as is rife in this beer science forum) is folly at best. It can be amusing, though.

So there we go. A.J., if you have issue or questions with any of this, I'd certainly like to hear your thoughts. I'm more than happy to engage in a scientific discussion. Cheers!

If a multiplicative factor of 0.60 is now recommended to be applied to averaged buffering values derived from titrations, and titration data derived from one source to another require admittedly wild swings in multiplicative factors since they "vary substantially", and if the AJ data is merely "assumed" to be the correct data, and the entire premise of Gen II is that mash pH prediction error is to be eliminated by careful titration and DI pH measurement, yet a clearly data normalizing fudge factor altering the average of actual measured values by 40% is called for, what does that say for the validity of the foundational premise of Gen II, and the promise of a precision in mash pH prediction that will be unquestionably better than Gen I and/or quasi-empirical models (which can be similarly massaged via fudge factors if/as needed in order to bring them in line with real world mash pH measurement)?

Edit: I applaud you for your honesty in this matter of uncertainty. Your statement that "it is difficult, if not impossible, to assign an absolute buffering-capacity to a given malt, as the measured value appears to depend upon (as of yet unknown) differences in measuring techniques." should serve as a brief synopsis of what I'm saying above. As should "The other multiplicative factors varied substantially -- from 0.86 (Walts data) to 1.62 (data of Kai Troester)." Substantially indeed!!! What sort of R squared correlation might be seen in such massively uncorrelating data sets (before they are heavily massaged post arbitrarily merely presuming that AJ is chosen to be the only one among them who is correct)?

 

[murphyslaw]

@dmr , thanks for the explanation. Have you been in touch with Brad Smith? It would be great to see a fix in Beersmith.

 

[eric19312]

Cool stuff here. Sounds like we need to add crush detail to the real world mash pH data thread. I’m amazed you guys can’t get agreement on the DI pH results and makes me wonder if universal predictive model is even possible in real world homebrew setting. Maybe we need a pretty good model and a way to determine a system based correction factor.

 

[Big Monk]

If a multiplicative factor of 0.60 is now recommended to be applied to averaged buffering values derived from titrations, and titration data derived from one source to another require admittedly wild swings in multiplicative factors since they "vary substantially", and if the AJ data is merely "assumed" to be the correct data, and the entire premise of Gen II is that mash pH prediction error is to be eliminated by careful titration and DI pH measurement, yet a clearly data normalizing fudge factor altering the average of actual measured values by 40% is called for, what does that say for the validity of the foundational premise of Gen II, and the promise of a precision in mash pH prediction that will be unquestionably better than Gen I and/or quasi-empirical models (which can be similarly massaged via fudge factors if/as needed in order to bring them in line with real world mash pH measurement)?

Edit: I applaud you for your honesty in this matter of uncertainty. Your statement that "it is difficult, if not impossible, to assign an absolute buffering-capacity to a given malt, as the measured value appears to depend upon (as of yet unknown) differences in measuring techniques." should serve as a brief synopsis of what I'm saying above. As should "The other multiplicative factors varied substantially -- from 0.86 (Walts data) to 1.62 (data of Kai Troester)." Substantially indeed!!! What sort of R squared correlation might be seen in such massively uncorrelating data sets (before they are heavily massaged post arbitrarily merely presuming that AJ is chosen to be the only one among them who is correct)?

In my opinion, it isn't about who is right or who is wrong. It's about understanding how the science translates to the brewery and how we can apply that chemistry so everyone can use it.

Titration co-efficiencts are currently the stick in the mud. We can get good DI pH data very easily. We have a good amount of data for a1, a little less for a2, and a little less still for a3. We may not be entirely sure of the veracity of all the measured data or how we can apply it so peoples eyes don't glaze over.

We need more data to understand how to improve things. If we understand more about how these things work, we all win.

 

[Silver_Is_Money]

With all that said, I currently find (based on the homebrewing data that has been posted on the recent thread) that a multiplicative factor of about 0.6 applied to the normalized values in the tables in my recent paper give the overall best agreement with the measured data. So for example, this would give an average buffering capacity of 27.3 for malt in the Pils/Lager/2-Row category. [BTW, my current comparison uses all of the water-chemistry science that you, Mr. deLange, have been arguing for in the forums for quite sometime. Charge must be conserved! I do choose, though, to assume a linear model of buffering (as described in my paper).]

@dmr, does this x0.60 factor apply to all of the buffering capacities found in your recent paper?

 

[Big Monk]

I do choose, though, to assume a linear model of buffering (as described in my paper).

The only place I can see this getting you into the weeds would be for more acidic (cara, roast, Sauermalz) malts, where assuming a linear buffering around:

dQ = a1 * (pHz - pH DI)

instead of:

dQ = a1 * (pHz - pH DI) + a2 * (pHz - pH DI) ^ 2 + a3 * (pHz - pH DI) ^ 3 + an * (pHz - pH DI) ^ n

Might predict lower than actual pHz (desired pH) values. My frame of reference here is my recent experience using the new algorithm with a simple grain bill and Sauermalz using the following parameters:

pHz = 5.4 pH DI = 3.50, a1 = -319.01, a2 = 68.94, a3 = -5.40

The linear approach gives:

dQSauermalz = -608.17

where as the full polynomial gives:

dQSauermalz = -395.03

The same would occur, to a lesser degree, for cara and roasted malts. Granted, this assumes we have either measured titration data for a 3 term solution, or at least an educated amalgamation of measured data, but the concern still stands.

 

[dmr]

@dmr, does this x0.60 factor apply to all of the buffering capacities found in your recent paper?

I need to emphasize this factor of 0.6 is only a preliminary estimate, based on homebrewers' mash pH data that have so far been posted (and that I have analyzed).

Furthermore, the data that are available certainly do not allow one to try to discern a different factor for different types of malt. I doubt that such data will ever provide such distinction.

 

[dmr]

The only place I can see this getting you into the weeds would be for more acidic (cara, roast, Sauermalz) malts, where assuming a linear buffering around:

dQ = a1 * (pHz - pH DI)

instead of:

dQ = a1 * (pHz - pH DI) + a2 * (pHz - pH DI) ^ 2 + a3 * (pHz - pH DI) ^ 3 + an * (pHz - pH DI) ^ n

Might predict lower than actual pHz (desired pH) values. My frame of reference here is my recent experience using the new algorithm with a simple grain bill and Sauermalz using the following parameters:

pHz = 5.4 pH DI = 3.50, a1 = -319.01, a2 = 68.94, a3 = -5.40

The linear approach gives:

dQSauermalz = -608.17

where as the full polynomial gives:

dQSauermalz = -395.03

The same would occur, to a lesser degree, for cara and roasted malts. Granted, this assumes we have either measured titration data for a 3 term solution, or at least an educated amalgamation of measured data, but the concern still stands.

I must respectfully disagree, at least with regards to dark roasted malts. As Fig. 1 in my latest paper shows, even though Briess roasted malt (e.g.) exhibits some nonlinearity in its acidity, once can fit this acidity data with a straight line and get a fit that is not appreciably different than the data. I should emphasize that such a linear fit gives a fitting parameter that is not the same as the linear-term parameter one obtains when one fits the data with a higher-order polynomial. In other words, I am not suggesting (nor have I ever suggested) that one can simply use a1 (ignoring a2, a3, etc.) that has been obtained from a higher-order fit.

As far a Sauermalz goes, I believe it is best to simply treat it as a source of lactic acid (which it is), rather than as a malt.

 

[Silver_Is_Money]

I need to emphasize this factor of 0.6 is only a preliminary estimate, based on homebrewers' mash pH data that have so far been posted (and that I have analyzed).

Furthermore, the data that are available certainly do not allow one to try to discern a different factor for different types of malt. I doubt that such data will ever provide such distinction.

Thank you! From this can it be assumed that with the buffering capacity of all malts and grains reduced, they will exhibit lower mash pH's in your upcoming version 4, such as their ability to resist pH changes is noticeably diminished by this factor?

 

[Big Monk]

In other words, I am not suggesting (nor have I ever suggested) that one can simply use a1 (ignoring a2, a3, etc.) that has been obtained from a higher-order fit.

I'll concede that for A.J.'s measurement of Roasted Barley, the difference in mEq/kg is only 5. So in that specific case, it's not a good example. Also, we'd have to agree that 300L roasted barley was a "dark" roasted malt.

In other cases, however, I guess I wonder how this differs. If you measure a1 for a specific grain (like you did in your paper, which I think is great BTW) and use it in:

dQMalt = a1 * (pHz - pH DI)

how is that any different than having measured a2 and a3 as well and just disregarded them? Whether you measure a2 and a3 or not, the malt still has those values. Isn't approximating dQMalt for a specific malt with only a linear approximation of it's full acidity going to introduce error in more acidic malts?

For instance, If I take the data from A.J.'s measurement of Crisp Chocolate:

pH DI = 4.70, a1 = -76.43, a2 = -0.40, a3 = -3.84

and plug and chug for pHz = 5.40:

Linear dQMalt = ~ -155 mEq/kg

Poly dQMalt = ~ -27 mEq/kg

That's certainly not a small difference.

As far a Sauermalz goes, I believe it is best to simply treat it as a source of lactic acid (which it is), rather than as a malt.

Here is where we get into more trouble though. Sauermalz is a malt treated with biological acid, i.e. Sauergut, and really can't be treated with any degree of accuracy as a straight source of Lactic Acid by weight. We can't even treat Sauergut as an equivalent to Lactic Acid, so how can we reliably do it for Sauermalz?

I use Sauermalz eclusively as my acidifying agent ("Agent of Acidfication" would be an awesome brewing superhero!) and for batches using Brun Water, My old sheet, and MpH, I have never had a time where I didn't have to alter the acid % or strength modifier in Brun Water significantly to match values in the field. Strictly speaking, I have never used the nominal percentages quoted by some for Sauermalz.

I believe the chart I have seen from A.J. with the Lactic and Sauermalz overlayed, only shows coincidence at one specific pH.

And again, we have valuable titration data measured for Sauermalz, so why wouldn't we use it? Certainly it's better than estimating it's acidity based on something that it isn't, no? Granted, it may not be perfect, but it seems a step in a better direction.

I just want to state that I am not trying to antagonize you at all. I am a curious about all these things and actively looking into figuring them out. I appreciate your papers and work.

I am disagreeing with you in the best and most productive terms because i want to know these things and how they work.

Cheers!

 

[dmr]

Thank you! From this can it be assumed that with the buffering capacity of all malts and grains reduced, they will exhibit lower mash pH's in your upcoming version 4, such as their ability to resist pH changes is noticeably diminished by this factor?

Indeed, that is likely to be the case (in situations where the brewer adds acids and/or significant amounts of Ca and/or Mg). It may be a while before the next version makes an appearance, as I am hoping to get more data to analyze. Plus I'll need to carefully check all of my calculations (I believe they are accurate, but one can never be too careful). Plus I don't have gobs of time to devote to this. Cheers!

 

[dmr]

I'll concede that for A.J.'s measurement of Roasted Barley, the difference in mEq/kg is only 5. So in that specific case, it's not a good example. Also, we'd have to agree that 300L roasted barley was a "dark" roasted malt.

As Briess Roasted Barley has pH_i and B_i values that are very much like other dark roasted malts, I believe we can safely treat it as such.

In other cases, however, I guess I wonder how this differs. If you measure a1 for a specific grain (like you did in your paper, which I think is great BTW) and use it in:

dQMalt = a1 * (pHz - pH DI)

how is that any different than having measured a2 and a3 as well and just disregarded them? Whether you measure a2 and a3 or not, the malt still has those values.

I guess I was not very clear. Think of it this way. If we fit a section of nonlinear data with a linear function, then we will extract a two coefficients: a_0 and a_1. If we now fit that section of the same data with a quadratic function, we shall obtain three coefficients: a_0, a_1, and a_2. However, the fitted values of a_0 and a_1 will (very likely) not be the same in the two cases.

If the fitted data is not too far from linear, then the linear fit will be a very good approximation to the actual curve. Conversely, if I try to describe the data using the linear function built from a_0 and a_1 that were obtained from the quadratic fit, then I would not expect this linear function to be a very good approximation to the actual data (as you have pointed out).

Excluding the analysis of our own data, the values of pH_i and B_i reported in my latest paper were obtained by using a linear function to fit the titration data that I could find in the literature. In the case of AJ deLange's "data" I did a linear fit to "data" that I reconstructed from AJ's pH_i and three reported coefficients (a_1, a_2, a_3). In my analysis I find that a linear approximation is a very good approximation to all titration data (for pH values between the malt's pH_i value and a pH of 5.4).

I'll certainly concede that a linear fit may not be a sufficient approximation in all cases, but I've yet to see titration data (between pH_i and a pH of 5.4) where this is not the case.

More generally, any fitting coefficients (a_0, a_1, ...) are a function of the data, the range (along the x axis) over which the data are fit, and the exact model being used (linear, quadratic, cubic, ...). The coefficients cannot be thought of as simply a property of the data itself.

Here is where we get into more trouble though. Sauermalz is a malt treated with biological acid, i.e. Sauergut, and really can't be treated with any degree of accuracy as a straight source of Lactic Acid by weight. We can't even treat Sauergut as an equivalent to Lactic Acid, so how can we reliably do it for Sauermalz?

I use Sauermalz eclusively as my acidifying agent ("Agent of Acidfication" would be an awesome brewing superhero!) and for batches using Brun Water, My old sheet, and MpH, I have never had a time where I didn't have to alter the acid % or strength modifier in Brun Water significantly to match values in the field. Strictly speaking, I have never used the nominal percentages quoted by some for Sauermalz.

I believe the chart I have seen from A.J. with the Lactic and Sauermalz overlayed, only shows coincidence at one specific pH.

I'm potentially convinced that one cannot treat Sauermalz as a source of lactic acid. I'd love to see AJ's titration data. Where can I get a copy of this?

Cheers!

 

[Big Monk]

As Briess Roasted Barley has pH_i and B_i values that are very much like other dark roasted malts, I believe we can safely treat it as such.



I guess I was not very clear. Think of it this way. If we fit a section of nonlinear data with a linear function, then we will extract a two coefficients: a_0 and a_1. If we now fit that section of the same data with a quadratic function, we shall obtain three coefficients: a_0, a_1, and a_2. However, the fitted values of a_0 and a_1 will (very likely) not be the same in the two cases.

If the fitted data is not too far from linear, then the linear fit will be a very good approximation to the actual curve. Conversely, if I try to describe the data using the linear function built from a_0 and a_1 that were obtained from the quadratic fit, then I would not expect this linear function to be a very good approximation to the actual data (as you have pointed out).

Excluding the analysis of our own data, the values of pH_i and B_i reported in my latest paper were obtained by using a linear function to fit the titration data that I could find in the literature. In the case of AJ deLange's "data" I did a linear fit to "data" that I reconstructed from AJ's pH_i and three reported coefficients (a_1, a_2, a_3). In my analysis I find that



I'm potentially convinced that one cannot treat Sauermalz as a source of lactic acid. I'd love to see AJ's titration data. Where can I get a copy of this?

Cheers!

Don’t you have his data? What did you use for your paper?

 

[dmr]

Don’t you have his data? What did you use for your paper?

AJ's data? No I do not have it; I simply reconstructed an approximation to his data using the cubic fits (pH_i, a_0, a_1, a_2) that AJ has posted on this forum.

Do you have his data? Is it available somewhere?