Sunday, October 11, 2020

see, that's the weird thing about trump - he may suppress his own vote, something that is almost unique on the right of the spectrum.

we usually talk about republicans suppressing the vote on the left, and how republicans see their chances go up when disgruntled liberals don't bother voting.

this election, biden's best chance in the south is probably republicans choosing to staying home. and, they very well might.
if you look at the charts, they may look like like this:


but, what's actually happening is more like this:


and, that may not sustain itself, in the end.

i'll post a final analysis closer to the election.
so, what's actually going on with the polling in weakly red states like arizona, ohio and north carolina? if you sort through the list, you'll find the odd poll that has trump winning in relatively blue states, too, but this cycle is a little different, because the numbers are actually fairly consistent in some of these places. is biden actually winning in these places, then? is that serious?

the right answer is that it's tricky, but i need to point to a factor that the poll aggregates are not designed to take account of, and that's the undecided vote. i frequently root my criticism in polling in how it treats undecideds, so this should sound familiar if you've been listening in over a long period.

so, if you sort through the polling in ohio, for example, you'll see that the numbers are pretty consistent for biden - he's very close to 45%, across the board, in poll after poll. by contrast, trump's support modulates wildly from the low to high 40s. and, the data is not that different in these other places, either.

i'm used to analyzing this in canada, where the conservatives numbers just simply don't change, and polling is often distorted by ignoring undecideds. a frequent thing that happens in canada is that liberal supporters move to the undecided column in large percentages, which inflates support for the conservative party. so, you end up thinking conservative support is up, when the truth is that the sample just got distorted, because they removed the undecideds from the tally. when you put the undecideds back in, you always reconstruct that stagnant conservative support level. that means that the reality is that, in canada, the liberals are often their own most powerful opponent - they lose more support to themselves than they do to any other party,

in the united states, the republicans are the default, and you're sort of seeing something similar with trump. just because republicans don't like trump doesn't mean they'll actually vote for biden - they're still republicans, remember. they might stay home, or they might relent at the last minute. but, what i'm seeing suggests is that there's a fairly large group of people - more than 5% - that are struggling with their decision, right now. they're having a hard time telling pollsters they're going to vote for trump, but they don't seem to want to vote for biden, either. this is consistent with the broader data that suggests that there's a substantial amount of the republican base that doesn't seem to like donald trump because he's too liberal, something we've more often seen on the other side of the spectrum recently (democrats that think the nominee is too conservative) and that works itself out in canada with perennially disgruntled liberals that are pissed off that the party won't do what they say but that don't like the other parties much, either. they're coming in right now as undecided, but what that means in the american spectrum is "disenfranchised republican that doesn't know what to do" - just as it means "irritated liberal that doesn't feel they have a good choice" in the canadian spectrum.

so, it's hard to say.

is that what happened in 2016? in a word: no. what i'll say is that we saw something like this in some of these places very early in 2016, but it corrected itself quickly. that is, finicky republicans that didn't like trump only needed a small dose of hillary clinton before they came bolting back home - like a yappy dog given the option to run away. the party won that game of chicken, four years ago. the data is more persistent, this cycle, but the fact that they're still not picking biden is suggestive that they're perhaps not likely to, in the end.

what it means when you're reading the polls in the red states (the sunbelt states), you need to ask the question: is biden actually up or is trump just way down? if the latter, those polls may be misleading, in the end, as the undecided republicans start to come back. but, they're running out of time; conversely, if biden starts ticking up in these states, then trump's chances to win back wandering conservative republicans begin to find.

the caveat is florida, and that has to do with the fact that trump is increasingly losing seniors, which is making florida more like the great lakes states than the sun belt states, this cycle. in the great lakes states, the swing vote is traditionally democratic, and far more liberal than in most of the country. its also very old and very white. again - i don't think it's rational, but older white voters in the great lakes are leaning more towards biden than trump, and that is why biden is winning these states. the same thing is happening in florida. so, you may, oddly, see florida vote with wisconsin this cycle - and that may be decisive.

but, i need to continue to pencil in trump as having an advantage in these sun belt states until i see biden's numbers explicitly go up, rather than watch trump's numbers slowly tick down - and i need to argue that aggregate polling that gives biden an advantage as a consequence of these types of polling results is misleading, and likely in error.
ok, i'm actually going to start with some portion control first, and this is to make sure i can actually eat it all, on a regular basis.

1) i don't need two bananas after all, due to closer computations, and the boost in yeast. that shaves off 100 calories. but, i'm recalculating the single banana to the large size, as that one i lowballed with seems to have been an outlier, after measuring them since then - every other banana has been in the 136+ range, most over 140.
2) i appear to be able to nearly halve the amount of pasta, in favour of a small boost in yeast and have it balance out. i need it at 55 g for the b3. so, that takes out nearly 200 more calories.
3) i'm going to leave the cheese with the eggs alone for now, but it seems like it's empty calories, right now. i may increase the amount of cheese in the pasta bowl to get it over 35%, instead. that could cut out another 100 calories.

remember - i want the breakfast at roughly 1000 and the other two at roughly 500, so it's roughly 2000 altogether.

my previous daily amount had about 600 for breakfast and was about the same for the other two, meaning it was around 1300-1400. and, i'd often skip meals because i wasn't hungry...

so, yeah - i'm increasing my calorie count; i was malnourished, i wasn't getting enough vitamins. but, the question of if i need two or three meals remains open, and i may in the end alternate between eggs and pasta, rather than eat them both every day. ideally, that would put me back closer to 1500/day. but, i wanted to gain a little weight to fill my figure out a bit...not too much, just a bit...

i will fill calories in in the end; the only reason i'm adjusting this now is because i am actually eating daily, remember.

if you want some kind of bounds around this, you could look at the following site:

while i'm using data for men regarding vitamin intake (i actually think it's sexist to tell women they need less vitamins. i guess they don't want to bother their little heads, right? vitamins regulate brain chemistry, energy expenditure, etc. how is that gender-specific? with the caveat that pregnant women are eating for two, there's no reason at all to set different targets based on gender.), i actually don't know what the better numbers to use for calories are. the reason these numbers are different is probably really just because men are expected to build larger muscle stores than women, who are expected to be skinny. but, that's not biology, it's a social construct. if you're an active woman that wants to bulk up, you should potentially be looking at the male numbers; conversely, if you're an effeminate male that would rather have a petite physique, you may want to look at the female numbers. don't buy into heteronormative bullshit when you're doing calorie counts - there's no science underlying that, it's just gender norms and social expectations.

for me, the confusion is that i'm a genetic male (xy) that is estrogen-dominant due to hormone therapy. so, that is very confusing for a chart, like this. the estrogen should be the dominant factor, so i should be looking more at the female numbers (as opposed to vitamin counts, where i want my brain to work as well as any cis-male, thanks). but, i want to be a little bit cautious that i don't under do it, too. 

in the end, i'll probably aim for something like a middle point - and i would consider myself more moderately active than heavily active, given that my lifestyle is really that i do heavy exercise infrequently. so, according to that chart, my aim would be around 2300, maybe a tad higher, if i take the middle point between men and women at my age range (31-50) and activity level (moderately active). that's roughly where i am, so taking it down further would mean i'm consuming less calories than is recommended.

what i want is a maximization process - i want to get the most vitamins with the least calories. but, i want the most vitamins, first and foremost.

for now, those are the three changes - i'm cutting pasta to 55 g & boosting yeast to 3 g in the pasta bowl, and i'm replacing two 118 g bananas with one 136 g one.

vitamin a

banana:
- now at 4.08 μg

so, 4.08 + 0.75+ 10.5 + 3 = 
18.33/900 = 2%

there's no change, there,

pasta: 
55*(.5/24) = 1.14583333333 μg 
[note that i should have multipled by 100 the first time, so this actually goes up]

then, 918 + 314 + 1.14583333333 = 1233.14583333
& 1233.14583333/900 = 137%, still.

hrmnn. maybe, it's a good time to double check everything, as i'm recalculating line-by-line.

yeast is still 0.

vitamin b1

banana is now in at .042.

so, 

(.042+.018+.1+.02025+.0528+.115)/1.2 = 29%
further, 8 + 155 + 20 + 29 = 212.
so, the fruit bowl comes down 2.5% on b1. that's fine.

pasta:
71*55/85 = 45.9411764706----->46%

yeast numbers were already recalculated for the fruit bowl:
155%

then, 27 + 46 + 155 = 228%

so, that's actually a boost of 14%, via a source that has higher bioavailability and less calories.

in total,
212+228+119+11=570, and that's a boost of 11.5%. so, that's a good sub...

vitamin b2

banana is now at .099.

so,

(.099+.0165+.195+.01875+.253+.011)/1.3 =
0.45634615384--->45.5%

then,
45.5+25+144+24=238.5%

that's down about 3.5% - again, fairly minor.

pasta:
55*35/85 = 22.6470588235 ---> 22.5%

yeast--->144%

so, 40+144+22.5 = 206.5%

again, that's a fairly hefty increase.

in total,
238.5 + 206.5 + 161.5 + 51.5 = 658

note that the b2 totals were previously off by 1, somewhere. so, i'm up 26%, despite it naively reading off as being 25%. again, we're doing well with this.

vitamin b3

banana is now at .904, so:
(.904 + 0.2895 + 2.61 + 0.25575 + 0.1276 + 0.216)/16 = 
0.275178125 = 27.5%

so,
27.5 + 10 + 65 + 36 = 138.5

pasta:
56*(55/85) = 36.2352941176 = 36%

yeast--->65%

first,
f: 36 + 65 = 101

then, 101 + 25 = 126.

this is down slightly, 8%, but still above the requirements, and above my thresholds. i don't need 200 calories for an excessive 8% of the rdi of niacin.

in total,
138.5+126+50.5+12.5 = 327.5, which is down 12% but still above everything. that's fine, i think.

vitamin b4

bananas are now:
1.2*1.36 = 1.632

so,
(1.632 + .375 + 15.9 + .339 + 19.25 + .9735 + 49.38)/75 = 87.8495/75 = 117%

that's down 1.5%, but that's ok.

pasta:
.55*4 = 2.2

yeast--->49.38

then,
(31.8+2.2+4.92+.77+49.38)/75 = 89.07/75 = 119%

that's a boost of 20%, from the yeast.

and, in total, 117+119+56+10 = 302, an 18.5% boost that gets me up into the blue.

vitamin b5

b5 is always the problem in a vegetarian diet because they don't fortify anything with it (and clearly should).

bananas now come in at .454, which means i can now get to the following total for the unlisted part of the  breakfast meal:
(0.454 + 0.09375 + 2.08 + .13725 + .6391 + .069)/5 =
3.4731/5 = 0.69462 = 69%

that takes me down 7%. and, in total, i get:

69 + 15 + 2.25 + 19 = 105.25--->105%, but not it's close to 106%.

this brings up a point i've brought up a few times - these numbers are all approximate. so, what do i do, now? do i hang on to a second large banana for 7% of the rdi of a vitamin who's daily needs are really unknown?

i'm going to lower my requirements to 100% of the  rdi for now - but remind you that i haven't weighed the strawberries yet, and have been toying with boosting the soy milk to 300 ml from the start.

pasta: 
.55*.431 = 0.23705 

so,
(.634 + 0.23705 + .246 + .3003 + .056)/5 = 1.47335/5 = 0.29467--->29%

this is down 4% (almost 3.5%), but i need a major source, regardless.

yeast---->2.25%

so,
29 + 2.25 = 31.25%--->31%. so, i'm down 3.5 (and rounded way down) instead of 4, but it doesn't matter - i need a better source.

in total, 
105 + 31 + 54.5 + 42 = 232.5%, down 10.5%. b5 is different because the yeast doesn't offset it. i need a source, regardless, so i'm not going to worry about it - for now.

vitamin b6

bananas are in at .499. so,

(.499+.03525+.386+.04725+.0528+.033)/2 = 1.0533/2 = 0.52665--->52.5%

that's down 18.5%, but i'm overshooting quite a bit as it is.

52.5 + 6 + 133 + 25 = 216.5%, then.

pasta:
.55*.142 = 0.0781

(0.582 + .0781 + 0.0396 +0.1518 + 0.06)/2 = 
0.9115/2 = 0.45575 = 45.5%

that's down 3%, but the yeast can compensate:

yeast--->133%

so,

45.5 + 133 = 178.5%,

which is a gain of 45%. 45-3-18.5 = 23.5%. so, this is a good sub...

in total, 

216.5+178.5+105+2 = 502%

vitamin b7

bananas:
3.07*(136/130) = 3.21169230769

then,
(3.21169230769 + 0.82291666666 + 5.4 + 10.0693333333  + 2.86)/35 =
0.63896978021 ----> 64%

that's down 6.5%, but i'm doing fine, still.

64+45+86 = 195%

pasta:
2*.20*.5 = 0.2

(6.6 + .2 + 1.038 + 5.5 + 2.73)/35
16.068/35 = 0.45908571428---->46%

so, the difference is minor.

yeast--->45%

so, 45 + 46 = 91, which is an increase of 14.5%.

in total, 

195 + 91 + 214 + 11 = 511, which is an 8% increase.

so, everything went up, then - except b3 & b5 - and nothing is really altered, except calories.

the next thing i'll want to look at is if i can decrease the cereal amount, and i think i can take it down to 75%. i just want to get the numbers in first.

pseudo-b8, soon.

disclaimer:
i've gone to town with a few things - i'm not making up vitamins but rather filling things in. i mean, there's all these "missing vitamin names". what were they, exactly? it also gives me an excuse to work in a few things like choline that are hard to otherwise define as they are essential in some amount but not technically vitamins.

note that these numbers are scavenged and should be interpreted approximately. that's partly why i'm aiming to overshoot on most of it.

fruit bowl
(08:00)
pasta salad bowl
(00:00)
fried eggs
(16:00)
coffee
ban
ana

1
136 g
straw
ber
ies

5-6
75 g
avo
cado

2*
75 g
kiwi
1
75 g
soy
milk

250 ml
cher
ry
ice
cre
am

200 ml
nut.
ye
ast

 1
med
tsp
3
g
fort
cer
eal

55 g
grd
flax
seed

1
tbsp
(7 g)
sum red
pep
per
1
200 g
dur
um
wht
fet
55 g
+
h20
med
ched
chse
60 g
car
rot

110 g
hul
led
hemp
seed
1
tbsp
10 g
dre
ssi
ng
nut.
ye
ast
1
med
tsp
3
g
sum fried
eggs
2*70g
med
ched
cheese
30 g
marg.
2 tbsp
whole
wheat
bread
with
germ
+
flax  
(1
slice)
(37 g)
nut.
yeast

small
tsp
2
g
juice
type
250
ml
sum brew
coffee
700
ml
soy
choc
100
ml
sum total
raison 
d'etre
b5
b9
b16
c
b16
b3,4
b5,7
b9,
o-6
k,b16
b5,9
c
k,b16
a,d
b3,4
b5,7
a
b5
b1,2
b3,4
b6
b7
a,e
b3
b5
b7
o-3
b16

b3,4
c
b3  a
a
b3
b3
o-3

b1,2
b3,4
b6

a
b2,7
 
a,d,e
b7
o-3 b2 c
caf
feine

a
(fat sol)
(900 μg rae)
4.08
μg
 
.75
μg
10.5
μg
3
μg
10
%
13
%
0 15
%
0 40
r:38
c:2
314 
μg
1.04
μg 
30
%
918
μg
0 - 0 167
r:30
c:137
r:29
c:6.9
μg
15
%
10
%
0 0- 55
r:54
c:1
0 4
%

4
r:4
c:0
266
r:126
c:140
b1
thiamin
(1.2 mg)
.042
mg
.018
mg
0.1
mg
.02025
mg
8
%
.0528
mg
155
%
20
%
.115
mg
212
u:29
.108
mg
46
%
.0174
mg
.0726
mg
.1275
mg
- 155
%
228
u:27
0.06
mg
.0087
mg
0 10.5
%
103
%
- 119
u: 5.5
0.1
mg
3
%
11
u:8
570
b2 [g, j]
riboflavin
(1.3 mg)
.099
mg
.0165
mg
0.195
mg
.01875
mg
25
%
.253
mg
144
%
24
%
.011
mg
238.5
u:45.5
.17
mg
22.5
%
.2568
mg
.0638
mg
.0285
mg
- 144
%
206.5
u:40
.684
mg
.1284
mg
0 3
%
96
%
- 161.5
u:62.5
.54
mg
10
%
51.5
u:41.5
658
b3
niacin
(16 mg)
.904
mg
.2895
mg
2.61
mg
.25575
mg
10
%
.1276
mg
65
%
36
%
.216
mg
138.5
n:27.5
f:111
1.958
mg
36
%
.0354
mg
1.0813
mg
0.92
mg
- 65
%
126
n:25
f:101
.114
mg
.0177
mg
0 6.5
%
43
%
- 50.5
n:1
f:49.5
1.36
mg
4
%
12.5
n:8.5
f:4
327.5
n:62
f:265
.5
b4*
adenine
(75 mg)
1.632
mg
0.375
mg
15.9
mg
.339
mg
19.25
mg
.9735
mg
49.38
mg
? ? 117 31.8
mg
2.2
mg
4.92
mg
0.77
mg
? - 49.38
mg
119 2.24
mg
2.46
mg
0 4.514
mg
32.92
g
- 56
? 7.7
mg
10 302
b5
pantothenic
acid
(5 mg)
.454
mg
.0938
mg
2.08
mg
.13725
mg
15
%
.6391
mg
2.25
%
19
%
.069
mg
105
u:69
.634
mg
.2371
mg
.246
mg
.3003
mg
.056
mg
yog
urt
sub
2.25
%
31%
u:29
2.292
mg
0.123
mg
0 5
%
1.5
%
- 54.5
u:48
1.808
mg
6
%
42
u:36
233
b6
pyridoxine
(1.7 mg)
.499
mg
.03525
mg
.386
mg
.04725
mg
6
%
.0528
mg
133
%
25
%
.033
mg
216.5
u:52.5
.582
mg
.0781
mg
.0396
mg
.1518
mg
.06
mg

133
%
178.5
u:45.5
.255
mg
.0198
mg
0 3.5
%
88
%
- 105
u:13.5
0 2
%
2 502
b7 [h]
biotin
(35 μg)
3.212
μg
.8229
μg
5.4
μg
? 10.069
μg
2.86
μg
45
%
86
%
? 195
u:64
6.6
μg
.2
μg
1.038
μg
5.5
μg
2.73
μg
- 45
%
91
u:46
58.33
μg
.519
μg
4.547
μg
3
%
30
%
- 214
u:181
0 11
%
11

511
b8*
inositol

(myo
or
lipid)
(1000 mg)
20 10 - 102 25 5 10 - - 172 99.75 70.27 - - - - 10 - 6.3 - 16  50 10 - - - - - -
b9
[m, b11, r]
folic acid
(400 μg)
12 4.5 30 6 6 1 23 34 2 118.5 19 71 3 3 3 - 23 122 18 1.5 0 5 23 - 47.54 2 6 294
b10*
pABA
(100 mg)
~0 ~0 - ~0 >0 ~0 - - - 0 0 - - - - - - - - - - - - - - - - - -
b12 [t]
(cyano)
cobalamin
(2.4 μg) 
0 0 0 0 50 20 1250 0 195 0 0 8.5 0 0 20+ 125 133.5 33 4 0 0 125 - 162 0 20 20 490.5
b13*
orotic acid
(mg)
~0 ~0 - ~0 ~0 20 - - - 20 - - - - - - - - - - - - - - - - - - -
b14*
taurine
(mg)
~0 ~0 - ~0 ~0 2 - - - 2 - - - - - - - - - - - - - - - - - - -
b15*
pangamic
acid
~0 ~0 - ~0 0? ~0 - - - 0 - - - - - - - - - - - - - - - - - - -
b16*
choline
(fat sol)
(550 mg)
4 1 4 1 11 5 1.5 1 1 29.5 2 2.5 2 1 - - 1.5 9 68 1 0 2 1.5 - 73.5 3 4.5 7.5 119.5
b20* [aka I]
l-carnitine
(25 mg)
~0 ~0 - ~0 ~0 5 - - - 5 - - - - - - - - - - - - - - - - - - -
c
(90 mg)
34 74 25 117 4 0 0 25 ~0 279 350 0 0 7 0 - 0 357 0 0 0 0 0 100+ 100+ 0 0 0 736+
d
(fat sol)
(15 μg)
0 0 0 0 45 0 0 6 0 51 0 0 2 0 0 20+ 0 2 12 1 30 0 0 - 43 0 18 18 114
e
(fat sol)
(15 mg)
2 1.5 16 10 0 2 0 36 0 67.5 13 1 1 2 7 30+ 0 24 9 .5 20 1.5 0 30+ 31 0 0 0 122.5
f1*
linoleic
acid
omega-6
(g)
(17 mg)
0.1086 0.09 2.534 0.187 1.5 .300 0 1.2 .414 6.3336 .0738 .540 .3462 .0828 2.87  - 0 3.9128 3.23 .1731 1.5 .5 0 - 5.4031 ~0 .8 .8 16.45
f2*
alpha
linolenic
acid
omega-3
(g)
(1.6 mg)
0.0638 0.065 0.165 0.0319 0.2 .200 0 0.2 1.597 2.5227.041 .024 .219 .0014 .93 - 0 1.2154 .228 .1095 .5 .75 0- 1.5875 ~0 .12 .12 5.45
f1:f2
ratio
- - - - - - - - - 2.51- - - - - 2:1 - 3.22 - - - - - - 3.40 - - - 3.02
k
(fat sol)
(138 μg)
2 1 39 38 5 0 0 - - 85 10 1 1 12 0 - 0 24 9 .5 10 .5 0 - 20 0 2 2 131
q1*
coenzyme
q10 (mg)
(30 mg)
0.272 0.075 - 0.0375 .625 .0308 - - - - - - - - - - - - - - - - - - - - - - -
q2*
pyrrolo
quinoline

 quinone
(mu-g)
3.536 - - 2.025 .063 .2101 - - - - - - - - - - - - - - - - - - - - - - -
s*
salicylic
acid
(mg)
~0 ~1 - ~0.375 ~0 ~0 - - - - - - - - - - - - - - - - - - - - - - -
- - - -- - - - - - - - - - - - - - - - - - - - - - - - -

* not really.

complete requirements

fat soluble:
- a: 120% of pre-formed + 100% of convertible rae, total daily. 30% + pre-formed per meal.
- choline: 30% + per meal, 120% total
- d: 30% + per meal, 120% total
- e: 30% + per meal, 120% total
- k: 30% + per meal, should not exceed 100%/meal, >120% & <200% total

water soluble (bs & c):
- 300+% total w/ 100% for each meal
- b1: 125% w/ each meal
- b2: 131% w/ each meal
- b3: 125% w/ each meal, but not more than 200% in fortified sources.
- b4: 75 mg w/ each meal
- b5: 100% w/ each meal
- b6: 118% w/ each meal
- b7: 171% w/ each meal, with 857% total as a goal.


incomplete requirements legend:
>300% without meeting 100%/meal
+75<=100% each meal    [=+200%<=300% total]
+50<=75% each meal   [=+100<=200% total] 
<=50% each meal    [<100% total]

specific brands used:
- so nice vanilla soy milk
- chapman's black cherry ice cream
- bulk barn nutritional yeast
- vector cereal

- black diamond brand medium cheddar cheese
- selection brand pasta [metro/food basics]
- bulk barn nutritional yeast

- irrestibles brand olive canola oil
- dempster's whole grain double flax bread
- black diamond brand medium cheddar cheese

- natura chocolate soy milk
- no specific brand or type of coffee

diet options:

daily:


2) pasta salad bowl:
- 100 g cooked pasta ----> reduce
- one large red pepper
- one large chopped carrot
- 60 g chopped medium cheddar cheese [12 slices]
- 10 g hulled hemp seeds
- yogurt dressing or canola oil caesar dressing
- 1 tsp nutritional yeast
- glass of pasta water 
+
- tomatoes
- flax seeds (ground!) (probably not) 
- spirulina 
- tahini  
- macademia nuts 
- croutons
- tomato powder 
- caesar dressing (very little b1, 35% e?, some a)
- one tbsp of imitation bacon bits (isoflavones, maybe_
- 5 g chopped crickets [5 crickets]  [b12]
- indoor farmed fish? <----b5, b12
- shittake mushrooms <------b5
- lemon (probably for phytonutrients) 
- garlic cloves (probably for phytonutrients)
- oregano & pepper (probably for phytonutrients)
- kalamata olives (probably not necessary for e) 
- microwaved/chopped broccoli (probably not, due to k and I3C)  <----but, b5
- broccoli leaves or kale or dandelion leaves? (probably not, due to I3C and k) 
- red clover (if locatable or foragable, for phytoestrogens)
- alfafa?

- need 65-85% b5

3) eggs:
- 2 jumbo fried eggs
- 1 slice of whole wheat bread (including the germ!) with flax
- 2 tbsp olive oil margarine
- 30 g sliced medium cheddar cheese [6 slices]
+
- salami (45 g) (25% b1, 8% b2, 12% b3, 5% b5, 11.5% b6, 0% b9, 20% b12)
- rice (100 g) (60% b1, 2% b2, 35% b3, 4% b5, 6% b6, 69% b9)
- soy meat (100% b1, 50-70% b2, 100% b3, 15% b5, 60% b6, 45% b9, 90% b12)
- indoor grown salmon? (50 g) (15% b1, 15% b2, 55% b3, 15% b5, 20% b6, 150% b12) <------can't find
- mushroom sauce (some supplemental b2,/b3/b6, substantive b5)
- + apple juice? (1 cup) (100% c)
- carrot juice (1 cup) (18% b1, 8% b2
- orange juice (1 cup) (15% b1, 4% b2, 5% b3, 5% b5, 5% b6, 19% b9, 207% c, added e?)
- cranberry juice (unsweetened. need added c, has e)
- tomato juice (likewise)

- need (85 b1, 50 b2, 95 b3, 75 b5, 85 b6, 75 b9, 65 b12)


==========

the list of everything i need to get.

added are green

13 vitamins:
1) A
2) B1 (thiamine)
3) B2 (riboflavin)
4) B3 (niacin)
5) B5 (pantothenic acid)
6) B6 (pyridoxine)

7) B7 (biotin)
8) B9 (folic acid)
9) B12 (cyano-cobolamin)
10)  C
11) D
12) E
13) K


15 amino acids:
1) histidine
2) isoleucine
3) leucine
4) lysine
5) methionine
6) phenylalanine
7) threonine
8) tryptophan
9) valine
10) arginine
11) cysteine
12) glycine
13) glutamine
14) proline
15) tyrosine
+ measure 6 non-essential

4 fatty acids:
1) linoleic acid
2) ala
3) dha
4) epa

23 minerals:
1) calcium
2) phosphorus
3) potassium
4) sulfur
5) sodium
6) chlorine
7) magnesium
8) iron
9) zinc
10) copper
11) manganese
12) iodine
13) selenium
14) molybdenum
15) chromium
16) fluoride
17) bromine
18) cobalt
19) tin
20) vanadium
21) silicon
22) boron
23) nickel
24) lead?

carotenoids (not including pro-vitamin a)
1) lutein
2) zeaxanthin
3) lycopene
4) phytofluene
5) phytoene
6) astaxanthin
7) capsanthin
8) canthaxanthin
9) cryptoxanthin

chlorophyll:
1) chlorophyll a
2) chlorophyll b

other molecules required for proper metabolic functions:
1) choline (cannot synthesize properly)
2) coQ10

3) lipoic acid
4) glutathione precursors
5) ergothioneine  (cannot synthesize)   <-----mushrooms
6) pyrroloquinoline quinone (PQQ) (cannot synthesize)   <-----kiwis
7) queuine  (cannot synthesize)    <-----cheese [made in stomach by bacteria]

8) taurine (cannot synthesize properly) <----cheese
9) betaine (more than a choline precursor?)

glucose:
i'm more concerned about diabetes than weight gain, so...
the glycemic index is:
running total...

fiber:
i don't need many different types, i just need some. i'm not worrying about this.

& water

also, let's measure flavonoids:

anthocyanidins:
1) pelargonidin
2) delphinidin
3) cyanidin
4) malvinidin
5) peonidin
6) petunidin
7) rosinidin

flavonols:
1) isorhamnetin
2) kaempferol
3) myricetin
4) quercetin
5) fisetin
6) kaempferide

flavones:
1) luteolin
2) apigenin
3) techtochrysin
4) baicalein (to avoid!)
5) norwogonin
6) wogonin
7) nobiletin

flavanones:
1) eriodictyol
2) hesperetin
3) naringenin
4) hesperidin
5) isosakuranetin
6) pinocembrin
7) sterubin

isoflavones:
1) daidzein
2) genistein
3) glycitein
4) biochanin A
5) formononetin

i should try to measure some further phytoestrogens:
1) matairesinol
2) secoisolariciresinol
3) pinoresinol
4) lariciresinol
5) coumestrol

& finally, let's also measure:
1) saponins
2) ursolic acid (& precursors)
3) cafestol
4) resveratrol
5) ellagic acid
6) coumarin
7) tyrosol
8) hydroxytyrosol
9) oleocanthal
10) oleuropein
11) gingerol
12) phytic acid