Question 1

Does anyone know what is the differences between Neuro Fuzzy and Mitcom Zojirushi rice cooker?  Which one is better?  Thanks.

Accepted Answer

This model, the NS-ZCC10/NS-ZCC18, is the only one I've found labeled "Neuro Fuzzy" and is made in Japan, while the comparable Micom Fuzzy Logic NS-TSC10/NS-TSC18 is made in China. Two differences are that on the ZCC there are cool touch handles to pull out the pot and the steam vent is easier to clean. I have read in another answer related to the NS-ZCC10 5.5 cup model that the Neuro Fuzzy models have 2 extra sensors to also check room and lid temperatures, while the cheaper TSC units just have a sensor on the center post the pot sits on. I haven't been able to confirm the existence or lack of extra sensors independently though.Steam vent cleaning video showing both models -https://www.youtube.com/watch?list=UU2Tssa-a-rEEWM5il8cWRuw&feature=player_detailpage&v=aypd1H2h_aA#t=40The biggest difference though between these models though, is that the ZCC has a spherical heating element, which was a pretty big innovation. Spherical heat is an important reason why induction models cook better, so I'd say the ZCC sits between the non-spherical TSC, and spherical induction HBC models. The ZCC Neuro Fuzzy model appears to be the sweet spot in quality and performance for money spent.Better comparison information than what retailers are displaying - http://www.zojirushi.com/ourproducts/how_and_chart/comparison_pdf/Zojirushi%20Rice%20Cooker%20Chart.pdBEGIN Japanology - Rice Cookers - mentions the introduction of spherical induction in the 1980shttps://www.youtube.com/watch?v=9KbRRHRbprUAs far as differences in programming between Neuro Fuzzy and Fuzzy Logic models, as the names insinuate, there may be some differences because the Neuro Fuzzy has the extra room and lid temperature sensors. The higher end models, up to the $500 NVC pressure induction units, don't mention Neuro Fuzzy but they likely have these extra sensors too. Fuzzy Logic is something they teach in textbooks, but "Neuro Fuzzy" seems to have been pulled out of nowhere by marketing, so the lack of clear explanation from Zojirushi confusing. 	It seems to me Zojirushi wanted to differentiate the Japanese made ZCC unit from its less expensive Chinese made cousin, the TSC/TGC, and Neuro Fuzzy was used as a buzzword to help identify the better model at a glance. Especially since ZCC has plain white appearance compared to the TSC. There are no comparable Chinese made versions of the higher end induction units, so the Neuro Fuzzy label is not needed for them. I also suspect the margins on the China made Micom Fuzzy Logic TSC models are good, and Zojirushi doesn't want to upset those sales by touting the spherical heating element or extra sensors on the Neuro Fuzzy ZCC too hard. I ended up ordering ZCC and would recommend spending the extra $20 over the TSC for it.

Question 2

Does the Teflon wear off easily in the pan?

Accepted Answer

This can’t be a coincidence so many people are having problems with the coding.   More than half say the non-stick coating is coming off.  And many of those mention they did not scratch it off with metal utensils.

I loved my zo, but I have not bought another one because they are all non-stick.

The other half are saying they’ve had it for 5-10 12 years with no problems.   I had a Zo years ago (induction/fuzzy), And after a couple of years of light use I noticed the nonstick coating was wearing away, it was so thin you could start to see the metal underneath (which I’ve never seen on any other nonstick cookware).

I was wondering if the induction heating was too hot, causing the nonstick coating to fail?   Or if this is a quality control issue where a fairly high percentage are defective (doomed to fail when you use the rice cooker).    I’ve been wanting to get another zo, but the nonstick coating problem is a dealbreaker.

Question 3

Have you tried cooking other whole grains in it- such as barley, quinoa, polenta, or buckwheat?  If so, what settings have you used?  Thanks!

Accepted Answer

I cook brown rice mixed with 25% wild rice at the setting of "Brown Rice."  The mixture cooks well with 150% of water without presoaking, but it takes 110 min.  When time is short, I use a pressure cooker; it takes about 30 min.  When I was a child, I used to eat barley at every meal, but I don't know how to cook.  I will ask around.  We always ate buckwheat in as noodles.  I have just bought a bag of quinoa.  I will find an answer in a month.

Question 4

Is rice cooker made in japan

Accepted Answer

Yes it is.  It says "made in japan" on the front of the rice cooker.  Its the reason I  choose this model over the others.  So far, its an excellent rice cooker.  Best one I've ever owned.  I find the 10 cup size works better than the 5 cup as sometimes you want to cook extra and refrigerate it for fried rice.  Get this cooker, you won't be sorry.

ASIN	B00007J5U7
Best Sellers Rank	#1,126,315 in Home & Kitchen ( See Top 100 in Home & Kitchen ) #465 in Rice & Pasta Cookers
Brand Name	ZOJIRUSHI
Capacity	5.5 cups
Colour	White
Customer Reviews	4.7 4.7 out of 5 stars (8,205)
Global Trade Identification Number	00023596215085
Included Components	1.0-Liter. Spherical inner cooking pan and heating system, 2-Measuring Cups, Nonstick Rice Spoon/Scooper, Premium White, Rice Spoon Holder Recipes, Zojirushi Ns-Zcc10 5-1/2-Cup (Uncooked) Neuro Fuzzy Rice Cooker And Warmer
Item Dimensions D x W x H	33D x 25.7W x 20.6H Centimeters
Item Type Name	Neuro Fuzzy Rice Cooker
Item Weight	1.4 Kilograms
Lid Material	Plastic
Manufacturer	Zojirushi
Material Type	Stainless Steel
Model Name	Neuro Fuzzy Rice Cooker
Model Number	NS-ZCC10
Number of Items	1
Number of Packs	1
Other Special Features of the Product	Automatic Keep Warm, Programmable, Timer
Part Number	NS-ZCC10
Power Source Type	Corded Electric
Product Care Instructions	Hand Wash
UPC	023596215085
Unit Count	1.0 Count
Voltage	110 Volts
Warranty Description	1 year limited warranty
Wattage	680 Watts

NS-ZCC10 5-1/2-Cup (Uncooked) Neuro Fuzzy Rice Cooker and Warmer, Premium White, 1.0-Liter

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