CN101872374A - Method for optimizing beer production formula - Google Patents
Method for optimizing beer production formula Download PDFInfo
- Publication number
- CN101872374A CN101872374A CN 201010180631 CN201010180631A CN101872374A CN 101872374 A CN101872374 A CN 101872374A CN 201010180631 CN201010180631 CN 201010180631 CN 201010180631 A CN201010180631 A CN 201010180631A CN 101872374 A CN101872374 A CN 101872374A
- Authority
- CN
- China
- Prior art keywords
- mrow
- msub
- formula
- msubsup
- mtd
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 235000013405 beer Nutrition 0.000 title claims abstract description 36
- 238000000034 method Methods 0.000 title claims abstract description 33
- 238000004519 manufacturing process Methods 0.000 title claims abstract description 28
- IJGRMHOSHXDMSA-UHFFFAOYSA-N Atomic nitrogen Chemical compound N#N IJGRMHOSHXDMSA-UHFFFAOYSA-N 0.000 claims abstract description 42
- 238000005457 optimization Methods 0.000 claims abstract description 25
- 239000002994 raw material Substances 0.000 claims abstract description 23
- FYGDTMLNYKFZSV-URKRLVJHSA-N (2s,3r,4s,5s,6r)-2-[(2r,4r,5r,6s)-4,5-dihydroxy-2-(hydroxymethyl)-6-[(2r,4r,5r,6s)-4,5,6-trihydroxy-2-(hydroxymethyl)oxan-3-yl]oxyoxan-3-yl]oxy-6-(hydroxymethyl)oxane-3,4,5-triol Chemical compound O[C@@H]1[C@@H](O)[C@H](O)[C@@H](CO)O[C@H]1OC1[C@@H](CO)O[C@@H](OC2[C@H](O[C@H](O)[C@H](O)[C@H]2O)CO)[C@H](O)[C@H]1O FYGDTMLNYKFZSV-URKRLVJHSA-N 0.000 claims abstract description 22
- 229920002498 Beta-glucan Polymers 0.000 claims abstract description 22
- 229910052757 nitrogen Inorganic materials 0.000 claims abstract description 21
- OAKJQQAXSVQMHS-UHFFFAOYSA-N Hydrazine Chemical compound NN OAKJQQAXSVQMHS-UHFFFAOYSA-N 0.000 claims abstract description 20
- GXCLVBGFBYZDAG-UHFFFAOYSA-N N-[2-(1H-indol-3-yl)ethyl]-N-methylprop-2-en-1-amine Chemical compound CN(CCC1=CNC2=C1C=CC=C2)CC=C GXCLVBGFBYZDAG-UHFFFAOYSA-N 0.000 claims description 18
- 239000003016 pheromone Substances 0.000 claims description 15
- 241000257303 Hymenoptera Species 0.000 claims description 11
- 238000013461 design Methods 0.000 claims description 8
- 238000000354 decomposition reaction Methods 0.000 claims description 5
- 229920001503 Glucan Polymers 0.000 claims description 3
- 238000009835 boiling Methods 0.000 claims description 3
- 238000001556 precipitation Methods 0.000 claims description 3
- 102000004169 proteins and genes Human genes 0.000 claims description 3
- 108090000623 proteins and genes Proteins 0.000 claims description 3
- 238000012360 testing method Methods 0.000 abstract description 4
- 235000013339 cereals Nutrition 0.000 description 8
- 238000001914 filtration Methods 0.000 description 6
- 239000000463 material Substances 0.000 description 6
- 239000000203 mixture Substances 0.000 description 6
- 239000000796 flavoring agent Substances 0.000 description 5
- 235000019634 flavors Nutrition 0.000 description 5
- 239000000126 substance Substances 0.000 description 5
- LFQSCWFLJHTTHZ-UHFFFAOYSA-N Ethanol Chemical compound CCO LFQSCWFLJHTTHZ-UHFFFAOYSA-N 0.000 description 4
- 241000209140 Triticum Species 0.000 description 4
- 235000021307 Triticum Nutrition 0.000 description 4
- 238000000855 fermentation Methods 0.000 description 4
- 230000004151 fermentation Effects 0.000 description 4
- 238000009472 formulation Methods 0.000 description 4
- QSJXEFYPDANLFS-UHFFFAOYSA-N Diacetyl Chemical group CC(=O)C(C)=O QSJXEFYPDANLFS-UHFFFAOYSA-N 0.000 description 2
- 241001316028 Euphaedusa tau Species 0.000 description 2
- 241000209219 Hordeum Species 0.000 description 2
- 235000007340 Hordeum vulgare Nutrition 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 2
- 238000013124 brewing process Methods 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 235000011389 fruit/vegetable juice Nutrition 0.000 description 2
- 235000021440 light beer Nutrition 0.000 description 2
- 238000004890 malting Methods 0.000 description 2
- 238000005360 mashing Methods 0.000 description 2
- 230000002035 prolonged effect Effects 0.000 description 2
- 238000007670 refining Methods 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 239000004458 spent grain Substances 0.000 description 2
- 238000012795 verification Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000002939 conjugate gradient method Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 235000013305 food Nutrition 0.000 description 1
- 239000004615 ingredient Substances 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 239000011664 nicotinic acid Substances 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000010998 test method Methods 0.000 description 1
Images
Landscapes
- Alcoholic Beverages (AREA)
Abstract
The invention relates to a method for optimizing a beer production formula. A conventional production formula is determined by a method which combines human experience and tests. The method comprises the following steps of: obtaining main raw materials in a beer formula; establishing a comprehensive production performance index estimation model according to the parameters of the raw materials, wherein main considered comprehensive performance indexes comprise saccharifying power, wort total nitrogen, wort alpha amino nitrogen, wort beta glucan and the thickness of a distilled grain layer of a filter tank; and optimizing a beer formula model by using a variable-metric ant colony optimization method and finally obtaining a production formula with the lowest cost. The method of the invention has the advantages of openness, robustness, parallelism and global convergence.
Description
Technical Field
The invention belongs to the technical field of information and control, relates to an automation technology, and particularly relates to a beer production formula optimization method.
Background
The optimization design problem of the raw material formula is an important research content in the fields of chemical industry, food, materials and the like. In order to obtain a formula which has excellent performance and can meet the use requirement, the use amount proportion relation of various raw materials is determined by testing, optimizing, identifying and reasonably selecting the raw materials according to the performance requirement and the process condition of a product. In recent years, research on application of formula optimization design is active, and for such a complex multi-target formula system, a test design method is mostly adopted at present. The formulation design of beer enterprises is no exception, and in order to make the style of the beer consistent, the malt enters the factory, the approximate calculation of raw material components is carried out through analysis, the batching scheme is determined, and then the batching production test scheme is finally determined through small saccharification inspection and verification. And finally, the product ingredients are ordered through production verification and modification.
In the production process of beer, the formula of the beer raw materials determines important indexes of the product such as flavor, quality, cost and the like. At present, the production formula of beer production enterprises is still determined by manual experience and a test method, and although the basic requirements of the process can be met, the index parameters such as the total cost of raw materials, taste and the like are easy to be high. Therefore, the optimization of the beer formula has important significance for improving the production efficiency of enterprises and reducing the product cost. The optimization of the beer formula is a formula optimization problem containing multiple extreme points. So far, the formulation optimization problem mostly adopts common traditional mathematical optimization methods, such as a simplex method, a conjugate gradient method, a geometric mean analysis method, an orthogonal design method and the like. Since these optimization methods lack robustness of global optimal search and most of the conventional optimizations require gradient information, it is difficult to solve such an optimization problem with a complex mathematical form.
Disclosure of Invention
The invention aims to provide a formula optimization method with strong global optimization capability aiming at some problems in beer formula optimization.
The technical scheme of the invention is to convert a continuous formula optimization problem into a discrete combined optimization problem, then adopt a bionic ant colony algorithm and adopt a variable-scale method to improve the algorithm optimization performance, shorten the calculation time and finally establish a beer production formula optimization method.
The method comprises the following specific steps:
and 2, establishing a comprehensive production performance index estimation model according to the parameters of the raw materials, wherein the main comprehensive performance indexes considered are malt saccharification capacity, wort total nitrogen, wort alpha-amino nitrogen, wort beta-glucan and the thickness of a filter tank grain layer.
Malt saccharification ability
Under normal saccharification operation (30-45 min at 65-68 ℃), each kilogram of mixed raw materials should contain 1500-2000 WK of saccharification force. The upper limit value can shorten the refining time and obtain the wort with higher fermentation degree; the lower limit value of saccharification time is long, and the fermentation degree is low. If the weight is less than 1500WK, the saccharification operation is influenced, the utilization rate of raw materials is influenced, and the composition of wort is influenced. And the total soluble nitrogen of the malt can be estimated according to the following formula:
② total nitrogen of wort
The total soluble nitrogen level of a typical beer wort is:
900-1200 mg/L whole malt wort
Adding 700-850 mg/L of concentrated alcohol beer wort as auxiliary material
550-700 mg/L of light beer wort added with auxiliary materials
Also, the total soluble nitrogen of wort can be estimated as follows:
③ wort alpha amino nitrogen
The alpha amino nitrogen of the wort is related to the flavor substances of the beer, namely high-grade alcohol and diacetyl, and the control of the concentration of the alpha amino nitrogen of the wort is particularly important for controlling the flavor of the beer. Generally, the alpha amino nitrogen of the wort is preferably controlled within the range of 160-180 mg/L. And the alpha amino nitrogen content of the wort can be estimated by the following formula:
in the formula,
is the mass concentration of alpha amino nitrogen of component i, and kappa is the amino nitrogen coefficient.
Fourthly, the wheat juice beta glucan
The beer containing a proper amount of beta glucan is one of the substances for keeping the mellow feeling of the beer, but if the beta glucan is too much, the decomposition of the beta glucan in the malt is insufficient, and a series of related problems are brought about in the beer brewing process. Therefore, the content of beta glucan in the malting process is lower than 250 mg/L. And the wort beta glucan content can be estimated by the following formula:
Fifth thickness of the groove layer of the filter tank
During mashing, the insoluble spent grain contained in the mash will form a layer of grains. The thickness of the grains is too thick, the filtration speed of the wort is slow, and the filtration time is prolonged; the thickness of the layer is too thin, which, although increasing the filtration rate, reduces the clarity of the wort. The thickness of the grain layer in the production is generally controlled to be 30-50 cm. And the thickness of the tank can be estimated by the following formula:
And 3, optimizing the beer formula model by using a variable-scale ant colony optimization method, and finally solving the production formula with the lowest cost. The method comprises the following specific steps:
firstly, initializing parameters, dividing each component into N equal parts by mass percentage, and performing discrete interval of each component
Wherein,
the upper and lower limits of the mass percentage of the components.
If max (h)1，h2，...，hn) Stopping the algorithm when the epsilon is less than or equal to epsilon, and outputting the current optimal scheme, wherein epsilon represents the ending condition; otherwise, turning to the step 3;
(r, i) is the ith node on the r component, and the numerical value is marked as Xr，i(ii) a (r +1, j) is the jth node on the r +1 component; [ (r, i), (r +1), j)]Is a connecting line from the node (r, i) to the node (r +1, j), the probability that the ant k transfers from the position (r, i) to the position (r +1, j) at the time t during the movement of the ant group with the number m of ants in the ant group is
In the formula: mr+1Is the allowable value range of the r +1 component, and ensures that the sum of the proportions of all varieties is not more than 100 percent. If the r +1 th variety is not the last undetermined variety, Mr+1A value range of
But for the last breed, Mr+1Can only take values of
τ[(r，i)，(r+1，j)](t) at time t at [ (r, i), (r +1), j]The intensity of pheromone concentration remained on the connecting line is equal to that on each path under the initial condition, i.e. tau[(r，i)，(r+1，j)](0) C constant.
Ant k (k 1, 2.. m) is randomly selected according to the probability on each path. In the process of creating the solution, after ants visit the nodes, the pheromones on the paths traveled by the ants are updated by adopting a local pheromone updating rule
Where ρ is an information amount attenuation parameter, (0 < ρ < 1), let
Q is a constant, JnnThe formula cost of the ant obtaining scheme is shown. Each ant is recurred in this way and finally generates a respective formulation.
Fourthly, eliminating the infeasible schemes which do not meet the production indexes by using the index model, calculating formula cost J of the feasible schemes according to the following formula, comparing the formula cost J with the best scheme, and recording the scheme as the best scheme if the formula cost J is less than the formula cost in the best scheme;
Fifthly, when all ants construct a formula scheme, the pheromone is globally updated according to the following formula to obtain the concentration intensity of the pheromone
In the formula: j. the design is a squaremin gbThe lowest value of the objective function obtained at the start of the iteration.
Sixthly, updating iteration times t ← t + 1; if t is more than or equal to tmaxTurning to the step 3; otherwise, find the best scheme at present, update xr0、wrWherein w isr＝2·hrAnd correcting the upper and lower search limits x according to the following formularupper、xrlowerGo to step 1, where xr0Is the best quality percentage of the r component in the best scheme.
Compared with the prior art, the invention has the following beneficial effects: the method has the characteristics of openness, robustness, parallelism, global convergence, no special requirement on the mathematical form of the problem and the like.
Drawings
FIG. 1 is a schematic diagram of the discrete intervals of the components in the process of the present invention.
Detailed Description
The invention will be further described with reference to the accompanying drawings.
The method comprises the following steps:
and 2, establishing a comprehensive production performance index estimation model according to the parameters of the raw materials, wherein the main comprehensive performance indexes considered are malt saccharification capacity, wort total nitrogen, wort alpha-amino nitrogen, wort beta-glucan and the thickness of a filter tank grain layer.
Malt saccharification ability
Under normal saccharification operation (30-45 min at 65-68 ℃), each kilogram of mixed raw materials should contain 1500-2000 WK of saccharification force. The upper limit value can shorten the refining time and obtain the wort with higher fermentation degree; the lower limit value of saccharification time is long, and the fermentation degree is low. If the weight is less than 1500WK, the saccharification operation is influenced, the utilization rate of raw materials is influenced, and the composition of wort is influenced. And the total soluble nitrogen of the malt can be estimated according to the following formula:
in the formula, Ti、XiRespectively representing the saccharifying power intensity and mass fraction of the component i, wherein i is more than or equal to 1 and less than or equal to n;
② total nitrogen of wort
The total soluble nitrogen level of a typical beer wort is:
900-1200 mg/L whole malt wort
Adding 700-850 mg/L of concentrated alcohol beer wort as auxiliary material
550-700 mg/L of light beer wort added with auxiliary materials
Also, the total soluble nitrogen of wort can be estimated as follows:
③ wort alpha amino nitrogen
The alpha amino nitrogen of the wort is related to the flavor substances of the beer, namely high-grade alcohol and diacetyl, and the control of the concentration of the alpha amino nitrogen of the wort is particularly important for controlling the flavor of the beer. Generally, the alpha amino nitrogen of the wort is preferably controlled within the range of 160-180 mg/L. And the alpha amino nitrogen content of the wort can be estimated by the following formula:
Fourthly, the wheat juice beta glucan
The beer containing a proper amount of beta glucan is one of the substances for keeping the mellow feeling of the beer, but if the beta glucan is too much, the decomposition of the beta glucan in the malt is insufficient, and a series of related problems are brought about in the beer brewing process. Therefore, the content of beta glucan in the malting process is lower than 250 mg/L. And the wort beta glucan content can be estimated by the following formula:
in the formula,is the beta glucan mass concentration of the component i, and nu is the glucan coefficient.
Fifth thickness of the groove layer of the filter tank
During mashing, the insoluble spent grain contained in the mash will form a layer of grains. The thickness of the grains is too thick, the filtration speed of the wort is slow, and the filtration time is prolonged; the thickness of the layer is too thin, which, although increasing the filtration rate, reduces the clarity of the wort. The thickness of the grain layer in the production is generally controlled to be 30-50 cm. And the thickness of the tank can be estimated by the following formula:
And 3, optimizing the beer formula model by using a variable-scale ant colony optimization method, and finally solving the production formula with the lowest cost. The method comprises the following specific steps:
firstly, initializing parameters, dividing each component into N equal parts by mass percentage, and performing discrete interval of each component
Wherein,the upper and lower limits of the mass percentage of the components.
As shown in fig. 1, each vertical stripe represents a material and is discretized into N equal parts, and the discretized nodes represent the mass fraction of the component. After discrete processing, the formula optimization problem is changed into a problem of finding an optimal path. Ants start from a start point, gradually pass through nodes on each variety, and finally reach an end point, so that one circulation is completed, and a complete formula is formed.
If max (h)1，h2，...，hn) Stopping the algorithm when the epsilon is less than or equal to epsilon, and outputting the current optimal scheme, wherein epsilon represents the ending condition; otherwise, turning to the step 3;
(r, i) is the ith node on the r component, and the numerical value is marked as Xr，i(ii) a (r +1, j) is the jth node on the r +1 component; [ (r, i), (r +1), j)]Is a connecting line from the node (r, i) to the node (r +1, j), the probability that the ant k transfers from the position (r, i) to the position (r +1, j) at the time t during the movement of the ant group with the number m of ants in the ant group is
In the formula: mr+1Is the allowable value range of the r +1 component, and ensures that the sum of the proportions of all varieties is not more than 100 percent. If the r +1 th variety is not the last undetermined variety, Mr+1A value range of
But for the last breed, Mr+1Can only take values of
At time t in [ (r, i), (r +1), j]The intensity of pheromone concentration remained on the connecting line is equal to that on each path under the initial condition, i.e. tau[(r，i)，(r+1，j)](0) C constant.
Ant k (k 1, 2.. m) is randomly selected according to the probability on each path. In the process of creating the solution, after ants visit the nodes, the pheromones on the paths traveled by the ants are updated by adopting a local pheromone updating rule
Where ρ is an information amount attenuation parameter, (0 < ρ < 1), let
Q is a constant, JnnShowing the formula cost of the ant obtaining scheme. Each ant is recurred in this way and finally generates a respective formulation.
Fourthly, eliminating the infeasible schemes which do not meet the production indexes by using the index model, calculating formula cost J of the feasible schemes according to the following formula, comparing the formula cost J with the best scheme, and recording the scheme as the best scheme if the formula cost J is less than the formula cost in the best scheme;
Fifthly, when all ants construct a formula scheme, the pheromone is globally updated according to the following formula to obtain the concentration intensity of the pheromone
In the formula: j. the design is a squaremin gbThe lowest value of the objective function obtained at the start of the iteration.
Sixthly, updating iteration times t ← t + 1; if t is more than or equal to tmaxTurning to the step 3; otherwise, find the best scheme at present, update xr0、wrWherein w isr＝2·hrAnd correcting the upper and lower search limits x according to the following formularupper、xrlowerGo to step 1, where xr0Is at bestThe optimal mass percentage of the component r in the scheme.
Claims (1)
1. A beer production formula optimization method is characterized by comprising the following steps:
step 1, obtaining the yield, alpha amino nitrogen, saccharifying power, total soluble nitrogen, beta glucan and unit price of main raw materials in a beer formula;
step 2, establishing a malt saccharification force, wort total nitrogen, wort alpha-amino nitrogen, wort beta-glucan and filter tank grain layer thickness comprehensive production performance index estimation model;
and 3, optimizing the beer formula model by using a variable-scale ant colony optimization method, and finally solving the production formula with the lowest cost, wherein the specific steps are as follows:
firstly, initializing parameters, dividing each component into N equal parts by mass percentage, and performing discrete interval of each componentWherein,
respectively representing the upper limit and the lower limit of the mass percentage of the components;
if max (h)1，h2，...，hn) Stopping the algorithm when the epsilon is less than or equal to epsilon, and outputting the current optimal scheme, wherein epsilon represents the ending condition; otherwise, turning to the step 3;
(r, i) is the ith node on the r component, and the numerical value is marked as Xr，i(ii) a (r +1, j) is the jth node on the r +1 component; [ (r, i), (r +1), j)]Is a connecting line from the node (r, i) to the node (r +1, j), the number of ants in the ant group is m, and the probability that the ant k is transferred from the position (r, i) to the position (r +1, j) at the moment t in the motion process is
In the formula: mr+1Is the allowable value range of the r +1 th component, tau[(r，i)，(r+1，j)](t) at time t at [ (r, i), (r +1), j]Residual pheromone concentration intensity on the connecting line is obtained;
an ant k (k is 1, 2.. m) is randomly selected according to the probability on each path, and after the ant visits a node, the pheromone on the path where the ant walks is updated by adopting a local pheromone updating rule
Where ρ is an information amount attenuation parameter, (0 < ρ < 1), let
Q is a constant, JnnRepresenting the formula cost of the ant obtaining scheme, and each ant recurs in such a way and finally generates a respective formula scheme;
fourthly, eliminating the infeasible schemes which do not meet the production index by using the index modelCalculating a formula cost J by the scheme and comparing the formula cost J with the best scheme, and if the formula cost J is less than the formula cost in the best scheme, recording the scheme as the best scheme;wherein M isiIs the unit price of the raw material component i;
fifthly, when all ants construct a formula scheme, globally updating the pheromone according to the following formula to obtain the pheromone concentration intensity tau'[(r，i)，(r+1，j)]
In the formula: j. the design is a squaremingbThe lowest objective function value obtained when the iteration is started;
sixthly, updating iteration times t ← t + 1; if t is more than or equal to tmaxTurning to the step 3; otherwise, find the best scheme at present, update xr0、wrWherein w isr＝2·hrAnd correcting the upper and lower search limits x according to the following formularupper、xrlowerGo to step 1, where xr0For the best mass percentage of the r-th component in the best case,
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2010101806318A CN101872374B (en) | 2010-05-21 | 2010-05-21 | Method for optimizing beer production formula |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2010101806318A CN101872374B (en) | 2010-05-21 | 2010-05-21 | Method for optimizing beer production formula |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN101872374A true CN101872374A (en) | 2010-10-27 |
| CN101872374B CN101872374B (en) | 2012-07-11 |
Family
ID=42997234
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN2010101806318A Expired - Fee Related CN101872374B (en) | 2010-05-21 | 2010-05-21 | Method for optimizing beer production formula |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN101872374B (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103548048A (en) * | 2010-11-05 | 2014-01-29 | 可口可乐公司 | A method of juice production, apparatus and system |
| CN104035327A (en) * | 2014-05-30 | 2014-09-10 | 杭州电子科技大学 | Production scheduling optimization method for beer saccharification process |
| CN110109430A (en) * | 2019-04-30 | 2019-08-09 | 杭州电子科技大学 | A kind of intermittent beer fermenting device Optimal Control System |
| CN117281752A (en) * | 2023-08-25 | 2023-12-26 | 广东泛华生物科技有限公司 | Composition with scalp and hair cleaning and moisturizing effects, and preparation method and application thereof |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1431292A (en) * | 2002-12-30 | 2003-07-23 | 上海交通大学 | Method for optimizing deployment of biofermentation batch procedure |
| US20070282583A1 (en) * | 2006-05-31 | 2007-12-06 | Kapadi Mangesh D | System and method for sugarcane recovery estimation |
| CN101430776A (en) * | 2007-11-05 | 2009-05-13 | 云南农业大学 | Fuzzy integrated judging method for feed formula |
-
2010
- 2010-05-21 CN CN2010101806318A patent/CN101872374B/en not_active Expired - Fee Related
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1431292A (en) * | 2002-12-30 | 2003-07-23 | 上海交通大学 | Method for optimizing deployment of biofermentation batch procedure |
| US20070282583A1 (en) * | 2006-05-31 | 2007-12-06 | Kapadi Mangesh D | System and method for sugarcane recovery estimation |
| CN101430776A (en) * | 2007-11-05 | 2009-05-13 | 云南农业大学 | Fuzzy integrated judging method for feed formula |
Non-Patent Citations (1)
| Title |
|---|
| 《计算机工程与应用》 20111130 郑松等 啤酒原料配方的蚁群优化设计研究 226-228，244 1 第47卷, 第11期 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103548048A (en) * | 2010-11-05 | 2014-01-29 | 可口可乐公司 | A method of juice production, apparatus and system |
| CN104035327A (en) * | 2014-05-30 | 2014-09-10 | 杭州电子科技大学 | Production scheduling optimization method for beer saccharification process |
| CN110109430A (en) * | 2019-04-30 | 2019-08-09 | 杭州电子科技大学 | A kind of intermittent beer fermenting device Optimal Control System |
| CN117281752A (en) * | 2023-08-25 | 2023-12-26 | 广东泛华生物科技有限公司 | Composition with scalp and hair cleaning and moisturizing effects, and preparation method and application thereof |
Also Published As
| Publication number | Publication date |
|---|---|
| CN101872374B (en) | 2012-07-11 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Wang et al. | Fermentation kinetics of different sugars by apple wine yeast Saccharomyces cerevisiae | |
| US8818562B2 (en) | Simulated fermentation process | |
| Ciani et al. | Enhanced glycerol content in wines made with immobilized Candida stellata cells | |
| CN101872374B (en) | Method for optimizing beer production formula | |
| Ough et al. | Factors contributing to urea formation in commercially fermented wines | |
| Kelkar et al. | Modeling the effects of initial nitrogen content and temperature on fermentation kinetics of hard cider | |
| CN106701518B (en) | Daqu strengthening method for reducing Daqu dosage and improving vinegar quality | |
| Wang et al. | Construction of recombinant fusant yeasts for the production of cider with low alcohol and enhanced aroma | |
| CN108064270A (en) | Yeast for preparing alcoholic beverage | |
| JP2530650B2 (en) | Method for producing low alcohol or no alcohol beer | |
| CN105349690A (en) | Solid-state fermented vinegar fermentation process monitoring method based on microbial community acid production index | |
| CN109658991A (en) | Method and system for predicting solid state fermentation performance of pit | |
| CN103805394B (en) | A kind of brewing method of white wine | |
| CN115895925A (en) | Saccharomyces cerevisiae Y28 and application thereof | |
| CN102279567A (en) | Method for controlling liquor fermentation period | |
| JPH06245750A (en) | Brewing of beer | |
| CN210560447U (en) | Separating device for degrading ethyl carbamate yeast | |
| KR20000000392A (en) | Preparation of honey wine by Saccaromyces bayanus | |
| Rodríguez-Sifuentes et al. | Identification of a yeast strain as a potential stuck wine fermentation restarter: a kinetic characterization | |
| Kosiv | Comparing the Efficiency of Applying Yeast of Different Generations in High Gravity Brewing | |
| Choudhary et al. | Contribution of Microbial Mechanism and Artificial Intelligence in Wine Production | |
| Rodrigues | Physiological features of Saccharomyces cerevisiae and alternative wine yeast species in relation to alcohol level reduction in wine | |
| CA2770702C (en) | Simulated fermentation process | |
| CN116050648A (en) | Prediction method for lager brewing yeast sedimentation | |
| CN111899805A (en) | Method for obtaining yellow wine fermentation process model based on improved ant lion optimization algorithm |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| ASS | Succession or assignment of patent right |
Owner name: HANGZHOU KUNTIAN AUTOMATIC SYSTEM CO., LTD. Free format text: FORMER OWNER: HANGZHOU ELECTRONIC SCIENCE AND TECHNOLOGY UNIV Effective date: 20150512 |
|
| C41 | Transfer of patent application or patent right or utility model | ||
| COR | Change of bibliographic data |
Free format text: CORRECT: ADDRESS; FROM: 310018 HANGZHOU, ZHEJIANG PROVINCE TO: 311100 HANGZHOU, ZHEJIANG PROVINCE |
|
| TR01 | Transfer of patent right |
Effective date of registration: 20150512 Address after: 615, room 1, No. 181, Wuchang Road, Yuhang District, Zhejiang, Hangzhou 311100, China Patentee after: HANGZHOU KUNTIAN AUTOMATION SYSTEM Co.,Ltd. Address before: Hangzhou City, Zhejiang province 310018 Xiasha Higher Education Park No. 2 street Patentee before: HANGZHOU DIANZI University |
|
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20120711 |