METHOD FOR PERFORMING A COOKING PROCESS ON THE BASIS OF A COOKING RECIPE INFORMATION

Abstract

The present invention relates to a method for performing a cooking process on a food product ready to be cooked on the basis of a cooking recipe information provided in a cooking recipe (10). At least one food model (30) is generated on the basis of the cooking recipe information and a database (14, 16, 20, 22, 26, 28). The cooking recipe (10) comprises at least one of the information about: —an ingredient, —a preparation step or process, —the shape of unprocessed food, and —composition, properties and condition of the food product. The database (14, 16, 20, 22, 26, 28) comprises information about ingredients and/or unprocessed food, which may be basic nutrient information of ingredients and/or unprocessed food, particularly information about content of at least one of: water, fat, carbohydrates and proteins. The database (14, 16, 20, 22, 26, 28) may also comprise, in addition or alternatively, information about at least one thermal property of the unprocessed food or food product ready to be cooked. If applicable, at least one thermal property of the food product ready to be cooked, in particular its density, thermal conductivity and/or heat capacity, is estimated on the basis of the cooking recipe information and the basic nutrient information. At least one cooking parameter of the cooking process, in particular temperature of the cooking equipment and/or environment, duration of a cooking program and/or program segment and/or program step, heating mode, etc., is defined based on the food model (30) and/or on at least the provided or estimated at least one thermal property of the food product.

Claims

1. A method for performing a cooking process on a food product on the basis of a cooking recipe information provided in a cooking recipe, wherein: at least one food model is generated on the basis of the cooking recipe information and a database, the cooking recipe information comprises at least one of information about: an ingredient, a preparation step or preparation process, a shape of unprocessed food, and composition, properties and condition of the food product, the database comprises information about ingredients and/or unprocessed food, including basic nutrient information thereof, said nutrient information comprising information about content of at least one of: water, fat, carbohydrates and proteins, and/or information about at least one thermal property of the food product, the at least one thermal property of the food product being selected from among its density, its thermal conductivity and/or its heat capacity and being estimated on the basis of the cooking recipe information and the basic nutrient information, if not already directly available from and provided by the database, and at least one cooking parameter of the cooking process selected from among a cooking temperature, a duration of a cooking program and/or program segment and/or program step, and/or a heating mode is defined based on at least the provided or estimated at least one thermal property of the food product.

2. The method according to claim 1, wherein the database includes information about a change of a cooking parameter and/or a property of an ingredient and/or of the food product during the cooking process and/or during the process of preparation of the food product.

3. The method according to claim 1, wherein the food model is, continuously or at discrete intervals, generated and/or adapted or updated during the cooking process by assistance of a user input and/or at least one detected parameter.

4. The method according to claim 3, wherein the detected parameter comprises the shape of the food product and/or the shape of the food product during the cooking process and/or a real temperature of the food product at a specific point in time during the cooking process.

5. The method according to claim 4, wherein the shape of the food product and/or of the food product during the cooking process is received by means of a 3D scanner and/or a camera, and/or by means of information extracted from a description and/or creation instruction in the cooking recipe and/or by means of a user input.

6. The method according to anyone of the preceding claim 1, wherein the food model is, continuously or at discrete intervals, generated and/or adapted or updated during the cooking process in consideration of information about an ingredient which influences a desired effect or change in the food product prior to or during the cooking process, said effect or change being selected from among denaturation of proteins, enzymatic activity, hydrolysis of connective tissue, formation of crumb structure and crust, browning kinetics, drying, breakdown of cell walls, leavening, and/or killing of bacteria.

7. The method according to claim 1, wherein the food model is, continuously or at discrete intervals, generated and/or adapted or updated during the cooking process in consideration of information about an amount or ratio of at least one gas incorporated in the food product due to a result or an effect of a preparation step or process and/or due to an influence of an ingredient and/or due to a chemical process, an amount or percentage or mass fraction of the at least one gas being continuously adapted or updated during the cooking process.

8. The method according to claim 7, wherein the amount or percentage or mass fraction of the at least one gas is considered in at least one formula calculating the at least one estimated thermal property of the food product.

9. The method according to claim 1, wherein at least one keyword is extracted from the cooking recipe and the food model is generated on the basis of the cooking recipe and at least one element of the database associated with the keyword, the database including at least one concordance list in which the keyword is associated with at least one element of the database.

10. The method according to claim 1, wherein at least one phrase is extracted from the cooking recipe wherein said phrase is associated with at least one element of the database, and wherein said phrase is tabled in a concordance list and associated therein with the at least one element of the database and/or is associated with at least one cooking parameter.

11. The method according to claim 1, wherein the at least one thermal property is calculated by a sum comprising summands of multipliers with different mass fractions selected from among carbohydrate mass fractions, protein mass fractions, fat mass fractions, mineral mass fractions, water mass fractions and air mass fractions.

12. The method according to claim 11, wherein at least one of the summands comprises a multiplier of carbohydrate mass fraction, fat mass fraction, water mass fraction or air mass fraction and further comprises a multiplier of the thermal property of a same molecule.

13. The method according to claim 12, wherein at least one thermal property of a water molecule and/or of an air gas mixture is a parabolic function over a temperature range and at least one thermal property of a fat molecule and/or carbohydrate molecule is a linear function over the temperature range.

14. The method according to claim 1, wherein the food model is adapted or adaptable to a specific cooking appliance by assistance of the database.

15. The method according to claim 1, wherein an amount of an ingredient provided without weight specification is converted into a standardized weight.

16. A cooking process comprising the following steps carried out by a cooking appliance: receiving over the Internet a cooking recipe for cooking a food product comprising recipe information, said recipe information comprising at least one of: identification of one or more ingredients for the food product, and a key word or phrase relating to the food product or to a said ingredient, or to a desired final property of the food product; comparing the recipe information to database information in one or more databases and generating a food model based on the recipe information and the database information, the food model comprising: an estimate of a mechanical or thermal property of the food product based on basic nutrient information for the food product contained within the database information, as well as a summand based on said keyword being correlated to said mechanical or thermal property in the database information, said mechanical or thermal property being selected from among density, shape, thermal conductivity and heat capacity, and a standardized weight for an amount of a said ingredient for the food product derived from the database information; continuously or successively updating the food model during the cooking process to reflect changes in said mechanical or thermal property that are either estimated from the database information or detected in the food product via a temperature sensor, a camera, or both; and adjusting a cooking parameter of the cooking appliance during the cooking process based on continuous or successive updates in the food model, said cooking parameter being selected from among cooking temperature, heating mode, and duration of a cooking step during the cooking process.

17. The cooking process according to claim 16, wherein the continuous or successive updates to said cooking model further are based on user inputs.

18. The cooking process according to claim 16, wherein the continuous or successive updates to said cooking model are based at least in part on updates to an amount or ratio of a gas in the food product during the cooking process, which gas is incorporated in the food product as a result of a preparation step, and/or due to an influence of said ingredient in the food product during the cooking process.

19. The cooking process according to claim 16, wherein said mechanical or thermal property is calculated by a sum comprising summands of multipliers with different mass fractions selected from among carbohydrate mass fractions, protein mass fractions, fat mass fractions, mineral mass fractions, water mass fractions and air mass fractions; at least one of the summands further comprises a multiplier of said mechanical or thermal property of a same biomolecule of the food product.

Description

[0041] The present invention will be described in further detail with reference to the drawing, in which

[0042] FIG. 1 illustrates a schematic flow chart diagram of a method for performing a cooking process on the basis of a cooking recipe according to a preferred embodiment of the present invention.

[0043] FIG. 1 illustrates a schematic flow chart diagram of a method for performing a cooking process on the basis of a cooking recipe 10 according to a preferred embodiment of the present invention. In this example, the cooking recipe 10 is downloaded from the internet and manipulated by a recipe deconstructor 12, a food model generator 18 and a cooking simulator 24.

[0044] The recipe deconstructor 12 is provided for scanning the cooking recipe for keywords. The recipe deconstructor 12 is connected to an ingredient database 14 and a cooking container database 16. The recipe deconstructor 12 provides further information about the food, e.g. the nutritional values, incorporated air and the shape by combing the extracted information from the recipe with the information of the connected databases 14, 16.

[0045] The food model generator 18 is connected to one or more conversion databases 20 and 22. The conversion databases 20 and 22 provide relationships between properties of the ingredients. The food model generator 18 considers information from the conversion databases 20 and 22.

[0046] The cooking simulator 24 is connected to an oven database 26 and a change database 28. The oven database 26 provides specific information about the used cooking oven and/or cooking hob. The change database 28 provides information about changes of the food during the cooking process. At last, a food model 30 is provided.

[0047] The food model 30 of the food described in the cooking recipe 10 is generated by evaluating the ingredients and processes. Since in most cooking recipes ingredients, time and temperature are used to achieve desired changes in or on the food, the food model 30 can be used to estimate best temperature, cooking time and heat transfer method in order to achieve the desired effects.

[0048] For example, some desired changes are a denaturation of proteins, e.g. in tender meat or egg, an enzymatic activity, e.g. in tender and tough meat, a hydrolysis of connective tissue, e.g. in tough meat, and a formation of crumb structure and crust, e.g. in bread or cake, browning kinetics, drying, breakdown of cell walls, e.g. in fruits or vegetables, leavening, e.g. in bread or cake, and killing of bacteria, e.g. in meat or fish.

[0049] The food model 30 according to the present invention is build up by comparing the ingredients in the cooking recipe 10 with a food database 14 containing the basic nutrient information, i.e. content of water, fat, carbohydrates and protein, in order to estimate the thermal and mechanical properties of the food, in particular density, heat conductivity and heat capacity.

[0050] Furthermore, the amount of the ingredients is converted to a standardized weight. For example, one egg has the standardized weight of 60 g and 100 ml oil has a standardized weight of 93 g.

[0051] On the basis of the ingredients like baking soda or yeast, the amount of incorporated gases, e.g. carbon dioxide or air, is added to the sum of the estimated thermal properties of the food. In a similar way, in processes described by phrases like “egg whites stiff” or “beat until fluffy”, the amount of incorporated gases, e.g. carbon dioxide or air, is added to the sum of the estimated thermal properties of the food in order to provide a simple thermal model substance for homogenous food.

[0052] Since the amounts of ingredients depend on the time, heat and substrate, the fraction of gases has to be continuously adapted for the model. For example, yeast produces more carbon dioxide at an optimum temperature and nutrient supply, e.g. freely available sugars for yeast digestion.

[0053] Keywords in the cooking recipe 10 may be used to categorise the food type in order to choose the structure of the food model 30. Examples of said keywords in relation to structure are “mix” or “knead” may be related to homogenous structure, “stack” or “layer” may be related to food with flat layers, “filling” or “stuffing” may be related to circular layered food. Further, the keywords in the cooking recipe 10 may be used to define desired thermal effects. For example, the keywords “bread” and “yeast” result in leavening of dough and, further, in a formation of crumb and crust.

[0054] The shape of the food model 30 can also be extracted from the description of the cooking recipe 10, e.g. type of baking tin. This information may also be described by the user or 3D scanned from the ready to be cooked food. For example, unbaked bread is put into the cooking oven and 3D scanned by a camera in a door handle, while the oven door is closed. Further, a 3D scanner in a cooker hood may scan the shape of roast in a pan.

[0055] Then, the food model 30 can be used to simulate different heat transfer scenarios based on information from the cooking oven. For example, the heating method of the cooking oven and the humidity and temperature inside the oven cavity are available. The simulation of the different heat transfer scenarios allows that the best result for the desired effects is obtained. Furthermore, ingredients that considerably affect the desired changes, e.g. sugar, egg, yolk on surface, available sugar for yeast, acid milieu for hydrolysis of collagen, are considered within the food model 30.

[0056] The food model 30 for the method according to the present invention is explained by way of two examples relating to a bread recipe and a roast beef recipe.

[0057] First example relating to the bread recipe:

[0058] The user with a high-end steam oven having a 3D scanning camera system imports a bread recipe from an internet cooking portal, wherein no leavening time is stated. Further, the cooking time and temperature are stated for a gas cooking oven. On the basis of the list of ingredients a homogenous food model is generated. Since the list of ingredients contains yeast and the keyword “bread” is found in the recipe, the proposed cooking method is a three-phase baking program.

[0059] In the first phase the bread is proofed at low temperatures with an initial steam boost in order to make the surface flexible and solve some starch to generate a starch water solution which develops a glossy crust during baking.

[0060] The second phase is the baking phase at high humidity and high temperature in order to get a closed crust and a fluffy crumb.

[0061] The third phase is performed at medium humidity and medium to high temperature in order to finish the bread based on the desired crust input of the user.

[0062] On the basis of the ingredients, e.g. amount of yeast or available sugars, the optimal cooking time, the temperature and the humidity of the first phase are set. The food model is constantly adapted due to the generation of gases, particularly air. The air is considered for the density, conductivity and heat capacity. Moreover, the air or other kind of gas is considered for adapting the shape of the food, e.g. spherical expansion or growing upward in tin. During the proofing of the bread the 3D scanning camera system monitors the growth of the dough.

[0063] The second phase is started when the desired volume of the bread is reached. The food model is used to calculate the change of the temperature distribution inside the bread based on gathered sensor information, e.g. oven temperature, humidity and/or shrinking of bread based on camera image, and the food model. An estimation of the time needed to achieve a full crumb formation is done.

[0064] The third phase is started before the crumb formation is finished. Depending on the desired crust input the cooking time and temperature of the third phase is set.

[0065] Second example relating to the roast beef recipe:

[0066] The user puts the roast beef into the oven cavity of the cooking oven and provides via application software or the user interface that the inserted food is a roast beef.

[0067] From the database the thermal properties of the roast beef are extracted. The user is asked to stick the food probe into the roast beef. The user is asked for the desired cooking degree of said roast beef and when the food should be finished.

[0068] The cooking oven starts heating the food. The size of the food is extracted on the basis of the thermal flow from the outside to the inside of said food, wherein the parameters on the outside are known from the cooking oven, while the parameters in the inside are known from the database and the food probe. The food model is built on the basis of the available data.

[0069] This food model is then used to obtain the best result in the time given by the user, by heating up the food to an optimal temperature depending on desired cooking degree. For the enzymatic activity, e.g. 40° C. to 60° C. for sarcoplasmic enzymes, the temperature is hold as long as possible. For example, the food model 30 for meat depends on the degree of “toughness”. In turn, said toughness depends substantially on type and age of said meat. For already tender meat according to “Modernist Cuisine” it is sufficient to reach the final temperature. For example, a medium tough cut like a flank can be kept at a temperature of 50° C. for three hours to get a firm texture, a temperature of 55° C. for twelve hours to get a tender texture and a temperature of 62° C. for thirty-six hours to get a flaky texture.

LIST OF REFERENCE NUMERALS

[0070] 10 cooking recipe from internet [0071] 12 recipe deconstructor [0072] 14 ingredient database [0073] 16 cooking container database [0074] 18 food model generator [0075] 20 conversion database [0076] 22 conversion database [0077] 24 cooking simulator [0078] 26 oven database [0079] 28 change database [0080] 30 food model