DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Remarks
This action is in response to the applicant’s response filed 16 March 2026, which is in response to the USPTO office action mailed 15 December 2025. Claims 1 and 11 are amended. Claims 12-17 are added. Claims 1-17 are currently pending.
Response to Arguments
With respect to the 35 USC §102 rejection of claims 1, 2, 5, 7 and 9-11 as well as the 35 USC §103 rejections of claims 3, 4, 6 and 8, the applicant’s arguments are moot in view of a new grounds of rejection, as necessitated by the applicant's amendments.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
This application includes one or more claim limitations that use the word “means” or “step” but are nonetheless not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph because the claim limitation(s) recite(s) sufficient structure, materials, or acts to entirely perform the recited function.
Such claim limitation(s) is/are: “a step of inputting”, “a step of transposing”, “a step of defining”, “a step of determining” and “a step of providing” in claims 1 and 12; “a step of entering” and “a step of optimizing” in claim 2; “a step of providing” in claim 10; and “a means of inputting”, “a means of transposing”, “a means of defining”, “a means of determining” and “a means of providing” in claim 11 and 17.
Because this/these claim limitation(s) is/are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are not being interpreted to cover only the corresponding structure, material, or acts described in the specification as performing the claimed function, and equivalents thereof.
If applicant intends to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to remove the structure, materials, or acts that performs the claimed function; or (2) present a sufficient showing that the claim limitation(s) does/do not recite sufficient structure, materials, or acts to perform the claimed function.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1, 2, 5, 7 and 9-17 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Pinel et al., US 9,519,620 B1 (hereinafter “Pinel”).
Claim 1: Pinel teaches a computer-implemented method to provide alternative flavor compositions, comprising:
- a step of inputting, upon a computer interface, at least two flavor ingredient digital identifier, the resulting input corresponding to a composition of flavor ingredients (Pinel, [Fig. 4] note 402-406, [Col. 11 Lines 64-67]-[Col. 12 Lines 1-5] note According to FIG. 4, a user may first input a set of ingredients 402—tortillas and chicken (e.g., via the query module 110 of FIG. 1). In some embodiments, the user input 202 may include entire recipes or other filters in addition or instead of tortillas and chicken (e.g., Mexican food, enchiladas only, no sour cream, etc.). In some embodiments, the user input 202 may correspond to the food ingredients that the user want substituted),
each ingredient digital identifier being associated with at least one equivalent constitutive molecule (Pinel, [Col. 3 Lines 19-22] note the term “chemical constituent(s)” may refer to the chemical composition that makes up a food ingredient/candidate food ingredient substitute such as one or more molecules),
each equivalent constitutive molecule being associated with at least one property (Pinel, [Col. 8 Lines 46-49] note chemical constituent datastore 226C may, in some embodiments, be a datastore that maps each food ingredient (or candidate food ingredient substitute) to the ingredient's/candidate's chemical constituents or properties),
- a step of transposing, by a computing system, the input composition into a list of equivalent constitutive molecules included in said composition and the quantity of each one of said equivalent constitutive molecules (Pinel, [Fig. 4] note 410, [Col. 12 Lines 40-58] note after each ingredient has been assigned to a class, the NLP system may identify the chemical constituents for one or more of the ingredients on the ingredient list 406… The chemical constituents of sour cream may include maltodextrin, sodium citrate, guar gum, carrageenan, calcium sulfate, locust bean gum potassium sorbate, whey, cultured milk, and cultured cream, [Col. 15 Lines 60-67]-[Col. 16 Lines 1-4] note a quantity or presence of a particular chemical constituents (e.g., moles of a particular molecules) within an old/source food ingredient… For example, the NLP system may determine (e.g., via the chemical constituent datastore 226C) that a dollop of sour cream contains a quantity of 200 potassium sorbate molecules),
- a step of defining, upon a computer interface, at least one reformulation rule to be applied to the list of transposed equivalent constitutive molecules obtained during a step of determining (Pinel, [Col. 12 Lines 3-5] note the user input 202 may correspond to the food ingredients that the user want substituted, [Col. 12 Line 67]-[Col. 13 Lines 1-6] note each substitute food ingredient candidate is chosen to be candidates for substitution based on meeting a threshold score or ranking (e.g., the substitute candidates share a threshold quantity of chemical compounds with sour cream). The NLP system may then score or rank each of the sour cream substitute candidates, [Fig. 6], [Col. 14 Lines 36-37] note score each of the candidate food ingredient substitutes),
- the step of determining, by a computing system, an alternative composition including at least one alternative flavor ingredient as a function of said at least one reformulation rule and said list of equivalent constitutive molecules, such that the resulting alternative composition includes equivalent constitutive molecules with same quantity as in said list (Pinel, [Col. 13 Lines 8-12] note As illustrated in the sour cream substitute candidate list 412, cottage cheese may be selected as the highest-ranked food ingredient substitute candidate and may therefore be included in the candidate recipe, which may include the new ingredient list 414, [Col. 16 Lines 1-14] note the NLP system may determine (e.g., via the chemical constituent datastore 226C) that a dollop of sour cream contains a quantity of 200 potassium sorbate molecules, whereas cottage cheese may contain 100 potassium sorbate molecules, and another second substitute ingredient candidate may contain only 80 potassium sorbate molecule. Accordingly, after comparing the quantities, cottage cheese may be scored higher than the second substitute ingredient candidate because cottage cheese may more closely match the quantity of potassium sorbate molecules contained in sour cream than the second substitute ingredient does. Therefore, cottage cheese may be ranked higher to be a substitute ingredient for sour cream), and
- a step of providing, upon a computer interface, the determined alternative composition of flavor ingredients (Pinel, [Col. 13 Lines 22-25] note Accordingly, a user may view each of the multiple candidate recipes and choose which recipe he or she will ultimately utilize for preparing and cooking a meal, [Col. 4 Lines 26-31] note present a graphical user interface (GUI) or other interface… to solicit queries from users for submission to one or more host devices 122 and to display answers/results obtained from the host devices 122 in relation to such user queries).
Claim 2: Pinel teaches the method according to claim 1, which comprises:
- a step of entering, upon a computer interface, at least one secondary reformulation rule to be applied on the alternative composition of flavor ingredients determined (Pinel, [Col. 5 Lines 46-56] note session manager 206 may keep track of user activity across sessions of interaction with the NLP system 212. Session manager 206 may also keep track of what inputs (e.g., ingredients) are submitted within the lifecycle of a session of a user. For example, session manager 206 may retain a succession of recipe restrictions posed by a user during a session (e.g., “find recipe with ‘chicken’ and ‘broccoli,’ but not ‘cheese’”). In some embodiments, preexisting recipes, newly generated recipes, and/or candidate food ingredient substitutes are produced by NLP system 212 in response to a user input),
- a step of optimizing, by a computer system, the alternative composition of flavor ingredients determined as a function of the entered at least one secondary reformulation rule (Pinel, [Col. 13 Lines 60-67]-[Col. 14 Lines 1-2] note the preparation or cooking instructions may also be changed based on the ingredients utilized for substitute in a newly generated recipe. For example, because cottage cheese is a substitute food ingredient for sour cream and because cottage cheese has more of a clumpy texture than sour cream, an additional preparation step may be added such as “heat” and/or “blend” the cottage cheese before combining it with the green chilies in order to make the cottage cheese have more of a smooth texture analogous to sour cream).
Claim 5: Pinel teaches the method according to claim 1, in which at least one reformulation rule is representative of a molecule availability of at least one equivalent constitutive molecule, each equivalent constitutive molecule being associated with at least one property representative of a molecule availability of said equivalent constitutive molecule (Pinel, [Col. 14 Lines 35-55] note The Jaccard index may be specifically utilized to measure overlap of two sets A and B (e.g., overlap or “shared” molecules between sour cream and yogurt). The Jaccard index is represented by the following formula: (A,B)=|A∩B|/|A∩B|. Therefore, the quantity of items (e.g., chemical constituents) that intersect or are shared between A and B are divided by the quantity of items in the union of A and B (e.g., the quantity of unique chemical molecules that makeup yogurt and sour cream)).
Claim 7: Pinel teaches the method according to claim 1, in which at least one reformulation rule is representative of an odor detection threshold of at least one equivalent constitutive molecule, each equivalent constitutive molecule being associated with at least one property representative of an odor detection threshold of said equivalent constitutive molecule (Pinel, [Col. 8 Lines 61-64] note each chemical constituent (or food ingredient/substitute food ingredient) may be mapped to a particular class of flavors, aromas, and/or textures in order to identify suitable candidate food ingredient substitutes).
Claim 9: Pinel teaches the method according to claim 1, in which each equivalent constitutive molecule is associated with at least one olfactory property, the step of determining being further performed as a function of at least one said olfactory property (Pinel, [Col. 8 Lines 61-64] note each chemical constituent (or food ingredient/substitute food ingredient) may be mapped to a particular class of flavors, aromas, and/or textures in order to identify suitable candidate food ingredient substitutes).
Claim 10: Pinel teaches the method according to claim 1, which comprises a step of providing, to an assembling device, an assembling command of the alternative composition of flavor ingredients (Pinel, [Col. 17 Lines 38-41] note the NLP system may then generate (e.g., via the result generator 228 of FIG. 2) a third set of recipes that include one or more substitute ingredients based on the determining in block 716, [Col. 7 Lines 64-67] note the result generator 228 may be a computer module that generates new recipes or obtains preexisting recipes, which include recipes that include food ingredient substitute ingredients).
Claim 11: Pinel teaches a system to provide alternative flavor compositions, comprising:
- means of inputting, upon a computer interface, at least two flavor ingredient digital identifier, the resulting input corresponding to a composition of flavor ingredients (Pinel, [Col. 11 Lines 64-67]-[Col. 12 Lines 1-5] note According to FIG. 4, a user may first input a set of ingredients 402—tortillas and chicken (e.g., via the query module 110 of FIG. 1). In some embodiments, the user input 202 may include entire recipes or other filters in addition or instead of tortillas and chicken (e.g., Mexican food, enchiladas only, no sour cream, etc.). In some embodiments, the user input 202 may correspond to the food ingredients that the user want substituted),
each ingredient digital identifier being associated with at least one equivalent constitutive molecule (Pinel, [Col. 3 Lines 19-22] note the term “chemical constituent(s)” may refer to the chemical composition that makes up a food ingredient/candidate food ingredient substitute such as one or more molecules),
each equivalent constitutive molecule being associated with at least one property (Pinel, [Col. 8 Lines 46-49] note chemical constituent datastore 226C may, in some embodiments, be a datastore that maps each food ingredient (or candidate food ingredient substitute) to the ingredient's/candidate's chemical constituents or properties),
- means of transposing, by a computing system, the input composition into a list of equivalent constitutive molecules included in said composition and the quantity of each one of said equivalent constitutive molecules (Pinel, [Fig. 4] note 410, [Col. 12 Lines 40-58] note after each ingredient has been assigned to a class, the NLP system may identify the chemical constituents for one or more of the ingredients on the ingredient list 406… The chemical constituents of sour cream may include maltodextrin, sodium citrate, guar gum, carrageenan, calcium sulfate, locust bean gum potassium sorbate, whey, cultured milk, and cultured cream, [Col. 15 Lines 60-67]-[Col. 16 Lines 1-4] note a quantity or presence of a particular chemical constituents (e.g., moles of a particular molecules) within an old/source food ingredient… For example, the NLP system may determine (e.g., via the chemical constituent datastore 226C) that a dollop of sour cream contains a quantity of 200 potassium sorbate molecules),
- means of defining, upon a computer interface, at least one reformulation rule to be applied to the list of transposed equivalent constitutive molecule obtained by means of determining (Pinel, [Col. 12 Lines 3-5] note the user input 202 may correspond to the food ingredients that the user want substituted, [Col. 12 Line 67]-[Col. 13 Lines 1-6] note each substitute food ingredient candidate is chosen to be candidates for substitution based on meeting a threshold score or ranking (e.g., the substitute candidates share a threshold quantity of chemical compounds with sour cream). The NLP system may then score or rank each of the sour cream substitute candidates, [Fig. 6], [Col. 14 Lines 36-37] note score each of the candidate food ingredient substitutes),
- said means of determining, by a computing system, an alternative composition including at least one alternative flavor ingredient as a function of said at least one reformulation rule said list of equivalent constitutive molecules, such that the resulting alternative composition includes equivalent constitutive molecules with same quantity as in said list (Pinel, [Col. 13 Lines 8-12] note As illustrated in the sour cream substitute candidate list 412, cottage cheese may be selected as the highest-ranked food ingredient substitute candidate and may therefore be included in the candidate recipe, which may include the new ingredient list 414, [Col. 16 Lines 1-14] note the NLP system may determine (e.g., via the chemical constituent datastore 226C) that a dollop of sour cream contains a quantity of 200 potassium sorbate molecules, whereas cottage cheese may contain 100 potassium sorbate molecules, and another second substitute ingredient candidate may contain only 80 potassium sorbate molecule. Accordingly, after comparing the quantities, cottage cheese may be scored higher than the second substitute ingredient candidate because cottage cheese may more closely match the quantity of potassium sorbate molecules contained in sour cream than the second substitute ingredient does. Therefore, cottage cheese may be ranked higher to be a substitute ingredient for sour cream), and
- means of providing, upon a computer interface, the determined alternative composition of flavor ingredients (Pinel, [Col. 13 Lines 22-25] note Accordingly, a user may view each of the multiple candidate recipes and choose which recipe he or she will ultimately utilize for preparing and cooking a meal, [Col. 4 Lines 26-31] note present a graphical user interface (GUI) or other interface… to solicit queries from users for submission to one or more host devices 122 and to display answers/results obtained from the host devices 122 in relation to such user queries).
Claim 12: Pinel teaches a computer-implemented method to provide alternative flavor compositions, characterized in that it comprises:
- a step of inputting, upon a computer interface, at least two flavor ingredient digital identifiers, the resulting input corresponding to a composition of flavor ingredients (Pinel, [Fig. 4] note 402-406, [Col. 11 Lines 64-67]-[Col. 12 Lines 1-5] note According to FIG. 4, a user may first input a set of ingredients 402—tortillas and chicken (e.g., via the query module 110 of FIG. 1). In some embodiments, the user input 202 may include entire recipes or other filters in addition or instead of tortillas and chicken (e.g., Mexican food, enchiladas only, no sour cream, etc.). In some embodiments, the user input 202 may correspond to the food ingredients that the user want substituted),
each ingredient digital identifier being associated with at least one equivalent constitutive molecule (Pinel, [Col. 3 Lines 19-22] note the term “chemical constituent(s)” may refer to the chemical composition that makes up a food ingredient/candidate food ingredient substitute such as one or more molecules),
each equivalent constitutive molecule being associated with at least one property (Pinel, [Col. 8 Lines 46-49] note chemical constituent datastore 226C may, in some embodiments, be a datastore that maps each food ingredient (or candidate food ingredient substitute) to the ingredient's/candidate's chemical constituents or properties),
- a step of transposing, by a computing system, the input composition into a list of equivalent constitutive molecules included in said composition and the quantity of each one of said equivalent constitutive molecules (Pinel, [Fig. 4] note 410, [Col. 12 Lines 40-58] note after each ingredient has been assigned to a class, the NLP system may identify the chemical constituents for one or more of the ingredients on the ingredient list 406… The chemical constituents of sour cream may include maltodextrin, sodium citrate, guar gum, carrageenan, calcium sulfate, locust bean gum potassium sorbate, whey, cultured milk, and cultured cream, [Col. 15 Lines 60-67]-[Col. 16 Lines 1-4] note a quantity or presence of a particular chemical constituents (e.g., moles of a particular molecules) within an old/source food ingredient… For example, the NLP system may determine (e.g., via the chemical constituent datastore 226C) that a dollop of sour cream contains a quantity of 200 potassium sorbate molecules),
- a step of defining, upon a computer interface, at least one reformulation rule to be applied to the list of transposed equivalent constitutive molecules obtained during a step of determining (Pinel, [Col. 12 Lines 3-5] note the user input 202 may correspond to the food ingredients that the user want substituted, [Col. 12 Line 67]-[Col. 13 Lines 1-6] note each substitute food ingredient candidate is chosen to be candidates for substitution based on meeting a threshold score or ranking (e.g., the substitute candidates share a threshold quantity of chemical compounds with sour cream). The NLP system may then score or rank each of the sour cream substitute candidates, [Fig. 6], [Col. 14 Lines 36-37] note score each of the candidate food ingredient substitutes),
- the step of determining, by a computing system, an alternative composition including at least one alternative flavor ingredient as a function of said at least one reformulation rule and said list of equivalent constitutive molecules, such that the resulting alternative composition includes equivalent constitutive molecules with same quantity as in said list (Pinel, [Col. 13 Lines 8-12] note As illustrated in the sour cream substitute candidate list 412, cottage cheese may be selected as the highest-ranked food ingredient substitute candidate and may therefore be included in the candidate recipe, which may include the new ingredient list 414, [Col. 16 Lines 1-14] note the NLP system may determine (e.g., via the chemical constituent datastore 226C) that a dollop of sour cream contains a quantity of 200 potassium sorbate molecules, whereas cottage cheese may contain 100 potassium sorbate molecules, and another second substitute ingredient candidate may contain only 80 potassium sorbate molecule. Accordingly, after comparing the quantities, cottage cheese may be scored higher than the second substitute ingredient candidate because cottage cheese may more closely match the quantity of potassium sorbate molecules contained in sour cream than the second substitute ingredient does. Therefore, cottage cheese may be ranked higher to be a substitute ingredient for sour cream), and
- a step of providing, upon a computer interface, the determined alternative composition of flavor ingredients (Pinel, [Col. 13 Lines 22-25] note Accordingly, a user may view each of the multiple candidate recipes and choose which recipe he or she will ultimately utilize for preparing and cooking a meal, [Col. 4 Lines 26-31] note present a graphical user interface (GUI) or other interface… to solicit queries from users for submission to one or more host devices 122 and to display answers/results obtained from the host devices 122 in relation to such user queries).
Claim 13: Pinel teaches the method according to claim 12, which comprises:
- a step of entering, upon a computer interface, at least one secondary reformulation rule to be applied on the alternative composition of flavor ingredients determined (Pinel, [Col. 5 Lines 46-56] note session manager 206 may keep track of user activity across sessions of interaction with the NLP system 212. Session manager 206 may also keep track of what inputs (e.g., ingredients) are submitted within the lifecycle of a session of a user. For example, session manager 206 may retain a succession of recipe restrictions posed by a user during a session (e.g., “find recipe with ‘chicken’ and ‘broccoli,’ but not ‘cheese’”). In some embodiments, preexisting recipes, newly generated recipes, and/or candidate food ingredient substitutes are produced by NLP system 212 in response to a user input),
- a step of optimizing, by a computer system, the alternative composition of flavor ingredients determined as a function of the entered at least one secondary reformulation rule (Pinel, [Col. 13 Lines 60-67]-[Col. 14 Lines 1-2] note the preparation or cooking instructions may also be changed based on the ingredients utilized for substitute in a newly generated recipe. For example, because cottage cheese is a substitute food ingredient for sour cream and because cottage cheese has more of a clumpy texture than sour cream, an additional preparation step may be added such as “heat” and/or “blend” the cottage cheese before combining it with the green chilies in order to make the cottage cheese have more of a smooth texture analogous to sour cream).
Claim 14: Pinel teaches the method according to claim 12, in which at least one reformulation rule is representative of:
- a geographical region of origin of at least one ingredient, each ingredient being associated with at least one property representative of a geographical region of origin of said ingredient, or - a molecule production ecological impact status of at least one equivalent constitutive molecule, each equivalent constitutive molecule being associated with at least one property representative of a molecule production ecological impact of said equivalent constitutive molecule, or - a molecule availability of at least one equivalent constitutive molecule, each equivalent constitutive molecule being associated with at least one property representative of a molecule availability of said equivalent constitutive molecule, or - a Henry constant of at least one equivalent constitutive molecule, each equivalent constitutive molecule being associated with at least one property representative of a Henry constant of said equivalent constitutive molecule, or - an odor detection threshold of at least one equivalent constitutive molecule, each equivalent constitutive molecule being associated with at least one property representative of an odor detection threshold of said equivalent constitutive molecule, or - a dose response curve of at least one equivalent constitutive molecule, each equivalent constitutive molecule being associated with at least one property representative of a dose response curve of said equivalent constitutive molecule (Pinel, [Col. 14 Lines 35-55] note The Jaccard index may be specifically utilized to measure overlap of two sets A and B (e.g., overlap or “shared” molecules between sour cream and yogurt). The Jaccard index is represented by the following formula: (A,B)=|A∩B|/|A∩B|. Therefore, the quantity of items (e.g., chemical constituents) that intersect or are shared between A and B are divided by the quantity of items in the union of A and B (e.g., the quantity of unique chemical molecules that makeup yogurt and sour cream)).
Claim 15: Pinel teaches the method according to claim 12, in which each equivalent constitutive molecule is associated with at least one olfactory property, the step of determining being further performed as a function of at least one said olfactory property (Pinel, [Col. 8 Lines 61-64] note each chemical constituent (or food ingredient/substitute food ingredient) may be mapped to a particular class of flavors, aromas, and/or textures in order to identify suitable candidate food ingredient substitutes).
Claim 16: Pinel teaches the method according to claim 12, which comprises a step of providing, to an assembling device, an assembling command of the alternative composition of flavor ingredients (Pinel, [Col. 17 Lines 38-41] note the NLP system may then generate (e.g., via the result generator 228 of FIG. 2) a third set of recipes that include one or more substitute ingredients based on the determining in block 716, [Col. 7 Lines 64-67] note the result generator 228 may be a computer module that generates new recipes or obtains preexisting recipes, which include recipes that include food ingredient substitute ingredients).
Claim 17: Pinel teaches a system to provide alternative flavor compositions, comprising:
- means of inputting, upon a computer interface, at least two flavor ingredient digital identifiers, the resulting input corresponding to a composition of flavor ingredients (Pinel, [Fig. 4] note 402-406, [Col. 11 Lines 64-67]-[Col. 12 Lines 1-5] note According to FIG. 4, a user may first input a set of ingredients 402—tortillas and chicken (e.g., via the query module 110 of FIG. 1). In some embodiments, the user input 202 may include entire recipes or other filters in addition or instead of tortillas and chicken (e.g., Mexican food, enchiladas only, no sour cream, etc.). In some embodiments, the user input 202 may correspond to the food ingredients that the user want substituted),
each ingredient digital identifier being associated with at least one equivalent constitutive molecule (Pinel, [Col. 3 Lines 19-22] note the term “chemical constituent(s)” may refer to the chemical composition that makes up a food ingredient/candidate food ingredient substitute such as one or more molecules),
each equivalent constitutive molecule being associated with at least one property (Pinel, [Col. 8 Lines 46-49] note chemical constituent datastore 226C may, in some embodiments, be a datastore that maps each food ingredient (or candidate food ingredient substitute) to the ingredient's/candidate's chemical constituents or properties),
- means of transposing, by a computing system, the input composition into a list of equivalent constitutive molecules included in said composition and the quantity of each one of said equivalent constitutive molecules (Pinel, [Fig. 4] note 410, [Col. 12 Lines 40-58] note after each ingredient has been assigned to a class, the NLP system may identify the chemical constituents for one or more of the ingredients on the ingredient list 406… The chemical constituents of sour cream may include maltodextrin, sodium citrate, guar gum, carrageenan, calcium sulfate, locust bean gum potassium sorbate, whey, cultured milk, and cultured cream, [Col. 15 Lines 60-67]-[Col. 16 Lines 1-4] note a quantity or presence of a particular chemical constituents (e.g., moles of a particular molecules) within an old/source food ingredient… For example, the NLP system may determine (e.g., via the chemical constituent datastore 226C) that a dollop of sour cream contains a quantity of 200 potassium sorbate molecules),
- means of defining, upon a computer interface, at least one reformulation rule to be applied to the list of transposed equivalent constitutive molecules obtained by means of determining (Pinel, [Col. 12 Lines 3-5] note the user input 202 may correspond to the food ingredients that the user want substituted, [Col. 12 Line 67]-[Col. 13 Lines 1-6] note each substitute food ingredient candidate is chosen to be candidates for substitution based on meeting a threshold score or ranking (e.g., the substitute candidates share a threshold quantity of chemical compounds with sour cream). The NLP system may then score or rank each of the sour cream substitute candidates, [Fig. 6], [Col. 14 Lines 36-37] note score each of the candidate food ingredient substitutes),
- said means of determining, by a computing system, an alternative composition including at least one alternative flavor ingredient as a function of said at least one reformulation rule and said list of equivalent constitutive molecules, such that the resulting alternative composition includes equivalent constitutive molecules with same quantity as in said list (Pinel, [Col. 13 Lines 8-12] note As illustrated in the sour cream substitute candidate list 412, cottage cheese may be selected as the highest-ranked food ingredient substitute candidate and may therefore be included in the candidate recipe, which may include the new ingredient list 414, [Col. 16 Lines 1-14] note the NLP system may determine (e.g., via the chemical constituent datastore 226C) that a dollop of sour cream contains a quantity of 200 potassium sorbate molecules, whereas cottage cheese may contain 100 potassium sorbate molecules, and another second substitute ingredient candidate may contain only 80 potassium sorbate molecule. Accordingly, after comparing the quantities, cottage cheese may be scored higher than the second substitute ingredient candidate because cottage cheese may more closely match the quantity of potassium sorbate molecules contained in sour cream than the second substitute ingredient does. Therefore, cottage cheese may be ranked higher to be a substitute ingredient for sour cream), and
- means of providing, upon a computer interface, the determined alternative composition of flavor ingredients (Pinel, [Col. 13 Lines 22-25] note Accordingly, a user may view each of the multiple candidate recipes and choose which recipe he or she will ultimately utilize for preparing and cooking a meal, [Col. 4 Lines 26-31] note present a graphical user interface (GUI) or other interface… to solicit queries from users for submission to one or more host devices 122 and to display answers/results obtained from the host devices 122 in relation to such user queries).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 3 and 4 are rejected under 35 U.S.C. 103 as being unpatentable over Pinel in view of Leifer et al., US 2019/0228855 A1 (hereinafter “Leifer”).
Claim 3: Pinel does not explicitly teach the method according to claim 1, in which at least one reformulation rule is representative of a geographical region of origin of at least one ingredient, each ingredient being associated with at least one property representative of a geographical region of origin of said ingredient.
However, Leifer teaches this (Leifer, [0008] note determining food substitution parameters based on the recipe database S120, [0019] note ingredient parameter set can additionally or alternatively include any other suitable ingredient-related characteristics (e.g., seasonality parameters, diet-related parameters such as nutrition information, origin parameters such as indications of organic, place of origin, sustainability parameters, etc.), [0033] note food substitution parameters can be associated with a probability that a health-related professional and/or other suitable entity… would agree that the food substitution is appropriate (e.g., according to any suitable optimization parameters, including taste parameters, dietary parameters, cost parameters, environmental sustainability parameters, perishability parameters, convenience parameters, etc.)).
It would have been obvious to one of ordinary skill in the art at the effective filing date of the application to combine the substitute ingredients of Pinel with the ingredient substitution parameters of Leifer according to known methods (i.e. determining ingredient substitutions based on origin parameters such as a place of origin). Motivation for doing so is that can function to improve food-related personalization for a user (Leifer, [0009]).
Claim 4: Pinel does not explicitly teach the method according to claim 1, in which at least one reformulation rule is representative of a molecule production ecological impact status of at least one equivalent constitutive molecule, each equivalent constitutive molecule being associated with at least one property representative of a molecule production ecological impact of said equivalent constitutive molecule.
However, Leifer teaches this (Leifer, [0008] note determining food substitution parameters based on the recipe database S120, [0019] note ingredient parameter set can additionally or alternatively include any other suitable ingredient-related characteristics (e.g., seasonality parameters, diet-related parameters such as nutrition information, origin parameters such as indications of organic, place of origin, sustainability parameters, etc.), [0033] note food substitution parameters can be associated with a probability that a health-related professional and/or other suitable entity… would agree that the food substitution is appropriate (e.g., according to any suitable optimization parameters, including taste parameters, dietary parameters, cost parameters, environmental sustainability parameters, perishability parameters, convenience parameters, etc.)).
It would have been obvious to one of ordinary skill in the art at the effective filing date of the application to combine the substitute ingredients of Pinel with the ingredient substitution parameters of Leifer according to known methods (i.e. determining ingredient substitutions based environmental sustainability parameters). Motivation for doing so is that can function to improve food-related personalization for a user (Leifer, [0009]).
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Pinel in view of Stanton, US 2012/0101862 A1 (hereinafter “Stanton”).
Claim 6: Pinel does not explicitly teach the method according to claim 1, in which at least one reformulation rule is representative of a Henry constant of at least one equivalent constitutive molecule, each equivalent constitutive molecule being associated with at least one property representative of a Henry constant of said equivalent constitutive molecule.
However, Stanton teaches this (Stanton, [0005] note designing consumer products and selected components for use in consumer products, [0006] note “consumer products” includes… food products, [0014] note A process, of selecting a consumer product component for use in a consumer product, that may comprise: [0015] a) comparing two or more independent properties of an actual or hypothetical initial consumer product component with the same independent properties of one or more actual or hypothetical additional consumer product components, [0041] note molecular similarity analysis, [0075] a.) correlating a dependent property of an initial consumer product component, [0086] note In said first aspect of said modelling method, said dependent property may be selected from the group consisting of component… Henrys Law constants).
It would have been obvious to one of ordinary skill in the art at the effective filing date of the application to combine the ingredient substitution of Pinel with the consumer product design of Stanton according to known methods (i.e. substituting ingredients based on dependent properties including Henry’s Law constants). Motivation for doing so is that allows for efficient multidimensional modeling systems (Stanton, [0003]).
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Pinel in view of Neumann, US 12,001,796 B2 (hereinafter “Neumann”).
Claim 8: Pinel does not explicitly teach the method according to claim 1, in which at least one reformulation rule is representative of a dose response curve of at least one equivalent constitutive molecule, each equivalent constitutive molecule being associated with at least one property representative of a dose response curve of said equivalent constitutive molecule.
However, Neumann teaches this (Neumann, [Col. 3 Lines 56-57] note the nutrient target may contain a recommended dose and/or time limit for consumption, [Col. 9 Lines 28-31] note information pertaining to which ingredients may be substituted for one another due to allergies, intolerances, dislikes and the like may be stored and contained within ingredient database, [Fig. 7], [Col. 19 Lines 7-15] note target profile A 704 may be prepared and calculated for a user. In such an instance, target profile A 704 may contain one or more recommended nutrient intakes for a first user. For instance, and without limitation, target profile A 704 may recommend a user to consume 100 mg/day of calcium. In an embodiment, target profile A 704 may contain one or more recommend nutrient intakes for a specified period of time, such as the recommended intake per meal, per day, per week, and the like).
It would have been obvious to one of ordinary skill in the art at the effective filing date of the application to combine the ingredient substation of Pinel with the ingredient substitutions based on recommended nutrient intakes of Neumann according to known methods (i.e. substituting ingredients based on a target recommended nutrient intake for a specified period of time). Motivation for doing so is that may allow the user to avoid nutrient deficiencies/excess (Neumann, [Col. 5 Lines 27-30]), thereby improving the user’s health.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/GIUSEPPI GIULIANI/Primary Examiner, Art Unit 2153
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