Method, system and computer software to automatically formulate an animal feed additive composition

Abstract

The method to automatically formulate an animal feed additive composition, comprises the steps of: - selecting (105) a livestock category indicator, said livestock category indicator being associated with at least one targeted nutrient digestibility index, - defining (110) an animal feed composition representation, comprising at least one raw feed material indicator, - converting (115) the defined animal feed composition representation into an equivalent nutrient feed composition representation, comprising at least one nutrient indicator, - determining (120) a quantity of undigested nutrients, - calculating (125) an animal feed additive composition, and - providing (130), upon a computer interface, the animal feed additive composition calculated.

Description

[0001] METHOD, SYSTEM AND COMPUTER SOFTWARE TO AUTOMATICALLY

[0002] FORMULATE AN ANIMAL FEED ADDITIVE COMPOSITION

[0003] TECHNICAL FIELD OF THE INVENTION

[0004] The present invention aims at a method to automatically formulate an animal feed additive composition, a system to automatically formulate an animal feed additive composition and a computer software to automatically formulate an animal feed additive composition.

[0005] It applies, in particular, to the industry of animal feed additive preparation.

[0006] BACKGROUND OF THE INVENTION

[0007] In the field of enzyme composition formulation for improving the digestibility of animal feed, several significant challenges remain unsolved today.

[0008] In current approaches, feed compositions are initially performed by feed producers or by feedstock exploitations directly. These feed compositions are then provided to animal feed additive composition laboratories, which formulate the appropriate animal feed additive composition based on extensive laboratory work. Such an animal feed additive composition is formed of at least one enzyme.

[0009] Feed enzymes in animal feed have been used by feed producers for a long time. Some enzymes required by animal metabolisms are either not produced by said metabolisms or not secreted to a sufficient extent by today’s superior animal breeds. Therefore, feed enzymes increase the utilization of certain nutrients already present in raw materials used in animal feeds but not usable by the animal's metabolism.

[0010] The main difficulty in feed additive composition formulation is that enzymes typically interact with several nutrients, thus inducing non-linear effects when mixed together, in which one enzyme can become an antagonist for the reaction produced by another enzyme.

[0011] This leads to either significant feed additive composition formulation time and calculation, when data relative to the animal feed is available, or to a trial-and-error based approach. These difficulties are further compounded by the fact that each species presents a different metabolism. As such, there is a challenge to formulate efficient enzymes across different species and diets. Animals have diverse dietary requirements and digestive systems, and an enzyme effective in one species may not work as well in another. Moreover, the composition of the feed itself can vary greatly, from grain-based to forage-based diets, each with its own set of complexities. Typically, enzyme blends are designed to be broadly effective across these variations, which leads to subpar performance upon specific species taken in isolation.

[0012] There is a need, today, to optimize enzyme efficacy, stability, and costeffectiveness while ensuring safety and regulatory compliance.

[0013] SUMMARY OF THE INVENTION

[0014] The present invention aims at addressing all or part of these drawbacks.

[0015] According to a first aspect, the present invention aims at a method to automatically formulate an animal feed additive composition, comprising the steps of:

[0016] - selecting, upon a computer interface, a livestock category indicator, said livestock category indicator bijectively corresponding to a physical category of livestock, each livestock category indicator being associated with a nutrient feed digestibility index, said livestock category indicator being associated with at least one targeted nutrient digestibility index,

[0017] - defining, upon a computer interface, an animal feed composition representation, comprising at least one raw feed material indicator, said raw material indicator bijectively corresponding to a physical raw feed material, said animal feed composition representation bijectively corresponding to a physical animal feed composition,

[0018] - converting, by a computing device, the defined animal feed composition representation into an equivalent nutrient feed composition representation, comprising at least one nutrient indicator, said nutrient representation bijectively corresponding to a physical nutrient, said nutrient feed composition representation bijectively corresponding to a physical nutrient feed composition,

[0019] - determining, by a computing device, a quantity of undigested nutrients, or metabolically unprocessed nutrients, in the equivalent nutrient feed composition as a function of at least one nutrient indicator and, for said nutrient indicator, the corresponding nutrient feed digestibility index for the selected livestock category indicator,

[0020] - calculating, by a computing device, an animal feed additive composition, as a function of the determined quantity of undigested nutrients and at least one targeted nutrient digestibility index, said animal feed additive composition comprising at least one enzyme indicator, each enzyme indicator being associated with a digestibility index of at least one nutrient, said enzyme indicator bijectively corresponding to a physical enzyme, said animal feed additive composition representation bijectively corresponding to a physical animal feed additive composition, and

[0021] - providing, upon a computer interface, the animal feed additive composition calculated.

[0022] Such provisions allow for the optimal formulation of an animal feed additive composition which optimizes nutrient digestibility by a determined category of feedstock (species). Such provisions save considerable time in formulating the most adapted animal additive composition. Such provisions further limit the need for labor-intensive formulation as well as limit the requirements for trial-and-error experimentation to determine the most adapted animal feed.

[0023] Furthermore, typically, in current systems, feed producers are required to reveal the feed composition to the animal feed additive composition producer, which is typically confidential information. This leads to partial information transfer which leads to suboptimal animal feed additive composition formulation. By providing accounts that are specifically provided to and held by individual users, said users are enabled to explore, test and use systems implementing the method of the invention in a confidential manner. For instance, feed producers can test and assess such systems without revealing their confidential feed composition to an animal feed additive composition producer.

[0024] In particular embodiments, the method object of the present further comprises a step of translating, by a computing device, the undigested nutrients in the equivalent nutrient feed composition representation into a list of at least one enzymatic activity to be performed upon the undigested nutrients as a function of nutrient indicators and of at least one targeted nutrient digestibility index, the step of calculating being executed as a function of at least one translated enzymatic activity, at least one enzyme indicator being associated with at least one enzymatic activity.

[0025] Such embodiments further optimize the quality of the provided animal feed additive composition.

[0026] In particular embodiments, several animal feed additive compositions are calculated, the method object of the present invention further comprising a step of selecting, upon a computer interface, a calculated animal feed additive composition as a function of the number of enzyme indicators associated with said animal feed additive composition.

[0027] Such embodiments further optimize the provided animal feed additive composition by limiting the complexity (and usually therefore cost) of said animal feed additive composition.

[0028] In particular embodiments, at least one animal feed additive composition comprises several enzyme indicators.

[0029] Such embodiments further optimize the provided animal feed additive composition by favoring, with one feed, several enzymatic activities by the targeted metabolism.

[0030] In particular embodiments, the method object of the present further comprises a step of selecting, upon a computer interface, at least one enzyme indicator associated with the provided animal feed additive composition, said method further comprising a step of recalculating, by a computing device, an adapted animal feed additive composition which comprises said selected at least one enzyme indicator and at least one other enzyme indicator determined as a function of the determined quantity of undigested nutrients, said selected at least one enzyme indicator and at least one targeted nutrient digestibility index.

[0031] Such embodiments further optimize the provided animal feed additive composition by allowing for dynamic reformulation based on user input.

[0032] In particular embodiments, the method object of the present further comprises a step of constituting a database of nutrient digestibility index, for at least one livestock category indicator, as a function of empirical measurements performed upon corresponding subjects of said livestock category, said database of nutrient digestibility index being used during the step of selecting a livestock category indicator.

[0033] In particular embodiments, the method object of the present further comprises a step of constituting a database of raw material to nutrient indicator correspondence, as a function of empirical measurements performed upon corresponding raw material, said database of nutrient digestibility index being used during the step of converting.

[0034] In particular embodiments, the method object of the present further comprises a step of constituting a database of enzyme indicator to nutrient digestibility index, as a function of empirical measurements performed upon corresponding enzymes, said database of digestibility index being used during the step of calculating.

[0035] In particular embodiments, the method object of the present further comprises a step of physically assembling the provided animal feed additive composition and / or a step of transmitting a command to a device, said command being representative of a command of assembling the provided animal feed additive composition.

[0036] According to a second aspect, the present invention aims at a system to automatically formulate an animal feed additive composition, comprising:

[0037] - one or more processors; and

[0038] - one or more non-transitory computer-readable media that collectively store instructions that, when executed by the one or more processors, cause the computing system to perform operations, the instructions being representative of steps of:

[0039] - selecting, upon a computer interface, a livestock category indicator, said livestock category indicator bijectively corresponding to a physical category of livestock, each livestock category indicator being associated with a nutrient feed digestibility index, said livestock category indicator being associated with at least one targeted nutrient digestibility index,

[0040] - defining, upon a computer interface, an animal feed composition representation, comprising at least one raw feed material indicator, said raw material indicator bijectively corresponding to a physical raw feed material, said animal feed composition representation bijectively corresponding to a physical animal feed composition, - converting, by a computing device, the defined animal feed composition representation into an equivalent nutrient feed composition representation, comprising at least one nutrient indicator, said nutrient representation bijectively corresponding to a physical nutrient, said nutrient feed composition representation bijectively corresponding to a physical nutrient feed composition,

[0041] - determining, by a computing device, a quantity of undigested nutrients in the equivalent nutrient feed composition as a function of at least one nutrient indicator and, for said nutrient indicator, the corresponding nutrient feed digestibility index for the selected livestock category indicator,

[0042] - calculating, by a computing device, an animal feed additive composition, as a function of the determined quantity of undigested nutrients and at least one targeted nutrient digestibility index, said animal feed additive composition comprising at least one enzyme indicator, each enzyme indicator being associated with a digestibility index of at least one nutrient, said enzyme indicator bijectively corresponding to a physical enzyme, said animal feed additive composition representation bijectively corresponding to a physical animal feed additive composition, and

[0043] - providing, upon a computer interface, the animal feed additive composition calculated.

[0044] According to a third aspect, the present invention aims at a computer-readable media that collectively store instructions that, when executed by one or more processors, cause a computing system to perform operations, the instructions being representative of steps of:

[0045] - selecting, upon a computer interface, a livestock category indicator, said livestock category indicator bijectively corresponding to a physical category of livestock, each livestock category indicator being associated with a nutrient feed digestibility index, said livestock category indicator being associated with at least one targeted nutrient digestibility index,

[0046] - defining, upon a computer interface, an animal feed composition representation, comprising at least one raw feed material indicator, said raw material indicator bijectively corresponding to a physical raw feed material, said animal feed composition representation bijectively corresponding to a physical animal feed composition,

[0047] - converting, by a computing device, the defined animal feed composition representation into an equivalent nutrient feed composition representation, comprising at least one nutrient indicator, said nutrient representation bijectively corresponding to a physical nutrient, said nutrient feed composition representation bijectively corresponding to a physical nutrient feed composition,

[0048] - determining, by a computing device, a quantity of undigested nutrients in the equivalent nutrient feed composition as a function of at least one nutrient indicator and, for said nutrient indicator, the corresponding nutrient feed digestibility index for the selected livestock category indicator,

[0049] - calculating, by a computing device, an animal feed additive composition, as a function of the determined quantity of undigested nutrients and at least one targeted nutrient digestibility index, said animal feed additive composition comprising at least one enzyme indicator, each enzyme indicator being associated with a digestibility index of at least one nutrient, said enzyme indicator bijectively corresponding to a physical enzyme, said animal feed additive composition representation bijectively corresponding to a physical animal feed additive composition, and

[0050] - providing, upon a computer interface, the animal feed additive composition calculated.

[0051] According to a fourth aspect, the present invention aims at a computer software, comprising a set of instructions that, when executed by one or more processors, cause a computing system to perform operations, the instructions being representative of steps of:

[0052] - selecting, upon a computer interface, a livestock category indicator, said livestock category indicator bijectively corresponding to a physical category of livestock, each livestock category indicator being associated with a nutrient feed digestibility index, said livestock category indicator being associated with at least one targeted nutrient digestibility index, - defining, upon a computer interface, an animal feed composition representation, comprising at least one raw feed material indicator, said raw material indicator bijectively corresponding to a physical raw feed material, said animal feed composition representation bijectively corresponding to a physical animal feed composition,

[0053] - converting, by a computing device, the defined animal feed composition representation into an equivalent nutrient feed composition representation, comprising at least one nutrient indicator, said nutrient representation bijectively corresponding to a physical nutrient, said nutrient feed composition representation bijectively corresponding to a physical nutrient feed composition,

[0054] - determining, by a computing device, a quantity of undigested nutrients in the equivalent nutrient feed composition as a function of at least one nutrient indicator and, for said nutrient indicator, the corresponding nutrient feed digestibility index for the selected livestock category indicator,

[0055] - calculating, by a computing device, an animal feed additive composition, as a function of the determined quantity of undigested nutrients and at least one targeted nutrient digestibility index, said animal feed additive composition comprising at least one enzyme indicator, each enzyme indicator being associated with a digestibility index of at least one nutrient, said enzyme indicator bijectively corresponding to a physical enzyme, said animal feed additive composition representation bijectively corresponding to a physical animal feed additive composition, and

[0056] - providing, upon a computer interface, the animal feed additive composition calculated.

[0057] BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Other advantages, purposes and particular characteristics of the invention shall be apparent from the following non-exhaustive description of at least one particular embodiment or succession of steps of the present invention, in relation to the drawings annexed hereto, in which: - Figure 1 shows, schematically, a first particular succession of steps of the method object of the present invention,

[0059] - Figure 2 shows, schematically, a particular embodiment of the system object of the present invention.

[0060] DETAILED DESCRIPTION OF THE INVENTION

[0061] This description is not exhaustive, as each feature of one embodiment may be combined with any other feature of any other embodiment in an advantageous manner.

[0062] Various inventive concepts may be embodied as one or more methods, of which an example has been provided. The acts performed as part of the method may be ordered in any suitable way. Accordingly, embodiments may be constructed in which acts are performed in an order different than illustrated, which may include performing some acts simultaneously, even though shown as sequential acts in illustrative embodiments.

[0063] The phrase “and / or,” as used herein in the specification and in the claims, should be understood to mean “either or both” of the elements so conjoined, i.e. , elements that are conjunctively present in some cases and disjunctively present in other cases. Multiple elements listed with “and / or” should be construed in the same fashion, i.e., “one or more” of the elements so conjoined. Other elements may optionally be present other than the elements specifically identified by the “and / or” clause, whether related or unrelated to those elements specifically identified. Thus, as a non-limiting example, a reference to “A and / or B”, when used in conjunction with open-ended language such as “comprising” can refer, in one embodiment, to A only (optionally including elements other than B); in another embodiment, to B only (optionally including elements other than A); in yet another embodiment, to both A and B (optionally including other elements); etc.

[0064] As used herein in the specification and in the claims, “or” should be understood to have the same meaning as “and / or” as defined above. For example, when separating items in a list, “or” or “and / or” shall be interpreted as being inclusive, i.e., the inclusion of at least one, but also including more than one of a number or lists of elements, and, optionally, additional unlisted items. Only terms clearly indicated to the contrary, such as “only one of’ or “exactly one of,” or, when used in the claims, “consisting of,” will refer to the inclusion of exactly one element of a number or list of elements. In general, the term “or” as used herein shall only be interpreted as indicating exclusive alternatives (i.e. , “one or the other but not both”) when preceded by terms of exclusivity, such as “either,” “one of,” “only one of,” or “exactly one of.” “Consisting essentially of,” when used in the claims, shall have its ordinary meaning as used in the field of patent law.

[0065] As used herein in the specification and in the claims, the phrase “at least one,” in reference to a list of one or more elements, should be understood to mean at least one element selected from any one or more of the elements in the list of elements, but not necessarily including at least one of each and every element specifically listed within the list of elements and not excluding any combinations of elements in the list of elements. This definition also allows that elements may optionally be present other than the elements specifically identified within the list of elements to which the phrase “at least one” refers, whether related or unrelated to those elements specifically identified. Thus, as a non-limiting example, “at least one of A and B” (or, equivalently, “at least one of A or B,” or, equivalently “at least one of A and / or B”) can refer, in one embodiment, to at least one, optionally including more than one, A, with no B present (and optionally including elements other than B); in another embodiment, to at least one, optionally including more than one, B, with no A present (and optionally including elements other than A); in yet another embodiment, to at least one, optionally including more than one, A, and at least one, optionally including more than one, B (and optionally including other elements); etc.

[0066] In the claims, as well as in the specification above, all transitional phrases such as “comprising,” “including,” “carrying,” “having,” “containing,” “involving,” “holding,” “composed of,” and the like are to be understood to be open-ended, i.e., to mean including but not limited to. Only the transitional phrases “consisting of’ and “consisting essentially of” shall be closed or semi-closed transitional phrases, respectively.

[0067] It should be noted at this point that the figures are not to scale.

[0068] As used herein, the terms “means of inputting” or “computer interface” is, for example, a keyboard, mouse and / or touchscreen adapted to interact with a computing system in such a way to collect user input. In variants, the means of inputting are logical in nature, such as a network port of a computing system configured to receive an input command transmitted electronically. Such an input means may be associated to a GUI (Graphic User Interface) shown to a user or an API (Application programming interface). In other variants, the means of inputting may be a sensor configured to measure a specified physical parameter relevant for the intended use case.

[0069] As used herein, the terms “computing system” or “computer system” designate any electronic calculation device, whether unitary or distributed, capable of receiving numerical inputs and providing numerical outputs by and to any sort of interface, digital and / or analog. Typically, a computing system designates either a computer executing a software having access to data storage or a client-server architecture wherein the data and / or calculation is performed at the server side while the client side acts as an interface.

[0070] As used herein, the terms “indicator” refers to any computerized identifier, such as one used in a computer database, representing a physical object, such an enzyme for example. An indicator may refer to a label representative of the name, chemical structure, or internal reference of said enzyme, for example.

[0071] In the present description, the term “physical” is intended as existing outside of the digital environment of the present invention. “Physical” may mean, for example, readily found in nature or synthesized in a laboratory or chemical plant. In any event, a physical composition presents a tangible reality. The term “assembling” refers to the act of materialization of a composition, whether via extraction and assembly of ingredients or via synthetization and assembly of ingredients.

[0072] In the present description, the terms “animal feed composition” refer to a mixture of feed raw materials, whether processed, semi-processed, or raw, which is intended for consumption by animals and contributes to their nutritional needs. The primary goal of animal feed is to provide animals with nutrients that are necessary for maintaining good health, growth, reproduction, and production performance (like milk in dairy animals or eggs in poultry). Animal feed typically comprises a variety of ingredients, or raw materials, that collectively meet the nutritional requirements of the target animal species. These requirements vary depending on the species, age, health status, and production goals of the animal. The major components of animal feed include:

[0073] - macronutrients, such as:

[0074] - proteins: essential for growth, tissue repair, and overall health. Sources can include plant-based materials like soybean meal, or animal-based sources like fish meal, - carbohydrates: provide energy and are found in ingredients like grains (com, wheat, barley) and by-products of the food industry, and / or

[0075] - fats and oils: also, energy sources, and important for the absorption of fatsoluble vitamins,

[0076] - micronutrients, such as:

[0077] - vitamins: necessary in small quantities for various physiological functions, and / or

[0078] - minerals: essential for bone development, nerve function, and numerous metabolic processes, and / or

[0079] - fiber, which are important for digestive health and is found in components like hay, straw, and certain by-products of crops.

[0080] In the present description, the term “livestock” refers to domesticated animals raised in an agricultural setting to produce commodities such as food, fiber, labor, and other products. The term encompasses, but is not limited to, species such as cattle (both dairy and beef), swine (pigs), poultry (including chickens, turkeys, ducks, and geese), sheep, goats, horses, and other equines. Livestock also includes animals farmed for non- traditional purposes or products, such as deer, rabbits, and other species that may be relevant to the scope and application of the disclosed invention. These animals are characterized by their role in agricultural production and are typically reared in environments ranging from small holdings to large, industrial-scale farming operations. The definition of 'livestock' as used herein encompasses these animals at all stages of their life cycle, including but not limited to, juveniles, adults, and breeding stock. It is also inclusive of both conventional and genetically modified species, as well as any subspecies or breeds within the aforementioned categories. This term is utilized in the context of the invention to specify the intended use or application of the disclosed methods, processes, compositions, or apparatuses in relation to the care, feeding, breeding, management, and production of these animals.

[0081] In the present description, the term “raw material” refers to any natural, processed, or synthetic substance, compound, or mixture thereof used in the formulation, preparation, or manufacture of feed for livestock. This term encompasses a wide range of materials including, but not limited to, grains (such as com, wheat, barley, and oats), oilseeds (like soybeans and canola), forages (including hay, silage, and pasture grasses), by-products of the agricultural and food processing industries (such as molasses, distillers grains, and beet pulp), protein sources (like fish meal, bone meal, and legumes), minerals, vitamins, amino acids, enzymes, and other nutritional or functional additives.

[0082] In the present description, the term “nutrient” refers to refers to any substance that provides nourishment essential for the growth and maintenance of life. Nutrients are components of food that are needed by an organism to provide energy, support growth, and maintain and repair body tissues. This term encompasses both macronutrients and micronutrients.

[0083] Macronutrients include carbohydrates, proteins, and fats, which are required in relatively large quantities and serve as the primary source of energy and the building blocks for growth and repair. Carbohydrates, composed of sugars, starches, and fibers, are primary energy sources. Proteins, made up of amino acids, are essential for building and repairing muscles, tissues, enzymes, hormones, and other crucial body components. Fats, including saturated, unsaturated, and polyunsaturated fats, are vital for energy, cell growth, and the protection of organs.

[0084] Micronutrients, required in smaller quantities, are vitamins and minerals that are crucial for healthy growth, development, and functioning of the body's systems. Vitamins are organic compounds that are necessary for various metabolic processes and prevention of certain disorders. Minerals, including elements like calcium, iron, and potassium, are inorganic compounds needed for processes such as bone formation, oxygen transport, and nerve signaling.

[0085] In some embodiments, the term 'nutrient' may also encompass other dietary components that contribute to health and well-being, such as water, phytonutrients, and certain non-digestible substances like dietary fiber that are beneficial for digestion.

[0086] In the present description, the term “enzyme” refers to refers to a biological molecule, typically a protein or RNA molecule, that acts as a catalyst to induce a specific biochemical reaction. Enzymes are characterized by their ability to increase the rate of virtually all the chemical reactions that take place within cells, thereby playing a critical role in various metabolic processes. Each enzyme is selective for its substrate, which is the reactant molecule that is transformed in the reaction and can be highly specific for the particular chemical reaction that it catalyzes. This specificity is due to the unique three-dimensional structure of the enzyme, particularly the active site, which precisely fits and interacts with the substrate.

[0087] Enzymes function under a range of environmental conditions related to factors such as temperature, pH, and the presence of cofactors or coenzymes. These conditions affect the enzyme's activity and stability and are considered in the application and manipulation of enzymes in industrial, medical, and research contexts.

[0088] Within the scope of this document, the term 'enzyme' includes naturally occurring enzymes, synthetically produced enzymes, and modified enzymes, which include but are not limited to genetically engineered or recombinant enzymes. The term also encompasses enzyme derivatives, such as enzyme complexes, conjugates, and immobilized enzymes, that retain catalytic activity and are suitable for specific applications as described herein.

[0089] In the present description, the term “activity” or “enzymatic activity” refers to refers to the functional ability of an enzyme to catalyze a chemical reaction. This activity is specific to the type of enzyme and is characterized by the transformation of substrates (reactants) into products through a series of biochemical reactions facilitated by the enzyme.

[0090] Enzymatic activity is quantified based on the rate at which a substrate is converted to a product, often measured under controlled conditions such as optimal temperature, pH, and substrate concentration. This rate, also known as the reaction velocity, is indicative of the efficiency and effectiveness of the enzyme. Enzymatic activity is influenced by various factors including enzyme concentration, presence of cofactors or inhibitors, environmental conditions like temperature and pH, and the physical state of the enzyme (such as solubility and stability).

[0091] Within the scope of this document, 'enzymatic activity' encompasses both the natural catalytic functions of enzymes as well as modified, enhanced, or inhibited activities resulting from genetic, chemical, or physical modifications to the enzyme or its environment. This includes, but is not limited to, activities in isolated, purified, synthetic, or immobilized enzyme forms. The term is intended to cover a wide range of applications where enzymatic reactions are utilized, including but not limited to industrial processing, biotechnology, pharmaceuticals, environmental applications, and analytical and diagnostic methodologies. Measurement and modulation of enzymatic activity are critical aspects in these applications, especially where the efficacy, specificity, and selectivity of the enzyme are of paramount importance.

[0092] The definition of 'enzymatic activity' as used herein is designed to be comprehensive, covering all forms and manifestations of enzyme-catalyzed reactions relevant to the field of the invention.

[0093] Such enzymatic activities can be, for example:

[0094] - cellulase activity for enhanced fiber digestion: enzymes exhibiting cellulase activity catalyze the breakdown of cellulose, a major component of plant cell walls, into simpler sugars,

[0095] - phytase activity for improved phosphorus utilization: phytases are enzymes that catalyze the hydrolysis of phytate, a common form of phosphorus in plant-based feeds, into inorganic phosphate,

[0096] - protease activity for protein optimization: proteases are enzymes that break down proteins into smaller peptides and amino acids,

[0097] - amylase activity for starch breakdown: amylases catalyze the breakdown of starch into simpler sugars like dextrose and maltose, and / or

[0098] - lipase activity for fat digestion: lipases catalyze the hydrolysis of fats into glycerol and fatty acids.

[0099] Figure 1 shows a particular succession of steps of the method 100 object of the present invention. This method 100 to automatically formulate an animal feed additive composition comprises the steps of:

[0100] - selecting 105, upon a computer interface, a livestock category indicator, said livestock category indicator bijectively corresponding to a physical category of livestock, each livestock category indicator being associated with a nutrient feed digestibility index, said livestock category indicator being associated with at least one targeted nutrient digestibility index, - defining 110, upon a computer interface, an animal feed composition representation, comprising at least one raw feed material indicator, said raw material indicator bijectively corresponding to a physical raw feed material, said animal feed composition representation bijectively corresponding to a physical animal feed composition,

[0101] - converting 115, by a computing device, the defined animal feed composition representation into an equivalent nutrient feed composition representation, comprising at least one nutrient indicator, said nutrient representation bijectively corresponding to a physical nutrient, said nutrient feed composition representation bijectively corresponding to a physical nutrient feed composition,

[0102] - determining 120, by a computing device, a quantity of undigested nutrients in the equivalent nutrient feed composition as a function of at least one nutrient indicator and, for said nutrient indicator, the corresponding nutrient feed digestibility index for the selected livestock category indicator,

[0103] - calculating 125, by a computing device, an animal feed additive composition, as a function of the determined quantity of undigested nutrients and at least one targeted nutrient digestibility index, said animal feed additive composition comprising at least one enzyme indicator, each enzyme indicator being associated with a digestibility index of at least one nutrient, said enzyme indicator bijectively corresponding to a physical enzyme, said animal feed additive composition representation bijectively corresponding to a physical animal feed additive composition, and

[0104] - providing 130, upon a computer interface, the animal feed additive composition calculated.

[0105] The step of selecting 105 a livestock category indicator can be performed automatically or manually.

[0106] In automatic embodiments, during this step of selecting 105, a selection command is received from a computing system, via a computer network (such as the internet for example). Such systems may use, for example, application programming interfaces (“API”). In such embodiments, the selection is performed by a computing device as a result of user interaction or as a result of the execution of an algorithm which presents, as an output, a livestock category indicator selection.

[0107] In manual embodiments, during this step of selecting 105, a selection is performed by a user via an input device 240, such as disclosed in regard to figure 2. In such embodiments, this input device 240 is typically associated with a graphic user interface (“GUI”) which is displayed upon a computer screen or any output other device 235 relevant to the particular use case of implementation of the present invention.

[0108] In such a GUI, a user may be prompted to select, from a list of selectable livestock category indicators, at least one livestock category indicator. Such a list of livestock category indicator may correspond to a list of livestock breeds, such as, for example, cow, chicken, turkey, ducks, geese, guinea fowls, quails, pigeons, equines, horses, mules, donkeys, camels, llama, alpacas, pigs, cattle, sheep, goats, ruminants, poultry, swine, finfish, shellfish, fresh water fish, salt water fish, shrimp, etc.

[0109] In other variants, a livestock category indicator is defined by a number of digestion- related and / or metabolism-related parameters, for which individual values may be preset or set by a user, thus defining a personalized livestock category indicator. Such digestion- related parameters may be, for example, a digestibility index for at least one nutrient or raw material, corresponding to the maximum digestibility for said nutrient or raw material.

[0110] In preferred embodiments, each livestock category indicator is associated, in a computer memory such as a database, with at least one targeted nutrient digestibility index or with at least one raw material nutrient digestibility. Such a digestibility index may correspond to a percentage of nutrient or raw material and corresponds to the ability of metabolisms of the animals of the livestock category to process said nutrient or raw materials.

[0111] Such a digestibility index may be obtained by empirical experimentation wherein, for a determined livestock category, the percentage of undigested raw material or nutrients is measured for a determined amount of raw material or nutrient fed to at least one animal of the determined livestock category. Such measured values may then be stored in a database and post-processed, algorithmically, to obtain statistical values representative of the distribution of measurements (such as the mean and standard deviation), for example. In particular embodiments, the method 100 object of the present invention comprises a step of constituting 155 a database of nutrient digestibility index, for at least one livestock category indicator, as a function of empirical measurements performed upon corresponding subjects of said livestock category, said database of nutrient digestibility index being used during the step of selecting a livestock category indicator.

[0112] The step of defining 110 an animal feed composition can be performed automatically or manually.

[0113] In automatic embodiments, during this step of designing 110, a definition command is received from a computing system, via a computer network (such as the internet for example). Such systems may use, for example, application programming interfaces (“API”). In such embodiments, the definition is performed by a computing device as a result of user interaction or as a result of the execution of an algorithm which presents, as an output, animal feed composition representation.

[0114] In manual embodiments, during this step of defining 110, a selection is performed by a user via an input device 240, such as disclosed in regard to figure 2. In such embodiments, this input device 240 is typically associated with a graphic user interface (“GUI”) which is displayed upon a computer screen or any output other device 235 relevant to the particular use case of implementation of the present invention.

[0115] In such a GUI, a user may be prompted to select, from a list of selectable raw feed material indicators, at least one raw feed material indicator. Such a list of raw feed material indicators may correspond to a list of raw materials, such as, for example, bakery by-product, barley, beans, blood meal, canola meal I rapeseed meal, cassava meal, copra meal, com, com germ meal, com gluten feed, com gluten meal, cottonseed meal, DDGS com, DDGS wheat, feather meal, fishmeal, full fat soy, groundnut meal, guar meal, lard and coconut oil, lupins, meat bone meal, meat meal, millet pearl, oats, palm kernal meal, peas, poultry by-product, poultry fat, rapeseed, rice bran de-oiled, rice bran full-fat, rice broken, rice DDGS, rice polishings, rye, sesame meal, sorghum, soy, soy bean meal, soy expelled, soya concentrate, sunflower meal, tallow, vegetable oil, wheat, wheat bran, wheat middlings, whey powder.

[0116] In preferred embodiments, during the step 110 of defining, a quantity for at least one raw feed material may be determined. For example, a user may be prompted, after selecting a raw feed material indicator, to provide a quantity for the corresponding raw feed material represented by such an indicator. Such a quantity may be measured in absolute (kg) or relative (%) terms. By default, a raw feed material may be associated with a default quantity, which, in relative terms, may correspond to 100% divided by the number of selected raw feed material indicators.

[0117] The step of converting 115 is performed, for example, by instructions representative of a computer software executed upon a computing device, such as shown in figure 2. During this step of converting 115, each defined raw material indicator is converted into equivalent nutrient indicators. Such a conversation may be performed on the basis of a conversion table, which may be stored in a computer memory such as a database, said conversion table providing, for a set of raw material indicators, corresponding nutrient indicators.

[0118] In preferred embodiments, during the step of converting 115, at least one raw material indicator is converted into equivalent nutrient indicators and associated, for at least one equivalent nutrient indicator, with an equivalent nutrient quantity.

[0119] Such a conversion table may be obtained by empirical experimentation wherein, for a determined raw material, a nutrient composition analysis is performed to measure values relative to the presence and / or quantity of a list of targeted nutrients in said determined raw material. Such measured values may then be stored in a database and post-processed, algorithmically, to obtain statistical values representative of the distribution of measurements (such as the mean and standard deviation), for example.

[0120] It should be noted that the relationship between raw material and nutrients are not exclusive: several raw materials can comprise the same nutrient and several nutrients can form one raw material.

[0121] In particular embodiments, the method 100 object of the present invention comprises a step of constituting 160 a database of raw material to nutrient indicator correspondence, as a function of empirical measurements performed upon corresponding raw material, said database of nutrient digestibility index being used during the step of converting. At the end of this step of converting 115, the animal feed composition representation is associated with a list of nutrient indicators and, preferably, with associated quantities.

[0122] The step of determining 120 is performed, for example, by instructions representative of a computer software executed upon a computing device, such as shown in figure 2. During this step of determining 120, the feed digestibility index associated with the selected feedstock category indicator is used as a multiplier on the equivalent nutrient feed composition representation to determine a quantity (relative or absolute) of undigested nutrients in the animal feed composition. It should be noted that the digestibility index can correspond to a plurality of values for a list of nutrients. Therefore, the appropriate digestibility index is applied to the related nutrient in order to assess, for said nutrient, the undigested quantity of said ingredient.

[0123] At the end of this step of determining 120, the undigested quantities for each nutrient represent potential sources of metabolization by the animal.

[0124] The step of calculating 125 is performed, for example, by instructions representative of a computer software executed upon a computing device, such as shown in figure 2. During the step of calculating 125, undigested nutrients are considered as substrates for enzymes. During the step of calculating 125, a computing device is made to solve an optimization problem in which the objective is to reduce the number, and preferably quantity, of undigested nutrients. To solve this optimization problem, an enzyme to nutrient interaction table, stored in a computer memory such as a database, may be used. This table stores positive and negative interactions with metabolic activities, each metabolic activities potentially involving consumption of nutrients. Such metabolic activities may further be impacted by the livestock category in which said metabolic activities occur.

[0125] During the step of calculating 125, the problem to be solved corresponds to a system of equations, for each nutrient, wherein, for each nutrient, a positive or negative interaction is modelled by a positive or negative coefficient applied to the quantity of an enzyme. At the end of the step of calculating 125, quantities of enzymes that solve the optimization problem are converted into a list of enzyme indicators, preferably with the associated quantities.

[0126] In particular embodiments, the method 100 object of the present invention comprises a step of constituting 165 a database of enzyme indicator to nutrient digestibility index, as a function of empirical measurements performed upon corresponding enzymes, said database of digestibility index being used during the step of calculating 125.

[0127] During the step of providing 130, an output device 240, such as disclosed in figure 2, may be used to show the calculated animal feed additive composition representation upon a GUI. Alternatively, this animal feed additive composition representation may be transferred via a computer network, through an API for example.

[0128] In particular embodiments, the method 100 object of the present invention further comprises a step of translating 135, by a computing device, the undigested nutrients in the equivalent nutrient feed composition representation into a list of at least one enzymatic activity to be performed upon the undigested nutrients as a function of nutrient indicators and of at least one targeted nutrient digestibility index, the step of calculating 125 being executed as a function of at least one translated enzymatic activity, at least one enzyme indicator being associated with at least one enzymatic activity.

[0129] In particular embodiments, animal feed additive compositions are calculated, the method further comprising a step of selecting 140, upon a computer interface, a calculated animal feed additive composition as a function of the number of enzyme indicators associated with said animal feed additive composition.

[0130] In such embodiments, considering the optimization problem solved, there can exist several animal feed additive compositions that satisfy the optimization problem. All or part of these animal feed additive compositions can be provided during the step of providing 130. An eligibility threshold may be set, such as a maximum total amount of undigested nutrients not processed by the animal feed additive composition which, if met, removes the animal feed additive composition from the list of eligible animal feed additive compositions to be provided. In particular embodiments, at least one animal feed additive composition comprises several enzyme indicators.

[0131] In particular embodiments, the method 100 object of the present invention comprises a step of selecting 145, upon a computer interface, at least one enzyme indicator associated with the provided animal feed additive composition, said method further comprising a step of recalculating 150, by a computing device, an adapted animal feed additive composition which comprises said selected at least one enzyme indicator and at least one other enzyme indicator determined as a function of the determined quantity of undigested nutrients, said selected at least one enzyme indicator and at least one targeted nutrient digestibility index.

[0132] The step of selecting 145 may be performed automatically or manually. In automatic embodiments, this selection may correspond to a selection command sent as a result of user interaction or as a result of the execution of an algorithm.

[0133] In manual embodiments, an input device 240 such as shown in figure 2 may be used in conjunction with a GUI to allow for a user to select at least one enzyme indicator provided during the step 130 of providing. Once the selection is complete, the step of recalculating 150 is executed.

[0134] This step of recalculating 150 is performed similarly to the step of calculating 130, with the added optimization limitation that the selected enzyme indicators must be used to solve the optimization problem.

[0135] It should be noted that the selection of an enzyme indicator may correspond to the selection of only the corresponding enzyme or to the corresponding enzyme and associated enzyme quantity in the animal feed additive composition.

[0136] In particular embodiments, the method 100 object of the present invention comprises a step 170 of physically assembling the provided animal feed additive composition and / or a step 175 of transmitting a command to a device, said command being representative of a command of assembling the provided animal feed additive composition.

[0137] The step 170 of physically assembling the animal feed additive composition may be performed in a variety of ways suited for the proper assembly and transport of the animal feed additive composition. The step 175 of transmitting a command may be performed, for example, by a computer software configured to be executed by a computing device. Such a transmission may use a computer network, for example, of any type suited for the particular implementation use case.

[0138] Figure 2 shows, schematically, a particular embodiment of the system object of the present invention. This system to automatically formulate an animal feed additive composition, comprises:

[0139] - one or more processors; and

[0140] - one or more non-transitory computer-readable media that collectively store instructions that, when executed by the one or more processors, cause the computing system to perform operations, the instructions being representative of steps of:

[0141] - selecting, upon a computer interface, a livestock category indicator, said livestock category indicator bijectively corresponding to a physical category of livestock, each livestock category indicator being associated with a nutrient feed digestibility index, said livestock category indicator being associated with at least one targeted nutrient digestibility index,

[0142] - defining, upon a computer interface, an animal feed composition representation, comprising at least one raw feed material indicator, said raw material indicator bijectively corresponding to a physical raw feed material, said animal feed composition representation bijectively corresponding to a physical animal feed composition,

[0143] - converting, by a computing device, the defined animal feed composition representation into an equivalent nutrient feed composition representation, comprising at least one nutrient indicator, said nutrient representation bijectively corresponding to a physical nutrient, said nutrient feed composition representation bijectively corresponding to a physical nutrient feed composition,

[0144] - determining, by a computing device, a quantity of undigested nutrients in the equivalent nutrient feed composition as a function of at least one nutrient indicator and, for said nutrient indicator, the corresponding nutrient feed digestibility index for the selected livestock category indicator,

[0145] - calculating, by a computing device, an animal feed additive composition, as a function of the determined quantity of undigested nutrients and at least one targeted nutrient digestibility index, said animal feed additive composition comprising at least one enzyme indicator, each enzyme indicator being associated with a digestibility index of at least one nutrient, said enzyme indicator bijectively corresponding to a physical enzyme, said animal feed additive composition representation bijectively corresponding to a physical animal feed additive composition, and

[0146] - providing, upon a computer interface, the animal feed additive composition calculated.

[0147] Figure 2 represents a block diagram that illustrates an example computer system with which an embodiment of the system and / or the method object of the present invention may be implemented. In the example of figure 2, a computer system 205 and instructions for implementing the disclosed technologies in hardware, software, or a combination of hardware and software, are represented schematically, for example as boxes and circles, at the same level of detail that is commonly used by persons of ordinary skill in the art to which this disclosure pertains for communicating about computer architecture and computer systems implementations.

[0148] The computer system 205 includes an input / output (IO) subsystem 220 which may include a bus and / or other communication mechanism(s) for communicating information and / or instructions between the components of the computer system 205 over electronic signal paths. The I / O subsystem 220 may include an I / O controller, a memory controller and at least one I / O port. The electronic signal paths are represented schematically in the drawings, for example as lines, unidirectional arrows, or bidirectional arrows.

[0149] At least one hardware processor 210 is coupled to the I / O subsystem 220 for processing information and instructions. Hardware processor 210 may include, for example, a general-purpose microprocessor or microcontroller and / or a special-purpose microprocessor such as an embedded system or a graphics processing unit (GPU) or a digital signal processor or ARM processor. Processor 210 may comprise an integrated arithmetic logic unit (ALU) or may be coupled to a separate ALU.

[0150] Computer system 205 includes one or more units of memory 225, such as a main memory, which is coupled to I / O subsystem 220 for electronically digitally storing data and instructions to be executed by processor 210. Memory 225 may include volatile memory such as various forms of random-access memory (RAM) or other dynamic storage device. Memory 225 also may be used for storing temporary variables or other intermediate information during execution of instructions to be executed by processor 210. Such instructions, when stored in non-transitory computer-readable storage media accessible to processor 210, can render computer system 205 into a special-purpose machine that is customized to perform the operations specified in the instructions.

[0151] Computer system 205 further includes non-volatile memory such as read only memory (ROM) 230 or other static storage device coupled to the I / O subsystem 220 for storing information and instructions for processor 210. The ROM 230 may include various forms of programmable ROM (PROM) such as erasable PROM (EPROM) or electrically erasable PROM (EEPROM). A unit of persistent storage 215 may include various forms of non-volatile RAM (NVRAM), such as FLASH memory, or solid-state storage, magnetic disk, or optical disk such as CD-ROM or DVD-ROM and may be coupled to I / O subsystem 220 for storing information and instructions. Storage 215 is an example of a non-transitory computer-readable medium that may be used to store instructions and data which when executed by the processor 210 cause performing computer-implemented methods to execute the techniques herein.

[0152] The instructions in memory 225, ROM 230 or storage 215 may comprise one or more sets of instructions that are organized as modules, methods, objects, functions, routines, or calls. The instructions may be organized as one or more computer programs, operating system services, or application programs including mobile apps. The instructions may comprise an operating system and / or system software; one or more libraries to support multimedia, programming or other functions; data protocol instructions or stacks to implement TCP / IP, HTTP or other communication protocols; file format processing instructions to parse or render files coded using HTML, XML, JPEG, MPEG or PNG; user interface instructions to render or interpret commands for a graphical user interface (GUI), command-line interface or text user interface; application software such as an office suite, internet access applications, design and manufacturing applications, graphics applications, audio applications, software engineering applications, educational applications, games or miscellaneous applications. The instructions may implement a web server, web application server or web client. The instructions may be organized as a presentation layer, application layer and data storage layer such as a relational database system using structured query language (SQL) or no SQL, an object store, a graph database, a flat file system or other data storage.

[0153] Computer system 205 may be coupled via I / O subsystem 220 to at least one output device 235. In one embodiment, output device 235 is a digital computer display. Examples of a display that may be used in various embodiments include a touch screen display or a light-emitting diode (LED) display or a liquid crystal display (LCD) or an e- paper display. Computer system 205 may include other type(s) of output devices 235, alternatively or in addition to a display device. Examples of other output devices 235 include printers, ticket printers, plotters, projectors, sound cards or video cards, speakers, buzzers or piezoelectric devices or other audible devices, lamps or LED or LCD indicators, haptic devices, actuators, or servos.

[0154] At least one input device 240 is coupled to I / O subsystem 220 for communicating signals, data, command selections or gestures to processor 210. Examples of input devices 240 include touch screens, microphones, still and video digital cameras, alphanumeric and other keys, keypads, keyboards, graphics tablets, image scanners, joysticks, clocks, switches, buttons, dials, slides.

[0155] Another type of input device is a control device 245, which may perform cursor control or other automated control functions such as navigation in a graphical interface on a display screen, alternatively or in addition to input functions. Control device 245 may be a touchpad, a mouse, a trackball, or cursor direction keys for communicating direction information and command selections to processor 210 and for controlling cursor movement on display 235. The input device may have at least two degrees of freedom in two axes, a first axis (e.g., x) and a second axis (e.g., y), that allows the device to specify positions in a plane. Another type of input device is a wired, wireless, or optical control device such as a joystick, wand, console, steering wheel, pedal, gearshift mechanism or other type of control device. An input device 240 may include a combination of multiple different input devices, such as a video camera and a depth sensor.

[0156] In another embodiment, computer system 205 may comprise an internet of things (loT) device in which one or more of the output device 235, input device 240, and control device 245 are omitted. Or, in such an embodiment, the input device 240 may comprise one or more cameras, motion detectors, thermometers, microphones, seismic detectors, other sensors or detectors, measurement devices or encoders and the output device 235 may comprise a special-purpose display such as a single-line LED or LCD display, one or more indicators, a display panel, a meter, a valve, a solenoid, an actuator or a servo.

[0157] Computer system 205 may implement the techniques described herein using customized hard-wired logic, at least one ASIC or FPGA, firmware and / or program instructions or logic which when loaded and used or executed in combination with the computer system causes or programs the computer system to operate as a specialpurpose machine. According to one embodiment, the techniques herein are performed by computer system 205 in response to processor 210 executing at least one sequence of at least one instruction contained in main memory 225. Such instructions may be read into main memory 225 from another storage medium, such as storage 215. Execution of the sequences of instructions contained in main memory 225 causes processor 210 to perform the process steps described herein. In alternative embodiments, hard-wired circuitry may be used in place of or in combination with software instructions.

[0158] The term “storage media” as used herein refers to any non-transitory media that store data and / or instructions that cause a machine to operation in a specific fashion. Such storage media may comprise non-volatile media and / or volatile media. Non-volatile media includes, for example, optical or magnetic disks, such as storage 215. Volatile media includes dynamic memory, such as memory 225. Common forms of storage media include, for example, a hard disk, solid state drive, flash drive, magnetic data storage medium, any optical or physical data storage medium, memory chip, or the like.

[0159] Storage media is distinct from but may be used in conjunction with transmission media. Transmission media participates in transferring information between storage media. For example, transmission media includes coaxial cables, copper wire and fiber optics, including the wires that comprise a bus of I / O subsystem 220. Transmission media can also take the form of acoustic or light waves, such as those generated during radiowave and infra-red data communications.

[0160] Various forms of media may be involved in carrying at least one sequence of at least one instruction to processor 210 for execution. For example, the instructions may initially be carried on a magnetic disk or solid-state drive of a remote computer. The remote computer can load the instructions into its dynamic memory and send the instructions over a communication link such as a fiber optic or coaxial cable or telephone line using a modem. A modem or router local to computer system 205 can receive the data on the communication link and convert the data to a format that can be read by computer system 205. For instance, a receiver such as a radio frequency antenna or an infrared detector can receive the data carried in a wireless or optical signal and appropriate circuitry can provide the data to I / O subsystem 220 such as place the data on a bus. I / O subsystem 220 carries the data to memory 225, from which processor 210 retrieves and executes the instructions. The instructions received by memory 225 may optionally be stored on storage 215 either before or after execution by processor 210.

[0161] Computer system 205 also includes a communication interface 260 coupled to bus 220. Communication interface 260 provides a two-way data communication coupling to network link(s) 265 that are directly or indirectly connected to at least one communication networks, such as a network 270 or a public or private cloud on the Internet. For example, communication interface 260 may be an Ethernet networking interface, integrated- services digital network (ISDN) card, cable modem, satellite modem, or a modem to provide a data communication connection to a corresponding type of communications line, for example an Ethernet cable or a metal cable of any kind or a fiber-optic line or a telephone line. Network 270 broadly represents a local area network (LAN), wide-area network (WAN), campus network, internetwork, or any combination thereof. Communication interface 260 may comprise a LAN card to provide a data communication connection to a compatible LAN, or a cellular radiotelephone interface that is wired to send or receive cellular data according to cellular radiotelephone wireless networking standards, or a satellite radio interface that is wired to send or receive digital data according to satellite wireless networking standards. In any such implementation, communication interface 260 sends and receives electrical, electromagnetic, or optical signals over signal paths that carry digital data streams representing various types of information.

[0162] Network link 265 typically provides electrical, electromagnetic, or optical data communication directly or through at least one network to other data devices, using, for example, satellite, cellular, Wi-Fi, or BLUETOOTH technology. For example, network link 265 may provide a connection through a network 270 to a host computer 250.

[0163] Furthermore, network link 265 may provide a connection through network 270 or to other computing devices via internetworking devices and / or computers that are operated by an Internet Service Provider (ISP) 275. ISP 275 provides data communication services through a world-wide packet data communication network represented as internet 280. A server computer 255 may be coupled to internet 280. Server 255 broadly represents any computer, data center, virtual machine, or virtual computing instance with or without a hypervisor, or computer executing a containerized program system such as DOCKER or KUBERNETES. Server 255 may represent an electronic digital service that is implemented using more than one computer or instance and that is accessed and used by transmitting web services requests, uniform resource locator (URL) strings with parameters in HTTP payloads, API calls, app services calls, or other service calls. Computer system 205 and server 255 may form elements of a distributed computing system that includes other computers, a processing cluster, server farm or other organization of computers that cooperate to perform tasks or execute applications or services. Server 255 may comprise one or more sets of instructions that are organized as modules, methods, objects, functions, routines, or calls. The instructions may be organized as one or more computer programs, operating system services, or application programs including mobile apps. The instructions may comprise an operating system and / or system software; one or more libraries to support multimedia, programming or other functions; data protocol instructions or stacks to implement TCP / IP, HTTP or other communication protocols; file format processing instructions to parse or render files coded using HTML, XML, JPEG, MPEG or PNG; user interface instructions to render or interpret commands for a graphical user interface (GUI), command-line interface or text user interface; application software such as an office suite, internet access applications, design and manufacturing applications, graphics applications, audio applications, software engineering applications, educational applications, games or miscellaneous applications. Server 255 may comprise a web application server that hosts a presentation layer, application layer and data storage layer such as a relational database system using structured query language (SQL) or no SQL, an object store, a graph database, a flat file system or other data storage.

[0164] Computer system 205 can send messages and receive data and instructions, including program code, through the network(s), network link 265 and communication interface 260. In the Internet example, a server 255 might transmit a requested code for an application program through Internet 280, ISP 275, local network 270 and communication interface 260. The received code may be executed by processor 210 as it is received, and / or stored in storage 215, or other non-volatile storage for later execution.

[0165] The execution of instructions as described in this section may implement a process in the form of an instance of a computer program that is being executed and consisting of program code and its current activity. Depending on the operating system (OS), a process may be made up of multiple threads of execution that execute instructions concurrently. In this context, a computer program is a passive collection of instructions, while a process may be the actual execution of those instructions. Several processes may be associated with the same program; for example, opening up several instances of the same program often means more than one process is being executed. Multitasking may be implemented to allow multiple processes to share processor 210. While each processor 210 or core of the processor executes a single task at a time, computer system 205 may be programmed to implement multitasking to allow each processor to switch between tasks that are being executed without having to wait for each task to finish. In an embodiment, switches may be performed when tasks perform input / output operations, when a task indicates that it can be switched, or on hardware interrupts. Time-sharing may be implemented to allow fast response for interactive user applications by rapidly performing context switches to provide the appearance of concurrent execution of multiple processes simultaneously. In an embodiment, for security and reliability, an operating system may prevent direct communication between independent processes, providing strictly mediated and controlled inter-process communication functionality. A particular use of the system 200 object of the present invention is disclosed in regard to figure 1 .

Claims

CLAIMS1. Method (100) to automatically formulate an animal feed additive composition, characterized in that it comprises the steps of:- selecting (105), upon a computer interface, a livestock category indicator, said livestock category indicator bijectively corresponding to a physical category of livestock, each livestock category indicator being associated with a nutrient feed digestibility index, said livestock category indicator being associated with at least one targeted nutrient digestibility index,- defining (110), upon a computer interface, an animal feed composition representation, comprising at least one raw feed material indicator, said raw material indicator bijectively corresponding to a physical raw feed material, said animal feed composition representation bijectively corresponding to a physical animal feed composition,- converting (115), by a computing device, the defined animal feed composition representation into an equivalent nutrient feed composition representation, comprising at least one nutrient indicator, said nutrient representation bijectively corresponding to a physical nutrient, said nutrient feed composition representation bijectively corresponding to a physical nutrient feed composition,- determining (120), by a computing device, a quantity of undigested nutrients in the equivalent nutrient feed composition as a function of at least one nutrient indicator and, for said nutrient indicator, the corresponding nutrient feed digestibility index for the selected livestock category indicator,- calculating (125), by a computing device, an animal feed additive composition, as a function of the determined quantity of undigested nutrients and at least one targeted nutrient digestibility index, said animal feed additive composition comprising at least one enzyme indicator, each enzyme indicator being associated with a digestibility index of at least one nutrient, said enzyme indicator bijectively corresponding to a physical enzyme, said animal feed additive composition representation bijectively corresponding to a physical animal feed additive composition, andproviding (130), upon a computer interface, the animal feed additive composition calculated.

2. Method (100) according to claim 1 , which further comprises a step of translating (135), by a computing device, the undigested nutrients in the equivalent nutrient feed composition representation into a list of at least one enzymatic activity to be performed upon the undigested nutrients as a function of nutrient indicators and of at least one targeted nutrient digestibility index, the step of calculating (125) being executed as a function of at least one translated enzymatic activity, at least one enzyme indicator being associated with at least one enzymatic activity.

3. Method (100) according to any one of claims 1 or 2, in which several animal feed additive compositions are calculated, the method further comprising a step of selecting (140), upon a computer interface, a calculated animal feed additive composition as a function of the number of enzyme indicators associated with said animal feed additive composition.

4. Method (100) according to any one of claims 1 to 3, in which at least one animal feed additive composition comprises several enzyme indicators.

5. Method (100) according to claim 4, which comprises a step of selecting (145), upon a computer interface, at least one enzyme indicator associated with the provided animal feed additive composition, said method further comprising a step of recalculating (150), by a computing device, an adapted animal feed additive composition which comprises said selected at least one enzyme indicator and at least one other enzyme indicator determined as a function of the determined quantity of undigested nutrients, said selected at least one enzyme indicator and at least one targeted nutrient digestibility index.

6. Method (100) according to any one of claims 1 to 5, which comprises a step of constituting (155) a database of nutrient digestibility index, for at least one livestock category indicator, as a function of empirical measurements performed uponcorresponding subjects of said livestock category, said database of nutrient digestibility index being used during the step of selecting a livestock category indicator.

7. Method (100) according to any one of claims 1 to 6, which comprises a step of constituting (160) a database of raw material to nutrient indicator correspondence, as a function of empirical measurements performed upon corresponding raw material, said database of nutrient digestibility index being used during the step of converting.

8. Method (100) according to any one of claims 1 to 7, which comprises a step of constituting (165) a database of enzyme indicator to nutrient digestibility index, as a function of empirical measurements performed upon corresponding enzymes, said database of digestibility index being used during the step of calculating.

9. Method (100) according to any one of claims 1 to 8, which comprises a step (170) of physically assembling the provided animal feed additive composition and / or a step (175) of transmitting a command to a device, said command being representative of a command of assembling the provided animal feed additive composition.

10. System to automatically formulate an animal feed additive composition, comprising:- one or more processors; and- one or more non-transitory computer-readable media that collectively store instructions that, when executed by the one or more processors, cause the computing system to perform operations, the instructions being representative of steps of:- selecting, upon a computer interface, a livestock category indicator, said livestock category indicator bijectively corresponding to a physical category of livestock, each livestock category indicator being associated with a nutrient feed digestibility index, said livestock category indicator being associated with at least one targeted nutrient digestibility index,- defining, upon a computer interface, an animal feed composition representation, comprising at least one raw feed material indicator, said rawmaterial indicator bijectively corresponding to a physical raw feed material, said animal feed composition representation bijectively corresponding to a physical animal feed composition,- converting, by a computing device, the defined animal feed composition representation into an equivalent nutrient feed composition representation, comprising at least one nutrient indicator, said nutrient representation bijectively corresponding to a physical nutrient, said nutrient feed composition representation bijectively corresponding to a physical nutrient feed composition,- determining, by a computing device, a quantity of undigested nutrients in the equivalent nutrient feed composition as a function of at least one nutrient indicator and, for said nutrient indicator, the corresponding nutrient feed digestibility index for the selected livestock category indicator,- calculating, by a computing device, an animal feed additive composition, as a function of the determined quantity of undigested nutrients and at least one targeted nutrient digestibility index, said animal feed additive composition comprising at least one enzyme indicator, each enzyme indicator being associated with a digestibility index of at least one nutrient, said enzyme indicator bijectively corresponding to a physical enzyme, said animal feed additive composition representation bijectively corresponding to a physical animal feed additive composition, and- providing, upon a computer interface, the animal feed additive composition calculated.11 . Computer-readable media characterized in that collectively store instructions that, when executed by one or more processors, cause a computing system to perform operations, the instructions being representative of steps of:- selecting, upon a computer interface, a livestock category indicator, said livestock category indicator bijectively corresponding to a physical category of livestock, each livestock category indicator being associated with a nutrient feed digestibilityindex, said livestock category indicator being associated with at least one targeted nutrient digestibility index,- defining, upon a computer interface, an animal feed composition representation, comprising at least one raw feed material indicator, said raw material indicator bijectively corresponding to a physical raw feed material, said animal feed composition representation bijectively corresponding to a physical animal feed composition,- converting, by a computing device, the defined animal feed composition representation into an equivalent nutrient feed composition representation, comprising at least one nutrient indicator, said nutrient representation bijectively corresponding to a physical nutrient, said nutrient feed composition representation bijectively corresponding to a physical nutrient feed composition,- determining, by a computing device, a quantity of undigested nutrients in the equivalent nutrient feed composition as a function of at least one nutrient indicator and, for said nutrient indicator, the corresponding nutrient feed digestibility index for the selected livestock category indicator,- calculating, by a computing device, an animal feed additive composition, as a function of the determined quantity of undigested nutrients and at least one targeted nutrient digestibility index, said animal feed additive composition comprising at least one enzyme indicator, each enzyme indicator being associated with a digestibility index of at least one nutrient, said enzyme indicator bijectively corresponding to a physical enzyme, said animal feed additive composition representation bijectively corresponding to a physical animal feed additive composition, and- providing, upon a computer interface, the animal feed additive composition calculated.

12. Computer software, comprising a set of instructions that, when executed by one or more processors, cause a computing system to perform operations, the instructions being representative of steps of:- selecting, upon a computer interface, a livestock category indicator, said livestock category indicator bijectively corresponding to a physical category of livestock, each livestock category indicator being associated with a nutrient feed digestibility index, said livestock category indicator being associated with at least one targeted nutrient digestibility index,- defining, upon a computer interface, an animal feed composition representation, comprising at least one raw feed material indicator, said raw material indicator bijectively corresponding to a physical raw feed material, said animal feed composition representation bijectively corresponding to a physical animal feed composition,- converting, by a computing device, the defined animal feed composition representation into an equivalent nutrient feed composition representation, comprising at least one nutrient indicator, said nutrient representation bijectively corresponding to a physical nutrient, said nutrient feed composition representation bijectively corresponding to a physical nutrient feed composition,- determining, by a computing device, a quantity of undigested nutrients in the equivalent nutrient feed composition as a function of at least one nutrient indicator and, for said nutrient indicator, the corresponding nutrient feed digestibility index for the selected livestock category indicator,- calculating, by a computing device, an animal feed additive composition, as a function of the determined quantity of undigested nutrients and at least one targeted nutrient digestibility index, said animal feed additive composition comprising at least one enzyme indicator, each enzyme indicator being associated with a digestibility index of at least one nutrient, said enzyme indicator bijectively corresponding to a physical enzyme, said animal feed additive composition representation bijectively corresponding to a physical animal feed additive composition, and- providing, upon a computer interface, the animal feed additive composition calculated.

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