Technology for measuring greenhouse gas emissions in ruminants after administration of feed additives.

Abstract

A technique for measuring greenhouse gas emissions in ruminants after the administration of feed additives includes receiving feed component usage data for each cattle breed via a server computer for a baseline period of the livestock operation. The feed component usage data includes the amount of feed provided for each cattle breed and identification of the feed additives contained in the feed. The feed additives are configured to reduce greenhouse gas emissions generated by each cattle in the herd that consumes the feed. The server computer also determines the estimated total controllable greenhouse gas emissions of the livestock operation for a baseline period of the livestock operation, using a model of total controllable greenhouse gas emissions, along with the feed component usage data as input to the model, which can be used to claim carbon credits.

Description

[Technical Field]

[0001] This application asserts the interests under Section 119(e) of the United States Patent Act (35 U.S.C.) of U.S. Provisional Patent Application No. 63 / 536,816, filed on 6 September 2023, the entire disclosure of which is incorporated herein by reference.

[0002] (Cross-reference of related applications) This invention cross-references with the concurrently pending international patent application PCT / US2024 / 045531, filed on September 6, 2024, entitled “METHODS FOR MEASURING GREENHOUSE GAS EMISSIONS IN RUMINANTS FOLLOWING ADMINISTRATION OF FEED ADDITIVES,” the entire disclosure of which is incorporated herein by reference.

[0003] This disclosure relates, in general, to a technology for measuring greenhouse gas emissions in ruminants after the administration of feed additives, and more specifically, to a technology for monitoring and managing the carbon footprint of livestock operations that use feed additives to obtain carbon credits. [Background technology]

[0004] In the modern era, there is a high demand for mechanisms to reduce greenhouse gas emissions. The mechanisms under investigation are inherently broad and wide-ranging. As a result, in almost every technological field, the challenge is to consider means of potentially reducing their "carbon footprint" in order to raise environmental awareness.

[0005] In the agriculture and food sectors, the reduction of greenhouse gases such as methane has been investigated. Various active ingredients that can be fed to animals have been studied to reduce greenhouse gas emissions, such as methane, released by animals. In particular, feeding animals monensin (Rumensin®) and 3-nitrooxypropanol (Bovaer®) may lead to a reduction in greenhouse gas emissions from animals, especially ruminants. Furthermore, the availability of carbon credits provides an incentive for farmers and producers to reduce greenhouse gas emissions. Therefore, there is a need to maximize the reduction of greenhouse gas emissions in animal industries, such as livestock farms, in order to obtain desirable carbon credits.

[0006] However, monitoring and managing greenhouse gas emissions from specific industries, including livestock farms, can be challenging due to the complexity of managing tracked inputs, the difficulties associated with accurately determining greenhouse gas emissions, and the difficulty in verifying reductions in greenhouse gas emissions through corrective measures such as the introduction of feed additives. [Overview of the project]

[0007] According to one aspect of the present disclosure, a method for managing the carbon footprint of a livestock operation having a herd of one or more cattle breeds may include receiving feed component usage data for each cattle breed in the herd, for a baseline period of the livestock operation, via a server computer, the feed component usage data including the amount of feed provided to each cattle breed in the herd and identification of feed additives contained in the feed, the feed additives being configured to reduce greenhouse gas emissions generated by each cattle in the herd that consumes the feed. The method may also include determining the estimated total controllable greenhouse gas emissions for the livestock operation, for a baseline period of the livestock operation, using a model of total controllable greenhouse gas emissions, together with feed component usage data as input to the model, via a server computer. Furthermore, the method may include claiming carbon credits, for a baseline period of the livestock operation, based on the estimated total controllable greenhouse gas emissions for the livestock operation, via a server computer.

[0008] In some embodiments, the feed additive may be embodied as monensin. Furthermore, or alternatively, the feed additive may be embodied as 3-nitrooxypropanol. In some embodiments, greenhouse gas emissions may include methane. Furthermore, in some embodiments, the herd may include dairy cows and / or beef cattle.

[0009] In some embodiments, the feed additive may be configured to reduce greenhouse gas emissions generated by each cattle in a herd that consumes the feed by reducing intestinal fermentation in each cattle. Alternatively, the feed additive may be configured to reduce greenhouse gas emissions generated by each cattle in a herd that consumes the feed by reducing the dry matter intake (DMI) of each cattle. In some embodiments, the amount of feed provided for each cattle breed includes a plurality of components and corresponding amounts of each component of the plurality of components.

[0010] Furthermore, in some embodiments, the method may further include receiving utility usage data from a server computer and indicating the amount of utility services used by the livestock operation for a baseline period of the livestock operation. In such embodiments, determining the estimated total controllable greenhouse gas emissions for the livestock operation may include determining the estimated total controllable greenhouse gas emissions for the livestock operation by using a model of total controllable greenhouse gas emissions together with (i) feed component usage data and (ii) utility usage data as inputs to the model. In such embodiments, receiving utility usage data may include receiving the proportion of utility services used by the livestock operation for dairy farming.

[0011] Furthermore, in some embodiments, the method may include receiving herd composition data from a server computer, indicating the number and breed of cattle in the herd for a baseline period of livestock operations. In such embodiments, determining the estimated total controllable greenhouse gas emissions for livestock operations may include using a model of total controllable greenhouse gas emissions, together with (i) feed component usage data, (ii) utility usage data, and (iii) herd composition data as inputs to the model, to determine the estimated total controllable greenhouse gas emissions for livestock operations. In such embodiments, receiving herd composition data may include receiving sales data indicating the number of cattle sold from the herd.

[0012] Furthermore, in some embodiments, the method may further include receiving milk production data from a server computer and identifying the amount of milk produced by each milking cow breed in the herd for a baseline period of livestock operations. In such embodiments, determining the estimated total controllable greenhouse gas emissions for livestock operations includes determining the estimated total controllable greenhouse gas emissions for livestock operations by using a model of total controllable greenhouse gas emissions together with (i) feed component usage data, (ii) utility usage data, (iii) herd composition data, and (iv) milk production data as inputs to the model.

[0013] In some embodiments, determining the estimated total controllable greenhouse gas emissions for livestock operations may include, by a server computer, determining the estimated greenhouse gas emissions attributable to feed cultivation for dairy operations for a baseline period of livestock operations, and by a server computer, determining the estimated total controllable greenhouse gas emissions for livestock operations based on the estimated greenhouse gas emissions attributable to feed cultivation for a baseline period of livestock operations.

[0014] Furthermore, in some embodiments, determining the estimated total controllable greenhouse gas emissions for livestock operations may include: determining the estimated greenhouse gas emissions attributable to herd intestinal fermentation for a baseline period of livestock operations using a server computer; and determining the estimated total controllable greenhouse gas emissions for livestock operations based on the estimated greenhouse gas emissions attributable to herd intestinal fermentation for a baseline period of livestock operations using a server computer.

[0015] In some embodiments, determining an estimated total controllable greenhouse gas emission for livestock operations may include determining, by a server computer and for a reference period of the livestock operation, an estimated greenhouse gas emission resulting from manure management of the livestock operation, and determining, by the server computer and for the reference period of the livestock operation, the estimated total controllable greenhouse gas emission for the livestock operation based on the estimated greenhouse gas emission resulting from the manure management of the livestock operation.

[0016] Further, in some embodiments, determining an estimated total controllable greenhouse gas emission for livestock operations may include determining, by a server computer and for a reference period of the livestock operation, an estimated greenhouse gas emission resulting from utility usage of the livestock operation, and determining, by the server computer and for the reference period of the livestock operation, the estimated total controllable greenhouse gas emission for the livestock operation based on the estimated greenhouse gas emission resulting from the utility usage of the livestock operation.

[0017] Further, in some embodiments, determining the estimated total controllable greenhouse gas emissions for a livestock operation includes determining, by a server computer and for a reference period of the livestock operation, estimated greenhouse gas emissions attributable to feed cultivation of the dairy operation, determining, by the server computer and for the reference period of the livestock operation, estimated greenhouse gas emissions attributable to enteric fermentation of the cattle herd, determining, by the server computer and for the reference period of the livestock operation, estimated greenhouse gas emissions attributable to manure management of the livestock operation, determining, by the server computer and for the reference period of the livestock operation, estimated greenhouse gas emissions attributable to utility usage of the livestock operation, and determining, by the server computer and for the reference period of the livestock operation, the estimated total controllable greenhouse gas emissions for the livestock operation based on (i) the estimated greenhouse gas emissions attributable to feed cultivation of the dairy operation, (ii) the estimated greenhouse gas emissions attributable to enteric fermentation of the cattle herd, (iii) the estimated greenhouse gas emissions attributable to manure management of the livestock operation, and (iv) the estimated greenhouse gas emissions attributable to utility usage of the livestock operation.

[0018] Further, in some embodiments, determining the estimated total controllable greenhouse gas emissions for a livestock operation may include allocating the estimated total controllable greenhouse gas emissions between the milk production operations of the livestock operation and the meat production operations of the livestock operation. In such embodiments, determining the estimated total controllable greenhouse gas emissions for the livestock operation may further include allocating utility usage indicating the amount of utility services used by the livestock operation based on the cattle breed of the cattle herd.

[0019] In some embodiments, claiming carbon credits may include determining a reduction in greenhouse gas emissions based on the estimated total controllable greenhouse gas emissions for the livestock operation and a baseline greenhouse gas emissions. In such embodiments, the method may also include a server computer claiming carbon credits based on the determined reduction in greenhouse gas emissions for a baseline period of the livestock operation.

[0020] Furthermore, in some embodiments, the method may include generating a greenhouse gas emission index based on an estimated total controllable greenhouse gas emissions and displaying the greenhouse gas emission index to the user. In such embodiments, the greenhouse gas emission index may include a display of a comparison of estimated total controllable greenhouse gas emissions for a base period and a previous period. Furthermore, in such embodiments, the estimated total controllable greenhouse gas emissions may include multiple greenhouse gas emission types, and the greenhouse gas emission index identifies the amount of each greenhouse gas emission type. Furthermore, in some embodiments, the method may include determining recommended greenhouse gas emission improvement measures for livestock operations based on the estimated total controllable greenhouse gas emissions.

[0021] According to another aspect of the present disclosure, a server computer for managing the carbon footprint of a livestock operation having a herd of one or more cattle breeds may include a processor and a memory storing a plurality of instructions, which, when executed by the processor, cause the server computer to receive feed component usage data for each cattle breed in the herd for a baseline period of the livestock operation, the feed component usage data including the amount of feed provided to each cattle breed in the herd and identification of feed additives contained in the feed, the feed additives configured to reduce greenhouse gas emissions produced by each cattle in the herd that consumes the feed. The plurality of instructions may further cause the server computer to determine the estimated total controllable greenhouse gas emissions for the livestock operation for a baseline period of the livestock operation, using a model of total controllable greenhouse gas emissions together with the feed component usage data as input to the model. In addition, the plurality of instructions may further cause the server computer to request carbon credits for the estimated total controllable greenhouse gas emissions for the livestock operation for a baseline period of the livestock operation based on the estimated total controllable greenhouse gas emissions for the livestock operation.

[0022] In some embodiments, the feed additive may be embodied as monensin. Furthermore, or alternatively, the feed additive may be embodied as 3-nitrooxypropanol. In some embodiments, greenhouse gas emissions may include methane. Furthermore, in some embodiments, the herd may include dairy cows and / or beef cattle.

[0023] In some embodiments, feed additives may be configured to reduce greenhouse gas emissions produced by each cattle consuming the feed by reducing intestinal fermentation in each cattle in the herd. Alternatively, feed additives may be configured to reduce greenhouse gas emissions produced by each cattle consuming the feed by reducing the dry matter intake (DMI) of each cattle. In some embodiments, the amount of feed provided for each cattle breed includes a plurality of components and corresponding amounts of each component of the plurality of components.

[0024] Furthermore, in some embodiments, the instructions may further cause the server computer to receive utility usage data indicating the amount of utility services used by the livestock operation for a baseline period of the livestock operation. In such embodiments, determining the estimated total controllable greenhouse gas emissions for the livestock operation may include using a model of total controllable greenhouse gas emissions, together with (i) feed component usage data and (ii) utility usage data as inputs to the model, to determine the estimated total controllable greenhouse gas emissions for the livestock operation. In such embodiments, receiving utility usage data may include receiving the proportion of utility services used by the livestock operation for dairy farming.

[0025] Furthermore, in some embodiments, the instructions may further cause the server computer to receive herd composition data indicating the number and breed of cattle in the herd for a baseline period of livestock operations. In such embodiments, determining the estimated total controllable greenhouse gas emissions for livestock operations may include using a model of total controllable greenhouse gas emissions, together with (i) feed component usage data, (ii) utility usage data, and (iii) herd composition data as inputs to the model, to determine the estimated total controllable greenhouse gas emissions for livestock operations. In such embodiments, receiving the herd composition data may include receiving sales data indicating the number of cattle sold from the herd.

[0026] Furthermore, in some embodiments, the instructions may further cause the server computer to receive milk production data identifying the amount of milk produced by each milking cow breed in the herd for a baseline period of livestock operations. In such embodiments, determining the estimated total controllable greenhouse gas emissions for livestock operations may involve using a model of total controllable greenhouse gas emissions, together with (i) feed component usage data, (ii) utility usage data, (iii) herd composition data, and (iv) milk production data as inputs to the model, to determine the estimated total controllable greenhouse gas emissions for livestock operations.

[0027] In some embodiments, determining the estimated total controllable greenhouse gas emissions for livestock operations may include determining the estimated greenhouse gas emissions attributable to feed cultivation in dairy operations for a baseline period of livestock operations, and determining the estimated total controllable greenhouse gas emissions for livestock operations based on the estimated greenhouse gas emissions attributable to feed cultivation for a baseline period of livestock operations.

[0028] Furthermore, in some embodiments, determining the estimated total controllable greenhouse gas emissions for livestock operations may include determining the estimated greenhouse gas emissions attributable to herd intestinal fermentation for a baseline period of livestock operations, and determining the estimated total controllable greenhouse gas emissions for livestock operations based on the estimated greenhouse gas emissions attributable to herd intestinal fermentation for a baseline period of livestock operations, using a server computer.

[0029] In some embodiments, determining the estimated total controllable greenhouse gas emissions for livestock operations may include determining the estimated greenhouse gas emissions attributable to manure management in livestock operations for a baseline period of livestock operations, and determining the estimated total controllable greenhouse gas emissions for livestock operations based on the estimated greenhouse gas emissions attributable to manure management in livestock operations for a baseline period of livestock operations.

[0030] Furthermore, in some embodiments, determining the estimated total controllable greenhouse gas emissions for livestock operations may include determining the estimated greenhouse gas emissions attributable to the use of utilities in livestock operations for a baseline period of livestock operations, and determining the estimated total controllable greenhouse gas emissions for livestock operations based on the estimated greenhouse gas emissions attributable to the use of utilities in livestock operations for a baseline period of livestock operations.

[0031] Furthermore, in some embodiments, determining the estimated total controllable greenhouse gas emissions for livestock operations may include: determining the estimated greenhouse gas emissions attributable to feed cultivation in dairy farming for a baseline period of livestock operations; determining the estimated greenhouse gas emissions attributable to enteric fermentation of cattle herds for a baseline period of livestock operations; determining the estimated greenhouse gas emissions attributable to manure management in livestock operations for a baseline period of livestock operations; determining the estimated greenhouse gas emissions attributable to utility use in livestock operations for a baseline period of livestock operations; and determining the estimated total controllable greenhouse gas emissions for livestock operations based on (i) the estimated greenhouse gas emissions attributable to feed cultivation in dairy farming, (ii) the estimated greenhouse gas emissions attributable to enteric fermentation of cattle herds, (iii) the estimated greenhouse gas emissions attributable to manure management in livestock operations, and (iv) the estimated greenhouse gas emissions attributable to utility use in livestock operations for a baseline period of livestock operations.

[0032] Furthermore, in some embodiments, determining the estimated total controllable greenhouse gas emissions for a livestock operation may include allocating the estimated total controllable greenhouse gas emissions between the dairy production operations and the meat production operations of the livestock operation. In such embodiments, determining the estimated total controllable greenhouse gas emissions for a livestock operation may further include allocating utility usage, which indicates the amount of utility services used by the livestock operation, based on the breed of cattle in the herd.

[0033] In some embodiments, requesting carbon credits may involve determining a reduction in greenhouse gas emissions based on the estimated total controllable greenhouse gas emissions for livestock operations and baseline greenhouse gas emissions. In such embodiments, a plurality of instructions may further cause a server computer to request carbon credits for a baseline period of livestock operations based on the determined reduction in greenhouse gas emissions.

[0034] Furthermore, in some embodiments, the instructions may further cause the server computer to generate a greenhouse gas emission index based on the estimated total controllable greenhouse gas emissions and to display the greenhouse gas emission index to the user. In such embodiments, the greenhouse gas emission index may include a display of a comparison of the estimated total controllable greenhouse gas emissions for a base period and a previous period. Furthermore, in such embodiments, the estimated total controllable greenhouse gas emissions may include multiple greenhouse gas emission types, and the greenhouse gas emission index may identify the amount of each greenhouse gas emission type. Furthermore, in some embodiments, the instructions may further cause the server computer to determine recommended greenhouse gas emission improvement measures for livestock operations based on the estimated total controllable greenhouse gas emissions.

[0035] In a further aspect of the present disclosure, one or more non-temporary computer-readable storage media may include a plurality of instructions which, in response to execution, cause a server computer to receive feed component usage data for each breed of cattle in a herd for a baseline period of livestock operations, the feed component usage data including the amount of feed provided to each breed of cattle in the herd and identification of feed additives contained in the feed, the feed additives configured to reduce greenhouse gas emissions generated by each cattle in the herd that consumes the feed. The plurality of instructions may further cause the server computer to determine the estimated total controllable greenhouse gas emissions for livestock operations for a baseline period of livestock operations, using a model of total controllable greenhouse gas emissions together with the feed component usage data as input to the model. In addition, the plurality of instructions may further cause the server computer to request carbon credits for the estimated total controllable greenhouse gas emissions for livestock operations for a baseline period of livestock operations based on the estimated total controllable greenhouse gas emissions for livestock operations.

[0036] In some embodiments, the feed additive may be embodied as monensin. Furthermore, or alternatively, the feed additive may be embodied as 3-nitrooxypropanol. In some embodiments, greenhouse gas emissions may include methane. Furthermore, in some embodiments, the herd may include dairy cows and / or beef cattle.

[0037] In some embodiments, feed additives may be configured to reduce greenhouse gas emissions produced by each cattle consuming the feed by reducing intestinal fermentation in each cattle in the herd. Alternatively, feed additives may be configured to reduce greenhouse gas emissions produced by each cattle consuming the feed by reducing the dry matter intake (DMI) of each cattle. In some embodiments, the amount of feed provided for each cattle breed includes a plurality of components and corresponding amounts of each component of the plurality of components.

[0038] Furthermore, in some embodiments, the instructions may further cause the server computer to receive utility usage data indicating the amount of utility services used by the livestock operation for a baseline period of the livestock operation. In such embodiments, determining the estimated total controllable greenhouse gas emissions for the livestock operation may include using a model of total controllable greenhouse gas emissions, together with (i) feed component usage data and (ii) utility usage data as inputs to the model, to determine the estimated total controllable greenhouse gas emissions for the livestock operation. In such embodiments, receiving utility usage data may include receiving the proportion of utility services used by the livestock operation for dairy farming.

[0039] Furthermore, in some embodiments, the instructions may further cause the server computer to receive herd composition data indicating the number and breed of cattle in the herd for a baseline period of livestock operations. In such embodiments, determining the estimated total controllable greenhouse gas emissions for livestock operations may include using a model of total controllable greenhouse gas emissions, together with (i) feed component usage data, (ii) utility usage data, and (iii) herd composition data as inputs to the model, to determine the estimated total controllable greenhouse gas emissions for livestock operations. In such embodiments, receiving the herd composition data may include receiving sales data indicating the number of cattle sold from the herd.

[0040] Furthermore, in some embodiments, the instructions may further cause the server computer to receive milk production data identifying the amount of milk produced by each milking cow breed in the herd for a baseline period of livestock operations. In such embodiments, determining the estimated total controllable greenhouse gas emissions for livestock operations may involve using a model of total controllable greenhouse gas emissions, together with (i) feed component usage data, (ii) utility usage data, (iii) herd composition data, and (iv) milk production data as inputs to the model, to determine the estimated total controllable greenhouse gas emissions for livestock operations.

[0041] In some embodiments, determining the estimated total controllable greenhouse gas emissions for livestock operations may include determining the estimated greenhouse gas emissions attributable to feed cultivation in dairy operations for a baseline period of livestock operations, and determining the estimated total controllable greenhouse gas emissions for livestock operations based on the estimated greenhouse gas emissions attributable to feed cultivation for a baseline period of livestock operations.

[0042] Furthermore, in some embodiments, determining the estimated total controllable greenhouse gas emissions for livestock operations may include determining the estimated greenhouse gas emissions attributable to herd intestinal fermentation for a baseline period of livestock operations, and determining the estimated total controllable greenhouse gas emissions for livestock operations based on the estimated greenhouse gas emissions attributable to herd intestinal fermentation for a baseline period of livestock operations, using a server computer.

[0043] In some embodiments, determining the estimated total controllable greenhouse gas emissions for livestock operations may include determining the estimated greenhouse gas emissions attributable to manure management in livestock operations for a baseline period of livestock operations, and determining the estimated total controllable greenhouse gas emissions for livestock operations based on the estimated greenhouse gas emissions attributable to manure management in livestock operations for a baseline period of livestock operations.

[0044] Furthermore, in some embodiments, determining the estimated total controllable greenhouse gas emissions for livestock operations may include determining the estimated greenhouse gas emissions attributable to the use of utilities in livestock operations for a baseline period of livestock operations, and determining the estimated total controllable greenhouse gas emissions for livestock operations based on the estimated greenhouse gas emissions attributable to the use of utilities in livestock operations for a baseline period of livestock operations.

[0045] Furthermore, in some embodiments, determining the estimated total controllable greenhouse gas emissions for livestock operations may include: determining the estimated greenhouse gas emissions attributable to feed cultivation in dairy farming for a baseline period of livestock operations; determining the estimated greenhouse gas emissions attributable to enteric fermentation of cattle herds for a baseline period of livestock operations; determining the estimated greenhouse gas emissions attributable to manure management in livestock operations for a baseline period of livestock operations; determining the estimated greenhouse gas emissions attributable to utility use in livestock operations for a baseline period of livestock operations; and determining the estimated total controllable greenhouse gas emissions for livestock operations based on (i) the estimated greenhouse gas emissions attributable to feed cultivation in dairy farming, (ii) the estimated greenhouse gas emissions attributable to enteric fermentation of cattle herds, (iii) the estimated greenhouse gas emissions attributable to manure management in livestock operations, and (iv) the estimated greenhouse gas emissions attributable to utility use in livestock operations for a baseline period of livestock operations.

[0046] Furthermore, in some embodiments, determining the estimated total controllable greenhouse gas emissions for a livestock operation may include allocating the estimated total controllable greenhouse gas emissions between the dairy production operations and the meat production operations of the livestock operation. In such embodiments, determining the estimated total controllable greenhouse gas emissions for a livestock operation may further include allocating utility usage, which indicates the amount of utility services used by the livestock operation, based on the breed of cattle in the herd.

[0047] In some embodiments, requesting carbon credits may involve determining a reduction in greenhouse gas emissions based on the estimated total controllable greenhouse gas emissions for livestock operations and baseline greenhouse gas emissions. In such embodiments, a plurality of instructions may further cause a server computer to request carbon credits for a baseline period of livestock operations based on the determined reduction in greenhouse gas emissions.

[0048] Furthermore, in some embodiments, the instructions may further cause the server computer to generate a greenhouse gas emission index based on the estimated total controllable greenhouse gas emissions and to display the greenhouse gas emission index to the user. In such embodiments, the greenhouse gas emission index may include a display of a comparison of the estimated total controllable greenhouse gas emissions for a base period and a previous period. Furthermore, in such embodiments, the estimated total controllable greenhouse gas emissions may include multiple greenhouse gas emission types, and the greenhouse gas emission index may identify the amount of each greenhouse gas emission type. Furthermore, in some embodiments, the instructions may further cause the server computer to determine recommended greenhouse gas emission improvement measures for livestock operations based on the estimated total controllable greenhouse gas emissions.

[0049] The concepts described herein are illustrated, not limited to, in the accompanying figures. For the sake of simplification and clarity of the illustrations, the elements shown in the figures are not necessarily drawn to scale. Where deemed appropriate, reference labels are repeated between figures to indicate corresponding or similar elements. [Brief explanation of the drawing]

[0050] [Figure 1] This is a simplified block diagram of at least one embodiment of a system for managing the carbon footprint of livestock farming operations. [Figure 2]This figure shows a simplified mathematical model for determining greenhouse gas emission reductions in livestock farming operations, which can be used by the server computer of the system in Figure 1, using a controllable total greenhouse gas emissions model. [Figure 3] Figure 1 is a simplified block diagram of an exemplary environment that can be established by the server computer of the system. [Figure 4] Figure 1 is a simplified block diagram of an exemplary environment that can be established by the user computer device of the system. [Figure 5A] ~ [Figure 5C] Figure 1 is a simplified flowchart of a method for managing the carbon footprint of livestock operations, which may be performed by the server computer of the system shown. [Figure 6] Figures 5A to 5C show simplified diagrams of the user interfaces that may be displayed on the user computer device by the server computer of the system in Figure 1 during the execution of the methods shown in Figures 5A to 5C. [Figure 7] Figures 5A to 5C show a simplified diagram of another user interface that may be displayed on the user computer device by the server computer of the system in Figure 1 during the execution of the methods shown in Figures 5A to 5C. [Figure 8] Figures 5A to 5C show a simplified diagram of another user interface that may be displayed on the user computer device by the server computer of the system in Figure 1 during the execution of the methods shown in Figures 5A to 5C. [Figure 9] Figures 5A to 5C show a simplified diagram of another user interface that may be displayed on the user computer device by the server computer of the system in Figure 1 during the execution of the methods shown in Figures 5A to 5C. [Figure 10] Figures 5A to 5C show a simplified diagram of another user interface that may be displayed on the user computer device by the server computer of the system in Figure 1 during the execution of the methods shown in Figures 5A to 5C. [Figure 11]Figures 5A to 5C show a simplified diagram of another user interface that may be displayed on the user computer device by the server computer of the system in Figure 1 during the execution of the methods shown in Figures 5A to 5C. [Figure 12] ~ [Figure 14] Figures 5A to 5C show simplified diagrams of the user interface portion that may be displayed on the user computer device by the server computer of the system in Figure 1 during the execution of the methods shown in Figures 5A to 5C. [Figure 15] Figures 5A to 5C show a simplified diagram of another user interface that may be displayed on the user computer device by the server computer of the system in Figure 1 during the execution of the methods shown in Figures 5A to 5C. [Figure 16] Figures 5A to 5C show a simplified diagram of another user interface that may be displayed on the user computer device by the server computer of the system in Figure 1 during the execution of the methods shown in Figures 5A to 5C. [Figure 17] Figures 5A to 5C show a simplified diagram of another user interface that may be displayed on the user computer device by the server computer of the system in Figure 1 during the execution of the methods shown in Figures 5A to 5C. [Figure 18] Figures 5A to 5C show a simplified diagram of another user interface that may be displayed on the user computer device by the server computer of the system in Figure 1 during the execution of the methods shown in Figures 5A to 5C. [Figure 19] Figures 5A to 5C show simplified diagrams of greenhouse gas emission indicators that may be displayed on a user computer device by the server computer of the system in Figure 1 during the execution of the methods shown in Figures 5A to 5C. [Figure 20] Figures 5A to 5C show simplified diagrams of other greenhouse gas emission indicators that may be displayed on the user computer device by the server computer of the system in Figure 1 during the execution of the methods shown in Figures 5A to 5C. [Figure 21] Figures 5A to 5C are simplified diagrams of other greenhouse gas emission indices showing various types of greenhouse gas emissions that may be displayed on the user computer device by the server computer of the system in Figure 1 during the execution of the methods shown in Figures 5A to 5C. [Figure 22] Figures 5A to 5C are tables of animal species considered in the methods. [Figure 23] This is a table of system boundaries for an exemplary livestock operation, including inputs, output, and greenhouse gas emissions. [Figure 24] This is a table showing the possible emissions from an exemplary livestock farming operation. [Figure 25] This is a table of emission factors for a sample list of feed components. [Figure 26] This is a table of emission factors for various fuel sources. [Modes for carrying out the invention]

[0051] The concepts of this disclosure are susceptible to various modifications and alternative forms, the particular embodiments of which are shown in the drawings as examples and described in detail herein. However, it should be understood that the concepts of this disclosure are not intended to be limited to the particular forms disclosed, but rather are intended to encompass all modifications, equivalents, and alternatives that are consistent with this disclosure and the appended claims.

[0052] References in this specification to “one embodiment,” “one example,” or “exemplary embodiment” indicate that the described embodiment may include certain features, structures, or characteristics, but not all embodiments may, or may not, include, certain features, structures, or characteristics. Furthermore, such phrasing does not necessarily refer to the same embodiment. In addition, when certain features, structures, or characteristics are described in relation to one embodiment, it is considered within the knowledge of those skilled in the art that such features, structures, or characteristics will be affected in relation to other embodiments, whether explicitly stated or not. Furthermore, it should be understood that items included in the list in the form of “at least one of A, B, and C” may mean (A), (B), (C), (A and B), (B and C), or (A, B, and C). Similarly, items enumerated in the form of “at least one of A, B, or C” may mean (A), (B), (C), (A and B), (B and C), or (A, B, and C).

[0053] The disclosed embodiments may, depending on the circumstances, be implemented in hardware, firmware, software, or any combination thereof. The disclosed embodiments may also be implemented as instructions carried or stored by a temporary or non-temporary machine-readable (e.g., computer-readable) storage medium that can be read and executed by one or more processors. The machine-readable storage medium may be embodied as any storage device, mechanism, or other physical structure for storing or transmitting information in a form readable by a machine (e.g., volatile or non-volatile memory, media disk, or other media device).

[0054] In drawings, certain structural or methodological features may be shown in a specific arrangement and / or order. However, it should be understood that such a specific arrangement and / or order may not always be necessary. Rather, in some embodiments, such features may be arranged in a different manner and / or order than those shown in the exemplary drawings. Furthermore, the inclusion of structural or methodological features in a particular drawing does not imply that such features are required in all embodiments, and in some embodiments they may not be included or may be combined with other features.

[0055] The pre-configured disclosures provide technologies for monitoring and managing greenhouse gas emissions (e.g., carbon dioxide, nitrous oxide, and methane) in livestock operations to determine the carbon footprint of such operations. In particular, the disclosed technologies monitor and determine reductions in greenhouse gas emissions resulting from the administration of feed additives, monensin, and / or 3-nitrooxypropanol, to the feed of livestock herds. Reductions in greenhouse gas emissions may be documented to receive carbon credits based on such reductions. Generally, carbon credits refer to mechanisms that compensate for emissions of carbon dioxide or other greenhouse gases. For example, one carbon credit may represent a reduction or elimination of one metric ton of carbon dioxide or an equivalent amount of greenhouse gas emissions. Carbon credits may also be referred to as carbon offsets.

[0056] Monensin (also known as Rumensin®) is a feed additive approved by the U.S. Food and Drug Administration (FDA) Center for Animal Health to improve the efficiency of milk production, and is defined as the commercially available solid-adjusted milk yield per unit of feed intake adjusted for weight change. For example, in the rearing of cattle (including juvenile heifers), monensin increases the rate of weight gain and prevents and controls coccidiosis. Monensin improves the efficiency of milk production in dairy cows by shifting the rumen bacterial community to produce more propionic acid, which is a more efficient use of feed as it reduces the amount of energy consumed as carbon dioxide and methane. Figure 1 summarizes the adjustments used to quantify the effect of monensin on greenhouse gas emissions.

[0057] The use of monensin in dairy cows can significantly reduce dry matter intake (DMI) by, for example, 2.3% and increase milk yield by 2.3%. Because significant heterogeneity was observed in milk components, the difference in solids-adjusted milk yield (SCM) between the control group and the monensin-treated group was calculated according to NRC 2001 using the reported milk yield and component percentages, suggesting a possible 0.5% increase in SCM due to monensin. Therefore, a conservative plus 0.5% increase can be used as the effect of monensin on both SCM and milk yield. For dry cows, the monensin study showed a 2.7% reduction in dry matter intake.

[0058] The mechanism of action of monensin for milk production efficiency is that it leads to a reduction in methane production. The effects of feeding monensin to cattle include both a direct reduction in CH4 emissions from intestinal fermentation and an indirect reduction in intestinal fermentation emissions due to a decrease in DMI, resulting in no adverse health effects and positive benefits to milk production. The sustained benefits of feeding monensin to cattle are supported by multiple scientific studies that measure the reduction in CH4 emissions from intestinal fermentation. The effect of monensin on the reduction of DMI also reduces the greenhouse gas impact associated with forage cultivation and fertilizers, resulting in additional greenhouse gas benefits. These effects are credited by the processes and calculations of this protocol.

[0059] Monensin reduces absolute emissions in the production of consumer goods along the value chain. Enteral methane is produced through the fermentation of feed that animals consume at regular intervals throughout the day. Because monensin works by reducing enteral methane and feed intake, the reduction in greenhouse gas emissions associated with monensin feeding is permanent and irreversible. On days when animals are not fed monensin, 3–5% more enteral methane is released into the environment.

[0060] Furthermore, peer-reviewed literature has shown that 3-nitrooxypropanol (also known as 3-NOP or Bovaer®) reduces intestinal methane emissions by approximately 30% or 1 metric ton (MT) in CO2 equivalent, under conditions that can be modeled according to dosage and diet, which allows for more accurate reduction estimates. Assuming an average annual intestinal methane output of 4 MT of carbon dioxide equivalent (CO2e) in dairy cows, 3-NOP could potentially permanently avoid 0.8–1.6 MT of CO2e per cow per year. If 3-NOP were implemented in 50% of the 7.9 million dairy cows in the United States (USDA-NASS, 2023), 3.1–6.3 MT of CO2e would be permanently avoided annually.

[0061] While not bound by any particular theory, 3-NOP has a mechanism of action that acts through the targeted oxidation of nickel in methyl coenzyme M reductase (MCR), resulting in its inhibition in the final step of methane formation. After exerting its action, 3-NOP is converted into a substance naturally produced in rumen fermentation. The impact of 3-NOP on methane reduction and productivity has been evaluated, and its effect on methane reduction is approximately 30% or 1 MT of CO2, depending on the dose and diet, which can be modeled to provide a more accurate reduction estimate. 3-NOP reduces intestinal methane and, consequently, absolute emissions in the production of consumer goods along the entire value chain. On each day when 3-NOP is not fed to animals, approximately 30% or 1 MT more intestinal methane is released into the environment compared to the amount released when 3-NOP is fed. The emission reduction associated with feeding 3-NOP is permanent and cannot be reversed.

[0062] As discussed above, the disclosed technology facilitates the determination of the carbon footprint of livestock operations, the evaluation of mitigation methods including feed additives, and the verification of reductions in greenhouse gas emissions in livestock operations through such mitigation efforts. To this end, the disclosed technology utilizes a controllable total greenhouse gas emissions model and uses a life cycle analysis approach to determine the carbon footprint of livestock operations.

[0063] A typical livestock operation can be embodied as a dairy farm primarily focused on milk production, with beef cattle and crop production as secondary products. The cattle of a livestock farm may be located on a single plot of land or across multiple plots. The herd may include one or more different breeds, as shown in Table 2200 in Figure 22. In exemplary embodiments, the herd may include milking cows, dry cows, 0-12 month old replacement heifers, over 12 months old replacement heifers, and / or beef cattle. Furthermore, as shown in System 2300 in Figure 23, a typical livestock operation includes several major inputs and outputs, along with the by-products of greenhouse gases generated. For example, major inputs may include feed components, fuel, and / or utilities (e.g., electricity), and major outputs may include milk production and meat production. Various cattle breeds, and the treatment of their manure, produce certain amounts of greenhouse gases, which may include carbon dioxide, nitrous oxide, and / or methane.

[0064] The techniques disclosed herein consider several emission sources, sinks, and / or storage areas (SSRs) while excluding others for various reasons when determining the total greenhouse gas emissions of an exemplary livestock operation. For example, in exemplary embodiments, the techniques of this disclosure may include system boundaries as identified in Table 2400 of Figure 24. In exemplary embodiments, greenhouse gas emissions from feed cultivation, enteric fermentation, manure management, and fuel and electricity use are considered, while those from direct land use, bedding, and waste treatment are not. In other embodiments, additional or different sources of greenhouse gas emissions may be considered.

[0065] Referring here to Figure 1, the system 100 for managing the carbon footprint of livestock operations includes a greenhouse gas (GHG) monitoring server 102 and at least one user computer device 104, which are configured to communicate with each other via a network 106. When in use, as will be discussed in more detail below, the user of the user computer device 104 may provide work data related to livestock operations to the GHG monitoring server 102, which is configured to use a model of controllable total greenhouse gas emissions, along with the work data as input to the model, to determine the estimated controllable total greenhouse gas emissions for livestock operations. The work data includes feed component usage data for a herd, including the identification of one or more feed additives (e.g., monensin and 3-nitrooxypropanol) contained in the feed. As discussed above, feed additives can be used to reduce the amount of greenhouse gas emissions produced by cattle during feeding. The GHG monitoring server 102 may also request carbon credits based on the estimated total controllable greenhouse gas emissions, which may be defined as a reduction in greenhouse gas emissions compared to a baseline period or a prior period.

[0066] In some embodiments, operational data related to livestock operations may include additional input data such as utility usage data and / or herd composition data and milk productivity data. The GHG monitoring server 102 utilizes each of these operational data as input to a mathematical model of controllable total GHG emissions. To this end, as discussed above, the mathematical model maintained by the GHG monitoring server 102 uses a feed cultivation submodel, a gut fermentation submodel, a manure management submodel, and a utility usage submodel, with the use of one or more of the feed component usage, utility usage, and / or herd composition and productivity data as inputs to their respective models, to determine the total greenhouse gas emissions from various emission sources. The GHG monitoring server 102 combines the outputs of these submodels to determine the total controllable greenhouse gas emissions from the livestock operations. In some embodiments, the GHG monitoring server 102 may be configured to allocate a portion of the total controllable greenhouse gas emissions from the livestock operations to the milk production and / or meat production of the livestock operations. Furthermore, the GHG monitoring server 102 is configured to determine an overall reduction in greenhouse gas emissions for the livestock operation, which may be attributable to the addition of feed additives, by comparing the determined total controllable greenhouse gas emissions of the livestock operation with a baseline amount of greenhouse gas emissions, which may be based on previous measurements or default levels. Thus, as discussed above, the GHG monitoring server 102 may request carbon credits for the determined reduction in the total greenhouse gas emissions of the livestock operation (i.e., a reduction in the carbon footprint of the livestock operation). In addition, the GHG monitoring server 102 may be configured to provide users of the user computer device with GHG indicators that may be useful for monitoring the overall generation of greenhouse gas emissions and the ongoing reduction of those greenhouse gas emissions. The GHG monitoring server 102 may also identify recommendations for possible improvements that can be taken in the livestock operation's work to further reduce the total greenhouse gas emissions of that livestock operation.

[0067] The GHG monitoring server 102 may be embodied as any type of computing or computer device capable of performing the functions described herein, including but not limited to servers, rack-mount servers, blade servers, workstations, network appliances, web appliances, desktop computers, laptop computers, tablet computers, smartphones, consumer electronics, distributed computing systems, and / or multiprocessor systems. Furthermore, in some embodiments, the GHG monitoring server 102 may be embodied as a “virtual server” formed from multiple computing devices distributed across network 106 and operating in a public or private cloud. Thus, although the GHG monitoring server 102 is shown in Figure 1 as embodied as a single computing device, it should be understood that the GHG monitoring server 102 may be embodied as multiple devices cooperating to facilitate the functions described below.

[0068] As shown in Figure 1, the exemplary GHG monitoring server 102 includes a computing circuit 120, an I / O subsystem 126, a data storage device 128, and a communication subsystem 130. Naturally, the GHG monitoring server 102 may include other or additional components, such as those commonly found in a typical server or other computer (e.g., various input / output devices), in other embodiments. Furthermore, in some embodiments, one or more of the exemplary components may be incorporated into another component or otherwise form part of another component.

[0069] The computing circuit 120 may be embodied as any type of device or set of devices capable of performing various computing functions. In some embodiments, the computing circuit 120 may be embodied as a single device such as an integrated circuit, an embedded system, a field-programmable array (FPGA), a system-on-a-chip (SOC), or other integrated system or device. Furthermore, in some embodiments, the computing circuit 120 includes a processor 122 and memory 124, or is embodied as a processor 122 and memory 124. The processor 122 may be embodied as any type of processor capable of performing the functions described herein. For example, the processor 122 may be embodied as a single or multi-core processor, a digital signal processor, a microcontroller, or other processor or processing / control circuit. Similarly, the memory 124 may be embodied as any type of volatile or non-volatile memory or data storage capable of performing the functions described herein. During operation, the memory 124 may store various data and software used during the operation of the GHG monitoring server 102, such as operating systems, applications, programs, libraries, and drivers.

[0070] The computing circuit 120 is communicably coupled to other components of the GHG monitoring server 102 via an I / O subsystem 126, which may be embodied as a circuit and / or component to facilitate input / output operations using the computing circuit 120 (e.g., the processor 122 and / or memory 124) and other components of the GHG monitoring server 102. For example, the I / O subsystem 126 may be embodied as a memory controller hub, an input / output control hub, a firmware device, communication links (i.e., point-to-point links, bus links, wires, cables, optical conductors, printed circuit board traces, etc.), and / or other components and subsystems, or otherwise include them, to facilitate input / output operations. In some embodiments, the I / O subsystem 126 may be incorporated into the computing circuit 120 together with the processor 122, memory 124, and other components of the GHG monitoring server 102.

[0071] The data storage device 128 may be embodied as one or more devices of any type configured for short-term or long-term storage of data, such as memory devices and circuits, memory cards, hard disk drives, solid-state drives, or other data storage devices. The communication subsystem 130 of the GHG monitoring server 102 may be embodied as any communication circuit, device, or set thereof that can enable communication between the GHG monitoring server 102 and the user computer device 104 over the network 106. The communication subsystem 130 may be configured to achieve such communication using any one or more communication technologies (e.g., wireless or wired communication) and associated protocols (e.g., Ethernet, Bluetooth®, Bluetooth Low Energy (BLE), Wi-Fi®, WiMAX, 3G LTE, 5G, etc.).

[0072] The user computer device 104 may be embodied as any type of computer device capable of performing the functions described herein. For example, the user computer device 104 may be embodied as a smartphone, mobile computer device, computer, laptop computer, notebook computer, tablet computer, wearable computing device, processor-based system, and / or home electronic device, but is not limited to these. In exemplary embodiments, each user computer device 104 is embodied, in some embodiments, as a personal computer device on which each user can maintain a personal digital calendar. The personal digital calendar may be stored locally on the user computer device 104 or on another computer device of the system 100 (e.g., the GHG monitoring server 102 or a third-party server).

[0073] As shown in Figure 1, similar to the GHG monitoring server 102, the user computer device 104 includes a computing circuit 150, an I / O subsystem 156, an output device 158, and a communication subsystem 160. Naturally, the user computer device 104 may include other or additional components, such as those commonly found in mobile computer devices (e.g., short-term and / or long-term data storage) in other embodiments. Furthermore, in some embodiments, one or more of the exemplary components may be incorporated into another component or otherwise form part of another component.

[0074] The computing circuit 150 may be embodied as any type of device or set of devices capable of performing various computing functions. In some embodiments, the computing circuit 150 may be embodied as a single device such as an integrated circuit, an embedded system, a field-programmable array (FPGA), a system-on-a-chip (SOC), or other integrated system or device. Furthermore, in some embodiments, the computing circuit 150 includes a processor 152 and memory 154, or is embodied as a processor 152 and memory 154. The processor 152 may be embodied as any type of processor capable of performing the functions described herein. For example, the processor 152 may be embodied as a single or multi-core processor, a digital signal processor, a microcontroller, or other processor or processing / control circuit. Similarly, the memory 154 may be embodied as any type of volatile or non-volatile memory or data storage capable of performing the functions described herein. During operation, the memory 154 may store various data and software used during the operation of the user computer device 104, such as an operating system, applications, programs, libraries, and drivers.

[0075] The computing circuit 150 is communicably coupled to other components of the user computer device 104 via an I / O subsystem 156, which may be embodied as a circuit and / or component to facilitate input / output operations using the computing circuit 150 (e.g., the processor 152 and / or memory 154) and other components of the respective user computer device 104. For example, the I / O subsystem 156 may be embodied as a memory controller hub, an input / output control hub, a firmware device, communication links (i.e., point-to-point links, bus links, wires, cables, optical conductors, printed circuit board traces, etc.), and / or other components and subsystems, or otherwise include them, to facilitate input / output operations. In some embodiments, the I / O subsystem 156 may be incorporated into the computing circuit 150 together with the processor 152, the memory 154, and other components of the respective user computer device 104.

[0076] The output device 158 may be embodied as any type of output device capable of presenting output or information to the users of each user computer device 104. For example, in an exemplary embodiment, the output device 158 may be embodied as a visual output device such as a display screen, or otherwise embodied to include such a visual output device.

[0077] The communication subsystem 160 of the user computer device 104 may be embodied as any communication circuit, device, or set thereof that can enable communication between the user computer device 104, the GHG monitoring server 102, and / or other computer devices of the system 100. The communication subsystem 160 may be configured to achieve such communication using any one or more communication technologies (e.g., wireless or wired communication) and associated protocols (e.g., Ethernet, Bluetooth®, Bluetooth Low Energy (BLE), Wi-Fi®, WiMAX, 3G LTE, 5G, etc.).

[0078] As will be discussed in more detail below, the GHG monitoring server 102 is configured to communicate with user computer devices and / or other devices of system 100 via network 106. Network 106 may be embodied as any number of different wired and / or wireless networks. For example, network 106 may be embodied as a publicly accessible global network such as a wired or wireless local area network (LAN), a wired or wireless wide area network (WAN), a cellular network, and / or the Internet, or otherwise include these. Thus, network 106 may include any number of additional devices such as additional computers, routers, stations, and switches to facilitate communication between devices of system 100.

[0079] In some embodiments, system 100 may also include a herd management system 110, a feed management system 112, and / or a utility management system 114, each of which may communicate with a GHG monitoring server 102 via a local network 116 (e.g., a local area network) and / or network 106. The herd management system 110 may be embodied as any hardware and / or software components configured to provide management services for the herd of a livestock operation (e.g., maintaining or determining the number of each breed in the herd). Similarly, the feed management system 112 may be embodied as any hardware and / or software components configured to provide management services for the feed provided to the herd of a livestock operation (e.g., maintaining or determining the total amount of each component of the feed per breed). Furthermore, the utility management system 114 may be embodied as any hardware and / or software components configured to provide management services for the use of utilities in a livestock operation (e.g., maintaining or determining utility use for each breed). Furthermore, in some embodiments, the system 100 may further include one or more sensors 118 that can be used by one or more of the management systems 110, 112, and 114 when determining the provision of relevant management services. For example, the sensors 118 may include a cattle sensor configured to generate sensor data indicating the number of cattle as they move from one monitoring station to another, or a feed sensor configured to generate sensor data indicating the total amount of feed provided to different cattle breeds.

[0080] Referring here to Figure 2, as discussed above, the GHG monitoring server 102 is configured to determine the total greenhouse gas emissions (and / or reductions thereof) of each livestock operation using a controllable total greenhouse gas emissions mathematical model 200. As shown, the mathematical model 200 includes several inputs, including a feed component use input 202, a utility use input 204, and a herd composition and productivity use 206. As will be discussed in more detail below, the feed component use input 202 defines the amount of feed provided to each breed during the baseline / reporting period and includes the identification of any feed additives contained in the feed (e.g., monensin and 3-nitrooxypropanol). The utility use input 204 defines the amount of utility services (e.g., fuel and / or electricity) used by the livestock operation during the baseline / reporting period. Furthermore, the herd composition and productivity use 206 defines the number and breeds of individuals in the herd, as well as the amount of milk produced by each milking cow breed in the herd.

[0081] As discussed above, the mathematical model 200 includes several submodels that determine the total controllable greenhouse gas emissions from livestock operations. Specifically, the submodels are included for each of the included emission sources, as identified in Table 2400 in Figure 4. In an exemplary embodiment, the mathematical model 200 includes greenhouse gas emissions from the feed cultivation submodel 210, greenhouse gas emissions from the enteric fermentation submodel 212, greenhouse gas emissions from the manure management submodel 214, and greenhouse gas emissions from the utility usage submodel 216.

[0082] Forage cultivation

[0083] The feed cultivation submodel 210 is a mathematical model configured to determine the greenhouse gas emissions from livestock operations due to feed cultivation activities during the baseline / reporting period. Thus, in an exemplary embodiment, the total greenhouse gas emissions from feed cultivation supplied to the herd during the baseline / reporting period are determined based on the following equation (1).

number

[0084] During the ceremony,

number

number

[0085] Total feed greenhouse gas emissions per cattle breed

number

number

[0086] During the ceremony,

number

number

number

number

[0087] Feed elimination coefficient of the diet fed to cattle breed T during the reporting period

number

number

[0088] During the ceremony,

number

number

number

[0089] Furthermore, the GHG emissions MR from the production of milk replacer fed during the reporting period is used in the determination of the total greenhouse gas emissions from the cultivation of feed fed to the herd during the reporting period, as shown in formula (1), but is determined based on formula (4) below.

number

[0090] In the formula, MR is the GHG emissions (kg CO2e) from the production of milk replacer fed during the reporting period, MRI is the amount of milk replacer consumed (DM kg per cow per day), MREF is the emission factor of milk replacer; 12.1 according to Rotz et al., 2021 (kg CO2e per 1 kg DM), PWHfr is the number of pre-weaning replacement cows fed during the reporting period (19.3% of replacement cows aged 0-12 months), and t is the number of days in the reporting period.

[0091] Furthermore, the MRI of milk substitute intake is determined based on the following formula (5).

number

[0092] In the formula, MRI is the amount of milk replacer consumed (DM kg per animal per day), 8.6 is the conversion factor (pounds per gallon), 4 is the conversion factor (quarts per gallon), 2.20462 is the conversion factor (pounds per kilogram), LFV is the volume of liquid feed given (quarts per day), MRP is the percentage of liquid feed that is milk replacer, and MRDM is the dry matter content of the milk replacer (13.0 according to NASEM, 2021). A list of emission factors, including dry matter content, for the sample feed components is shown in Table 25 of Figure 25.

[0093] Intestinal fermentation

[0094] The enteric fermentation submodel 212 is a mathematical model configured to determine the greenhouse gas emissions from livestock operations generated by enteric fermentation in each herd during the baseline / reporting period. To this end, in an exemplary embodiment, the total greenhouse gas emissions from enteric fermentation in the herd during the baseline / reporting period are determined based on the following equation (6).

number

[0095] During the ceremony,

number

number

number

[0096] Methane emissions from intestinal fermentation in cattle breed T during the reporting period

number

number

[0097] During the ceremony,

number

number

[0098] Methane emission factors for cattle breed T during the reporting period

number

number

[0099] During the ceremony,

number

number

number

[0100] Fecal and urine management The manure management submodel 214 is a mathematical model configured to determine the greenhouse gas emissions from livestock operations generated during the baseline / reporting period by manure management work in a cattle herd. To this end, in an exemplary embodiment, the total greenhouse gas emissions from manure management for the baseline / reporting period are determined based on the following equations (9), (10), and (11).

number

number

number

[0101] In the formula, GHG man, p This represents the total amount of GHG emissions (kg CO2e) from manure management during the reporting period.

number

number

number

number

number

number

[0102] Methane emissions from manure production of cattle breed T during the reporting period

number

number

[0103] During the ceremony,

number

number

[0104] Methane emissions from storage / treatment system S by cattle breed T

number

number

[0105] During the ceremony,

number

number

number

number

number

[0106] Volatile solids produced by cattle breed T on a dry matter basis during the reporting period

number

number

number

[0107] During the ceremony,

number

number

number

number

[0108] Nitrous oxide emissions from manure generation of cattle breed T during the reporting period from Equation (11) [Formula] is determined from Equation (16) below. [Formula]

[0109] In the formula, [Formula] is the amount of nitrous oxide emissions from manure generation of cattle breed T during the reporting period (kg N2O), [Formula] is the direct N2O emissions from manure management of cattle breed T during the reporting period (kg N2O), [Formula] is the indirect N2O emissions from leaching of manure of cattle breed T during the reporting period (kg N2O), [Formula] is the indirect N2O emissions from volatilization of NH3 and NO of cattle breed T during the reporting period x (kg N2O).

[0110] Direct N2O emissions from manure management of cattle breed T during the reporting period [Formula] This is determined from the following equations (17) and (18).

number

number

[0111] During the ceremony,

number

number

number

number

number

[0112] Nitrogen excretion by cattle breed T, compiled for the reporting period.

number

number

[0113] During the ceremony,

number

number

number

[0114] Nitrogen intake of cattle breed T during the reporting period

number

number

[0115] During the ceremony,

number

number

[0116] Nitrogen retained by lactating mammals

number

number

[0117] During the ceremony,

number

[0118] Furthermore, nitrogen excretion for all other cattle breeds (e.g., dry cows, juvenile cows, and beef cattle) is determined using the following formula (22).

number

[0119] During the ceremony,

number

number

[0120] Indirect N2O emissions from manure leaching for cattle type T during the reporting period [Mathematical formula] is determined using the following equation (23). [Mathematical formula]

[0121] wherein, [Mathematical formula] is the indirect N2O emissions from manure leaching for cattle type T during the reporting period (kg N2O), [Mathematical formula] is the total nitrogen from cattle type T managed by storage system S during the reporting period (kg N), [Mathematical formula] is the fraction of managed manure nitrogen losses due to runoff and leaching during solid and liquid storage of manure in manure management system S for cattle type T (IPCC, 2019a, Table 10.22), and EF5 is the emission factor for N2O emissions from nitrogen leaching and runoff (IPCC, 2019b, Table 11.3; kg N2O-N per 1 kg of leached and runoff nitrogen),

number

[0122] NH3 and NO of cattle T during the reporting period x Indirect N2O emissions due to volatilization

number

number

[0123] During the ceremony,

number

number

number

number

[0124] Utility (fuel and electricity) usage

[0125] The utility usage submodel 216 is a mathematical model configured to determine greenhouse gas emissions from livestock operations generated during the reference / reporting period from utility usage. To this end, in an exemplary embodiment, the total greenhouse gas emissions from utility usage for the reference / reporting period are determined based on the following Equation (25). [Formula]

[0126] In the equation, GHG fuel&electricity is the total greenhouse gas emissions (kg CO2e) from fuel and power usage during the reporting period, GHG fuel is the total greenhouse gas emissions (kg CO2e) from fuel usage during the reporting period, and GHG electricity is the total greenhouse gas emissions (kg CO2e) from power usage during the reporting period.

[0127] The total greenhouse gas emissions GHG from fuel usage during the reporting period fuel is determined based on the following Equation (26). [Formula]

[0128] In the equation, GHG fuel is the total greenhouse gas emissions (kg CO2e) from fuel usage during the reporting period, F T is the fuel usage amount of fuel type T during the reporting period (in units according to the fuel types presented in Table 2600 of Figure 26), [Formula] is the combustion emission factor for fuel of fuel type T (kg CO2e / unit of fuel type, EIA value), [Formula] This is the emission factor for fuel extraction and processing of fuel type T (Rotz et al., 2019).

[0129] Total greenhouse gas emissions (GHG) from electricity use during the reporting period. electricity This is determined using the following formula (27).

number

[0130] In the formula, GHG electricity is the total greenhouse gas emissions from electricity use during the reporting period (kg CO2e), U is the electricity use during the reporting period (kWh), and eGRID is the state-specific emission factor (lb / MWh) obtained from the EPA Emissions & Generation Resource Integrated Database, where 2.20462 is lb / kg and 1000 is kWh / MWh.

[0131] Referring again to Figure 2, mathematical model 200 includes the total greenhouse gas emissions from the controllable emission source submodel 220, thereby determining the total greenhouse gas emissions from livestock operations based on the outputs of submodules 210, 212, 214, and 216 according to equation (28).

number

[0132] During the ceremony,

number

number

number

number

[0133] Output of submodel 220

number

number

[0134] During the ceremony,

number

number

number

[0135] In some embodiments, the controllable total greenhouse gas emissions model 200 may also include an allocation submodel 230 configured to allocate the total greenhouse gas emissions to cattle breed T determined by a submodel 220. In such embodiments, the allocation submodel 230 may include greenhouse gases from dairy and meat production submodels 232, which are configured to allocate the determined greenhouse gas emissions using the following equations (30) and (31).

number

number

[0136] During the ceremony, AF milk This is the allocation coefficient for milk (the proportion of the overall dairy carbon footprint allocated to milk production), and AF meat This is the allocation coefficient for meat category i (the proportion of the total dairy carbon footprint allocated to meat production from meat category i), and NE L This is the net energy requirement for lactation (3.1 MJ / kg of fat- and protein-adjusted milk; Nemecek and Thoma, 2020), and M milk This is the total weight (kg) of fat- and protein-adjusted milk.

number

number

[0137] Furthermore, the allocation submodel 230 may include greenhouse gases from a cattle breed-based utility usage submodel 234, which is configured to allocate utility usage based on cattle breed using the following equation (32).

number

[0138] During the ceremony,

number

[0139] Referring again to Figure 2, as discussed above, the controllable total emissions model 200 is configured to generate a set of greenhouse gas emission indices based on the total greenhouse gas emissions determined by submodel 220 and the overall reduction of greenhouse gas emissions determined by submodel 240. Based on these indices, model 200 may be configured to produce greenhouse gas indices for carbon credits. Furthermore, model 200 may generate a set of greenhouse gas improvement recommendations (e.g., the addition of feed additives) based on the total greenhouse gas emissions determined by submodel 220 and the overall reduction of greenhouse gas emissions determined by submodel 240.

[0140] Referring here to Figure 3, in an exemplary embodiment, the GHG monitoring server 102 is configured to establish an environment 300 during operation. The exemplary environment 300 includes a communications manager, a greenhouse gas estimator 304, and a greenhouse gas index determiner 316, along with a greenhouse gas database 320 and an equation or model database 322. Various components of the environment 300 can be embodied as hardware, firmware, software, or a combination thereof. Thus, in some embodiments, one or more of the components of the environment 300 may be embodied as a set of circuits or electrical devices (e.g., greenhouse gas index determiner circuit 316, greenhouse gas estimator circuit 304, and greenhouse gas index determiner circuit 316, etc.). Naturally, in such embodiments, one or more of these components may form part of the processor 122, the I / O subsystem 126, and / or other components of the GHG monitoring server 102.

[0141] The communication manager 302 is configured to manage communication between the GHG monitoring server 102 and the user computer device 104. To this end, the communication manager 302 may utilize any suitable communication protocol.

[0142] The greenhouse gas emission estimator 304 is configured to determine the total amount of greenhouse gas emissions for livestock operations based on various inputs received from the user computer device 104. To this end, the greenhouse gas emission estimator 304 includes a feed cultivation greenhouse gas emission estimator 306, a gut fermentation greenhouse gas emission estimator 308, a manure management greenhouse gas emission estimator 310, and a utility use greenhouse gas emission estimator 312. The feed cultivation greenhouse gas emission estimator 306 is configured to determine the total amount of greenhouse gas emissions from livestock operations attributable to feed cultivation, using submodel 210 and the relevant formulas discussed above. Similarly, the gut fermentation greenhouse gas emission estimator 308 is configured to determine the total amount of greenhouse gas emissions from livestock operations attributable to gut fermentation, using submodel 212 and the relevant formulas discussed above. The manure management greenhouse gas emission estimator 310 is configured to determine the total greenhouse gas emissions from livestock operations due to manure management, using submodel 214 and the relevant equations discussed above. The utility use greenhouse gas emission estimator 312 is configured to determine the total greenhouse gas emissions from livestock operations due to utility use, using submodel 216 and the relevant equations discussed above.

[0143] The greenhouse gas emission index determination system 316 is configured to generate a set of greenhouse gas emission indices based on the total greenhouse gas emissions determined by submodel 220 and the overall reduction of greenhouse gas emissions determined by submodel 240. As discussed above, the greenhouse gas emission indices may also provide a comparison with a baseline or historical greenhouse gas emission indices for livestock operations, which may provide the user with actionable data to improve the carbon footprint of livestock operations and to claim carbon credits for any reductions. The determined greenhouse gas emission data may be stored in the greenhouse gas database 320, and various mathematical models used by the greenhouse gas monitoring server 102 may be stored in the model database 322.

[0144] Referring here to Figure 4, in an exemplary embodiment, the user computer device 104 is configured to establish an environment 400 during operation. The exemplary environment 400 includes a communication manager 402 and a greenhouse gas database 420. Furthermore, in some embodiments, the environment 400 may also include a livestock herd management interface 404, a feed management interface 406, a utility management interface 408, and a sensor management interface 410. Various components of the environment 400 can be embodied as hardware, firmware, software, or a combination thereof. Thus, in some embodiments, one or more of the components of the environment 400 may be embodied as a set of circuits or electrical devices (e.g., the communication manager circuit 402, the livestock herd management interface circuit 404, the feed management interface circuit 406, the utility management interface circuit 408, and the sensor management interface circuit 410, etc.). Naturally, in such embodiments, one or more of those components may form part of the processor 152, the I / O subsystem 156, and / or other components of each user computer device 104.

[0145] The communication manager 402 is configured to manage communication between the user computer device 104 and the GHG monitoring server 102. To this end, the communication manager 402 may utilize any suitable communication protocol.

[0146] The livestock herd management interface 404 is configured to interface with the livestock herd management system 110 and receive livestock herd management data from that system. Similarly, the feed management interface 406 is configured to interface with the feed management system 112 and receive feed management data from that system, and the utility management interface 408 is configured to interface with the utility management system 114 and receive livestock herd management data from that system. The sensor management interface 410 is configured to interface with the sensor 118 and may form part of the livestock herd management system 110, the feed management system 112, and / or the utility management system 114.

[0147] Referring here to Figures 5A to 5C, when in use, the GHG monitoring server 102 may perform the method of method 500 for managing the carbon footprint of livestock operations. In some embodiments, the operation of method 500 may be performed by one or more components of the environment 300 of the GHG monitoring server 102, as shown in Figure 3.

[0148] Method 500 begins in block 502, where the GHG monitoring server 102 determines whether a login request has been received. If so, Method 500 proceeds to block 504, where the GHG monitoring server 102 logs the user into the server 102. In doing so, the GHG monitoring server 102 may display a user interface 600 to the user on the user computer device 104. The exemplary user interface 600 allows the user to access various links for inputting baseline greenhouse gas emission data from livestock operations, and to select new inputs for the current reporting / baseline period (e.g., this month). These new inputs include feed component use, utility use, and herd composition and productivity, as shown in Figure 6.

[0149] Referring again to Figure 5A, after the user logs in in block 504, method 500 proceeds to block 506, where the GHG monitoring server 102 determines whether a baseline (or historical) set of greenhouse gas emissions has already been established. If not, method 500 proceeds to block 508, where the GHG monitoring server 102 receives baseline (or historical) greenhouse gas emission information from the user. For example, in block 510, the GHG monitoring server 102 may receive farm contact data. To this end, the GHG monitoring server 102 may display a user interface 700 to the user on the user computer device 104, as shown in Figure 7. The user interface 700 provides a data cell in which the user can provide contact information for livestock operations.

[0150] Referring again to Figure 5A, in block 512, the GHG monitoring server 102 may require a user to enter into one or more user agreements to use the services of the GHG monitoring server 102. Furthermore, in block 514, the GHG monitoring server 102 may receive successor cow data from the user. For example, in block 516, the GHG monitoring server 102 may receive successor cow feeding information. To this end, the GHG monitoring server 102 may display a user interface 800 to the user on the user computer device 104, as shown in Figure 8. The user interface 800 provides data cells into which the user can supply various information related to the successor cow, including whether the successor cow was raised on the farm throughout the entire heifer rearing period, the average daily amount of milk and / or milk replacer fed to the pre-weaned calf, and the average percentage of milk that is milk replacer fed to the pre-weaned calf.

[0151] Referring again to Figure 5A, in block 518, the GHG monitoring server 102 may receive manure management data from the user. For example, in block 520, the GHG monitoring server 102 may receive percentage data from the user regarding the type of manure management required for each cattle breed. To this end, the GHG monitoring server 102 may display a user interface 900 to the user on the user computer device 104, as shown in Figure 9. The user interface 900 provides data cells that allow the user to identify the percentage of groups managed by each type of manure management (e.g., dry lot, uncovered anaerobic lagoon, anaerobic digester, etc.).

[0152] Referring again to Figure 5A, in block 522, the GHG monitoring server 102 may receive and / or verify historical input and output data for livestock operations. In some embodiments, historical input / output data may form baseline greenhouse gas emission data. For example, in block 524, the GHG monitoring server 102 may receive and / or verify historical headage for each cow. Furthermore, in block 526, the GHG monitoring server 102 may receive and / or verify daily dry matter intake for each cow. Furthermore, in block 528, the GHG monitoring server 102 may receive and / or verify milk production for dairy cow breeds. To receive and / or verify such information, the GHG monitoring server 102 may be configured to display a user interface 1000 to a user on a user interface device 104. The user interface 100 displays historical / baseline data for each cow breed in the livestock operation, including breed, headage, daily dry matter intake, and milk production.

[0153] Referring again to Figure 5A, after the GHG monitoring server 102 receives and validates baseline / historical greenhouse gas emission data in block 508, or if baseline / historical greenhouse gas emission data has already been established in block 506, method 500 proceeds to block 530. In block 530, the GHG monitoring server 102 determines whether the user wishes to submit new greenhouse gas emission data for the current reporting period. In doing so, the GHG monitoring server 102 may display a user interface 1100 (similar to user interface 600) to the user on the user computer device 104. From the user interface 1100, the user may choose to submit feed component usage data, utility usage data, and / or herd composition and productivity data for the reporting period (e.g., this month). If so, method 500 proceeds to block 532 in Figure 5B. In block 532, the GHG monitoring server 102 receives feed component usage data from each cattle breed for the reporting / baseline period. For example, in block 534, the GHG monitoring server 102 receives a diet identifier 534. Furthermore, in block 536, the GHG monitoring server 102 receives instructions for any feed additives for the current diet. To this end, the GHG monitoring server 102 may present a user interface 1200 to the user on the user computer device 104, as shown in Figure 12. The user interface 1200 allows the user to input a diet identifier for each cattle breed (e.g., milking cows, dry cows, heifers). Furthermore, the user may select indicators to show which feed additives and what types of feed additives are included in that particular diet.

[0154] Referring again to Figure 5B, in block 538, the GHG monitoring server 102 receives the component types for the current data. For example, in block 540, the GHG monitoring server 102 receives the component amounts for each identified component. To this end, the GHG monitoring server 102 may present the user interface 1300 shown in Figure 13 and the user interface 1400 shown in Figure 14 to the user on the user computer device 104. User interface 1300 allows the user to add additional components and select component types from a drop-down menu. User interface 1400 allows the user to input the amount for each identified component.

[0155] Referring again to Figure 5B, after the user has provided feed component usage data, or if the user does not provide such data, method 500 proceeds to block 542. In block 542, the GHG monitoring server 102 receives utility usage data from the user for the reporting period. For example, in block 544, the GHG monitoring server 102 receives utility identifiers for each utility used. In block 546, the GHG monitoring server 102 receives usage and unit type for each identified utility. Furthermore, in block 548, the GHG monitoring server 102 receives the percentage of each identified utility used in dairy operations. To this end, the GHG monitoring server 102 may present a user interface 1500, as shown in Figure 15. The user interface 1500 includes data cells and drop-down windows where the user can submit the utility type, the total number of units used, and the unit type, as well as the percentage of energy used in dairy operations.

[0156] Referring again to Figure 5B, after the user has provided utility usage data, or if the user does not provide such data, method 500 proceeds to block 550. In block 550, the GHG monitoring server 102 receives herd composition and productivity data for the reporting / baseline period. For example, in block 522, the GHG monitoring server 102 receives individual data for each breed. Furthermore, in some embodiments, the GHG monitoring server 102 may also receive sales data for each breed since the last reporting period in block 554. To this end, the GHG monitoring server 102 may present a user interface 1600, as shown in Figure 16. The user interface 1600 includes data cells for each breed, from which the user can submit the current individual count. Furthermore, the user interface 600 includes data cells from which the user can supply the number and weight of cattle sold.

[0157] Referring again to Figure 5B, in block 556, the GHG monitoring server 102 receives breed data from the user for each cow. For example, in block 558, the GHG monitoring server 102 may receive percentage data for each identified breed. To this end, the GHG monitoring server 102 may present a user interface 1700, as shown in Figure 17. The user interface 1700 includes data cells that allow the user to identify the percentage of each breed for each different cattle species.

[0158] Referring again to Figure 5B, in block 560, the GHG monitoring server 102 receives milk production data for dairy cow breeds. For example, in block 562, the GHG monitoring server 102 receives production volume data for each identified milk type. To this end, the GHG monitoring server 102 may present a user interface 1700, as shown in Figure 17. The user interface 1800 includes data cells that allow the user to identify the total production value for each milk type for the current reporting period.

[0159] Referring again to Figure 5B, after the user has provided (or has not provided) herd composition and productivity data for the current reporting period, Method 500 proceeds to block 564 in Figure 5C. In block 564, the GHG monitoring server 102 determines an estimate of the total greenhouse gas emissions resulting from controllable emission sources in livestock operations. To this end, the GHG monitoring server 102 utilizes the controllable total greenhouse gas emissions model 200 described above with respect to Figure 2. For example, in block 566, the GHG monitoring server 102 may use submodel 210 of model 200, as described above, to determine an estimate of greenhouse gas emissions from feed cultivation. Furthermore, in block 568, the GHG monitoring server 102 may use submodel 212 of model 200, as described above, to determine an estimate of greenhouse gas emissions from enteric fermentation. Furthermore, in block 570, the GHG monitoring server 102 may determine an estimate of greenhouse gas emissions from manure management using submodel 214 of model 200, as described above. Furthermore, in block 572, the GHG monitoring server 102 may determine an estimate of greenhouse gas emissions from utility use using submodel 216 of model 200, as described above.

[0160] In some embodiments, in block 574, the GHG monitoring server 102 may be configured to allocate a portion of the total greenhouse gas emissions. For example, in blocks 576 and 578, the GHG monitoring server 102 may allocate the estimated total greenhouse gas emissions attributable to dairy and meat production using submodel 232 of model 200, as described above. Furthermore, in block 580, the GHG monitoring server 102 may allocate estimated utility usage based on cattle breed using submodel 234 of model 200, as described above.

[0161] In block 582, the GHG monitoring server 102 determines the reduction in greenhouse gas emissions relative to baseline / historical emissions. To this end, the GHG monitoring server 102 uses the submodel 240 of model 200 described above with respect to Figure 2 to determine the reduction in greenhouse gas emissions that may be caused at least in part by feed additives.

[0162] In block 584, the GHG monitoring server 102 generates greenhouse gas emission indices based on the estimated total greenhouse gas emissions and the estimated reductions in total greenhouse gas emissions. Such indices may be presented as a comparison to baseline / historical data. For example, the GHG monitoring server 102 may present user interface 1900 shown in Figure 19, user interface 2000 shown in Figure 20, and / or user interface 2100 shown in Figure 21. User interface 2100 shows the carbon footprint of livestock operations by emission sources. Furthermore, the GHG monitoring server 102 may also determine one or more greenhouse gas emission improvement recommendations in block 586 of Figure 5C.

[0163] After the GHG monitoring server 102 generates and displays the indicator to the user, method 500 proceeds to block 588, where the GHG monitoring server 102 determines whether the user wishes to submit the greenhouse gas emission indicator for carbon credits. If so, method 500 proceeds to block 590, where the GHG monitoring server 102 submits the indicator for carbon credits. For example, if the indicator shows a reduction in greenhouse gas emissions over a past reporting period, the livestock operation may receive carbon credits for such a reduction. Thus, the described system and methodology can support the receipt of carbon credits for livestock operations using the described feed additives.

[0164] While this disclosure is illustrated and described in detail in the drawings and the foregoing description, such illustrations and descriptions should be considered illustrative and not limiting in nature, and it should be understood that only exemplary embodiments are shown and described, and that all changes and modifications that fall within the scope of the intent of this disclosure should be protected.

[0165] There are several advantages of this disclosure arising from the various features of the methods, apparatus, and systems described herein. It should be noted that alternative embodiments of the methods, apparatus, and systems of this disclosure may not include all of the features described, but still benefit from at least some of the advantages of such features. Those skilled in the art may readily devise their own implementations of the methods, apparatus, and systems incorporating one or more of the features of the present invention, within the spirit and scope of this disclosure as defined by the appended claims.

Claims

1. A method for managing the carbon footprint of a livestock farm operation that has a herd of cattle including one or more breeds, Receiving feed component usage data for each breed of cattle in the herd, via a server computer and for a standard period of the livestock operation, wherein the feed component usage data includes the amount of feed provided to each breed of cattle in the herd and identification of feed additives contained in the feed, wherein the feed additives are configured to reduce greenhouse gas emissions generated by each cattle in the herd that consume the feed. The server computer, and for the base period of the livestock operation, determines the estimated total controllable greenhouse gas emissions of the livestock operation by using a model of total controllable greenhouse gas emissions together with the feed component usage data as input to the model. A method comprising: using the server computer to request carbon credits for the livestock operation based on the estimated total controllable greenhouse gas emissions for the livestock operation for the base period of the livestock operation.

2. The method according to claim 1, wherein the feed additive is monensin.

3. The method according to claim 1, wherein the feed additive is 3-nitrooxypropanol.

4. The method according to claim 1, wherein the greenhouse gas emissions include methane.

5. The method according to claim 1, wherein the herd includes dairy cows.

6. The method according to claim 1, wherein the herd of cattle includes beef cattle.

7. The method according to claim 1, wherein the feed additive is configured to reduce greenhouse gas emissions generated by each cow in the herd that consumes the feed by reducing intestinal fermentation in each cow.

8. The method according to claim 1, wherein the feed additive is configured to reduce the greenhouse gas emissions generated by each cow in the herd that consumes the feed by reducing the dry matter intake (DMI) of each cow.

9. The method according to claim 1, wherein the amount of feed provided to each cattle breed includes a plurality of components and a corresponding amount of each of the plurality of components.

10. The server computer further includes receiving utility usage data indicating the amount of utility services used by the livestock operation for the reference period of the livestock operation, The method according to claim 1, wherein determining the estimated total controllable greenhouse gas emissions for the livestock operation includes determining the estimated total controllable greenhouse gas emissions for the livestock operation by using a model of total controllable greenhouse gas emissions together with (i) feed component usage data and (ii) utility usage data as inputs to the model.

11. The method according to claim 10, wherein receiving the utility usage data includes receiving the percentage of use of the utility services used in the dairy farming operations of the livestock operations.

12. The server computer further includes receiving herd composition data indicating the number and breed of cattle in the herd for the reference period of the livestock operation, The method of claim 10, wherein determining the estimated total controllable greenhouse gas emissions for the livestock operation includes using a model of total controllable greenhouse gas emissions together with (i) feed component usage data, (ii) utility usage data, and (iii) herd composition data as inputs to the model to determine the estimated total controllable greenhouse gas emissions for the livestock operation.

13. The method according to claim 12, wherein receiving the herd composition data includes receiving sales data indicating the number of cattle sold from the herd.

14. The server computer receives milk production data that identifies the amount of milk produced by each milking cow breed in the herd for the aforementioned reference period of livestock operations, The method of claim 12, wherein determining the estimated total controllable greenhouse gas emissions for the livestock operation includes using a model of total controllable greenhouse gas emissions together with (i) feed component usage data, (ii) utility usage data, (iii) herd composition data, and (iv) milk production data as inputs to the model to determine the estimated total controllable greenhouse gas emissions for the livestock operation.

15. Determining the estimated total controllable greenhouse gas emissions for the aforementioned livestock farming operations is The server computer determines, for the aforementioned reference period of the livestock operation, the estimated greenhouse gas emissions attributable to feed cultivation in the dairy farm operation, The method according to claim 1, comprising: using the server computer to determine, for the reference period of the livestock operation, the estimated total controllable greenhouse gas emissions for the livestock operation based on the estimated greenhouse gas emissions attributable to feed cultivation.

16. Determining the estimated total controllable greenhouse gas emissions for the aforementioned livestock farming operations is The server computer determines, for the aforementioned reference period of livestock farming operations, the estimated greenhouse gas emissions caused by intestinal fermentation in the cattle herd, The method according to claim 1, comprising determining, by the server computer, the estimated total controllable greenhouse gas emissions for the livestock operation based on the estimated greenhouse gas emissions attributable to intestinal fermentation of the cattle herd for the reference period of the livestock operation.

17. Determining the estimated total controllable greenhouse gas emissions for the aforementioned livestock farming operations is The server computer determines, for the aforementioned reference period of the livestock operation, the estimated greenhouse gas emissions resulting from the management of manure in the livestock operation. The method according to claim 1, comprising: using the server computer to determine, for the reference period of the livestock operation, the estimated total controllable greenhouse gas emissions for the livestock operation based on the estimated greenhouse gas emissions attributable to the manure management of the livestock operation.

18. Determining the estimated total controllable greenhouse gas emissions for the aforementioned livestock farming operations is The server computer determines, for the reference period of the livestock operation, the estimated greenhouse gas emissions resulting from the use of utilities in the livestock operation. The method according to claim 1, comprising: using the server computer to determine the estimated total controllable greenhouse gas emissions for the livestock operation, based on the estimated greenhouse gas emissions attributable to the utility use of the livestock operation for the reference period of the livestock operation.

19. Determining the estimated total controllable greenhouse gas emissions for the aforementioned livestock farming operations is The server computer determines, for the aforementioned reference period of the livestock operation, the estimated greenhouse gas emissions attributable to feed cultivation in the dairy farm operation, The server computer determines, for the aforementioned reference period of livestock farming operations, the estimated greenhouse gas emissions caused by intestinal fermentation in the cattle herd, The server computer determines, for the aforementioned reference period of the livestock operation, the estimated greenhouse gas emissions resulting from the management of manure in the livestock operation. The server computer determines, for the reference period of the livestock operation, the estimated greenhouse gas emissions resulting from the use of utilities in the livestock operation. The method according to claim 1, comprising: using the server computer and determining, for the reference period of the livestock operation, the estimated total controllable greenhouse gas emissions for the livestock operation based on (i) the estimated greenhouse gas emissions attributable to feed cultivation of the dairy operation, (ii) the estimated greenhouse gas emissions attributable to intestinal fermentation of the herd, (iii) the estimated greenhouse gas emissions attributable to manure management of the livestock operation, and (iv) the estimated greenhouse gas emissions attributable to utility use of the livestock operation.

20. The method according to claim 1, wherein determining the estimated total controllable greenhouse gas emissions for the livestock operation includes allocating the estimated total controllable greenhouse gas emissions between the milk production operations and the meat production operations of the livestock operation.

21. The method according to claim 20, further comprising determining the estimated total controllable greenhouse gas emissions for the livestock operation, by allocating utility usage indicating the amount of utility services used by the livestock operation based on the breed of cattle in the herd.

22. Requesting the aforementioned carbon credits Based on the estimated total controllable greenhouse gas emissions for the aforementioned livestock operation and the baseline greenhouse gas emissions, a reduction in greenhouse gas emissions is determined. The method according to claim 1, comprising: the server computer requesting the carbon credits based on the determined reduction in greenhouse gas emissions for the reference period of the livestock operation.

23. Based on the estimated total amount of controllable greenhouse gas emissions, a greenhouse gas emission index is generated. The method according to claim 1, further comprising displaying the greenhouse gas emission index to the user.

24. The method according to claim 23, wherein the greenhouse gas emission index includes a representation of a comparison of the estimated total controllable greenhouse gas emissions for the base period and prior periods.

25. The method according to claim 24, wherein the estimated total controllable greenhouse gas emissions include a plurality of greenhouse gas emission types, and the greenhouse gas emission index identifies the amount of each greenhouse gas emission type.

26. The method according to claim 1, further comprising determining recommended greenhouse gas emission improvement measures for the livestock operation based on the estimated total controllable greenhouse gas emissions.

27. A server computer for managing the carbon footprint of a livestock farm operation having a herd of cattle including one or more breeds, wherein the server computer 1. Processor, 2 A memory in which multiple instructions are stored, and when an instruction is executed by the processor, the server computer, Receiving feed component usage data for each breed of cattle in the herd for the standard period of the livestock operation, wherein the feed component usage data includes the amount of feed provided to each breed of cattle in the herd and the identification of feed additives contained in the feed, and the feed additives are configured to reduce greenhouse gas emissions generated by each cattle in the herd that consume the feed. For the aforementioned reference period of the livestock operation, a model of controllable total greenhouse gas emissions is used together with the feed component usage data as input to the model to determine the estimated total controllable greenhouse gas emissions for the livestock operation. A server computer that performs the following actions: requesting carbon credits for the aforementioned livestock operation over the aforementioned reference period, based on the estimated total controllable greenhouse gas emissions for the said livestock operation.

28. The server computer according to claim 27, wherein the feed additive is monensin.

29. The server computer according to claim 27, wherein the feed additive is 3-nitrooxypropanol.

30. The server computer according to claim 27, wherein the greenhouse gas emissions include methane.

31. The server computer according to claim 27, wherein the herd includes dairy cows.

32. The server computer according to claim 27, wherein the herd of cattle includes beef cattle.

33. The server computer according to claim 27, wherein the feed additive is configured to reduce greenhouse gas emissions generated by each cow in the herd that consumes the feed by reducing intestinal fermentation in each cow.

34. The server computer according to claim 27, wherein the feed additive is configured to reduce the greenhouse gas emissions generated by each cow in the herd that consumes the feed by reducing the dry matter intake (DMI) of each cow.

35. The server computer according to claim 27, wherein the amount of feed provided to each cattle breed includes a plurality of components and a corresponding amount of each of the plurality of components.

36. When the aforementioned plurality of instructions are further executed by the processor, the server computer receives utility usage data indicating the amount of utility services used by the livestock operation for the aforementioned reference period of the livestock operation. The server computer according to claim 27, wherein determining the estimated total controllable greenhouse gas emissions for the livestock operation includes determining the estimated total controllable greenhouse gas emissions for the livestock operation by using a model of total controllable greenhouse gas emissions together with (i) feed component usage data and (ii) utility usage data as inputs to the model.

37. The server computer according to claim 36, wherein receiving the utility usage data includes receiving the percentage of use of the utility services used in the dairy farming operations of the livestock operations.

38. When the aforementioned plurality of instructions are further executed by the processor, the server computer receives herd composition data indicating the number and breed of cattle in the herd for the aforementioned reference period of livestock operation. The server computer according to claim 36, wherein determining the estimated total controllable greenhouse gas emissions for the livestock operation includes using a model of total controllable greenhouse gas emissions together with (i) feed component usage data, (ii) utility usage data, and (iii) herd composition data as inputs to the model to determine the estimated total controllable greenhouse gas emissions for the livestock operation.

39. The server computer according to claim 38, wherein receiving the herd composition data includes receiving sales data indicating the number of cattle sold from the herd.

40. When the aforementioned plurality of instructions are further executed by the processor, the server computer receives milk production data that identifies the amount of milk produced by each breed of dairy cow in the herd for the reference period of the livestock operation. The server computer according to claim 38, wherein determining the estimated total controllable greenhouse gas emissions for the livestock operation includes using a model of total controllable greenhouse gas emissions together with (i) feed component usage data, (ii) utility usage data, (iii) herd composition data, and (iv) milk production data as inputs to the model to determine the estimated total controllable greenhouse gas emissions for the livestock operation.

41. Determining the estimated total controllable greenhouse gas emissions for the aforementioned livestock farming operations is For the aforementioned reference period of the livestock operation, the estimated greenhouse gas emissions attributable to feed cultivation in the dairy farm operation shall be determined, The server computer according to claim 27, comprising determining the estimated total controllable greenhouse gas emissions for the livestock operation based on the estimated greenhouse gas emissions attributable to feed cultivation for the aforementioned reference period of the livestock operation.

42. Determining the estimated total controllable greenhouse gas emissions for the aforementioned livestock farming operations is For the aforementioned reference period of the livestock farming operation, the estimated greenhouse gas emissions due to intestinal fermentation in the cattle herd shall be determined, The server computer according to claim 27, comprising determining the estimated total controllable greenhouse gas emissions for the livestock operation based on the estimated greenhouse gas emissions attributable to intestinal fermentation of the cattle herd for the reference period of the livestock operation.

43. Determining the estimated total controllable greenhouse gas emissions for the aforementioned livestock farming operations is For the aforementioned reference period of the livestock operation, the estimated greenhouse gas emissions resulting from the management of manure in the livestock operation shall be determined, The server computer according to claim 27, comprising determining the estimated total controllable greenhouse gas emissions for the livestock operation based on the estimated greenhouse gas emissions resulting from manure management of the livestock operation for the reference period of the livestock operation.

44. Determining the estimated total controllable greenhouse gas emissions for the aforementioned livestock farming operations is For the aforementioned reference period of the livestock operation, the estimated greenhouse gas emissions attributable to the use of utilities in the livestock operation shall be determined, The server computer according to claim 27, comprising determining the estimated total controllable greenhouse gas emissions for the livestock operation based on the estimated greenhouse gas emissions attributable to the utility use of the livestock operation for the reference period of the livestock operation.

45. Determining the estimated total controllable greenhouse gas emissions for the aforementioned livestock farming operations is For the aforementioned reference period of the livestock operation, the estimated greenhouse gas emissions attributable to feed cultivation in the dairy farm operation shall be determined, For the aforementioned reference period of the livestock farming operation, the estimated greenhouse gas emissions due to intestinal fermentation in the cattle herd shall be determined, For the aforementioned reference period of the livestock operation, the estimated greenhouse gas emissions resulting from the management of manure in the livestock operation shall be determined, For the aforementioned reference period of the livestock operation, the estimated greenhouse gas emissions attributable to the use of utilities in the livestock operation shall be determined, The server computer according to claim 27, comprising determining the estimated total controllable greenhouse gas emissions for the livestock operation based on (i) the estimated greenhouse gas emissions attributable to feed cultivation of the dairy operation, (ii) the estimated greenhouse gas emissions attributable to intestinal fermentation of the cattle herd, (iii) the estimated greenhouse gas emissions attributable to manure management of the livestock operation, and (iv) the estimated greenhouse gas emissions attributable to utility use of the livestock operation, for the reference period of the livestock operation.

46. The server computer according to claim 27, wherein determining the estimated total controllable greenhouse gas emissions for the livestock operation includes allocating the estimated total controllable greenhouse gas emissions between the milk production operations and the meat production operations of the livestock operation.

47. The server computer according to claim 46, further comprising determining the estimated total controllable greenhouse gas emissions for the livestock operation, which includes allocating utility usage indicating the amount of utility services used by the livestock operation based on the breed of cattle in the herd.

48. Requesting the aforementioned carbon credits Based on the estimated total controllable greenhouse gas emissions for the aforementioned livestock operation and the baseline greenhouse gas emissions, a reduction in greenhouse gas emissions is determined. The server computer according to claim 27, comprising requesting carbon credits based on the determined reduction in greenhouse gas emissions for the aforementioned reference period of livestock operations.

49. Based on the estimated total amount of controllable greenhouse gas emissions, a greenhouse gas emission index is generated. The server computer according to claim 27, further comprising displaying the aforementioned greenhouse gas emission index to the user.

50. The server computer according to claim 49, wherein the greenhouse gas emission index includes a display of a comparison of the estimated total controllable greenhouse gas emissions for the base period and prior periods.

51. The server computer according to claim 50, wherein the estimated total controllable greenhouse gas emissions include a plurality of greenhouse gas emission types, and the greenhouse gas emission index identifies the amount of each greenhouse gas emission type.

52. The server computer according to claim 27, wherein, when the plurality of instructions are further executed by the processor, the server computer determines recommended greenhouse gas emission improvement measures for the livestock operation based on the estimated total controllable greenhouse gas emissions.

53. One or more non-temporary computer-readable storage media containing multiple instructions, wherein the instructions, in response to execution, are transmitted to a server computer. Receiving feed component usage data for each breed of cattle in the herd for the standard period of the livestock operation, wherein the feed component usage data includes the amount of feed provided to each breed of cattle in the herd and the identification of feed additives contained in the feed, and the feed additives are configured to reduce greenhouse gas emissions generated by each cattle in the herd that consume the feed. For the aforementioned reference period of the livestock operation, a model of controllable total greenhouse gas emissions is used together with the feed component usage data as input to the model to determine the estimated total controllable greenhouse gas emissions for the livestock operation. One or more non-temporary computer-readable storage media that allows the calculation of carbon credits for the livestock operation over the aforementioned reference period, based on the estimated total controllable greenhouse gas emissions for the livestock operation.

54. The one or more non-temporary computer-readable storage medium according to claim 53, wherein the feed additive is monensin.

55. The non-temporary computer-readable storage medium according to claim 53, wherein the feed additive is 3-nitrooxypropanol.

56. One or more non-temporary computer-readable storage media according to claim 53, wherein the greenhouse gas emissions include methane.

57. The herd of cattle includes dairy cows, and one or more non-temporary computer-readable storage media according to claim 53.

58. The herd of cattle includes beef cattle, one or more non-temporary computer-readable storage media according to claim 53.

59. One or more non-temporary computer-readable storage media according to claim 53, wherein the feed additive is configured to reduce greenhouse gas emissions generated by each cow in the herd that consumes the feed by reducing intestinal fermentation in each cow.

60. One or more non-temporary computer-readable storage media according to claim 53, wherein the feed additive is configured to reduce the greenhouse gas emissions generated by each cow in the herd that consumes the feed by reducing the dry matter intake (DMI) of each cow.

61. The amount of feed provided to each cattle breed comprises a plurality of components and a corresponding amount of each of the plurality of components, according to one or more non-temporary computer-readable storage media according to claim 53.

62. When the aforementioned plurality of instructions are further executed by the processor, the server computer receives utility usage data indicating the amount of utility services used by the livestock operation for the aforementioned reference period of the livestock operation. Determining the estimated total controllable greenhouse gas emissions for the livestock operation comprises determining the estimated total controllable greenhouse gas emissions for the livestock operation by using a model of the total controllable greenhouse gas emissions together with (i) feed component usage data and (ii) utility usage data as inputs to the model.

63. One or more non-temporary computer-readable storage media according to claim 62, wherein receiving the utility usage data includes receiving the percentage of use of the utility services used in the dairy farming operations of the livestock operations.

64. When the aforementioned plurality of instructions are further executed by the processor, the server computer receives herd composition data indicating the number and breed of cattle in the herd for the aforementioned reference period of livestock operation. Determining the estimated total controllable greenhouse gas emissions for the livestock operation comprises determining the estimated total controllable greenhouse gas emissions for the livestock operation by using a model of the total controllable greenhouse gas emissions together with (i) feed component usage data, (ii) utility usage data, and (iii) herd composition data as inputs to the model.

65. One or more non-temporary computer-readable storage media according to claim 64, wherein receiving the herd composition data includes receiving sales data indicating the number of cattle sold from the herd.

66. When the aforementioned plurality of instructions are further executed by the processor, the server computer receives milk production data that identifies the amount of milk produced by each breed of dairy cow in the herd for the reference period of the livestock operation. Determining the estimated total controllable greenhouse gas emissions for the livestock operation comprises using a model of the total controllable greenhouse gas emissions together with (i) feed component usage data, (ii) utility usage data, (iii) herd composition data, and (iv) milk production data as inputs to the model to determine the estimated total controllable greenhouse gas emissions for the livestock operation, one or more non-temporary computer-readable storage media according to claim 64.

67. Determining the estimated total controllable greenhouse gas emissions for the aforementioned livestock farming operations is For the aforementioned reference period of the livestock operation, the estimated greenhouse gas emissions attributable to feed cultivation in the dairy farm operation shall be determined, One or more non-temporary computer-readable storage media according to claim 53, comprising determining the estimated total controllable greenhouse gas emissions for the livestock operation based on the estimated greenhouse gas emissions attributable to feed cultivation for the aforementioned reference period of the livestock operation.

68. Determining the estimated total controllable greenhouse gas emissions for the aforementioned livestock farming operations is For the aforementioned reference period of the livestock farming operation, the estimated greenhouse gas emissions due to intestinal fermentation in the cattle herd shall be determined, One or more non-temporary computer-readable storage media according to claim 53, comprising determining the estimated total controllable greenhouse gas emissions for the livestock operation based on the estimated greenhouse gas emissions attributable to intestinal fermentation of the cattle herd for the reference period of the livestock operation.

69. Determining the estimated total controllable greenhouse gas emissions for the aforementioned livestock farming operations is For the aforementioned reference period of the livestock operation, the estimated greenhouse gas emissions resulting from the management of manure in the livestock operation shall be determined, One or more non-temporary computer-readable storage media according to claim 53, comprising determining, for the reference period of the livestock operation, the estimated total controllable greenhouse gas emissions for the livestock operation based on the estimated greenhouse gas emissions resulting from the manure management of the livestock operation.

70. Determining the estimated total controllable greenhouse gas emissions for the aforementioned livestock farming operations is For the aforementioned reference period of the livestock operation, the estimated greenhouse gas emissions attributable to the use of utilities in the livestock operation shall be determined, One or more non-temporary computer-readable storage media according to claim 53, comprising determining, for the reference period of the livestock operation, the estimated total controllable greenhouse gas emissions for the livestock operation based on the estimated greenhouse gas emissions attributable to the utility use of the livestock operation.

71. Determining the estimated total controllable greenhouse gas emissions for the aforementioned livestock farming operations is For the aforementioned reference period of the livestock operation, the estimated greenhouse gas emissions attributable to feed cultivation in the dairy farm operation shall be determined, For the aforementioned reference period of the livestock farming operation, the estimated greenhouse gas emissions due to intestinal fermentation in the cattle herd shall be determined, For the aforementioned reference period of the livestock operation, the estimated greenhouse gas emissions resulting from the management of manure in the livestock operation shall be determined, For the aforementioned reference period of the livestock operation, the estimated greenhouse gas emissions attributable to the use of utilities in the livestock operation shall be determined, One or more non-temporary computer-readable storage media according to claim 53, comprising determining, for the reference period of the livestock operation, the estimated total controllable greenhouse gas emissions for the livestock operation based on (i) the estimated greenhouse gas emissions attributable to feed cultivation of the dairy operation, (ii) the estimated greenhouse gas emissions attributable to intestinal fermentation of the herd, (iii) the estimated greenhouse gas emissions attributable to manure management of the livestock operation, and (iv) the estimated greenhouse gas emissions attributable to utility use of the livestock operation.

72. Determining the estimated total controllable greenhouse gas emissions for the livestock operation comprises allocating the estimated total controllable greenhouse gas emissions between the milk production operation and the meat production operation of the livestock operation, according to one or more non-temporary computer-readable storage media of claim 53.

73. Determining the estimated total controllable greenhouse gas emissions for the livestock operation further comprises allocating utility usage, indicating the amount of utility services used by the livestock operation, based on the breed of the herd, according to one or more non-temporary computer-readable storage media according to claim 72.

74. Requesting the aforementioned carbon credits Based on the estimated total controllable greenhouse gas emissions for the aforementioned livestock operation and the baseline greenhouse gas emissions, a reduction in greenhouse gas emissions is determined. One or more non-temporary computer-readable storage media according to claim 53, comprising requesting the carbon credits based on the determined reduction in greenhouse gas emissions for the aforementioned reference period of livestock operations.

75. Based on the estimated total amount of controllable greenhouse gas emissions, a greenhouse gas emission index is generated. One or more non-temporary computer-readable storage media according to claim 53, further comprising displaying the aforementioned greenhouse gas emission index to the user.

76. One or more non-temporary computer-readable storage media according to claim 75, wherein the greenhouse gas emission index includes a display of a comparison of the estimated total controllable greenhouse gas emissions for the base period and prior periods.

77. The one or more non-temporary computer-readable storage medium according to claim 76, wherein the estimated total amount of controllable greenhouse gas emissions includes a plurality of greenhouse gas emission types, and the greenhouse gas emission index identifies the amount of each greenhouse gas emission type.

78. The one or more non-temporary computer-readable storage medium according to claim 53, wherein, when the plurality of instructions are further executed by the processor, the server computer determines recommended greenhouse gas emission improvement measures for the livestock operation based on the estimated total controllable greenhouse gas emissions.

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