Method and apparatus for estimating feed intake, and method and system for adjusting feed supply.

Abstract

Regardless of whether the animal husbandry management system is individual or group management, the amount of feed consumed by an animal is estimated based on the composition of bodily fluids collected from the animal under a given environment. [Solution] A method for estimating feed intake according to one embodiment of the present invention involves feeding a target animal (excluding humans) a predetermined feed F, collecting body fluids from the animal after a certain period of time has elapsed, detecting ketones in the body fluids with a detection means, and using the signal output from the detection means, determining the DMI (DMI) from the feed F by the animal based on a relationship formula between the value obtained from the signal and the dry matter intake (DMI). F This includes finding ).

Description

[Technical Field]

[0001] The present invention relates to a method and apparatus for estimating feed intake of animals raised in a certain environment, as well as a method and system for adjusting feed supply. Specifically, the present invention relates to the estimation of feed intake and adjustment of feed supply based on the detection results of ketones in milk produced by the animal or other bodily fluids collected from the animal. [Background technology]

[0002] In recent years, against the backdrop of the increasing scale of farms, the management systems for livestock (industrial animals), including dairy cows, have been shifting from individual management to herd management. As an example of herd management, free-range barns allow for labor-saving management of large numbers of animals, but because there are no individual feeding troughs and feeding is mostly managed to ensure the animals are getting enough feed, it is difficult to ascertain whether each individual cow is consuming sufficient feed.

[0003] If dairy cows with reduced feed intake due to heat stress or limb / hoof problems are left untreated, it will not only lead to decreased milk production and economic losses, but also raise concerns about the development of metabolic diseases with clinical symptoms, such as ketosis.

[0004] In Patent Document 1, the applicants disclosed a method for determining ketosis based on the composition of gases generated from bodily fluids collected from animals such as dairy cows, and proposed a way to easily determine, on-site, whether an animal is suffering from ketosis and / or has a high probability of suffering from ketosis.

[0005] Furthermore, Patent Document 2 proposes a system for automating feeding, milking, and ketosis diagnosis from milk of dairy cows and other dairy-producing animals. [Prior art documents] [Patent Documents]

[0006] [Patent Document 1] International Publication No. 2022 / 014512 [Patent Document 2] Patent No. 5535636 [Patent Document 3] International Publication No. 2011 / 148774 [Non-patent literature]

[0007] [Non-Patent Document 1] K. Minami, M. Matoba, R. Nakakubo and G. Yoshikawa, "Detection of acetone in milk through odor towards monitoring of ketosis in dairy cows", 2024 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN), 2024, pp. 1-4, doi: 10.1109 / ISOEN61239.2024.10556299. [Overview of the project] [Problems that the invention aims to solve]

[0008] According to the technology described in Patent Document 1, it is possible to determine whether an animal is at risk of developing ketosis, and it is expected that necessary measures can be taken for the animal in question before clinical symptoms appear. Furthermore, Patent Document 2 describes a system in which, when an analytical device determines that a target dairy animal is at risk of ketosis, a specific additive is automatically added to the feed.

[0009] However, animals at risk of diseases such as ketosis are likely to have altered (decreased) feed intake compared to healthy animals, and the extent of this change is unknown. Therefore, adjusting the appropriate amount and / or menu of feed for these animals is not easy, whether through an automated system or manual intervention by the farmer. In the case of individual management, for example in tie-stall barns, farmers can check milk yield and feed intake during milking and feeding, but if objective indicators are provided, they are expected to be useful as a tool to support livestock management.

[0010] Therefore, the present invention aims to estimate the feed intake of animals based on the composition of bodily fluids collected from animals raised in a certain environment, regardless of whether the animal husbandry management system is individual management or group management. Furthermore, the present invention aims to enable the adjustment of appropriate feed amounts and / or menus for target animals by utilizing the feed intake thus estimated. [Means for solving the problem]

[0011] The features of the present invention for achieving the above objective are as follows.

[0012] The feed intake estimation method according to the present invention involves feeding a target animal (excluding humans) a predetermined feed F, collecting body fluids from the animal after a certain period of time, detecting ketones in the body fluids using a detection means, and using the signal output from the detection means to determine the DMI from the animal's feed F based on a relationship formula between the value obtained from the signal and the dry matter intake (DMI). F This includes finding the above problem.

[0013] The method for estimating feed intake of the present invention may further include a process of determining the relational expression before feeding the feed F, the process of preparing first to third test feeds having different dry matter amounts (DM) in a predetermined environment in which the animals are raised, feeding the first test feed to the animals, collecting body fluids from the animals after a certain period of time has elapsed since ingestion, and detecting ketones in the body fluids with a detection means, feeding the second test feed to the animals, collecting body fluids from the animals after a certain period of time has elapsed since ingestion, and detecting ketones in the body fluids with a detection means, and feeding the third test feed to the animals, collecting body fluids from the animals after a certain period of time has elapsed since ingestion. The method may include detecting ketones in the body fluid using a detection means, performing the same steps as when using the first to third test feeds using a fourth to nth test feed (n is a natural number of 5 or more) having a predetermined DM, considering the DM of the first to third test feeds and the optional fourth to nth test feeds as the dry matter intake (DMI) by the animal from the first to third test feeds and the optional fourth to nth test feeds, and determining an expression that represents the relationship between the DMI and a value V obtained from the signal output from the detection means using the first to third test feeds and the optional fourth to nth test feeds.

[0014] Furthermore, in the feed intake estimation method of the present invention, the DMI F After determining the relation, the process may further include a process to make the relation modifiable, wherein the DM(DM) of the feed F F ) and the aforementioned DMI F This may include calculating the difference between and and determining whether the difference satisfies a predetermined appropriate level. Here, If the above difference satisfies the above appropriate level, the above relational expression may be maintained and the process may be terminated. If the above difference does not meet the above appropriate level, feed F1 having a different DM than feed F is given to the animal, a certain period of time is elapsed, and body fluid is collected from the animal, and ketones in the body fluid are detected by a detection means, and the value V obtained from the signal output from the detection means is obtained. F1 Using the above relational expression, DMIF1 is determined, and the DM of the feed F1 (DM F1 ) and the DMI F1 are used to determine a ratio therebetween, when the ratio satisfies a predetermined condition set based on the appropriate level, it is regarded that the animal has appropriately ingested the feed F1, and using the DMI F1 , the value V F1 , the DMI and the value V that are the basis of the relational expression, and optionally the DM F and the V F , an expression representing the relationship with DMI (DMI x ) from a feed having a predetermined DM (DM x ) by the animal may be determined, the obtained expression may be replaced with the relational expression, and the process may be terminated, when the ratio does not satisfy the predetermined condition set based on the appropriate level, a feed F having a DM different from that of the feed F1 m (m is a natural number of 2 or more) is used to perform the same steps as those performed using the feed F1, and the steps using the feed F in which m is incremented by 1 from 2 are repeated until the predetermined condition is satisfied, m when the predetermined condition is satisfied, it is regarded that the animal has appropriately ingested the feed F m , and using the DMI Fm , the value V Fm , the DMI and the value V that are the basis of the relational expression, and optionally the DM F and the V F , the DM F(m-1) to DM F1 , and the V F(m-1) to V F1 , an expression representing the relationship with DMI (DMI x ) from a feed having a predetermined DM (DM x ) by the animal is determined, the obtained expression is replaced with the relational expression, and the process may be terminated. Here, the appropriate level is based on the normal DMI of the animal, and the DM F and the DMI F the difference (DM F -DMI FThe value of ) may be expressed as a certain conditional expression that indicates the range that should be satisfied, and the predetermined conditions set based on the appropriate level are based on the conditional expression of the appropriate level and the normal DMI of the animal, and the DM F1 and the aforementioned DMI F1 Ratio to (DM) F1 :DMI F1 ) value or the DM Fm and the aforementioned DMI Fm Ratio to (DM) Fm :DMI Fm It may be expressed as a certain conditional expression that indicates the range that the value of ) must satisfy.

[0015] Furthermore, in the feed intake estimation method of the present invention, the above relational expression is a predetermined feed F x The formula may represent the difference between the theoretical DMI and the actual DMI. Here, when the difference is expressed as kV (where k is a predetermined coefficient) using a value V obtained from the signal output from the detection means, the feed intake estimation method of the present invention is the formula that represents the difference between the theoretical DMI and the actual DMI. F After determining the relation, the process may further include a process to make the relation modifiable, wherein the DM(DM) of the feed F F ) and the aforementioned DMI F This may include calculating the difference between and and determining whether the difference satisfies a predetermined appropriate level. Here, If the above difference satisfies the above appropriate level, the above relational expression may be maintained and the process may be terminated. If the above difference does not meet the above appropriate level, feed F1 having a different DM than feed F is given to the animal, a certain period of time is elapsed, and body fluid is collected from the animal, and ketones in the body fluid are detected by a detection means, and the value V obtained from the signal output from the detection means is obtained. F1 The value V obtained when the aforementioned feed F was given to the animal. F Compared with, Condition "V F1 ≤ V F If the condition is met, then the DM (DM) of feed F1 F1 ) DMI (DMI) from feed F1 by the aforementioned animals F1 ) and the DMI F1And the aforementioned value V F1 And, the DMI and value V that formed the basis of the above relational expression, and optionally, the DM F and the aforementioned V F Using the above, a predetermined DM (DM) is performed by the animal. x DMI (DMI) from feed containing ) x The process can be terminated by finding an equation that represents the relationship between ( ) and the aforementioned relationship, and then substituting the obtained equation for the aforementioned relationship. Condition "V F1 > V F If the condition is met, then feed F has a different DM than feed F1. m (m is a natural number greater than or equal to 2.) Using this, perform the same steps as when using feed F1, under the condition "V Fm ≤ V F(m-1) Feed F, where m is increased by 1 from 2 until the condition is met. m Repeat the steps using the condition "V Fm ≤ V F(m-1) Feed F when the condition is met m (m is a natural number greater than or equal to 2.) DM(DM Fm ) feed F by the aforementioned animals m DMI from (DMI Fm ) and the DMI Fm And the aforementioned value V Fm And, the DMI and value V that formed the basis of the above relational expression, and optionally, the DM F and the aforementioned V F And, DM F(m-1) From DM F1 And, V F(m-1) From V F1 Using the above, a predetermined DM (DM) is performed by the animal. x DMI (DMI) from feed containing ) x You can find an equation that represents the relationship between ( ) and the aforementioned relationship, and then replace the obtained equation with the aforementioned relationship equation and terminate the process. Here, the appropriate level is based on the DMI of the animal under normal conditions, F and the aforementioned DMI F The difference (DM) F -DMI F It may be expressed as a certain conditional expression that indicates the range that the value of ) must satisfy.

[0016] In the feed intake estimation method of the present invention, the animal may be a dairy-producing animal, the collection may be the collection of milk from the dairy-producing animal, and the detection may be the detection of ketones in the milk using a detection means. Here, the detection may be the detection of acetone in the gas generated from the milk using a gas sensor, and the DMI F In determining this, the time-varying pattern of the signal output from the gas sensor may be used to determine the values ​​of the variables included in the relational expression. Furthermore, the gas sensor may be a surface stress sensor.

[0017] The feed intake estimation device according to the present invention comprises at least one detection means for detecting ketones in a sample, a supply means for supplying bodily fluids collected from a target animal to the detection means, and an analysis means for analyzing a signal output from the detection means. The analysis means comprises an input unit to which the signal output from the detection means is input, a calculation unit for calculating a predetermined value using the signal input to the input unit, a storage unit for storing a program executed by the calculation unit, and an output unit for outputting a calculation result including the signal and the value obtained by the calculation. The calculation unit performs the following actions: at least, it refers to a relational expression relating to the dry matter intake (DMI) of the animal stored in the storage unit, calculates the values ​​of the variables included in the relational expression based on the signal, and calculates the DMI of the animal by substituting the calculated values ​​into the relational expression, thereby solving the above problem.

[0018] In the feed intake estimation device of the present invention, the supply means may be configured to supply milk collected from the target dairy-producing animal to the detection means. Here, the supply means may be configured to supply the gas generated from the milk to a gas sensor capable of detecting acetone in the target gas, and the calculation unit may use the time-varying pattern of the signal output from the gas sensor to calculate the values ​​of the variables included in the relational expression. Furthermore, the gas sensor may be a surface stress sensor.

[0019] The feed intake estimation program according to the present invention provides a computer with the function of calculating the values ​​of variables included in a relational expression for the dry matter intake (DMI) of an animal, based on a signal output from a detection means to which bodily fluids collected from the target animal are supplied, and the function of calculating the DMI of the animal by substituting the calculated values ​​into the relational expression, thereby solving the above problem.

[0020] The feed intake estimation system according to the present invention includes a feed supply unit that provides a predetermined feed to a target animal, a detection unit that detects ketones in body fluids collected from the animal, and an analysis unit that uses the signal output from the detection unit to determine the DMI from the feed by the animal based on a relationship formula between the value obtained from the signal and the DMI. The detection unit and the analysis unit are configured using the feed intake estimation device described above, thereby solving the above problem.

[0021] The feed intake estimation system of the present invention may further include a body fluid collection unit for collecting body fluids from the animal, and the body fluid collection unit may be configured to collect body fluids from the animal after a certain period of time has elapsed since the animal was given the feed.

[0022] The feed adjustment method according to the present invention is based on the DMI estimated by the feed intake estimation method described above. F This includes adjusting the amount and / or menu of the animal's feed based on the above, thereby solving the above problem.

[0023] In the feed adjustment method of the present invention, the adjustment is performed by the metabolic energy value calculated based on the DM of the feed F and the DMI. F The difference between the estimated energy intake based on the above is considered to be the energy deficit of the animal, and the DMI F This may include adjusting the feed menu to ensure that the amount of feed does not exceed a certain limit.

[0024] The feed supply adjustment system according to the present invention includes a feed supply unit that supplies a predetermined feed to a target animal, a detection unit that detects ketones in body fluids collected from the animal, and an analysis unit that uses the signal output from the detection unit to determine the DMI from the feed by the animal based on a relationship formula between the value obtained from the signal and the DMI. The detection unit and the analysis unit are configured using the feed intake estimation device described above, and the feed supply unit is configured to adjust the amount of feed and / or menu for the animal based on the feed supply adjustment method described above, thereby solving the above problems. [Effects of the Invention]

[0025] According to the present invention, regardless of whether the animal husbandry management system is individual management or group management, the amount of feed intake of an animal can be estimated based on the composition of bodily fluids collected from the animal under a given environment. Furthermore, according to the present invention, the estimated feed intake can be used to design and / or adjust a feed suitable for the target animal.

[0026] For example, when the target animal is a dairy cow or other milk-producing animal, conventionally, the caretaker has assessed the nutritional status of each individual animal by checking the degree of abdominal distension, skin firmness, body surface temperature felt when touching the skin, body shape, wetness of the nasal speculum, and how well the animal eats when given feed. However, according to the present invention, even caretakers with little experience in animal husbandry can improve animal husbandry management using objective indicators and maintain and manage the desired nutritional status for each individual animal. [Brief explanation of the drawing]

[0027] [Figure 1] A flowchart illustrating the steps of a method for estimating feed intake according to one embodiment of the present invention. [Figure 2] A diagram showing an example of a schematic configuration of a measurement system that can be used in a feed intake estimation device according to one embodiment of the present invention. [Figure 3] A diagram showing an example of an optical microscope image of an MSS. [Figure 4] A conceptual diagram illustrating the time evolution of signal intensity when a sample gas is applied to a surface stress sensor such as an MSS. [Figure 5] A diagram showing an example of the schematic configuration of a feed intake estimation device according to one embodiment of the present invention. [Figure 6] A block diagram showing an example configuration of the analysis means for a feed intake estimation device according to one embodiment of the present invention. [Figure 7] A flowchart illustrating an example of the contents of a feed intake estimation program according to one embodiment of the present invention. [Figure 8] A schematic diagram showing the configuration of a feed intake estimation system according to one embodiment of the present invention. [Figure 9] A schematic diagram illustrating an example of a process that allows modification of the DMI relationship in a feed supply adjustment method according to one embodiment of the present invention. [Figure 10A] This figure shows the relationship between the amount of feed given and the amount of dry matter ingested from each feed in the example. [Figure 10B] A diagram showing the relationship between the amount of feed given and the concentration of NEFA in the blood in the example. [Figure 10C] A diagram showing the relationship between the amount of feed given and the concentration of total ketones in the blood in the example. [Figure 10D] A diagram showing the relationship between the amount of feed given and the acetone concentration in the milk in the example. [Figure 10E] A diagram showing the relationship between the amount of feed given and the MSS output value in the example. [Figure 11A] This figure shows the relationship between DMI on the day of feed administration and blood NEFA concentration the following day in the example. [Figure 11B] This figure shows the relationship between blood NEFA concentration and MSS output value on the same day in the example. [Figure 11C] This figure shows the relationship between the DMI on the feed feeding day and the MSS output value on the following day in the example. [Modes for carrying out the invention]

[0028] Embodiments of the present invention will be described below with reference to the attached drawings.

[0029] The following description of the constituent elements may be based on a typical embodiment of the present invention, but the present invention is not limited to such embodiments. Specifically, the following description will focus on a configuration in which the bodily fluid collected from the target animal is milk, but other bodily fluids collected from animals, such as blood, or bodily fluids that reflect changes in blood components, such as saliva, urine, and sweat, can also be used if they can be obtained relatively easily. In the case of blood, it is possible to avoid imposing additional burden on the animal by reusing a portion of the blood when it is necessary to collect blood for other tests or other purposes. Furthermore, if equipment and collection methods are established that can collect blood from animals in a simple and painless manner, the usefulness of collecting blood at predetermined times (periodically) and using it in the present invention will be further enhanced. In addition, regarding urine, in recent years there has been growing interest in suppressing the generation (volatilization) of ammonia from livestock barns where dairy cows and other animals are raised, and devices for collecting urine have been developed from the viewpoint of more appropriate manure treatment, and attempts have also been made to utilize the collected urine as a substitute for chemical fertilizers. Therefore, by reusing a portion of the urine, it is possible to avoid placing an additional burden on the animals.

[0030] [Method for estimating feed intake] Figure 1 is a flowchart showing the steps of a feed intake estimation method according to one embodiment of the present invention (hereinafter also referred to as "the estimation method of this embodiment").

[0031] The estimation method of this embodiment involves feeding a target animal (excluding humans) a predetermined feed F, collecting milk (body fluid) from the animal after a certain period of time has elapsed (step S110), detecting ketones in the milk (body fluid) with a detection means (step S120), and using the signal output from the detection means, determining the DMI from the feed F by the animal based on a relationship formula between the value obtained from the signal and the dry matter intake (DMI). F This includes determining (step S130).

[0032] In the estimation method of the present embodiment, the above relational expression is, for example, DMI [kg / day] = kV (k is a predetermined coefficient, and V is a value obtained from the above signal (unit is arbitrary).) can be expressed as follows. Alternatively, the above relational expression is, for example, (Predetermined feed F x Difference between theoretical DMI from and actual DMI) [kg / day] = kV (k is a predetermined coefficient, and V is a value obtained from the above signal (unit is arbitrary).) can be expressed as follows.

[0033] In other words, in one aspect, using the value V (unit is arbitrary) obtained from the above signal, it may be possible to determine the DMI from the above feed F (DMI F ) [kg / day]. Also, in another aspect, using the value V (unit is arbitrary) obtained from the above signal, it may be possible to determine the difference [kg / day] between the theoretical DMI (appropriate level) from the above feed F and the actual DMI (DMI F ).

[0034] Furthermore, in the above example, the case where the value V obtained from the above signal is one type, and a predetermined coefficient k is given to the value V is shown, but the value V may be two or more types (that is, V1, V2, ..., V p (p is a natural number of 3 or more.)), and a predetermined coefficient k (that is, k1, k2, ..., k q (q is a natural number of 3 or more.)) may be given to each value V. Here, each coefficient k may be a positive number, a negative number, or zero.

[0035] The estimation method of this embodiment is applicable to animals that secrete milk (which may also be called dairy-producing animals). Examples of dairy-producing animals include, but are not limited to, livestock (industrial animals) such as dairy cows, beef cattle, goats, sheep, water buffalo, yaks, and horses. More preferably, the estimation method of this embodiment is used for the management of livestock raised for milk production, or as an aid to livestock management.

[0036] In the estimation method of this embodiment, it is preferable to detect ketones in the milk using a detection means, or to detect ketones in the gas generated from the milk using a detection means. Compared to using milk (liquid) as a sample, it is expected that the accuracy of estimating feed intake will improve by using the gas generated from the milk as a sample.

[0037] In this specification, "gas generated from milk" refers to gaseous components that volatilize or evaporate from milk under certain conditions, i.e., volatile and evaporated components of milk. These volatile and evaporated components include both aromatic components that can be detected by the human sense of smell and non-aromatic components that cannot be detected by the human sense of smell. It should be noted that there are significant individual differences in the human sense of smell, and the components that can be detected vary greatly from person to person. Therefore, it is not intended to classify the gas generated from the milk sample used in the estimation method of this embodiment based on the presence or absence of aroma, nor is it intended to limit it to either one or the other. Furthermore, when a bodily fluid other than milk is used as the sample to be given to the detection means, the gas generated from that bodily fluid is intended to be the same as the gas generated from the bodily fluid in the above definition, with "milk" replaced by that bodily fluid.

[0038] Specifically, gases generated from milk include, for example, ketones such as acetone; alcohols such as methanol, ethanol, propanol, and butanol; aldehydes such as formaldehyde and acetaldehyde; nitriles such as acetonitrile; organic acids such as formic acid, acetic acid, propionic acid, and butyric acid; and water (water vapor), nitrogen, oxygen, and carbon dioxide. Furthermore, preliminary experiments by the inventors have shown that while the peak positions (m / z values) of gases generated from milk are highly similar, there is a significant difference in peak intensity in the m / z range of approximately 50-80 between ketotic and healthy cows, and it has been confirmed that at least peaks derived from acetone and 2-butanone are included. In addition to the substances mentioned above, the gas produced from milk may also contain substances with an m / z value of approximately 72 (such as 2-butanone, butanal, 2-methoxy-1-propene, and 2-methyl-propanal).

[0039] Ketones contained in milk include acetoacetic acid, β-hydroxybutyric acid, and acetone. However, because acetone is highly volatile, it is not measured in conventional tests that use liquid samples, and β-hydroxybutyric acid and / or acetoacetic acid are used instead. In contrast, the estimation method of this embodiment allows the gas generated from milk to be used as the sample, and the ketones to be detected by the detection means are not limited to β-hydroxybutyric acid and acetoacetic acid, but can also include acetone. Furthermore, since β-hydroxybutyric acid and acetoacetic acid are precursors of acetone, and there is a correlation between the concentrations of β-hydroxybutyric acid, acetoacetic acid, and acetone in the sample, the estimation method of this embodiment allows acetone in the gas generated from milk to be detected by the detection means.

[0040] In the estimation method of this embodiment, the detection means is not particularly limited as long as it can detect the target ketones and output the detection result as some kind of signal. Typically, a liquid detection means can be used when the sample is a liquid, and a gas detection means can be used when the sample is a gas. For example, the latter gas detection means can be a gas sensor, a gas chromatograph, or gas analysis test strips.

[0041] In one embodiment of the estimation method of this embodiment, the gas detection means is a gas sensor, and in this embodiment, a desired value can be obtained using the time-varying pattern of the signal output from the gas sensor. In this context, while the gas chromatograph has a configuration in which, after a liquid sample is given, the components in the sample are thermally vaporized in the sample vaporization chamber and separated in the column section, the gas sensor, in its configuration, does not have an element equivalent to the sample vaporization chamber, and is intended to be capable of detecting a target substance when a gaseous sample is given. Furthermore, in an embodiment in which the gas detection means is a gas analysis test paper, the signal output from the test paper may be a change in the color of the test paper, and in such a case, a desired value can be obtained by expressing the degree of the color change numerically using some index.

[0042] Examples of gas sensors include those that detect changes in physical parameters that occur due to the adsorption of the target molecule (sample molecule). The physical parameters detected by this type of sensor are diverse, but non-limiting examples include surface stress, stress, force, surface tension, pressure, mass, elasticity, Young's modulus, Poisson's ratio, resonant frequency, frequency, volume, thickness, viscosity, density, magnetic force, magnetic quantity, magnetic field, magnetic flux, magnetic flux density, electrical resistance, electric quantity, dielectric constant, power, electric field, charge, current, voltage, potential, mobility, electrostatic energy, capacitance, inductance, reactance, susceptance, admittance, impedance, conductance, plasmon, refractive index, luminosity, and temperature, as well as combinations thereof. Alternatively, gas sensors may also be optical gas sensors that utilize various optical methods, such as NDIR (non-dispersive infrared) sensors that utilize the infrared absorption band specific to the sample molecule.

[0043] In one preferred embodiment, the gas sensor is a surface stress sensor, and more preferably, the surface stress sensor is a film-type surface stress sensor (MSS). In the following description, in order to facilitate understanding of the present invention, the embodiment in which the gas detection means is a gas sensor, and in which the gas sensor is a surface stress sensor, will be used as an example.

[0044] Surface stress sensors can obtain a signal (also called a response signal) for a specific target substance from a single sensing film by selecting an appropriate sensing film material, or they can obtain signals for multiple target substances from a single sensing film in a superimposed form. The former is effective when the target substance to be detected is clearly defined, while the latter, when detecting many target substances, allows for the amplitude and response waveform of the surface stress sensor's response to each target substance to differ from one another by appropriately selecting the sensing film material.

[0045] By utilizing these characteristics, in one embodiment, it is possible to obtain measured values ​​with appropriately combined parameters corresponding to multiple target substances by combining the outputs from multiple surface stress sensors. In this case, by performing pattern matching or machine learning on the outputs of the surface stress sensors, it is possible to appropriately extract features from these outputs and obtain more parameters (values) than the number of surface stress sensors by using a relatively small number of sensors. Of course, this is not the only option, but if other types of gas sensors are available that are particularly convenient for detecting specific components present in the gas generated from milk that are useful for estimating feed intake, such gas sensors can be used in combination with surface stress sensors as needed.

[0046] Alternatively, in another embodiment, a specific component (for example, acetone) that is particularly useful for estimating feed intake can be designated as the target substance, a sensitive membrane material suitable for detecting acetone can be selected, and an output from a surface stress sensor can be obtained. Here, the sensitive membrane material suitable for detecting acetone is not limited to one type, so it is possible to use multiple types of sensitive membrane materials suitable for detecting acetone and combine the outputs from multiple surface stress sensors, and, as described above, it is also possible to perform pattern matching or machine learning on the obtained outputs.

[0047] Figure 2 shows an example of a schematic configuration of a measurement system that can be used in the feed intake estimation device that performs the estimation method of this embodiment. Although Figure 2 shows a configuration in which the above-mentioned MSS is used as the surface stress sensor, this does not mean that the system is not generalizable.

[0048] In the schematic configuration shown in Figure 2, an inert gas (also called purge gas or reference gas) that does not affect the measurement of the gas component to be measured, and that does not interfere with the measurement of the gas component, is supplied to the two gas flow paths from the left side of the figure, as indicated by the white arrows. For example, nitrogen gas or air can be used as the purge gas, and in the embodiment described later, nitrogen gas is used as the purge gas. When performing a simple measurement using air or the like as the purge gas, there is a possibility that the air at the measurement site (farm, etc.) may contain small amounts of gases that may affect the detection of the target substance (for example, organic acids or ammonia generated from feed). In such cases, the concentration of the aforementioned gases can be reduced by simply filtering the air at the measurement site using activated carbon or silica gel. Alternatively, if the influence of such gas concentrations on the detection results does not adversely affect the achievement of the intended measurement accuracy (in such cases, this is referred to as "substantially free of components that affect the detection of the target substance"), then such gas contamination can be ignored. The flow rates of these two gas channels are controlled by a mass flow controller (MFC) installed in each gas channel. Specifically, the gas flow in the two gas channels is switched alternately at desired time intervals, and the gas flow rate is controlled to remain constant on the time axis. Of course, gas flow control is not limited to MFCs; various systems combining pumps and valves may also be used. In this case, the pumps and valves may be installed upstream or downstream of the sample, and it goes without saying that the order in which they are configured, including the positions of the sample and sensors, is also flexible.

[0049] In Figure 2, the upper gas channel supplies a purge gas to the MSS that does not contain the gas components to be measured, thereby desorbing various gases diffused in the sensitive film coated on the surface of the MSS and initializing the MSS. On the other hand, the gas flow through the lower gas channel in Figure 2 is supplied to the MSS containing gas components that have volatilized and evaporated from the sample in a vial placed immediately after the MFC. Of course, if the sample is gaseous from the beginning, or if gases that have volatilized and evaporated from a liquid sample are supplied to the measurement system, a configuration that does not use a vial can be adopted. In the configuration shown in Figure 2, the gas flows from the two gas channels merge in another vial before being supplied to the MSS.

[0050] Furthermore, since the rate of gas adsorption and desorption by the sensitive film on the MSS surface is affected by temperature, it is preferable to maintain the temperature of the measurement system shown in Figure 2 at a desired value. As a means to achieve this, for example, the entire measurement system may be housed in a constant temperature bath, incubator, etc., or the MSS and its peripheral components (hereinafter referred to as the "sensor module" or simply the "module") may be housed in an incubator, etc., while the vial containing the sample is placed outside the incubator, etc., and the temperature of the measurement system is maintained at a desired value. In the latter configuration, when measuring multiple samples, vial replacement work can be performed outside the incubator, etc., which houses the sensor module, so there is an advantage in that temperature maintenance and management of the measurement system (especially the sensor module) is relatively easier compared to the former configuration. In other words, the former configuration is more suitable when measuring a single sample, while the latter configuration is more suitable when measuring multiple samples.

[0051] Furthermore, it is preferable to maintain the temperature of the vial containing the sample at a desired value in Figure 2. This reduces variations in the concentration of gaseous components volatilizing and evaporating from the sample, thereby further improving measurement accuracy. In this case, the temperature of the vial may be the same as or different from the temperature of the measurement system described above. Specifically, the set value for the vial temperature can be any value selected from the range of 5°C to 50°C, such as 5°C, 10°C, 20°C, 25°C, 30°C, 40°C, and 50°C, but is not limited to these.

[0052] Furthermore, the system may also include an information processing device that implements the feed intake estimation method according to the present invention by controlling the operation of various devices within the system such as the MFC, and / or by taking in, recording, and analyzing signals output from the MSS, as well as interfaces and communication devices for exchanging information and commands with external devices, but these are omitted in Figure 2.

[0053] Figure 3 shows an example of an optical microscope image of an MSS. The MSS shown in Figure 3 is formed from a silicon wafer used in semiconductor device technology, cut from a silicon single crystal. Its central circular portion (it may also be a square or other shape) is connected and fixed to the surrounding frame-like portion at four points: top, bottom, left, and right. When a gas component is applied to the MSS, it is adsorbed and desorbed onto a sensitive film coated on the surface of the circular portion. This causes the surface stress applied to the MSS to concentrate in these four fixed regions, resulting in a change in the electrical resistance of the piezoresistive elements provided in these fixed regions. These piezoresistive elements are interconnected by conductive regions (shown as granular regions in Figure 3) provided in the frame-like portion, forming a Wheatstone bridge. A voltage is applied between two opposing nodes of this Wheatstone bridge, and the voltage appearing between the remaining two nodes is extracted as a signal output from the MSS and taken outside the MSS for necessary analysis. The structure and operation of such an MSS are described in detail, for example, in Patent Document 3. In Figure 3, the sensitive film is applied broadly to the surface of the MSS chip, including not only the circular portion but also the frame-shaped portion. This is a condition seen when the sensitive film is applied by spray coating, but since the sensitive film applied to the frame-shaped portion and other areas does not substantially contribute to the sensor signal, it is possible to use it as a sensor without any problems even when applied in this way. Of course, it is also possible to manufacture an MSS with the sensitive film applied only to the circular portion using an inkjet or dispenser.

[0054] Figure 4 shows a conceptual diagram of the time evolution of the signal intensity when a sample gas is applied to a surface stress sensor such as an MSS. Figure 4(a) shows on the time axis whether the gas applied to the MSS is the sample gas or the purge gas. Specifically, during the sample gas injection period when the sample gas is applied, the concentration of the target gas in the gas applied to the MSS is greater than 0. gDuring the purging period, a purging operation is performed by supplying purge gas to flush out the sample gas in the downstream gas channel and to desorb the sample gas components adsorbed on the MSS's sensitive membrane (and the tube wall of the gas channel, etc.), resulting in a sample gas concentration (concentration of the gas to be detected) of 0. Figure 4(b) shows the signal intensity output from the MSS when the gas type shown in Figure 4(a) is switched, with the time axis aligned with Figure 4(a). The signal intensity is governed by many factors, but basically, the main factor is the rate of adsorption and desorption of the component between the gas and the sensitive membrane, caused by the difference in the concentration of the component in the gas near the sensitive membrane on the MSS and the concentration of the same component on the surface of the sensitive membrane. Therefore, the change in signal intensity begins immediately after the gas switch shown in Figure 4(a), and the curve approaches the upper and lower saturation values ​​exponentially. Figure 4(b) shows the curve in the ideal case. The actual shape and maximum value of the curve vary considerably depending on the adsorption / desorption rate to the sensitive membrane and the types of components adsorbed / desorbed to the sensitive membrane, and the range of signal change also often differs significantly. Furthermore, the signal may exhibit more complex temporal changes due to the viscoelastic properties of the sensitive membrane, the diffusion of the target gas into the sensitive membrane, or the physicochemical interaction between the sensitive membrane material and the target gas. In this way, it is possible to determine the amount and concentration of each component in the sample, as well as the ratios between multiple components, based on the temporal changes and amplitude of the signal from the MSS. Specifically, there are sensitive membrane materials that give signals suitable for detecting ketones among the gases generated from milk, and there are also sensitive membrane materials that give signals suitable for detecting alcohols. Therefore, by using a surface stress sensor coated with an appropriately selected material from these to measure the gas generated from milk, or by performing similar measurements using multiple types of surface stress sensors coated with different materials, it is possible to detect target substances based on the composition of the gas generated from milk.

[0055] Here, the adsorption and desorption characteristics of the materials forming the sensitive film are diverse, and some sensitive film materials exhibit responses that deviate from the simplified model described above. However, when analyzing the response of a surface stress sensor, it can be said that using the above model for the initial investigation is often beneficial.

[0056] Although Figure 4 shows the sample gas being supplied to the MSS only once, in measurements using surface stress sensors such as MSS, it is common practice to repeat the measurement as shown in Figure 4 multiple times by alternately supplying the sample gas and purge gas. Hereafter, the set of sample gas injection and the purge associated with that injection will be referred to as the measurement cycle (details will be described later). In addition, unless there are circumstances such as a significant difference between the adsorption rate and desorption rate of a certain component in the sample gas, the sample gas injection period and the purge period are often set to the same length, but of course, the sample gas injection period and the purge period may be set to different length.

[0057] Typically, the gases emitted from the milk being measured are trace components of the milk. Therefore, it can take a relatively long time to obtain valid signal values ​​from the sensor signals generated by the adsorption and desorption of gas components to the sensor. Furthermore, if components that are difficult to desorb remain on the sensor, the reproducibility of the signal value of the next sample gas to be measured may decrease. For this reason, in one embodiment, it may be effective to have different lengths for the sample gas injection period and the purge period in a single measurement cycle. It is preferable to ensure sufficient time for obtaining a valid signal value during the sample gas injection period, and to make the purge period longer than the sample gas injection period. It is also effective to set the measurement sequence of a single measurement cycle as "purge period - sample gas injection period - purge period" so that when performing multiple measurements, purging is substantially performed twice before the second and subsequent sample gas injections. Thus, by extending the purging period relative to the sample gas injection period, the desorption of components adsorbed on the sensitive film on the MSS during sample gas injection becomes more efficient, and the baseline can be made more stable. This is particularly effective in ensuring the detection accuracy of the target substance when measurements are repeated multiple times.

[0058] In other words, if the purge period is short relative to the sample gas injection period, it may negatively affect the detection accuracy of the target substance. In actual measurements, longer measurement times not only reduce the throughput of the measurement, but also make it difficult to stabilize various parameters of the environment inside and outside the measurement system (flow rate, gas pressure, temperature, etc.) for extended periods, and can lead to larger and more expensive measurement systems. Furthermore, since measurement systems usually include active components such as pumps, prolonged temperature changes due to heat generated from these components can also negatively affect the detection accuracy of the target substance. Therefore, in one embodiment, it is desirable to allocate the time of the measurement cycle so that the sample gas injection period (sampling time) is as short as possible while still being able to obtain an effective signal value, and the purge period (purge time) is as long as possible. Alternatively, as a countermeasure when baseline fluctuations are a problem, a reference milk sample (details to be described later) containing predetermined amounts of components that could affect the detection accuracy of the target substance can be prepared. Calibration can then be performed by measuring the gas emitted from the reference milk sample after each measurement, thereby eliminating or mitigating the adverse effects of short-term purging.

[0059] As mentioned above, in a measurement system having the schematic configuration shown in Figure 2, the gas flow in the two gas channels is usually switched alternately at desired time intervals and controlled by an MFC (or pump, etc.) so that the gas flow rate remains constant on the time axis. However, depending on the configuration of the measurement system and the specifications of the gas detection means (MSS in Figure 2), it may be possible to stabilize the baseline more by making the gas flow rate during the purge period greater than the gas flow rate during the sample gas injection period.

[0060] In one aspect of the estimation method of this embodiment, the measurement results of the time change in signal intensity, as shown in Figure 4, obtained by applying a sample gas to a surface stress sensor such as an MSS, are used to determine the value V of one or more variables that are suitable for the above-mentioned relation (hereinafter also conveniently referred to as the "DMI relation").

[0061] Specifically, the measurement results may be used as is, or any data analysis processing may be applied to the measurement results. For example, an arbitrarily selected time point within the measurement cycle time range is used as a reference point, and an offset process is performed based on this point. Then, another arbitrary time point within the above time range is used as a decision point, and the value of the target variable can be obtained by calculating features from the decision point or the values ​​in the vicinity of the decision point. These features may be, for example, the signal intensity after the offset process at the decision point, the slope of the signal graph (waveform) at the decision point, or the average slope or curvature of the signal graph in the vicinity of the decision point. Note that the raw signal without offset processing contains unique information such as the long-term changes in the sensor over time and the current state as the absolute value of the sensor signal, so the raw signal value may be used as is without offset processing, or arbitrary features may be extracted from the raw signal for analysis.

[0062] In this context, offset processing refers to the process of shifting the signal intensity graph in the direction of its intensity axis so that the signal intensity S(t0) at the reference point t0 becomes 0 (generally an arbitrary constant), thereby obtaining the signal intensity S'(t) = S(t) - S(t0) after offset processing.

[0063] As reference points, for example, the time immediately before the start of the sample gas injection period (i.e., the end of the purge period) and the time immediately before the start of the purge period (i.e., the end of the sample gas injection period) may be used, but any other time point may also be used. However, since the gas supplied to the surface stress sensor is switched at the time of switching between purging and injection, the signal from the surface stress sensor may be disturbed near this boundary point. Furthermore, even after the switch is made, there may be a non-negligible time delay before the gas around the surface stress sensor, which is located after passing through a gas flow path of a certain length from the switching mechanism such as a valve, actually switches. If the instability such as this signal disturbance or the effects of the time delay may be problematic, a time point slightly shifted in time from the time of the switch may be adopted as the reference point.

[0064] Furthermore, a point in time arbitrarily selected from the measurement cycle time range can be used as a reference point. After performing an offset process based on this selected point, another arbitrary point within the time range can be used as a decision point, and feature quantities can be obtained from the decision point or values ​​near the decision point. These feature quantities may include, for example, the signal intensity after the offset process at the decision point, the slope of the signal graph at the decision point, or the average slope or curvature of the signal graph near the decision point. Note that if the signal offset amount is sufficiently small, or if the feature quantities obtained from the signal intensity before the offset are sufficiently large, the offset process may be omitted. However, the decision point that satisfies these conditions may vary depending not only on the measurement cycle time length and the sample gas injection and purge periods, but also on the configuration of the measurement system (gas flow path, gas supply method to the measurement system, gas flow rate, etc.), measurement conditions, and, if the gas detection means is a surface stress sensor (more specifically, MSS), the type of sensitive film material. Therefore, it is preferable to confirm in advance, using a reference milk or similar, the combination of reference point and decision point from which feature quantities suitable for the DMI relationship can be extracted for each sensitive film material.

[0065] As mentioned above, in this embodiment, baseline fluctuations can be suppressed and the baseline stabilized by appropriately setting the time allocation of the measurement cycle and the configuration of the measurement sequence. Therefore, even when the differences in the extracted features are minute, the accuracy of the DMI relation can be ensured. Specifically, by extending the purge period, sufficient gas is desorbed from the sensitive membrane, making it possible to return the state before sample gas injection to a similar state each time. In other words, extending the purge period is useful for sufficiently resetting the measurement system. The point at which this sufficient reset is achieved is just before sample gas injection, and signal reproducibility is ensured by using this as the reference point for the offset. In particular, by performing offset processing based on the purge signal just before the start of sample gas injection, and setting the judgment point a short time after the end of the injection period, the fluctuation in signal intensity at the judgment point becomes clearer, and features suitable for the DMI relation can be easily obtained.

[0066] The above explanation assumes a measurement based on a measurement sequence that switches between sample gas and purge gas, but the measurement method is not limited to this. For example, the measurement sequence can be modified to include a measurement of another gas (standard gas) containing components that may affect the determination of the value V of the target variable, and the value V of the target variable can be determined based on the signals from the switching measurements of the three types of gases. Alternatively, as is commonly done in measurements using conventional gas sensors, it is also possible to determine the value V of the target variable based on measurement results obtained by continuously supplying only the sample gas without using a purge gas.

[0067] Here, as the standard gas mentioned above, milk obtained from healthy animals with normal feed intake may be used as the reference milk, and a gas having the same component composition as the sample gas components generated from said reference milk may be used as the standard gas. Such reference milk may be, for example, milk obtained from animals belonging to the same rearing environment as the target animal (hereinafter also referred to as "animals of the same group"), in which case the milk may be individual milk (milk obtained from a single individual; milk obtained from an animal of the same group that is known to be healthy) or mixed milk (milk from which the milk of multiple individuals has been mixed in a milking tank, etc.; also called bulk milk).

[0068] Alternatively, the standard gas can be set to various compositions as needed, such as using a gas with the same composition as some components of the sample gas that are expected to be affected (for example, components for which slight differences in quantity are particularly important to measure with high precision). Then, taking into account various measurement requirements and constraints, the supply sequence of the three types of gases described above is set appropriately. For example, a measurement sequence including repetition of the following gas supply time intervals is conceivable: A. Supply purge gas → [Supply one of the sample gas and standard gas → Supply purge gas → Supply the other of the sample gas and standard gas → Supply purge gas] (or repeat the steps in brackets) B. Supply purge gas → [Alternately supply sample gas and standard gas → Supply purge gas] (or repeat the steps in brackets) C. Supply purge gas → [Repeat alternating supply of one of the sample gas and standard gas with the purge gas → Supply purge gas → Repeat alternating supply of the other of the sample gas and standard gas with the purge gas] (or repeat the steps in brackets) In addition to the above, various gas supply sequences for the gas supply time interval are possible. In any gas supply sequence, measurement conditions such as temperature, gas pressure / flow rate, and changes in sensor characteristics over time are not expected to change significantly within the sequence. Therefore, by comparing the sample gas with the standard gas, minute differences in composition between the two gases can be precisely measured, and the influence of disturbances on the measurement results can be reduced, thereby improving the stability of the measurement.

[0069] Furthermore, if a standard gas is used in addition to the sample gas and purge gas, a gas channel for the standard gas will need to be added to the gas supply system of the measuring instrument. This can be easily achieved using various existing technologies for gas supply systems. For example, the standard gas can be prepared in a gaseous state from the beginning, or it can be introduced into the gas supply system by evaporation from a liquid or solid. Alternatively, when providing the standard gas, another gas, such as a purge gas, can be mixed with the gas that was initially prepared or the gas generated from the liquid or solid. In addition, these three gas channels will eventually need to be merged. The three channels can be merged at one point, or a portion of the upstream side of the sample gas channel can be used to form a standard gas channel, into which the standard gas is introduced, and then the two gas channels can be merged just before the point where they merge with the purge gas.

[0070] Furthermore, if the measurement reproducibility is high to the extent that the required accuracy can be achieved, and variations between sensor chips and measuring devices can be calibrated, it is possible to construct measurement procedures and measurement systems that allow for the measurement of the sample gas and the standard gas to be performed independently at separate, convenient times. For example, instead of performing the measurement of the standard gas and the sample gas simultaneously or successively in a series of measurement sequences, they may be performed separately, and the standard gas measurement data and sample gas measurement data obtained from these measurements may be compared. Here, as long as the conditions mentioned above—that is, the measurement reproducibility is high to the extent that the required accuracy can be achieved, and variations between sensor chips and measuring devices can be calibrated—the sensor chip and measuring device used for measuring the sample gas and the sensor chip and measuring device used for measuring the standard gas may be the same unit, or different sensor chips and measuring devices may be used for one of the measurements. Also, measurements may be performed using only the sample gas and standard gas without using a purge gas. In this case, the standard gas may be used as a purge gas for the measurement. Furthermore, measurements using only the sample gas or only the standard gas are also possible. In this case, the sample gas or standard gas may be exposed to the sensor for a sufficiently long time until the gas is sufficiently adsorbed and diffused onto the sensitive film and the sensor shows a certain signal value. The absolute value of this signal may be used directly as a feature, or the signal obtained when exposed to air or other air for a sufficiently long time before measurement may be measured and used as a reference point.

[0071] While not limited to this, for example, when comparing past milk from the same animal with milk from the current milking result, it is not practical to preserve the past milk itself or its volatile / evaporative components without alteration. Therefore, if the gas obtained from milk from a previously known healthy animal is measured and stored as standard gas data, then the gas obtained from the current milk from the same animal can be similarly digitized as a sample gas. As long as the reproducibility of the measurement and the possibility of calibrating various variability can be ensured, it is possible to compare the above gases from each milk sample while they are all in a fresh state. Note that the format of digitizing the measurement results for each gas is not particularly limited. To give a non-limiting example, it is possible to simply digitize the output from the sensor when switching between each gas and the purge gas, or to digitize the sensor output during other types of measurements, or to further process the digital values ​​of the digitized results as described above.

[0072] Examples of materials for the sensitive membrane of a surface stress sensor include, but are not limited to, Poly(4-methylstyrene), Poly(2,6-diphenyl-p-phenylene oxide), Poly(vinylidene fluoride), Cellulose Acetate Butyrate, Poly(ethyleneimine), Phenyl-modified silica / titania composite nanoparticles (which may also be conveniently referred to as "Phenyl-STNPs"), and Polystyrene. These sensitive membrane materials may be used individually or in combination.

[0073] For example, in an embodiment in which a gas generated from milk is used as the target sample, at least one of the above-mentioned sensitive membrane materials selected from the group consisting of Poly(4-methylstyrene), Poly(2,6-diphenyl-p-phenylene oxide), Poly(vinylidene fluoride), Cellulose Acetate Butyrate, and Poly(ethyleneimine) can be used. Among these, it is preferable to use at least one selected from the group consisting of Poly(4-methylstyrene), Poly(2,6-diphenyl-p-phenylene oxide), Cellulose Acetate Butyrate, and Poly(ethyleneimine).

[0074] Poly(2,6-diphenyl-p-phenylene oxide) is a material also known as "Tenax" or "Tenax" (registered trademark), and several types are commercially available depending on their purity and additives. For example, by adding a suffix to Tenax, you can get Tenax TA or Tenax GR (Tenax GR is Tenax polymerized with 23% graphite carbon), and any of these can be used in the estimation method of this embodiment. Furthermore, Tenax is available in various particle size distributions, and the particle size range is expressed in mesh, for example, Tenax TA 20 / 35.

[0075] The estimation method of this embodiment may further include a process of determining the above-mentioned relational equation before feeding the above-mentioned feed F. In other words, when the estimation method of this embodiment is performed for the first time at a measurement site such as a farm, it is thought that by performing this process in advance, a relational equation more suitable for the environment of that site can be set, and the accuracy of the estimation of feed intake can be improved based on that relational equation, and thus more precise livestock management can be expected. On the other hand, if we assume that the estimation method of this embodiment is to be performed at a specific farmland (which may be interpreted more broadly as a district or region), it may be possible to perform comprehensive livestock management by setting an initial relational equation for that farmland in advance.

[0076] In one exemplary embodiment, the process for determining the above relation is as follows: Prepare first to third test feeds with different dry matter amounts (dry matter weight after deducting water content in the feed: DM) in a predetermined environment in which the target animal is raised; feed the first test feed to the animal; after a certain period of time has elapsed since ingestion, collect body fluid from the animal and detect ketones in the body fluid using a detection means; feed the second test feed to the animal; after a certain period of time has elapsed since ingestion, collect body fluid from the animal and detect ketones in the body fluid using a detection means; feed the third test feed to the animal; after a certain period of time has elapsed since ingestion, collect body fluid from the animal and detect ketones in the body fluid The method includes detecting substances using a detection means, performing the same steps as when using the first to third test feeds using fourth to nth test feeds (n is a natural number of 5 or more) having predetermined DMs as necessary, and considering the DMs of the first to third test feeds and the optional fourth to nth test feeds as the dry matter intake (DMI) by the animals from the first to third test feeds and the optional fourth to nth test feeds, and determining an expression that represents the relationship between the DMI and the value V obtained from the signal output from the detection means using the first to third test feeds and the optional fourth to nth test feeds.

[0077] In other words, the process of deriving the above relational equation is preferably carried out by the DM preparing at least three different test feeds. This ensures a certain level of accuracy for the resulting relational equation. More preferably, by preparing four or more test feeds, the accuracy of the resulting relational equation is expected to increase.

[0078] In the embodiment where the detection means is a gas sensor, if the gas sensor is a surface stress sensor, for example, one or more values ​​V suitable for representing the relationship with DMI can be obtained based on the shape of the signal intensity curve and the maximum value of the curve, as shown in Figure 4(b). In this context, the maximum value of the curve is preferably considered as a candidate for the value V because it can be obtained relatively easily. On the other hand, it is expected that multiple feature values ​​can be obtained from the shape of the curve, and it is possible to find a value that is suitable for representing the relationship with DMI or suitable for use in combination with the maximum value mentioned above.

[0079] Furthermore, the estimation method of this embodiment is the DMI described above. F After obtaining the above-mentioned relation, the process may further include a step to modify the relation. This step may be performed to adjust the relation for each individual animal being raised at a given measurement site, and / or to adjust it according to the growth stage of the animals being raised, if such a relation has been established at that site. Alternatively, as described above, if an initial relation has been established for a particular farmland, this process may allow the relation to be updated based on the results at each measurement site.

[0080] In one exemplary embodiment, the process that makes the above relational expression modifiable is the DM(DM) of the feed F. F ) and the above DMI Fcalculating a difference therebetween, and determining whether the difference satisfies a predetermined appropriate level. Calculating the above difference is substantially synonymous with calculating the difference between the theoretical DMI resulting from feeding feed F and the (estimated value of the) actual DMI. Here, the appropriate level can serve as a criterion for whether the target animal has appropriately ingested the fed feed, and is, for example, based on the normal DMI [kg / day] of the target animal or the like, set as "0 ≦ (DM F -DMI F ) ≦ 1" or the like, which can be expressed by a conditional expression. In the case of this example, it is most preferable that the difference between the theoretical DMI [kg / day] and the actual DMI [kg / day] is 0 (zero), and if the difference is 1.0 [kg / day] or less, this can mean that the ingestion is permitted as appropriate ingestion. However, it should be noted that the above example is merely an illustration, and the value (range) set by the conditional expression may vary depending on the type, growth stage, etc. of the target animal.

[0081] In this embodiment, if the result of the above determination shows that the appropriate level is satisfied, the above relational expression can be maintained and the process can be terminated.

[0082] On the other hand, if the appropriate level is not satisfied, feed F1 having a DM different from that of the feed F is fed to the target animal, and after a certain period of time elapses, a body fluid is collected from the animal, ketones in the body fluid are detected by a detection unit, and a value V obtained from a signal output from the detection unit F1 is used to calculate DMI based on the above relational expression F1 , and the DM of the feed F1 (DM F1 ) and the DMI F1The ratio is calculated, and it is determined whether the ratio satisfies predetermined conditions. Here, the conditions used for this determination can be set based on the appropriate level described above, and can be set based on the perspective of what percentage of the DM of the fed feed (i.e., the theoretical DMI resulting from feeding the feed) the actual DMI (i.e., the DMI obtained based on the above relational expression using the value obtained from the signal output from the detection means) should be compared to the DM of the fed feed (i.e., the theoretical DMI resulting from feeding the feed) for the target animal to be considered to have consumed the feed appropriately. For example, if the normal DMI of the target animal is approximately 20.0 [kg / day], the appropriate level described above is "0 ≤ (DM F -DMI F If the condition is expressed as "(DM of fed feed):(actual DMI) = 1 ≤ 1", it could mean that an amount of 1.0 kg out of 20.0 kg, or approximately 5.0%, or less, is acceptable as an appropriate intake. Therefore, this condition can be expressed as a condition such as "(DM of fed feed):(actual DMI) = 1:1 ~ 1:0.95". In this example, a ratio of 1:1 is most preferable, and a ratio up to 1:0.95, i.e., an actual DMI of 95% or more of the theoretical DMI, could mean that an appropriate intake is acceptable. However, the above example is merely illustrative, and it should be noted that the value (range) set by the condition may differ depending on the type of animal and its growth stage.

[0083] Here, assuming that the condition used to determine the above ratio is the above conditional expression "(DM of fed feed):(actual DMI) = 1:1 ~ 1:0.95", then the above ratio is under the condition "DM F1 :DMI F1 If the ratio "=1:1 ~ 1:0.95" is met, the animals are considered to have adequately consumed feed F1, and the above DMI F1 And the above value V F1 And, the DMI and value V that formed the basis of the above relationship, and optionally, the above DM F and the above V F Using the above animals, a predetermined DM (DM) x DMI (DMI) from feed containing ) xThe process can be terminated by finding an equation that expresses the relationship between ( ) and the above relationship equation, and then substituting the obtained equation into it.

[0084] Conversely, if the above ratio does not satisfy the above conditions, that is, if the above ratio does not satisfy the condition "DM F1 :DMI F1 If the condition "=1: (value less than 0.95)" is met, then feed F has a different DM than the above feed F1. m Using (m is a natural number greater than or equal to 2), perform the same steps as when using feed F1 above, under the condition "DM Fm :DMI Fm Feed F, where m is increased by 1 from 2 until the ratio satisfies "=1:1 ~ 1:0.95". m Repeat the steps using the condition "DM Fm :DMI Fm When the ratio "=1:1 ~ 1:0.95" is satisfied, the above animals feed F m Assuming that the above DMI has been consumed appropriately, Fm And the above value V Fm And, the DMI and value V that formed the basis of the above relationship, and optionally, the above DM F and the above V F And, DM F(m-1) From DM F1 And, V F(m-1) From V F1 Using the above animals, a predetermined DM (DM) x DMI (DMI) from feed containing ) x The process can be terminated by finding an equation that represents the relationship between ( ) and the aforementioned relationship, and then substituting the obtained equation for the aforementioned relationship.

[0085] Here, as another illustrative embodiment, the above relational expression is given by a predetermined feed F x This section describes an equation that represents the difference between the theoretical DMI and the actual DMI, where the difference is expressed as kV (where k is a predetermined coefficient) using the value V obtained from the signal output from the detection means.

[0086] In this embodiment as well, the process that allows the above relational expression to be modified is the DM(DM) of the feed F. F ) and the above DMIF This includes calculating the difference between and and determining whether the difference satisfies a predetermined appropriate level, and if the appropriate level is met, the relational expression can be maintained and the process can be terminated.

[0087] Furthermore, if the above appropriate level is not met, the target animal is fed feed F1 having a different DM than the above feed F, as in the embodiment described above, and after a certain period of time has elapsed, a bodily fluid is collected from the animal and the ketones in the bodily fluid are detected by a detection means. In this embodiment, the value V obtained from the signal output from the detection means is used. F1 The value V obtained when the aforementioned feed F was given to the animal. F This is compared with the above embodiment. Unlike the embodiment described above, in this embodiment, a predetermined coefficient k is given to the value V obtained from the signal output from the detection means, thereby determining the predetermined feed F x The difference between the theoretical DMI and the actual DMI is expressed, therefore the above value V F1 and the above value V F One can adopt the step of comparing the two.

[0088] Specifically, the above value V F1 and the above value V F Compare with the condition "V F1 ≤ V F If the condition is met, then the DM (DM) of feed F1 F1 ) DMI from feed F1 by the above animals (DMI F1 ) and the DMI F1 And the above value V F1 And, the DMI and value V that formed the basis of the above relationship, and optionally, the above DM F and the above V F Using the above animals, a predetermined DM (DM) x DMI (DMI) from feed containing ) x The process can be terminated by finding an equation that represents the relationship between ( ) and the aforementioned relationship, and then substituting the obtained equation for the aforementioned relationship.

[0089] Conversely, the above value V F1 and the above value V F The condition is "V F1> V F If the above condition is met, then feed F has a different DM than feed F1. m (m is a natural number greater than or equal to 2.) Using this, perform the same steps as when using feed F1 above, under the condition "V Fm ≤ V F(m-1) Feed F, where m is increased by 1 from 2 until the condition is met. m Repeat the steps using the condition "V Fm ≤ V F(m-1) Feed F when the condition is met m (m is a natural number greater than or equal to 2.) DM(DM Fm ) Feed F by the above animals m DMI from (DMI Fm ) and the DMI Fm And the above value V Fm And, the DMI and value V that formed the basis of the above relationship, and optionally, the above DM F and the above V F And, DM F(m-1) From DM F1 And, V F(m-1) From V F1 Using the above animals, a predetermined DM (DM) x DMI (DMI) from feed containing ) x The process can be terminated by finding an equation that represents the relationship between ( ) and the aforementioned relationship, and then substituting the obtained equation for the aforementioned relationship.

[0090] In other words, the process that makes the above relational expression modifiable is, first, the DMI described above. F Based on this, it is determined whether the target animal has adequately ingested DM from the above feed F. Here, the criteria for determining whether it is adequate (appropriate level) can be set based on the target animal's normal DMI [kg / day], etc., taking into consideration the type of animal and its growth stage, as described above. For example, the criteria may be the above DM F and the above DMI F Examples include the difference being 1.0 [kg / day] or less. Of course, the value "1.0" is merely an example, so it may be a value less than 1.0 (0.8, 0.75, 0.5, etc.) or a value greater than 1.0 (1.5, 2.0, or any value greater than or equal to 2.0). According to this standard, DMIF If it is determined that the relationship is appropriate, the above relationship can be maintained and the process can be terminated.

[0091] On the other hand, if it is determined that the above appropriate level is not met, it is considered necessary to modify the above relational expression, so a feed F1 with a different DM than the above feed F is prepared and feed F1 is given to the target animal. Here, in the former embodiment described above, the DMI obtained for feed F1 is F1 Based on this, it is determined whether the target animal has adequately ingested DM from the feed F1 (or whether it can be considered that it has ingested it). Furthermore, in the latter embodiment described above, the value V obtained for feed F1 is used. F1 And the value V obtained for feed F. F This is compared with the previous one. Here, in either embodiment, if the predetermined conditions are met, it is considered that the DMI of the animal has recovered to an appropriate level (or is showing a tendency to recover) by feeding feed F1. At this stage, the above relational equation can be modified using the various values ​​mentioned above, and the resulting equation can be replaced with the previous relational equation to terminate the process.

[0092] Alternatively, if the predetermined conditions set in both embodiments are not met, the animal is still considered to have a DMI outside the appropriate level, and therefore, feed F2 with a different DM than feed F1 is prepared. The subsequent procedure is the same as described above, feed F m The above steps are repeated until the above-specified conditions are met, based on the salary (where m is a natural number greater than or equal to 2). Once it is confirmed that the conditions are met, the above relational expression is modified using the various values ​​obtained so far, the resulting expression is replaced with the previous relational expression, and the process is terminated.

[0093] Furthermore, in the latter embodiment described above, the above condition "V F1 ≤ V F "V F1 > V F ", and "V Fm ≤ V F(m-1)It should be noted that the relationships between the inequalities "≦", ">" and "≦" in the above condition can change depending on the type of value V, that is, the type of variable included in the original relation. On the other hand, to put it in terms of clarity, the above condition "V F1 ≤ V F "V F1 > V F ", and "V Fm ≤ V F(m-1) It may also be possible to adjust the sign (positive or negative) of the coefficient k for a given value V so that it is possible to determine whether the feed intake of the target animal is at an appropriate level using this method.

[0094] [Feed Intake Estimator] Figure 5 shows an example of a schematic configuration of a feed intake estimation device according to one embodiment of the present invention (hereinafter also referred to as "the estimation device of this embodiment").

[0095] The estimation device 100 of this embodiment includes at least one detection means 110 for detecting ketones in a sample, a supply means 120 for supplying bodily fluids collected from the target animal to the detection means 110, and an analysis means 130 for analyzing the signal output from the detection means 110. Here, the detection means 110 and the supply means 120 can be configured in the same way as the measurement system described above with reference to Figure 2, so their description will be omitted below.

[0096] Figure 6 is a block diagram showing an example configuration of the analysis means 130 of the feed intake estimation device 100 shown in Figure 5.

[0097] As shown in Figure 6, the analysis means 130 includes an input unit 131 to which a signal output from the detection means 110 is input, a calculation unit 132 that calculates a predetermined value using the signal input to the input unit 131, a storage unit 133 that stores a program executed by the calculation unit 132, and an output unit 134 that outputs the calculation result including the signal and the value obtained by the calculation.

[0098] The memory unit 133 stores a computer program (feed intake estimation program) for executing the feed intake estimation method described above, and also has a storage area for various data that are stored and referenced during program execution. For example, the relational expression 133A relating to the DMI of the target animal is stored in this data storage area. The relational expression 133A is intended to be an expression that can be expressed as, for example, DMI[kg / day]=kV (where k is a predetermined coefficient and V is a value obtained from the above signal (unit is arbitrary)). In addition, the signal input to the input unit 131, the shape of the curve of the signal intensity and the maximum value of the curve, as well as biological information and growth status information of the target animal (body weight, milk yield, feed intake time for each individual, etc.), feed information (feed amount, feed menu, metabolic energy value, etc.), and information on rearing management (rearing location, rearing method, management records, etc.) may also be stored in the data storage area.

[0099] The calculation unit 132 performs predetermined processing based on the feed intake estimation program, and the execution result is output to the output unit 134. Specifically, the calculation unit 132 at least refers to the relational expression 133A stored in the storage unit 133, calculates the value V of the variable included in relational expression 133A based on the signal, and calculates the DMI of the target animal by substituting the calculated value into relational expression 133A. For example, a liquid crystal display device or a printer can be used as the output unit 134. Alternatively, a recording device that records the execution result on a recording medium such as a floppy disk or USB memory may be used as the output unit 134.

[0100] [Feed Intake Estimation Program] Figure 7 is a flowchart showing an example of the contents of the feed intake estimation program executed by the calculation unit 132 of the analysis means 130 shown in Figure 6.

[0101] First, the signal input to the input unit 131 of the analysis means 130 (the signal output from the detection means 110) is acquired (s710). Next, the value V of the variable included in relational expression 133A is calculated based on the signal (s720). Then, the DMI of the animal is calculated by substituting the calculated value into relational expression 133A (s730).

[0102] The calculation performed in s720 above may, for example, in the embodiment where the detection means 110 is a gas sensor, as described above, be a calculation based on the shape of the signal intensity curve and the maximum value of the curve of the signal output from the surface stress sensor (see Figure 4(b)).

[0103] Although not shown in the figures, the feed intake estimation program of the present invention may further include processes and conditional branches corresponding to the process of obtaining the above-mentioned relational equations, and / or processes and conditional branches corresponding to the process of modifying the above-mentioned relational equations, which may be included in the feed estimation method described above. A flowchart showing the flow of these processes can be appropriately created by a person skilled in the art based on the above content.

[0104] Furthermore, the feed intake estimation program of the present invention can also be configured as a feed adjustment program by including processes and conditional branching corresponding to the feed adjustment method described later. In this case as well, a flowchart showing the flow of the feed adjustment process can be appropriately created by a person skilled in the art based on the following content.

[0105] [Feed Intake Estimation System] The above-described feed intake estimation device 100 can be combined with a feed supply means to constitute a feed intake estimation system.

[0106] In other words, as schematically shown in Figure 8, the feed intake estimation system 200 according to one embodiment of the present invention includes a feed supply unit 210 that supplies a predetermined feed to a target animal Sbj, a detection unit that detects ketones in body fluids collected from the animal Sbj, and an analysis unit that uses the signal output from the detection unit to determine the DMI from the feed by the animal Sbj based on a relationship between the value obtained from the signal and DMI, wherein the detection unit and the analysis unit are configured using the feed intake estimation device 100 described above.

[0107] The feed supply unit 210 is not particularly limited in its configuration, as long as it can supply the above-mentioned feed to the animal Sbj. In one exemplary embodiment, the feed supply unit 210 may be a device called an automatic feeder.

[0108] The collection of bodily fluids from the animal Sbj may be performed by any method, and the collected bodily fluids may be supplied to the detection unit (detection means 110) by a measurement system as described with reference to Figure 2. Here, the feed intake estimation system 200 may optionally further include a bodily fluid collection unit 220 for collecting bodily fluids from the animal Sbj. Furthermore, it is preferable that the bodily fluid collection unit 220 is configured to collect bodily fluids from the animal Sbj after a certain period of time has elapsed since the animal Sbj was given a predetermined feed. In this context, the bodily fluid collection unit 220 may be, for example, a device called a milking robot, etc., in the embodiment where the animal Sbj is the dairy-producing animal described above. Even in the embodiment where the feed intake estimation system 200 includes a bodily fluid collection unit 220, the collected bodily fluids may be supplied to the detection unit (detection means 110) by a measurement system as described with reference to Figure 2.

[0109] [Feed Feeding Adjustment Methods] To improve the management of dairy cows and other animals and increase or maintain farm productivity, it is necessary to properly design the feed to be given, to provide the prescribed amount, and to ensure that the animals properly consume the feed. In this invention, by using the feed intake estimation method described above, the feed intake of the target animals can be easily monitored, and signs of insufficient intake can be detected early and accurately, allowing the feed design to be reviewed based on the results obtained.

[0110] In the feed adjustment method according to one embodiment of the present invention (hereinafter also referred to as "the adjustment method of this embodiment"), the amount of feed and / or menu for the target animal may be adjusted using the value of DMI estimated by the feed intake estimation method described above, or the value of the decrease (difference) in DMI from the appropriate level. Alternatively, the metabolic energy value may be calculated from the DM of the fed feed using a predetermined conversion formula, and the amount of feed and / or menu for the animal may be adjusted using the value converted to metabolic energy. In the latter embodiment, for example, the metabolic energy value calculated using a predetermined conversion formula based on the DM of the feed F and the DMI F The difference between the estimated energy intake based on this and the target animal's energy deficit is considered to be the DMI. F This includes adjusting the feed menu to ensure that the amount of feed does not exceed a certain limit.

[0111] For example, in the case of dairy cows, the required amount of energy (nutrient intake) differs between individual management (tethered housing) and herd management (free-range farming). Furthermore, it is sometimes preferable to design feed considering factors such as outside temperature and the environment of the barn. Therefore, feed design using values ​​converted to metabolizable energy is likely to be more effective and practical than using DMI standard values, and is expected to contribute more to maintaining and improving farm productivity.

[0112] Animals whose DMI has fallen below the appropriate level also tend to have a lower energy intake than the appropriate level. In the adjustment method of this embodiment, the amount of feed that the target animal can consume can be estimated from the previously obtained decrease in DMI. Therefore, instead of the normal feeding amount, it is possible to design a feed that compensates for the estimated energy deficit by adjusting the ratio of feed crops and compound feed within the range of the estimated amount of feed that can be consumed, based on the estimated amount of feed that can be consumed. Here, since major countries and regions have established feeding standards that serve as guidelines and standards for livestock management, it is also preferable to consider incorporating the content shown therein and setting an upper limit (threshold) for the amount of energy to be increased per day.

[0113] Generally, a deficiency in DMI causes hunger stress for the animals, and if this condition persists for a long time, it is a concern that it may lead to a decrease in milk production. However, excessively increasing the amount of energy given can cause other stress on the animals' bodies, and in the case of dairy cows, it is desirable to design feed that stabilizes the environment of the rumen (first stomach) and contributes to the normal production of rumen fermentation products.

[0114] When feeding animals with feed adjusted to increase their energy content as described above, it is preferable to record the amount of energy increase. For animals fed the adjusted feed, the amount of feed intake will be estimated again in the next measurement. If an energy deficiency is still suspected, a new feed design should be created to compensate for the estimated energy deficit, and this feed should be given to the animals. In this case, it is also preferable to record the amount of energy increase.

[0115] It is preferable to repeat this series of steps—measurement, estimation, feed design, and recording of energy supplementation—and to record the corresponding feed menu once an improvement in energy intake is observed. Since this feed menu is considered to be a suitable feed design for obtaining the necessary nutrients for the target animal, the animal should continue to be fed according to this feed menu. This is expected to improve the nutritional status of the target animal, and the concentration of ketones in the body fluids collected from the animal will approach (return to) normal levels.

[0116] Here, feedback can be added to the previously used relational expression, allowing it to be modified as needed. Figure 9 is a schematic diagram illustrating an example of a process for modifying the DMI relational expression in the adjustment method of this embodiment.

[0117] In one specific embodiment, a characteristic quantity (V) of the signal output from a detection means (gas sensor) increases at a certain time (t1), and a decrease in the target animal's DMI can be estimated based on the DMI relation. Here, we assume that when the feed adjusted by increasing the energy content (E) as described above is given, a decrease in the above characteristic quantity (V) is confirmed at another time (t2), and thereafter the characteristic quantity (V) returns to normal. At this time, the DMI relation can be modified by considering the change in the above characteristic quantity (V) (ΔV) between time t1 and time t2, and the increase in energy content (E) in the given feed (ΔE). This makes it possible to make the relation applied to subsequent measurement results appropriate to the target animal's growth state (health state) at that time, improve the accuracy of feed intake estimation, and ultimately improve the efficiency of feed design, allowing for more appropriate management of the target animal's rearing.

[0118] Furthermore, if the above-mentioned relational expression is modified in the adjustment method of this embodiment, it is preferable to check the energy intake of the target animal at regular intervals and adjust the amount of feed and / or menu as necessary. This is intended to improve the situation in which, if the relational expression is modified at some point after a review of the feed design described above, and the modified relational expression is continued to be applied, the energy level may become excessive for the target animal. In another aspect, it is intended to confirm whether the relational expression applied to the measurement results is appropriate for the growth stage of the target animal.

[0119] In one specific embodiment, animals whose DMI, estimated using the above-described feed intake estimation method, is determined to be appropriate are given a feed adjusted by reducing the energy content by a certain amount (e.g., a few percent) compared to the feed given immediately beforehand. Then, the DMI from this feed is calculated according to the above-described feed intake estimation method. If the estimated DMI is determined to not meet the appropriate level, the animals are given a feed adjusted by increasing the energy content to a level that does not exceed the energy content before the reduction, and the DMI from this feed is calculated in the same manner as above. If the estimated DMI does not meet the appropriate level, the cycle of feed adjustment, feeding, and measurement is repeated. If the estimated DMI meets the appropriate level, the energy intake of the animals in question is determined to be at an appropriate level.

[0120] On the other hand, if the DMI obtained by feeding the adjusted feed meets the appropriate level, the amount of energy reduction during the feed adjustment is compared with the amount of energy (increase) when the feed was increased previously. If the condition "energy reduction ≤ energy increase" is met, the animal is then fed a feed adjusted by further reducing the energy content to a certain extent, and the DMI from that feed is calculated in the same manner as above. The subsequent procedures are then the same as above to bring the energy intake of the animal to an appropriate level. In contrast, if the condition "energy reduction > energy increase" is met, it may be determined that the animal is being fed a normal amount of feed. However, even in this state, the energy level may still be excessive for the animal, so it may be necessary to consider whether the caretaker needs to take action, or to monitor the animal's progress.

[0121] [Feed Feeding Adjustment System] The feed adjustment method described above can be implemented by a feed adjustment system that uses the feed intake estimation system described with reference to Figure 8 as its basic configuration. In one preferred embodiment, the feed supply unit 210 is configured to adjust the amount and / or menu of feed for the target animal based on the feed adjustment method described above. This configuration can be realized, for example, by using conventional feed supply equipment or devices such as an automatic feeder.

[0122] The present invention will be described in more detail below with reference to examples. Please note that the following examples are not intended to limit the present invention, but rather to aid in its understanding. [Examples]

[0123] In this example, a feed intake estimation device, whose schematic configuration is shown in Figure 5, was fabricated using a measurement system whose schematic configuration is shown in Figure 2. The MSS used was an assembly consisting of multiple MSS coated with different sensitive membrane materials. The list of sensitive membrane materials included materials that had been confirmed to be suitable for detecting acetone in gases generated from milk, and these materials included Poly(2,6-diphenyl-p-phenylene oxide) (Tenax TA 60 / 80, obtained from GL Sciences Co., Ltd.) and AK02-04 (obtained from Asahi Kasei Corporation, see Non-Patent Literature 1). Furthermore, a commercially available automatic feeder was combined with the feed intake estimation device as a means of feed delivery to construct a feed intake estimation system (see Figure 8). This feed intake estimation system also functioned as a feed delivery adjustment system.

[0124] <Example Test 1: Process for Determining the Relationship> A study was conducted on four dairy cows raised in a free-range barn at a farm managed by the National Agriculture and Food Research Organization (NARO) in Nasushiobara City, Tochigi Prefecture. The amount of feed given to the cows was gradually reduced from the normal amount (100%) to approximately 25% over six days, and then increased back to 100% over nine days. Since the moisture content of each feed was approximately the same, as the amount of feed decreased, DM decreased, and DMI also decreased. Similarly, as the amount of feed increased, DM increased, and DMI also increased. This is illustrated in Figure 10A.

[0125] Day 0 was defined as the day when the cows were fed the normal amount (100%) of feed. From day 1 to day 17, blood samples were collected from the target dairy cows, and the concentrations of blood NEFA (non-esterified fatty acids) and blood total ketones were measured. The results are shown in Figures 10B and 10C.

[0126] Furthermore, the acetone concentration in milk collected from the target dairy cows from day 2 to day 17 was measured by proton transfer reaction time-of-flight mass spectrometry (PTR-TOF-MS). The results are shown in Figure 10D. In addition, the gas generated from each milk sample was supplied to the detection means (MSS) of the feed intake estimation device described above, and the signal output from the MSS was recorded. Here, the milk sample was contained in a Teflon® chamber with a capacity of approximately 30 mL, and the gas generated from the milk sample (headspace gas) was supplied to the MSS (sensor module) using nitrogen gas as the carrier gas. During the measurement, the chamber containing the milk sample was placed in an incubator set to 37°C. The flow rate of the sample gas and purge gas (nitrogen gas) was set to 10 sccm, and the sampling time (the time for sample gas injection in each measurement cycle) was set to 120 seconds. In this test example, the MSS output value immediately before the start of the sample gas injection period was used as the baseline (reference point for offset processing: zero signal), and the MSS output value 30 seconds after the start of nitrogen purging (i.e., 150 seconds after the start of sample gas injection) was used as a feature of the decision point in the analysis. Since this baseline depends on the length of the nitrogen purging time after the previous sample gas measurement, the nitrogen purging time dependence of the baseline was measured using water vapor after the first measurement using the milk sample (on the second day), and the baseline of the measurement results for the following day was corrected. Similarly, thereafter, the baseline of the measurement results for the day was corrected based on the nitrogen purging time dependence of the baseline measured the previous day. The results are shown in Figure 10E.

[0127] The results shown in Figures 10A to 10E confirm that, with a decrease or increase in DMI in dairy cows, blood NEFA concentration and total ketone body concentration, as well as acetone concentration in milk, increase or decrease. Furthermore, it was confirmed that, with an increase or decrease in acetone concentration in milk, the characteristic values ​​of the above-mentioned judgment points (hereinafter simply referred to as "MSS output values") increase or decrease.

[0128] Next, using the obtained results, we examined the relationship between DMI on the feeding day and blood NEFA concentration on the following day, such as DMI on day 0 and blood NEFA concentration on day 1. As shown in Figure 11A, a negative correlation was confirmed. Furthermore, we examined the relationship between blood NEFA concentration on the same day and MSS output value, such as blood NEFA concentration on day 2 and MSS output value on day 2. As shown in Figure 11B, a positive correlation was confirmed. Finally, when we examined the relationship between DMI on the feeding day and MSS output value on the following day, a negative correlation was confirmed, as shown in Figure 11C.

[0129] Based on these results, the relationship between MSS output value and DMI can be expressed as follows, using the MSS output value as the reference for the DMI (theoretical DMI) ingested from a given feed: -238 × (Change in MSS output value from baseline) It was found that by applying this method, it is possible to estimate the change in DMI (i.e., the difference between the theoretical DMI and the actual DMI) for the dairy cow in question. Naturally, being able to estimate the change in DMI also means that it is possible to estimate the actual DMI.

[0130] <Example Test 2: Feed Adjustment and Feeding Based on Estimation of Feed Intake> Using the relationship between the MSS output value and DMI obtained in Experiment 1, it is possible to estimate feed intake and conduct experiments on feed adjustment and feeding using the estimated feed intake for dairy cows raised in the free-range barn described above.

[0131] In this test example, first, the animals are fed the prescribed feed in accordance with normal feeding guidelines, a milk sample is obtained from the milk during milking, the gas generated from the milk sample is supplied to the detection means (MSS) of the feed intake estimation device described above, the signal output from the MSS is recorded, and the MSS output value, which is a characteristic quantity of the judgment point, is confirmed.

[0132] As a result, for example, if an increase in the MSS output value is observed in a certain dairy cow on day 5, with the start date of the experiment being day 0, it can be estimated that the cow's DMI decreased on the previous day, i.e., day 4. Subsequently, if the MSS output value continues to increase until day 8, and then rises to an even higher value on day 9, it can be estimated that the cow's DMI on day 8 was approximately 1 kg lower than the theoretical DMI. Here, assuming that the theoretical DMI is approximately 20 kg / day, a decrease of approximately 1 kg in DMI means that the cow's DMI is approximately 5% lower than normal, which could mean that it is in a state of insufficient energy intake.

[0133] In such cases, for example, assuming the metabolic energy value of the feed given in this test example is 15 MJ / kgDM, the amount of energy that the dairy cow is not getting enough of due to the decrease in DMI can be calculated, and the feed composition and quantity can be adjusted so that the amount of energy deficit can be compensated for with the amount of feed the dairy cow can consume, and this can be fed to the dairy cow from the 10th day onward.

[0134] As a result, the DMI remains low because the total amount of the adjusted feed is reduced, but a decrease in the MSS output value may be observed, for example, on day 12. This means that the energy balance of the dairy cow improved as a result of being fed the adjusted feed, and the acetone concentration in the milk produced decreased significantly, leading to a significant decrease in the MSS output value, i.e., the feature related to the signal intensity of acetone detected by the MSS.

[0135] In this way, the feed intake of an animal can be estimated based on the composition of bodily fluids collected from an animal raised in a certain environment (in this example, the acetone concentration in milk collected from a dairy cow), and a suitable feed can be designed and / or adjusted using the estimated feed intake. Furthermore, according to the above Test Example 2, it is considered that the dairy cow in question was able to properly consume the feed given on the 12th day and the previous day, the 11th day. Therefore, using the DMI (estimated value) and MSS output value on the 12th day, the DMI and MSS output values ​​based on the relational formula obtained in Test Example 1, and optionally the DMI (estimated value) and MSS output values ​​on the 10th and 11th days when the feed was adjusted, a predetermined DM (DM) can be calculated for the dairy cow. x DMI (DMI) from feed containing ) x It may also be possible to derive an equation that expresses the relationship between ( ) and replace the above relationship with the obtained equation. Furthermore, when modifying the above relationship, it may be effective to consider the amount of energy added to the feed from the original feed for each feed from the 10th to the 12th day. [Industrial applicability]

[0136] The present invention is typically suitable for application to dairy cows when milk is used as the bodily fluid. It is also suitable for application to other animals raised for milk production as an industry, such as goats, sheep, water buffalo, yaks and other Bovidae animals, and horses. More specifically, the present invention is particularly suitable for checking whether animals raised for milk production, such as dairy cows, are adequately ingesting the feed they are given, and for improving feeding management by reviewing the feed design if insufficient intake is suspected. The bodily fluid to be collected is not limited to milk; other bodily fluids can also be used, although the ease of collection and the certainty of obtaining them at the required time will differ depending on the type of bodily fluid, the type of animal, and the collection method.

[0137] In recent years, efforts have been made to detect early signs of disease or changes in health in dairy cows and other livestock management systems by utilizing motion sensors and the like. By combining the present invention with such livestock management systems, it is possible to manage the health of animals more simply and efficiently, and it is expected that this will contribute to improving or maintaining productivity. [Explanation of Symbols]

[0138] 100 Feed Intake Estimation Device 110 Detection means (gas sensor) 120 Supply Means 121 Gas flow path 122 MFC 123 vials 130 Analysis Means 131 Input section 132 Arithmetic section 133 Storage section 134 Output section 200 Feed Intake Estimation System (Feed Feeding Adjustment System) 210 Feed Supply Department 220 Body Fluid Sampling Department Sbj Target Animals

Claims

1. The procedure involves feeding a specified feed F to the target animal (excluding humans), and after a certain period of time has elapsed, collecting bodily fluids from the animal. The detection of ketones in the body fluid using a detection means, Using the signal output from the detection means, and based on the relationship formula between the value obtained from the signal and the dry matter intake (DMI), the DMI from the feed F of the animal is calculated (DMI Ｆ ) and A method for estimating feed intake, including the above.

2. The process further includes determining the relation before feeding the aforementioned feed F, wherein the process involves preparing first to third test feeds with different dry matter amounts (DM) in a predetermined environment in which the animals are kept. The first test feed is given to the animal, and after a certain period of time has elapsed since ingestion, body fluids are collected from the animal, and ketones in the body fluids are detected using a detection device. The second test feed is given to the animals, and after a certain period of time has elapsed since ingestion, bodily fluids are collected from the animals, and ketones in the bodily fluids are detected using a detection device. A third test feed is given to the animals, and after a certain period of time has elapsed since ingestion, body fluids are collected from the animals, and ketones in the body fluids are detected using a detection device. If necessary, the same steps as those used with the first to third test feeds shall be carried out using the fourth to nth (n is a natural number of 5 or greater) test feeds having a predetermined DM, The DM of the first to third test feeds and the optional fourth to nth test feeds are considered as the dry matter intake (DMI) by the animals from the first to third test feeds and the optional fourth to nth test feeds, and an equation is derived that represents the relationship between the DMI and the value V obtained from the signal output from the detection means using the first to third test feeds and the optional fourth to nth test feeds. A method for estimating feed intake according to claim 1, including the method described in claim 1.

3. The aforementioned DMI Ｆ After obtaining the relation, the process further includes a process to make the relation modifiable, the process is The DM of the aforementioned feed F (DM Ｆ ) and the aforementioned DMI Ｆ To find the difference between and To determine whether the difference meets a predetermined appropriate level. Including, here, If the appropriate level is met, the relational expression is maintained and the process is terminated. If the appropriate level is not met, Feed F having a different direct meal (DM) than the aforementioned Feed F. １ The substance is given to the animal, and after a certain period of time has elapsed, body fluid is collected from the animal, and ketones in the body fluid are detected using a detection means. A value V obtained from the signal output from the detection means Ｆ１ is used to calculate DMI based on the aforementioned relational expression Ｆ１ , and the feed F １ DM (DM Ｆ１ ) and the DMI Ｆ１ are used to determine the ratio If the ratio satisfies predetermined conditions set based on the appropriate level, The aforementioned animals feed F １ It is considered that the DMI was taken appropriately. Ｆ１ And the aforementioned value V Ｆ１ And, the DMI and value V that formed the basis of the above relational expression, and optionally, the DM Ｆ and the aforementioned V Ｆ Using the above, a predetermined DM (DM) is performed by the animal. ｘ DMI from feed containing ) ｘ Find an equation that expresses the relationship with ), Replace the obtained equation with the aforementioned relational equation and terminate the process. If the ratio does not meet the predetermined conditions set based on the appropriate level, then the feed F １ Feed F has a different DM. ｍ Using (where m is a natural number greater than or equal to 2), the feed F １ Perform the same steps as when using and increase m from 2 to 1 increments until the predetermined conditions are met, then feed F ｍ Repeat the steps using When the aforementioned predetermined conditions are met, the animal feeds F ｍ It is considered that the DMI was taken appropriately. Ｆｍ And the aforementioned value V Ｆｍ And, the DMI and value V that formed the basis of the above relational expression, and optionally, the DM Ｆ and the aforementioned V Ｆ And, DM Ｆ（ｍ－１） DM Ｆ１ And, V Ｆ（ｍ－１） From V Ｆ１ Using the above, a predetermined DM (DM) is performed by the animal. ｘ DMI from feed containing ) ｘ Find an equation that expresses the relationship with ), Replace the obtained equation with the aforementioned relational equation and terminate the process. The method for estimating feed intake according to claim 2.

4. The appropriate level is determined based on the normal DMI of the animal, Ｆ and the aforementioned DMI Ｆ The difference (DM Ｆ - DMI Ｆ This is expressed as a certain conditional expression that indicates the range that the value of ) must satisfy. The predetermined conditions set based on the aforementioned appropriate level are determined based on the conditional formula for the appropriate level and the DMI of the animal under normal conditions, and the DMI Ｆ１ and the aforementioned DMI Ｆ１ Ratio to (DM Ｆ１ : DMI Ｆ１ ) value or the DM Ｆｍ and the aforementioned DMI Ｆｍ Ratio to (DM Ｆｍ : DMI Ｆｍ This is expressed as a certain conditional expression that indicates the range that the value of ) must satisfy. The method for estimating feed intake according to claim 3.

5. The above relationship is given by a predetermined feed F ｘ This is an equation that represents the difference between the theoretical DMI and the actual DMI, and when this difference is expressed as kV (where k is a predetermined coefficient) using a value V obtained from the signal output from the detection means, The aforementioned DMI Ｆ After obtaining the relation, the process further includes a process to make the relation modifiable, the process is The DM of the aforementioned feed F (DM Ｆ ) and the aforementioned DMI Ｆ To find the difference between and To determine whether the difference meets a predetermined appropriate level. Including, here, If the criteria are met, maintain the above relation and terminate the process. If the criteria are not met, Feed F having a different direct meal (DM) than the aforementioned Feed F. １ The substance is given to the animal, and after a certain period of time has elapsed, body fluid is collected from the animal, and ketones in the body fluid are detected using a detection means. The value V obtained from the signal output from the detection means Ｆ１ The value V obtained when the aforementioned feed F is given to the animal. Ｆ Compared with, Condition "V Ｆ１ ≤ V Ｆ If the condition is met, Feed F １ DM (DM Ｆ１ ) feed F by the aforementioned animals １ DMI from (DMI Ｆ１ ) and the DMI Ｆ１ And the aforementioned value V Ｆ１ And, the DMI and value V that formed the basis of the above relational expression, and optionally, the DM Ｆ and the aforementioned V Ｆ Using the above, a predetermined DM (DM) is performed by the animal. ｘ DMI from feed containing ) ｘ Find an equation that expresses the relationship with ), Replace the obtained equation with the aforementioned relational equation and terminate the process. Condition "V Ｆ１ > V Ｆ If the above condition is met, then the feed F １ Feed F has a different DM. ｍ Using (where m is a natural number greater than or equal to 2), the feed F １ Perform the same steps as when using the condition "V Ｆｍ ≤ V Ｆ（ｍ－１） Feed F, in which m is increased by 1 from 2 until the condition is met. ｍ Repeat the steps using Condition "V Ｆｍ ≤ V Ｆ（ｍ－１） Feed F when the condition is met ｍ (m is a natural number greater than or equal to 2.) DM (DM Ｆｍ ) feed F by the aforementioned animals ｍ DMI from (DMI Ｆｍ ) and the DMI Ｆｍ And the aforementioned value V Ｆｍ And, the DMI and value V that formed the basis of the above relational expression, and optionally, the DM Ｆ and the aforementioned V Ｆ And, DM Ｆ（ｍ－１） DM Ｆ１ And, V Ｆ（ｍ－１） From V Ｆ１ Using the above, a predetermined DM (DM) is performed by the animal. ｘ DMI from feed containing ) ｘ Find an equation that expresses the relationship with ), Replace the obtained equation with the aforementioned relational equation and terminate the process. The method for estimating feed intake according to claim 2.

6. The appropriate level is based on the normal DMI of the animal, the DM Ｆ and the DMI Ｆ difference (DM Ｆ -DMI Ｆ ) is expressed by a certain conditional expression indicating the range that the value should satisfy, the feed intake estimation method according to claim 5.

7. The aforementioned animal is a milk-producing animal, The aforementioned collection involves collecting milk from the milk-producing animal, The aforementioned detection involves detecting ketones in the milk using a detection means. A method for estimating feed intake according to any one of claims 1 to 6.

8. The aforementioned detection involves detecting acetone in the gas generated from the milk using a gas sensor. The aforementioned DMI Ｆ In determining this, the time-varying pattern of the signal output from the gas sensor is used to determine the values ​​of the variables included in the relational expression. The method for estimating feed intake according to claim 7.

9. The method for estimating feed intake according to claim 8, wherein the gas sensor is a surface stress sensor.

10. At least one detection means for detecting ketones in a sample, A supply means for supplying bodily fluids collected from the target animal to the detection means, An analysis means for analyzing the signal output from the detection means, Equipped with, The aforementioned analysis means is An input unit to which the signal output from the detection means is input, A calculation unit that calculates a predetermined value using the signal input to the input unit, A storage unit in which the program executed by the arithmetic unit is stored, The system includes an output unit that outputs the signal and the calculation result including the value obtained by the calculation, The aforementioned arithmetic unit comprises at least, The DMI of the animal is calculated by referring to a relational expression relating to the dry matter intake (DMI) of the animal stored in the memory unit, calculating the values ​​of the variables included in the relational expression based on the signal, and substituting the calculated values ​​into the relational expression. Execute Feed intake estimation device.

11. The feed intake estimation device according to claim 10, wherein the supply means is configured to supply milk collected from a target dairy-producing animal to the detection means.

12. The supply means is configured to supply the gas generated from the milk to a gas sensor capable of detecting acetone in the target gas. The feed intake estimation device according to claim 11, wherein the calculation unit calculates the value of a variable included in the relational expression using the time change pattern of the signal output from the gas sensor.

13. The feed intake estimation device according to claim 12, wherein the gas sensor is a surface stress sensor.

14. On the computer, A function that calculates the values ​​of variables included in a relational expression concerning the dry matter intake (DMI) of an animal, based on a signal output from a detection means supplied with bodily fluids collected from the target animal, The function of calculating the DMI of the animal by substituting the calculated value into the relational formula, To make it happen Feed intake estimation program.

15. A feed supply unit that provides the target animals with the prescribed feed, A detection unit for detecting ketones in bodily fluids collected from the aforementioned animal, An analysis unit uses the signal output from the detection unit to determine the DMI of the animal from the feed, based on a relationship formula between the value obtained from the signal and the dry matter intake (DMI). Includes, The detection unit and analysis unit are configured using the feed intake estimation device described in any one of claims 10 to 13. Feed intake estimation system.

16. The feed intake estimation system according to claim 15, further comprising a body fluid collection unit for collecting body fluid from the animal, wherein the body fluid collection unit is configured to collect body fluid from the animal after a certain period of time has elapsed since the animal was given the feed.

17. DMI estimated by the feed intake estimation method according to any one of claims 1 to 9 Ｆ A method for adjusting animal feed, comprising adjusting the amount and / or menu of feed for the animal based on the above.

18. The above adjustment is based on the metabolic energy value calculated using the DM of the feed F and the DMI. Ｆ The difference between the estimated energy intake based on the above is considered to be the energy deficit of the animal, and the DMI Ｆ A method for adjusting feed supply according to claim 17, which includes adjusting the feed menu so as not to exceed a certain amount of feed.

19. A feed supply unit that provides the target animals with the prescribed feed, A detection unit for detecting ketones in bodily fluids collected from the aforementioned animal, An analysis unit uses the signal output from the detection unit to determine the DMI of the animal from the feed, based on a relationship formula between the value obtained from the signal and the dry matter intake (DMI). Includes, The detection unit and analysis unit are configured using the feed intake estimation device described in any one of claims 10 to 13. A feed supply adjustment system wherein the feed supply unit is configured to adjust the amount and / or menu of feed for the animal based on the feed supply adjustment method described in claim 17 or 18.

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