Method and device for evaluating silage fermentation quality

Abstract

The present invention aims to enable simple evaluation of silage fermentation quality on-site. In one embodiment of the present invention, gas generated from silage is supplied to a surface stress sensor to determine the amount of either organic acids or nitrogen-containing compounds contained therein. The surface stress sensor can detect trace components in the gas using a simple device configuration and procedures. Therefore, leveraging the known relationship between the content of these components and fermentation quality, fermentation quality can be easily evaluated through this measurement.

Description

Technical Field

[0001] The present invention relates to silage mainly used as cattle feed, and more particularly to a silage manufacturing process or an evaluation of the fermentation quality of the silage during storage. Background Art

[0002] As feed for ruminants and other herbivores such as cattle, silage made by fermenting plants such as grasses, legumes, and waste from food processing processes is used in large quantities. The fermentation during the manufacture of silage is mainly lactic acid fermentation, but due to the fermentation conditions or subsequent storage conditions, fermentation other than lactic acid fermentation may also occur, and it may also spoil depending on the circumstances. Due to the deterioration of fermentation quality, that is, fermentation other than lactic acid fermentation or corruption, etc., which leads to an increase in carboxylic acids with a large number of carbon atoms such as butyric acid and valeric acid or volatile basic nitrogen such as ammonia in the silage, it will become silage that ruminants do not like. In addition, if ruminants ingest such low-quality silage, it may be harmful to their health. Therefore, in the process of manufacturing, storing, circulating, and using silage, it is important to inspect and manage the fermentation quality of silage in the animal husbandry industry.

[0003] Currently, there are two methods for evaluating the fermentation quality of silage: a method using chemical analysis and a method using human senses.

[0004] Among the indices of evaluation using chemical analysis, the V-Score (non-patent literature 1) that is widely used at present. The V-Score is to evaluate the fermentation quality with 100 points of full marks, and the smaller the value of ammonia nitrogen content (VBN) / total nitrogen amount (TN), the better to distribute 50 points, and the remaining 50 points are distributed to organic acids (VFA). About the distribution score of organic acid, when the number of carbon atoms is the same as butyric acid or the organic acid above butyric acid (i.e., above C4), the fewer the scores are higher (40 points of full marks), the fewer the acetic acid+propionic acid content is, the higher the scores are (10 points of full marks). In addition, as the total of these evaluation points, the V-Score is calculated.

[0005] However, determining the V score involves immersing silage in water for several hours and analyzing the water to extract its components. This not only takes a long time to obtain results, but also requires specialized analytical equipment. This makes it difficult to determine the V score on-site using simple procedures and equipment.

[0006] Another evaluation index other than the V score is the Freund's score, which is calculated based on the weight ratio of the estimated values ​​of lactic acid, acetic acid, and butyric acid obtained by steam distilling silage under certain conditions and titrating the resulting organic acids. This score has been shown to be highly consistent with the values ​​obtained using the Freund's distillation method, even when calculated based on quantitative values ​​of lactic acid and VFAs obtained using other analytical methods. The Freund's score is commonly used outside of Japan, and a similar index called the V2 score, which similarly does not take basic nitrogen into account, is also used in Japan. However, even with the Freund's score and other methods, the problems described above regarding the V score persist, making simple evaluation difficult on-site.

[0007] In addition, Patent Document 1 describes a method for evaluating the fermentation quality of silage coated with a synthetic resin film by observing the change over time in the ammonia concentration in the gas leaking out of the film and evaluating the quality based on the increase or decrease.

[0008] However, in this evaluation method, since the quality evaluation is performed based on the change over time, it takes a long time until the evaluation result is obtained. In this embodiment, after the grass just harvested is immediately covered with a film, the ammonia concentration is measured about every day, and the change in the ammonia leakage concentration for 33 days starting from the first day is observed. Such a measurement method cannot be used for the purpose of immediately evaluating the fermentation quality of silage. In addition, it is natural that the evaluation method of Patent Document 1 is a method of measuring how much the ammonia concentration has changed since the raw material stage of the silage, so it is necessary to have information on the change from the raw material state or at least from the concentration at the beginning of storage. Therefore, it cannot be applied to silage in the initial state where the ammonia concentration has not been measured, or to silage purchased from outside for which the initial ammonia concentration information is not provided.

[0009] On the other hand, fermentation quality evaluation using human senses involves a comprehensive assessment based on, for example, the color, texture, odor, and taste of silage. The human sense of smell is highly sensitive, particularly to organic acids, and therefore, if the evaluator is well-trained, it should, in principle, play a central role in evaluating fermentation quality. In practice, silage of very high fermentation quality has a very subtle odor, making the sense of smell well suited for evaluation in this area. On the other hand, when fermentation quality deteriorates slightly, the increase in organic acids, and in some cases, even a rancid odor, can be too irritating for the human sense of smell, preventing subtle differences in composition from being detected as differences in odor.

[0010] As described above, the sense of smell, which plays an important role in evaluation methods using sensory perception, is not suitable for silage emitting a strong odor, and this has become a major obstacle to evaluating fermentation quality using human sensory perception. Summary of the Invention

[0011] Problems to be solved by the invention

[0012] The present invention aims to detect volatile components (odor) from silage using a surface stress sensor, thereby evaluating the fermentation quality of silage at that moment without complicated operations, and to provide an apparatus for such evaluation.

[0013] Means for solving problems

[0014] According to one aspect of the present invention, a method for evaluating the fermentation quality of silage is provided, wherein gas generated from silage is provided to a surface stress sensor, and a signal output from the surface stress sensor in response to the gas generated from the silage is used to evaluate the fermentation quality of the silage based on the composition of the gas generated from the silage.

[0015] Here, the evaluation of the fermentation quality of the silage based on the composition of the gas generated from the silage may be based on the amount of at least one of organic acids and nitrogen-containing compounds in the gas.

[0016] In addition, the fermentation quality can be evaluated based on the temporal change pattern of the signal.

[0017] In addition, the evaluation of the fermentation quality may be performed based on the evaluation of the effect of the temporal change pattern of the amount of butyric acid in the gas generated from the silage.

[0018] In addition, the evaluation of the fermentation quality may be performed based on the evaluation of the effect of the temporal change pattern of the amount of acetic acid in the gas generated from the silage.

[0019] Alternatively, gas obtained by passing a gas substantially free of components that affect the evaluation of fermentation quality into a container storing silage to be evaluated may be supplied to the surface stress sensor as the gas generated from the silage.

[0020] Furthermore, the fermentation quality of the silage may be evaluated using the signal after the supply of the gas generated from the silage to the surface stress sensor is started.

[0021] In addition, the surface stress sensor may be a film-type surface stress sensor.

[0022] In addition, as a material of the sensing film of the surface stress sensor, at least one selected from the group consisting of poly(methyl vinyl ether-alt-maleic anhydride), poly(2,6-diphenyl-p-phenylene ether), and poly(4-methylstyrene) may be used.

[0023] In addition, as the material of the sensing film of the surface stress sensor, at least one selected from the group consisting of polymethyl methacrylate, poly(4-methylstyrene), phenyl-modified silica / titanium dioxide composite nanoparticles, octadecyl-modified silica / titanium dioxide composite nanoparticles, poly(2,6-diphenyl-p-phenylene ether), polyvinyl fluoride, polystyrene, polycaprolactone, cellulose acetate butyrate, polyethyleneimine and tetraethoxysilane-modified silica / titanium dioxide composite nanoparticles can be used.

[0024] Furthermore, as the surface stress sensor, at least a first surface stress sensor using one material selected from the group as a sensing film and a second surface stress sensor using another material selected from the group as a sensing film can be used.

[0025] In addition, the surface stress sensor may be alternately supplied with gas generated from the silage and purge gas, and the fermentation quality of the silage may be evaluated using the signal corresponding to the gas generated from the silage and the signal corresponding to the purge gas.

[0026] In addition, in addition to the time interval for supplying the gas generated from the silage to the surface stress sensor and the time interval for supplying the purge gas to the surface stress sensor, a time interval for supplying a specified standard gas to the surface stress sensor can be set, and the signal corresponding to the standard gas can be further used in evaluating the fermentation quality of the silage.

[0027] In addition, the standard gas may be a gas generated from a liquid or a solid.

[0028] Furthermore, the gas generated from the silage may be supplied to an additional gas sensor, and the fermentation quality of the silage may be evaluated based on the signal from the surface stress sensor and the signal from the additional gas sensor.

[0029] According to another aspect of the present invention, a silage fermentation quality evaluation device is provided, which is provided with at least one surface stress sensor, a first gas flow path for supplying a sample gas generated from the silage as a measurement object, and a second gas flow path for supplying a purge gas that does not contain the gas components to be measured. By alternately switching the supply of the sample gas supplied from the first gas flow path and the purge gas supplied from the second gas flow path to the at least one surface stress sensor, a signal is generated from the at least one surface stress sensor, thereby performing any of the above-mentioned silage fermentation quality evaluation methods.

[0030] Here, an additional gas sensor and an additional gas flow path for supplying the sample gas to the additional gas sensor may be provided, and the fermentation quality of the silage may be evaluated based on the signal from the at least one surface stress sensor and the signal from the additional gas sensor.

[0031] According to another aspect of the present invention, a silage fermentation quality evaluation device is provided, which is provided with at least one surface stress sensor, a first gas flow path for supplying a sample gas generated from the silage as a measurement object, a second gas flow path for supplying a purge gas that does not contain the gas components to be measured, and a third gas flow path for supplying a standard gas with a specified component composition. By switching the sample gas supplied from the first gas flow path, the purge gas supplied from the second gas flow path, and the standard gas supplied from the third gas flow path to the at least one surface stress sensor in a specified order, a signal is generated from the at least one surface stress sensor, thereby performing any of the above-mentioned silage fermentation quality evaluation methods.

[0032] Here, an additional gas sensor and an additional gas flow path for supplying the sample gas to the additional gas sensor may be provided, and the fermentation quality of the silage may be evaluated based on the signal from the at least one surface stress sensor and the signal from the additional gas sensor.

[0033] Effects of the Invention

[0034] The present invention makes it possible to easily evaluate the composition of organic acids, one of the key indicators for evaluating silage fermentation quality, such as the ratio of butyric acid to acetic acid in gases volatilized from silage. This makes it possible to easily determine the ratio of C2 and C3 components to C4 and higher components, or the amount of C2 and C3 components, in the organic acids produced by silage fermentation. Furthermore, detection of volatile components containing nitrogen is possible, and if substances related to fermentation quality exist other than organic acids or nitrogen-containing volatile components, such substances can also be detected. The present invention enables a comprehensive evaluation of silage fermentation quality based on the output signals from multiple surface stress sensors coated with a sensitive membrane capable of highly sensitively detecting organic acids, volatile basic nitrogen, and the like. By selecting appropriate membrane materials, a single surface stress sensor can detect multiple target substances. Since the amplitude or waveform of the sensor's response to each target substance can be made different, combining the outputs of multiple surface stress sensors allows for the determination of a fermentation quality evaluation value that appropriately combines parameters corresponding to the multiple target substances. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1This is a diagram showing a schematic configuration of a measurement system that can be used in the present invention.

[0036] Figure 2 It is a figure which shows an example of the optical microscope photograph of MSS.

[0037] Figure 3 This is a conceptual diagram explaining the temporal change in signal intensity when a sample gas is supplied to a surface stress sensor such as an MSS.

[0038] Figure 4 In Example 1, 1% aqueous solution of each organic acid was placed in a vial and Figure 1 Graph showing the temporal change (in seconds) of the signal (in mV) from the MSS of ChA when measured using the measurement device shown.

[0039] Figure 5 It means that a mixed organic acid aqueous solution (simulated silage aqueous solution) having the same organic acid composition as the silage extract to be measured is prepared according to the Figure 4 FIG is a diagram showing the results of measuring the same steps as in the case of FIG.

[0040] Figure 6 It means that the silage to be measured is stored in vials and Figure 5 The results of measuring the sample gas generated by the same steps as those in the case of FIG.

[0041] Figure 7 It means that Figure 4 The same 1% aqueous solution of each organic acid was stored in a vial and Figure 1 The measuring device shown is in accordance with Figure 4 This graph shows the temporal change (in seconds) of the signal (in mV) from the MSS of ChB when the measurement procedure is performed in the same manner as in the case of FIG.

[0042] Figure 8 Is to indicate that it will have Figure 5 The same organic acid extract of the same silage as the test object (simulated silage aqueous solution) was prepared by mixing the organic acid solution with the same organic acid as the test object. Figure 7 FIG is a diagram showing the results of measuring the same steps as in the case of FIG.

[0043] Figure 9 Is to indicate that it will be used as Figure 6 The silage of the same test object was stored in a vial and the test results were compared with those of Figure 8 The results of measuring the sample gas generated by the same steps as those in the case of FIG.

[0044] Figure 10 It means that Figure 4 The same 1% aqueous solution of each organic acid was stored in a vial and Figure 1 The measuring device shown is in accordance with Figure 4 Graph showing the time change (in seconds) of the signal (in mV) from the MSS of the ChC when the measurement is performed using the same procedure as in the case of FIG.

[0045] Figure 11 Is to indicate that it will have Figure 5 The same organic acid extract of the same silage as the test object (simulated silage aqueous solution) was prepared by mixing the organic acid solution with the same organic acid as the test object. Figure 10 FIG is a diagram showing the results of measuring the same steps as in the case of FIG.

[0046] Figure 12 Is to indicate that it will be used as Figure 6 The silage of the same test object was stored in a vial and the test results were compared with those of Figure 11 The results of measuring the sample gas generated by the same steps as those in the case of FIG.

[0047] Figure 13 In Example 2, three kinds of silage samples as the test objects were placed in vials, Figure 1 The graph shows the time change (in seconds) of the signal (in mV) from the MSS of the ChD when the measurement device shown measures the sample gas generated in this manner.

[0048] Figure 14 It means according to Figure 13 The same steps are performed as for the case with Figure 13 This graph shows the temporal change (in seconds) of the signal (in mV) from the MSS of ChE when three silage samples of the same measurement object were measured.

[0049] Figure 15 It means according to Figure 13 The same steps are performed as for the case with Figure 13 This graph shows the time change (in seconds) of the signal (in mV) from the MSS of the ChF when three silage samples of the same measurement object were measured.

[0050] Figure 16 It means according to Figure 13 The same steps are performed as for the case with Figure 13 This graph shows the time change (in seconds) of the signal (in mV) from the MSS of ChG when three silage samples of the same measurement object were measured.

[0051] Figure 17 It means according to Figure 13 The same steps are performed as for the case with Figure 13 This graph shows the time change (in seconds) of the signal (in mV) from the MSS of ChH when three silage samples of the same measurement object were measured.

[0052] Figure 18 It means according to Figure 13 The same steps are performed as for the case with Figure 13 This graph shows the time change (in seconds) of the signal (in mV) from the MSS of ChI when three silage samples of the same measurement object were measured.

[0053] Figure 19 It means according to Figure 13 The same steps are performed as for the case with Figure 13 This graph shows the time change (in seconds) of the signal (in mV) from the MSS of ChJ when three silage samples of the same measurement object were measured.

[0054] Figure 20 It means according to Figure 13 The same steps are performed as for the case with Figure 13 This graph shows the time change (in seconds) of the MSS signal (in mV) from ChK when three silage samples of the same measurement object were measured.

[0055] Figure 21 It means according to Figure 13 The same steps are performed as for the case with Figure 13 This graph shows the time change (in seconds) of the signal (in mV) from the MSS of ChL when three silage samples of the same measurement object were measured.

[0056] Figure 22 It means according to Figure 13 The same steps are performed as for the case with Figure 13 This graph shows the time change (in seconds) of the MSS signal (in mV) from the ChM when three silage samples of the same measurement object were measured.

[0057] Figure 23 It means according to Figure 13 The same steps are performed as for the case with Figure 13 This graph shows the time change (in seconds) of the signal (in mV) from the MSS of the ChN when three silage samples of the same measurement object were measured. DETAILED DESCRIPTION

[0058] Since various components produced during the fermentation of silage will volatilize from the silage, the fermentation quality can be evaluated by detecting these various components. As part of the important items for evaluating the fermentation quality of silage, the amount of each organic acid contained in the silage and the ratio between them can be cited. Specifically, there are: 0 Benchmark 1: Silage with a large ratio of the amount of organic acids with 4 or more carbon atoms in the molecule (hereinafter referred to as C4) to the amount of organic acids with 2 or 3 carbon atoms (hereinafter referred to as C2, C3, respectively) has poor quality (the evaluation from this point of view is also called C4 evaluation); and 0 Benchmark 2: Silage with a large amount of organic acids with 2 or 3 carbon atoms also has poor quality (the evaluation from this point of view is also called C2+C3 evaluation).

[0059] The inventors of the present application have obtained an idea to evaluate the quality of silage by detecting the amounts of various organic acids in such silage using a surface stress sensor, and have completed the present invention as a result of conducting research.

[0060] According to one embodiment of the present invention, at least one surface stress sensor is provided that has a different response characteristic to at least one organic acid belonging to C2 and / or C3 than to at least one organic acid belonging to C4. Silage quality is evaluated based on the output of this surface stress sensor. More specifically, the output of the surface stress sensor is evaluated according to at least one of the aforementioned criteria 1 and 2, and the silage quality is evaluated based on the result.

[0061] Here, a separate surface stress sensor can be provided for each organic acid. Alternatively, in most cases, a surface stress sensor can be used to respond to different signal waveforms for multiple chemical substances, and a surface stress sensor with fewer than the number of organic acids to be detected can also be used. In the latter case, the response waveform of each organic acid is significantly different. In addition, even when multiple organic acids are mixed, the output of the surface stress sensor as a whole does not significantly deviate from the linear superposition of the responses of each organic acid. It is more possible to easily achieve the identification of each organic acid and the determination of its amount by using simple methods such as simple pattern matching of an information processing device. However, even if this is not the case, in addition, in complex situations where there are many types of organic acids with the possibility of being detected, such as a large number of parameters that affect the output signal, it is also possible to use a well-known method to perform machine learning on the relationship between the output component and the amount of each component or the ratio between the amounts of multiple components (or evaluation score or evaluation result category) to obtain a more accurate result. Although such machine learning is not specifically described in this application, it is well known as a method that can be applied to machine learning itself and a wide range of technical fields. In addition, it can be applied to surface stress sensor applications, such as described in detail in Patent Document 2.

[0062] Here, rather than evaluating the amounts of all organic acids or the ratios between them, which contribute to the silage evaluation results, it is possible to determine the amounts or ratios of a smaller number of representative organic acids. This is because the reactions that generate these organic acids or the composition of the raw materials have limited freedom, so the amount of a particular component cannot be completely independent of the amounts of other similar components. Taking advantage of this, for example, acetic acid can be used as a representative component for C2+C3, and butyric acid can be used as a representative component for C4. When these representative components are selected, since acetic acid and butyric acid are the most volatile within each organic acid group, they are easily detected as gases, facilitating measurement.

[0063] In addition, the above description mainly describes the evaluation of the fermentation quality of silage by measuring the amount or ratio of various organic acids volatilized from the silage, but the components to be measured are not limited to this. For example, as already explained above, when evaluating the fermentation quality of silage, the fermentation quality of silage can be evaluated by measuring not only the amount or ratio of organic acids, but also the amount or ratio of volatile nitrogen-containing compounds. In addition, by determining the amount of components in the two categories of organic acids and nitrogen-containing compounds or the ratio between the components, a more accurate evaluation of the fermentation quality of silage can be achieved. In addition, instead of measuring both the amount of organic acids and nitrogen-containing compounds, knowing only one of them can evaluate the fermentation quality of silage to a very practical level. For example, the Freund's score described in Non-Patent Document 2 evaluates based on the composition of organic acids such as lactic acid, acetic acid, and butyric acid. However, as described herein, this score also depends on the silage production and fermentation conditions (for example, according to Non-Patent Document 2, the difference from the V score increases when acid addition methods, which add acid during the production process, or low-moisture silage preparation methods are used). However, in many cases, a good quality evaluation can be obtained that correlates well with the V score, which also measures nitrogen-containing compounds. Furthermore, it is believed that simply determining the butyric acid concentration, which has been reported to increase the risk of disease when the intake is high (45 g / day or more), is consistent with field needs. Alternatively, by also measuring the amount of an organic acid selected from the C2+C3 organic acids, such as acetic acid as described in the Examples, a more accurate and stable quality evaluation can be achieved. Furthermore, if components other than organic acids or nitrogen-containing compounds are useful for evaluating silage fermentation quality, silage quality evaluation can be performed by measuring these components in addition to or in place of the organic acid and / or nitrogen-containing compound measurements.

[0064] By selecting an appropriate sensing membrane material, a surface stress sensor can generate a superposition of response signals (also called signals) from a single sensing membrane to multiple target substances. Specifically, by appropriately selecting the sensing membrane material for a variety of target substances, the amplitude or waveform of the surface stress sensor's response to each target substance can be made different. Therefore, by combining the outputs of multiple surface stress sensors, a fermentation quality evaluation value can be determined that appropriately combines parameters corresponding to the multiple target substances. In this case, as described above, by performing pattern matching or machine learning on the outputs of the surface stress sensors and appropriately extracting features from these outputs, silage fermentation quality evaluation can be achieved using only a relatively small number of surface stress sensors based on a greater number of parameters than the number of surface stress sensors. Of course, this is not limiting; if other types of gas sensors are particularly useful for detecting specific components present in the gas emitted from the measurement object and useful for silage quality evaluation, such gas sensors can be used in conjunction with surface stress sensors as needed.

[0065] In the present invention, a surface stress sensor is used to measure the gas generated from a sample to be measured. The following is an overview of the measurement system configuration that can be used for this purpose. Figure 1 .exist Figure 1 In the schematic configuration shown, a membrane type surface stress sensor (MSS) is used as the surface stress sensor, but this does not necessarily mean that the generality is lost. Figure 1 In the schematic configuration shown, an inactive gas (also called a purge gas or a reference gas) that is not a gas component to be measured and that does not affect the measurement of the gas component to be measured as much as possible is supplied to the two gas flow paths as indicated by the white empty arrows starting from the left side of the figure. As a purge gas, nitrogen or atmospheric air can be used, for example, but nitrogen is used here. It should be noted that when a simple measurement is performed using atmospheric air or the like as a purge gas, there is a possibility that a small amount of organic acids or ammonia generated from silage, which may affect the fermentation quality evaluation, may be mixed into the atmosphere at the measurement site. In this case, as long as the concentration of such mixed gas does not adversely affect the achievement of the intended measurement accuracy (such a situation is referred to as "substantially containing no components that affect the fermentation quality evaluation"), the mixing of such gas can be ignored. The flow rates of these two gas streams are controlled by a mass flow controller (MFC) provided in each gas flow path. Specifically, while the gas flows in the two gas flow paths are alternately switched at desired time intervals, the gas flow rate is controlled to be constant on the time axis. It should be noted that, of course, the control of the airflow is not limited to MFC, and various pumps and the like can be used.

[0066] exist Figure 1In the gas flow path shown on the upper side, a purge gas that does not contain the gas components to be measured is supplied to the MSS to perform a purge process that desorbs various gases diffused in the sensitive film coated on the surface of the MSS to initialize the MSS. Figure 1 The airflow through the gas flow path on the lower side is supplied to the MSS in a state containing gas components volatilized from the sample in the vial set immediately behind the MFC. Of course, when the sample is in a gaseous state from the beginning or when the gas volatilized / evaporated from the liquid or solid state sample is provided to the measurement system, a structure without a vial can be adopted. The airflows from the two gas flow paths are combined in other vials and then supplied to the MSS. In addition, since the rate of gas adsorption / desorption of the sensitive film on the surface of the MSS is affected by temperature, it is preferred to Figure 1 The measurement system shown is housed in a thermostatic bath, thermostat, or other device to maintain its temperature at the desired value. It should be noted that in the following examples, the entire measurement system is housed in a thermostat for measurement. Furthermore, this system also includes an information processing device that controls the operation of various devices within the system, such as the MFC, and performs various processing operations such as acquiring, recording, and analyzing signals from the surface stress sensor to implement the evaluation method described below. Interfaces and communication devices for exchanging information and commands with external devices are also included, but these are not shown in the figure.

[0067] An example of an optical microscope photograph of MSS is shown in Figure 2 . Figure 2 The MSS shown is formed by cutting single crystal silicon from a silicon wafer used in the field of semiconductor device technology. The central circular portion (which can also be a square or other shape) is connected and fixed to the surrounding frame-like portion at four locations. By causing the gas components supplied to the MSS to adsorb and desorb in the sensitive film coated on the surface of the circular portion, the surface stress applied to the MSS is concentrated in these four fixed areas, causing the resistance of the piezoresistive elements installed in these fixed areas to change. These piezoresistive elements are connected to the conductive area ( Figure 2 The MSS (shown as a sand-like area) is connected to form a Wheatstone bridge. A voltage is applied between two opposing nodes of the Wheatstone bridge, and the voltage between the remaining two nodes is taken out as a signal from the MSS for analysis. For example, the structure and operation of such an MSS are described in detail in Patent Document 3. Figure 2In this example, the sensitive film is applied not only to the circular portion of the MSS but also to the entire surface of the MSS chip, including the frame. This is the case when the sensitive film is applied by spray coating. However, since the sensitive film applied to the frame and other parts does not contribute substantially to the sensor output signal, it can function as a sensor even with this coating. Of course, it is also possible to use MSS with the sensitive film applied only to the circular portion using an inkjet or dispenser.

[0068] Figure 3 A conceptual diagram showing the temporal change in signal intensity when a sample gas is supplied to a surface stress sensor such as an MSS. Figure 3 (a) The time axis shows whether the gas supplied to the MSS is sample gas or purge gas. Specifically, the concentration of the target gas in the gas supplied to the MSS is Cg, which is greater than 0 during the sample gas injection period. The purge gas supply flushes the sample gas in the downstream gas flow path while simultaneously desorbing sample gas components adsorbed on the MSS's sensitive membrane (and the gas flow path walls, etc.). During the purge period, the sample gas concentration is zero. Figure 3 (b) Shows that Figure 3 (a) The time axis of the signal intensity from the MSS when the gas type is switched Figure 3 (a) Alignment. The signal intensity depends on many important factors, but basically, the main factor is the rate of adsorption / desorption of the component between the gas and the sensing membrane caused by the difference in the concentration of the component in the gas near the sensing membrane on the MSS and the concentration of the same component on the sensing membrane surface. Therefore, the temporal variation of the signal intensity is derived from Figure 3 The curve shown in (a) immediately after the gas is switched approaches a saturation value in the form of an exponential function. Figure 3 (b) shows the curve under ideal conditions. The actual shape and maximum value of this curve vary significantly depending on the adsorption / desorption rate of the membrane and the type of component adsorbed / desorbed from the membrane, and the signal variation range generally also varies significantly. Furthermore, the signal exhibits more complex temporal variations due to factors such as the viscoelastic properties of the membrane, diffusion of the target gas into the membrane, and physicochemical interactions between the membrane material and the target gas. Thus, the amount / concentration of each major component in the sample or the ratio between multiple components can be determined based on the temporal variation and amplitude of the signal from the MSS. Specifically, some membrane materials provide signals suitable for C4 evaluation, while others provide signals suitable for C2+C3 evaluation. Therefore, by measuring gases extracted from silage using a single surface stress sensor coated with a material appropriately selected from these materials, or by performing the same measurement using multiple surface stress sensors coated with different materials, silage evaluation based on desired characteristics can be performed.

[0069] The adsorption / desorption characteristics of materials forming the sensitive film vary, and some materials may exhibit responses that deviate from the simplified model described above. However, it can be argued that initial research using the model described above is often beneficial when analyzing the response of surface stress sensors.

[0070] It should be noted that Figure 3 The sample gas is supplied to the MSS only once in the figure. However, in the measurement of surface stress sensors such as MSS, the sample gas and the purge gas are supplied alternately and repeatedly. Figure 3 The measurement shown is common. Hereinafter, the combination of sample gas injection and subsequent purging is referred to as a measurement cycle. In addition, as long as there is no significant difference between the adsorption rate and desorption rate of a certain component in the sample gas, there are many cases where the sample gas injection period and the purge period have the same length of time. However, in cases where better results can be obtained by fully desorbing the components adsorbed on the sensitive membrane from the sample gas, the purge period can be longer than the sample gas injection period. Specifically, as described in the embodiment, when the ratio of the length of the sample gas injection period to the purge period is 1:1, there is a risk that the baseline fluctuation of the signal increases due to insufficient desorption during the purge period, which may adversely affect the discrimination accuracy. In this case, the purge period can be extended by, for example, making the above ratio 1:2.

[0071] It should be noted that the above description is based on the measurement sequence of switching the sample gas and the purge gas, but the present invention is not limited to this. For example, it is possible to insert another gas (standard gas) contained in the sample gas into the measurement sequence, and perform fermentation quality evaluation based on the signal from the switching measurement of the three gases, and the other gas (standard gas) contains a certain component whose concentration may affect the fermentation quality evaluation of the silage. As such a standard gas, for example, a standard silage can be assumed, and a gas having the same composition as the sample gas component generated therefrom can be used as the standard gas. Alternatively, a gas having the same composition as a part of the assumed sample gas (for example, a component with a small difference in the amount of a component measured with particularly high precision, etc.) can be used as the standard gas, and various compositions can be set as needed. In addition, the supply sequence of the three gases can be appropriately set in consideration of various requirements or restrictions on the measurement. For example, the following measurement sequence including repeated gas supply time intervals can be considered.

[0072] A: Supply purge gas → [supply one of sample gas and standard gas → supply purge gas → supply the other of sample gas and standard gas → supply purge gas] (or repeat in [ ]).

[0073] B: Supply purge gas → [supply sample gas and standard gas alternately → supply purge gas] (or repeat in [ ]).

[0074] C: Supply purge gas → [repeat the alternating supply of one of the sample gas and standard gas and the purge gas → supply purge gas → repeat the alternating supply of the other of the sample gas and standard gas and the purge gas] (or repeat within [ ]).

[0075] In addition, various gas supply sequences within the gas supply time interval can be considered. In any gas supply sequence, since measurement conditions such as temperature, gas pressure / flow rate, and temporal changes in sensor characteristics are expected to remain stable over the course of a series of measurements, precise measurement of minute compositional differences between the sample gas and the standard gas can be achieved by comparing them. This also improves measurement stability by minimizing the effects of interference on measurement results.

[0076] It should be noted that, when using a standard gas, a gas flow path for the standard gas is added to the gas supply system of the measuring device, but this can be easily achieved by utilizing various existing technologies for the gas supply system. For example, the standard gas can be prepared in a gaseous state from the beginning, or can be introduced into the gas supply system by evaporation from a liquid or solid in the same way as the sample gas. In addition, when providing the standard gas, other gases such as a purge gas can be mixed with the gas initially prepared or the gas generated from the liquid / solid. In addition, it is necessary to make these three gas flow paths eventually converge, and the three flow paths can be merged at one point, or it can also be considered to divert the upstream side of the sample gas flow path to form a standard gas flow path, and after the standard gas is introduced, the two gas flow paths are merged before the confluence point with the purge gas.

[0077] While not intended to be limiting, the sensing membrane material can be made of at least one material selected from the group consisting of poly(methyl vinyl ether-alt-maleic anhydride), poly(2,6-diphenyl-p-phenylene oxide), and poly(4-methylstyrene). In another embodiment, at least one material selected from the group consisting of polymethyl methacrylate, poly(4-methylstyrene), phenyl-modified silica / titania composite nanoparticles, octadecyl-modified silica / titania composite nanoparticles, poly(2,6-diphenyl-p-phenylene oxide), polyvinyl fluoride, polystyrene, polycaprolactone, cellulose acetate butyrate, polyethyleneimine, and tetraethoxysilane-modified silica / titania composite nanoparticles can be used. A single material selected from these groups can be used alone, or multiple materials can be used in combination by using a first MSS containing one of the selected materials as the sensing membrane and a second MSS containing another material selected from the aforementioned group as the sensing membrane. Of course, when multiple materials are used in combination, the number of MSSs used is not limited to two, and a third, fourth, or more MSSs may be used, with the sensitive membrane of each MSS using a different material selected from the above group.

[0078] [Example]

[0079] The present invention will be described in more detail below by way of examples. It should be noted that the following examples are not intended to limit the present invention but are provided to aid understanding.

[0080] [Example 1]

[0081] In this embodiment, the Figure 1The measurement system, schematically shown, is housed in a thermostat. Samples to be measured were aqueous solutions of organic acids, abundant in silage, and silage of various qualities, stored in vials. Measurements were performed at three thermostat temperature settings: 20°C, 30°C, and 45°C. Because discrimination (the degree to which sample differences manifest as differences in the MSS response signal waveform) was best at 30°C, the results of measurements at this temperature setting are shown below. Measurements were also performed at sample and purge gas flow rates of 10 sccm and 30 sccm, with 10 sccm providing superior discrimination. However, it should be noted that the sample gas diffusion rate, the adsorption rate of the sensor membrane, and the flow rate all significantly influence discrimination. Therefore, the discrimination mentioned above simply reflects the conclusion that discrimination at 10 sccm is higher than at 30 sccm in the current measurement system. For example, the optimal flow rate may vary if the thickness of the sensor membrane or the amount of sample collected changes. Furthermore, a flow rate of 10 sccm, which can suppress heat generation from the pump, offers significant advantages, while avoiding temporal variations in the gas flow path temperature that can affect gas temperature. While the measurement system used in this example lacks thermal countermeasures for the gas flow path, such as the installation of a cooling fan, the aforementioned flow rate provides suitable measurement conditions for this measurement configuration. Measurements were conducted with sampling times (the time during which sample gas is injected during each measurement cycle) of 30 seconds and 120 seconds, but no difference in discrimination was observed. The following data shows the results for a sampling time of 120 seconds. Measurements were conducted with a ratio of 1:2 between the sampling time and the purge time (the time during which purge gas is supplied to the MSS during each measurement cycle). Experiments conducted by the present inventors have confirmed that shortening the purge time, such as by reducing the sampling time to a 1:1 ratio, results in insufficient desorption of components adsorbed from the sensitive membrane during the purge (i.e., sample gas injection) and increases baseline fluctuation. Therefore, using only a short purge time can negatively impact discrimination accuracy. In actual measurements, extending the measurement time not only has the disadvantage of reducing the throughput of the measurement itself, but also often makes it difficult to stabilize various parameters of the internal and external environments of the measurement system (flow rate, gas pressure, temperature, etc.) for a long time, resulting in the problem of large-scale and high-priced measurement systems. In addition, since the measurement system usually includes active components such as pumps, there is a risk that long-term temperature changes caused by the heat generated by the active components will also have an adverse effect on the accuracy. Therefore, in the present invention, it is preferred to allocate the measurement cycle time to be as short as possible within the range of the sampling time to obtain a valid signal value, and to make the purge time as long as possible. Alternatively, as a countermeasure when baseline fluctuation becomes a problem, standard silage is prepared in which the amount of the component that affects the quality is a predetermined value. By measuring the standard silage in each measurement for calibration, etc., the adverse effects of short-time purge can be eliminated or reduced.

[0082] As aqueous solutions of organic acids, 1% aqueous solutions of each single organic acid were prepared and measured. Silage of a predetermined weight was directly placed in a vial and measured without adding water or the like to the silage.

[0083] It should be noted that the organic acids contained in each of the various silages used as measurement targets were separately measured using the V score measurement method. It should be noted that organic acids such as malic acid and succinic acid, which were not used in calculating the V score, were also measured. The results are shown in the table below.

[0084] [Table 1]

[0085]

[0086] Furthermore, the nitrogen compound content of these silages was measured, and V scores were calculated as shown in the following table based on the results of the above-mentioned organic acid measurement.

[0087] [Table 2]

[0088]

[0089] The MSS used is actually an aggregate of multiple MSSs coated with different sensitive membrane materials. Among them, the MSS using poly(methyl vinyl ether-alt-maleic anhydride) as the sensitive membrane material (designated ChA) exhibited the best discrimination performance. The following description will primarily focus on the signal output from ChA. It should be noted that since the signals from the remaining two MSSs are also effective for discrimination, they will be referred to as ChB (sensitive membrane material: poly(2,6-diphenyl-p-phenylene oxide)) and ChC (sensitive membrane material: poly(4-methylstyrene)) in the description.

[0090] Figure 4 The 1% aqueous solution of each organic acid is stored in a vial. Figure 1 The time change (in seconds) of the signal (in mV) of the MSS from ChA when the measuring device shown is used for measurement. Here, acetic acid, butyric acid, lactic acid, propionic acid and valeric acid are measured as organic acids. In addition, water before dissolving the organic acid is also measured as a comparison object. The measurement order is to first pass the purge gas for 240 seconds, then pass the sample gas for 120 seconds, and then pass the purge gas for another 240 seconds. In addition, the flow rate of the purge gas and the sample gas is 10 sccm. In addition, by Figure 4 As can be seen, each sample was measured twice, and the results of both are plotted here. Figure 5 and Figure 6 The measurements shown were also performed using the same measurement sequence and flow rate. Figure 4 It can be seen that when the vapor from the aqueous solution of each organic acid is measured as the sample gas, the signal for acetic acid is saturated in a short period of time, and the signal decreases significantly after about 60 seconds after the start of sample gas injection. In contrast, the signals for other organic acids such as butyric acid show a tendency to be almost constant or slightly decreasing after saturation, or because the signal slowly increases, the increase in signal continues even at the end of the sample gas injection period (the moment 120 seconds after the start of sample gas injection). It should be noted that since lactic acid, one of the organic acids measured here, is not volatile, its signal is almost the same as that of water.

[0091] Next, when measuring a gas containing a mixture of multiple organic acids, as in the case of a sample gas generated from actual silage, we will verify whether the response of each component from the MSS is a relatively linear and superimposed signal, or whether the response of each component affects each other, making it impossible to simply separate the contribution of each component even when examining the signal from the MSS. Figure 4 The results of measuring the mixed organic acid aqueous solution (simulated silage aqueous solution) having the organic acid composition in the extracts of silage samples 1 to 6 shown in the above table are shown in the following table. Figure 5 Here, each simulated silage is indicated by adding the suffix "-VFA" after the sample number of the silage corresponding to the silage.

[0092] By comparison Figure 5 and Figure 4It was confirmed that the sensitive membrane used in the ChA MSS, when measuring gases generated by samples composed of organic acids from silage, exhibited temporal variations similar to those obtained by linearly superimposing the signals for each organic acid gas. Specifically, the 1-VFA signal for Sample 1, which had a high butyric acid concentration, exhibited a gradual rise similar to that of gases from a pure butyric acid aqueous solution. In contrast, the 2-VFA signal for Sample 2, which had a low butyric acid concentration and a high acetic acid concentration, rose as rapidly as that of gases from a pure acetic acid aqueous solution. Furthermore, after reaching its peak, the large signal value, thought to be derived from pure acetic acid, decreased, and was displayed as a slightly more gradual signal by superimposing the signals of other gases that had barely changed since the start of the sample gas injection. Furthermore, the 3-VFA, 4-VFA, and 5-VFA signals for Samples 3, 4, and 5, respectively, which had zero butyric acid concentration and low acetic acid concentration, all rose relatively quickly before remaining nearly constant. This is believed to be due to the lack of influence from butyric acid, which has the slowest signal increase, and the minimal influence from acetic acid, which rapidly decreases within a relatively short period. Furthermore, it was confirmed that the rise and subsequent changes in the signal of sample 6-VFA corresponding to sample 6, which had a slightly higher acetic acid concentration than samples 3, 4, and 5 and contained a trace amount of butyric acid, were both between samples 1-VFA and 2-VFA.

[0093] In addition, silages 1 to 6 were placed in vials, and the sample gas generated from each vial was measured in the same manner. The results are shown in FIG. Figure 6 However, in Figure 4 and Figure 5 In the measurements shown, individual organic acids or aqueous solutions of multiple organic acids were measured, but Figure 6 In the silage measurement shown, only a predetermined weight of silage was placed in a vial without mixing liquids such as water or other substances.

[0094] The signal from the actual silage will be shown Figure 6 , and shows the signals from simulated silages with the same organic acid composition as these silages Figure 5When compared, it can be seen that the order relationship between the actual silages is different from the order relationship between the simulated silages when compared at the maximum value of the signal, but the characteristics of the signal time change described above are almost the same between the actual silage and the simulated silage. Therefore, the amount of various organic acids in the silage or their composition can be determined by the characteristics of the time change pattern of the signal of the surface stress sensor such as MSS during the injection of the gas generated from the silage itself. In particular, it can be judged that the determination using ChA is particularly useful for the above-mentioned C4 evaluation. Thus, by evaluating the amount of organic acids above C4 such as butyric acid, and further evaluating the amount of C2 and C3 organic acids such as acetic acid as needed, the fermentation quality of the silage can be evaluated with simple steps. In addition, by comparison with the second table mentioned above, it can be seen that the determination of nitrogenous compounds is not performed in this embodiment, but the evaluation results of the signals of various silages and the amount of butyric acid and acetic acid described above have a high correlation with the V score value. In addition, by Figure 5 and Figure 6 As can be seen from the comparison results, since the results of measuring the gas generated from the organic acid mixed aqueous solution using a surface stress sensor such as MSS are highly consistent with the results of measuring the gas generated from the silage itself measured by the present invention using the same surface stress sensor, the present invention also has the advantages of calibrating the measurement system in the measurement and making it easy to compare / contrast with the evaluation results of the silage evaluation method using the existing silage extract as the measurement object. It should be noted that the silage used as the evaluation object in this embodiment is made using dent corn and forage grass by a general method, and is a type widely used as feed for animals such as cattle. However, the method of the present invention can be advantageously applied to a wide range of silage types, such as other silages with different raw materials or fermentation methods, or fermented TMR (Total Mixed Rations) that are secondary processed from the silage.

[0095] In addition to the above-described measurement using ChA, measurements were also performed using MSS of ChB and ChC to obtain signals from these. The measurement results using ChB are shown in FIG. Figures 7 to 9 The results of the ChC measurements are shown in Figures 10 to 12 The results of the measurement of each organic acid using ChB and ChC were less correlated with the results of the measurement using simulated silage than those using ChA. However, the differences in the composition of organic acids produced by silage were not significant. Figure 9 (using ChB) and Figure 12 This is clearly evident in the temporal variation of the signal shown (using ChC). As described below, measurements using both ChB and ChC are useful for evaluating C2+C3.

[0096] Right now, Figure 9The chart shows the temporal changes in the signal when measuring actual silage (samples 1 to 6) using ChB. The saturation rates of signal rise and fall (the time it takes for the signal to converge to a nearly constant value after switching the sample gas and purge gas) for sample 1, which has a high content of butyric acid, sample 2, which has a high content of acetic acid, and sample 6, which has a high content of C2+C3 (see the first table above) differ greatly from each other. Furthermore, compared to the other silages with sample numbers 3 to 5, whose signals saturate quickly after switching gases, the saturation rates of the silages with sample numbers 1, 2, and 6 are relatively slow (saturation is slow). As can be seen from the second table above, the C2+C3 evaluations of the silages with samples 1, 2, and 6 are significantly lower than those of the other silages. Therefore, it can be said that the saturation rates of the ChB signal rise and fall are strongly correlated with the C2+C3 evaluation. Therefore, the C2+C3 evaluation of the silage being measured can be performed by using either or both of the MSSs of ChB and ChC.

[0097] It should be noted that since the temporal variation patterns of the signals from ChB and ChC are similar to those of VFAs, which may be present in large quantities in silage, Figure 9 and Figure 12 It can be seen that rather than having different temporal variation patterns, the temporal variations in the signal intensity direction are often nearly identical (the temporal variation in the signal intensity from one sample is multiplied by a constant and then shifted parallel to the intensity direction, resulting in nearly identical temporal variations in the signal intensity from other samples). Therefore, by stabilizing the sample gas supply and normalizing or standardizing other signals, such as by keeping the sample volume used for measurement as constant as possible, the silage evaluation system can be further improved.

[0098] [Example 2]

[0099] In this embodiment, the Figure 1 The measurement system, schematically shown, is housed in a constant temperature chamber. Three different silages from those used in Example 1 were stored in vials as test samples. No water or other additives were added to each silage; a predetermined weight of silage was directly stored in the vial for measurement. The constant temperature chamber was maintained at 30°C, and the flow rates of the sample gas and purge gas were 10 sccm. The sampling time was 120 seconds, with a sampling time to purge time ratio of 1:2.

[0100] It should be noted that in actual measurements, the temperature and relative humidity in the constant temperature chamber will inevitably change slightly, but in this embodiment, the changes in temperature and relative humidity in the constant temperature chamber (inside the module of the measurement system) during measurement are suppressed to a range that can be considered to have no significant impact on the measurement results.

[0101] In addition, in this embodiment, before obtaining the measurement data, as a preparatory action, the sample gas and purge gas to be measured are flowed into the measurement system at the same flow rate as the actual measurement and the switching cycle of the two gases is set in the same way as the actual measurement. By performing this preparatory action, the measurement data can be made more stable (that is, the accuracy of the measurement data can be further improved). Such a preparatory action is often performed in the measurement of samples with any gas as the measurement object. The number of cycles (time) is not particularly limited. In this embodiment, 200 cycles (a total of 20 hours) are performed. It should be noted that the measurement data shown in the above-mentioned embodiment 1 were also obtained after performing the same preparatory action.

[0102] The silages used as the measurement objects in this embodiment are "high-quality silage samples", "low-quality silage samples" and "high-quality silage samples with reduced volatile components". The "high-quality silage samples" and "low-quality silage samples" are respectively the results of chemical analysis of the organic acid content shown in the table below, which evaluates the quality of the silage samples and are evaluated as high-quality silage samples and low-quality silage samples. The "high-quality silage sample with reduced volatile components" is a silage sample in which a certain amount of the above-mentioned "high-quality silage sample" is placed in a vial and exposed to a purge gas for a certain period of time, thereby reducing the volatile components. Hereinafter, the "high-quality silage sample", "low-quality silage sample" and "high-quality silage sample with reduced volatile components" are referred to as sample 7, sample 8 and sample 9, respectively. The following table shows the measurement results of the organic acids contained in samples 7 to 9.

[0103] [Table 3]

[0104]

[0105] The MSS used is actually a collection of multiple MSSs coated with different sensitive film materials. The following explanation primarily uses the ChD output signal as an example, but reference is also made to the signals output from the remaining MSSs. The MSS numbers and the sensitive film materials used are as follows.

[0106] ChD: polymethyl methacrylate.

[0107] ChE: poly(4-methylstyrene).

[0108] ChF: Phenyl-modified silica / titania composite nanoparticles (hereinafter also referred to as "Phenyl-STNPs").

[0109] ChG: octadecyl-modified silica / titania composite nanoparticles (hereinafter, also referred to as “C18-STNPs”).

[0110] ChH: poly(2,6-diphenyl-p-phenylene ether) (Tenax TA (mesh: 60 / 80)).

[0111] ChI: Polyvinyl fluoride.

[0112] ChJ: Polystyrene.

[0113] ChK: Polycaprolactone.

[0114] ChL: cellulose acetate butyrate.

[0115] ChM: Polyethylenimine.

[0116] ChN: tetraethoxysilane-modified silica / titania composite nanoparticles (hereinafter also referred to as “TEOS-STNPs”).

[0117] Figure 13 The three silage samples to be measured are placed in vials and Figure 1 The measurement device shown measures the time change (in seconds) of the MSS signal (in mV) from the ChD when the sample gas generated is measured. The measurement sequence is to first pass the purge gas for 240 seconds, then pass the sample gas for 120 seconds, and then pass the purge gas again for 240 seconds. It should be noted that in actual measurement, multiple measurements are performed on each sample, but Figure 13 Representative data from these measurement results are shown.

[0118] Depend on Figure 13Measurements using ChD (sensing membrane material: polymethyl methacrylate) revealed significant differences in signal changes (signal waveforms) during the sample gas injection period (120 seconds) among the three silage samples. More specifically, ChD measurements confirmed that, in addition to identifying differences between Samples 7 and 8, whose quality was determined by chemical analysis, ChD measurements also revealed differences in volatile component content between silage samples (Samples 7 and 9) of comparable quality (high quality) assessed by chemical analysis. Separately, measurements using a proton transfer reaction time-of-flight mass spectrometer revealed concentrations of acetic acid and butyric acid, representative volatile components, of 57 ppm and 21 ppm, respectively, for Sample 7, 32 ppm and 23 ppm for Sample 8, and 16 ppm and 6 ppm for Sample 9. These differences in MSS concentrations are believed to be reflected in the ChD measurements. Furthermore, the saturation rate of signal decline during the purge period following the sample gas injection period also differed significantly between Samples 7, 8, and 9.

[0119] exist Figures 14 to 23 In the figure, the following are shown respectively: Figure 13 The same steps are performed as for the case with Figure 13 The time change (in seconds) of the signal (in mV) from the MSS of ChE to ChN when three silage samples of the same measurement object are measured.

[0120] The characteristics of the signal changes (time-dependent changes) obtained by each MSS vary depending on the difference in the sensing membrane material used, but Figures 14 to 23 It can be seen that even in the measurements using ChE to ChN, the signal changes (signal waveforms) during the sample gas injection period (120 seconds) differed between the three silage samples. In particular, in the measurements using ChE (sensing membrane material: poly(4-methylstyrene), the same material as ChC in Example 1), ChH (sensing membrane material: poly(2,6-diphenyl-p-phenylene ether), the same material as ChB in Example 1), ChI (sensing membrane material: polyvinyl fluoride), ChJ (sensing membrane material: polystyrene), ChL (sensing membrane material: cellulose acetate butyrate), and ChM (sensing membrane material: polyethyleneimine), the signal changes (signal waveforms) during the sample gas injection period (120 seconds) differed between the three silage samples. Figure 13 As shown in the measurement using ChD, the signal changes (signal waveforms) during the sample gas injection period (120 seconds) were significantly different among the three silage samples ( Figure 14 、 17, 18, 19, 21, 22). On the other hand, it was found that the saturation rate of signal decrease of these MSSs during the purge period after the sample gas injection period tended to be different. For example, in the measurement using ChE and ChI, similar to the case of ChD, the saturation rate of signal decrease was found to be different between Sample 7, Sample 8, and Sample 9. In the measurement using ChH, ChJ, ChL, and ChM, the saturation rate of signal decrease of Sample 7 and Sample 8 was found to be almost the same or slightly different. In contrast, the saturation rate of signal decrease of Sample 9 tended to be faster than that of Samples 7 and 8.

[0121] In the measurement using ChF (sensing membrane material: Phenyl-STNPs), significantly different signal changes were observed between Sample 7, Sample 8, and Sample 9 during the sample gas injection period and the purge period after the sample gas injection period. Figure 15 ).

[0122] In measurements using ChG (sensitive membrane material: C18-STNPs), during the sample gas injection period, the difference in signal change between samples 7 and 8 and sample 9 tended to be greater than the difference in signal change between sample 7 and sample 8. Furthermore, during the purge period after the sample gas injection period, a difference in the saturation rate of signal decrease was observed between sample 8 and samples 7 and 9, indicating that differences between samples whose quality was determined by chemical analysis can be identified ( Figure 16 ).

[0123] In the measurement using ChK (sensing membrane material: polycaprolactone), while no significant difference was observed compared to the other MSS used in the measurement of this example, differences in signal changes were observed between Samples 7, 8, and 9 during the sample gas injection period. On the other hand, during the purge period after the sample gas injection period, almost no difference was observed in the saturation rate of signal decrease between Samples 7, 8, and 9 ( Figure 20 ).

[0124] In the measurement using ChN (sensitive membrane material: TEOS-STNPs), similar to the case of ChK, although there was no significant difference compared to the other MSS used in the measurement of this example, differences in signal changes were found between Samples 7, 8, and 9 during the sample gas injection period. In addition, similar to the case of ChG, differences in the saturation rate of signal decrease were found between Sample 8 and Samples 7 and 9 during the purge period after the sample gas injection period. This indicates that differences between samples whose quality was determined by chemical analysis can be identified ( Figure 23 ).

[0125] It should be noted that the silage evaluated in this example was the same as that used in Example 1, produced using dent corn and forage grasses using conventional methods, and is a type widely used as feed for animals such as cattle. Therefore, based on the results of this example, the method of the present invention can also be advantageously applied to a wide range of silage types, including other silages using different raw materials or fermentation methods, as well as fermented TMRs (Total Mixed Rations) obtained by secondary processing of these silages.

[0126] It should be noted that in the present invention, when evaluating the signal provided by the measurement system, if a rough evaluation is sufficient, the temporal variation of the signal can be simply visually observed. However, for a more precise evaluation, for example, temporal variation patterns of the signal corresponding to various silage qualities can be prepared as reference patterns, and a general pattern matching method commonly used in the field of measurement technology can be performed to compare the temporal variation pattern of the signal obtained from the silage being measured with the reference pattern. Alternatively, the quality of the silage can be evaluated based on the temporal variation pattern of the signal obtained from the silage using machine learning techniques that have been frequently used in the field of measurement technology in recent years. Such pattern matching or machine learning can be performed by any information processing device, such as an information processing device installed in the measurement system or an information processing device connected from the measurement system by an interface or communication line. It should be noted that since the principles and techniques for applying these pattern matching or machine learning to various measurement results are well known, further explanation will be omitted.

[0127] Industrial Applicability

[0128] As described above, according to the present invention, since the fermentation quality of silage can be evaluated in a short time using a simpler device configuration than conventional ones and through simple steps, the fermentation quality evaluation of silage can be easily performed at the production, distribution, and use sites of silage.

[0129] Prior art literature

[0130] Patent Literature

[0131] Patent document 1: Japanese Patent Application Laid-Open No. 2019-128312.

[0132] Patent document 2: Japanese Patent Application Laid-Open No. 2018-132325.

[0133] Patent document 3: International Publication No. 2011 / 148774.

[0134] Non-patent literature

[0135] Non-patent document 1: "Revised Edition of the Guidelines for the Quality Evaluation of Roughages" compiled by the Self-sufficient Feed Quality Evaluation Research Group, Japan Grassland Livestock Seed Association (2001).

[0136] Non-Patent Literature 2: Minami-Nemuro Regional Agricultural Improvement Council, Nemuro Agricultural Improvement Popularization Center, 2009 Agricultural Improvement Materials, Vol. 26, "Special Feature: THE Silage," "7. How is the Fermentation Quality of Silage Inspected?"

Claims

1. A method for evaluating the fermentation quality of silage, wherein: A surface stress sensor is provided having a response characteristic different from that of at least one of an organic acid C2 having 2 carbon atoms in its molecule and an organic acid C3 having 3 carbon atoms and a response characteristic different from that of at least one of an organic acid C4 having 4 or more carbon atoms. providing the surface stress sensor with gas generated from silage, using a signal output from the surface stress sensor in response to gas generated from the silage, evaluating the signal according to at least one of the following criteria 1 and 2, and evaluating the fermentation quality of the silage based on the composition of the gas generated from the silage according to the evaluation result; Benchmark 1: Ratio of the amount of C4 to the amount of C2 and C3, Benchmark 2: Amount of C2 and C3.

2. The method for evaluating silage fermentation quality according to claim 1, wherein: Furthermore, the amount of nitrogen-containing compounds in the gas generated from the silage is evaluated, and the fermentation quality of the silage is evaluated based on the composition of the gas generated from the silage.

3. The method for evaluating silage fermentation quality according to claim 1, wherein: The fermentation quality is evaluated based on the temporal variation pattern of the signal.

4. The method for evaluating silage fermentation quality according to claim 3, wherein: The evaluation of the fermentation quality was performed based on the evaluation of the effect of the temporal pattern of the amount of butyric acid in the gas generated from the silage.

5. The method for evaluating silage fermentation quality according to claim 3, wherein: The evaluation of the fermentation quality was performed based on the evaluation of the effect of the time-varying pattern of the amount of acetic acid in the gas generated from the silage.

6. The method for evaluating silage fermentation quality according to claim 1, wherein: Gas obtained by passing a gas substantially free of components that affect the evaluation of fermentation quality into a container storing silage to be evaluated is supplied to the surface stress sensor as gas generated from the silage.

7. The method for evaluating silage fermentation quality according to claim 1, wherein: The fermentation quality of the silage is evaluated using the signal after the supply of the gas generated from the silage to the surface stress sensor is started.

8. The method for evaluating silage fermentation quality according to claim 1, wherein: The surface stress sensor is a membrane type surface stress sensor.

9. The method for evaluating silage fermentation quality according to claim 1, wherein: As a material of the sensing film of the surface stress sensor, at least one selected from the group consisting of poly(methyl vinyl ether-alt-maleic anhydride), poly(2,6-diphenyl-p-phenylene ether), and poly(4-methylstyrene) is used.

10. The method for evaluating silage fermentation quality according to claim 1, wherein: As the material of the sensing film of the surface stress sensor, at least one selected from the group consisting of polymethyl methacrylate, poly(4-methylstyrene), phenyl-modified silica / titanium dioxide composite nanoparticles, octadecyl-modified silica / titanium dioxide composite nanoparticles, poly(2,6-diphenyl-p-phenylene ether), polyvinyl fluoride, polystyrene, polycaprolactone, cellulose acetate butyrate, polyethyleneimine and tetraethoxysilane-modified silica / titanium dioxide composite nanoparticles is used.

11. The method for evaluating silage fermentation quality according to claim 9 or 10, wherein: As the surface stress sensor, at least a first surface stress sensor using one material selected from the group for a sensing film and a second surface stress sensor using another material selected from the group for a sensing film are used.

12. The method for evaluating silage fermentation quality according to claim 1, wherein: Gas generated from the silage and purge gas are alternately supplied to the surface stress sensor, and fermentation quality of the silage is evaluated using the signal corresponding to the gas generated from the silage and the signal corresponding to the purge gas.

13. The method for evaluating silage fermentation quality according to claim 12, wherein: In addition to the time interval for supplying the gas generated from the silage to the surface stress sensor and the time interval for supplying the purge gas to the surface stress sensor, a time interval for supplying a specified standard gas to the surface stress sensor is also set, and the signal corresponding to the standard gas is further used in evaluating the fermentation quality of the silage.

14. The method for evaluating silage fermentation quality according to claim 13, wherein: The standard gas is a gas generated from a liquid or a solid.

15. The method for evaluating silage fermentation quality according to claim 1, wherein: Gas generated from the silage is supplied to an additional gas sensor, and the fermentation quality of the silage is evaluated based on a signal from the surface stress sensor and a signal from the additional gas sensor.

16. A device for evaluating the fermentation quality of silage, wherein: The silage fermentation quality evaluation device is provided with: at least one surface stress sensor having a response characteristic different from that of at least one of an organic acid C2 having 2 carbon atoms in its molecule and an organic acid C3 having 3 carbon atoms and a response characteristic different from that of at least one organic acid C4 having 4 or more carbon atoms; a first gas flow path for supplying a sample gas generated from silage to be measured; and A second gas flow path that supplies a purge gas that does not contain the gas components to be measured, By alternately switching the supply of the sample gas supplied from the first gas flow path and the purge gas supplied from the second gas flow path to the at least one surface stress sensor, a signal is generated from the at least one surface stress sensor, thereby performing the silage fermentation quality evaluation method described in any one of claims 1 to 12.

17. The silage fermentation quality evaluation device according to claim 16, wherein: The silage fermentation quality evaluation device is provided with an additional gas sensor and an additional gas flow path for supplying the sample gas to the additional gas sensor. The fermentation quality of the silage is evaluated based on the signal from the at least one surface stress sensor and the signal from the additional gas sensor.

18. A device for evaluating the fermentation quality of silage, wherein: The silage fermentation quality evaluation device is provided with: at least one surface stress sensor having a response characteristic different from that of at least one of an organic acid C2 having 2 carbon atoms in its molecule and an organic acid C3 having 3 carbon atoms and a response characteristic different from that of at least one organic acid C4 having 4 or more carbon atoms; a first gas flow path for supplying a sample gas generated from silage to be measured; a second gas flow path for supplying a purge gas that does not contain a gas component to be measured; and A third gas flow path that supplies a standard gas having a predetermined composition, By switching the supply of the sample gas supplied from the first gas flow path, the purge gas supplied from the second gas flow path, and the standard gas supplied from the third gas flow path to the at least one surface stress sensor in a prescribed order, a signal is generated from the at least one surface stress sensor, thereby performing the silage fermentation quality evaluation method according to claim 13 or 14.

19. The silage fermentation quality evaluation device according to claim 18, wherein: The silage fermentation quality evaluation device is provided with an additional gas sensor and an additional gas flow path for supplying the sample gas to the additional gas sensor. The fermentation quality of the silage is evaluated based on the signal from the at least one surface stress sensor and the signal from the additional gas sensor.

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