JP4019153B2 - Fertilizer quality evaluation method, fertilizer quality evaluation device, and fertilizer quality evaluation program - Google Patents

Description

  The present invention relates to a fertilizer quality evaluation method, a fertilizer quality evaluation device, and a fertilizer quality evaluation program for evaluating fertilizer quality such as the degree of maturity of compost.

  Conventionally, incineration and landfilling have generally been implemented as waste treatment, but environmental issues have been actively discussed in recent years, so it is not possible to recycle and reuse waste for new things or energy. Progressing. On the other hand, the amount of kitchen waste and food processing factory residues is increasing, and how to deal with organic waste, a by-product of city life, is a major issue. ing.

  Under such circumstances, composting of organic waste is attracting attention. Composting organic waste is an effective way to prevent energy loss. In addition, it is reported that compost made from kitchen waste has a high content of nitrogen, phosphorus and potassium and is less contaminated with heavy metals and other toxic substances. In this way, organic waste can become good quality compost, so there is an expectation from all sides to establish a composting system for organic waste, but in order to further develop and expand the recycling market. It is essential to stabilize the quality of the compost to be supplied and that the composting system is suitable for cost.

  By the way, the quality of fertilizers such as compost is determined by the content of active ingredients, maturity, toxicity, etc., and quality evaluation is important in considering the compost process and the application of the product fertilizer. For example, when immature compost is applied, the crop becomes severely nitrogen starved and oxygen is consumed in the decomposition of the compost in the vicinity of the root of the crop and becomes deficient. Furthermore, the application of immature compost also causes inconvenience that the growth of substances such as ammonia, ethylene oxide and various organic acids is generated to inhibit the growth of plants. As described above, in order to prevent the shipment of immature compost, it is strongly required to establish a technology that evaluates the degree of maturity of whether the compost is sufficiently matured and evaluates the quality of compost quickly and easily. ing.

  Therefore, various methods for evaluating maturity have been proposed so far. For example, methods for evaluating maturity that can be performed in the field include a scoring method by appearance, a product temperature (deposit temperature) evaluation method, a color tone evaluation method, an odor evaluation method, a touch evaluation method, a plastic bag evaluation method, and an earthworm evaluation method. (For example, refer nonpatent literature 1 etc.). In addition, as methods for evaluating the degree of maturity using chemical analysis, C / N ratio, nitric acid detection method, BOD / COD evaluation method, reducing sugar ratio evaluation method, humus color difference evaluation method, cation exchange (CEC) method , Circular filter paper chromatography method, gel chromatography method and the like (for example, see Non-Patent Document 1 etc.). However, each of the evaluation methods has problems such as limited applicable compost and complicated evaluation work, and is still inadequate in terms of evaluation accuracy of maturity.

  In addition, as a method for evaluating the degree of maturity, a method using a plant response has been proposed. The evaluation method using the response of the plant is very effective for testing the compost maturity and evaluating it as an organic fertilizer. The germination index (hereinafter referred to as GI) method is one of the methods for assessing maturity using the response of plants, and is one of the most sensitive parameters for assessing compost toxicity and maturity. Known as. GI is determined by a germination test. Specifically, a compost water extract immediately after extraction is added to a plastic petri dish with filter paper, and seeds of plants such as komatsuna are sown on the filter paper, and 48 in a dark place at 26 ° C. After incubation for a period of time, the number of germinated seeds and the length of roots are measured, and the ratio is obtained by taking the ratio of the number of germinated seeds and the length of roots in the control plot (distilled water). In order to increase the accuracy of the GI, it is necessary to perform the germination test on a large number of samples. However, a petri dish containing filter paper is used as a measuring instrument, and it takes time to grow plant seeds. There is a problem in that it takes time and labor to maintain a growth environment for growing seeds and to measure after growth.

Therefore, a cultivation tank having visibility opened at the top, a landing member for germinating seeds of plants accommodated in the cultivation tank, and a plant sprouted from the implantation member while growing in the cultivation tank. And a supporting substrate provided in parallel with a cylindrical growth holder having visibility, the flooring member is provided at the lower portion of the growth holder, and the cultivation tank having visibility is provided within the growth holder. A plant growth measuring instrument provided with a scale portion for measuring the degree of growth of a growing plant has been proposed (see, for example, Patent Document 1). According to the invention described in Patent Document 1, a germination test can be performed with a simple operation even when the number of samples is large, and the maturity of organic matter such as compost (compost) can be determined.
Kanazawa Shinjiro, Utilization of Organic Resources in Agricultural Lands 1st Report Compost Maturity Test, Regeneration and Utilization, Vol.27 No.102 (2004) JP 2004-151586 A

  However, the invention of Patent Document 1 also requires problems such as a long measurement time and a complicated measurement because the GI is obtained by actually performing a germination test. However, it is not realistic considering the actual use of composting at the site. Therefore, a technique for estimating the GI with high accuracy without performing a germination test or the like and evaluating the maturity of fertilizer such as compost is desired. However, such a technique has not been established yet. .

  Therefore, the present invention has been proposed in view of such conventional circumstances, for example, in the field of composting organic waste, it is possible to estimate the germination index of fertilizer with high accuracy, such as the degree of maturity An object of the present invention is to provide a fertilizer quality evaluation method, a quality evaluation device, and a fertilizer quality evaluation program capable of quickly, simply and accurately evaluating the quality of a fertilizer.

  The inventors of the present invention have made extensive studies in order to achieve the above-described object. As a result, we have obtained knowledge that there is a good correlation between the germination index as an index for evaluating the degree of maturity of fertilizer, the specific physicochemical index of the fertilizer water extract and the specific enzyme activity. It was. The present invention has been completed based on such findings.

  That is, the fertilizer quality evaluation method according to the present invention acquires at least two kinds of information selected from the physicochemical index and enzyme activity of the fertilizer extract to be evaluated, and applies the information to a predetermined calculation formula. And estimating the germination index of the fertilizer.

  The fertilizer quality evaluation apparatus according to the present invention includes an information acquisition unit that acquires at least two types of information selected from a physicochemical index and an enzyme activity for an extract of a fertilizer to be evaluated; And a control unit that estimates a germination index of the fertilizer by applying to a calculation formula.

  In the present invention, the parameters for determining the germination index as an index of maturity are selected from physicochemical indicators such as pH and ammonium ion concentration of fertilizer extract, and enzyme activities such as enzyme activity representing the activity of microorganisms. By combining multiple parameters, the germination index of the fertilizer can be estimated with high accuracy. Since the germination index expresses the maturity of the fertilizer with high sensitivity, the maturity of the fertilizer can be accurately grasped by the present invention. The measurement of physicochemical indicators such as pH measurement, ammonium ion concentration measurement, and enzyme activity measurement are shorter than the germination test, etc., and the time required for measurement is also short. Is quickly and easily evaluated.

  Furthermore, the fertilizer quality evaluation program according to the present invention includes an information acquisition input function for acquiring at least two types of information selected from a physicochemical index and an enzyme activity for an extract of a fertilizer to be evaluated; A control function for estimating the germination index of the fertilizer by applying to the above formula is realized by a computer.

  According to the fertilizer quality evaluation program configured as described above, in order to make the computer estimate the germination index of the fertilizer, the computer can estimate the germination index, which is an index of the fertilizer maturity, quickly, easily and with high accuracy. Can evaluate the quality of fertilizer.

  According to the present invention, it is possible to estimate the fertilizer germination index with high accuracy by measuring the pH of the fertilizer extract, physicochemical indicators such as ammonium ion concentration, enzyme activity, etc., and evaluate the maturity of the fertilizer. It is possible to provide a fertilizer quality evaluation method capable of evaluating the quality of a fertilizer quickly, easily and with high accuracy.

  Further, according to the fertilizer quality evaluation apparatus of the present invention, it is possible to estimate the germination index, which is an index of the fertilizer maturity, with high accuracy, and it is possible to evaluate the quality of the fertilizer quickly, easily and with high accuracy. . In addition, by using the fertilizer quality evaluation apparatus of the present invention, a high-quality fertilizer can be stably supplied in a composting system that composts municipal waste and the like.

  Furthermore, according to the fertilizer quality evaluation program of the present invention, since the fertilizer quality evaluation can be executed by a computer, the quality of the fertilizer can be evaluated quickly, easily and with high accuracy.

  Hereinafter, the fertilizer quality evaluation method, the fertilizer quality evaluation device, and the fertilizer quality evaluation program according to the present invention will be described in detail.

  In the fertilizer quality evaluation method of the present invention, the germination index of the fertilizer to be evaluated is estimated, the maturity of the fertilizer is evaluated using the estimated germination index as an index, and the quality of the fertilizer is evaluated.

  Here, the fertilizer means an organic fertilizer produced by drying raw materials such as compost produced by fermenting or rotting organic waste containing organic matter, and fish meal, a soil improvement material, etc. It is applicable to all these fertilizers. The present invention is also applicable to fertilizers that are in the middle of production, such as immature compost. As raw materials (materials) for compost and fertilizer, raw garbage discharged from general households and facilities, food residues discharged from food processing factories, pruned branches of trees, rice crackers, cows, pigs, chickens, etc. It is not particularly limited, such as livestock excrement and bark (bark compost raw material), and any conventionally known waste can be used.

  Germination index (hereinafter referred to as GI) represents the degree of maturity of fertilizer from the degree of germination and growth of plant seeds, and serves as an index of maturity of fertilizer. The GI measures, for example, the number of seeds and root length germinated by the germination test, and the number of seeds germinated in the control plot (distilled water) and the length of root, and applies each data to the following formula (1). Is required. In the germination test, for example, a fertilizer water extract immediately after extraction or 10 ml of water (distilled water) is added to a petri dish on which filter paper is laid, and seeds of plants such as Komatsuna are sown on the filter paper, and in a dark place at 26 ° C. for 48 hours. After incubation, the number of germinated seeds and root length are measured. In calculating the GI, a stem length or the like may be used in addition to the root length.

  In the present invention, the GI of the fertilizer to be evaluated is estimated in order to evaluate the degree of maturity of the fertilizer. Prior to the estimation of the GI, an expression necessary for the estimation of the GI is obtained in advance as described below.

  First, a fertilizer similar to the fertilizer to be evaluated is separately prepared, an appropriate number is sampled from this similar fertilizer at an appropriate time interval, and extracted with water, for example, to prepare an extract.

  Here, the fertilizer similar to the fertilizer to be evaluated means a fertilizer manufactured using a raw material substantially similar to the raw material of the fertilizer to be evaluated. From the viewpoint of increasing the estimation accuracy of GI, it is preferable to use a raw material having the same composition as that of the fertilizer to be evaluated. However, due to the nature of the raw material (waste), it is difficult to accurately reproduce the raw material composition. Therefore, the raw material substantially similar to the raw material of the fertilizer to be evaluated may be, for example, a raw material having the same source as the raw material of the fertilizer to be evaluated. Specifically, the raw material substantially the same as the raw material of the fertilizer to be evaluated is, for example, the same species of livestock such as cow dung, pig dung, chicken dung, etc. when the fertilizer raw material to be evaluated is animal dung. . Furthermore, when the fertilizer raw material to be evaluated is raw garbage, it is preferable to match the raw material of the fertilizer to be evaluated with the presence or absence of fish meal.

  Further, from the viewpoint of further improving the estimation accuracy, it is preferable to use a fertilizer manufactured by a manufacturing method substantially similar to the fertilizer to be evaluated as a similar fertilizer. The fertilizer manufacturing method is also preferably the same as the fertilizer to be evaluated, but may be slightly different.

  Next, a normal germination test is performed using the prepared extract, and, for example, GI is obtained based on the formula (1).

  Here, as the physicochemical index of the fertilizer extract, various physicochemical indexes of conventionally known aqueous solutions can be mentioned, for example, pH, ammonium ion concentration, nitrate ion concentration, electrical conductivity, Examples thereof include temperature, redox potential, etc. Among them, it is desirable to employ pH and ammonium ion concentration as physicochemical indicators.

  As the enzyme activity, the activity of any conventionally known enzyme can be targeted, but it is preferable to employ the enzyme activity of an enzyme selected from the group of enzymes representing the activity of microorganisms. Examples of the enzyme activity representing the activity of the microorganism include protease activity, amylase activity, cellulase activity, alkaline phosphatase activity, acid phosphatase activity, phosphohydrase activity, esterase activity, esterase-lipase activity, lipase activity, leucine allylamidase activity, Valine allylamidase activity, cystine allylamidase activity, trypsin activity, chymotrypsin activity, α-galactosidase activity, β-galactosidase activity, β-glucuronidase activity, α-glucosidase activity, β-glucosidase activity, N-acetyl-β-glucosaminidase activity, Examples include α-mannosidase activity and α-fucosidase activity. As the enzyme activity, an optimal one may be appropriately selected from these according to the type of fertilizer, and it is preferable to select an acid phosphatase activity and an esterase activity, particularly when evaluating the quality of compost.

  Then, the relationship between the acquired GI and information such as a physicochemical index and enzyme activity is analyzed. Specifically, by performing multiple regression analysis on the relationship between the acquired GI and the corresponding information such as physicochemical index and enzyme activity, GI is the target variable, and the physicochemical index and enzyme activity are explanatory variables. The multiple regression equation is obtained. As parameters for the analysis, it is preferable to select a large number of parameters from the physicochemical indicators listed above and the enzyme activities listed above from the viewpoint of improving accuracy, but at least two of these parameters are selected. Just choose.

  In this invention, GI of the fertilizer of evaluation object is estimated as follows using the said multiple regression equation, and maturity is evaluated.

  First, the fertilizer to be evaluated is extracted using, for example, water to prepare an extract.

  Next, at least two types selected from measurement of physicochemical index and enzyme activity measurement are performed on the prepared extract, and at least two types selected from physicochemical index and enzyme activity of the extract Get information about. That is, information on parameters adopted in the multiple regression equation is acquired.

  Next, the GI of the fertilizer to be evaluated is obtained by applying at least two types of information selected from the physicochemical index and the enzyme activity of the extract of the fertilizer to be evaluated to the multiple regression equation obtained in advance. presume. Since the obtained estimated value of GI shows a good correlation with the measured value of GI, the maturity of the fertilizer is evaluated using this estimated GI as an index. For example, GI 50% is a criterion for determining whether or not the fertilizer is sufficiently matured. The reference value of GI may be determined as appropriate according to the type of fertilizer.

  In this way, these relationships are analyzed in advance using the physicochemical index, enzyme activity, etc. of the fertilizer extract, and corresponding information such as the physicochemical index, enzyme activity, etc. of the fertilizer to be evaluated is applied to the obtained formula. As a result, the GI can be estimated with high accuracy. In particular, by selecting the pH, ammonium ion concentration, and enzyme activity as parameters, GI can be estimated easily with high accuracy. In addition to the pH, ammonium ion concentration, and enzyme activity, the fertilizer extract may be used in combination with other physicochemical indicators, enzyme activity, etc. as described above as parameters for multiple regression analysis. If selected, the accuracy of GI estimation can be further improved.

  By the fertilizer quality evaluation method of the present invention as described above, the maturity of the fertilizer to be evaluated can be evaluated with high accuracy, and the quality of the fertilizer can be evaluated with high accuracy. In the present invention, the GI can be estimated on the basis of information that can be obtained by a simple operation with a short measurement time such as a physicochemical index and enzyme activity, and it is not necessary to perform a germination test for each evaluation. That is, the labor and time required for the measurement are drastically reduced, and the maturity of the fertilizer can be evaluated quickly and easily. Therefore, according to the present invention, it is possible to evaluate the quality of the fertilizer quickly, simply and with high accuracy at, for example, a composting site, and contribute to the supply of high-quality fertilizer. In addition, the present invention can be applied to quality evaluation of various types of fertilizers regardless of raw materials and manufacturing methods by appropriately changing the coefficient of the multiple regression equation.

  Next, the fertilizer quality evaluation program of the present invention will be described. The fertilizer quality evaluation program of the present invention is a program for controlling the operation of the computer and performing the fertilizer quality evaluation as described above, such as the pH and ammonium ion concentration of the fertilizer extract to be evaluated. Information acquisition input function to acquire at least two types of information selected from enzyme activities such as physicochemical index and enzyme activity representing the activity of microorganisms, and fertilizer germination index by applying the acquired information to a predetermined calculation formula This is a program for causing a computer to realize a control function to be estimated. With such a program, the germination index of the fertilizer can be automatically estimated by a computer, and the quality of the fertilizer can be grasped quickly, easily and with high accuracy.

  Next, the fertilizer quality evaluation apparatus of this invention is demonstrated. An example of the fertilizer quality evaluation apparatus of the present invention is shown in FIG. The fertilizer quality evaluation device 1 includes an information acquisition input unit 2 that obtains various information such as compost and other physicochemical indicators about fertilizer extracts and enzyme activity, a control unit 3, a program executed by the control unit 3, It basically includes a storage unit 4 that stores various data such as a multiple regression equation necessary for estimating the GI value. Moreover, the fertilizer quality evaluation apparatus 1 is comprised from a display etc., and is provided with the display part 5 which displays the information acquired by the information acquisition input part 2, the result calculated by the control part 3, etc.

  In the following, the information acquisition input unit 2 will be described by taking as an example a configuration capable of acquiring information about pH, ammonium ion concentration, acid phosphatase activity, and esterase activity, but the present invention is limited to these. However, it goes without saying that it is only necessary to obtain information on at least two of the physicochemical indicators and enzyme activities as described above.

  The information acquisition input unit 2 includes, for example, a pH measurement unit 2a that performs pH measurement on a fertilizer extract, an ammonium ion concentration measurement unit 2b that performs measurement of ammonium ion concentration, and a first enzyme activity measurement unit that performs measurement of acid phosphatase activity. 2c, a second enzyme activity measuring unit 2d for measuring esterase activity, and the like, and acquires information on pH, ammonium ion concentration, enzyme activity, etc. of the fertilizer extract. The pH measuring unit 2a, the ammonium ion concentration measuring unit 2b, the first enzyme activity measuring unit 2c, and the second enzyme activity measuring unit 2d are respectively known pH sensors, ammonium ion concentration sensors, enzyme activity sensors, and the like. Moreover, it may be comprised from test papers, such as pH test paper, for example. The configuration of the information acquisition input unit 2 is not limited to these as long as various types of information can be acquired. For example, each measurement unit may be externally attached to the fertilizer quality evaluation device 1. Moreover, the information acquisition part 2 may be comprised by input devices, such as a keyboard, for example. In this case, information on pH, ammonium ion concentration, acid phosphatase activity, esterase activity, etc. is measured separately using a test paper such as a pH test paper, and is input via the input device of the information acquisition unit 2. .

  The control part 3 and the memory | storage part 4 are comprised by computer apparatuses containing memory | storage devices, such as CPU and ROM, RAM, a magnetic disk, etc., for example, and control each part of the fertilizer quality evaluation apparatus 1. FIG. The control unit 3 reads out a program or a predetermined calculation formula stored in the storage unit 4 in advance as necessary, and pH, ammonium ion concentration, enzyme activity of the fertilizer extract obtained by the information acquisition input unit 2 Apply information about etc. and perform calculations. The calculation formula is, for example, a multiple regression equation with an actual measurement GI of an extract of a fertilizer similar to the fertilizer to be evaluated as an objective variable and at least two types selected from pH, ammonium ion concentration, and enzyme activity as explanatory variables. .

  A method of estimating the maturity by estimating the GI of the fertilizer using the fertilizer quality evaluation apparatus 1 having such a configuration will be described. In the following, an example in which the information acquisition unit 2 includes a pH sensor, an ammonium ion concentration sensor, and an enzyme activity sensor, and performs both various measurements and information acquisition of the pH, ammonium ion concentration and enzyme activity of the fertilizer extract. To

  First, the information acquisition input unit 2 is immersed in the fertilizer extract to be evaluated, for example, and various measurements are performed in the information acquisition input unit 2 to select at least two types selected from pH, ammonium ion concentration, acid phosphatase activity, and esterase activity. Get information about. The acquired information is converted into an electric signal or the like and sent to the control unit 3 or the storage unit 4.

  Next, the control part 3 calculates | requires the estimation GI of the fertilizer of evaluation object by reading the multiple regression equation etc. which were memorize | stored beforehand in the memory | storage part 4, and performing calculation by applying the said information. The estimated GI calculated by the control unit 3 and the maturity evaluation based on the estimated GI are displayed, for example, on the display unit 5 or the like.

  As described above, according to the fertilizer quality evaluation apparatus 1, the GI can be estimated without performing a germination test, and the quality such as the fertilizer maturity can be evaluated quickly and accurately with a simple operation. Moreover, the fertilizer quality evaluation apparatus 1 has the advantage that it is small compared with the growth tool etc. which are used for the germination test at the time of calculating | requiring GI. Furthermore, since the fertilizer quality evaluation apparatus 1 is easier to maintain and the like than a growing instrument used for a germination test, it is possible to evaluate the quality of the fertilizer at a low cost.

  Examples of the present invention will be described below based on experimental results.

<Composting and sampling>
In this experiment, compost was made using pruned branches of park trees and roadside trees from Kaga City, Ishikawa Prefecture, and school meal residues as raw materials. School lunches were collected from junior high schools in the city. The pruned branches and rice husks made into chips in these school meal residues are added so that the water content is about 65%, and further commercially available fermentation-promoting microorganisms (A: Uron C or B: Uchijou) are mixed. Mechanically stirred at 65 ° C. for hours. The mixture was then processed in two ways. One is piled up in the yard and stirred twice a week (deposition method). The other is a method using a reactor manufactured by Mizushima Bussan Co., Ltd. (reactor method). The reactor is naturally supplied with oxygen from the side mesh. Sampling was performed from 3 locations within the same treatment group each week. At that time, the product temperature was also measured. The composting test was conducted from October to March in the city. The average daily temperature in the city during the test period was 1.6 ° C to 11.7 ° C. Table 1 shows various manufacturing methods and raw material components.

<Physicochemical analysis>
The water content was calculated from the decrease after compost was heated at 105 ° C. for 5 hours. The total carbon and total nitrogen amounts were measured by an automatic elemental analyzer (trade name Vario EL III), and the C / N ratio was calculated therefrom.

  The water extract of compost was prepared by adding 10 times the amount of distilled water per dry weight to compost, stirring at 120 rpm for 30 minutes, and then filtering. The pH and electrical conductivity of the extract were immediately measured. The extract was stored at -20 ° C. The ammonium ion concentration and nitrate ion concentration of the extract were measured by a colorimetric method.

<Enzyme activity: Agar plate assay>
Protease, amylase and cellulase activities in the water extract were detected according to the following method.
(1) Protease: 2 g of agar and 0.1 g of sodium azide are dissolved in 0.1 M phosphate buffer (pH 7.0) by heating, and 1 mL of 1 M calcium chloride and 10 mL of 1% casein are added thereto. It was. 15 mL of these mixtures were put into a plastic petri dish having a diameter of 9 cm and cooled.
(2) Amylase: 0.8 g of soluble starch and 2 g of agar were dissolved in 100 mL of 1.0 M acetate buffer (pH 5.0) by heating. It was put into a petri dish and cooled as described above.
(3) Cellulase: 0.8 g of carboxymethyl cellulose and 2 g of agar were dissolved in 100 mL of 1.0 M acetate buffer (pH 5.0). It was put into a petri dish and cooled as described above.

  A hole with a diameter of 3 mm was made in each agar plate of (1) to (3) with a cork borer, and 10 μL of a compost water extract was dropped into the hole and incubated at 55 ° C. for 18 hours. After incubation, protease activity could be confirmed by observing a clear halo around the sample hole. The amylase activity was visualized by adding 0.2% potassium iodide and 0.02% iodine solution, and the cellulase activity was visualized by adding 0.1% Congo red solution followed by washing, and halo around the sample hole. The diameter of each halo was measured by grazing.

<Enzyme activity: Apizza Im assay>
Nineteen kinds of enzyme activities of the compost water extract were measured using a trade name Apizza Im which is an assay kit. The measured enzymes were alkaline phosphatase, acid phosphatase, phosphohydrase, esterase, esterase-lipase, lipase, leucine allylamidase, valine allylamidase, cystine allylamidase, trypsin, chymotrypsin, α-galactosidase, β-galactosidase, β-glucuronidase , Α-glucosidase, β-glucosidase, N-acetyl-β-glucosaminidase, α-mannosidase and α-fucosidase.
For enzyme activity, 60 μL of a reagent was placed in a well coated with a chromogenic substrate specific for each enzyme, incubated at 36 ° C. for 4 hours, and then the reaction was stopped with reagents A and B to cause color development. The enzyme activity was judged by visual comparison of the color density with the attached color chart.

<Komatsuna germination test>
10 mL of the water extract immediately after extraction was put in a plastic petri dish with filter paper, 30 seeds of Komatsuna were seeded, and incubated in a dark place at 26 ° C. for 48 hours. Thereafter, the number of germinated seeds and the root length were measured. As a control, the same operation was performed using 10 mL of distilled water. The GI was calculated according to the equation (1) proposed by Zucconi et al. (1981). About 50% of GI is a measure for the presence or absence of growth inhibition of the compost. In this experiment, the extract was prepared from compost immediately after sampling, and the extract immediately after extraction was used for the germination test. . The change in GI in the deposition method is shown in FIG. 2, and the change in GI in the reactor method is shown in FIG.

<Statistical analysis>
The relationship between GI and other parameters (water content, temperature, pH, electrical conductivity, ammonium ion concentration, nitrate ion concentration, carbon and nitrogen content, C / N ratio, 22 enzyme activities) This was performed by linear multiple regression analysis by a stepwise method using a stat view. The correlation between each parameter was also analyzed using the same software.

GI (actual value) obtained by the Komatsuna germination test and the corresponding moisture content, temperature, pH, electrical conductivity, ammonium ion concentration, nitrate ion concentration, carbon content, nitrogen content, C / N ratio, The relationship with the activity of 22 types of enzymes was analyzed using stepwise linear multiple regression analysis. The number of samples was 159 for all composting systems. Table 2 shows the parameters selected in the multiple regression analysis and their characteristics. The coefficient of determination R ² in the multiple regression model is 0.896, the GI estimated from these parameters were found to be in good agreement with the measured values.

In order to obtain a simpler model, four parameters having a high F value, namely, pH, ammonium ion concentration, acid phosphatase activity and esterase activity were selected from Table 2 and a multiple regression analysis was performed. As a result, the following formula (2) was obtained. In formula (2), “NH ₄ ⁺ ” represents the ammonium ion concentration (mg / l). “AP” represents acid phosphatase activity, and “E” represents esterase activity.

GI = −60.239 + 19.057pH−0.238 [NH ₄ ⁺ ] −5.381AP−5.117E Formula (2)

The coefficient of determination ^{R 2} in the multiple regression model was 0.791. In each composting system, the correlation between the GI estimated from these parameters and the actual GI is shown in FIGS. Pearson's correlation coefficients (r) in deposition method A, deposition method B, reactor method A, and reactor method B were 0.96, 0.93, 0.84, and 0.89, respectively. The slope of the regression equation was about 1 in the deposition method, but both A and B were smaller in the reactor method than in the deposition method. When estimating the GI, it may be more effective to perform analysis for each composting method.

  It should be noted that the four parameters selected this time (pH, ammonium ion concentration, acid phosphatase activity, esterase activity) are not substantially correlated with GI alone (r is 0.369, 0.019, −0. 047, 0.321). For this reason, GI cannot be estimated from these parameters themselves. However, GI can be estimated by combining these, and the multiple regression analysis was effective in selecting the parameters at that time.

  As is clear from FIGS. 4 to 7, the estimated GI showed a good correlation with the actual GI. Therefore, a multiple regression analysis is performed on the GI and the corresponding physicochemical index and enzyme activity from the above experiment, for example, a multiple regression equation such as equation (2) is obtained. It can be seen that the fertilizer GI can be estimated with high accuracy by applying the fertilizer data. Moreover, in the fertilizer used in this experiment, the pH, ammonium ion concentration, acid phosphatase activity, and esterase activity were selected as parameters, so that high-precision estimation of GI was realized with a simple model.

It is a schematic diagram which shows an example of the fertilizer quality evaluation apparatus of this invention. It is a characteristic view which shows a time-dependent change of GI of the fertilizer produced by the deposition method. It is a characteristic view which shows a time-dependent change of GI of the compost produced by the reactor method. It is a characteristic view which shows the relationship between the actual GI and the estimated GI in the deposition method A. FIG. 6 is a characteristic diagram showing a relationship between an actual GI and an estimated GI in the deposition method B. It is a characteristic view which shows the relationship between the actual GI and the estimated GI in the reactor method A. It is a characteristic view which shows the relationship between the actual GI and the estimated GI in the reactor method B.

Explanation of symbols

  1 fertilizer quality evaluation device, 2 information acquisition input unit, 3 control unit, 4 storage unit, 5 display unit

Claims (18)

  Obtaining at least two types of information selected from the physicochemical index and enzyme activity of the fertilizer extract to be evaluated, and applying the information to a predetermined calculation formula to estimate the germination index of the fertilizer And fertilizer quality evaluation method.   Multiple regression obtained by performing the multiple regression analysis on the germination index for the fertilizer similar to the fertilizer to be evaluated and at least two types of information selected from the physicochemical index and the enzyme activity. The fertilizer quality evaluation method according to claim 1, which is an equation.   The physicochemical index is at least one selected from the group consisting of pH, ammonium ion concentration, nitrate ion concentration, electrical conductivity, temperature, and oxidation-reduction potential. Fertilizer quality evaluation method.   The fertilizer quality evaluation method according to claim 3, wherein the physicochemical index is pH and ammonium ion concentration.   The fertilizer quality evaluation method according to any one of claims 1 to 4, wherein the enzyme activity is an enzyme activity representing the activity of a microorganism.   The enzyme activity representing the activity of the microorganism is protease activity, amylase activity, cellulase activity, alkaline phosphatase activity, acid phosphatase activity, phosphohydrase activity, esterase activity, esterase-lipase activity, lipase activity, leucine allylamidase activity, valine. Allylamidase activity, cystine allylamidase activity, trypsin activity, chymotrypsin activity, α-galactosidase activity, β-galactosidase activity, β-glucuronidase activity, α-glucosidase activity, β-glucosidase activity, N-acetyl-β-glucosaminidase activity, α 6. The method for evaluating fertilizer quality according to claim 5, wherein the fertilizer quality is at least one selected from the group consisting of mannosidase activity and α-fucosidase activity. An information acquisition unit for acquiring at least two types of information selected from the physicochemical index of the fertilizer extract to be evaluated and the enzyme activity;
A fertilizer quality evaluation apparatus comprising: a controller that applies the information to a predetermined calculation formula to estimate a germination index of the fertilizer.   Multiple regression obtained by performing the multiple regression analysis on the germination index for the fertilizer similar to the fertilizer to be evaluated and at least two types of information selected from the physicochemical index and the enzyme activity. The fertilizer quality evaluation apparatus according to claim 7, wherein the fertilizer quality evaluation apparatus is an equation.   9. The physicochemical index is at least one selected from the group consisting of pH, ammonium ion concentration, nitrate ion concentration, electrical conductivity, temperature, and oxidation-reduction potential. Fertilizer quality evaluation device.   The fertilizer quality evaluation apparatus according to claim 9, wherein the physicochemical index is pH and ammonium ion concentration.   The fertilizer quality evaluation apparatus according to any one of claims 7 to 10, wherein the enzyme activity is an enzyme activity representing the activity of a microorganism.   The enzyme activity representing the activity of the microorganism is protease activity, amylase activity, cellulase activity, alkaline phosphatase activity, acid phosphatase activity, phosphohydrase activity, esterase activity, esterase-lipase activity, lipase activity, leucine allylamidase activity, valine. Allylamidase activity, cystine allylamidase activity, trypsin activity, chymotrypsin activity, α-galactosidase activity, β-galactosidase activity, β-glucuronidase activity, α-glucosidase activity, β-glucosidase activity, N-acetyl-β-glucosaminidase activity, α 12. The fertilizer quality evaluation device according to claim 11, wherein the fertilizer quality evaluation device is at least one selected from the group consisting of mannosidase activity and α-fucosidase activity. Information acquisition and input function for acquiring at least two types of information selected from the physicochemical index of the fertilizer extract to be evaluated and enzyme activity;
A fertilizer quality evaluation program that causes a computer to realize a control function for estimating the germination index of the fertilizer by applying the information to a predetermined calculation formula.   Multiple regression obtained by performing the multiple regression analysis on the germination index for the fertilizer similar to the fertilizer to be evaluated and at least two types of information selected from the physicochemical index and the enzyme activity. 14. The fertilizer quality evaluation program according to claim 13, which is an equation.   15. The physicochemical index is at least one selected from the group consisting of pH, ammonium ion concentration, nitrate ion concentration, electrical conductivity, temperature, and oxidation-reduction potential. Fertilizer quality evaluation program.   The fertilizer quality evaluation program according to claim 15, wherein the physicochemical index is pH and ammonium ion concentration.   The fertilizer quality evaluation program according to any one of claims 13 to 16, wherein the enzyme activity is an enzyme activity representing the activity of a microorganism.   The enzyme activity representing the activity of the microorganism is protease activity, amylase activity, cellulase activity, alkaline phosphatase activity, acid phosphatase activity, phosphohydrase activity, esterase activity, esterase-lipase activity, lipase activity, leucine allylamidase activity, valine. Allylamidase activity, cystine allylamidase activity, trypsin activity, chymotrypsin activity, α-galactosidase activity, β-galactosidase activity, β-glucuronidase activity, α-glucosidase activity, β-glucosidase activity, N-acetyl-β-glucosaminidase activity, α The fertilizer quality evaluation program according to claim 17, wherein the program is at least one selected from the group consisting of mannosidase activity and α-fucosidase activity.

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