JP6557100B2 - Plant diagnosis method and apparatus - Google Patents

Description

The present invention relates to a diagnostic method and diagnostic equipment of the plant.

Examples of control factors for cultivating plants in the entire agriculture including a plant factory include external factors such as weather, air temperature, humidity, wind power, wind direction, illuminance, light intensity, and CO ₂ concentration.
Moreover, there exist environmental control, a speaking plant approach (Speaking Plant Approach; SPA (for example, refer nonpatent literature 1)) etc. as a method of controlling cultivation of a plant in the whole agriculture including a plant factory.

Environmental control when cultivating plants is to adjust the pH of the soil and water, the environmental temperature, etc. to the optimal range as appropriate according to the plant to be cultivated, as has been widely done conventionally. Say.
SPA, on the other hand, is one of the technical ideas for performing cultivation management using information obtained from the plant to be cultivated as a control factor, and harvests corresponding to changes in weather conditions and plant growth state in plant cultivation. In order to maintain and increase the quantity, it refers to the technical idea of appropriately performing growth diagnosis and cultivation management (environmental control, etc.) by capturing changes in plants. In addition, it is mentioned that the cultivation management based on huge external factor variation factor data is becoming possible from the operation of big data in recent years as a background that SPA has become possible.

  SPA obtains data about the condition and growth of a plant to be monitored directly as a measurement target, and corrects the cultivation condition to a more optimal one by performing environmental control based on the data. As a result, it has become possible to optimize cultivation conditions by obtaining information directly from a plant, which has been conventionally controlled by humans based on experience and knowledge. As a technique for implementing SPA, for example, attaching a small temperature sensor to a plant, measuring the moisture state by wrapping the sensor on a stem, or attaching a small assimilation box (photosynthesis measuring device) to the leaf, and examining photosynthesis Have been proposed. In particular, non-destructive image measurement has recently made it possible to understand plant temperature, moisture status, elongation (hypertrophy) rate, photosynthetic activity (chlorophyll fluorescence), etc., and a system to optimize external factors based on these Development is underway.

  In recent years, the development of biometric technology used in SPA has made it possible to use a variety of information about the environment and plants, and various operations such as air conditioning, irrigation, fertilization, leaf cutting, and pruning are performed according to the state of the plant. It has been tried. However, various physicochemical and plant physiological phenomena occur inside and outside the plant under complex interrelationships, and the measurement data obtained by measurement is reduced to cultivation management and environmental control. In order to reflect this in harvesting, it is necessary to clarify the direct causal relationship between individual environmental factors and plant life science phenomena. However, the academic research is still in progress, and it is not always clear as to what kind of information in the environment-plant system is used and how the cultivation conditions are modified and what effect is found in production. It is not just the scene where the answer was obtained, the practice is halfway, and further development is desired in the future.

Recently, a speaking cell approach (SCA), which further develops the idea of SPA, has been proposed (for example, see Non-Patent Document 2).
SCA refers to a technical idea that appropriately performs growth diagnosis and cultivation management (environmental control, etc.) based on biological information at the cell level (or gene expression) of a plant in the same technical idea as described above.

  SCA measures plant cells by utilizing Matrix Assisted Laser Desorption / Ionization-Time of Flight Mass Spectrometry (MALDI-TOFMS). Is used for plant cultivation management. Therefore, SCA can rapidly reflect biological information in environmental control, and is expected to more directly specify the interrelationship between environmental factors and life phenomena in the plant body. For these reasons, research on SCA has been actively conducted recently. In SCA, a technique is also being developed in which a minute device is attached to a plant, a minute amount of cell contents is collected, and molecular analysis is immediately performed. According to such a technique, it is possible to sequentially grasp gene expression and protein synthesis that occur when there is a change in an external factor for a plant. That is, changes in cells can be observed sequentially, and it can be quickly detected that a plant is reacting in some way.

“News Letter”, [online], February 2010, Agricultural Administration Office, Shikoku, China, [Search May 20, 2014], Internet <URL: http://www.maff.go.jp/chushi /kohoshi/mag#newsletter/pdf/1002-38newsletter.pdf> Hiroshi Nonami, “Botany and“ Bio-environmental regulation ”“ Approach to biological-oriented engineering ”” [online], September 1, 2012, Japan Society for Bio-Environmental Engineering, [Search May 20, 2014], Internet <URL: https://www.jstage.jst.go.jp/article/shita/24/3/24#150/#pdf>

  However, as described above, the SPA attempts by the measuring means described in Non-Patent Document 1 are based on diagnosis and cultivation management based on the body temperature, water state, elongation (hypertrophy) speed, photosynthetic activity (chlorophyll fluorescence), etc. Although research to conduct is being carried out, it is not suitable for a bird's-eye evaluation of the state of the entire cultivation area because the biological measurement information of the plant individual is based on the collected data.

  In addition, the SCA described in Non-Patent Document 2 can sequentially grasp information on gene expression and metabolism, and is expected to be logically applied than SPA. However, the methodology using a fine sampling system and an advanced mass spectrometer in SCA is performed in the laboratory as an academic research, and when producing plants, on-site measurement by non-destructive and non-contact, that is, In addition, it is difficult to perform on-site measurement at present, and as described above, it is not suitable for a bird's-eye evaluation of the state of the entire cultivation area.

The present invention has been made in view of the above-mentioned problems, and can comprehensively evaluate the state of the entire cultivation area based on the volatile substances in the cultivation area, and can be accurately diagnosed by biological information based on the volatile substances. can be derived cultivation management and shall be the challenge is to provide a diagnostic method and diagnostic apparatus for a plant that can be performed on-site measurement by nondestructive and non-contact in producing plants.

Diagnostic methods and diagnostic equipment of the plant according to the present invention which has solved the above problems has the following means.

The method for diagnosing a plant according to the present invention includes a concentration of a volatile substance emitted from the plant, a type of the volatile substance, and the volatile substance in an area where one or more plants to be examined are grown. Monitoring at least one of the mixing ratio of the compound contained in the area and the location information of the volatile substance in the area, diagnosing the state of the plant in the area, and the monitoring in the area Based on the detection step of detecting one or more volatile substances in the area by a sensor provided in a non-destructive and non-contact manner on the plant, and based on the volatile substance detected in the detection step, Based on the encoding step of encoding molecular information related to the volatile substance and transmitting it to the measurement control device, and the molecular information encoded in the encoding step, the measurement Is set to the control device comprises a, an identification map creating step of creating an identification map for identifying a type of the volatile substance.

Further, the plant diagnostic apparatus according to the present invention includes a concentration of a volatile substance emitted from the plant, a type of the volatile substance, and the volatilization in an area where one or more plants to be examined are grown. Monitoring means for monitoring at least one of the mixing ratio of the compound contained as the active substance and the positional information of the volatile substance in the area, and the area based on the information monitored by the monitoring means possess a diagnostic means for diagnosing the condition of the plants of the inner, and the monitoring means, the sensor provided in a non-destructive and non-contact with the plant in the zone, one or more volatile substances in the zone Based on the volatile substance detected by the detecting means and the detecting means, the sensor codes molecular information related to the volatile substance. And an identification unit for creating an identification map for identifying the type of the volatile substance based on the molecular information encoded by the encoding unit and the encoding unit to be transmitted to the measurement control unit. and map creation means, a is a chromatic Rukoto.

  As described above, the plant diagnosis method and diagnosis apparatus according to the present invention monitor the concentration of volatile substances emitted from plants, and therefore can diagnose the state of plants.

  The plant diagnosis method and diagnosis apparatus according to the present invention diagnoses the state of a plant by monitoring the concentration of a volatile substance emitted from the plant. Therefore, according to the plant diagnosis method and diagnosis apparatus according to the present invention, the state of the entire cultivation area can be comprehensively evaluated based on the volatile substances in the cultivation area, and more accurately based on the biological information based on the volatile substances. Diagnosis and cultivation management can be derived, and non-destructive and non-contact on-site measurement can be performed when producing plants.

It is a schematic perspective view explaining 1st Embodiment of the diagnostic apparatus of the plant which concerns on this invention. It is explanatory drawing explaining the concept which encodes the molecular information regarding a volatile substance based on the detected volatile substance. It is explanatory drawing which shows an example of the identification map (cluster map) for identifying the kind of volatile substance. The horizontal axis represents the molecular size (unit: Å), and the vertical axis represents the polarity. It is a graph which shows the daily fluctuation | variation of a peryl compound response value. In FIG. 4, the horizontal axis represents the number of days elapsed (days), and the vertical axis represents the peryl compound response value (average value) (unit: arbitrary unit (au)). It is a graph which shows the daily fluctuation | variation of a total VOC equivalent value. In FIG. 5, the horizontal axis represents the number of days elapsed (day), and the vertical axis represents the peryl compound response value (average value) (unit: arbitrary unit (au)).

  DETAILED DESCRIPTION OF EMBODIMENTS Hereinafter, a plant diagnosis method and diagnosis apparatus, and a pest determination method and determination apparatus (embodiment) according to the present invention will be described in detail with reference to the drawings as appropriate.

[First Embodiment of Plant Diagnosis Device]
For convenience of explanation, first, a first embodiment of a plant diagnostic apparatus according to the present invention will be described with reference to FIG.
As shown in FIG. 1, the plant diagnosis apparatus 1 according to the first embodiment of the present invention is volatile emitted from a plant 2 in an area 3 where one or more plants 2 to be examined are grown. Monitor at least one of the concentration of the substance, the type of volatile substance, the mixing ratio of the compounds contained as volatile substances and the positional information of the volatile substance in the area 3, and the plant 2 in the area 3 It is to diagnose the state of.

Here, the monitoring described above is performed by monitoring means (not shown), and the diagnosis described above is performed by diagnostic means (not shown). That is, the diagnostic device 1 has a monitoring unit and a diagnostic unit.
The monitoring means is, for example, a detection means such as the sensor 4 for detecting the information described above, a coding means for encoding the molecular information of the volatile substance detected by the detection means, and the sensor 4 based on the molecular information. And an identification map creating means for creating an identification map for identifying the information (type of volatile substance).
The identification map creating means reads a predetermined program stored in a storage medium such as a hard disk drive (HDD, not shown) by a central processing unit (CPU) provided in the measurement control device 5 (computer). It is realized by operating (calculating) to perform a predetermined function according to the program.
Similarly to the identification map creating means, the diagnosis means also operates such that a CPU provided in the measurement control device 5 reads a predetermined program stored in a storage medium such as an HDD and performs a predetermined function according to the program (calculation processing). ).
Specific modes of the monitoring means (detection means, coding means, identification map creation means) and diagnosis means will be described later.

  The plant 2 in the present specification may be any organism that performs photosynthesis, and may be a multicellular organism or a unicellular organism. Examples of plants in the present specification include vegetables, grains, fruits, and algae.

  Examples of vegetables include perilla, strawberry, watermelon, melon, radish, carrot, burdock, potato, sweet potato, onion, asparagus, cabbage, lettuce, spinach, Chinese cabbage, tomato, eggplant, pumpkin, bell pepper, cucumber, ginger, cauliflower , Broccoli, edible chrysanthemum, ginger, turmeric.

  Examples of cereals include corn, rice, wheat, barley, oat, rye, millet, millet, millet, sorghum (periwinkle, sorghum, sorghum), soybean, azuki bean, mung bean, kidney bean, peanut, pea, broad bean, lentil, chickpea. , Buckwheat and tartary buckwheat.

  Examples of fruits include orange, grapefruit, yuzu, daidai, kabosu, sudachi, shikuwasa, lemon, lime, citron, natsumikan, hassaku, hyuga natsu, bellows, sweetie, yeokan, mandarin orange, unshu mikan, ponkan, mandarin orange, kumquat , Karin, Chugoku pear, Pear, Atlantic quince, Apple, American cherry, apricot, ume, cherry, plum, peach, almond, ginkgo, chestnut, walnut, pecan, akebi, fig, oyster, cassis, kistrawberry, kiwi, gummy, Mulberry, cranberry, cowberry, pomegranate, currant, jujube, lotus cup, bilberry, grape, blackberry, blueberry, raspberry, olive, loquat, bayberry and the like.

  Examples of algae include seaweeds such as green algae, red algae, and blue-green algae, cyanobacteria, and Euglena.

The above-mentioned cultivation of land plants such as vegetables, grains, and fruits can be performed using soil, hydroponics, solid medium, or the like, as is generally done.
The algae can be grown by putting a liquid medium and algae having a predetermined composition (a composition suitable for the algae to be grown) into a predetermined container. In addition, what is necessary is just to refer suitably for the various literature, the paper, etc. regarding the algae to grow for the composition suitable for the algae to grow.
And the area 3 in the present invention refers to a predetermined area or volume where one or more plants are grown. The area 3 can be set according to the ability of the sensor 4 that monitors volatile substances emitted from plants to detect the volatile substances. That is, when the ability of the sensor 4 to detect a volatile substance can cover only one growing plant 2, the section where the one plant 2 is growing is the above-described area 3 (in this case). 1 corresponds to the area 31 shown in FIG. In addition, when the ability of the sensor 4 to detect volatile substances can cover two or more plants 2 that are growing, the section where the two or more plants 2 are growing is the area described above. 3 (in this case, the area 32 shown in FIG. 1 corresponds). Further, one area 3 may be monitored by a plurality of sensors 4, or a plurality of areas 3 may be monitored by a plurality of sensors. That is, the areas 31 and 31 shown in FIG. 1 may overlap each other to monitor one or more plants 2. As shown in FIG. 1, the sensor 4 is preferably provided above the plant 2 to be examined, and is connected to the measurement control device 5 by wire or wirelessly.

  The volatile substance is preferably at least one of metabolic intermediates, metabolites, and metabolite degradation products, but is not limited thereto, for example, volatile plant hormones, optionally It includes a small number of identified chemical chemicals. Examples of the small number of marker-like chemical substances specified arbitrarily include jasmonic acid, methyl salicylate, allyl isothiocyanate, camphor, and cineol. By detecting these substances as volatile substances, the state of the plant can be diagnosed.

  Specific examples of such volatile substances include quinazoline alkaloid, acridine alkaloid, quinoline alkaloid, simple alkaloid synthesized through the shikimate pathway, Via various alkaloids such as simple β-carboline, terpenoid indole, quinolone alkaloid, quinoline alkaloid, pyrroloindole alkaloid, and aspartic acid Zetian synthesis system, terpenoid synthesis system, diterpenoid synthesis system via various alkaloids such as piperidine, quinolidine, indolizine, mevalonate pathway, non-mevalonate pathway (MEP / DOPX pathway) and malonyl CoA Carotenoid synthesis system, ubiquinone synthesis system, terpenoid-quinone synthesis system, monoterpene synthesis system, steroid synthesis system, sesquil terpene and triterpene synthesis system materials, etc. Some include plant hormones and their degradation products. Among these, examples of the monoterpene synthesis material include peryl compounds (perillyl compounds, perilla compounds). Examples of the peryl compound include peryl aldehyde, peryl alcohol, perilla ketone, perillyl acetate, and perillartin.

FIG. 2 is an explanatory diagram for explaining the concept of encoding molecular information related to a volatile substance based on the volatile substance detected by the sensor 4. The diagnosis of the state of the plant 2 will be described with reference to FIG.
As shown in FIG. 2, the plant 2 volatilizes the volatile substances a and b at a stage (hereinafter referred to as the initial stage) where there is little change with time in the growth immediately after sprouting. The volatile substances a, b, and c are volatilized at a stage where the environmental change has progressed to some extent (hereinafter referred to as the middle period), and the stage over which the temporal change with growth has further progressed (hereinafter referred to as the harvest period). If so, the volatile substances b, c and d are volatilized.

  On the other hand, the sensor 4 detects the volatile substances a, b, c, and d, and detects the volatile substances a, b, c, and d. , B, C, and D, encoding means (not shown) for encoding, and the encoded molecular information can be transmitted to the measurement control device 5. In other words, the plant diagnostic apparatus 1 includes such a sensor 4 so that the concentration of the volatile substance, the type of the volatile substance, the mixing ratio of the compound contained as the volatile substance, and the area 3 The position information of volatile substances can be grasped. Note that the mixing ratio of the compounds contained as volatile substances is determined by the measurement control device 5 quantifying the content of each compound based on the number of times the molecular information transmitted from the sensor 4 is received. Can be obtained. That is, if the concentration of the compound is high, the number of receptions of molecular information increases and the numerical value also increases. On the other hand, if the concentration of the compound is low, the number of times of receiving molecular information decreases, and the numerical value also decreases. Therefore, if these numerical values are compared, the mixing ratio of each compound contained as a volatile substance can be determined. In addition, the positional information of the volatile substance is, for example, stored in the sensor 4 that has detected the volatile substance in advance, the positional information (for example, information regarding the installation position of the sensor 4 in the breeding facility), and encoded molecular information. At the same time, by transmitting the position information to the measurement control device 5, the measurement control device 5 can grasp the position information. Therefore, by using the sensor 4, the state of the entire cultivation area can be comprehensively evaluated based on the volatile substances in the cultivation area.

  The sensor 4 has, for example, a molecular recognition filter using a molecular template polymer, and specifically targets a target molecule (that is, a target volatile substance such as perylaldehyde) from one or more volatile substances. In other words, only the target molecule can be selectively detected for selective capture or passage. The molecular template polymer is a polymer obtained by synthesizing a polymer using a target molecule as a template and then removing the target molecule, and can selectively detect the target molecule.

  The molecular information is stored in advance in a storage device provided in the sensor 4, for example. When the sensor 4 detects one or more target molecules from the volatile substance, the sensor 4 reads the molecular information of the target molecule from the storage device, and the codes A, B, C, and D are read as described above. Thus, the data is encoded and transmitted to the measurement control device 5. Examples of the molecular information include the molecular size and polarity of the target volatile substance.

The measurement control device 5 has an identification map creating means (not shown) for creating an identification map for identifying the type of the volatile substance detected by the sensor 4 based on the received molecular information.
As an identification map, for example, an identification map (cluster) that can classify volatile substances a, b, c, and d into clusters cA, cB, cC, cD and the like according to molecular size and polarity as shown in FIG. Map), but is not limited to this. The identification map may be a table. In addition, the parameters of the identification map are not limited to the above-described molecular size and polarity. For example, molecular shape, pKa (acid dissociation constant), hydrophobicity / hydrophilicity, polar functional group, and the like can be used.

Returning to FIG. 2, the description will be continued.
As described above, since the plant 2 emits the volatile substances a and b at the initial stage, the sensor 4 that detects them emits the volatile substances a and b based on the volatile substances a and b. Encode molecular information. In coding, as shown in FIG. 2, the sensor 4 detects volatile substances a and b, so that code A is coded OK (◯), code B is coded OK (◯), and code C. Is processed as coded NG (x), and code D is processed as coded NG (x).

  The sensor 4 transmits the codes A and B of the volatile substances a and b that are coded OK (◯) to the measurement control device 5. At this time, in the case of codes A and B, the sensor 4 can also include information that the growth state of the plant 2 is in the initial stage in the encoded molecular information.

  For example, the measurement control device 5 maps the clusters cA and cB in the identification map (cluster map) shown in FIG. 3 based on the molecular information (that is, the molecular size and polarity) of the volatile substances a and b. If it does in this way, the kind of volatile substance detected with sensor 4, the mixture ratio of the compound contained as volatile substance, etc. can be grasped. The concentration of the volatile substance can be grasped based on the number of times detected by the sensor 4 and the strength of the electric signal. If the result mapped to the identification map is seen, it can be diagnosed whether the plant 2 is in a preferable state or an unfavorable state. In other words, if the plant 2 is in a preferable state, it can be evaluated that the cultivation space by the identification map (cluster map) is good, and if the plant 2 is not preferable, the identification map (cluster map). It can be evaluated that the cultivation space by is not good. At this time, if there is information that it is an initial stage, the state of the plant 2 can be diagnosed more accurately by taking the growth stage into consideration.

  In addition, the diagnosis that it is an unfavorable state corresponds to a case where the plant 2 is originally a combination of volatile substances not emitted by the plant 2 or a case where the mixing ratio of the volatile substances is different from a desirable state. Originally, as a combination of volatile substances not emitted by the plant 2, for example, when volatile substances a and c are detected or when volatile substances c and d are detected, volatile substances that are not originally detected are detected. And so on.

  In addition, since the plant 2 emits volatile substances a, b, and c at the middle stage, the sensor 4 that detects them emits volatile substances a, b, based on the volatile substances a, b, c. , C to encode molecular information. In encoding, as shown in FIG. 2, since the sensor 4 detects volatile substances a, b, and c, code A is coded OK (◯), code B is coded OK (◯), Code C is processed as coded OK (◯), and code D is processed as coded NG (×).

  The sensor 4 transmits the codes A, B, and C of the volatile substances a, b, and c that are coded OK (◯) to the measurement control device 5. At this time, in the case of codes A, B, and C, the sensor 4 can also include information that the growth status of the plant 2 is in the middle stage in the encoded molecular information.

  For example, the measurement control device 5 maps the clusters cA, cB, and cC in the identification map (cluster map) shown in FIG. 3 based on the molecular information (that is, the molecular size and polarity) of the volatile substances a, b, and c. To do. If it does in this way, the kind of volatile substance detected with sensor 4, the mixture ratio of the compound contained as volatile substance, etc. can be grasped. Moreover, if the result mapped to the identification map is seen, it can be diagnosed whether the plant 2 is in a preferable state or an unfavorable state. At this time, if there is information that it is in the middle stage, the state of the plant 2 can be diagnosed more accurately in consideration of the growth stage.

  Furthermore, since the plant 2 emits volatile substances b, c, d at the stage of the harvesting period, the sensor 4 that detects them emits the volatile substances b, c, d based on the volatile substances b, c, d. Encode molecular information about c and d. In encoding, as shown in FIG. 2, since the sensor 4 detects volatile substances b, c, and d, the code A is encoded NG (×), the code B is encoded OK (◯), The code C is processed as coded OK (◯), and the code D is processed as coded OK (◯).

  The sensor 4 transmits the codes B, C, and D of the volatile substances b, c, and d that are coded OK (◯) to the measurement control device 5. At this time, in the case of codes B, C, and D, the sensor 4 can include information indicating that the growth status of the plant 2 is at the harvesting stage in the encoded molecular information.

  For example, the measurement control device 5 maps the clusters cB, cC, and cD in the identification map (cluster map) shown in FIG. 3 based on the molecular information (that is, the molecular size and polarity) of the volatile substances b, c, and d. To do. If it does in this way, the kind of volatile substance detected with sensor 4, the mixture ratio of the compound contained as volatile substance, etc. can be grasped. Moreover, if the result mapped to the identification map is seen, it can be diagnosed whether the plant 2 is in a preferable state or an unfavorable state. At this time, if there is information that it is the stage of the harvesting period, the state of the plant 2 can be diagnosed more accurately in consideration of the growth stage.

  As described above, the plant diagnostic apparatus 1 according to the present embodiment has a diagnostic means. The diagnostic means includes, for example, the concentration of the volatile substance detected by the sensor 4, the type of the volatile substance identified based on the identification map, the mixing ratio of the compound contained as the volatile substance, and the area 3 The state of the plant 2 in the area 3 is diagnosed using at least one piece of information on the position of the volatile substance in the inside. If it does in this way, the state of the plant 2 detected with the sensor 4 of the specific position can be diagnosed more correctly.

  Moreover, the detection means in the plant diagnostic apparatus 1 according to the present embodiment may include a visualization means for displaying the distribution of the detected volatile substance in the image in which the area 3 is copied. The image in which the area 3 is copied may be, for example, a photograph taken separately, a moving image, a plan view of the facility (plan view), or the like. The distribution of the volatile substances is based on the position information of the volatile substances in the area 3, the concentration of the volatile substances, the kind of the volatile substances, the mixing ratio of the compounds contained as the volatile substances, etc. From the above, it is preferable to create a volatile substance distribution map with an arbitrary color and shading, and to display it overlaid on an image in which the above-described area 3 is copied. In this way, the user can intuitively and easily grasp the distribution of volatile substances.

  According to the plant diagnostic apparatus 1 according to the present embodiment described above, the concentration of volatile substances emitted from plants, the type of volatile substances, the mixing ratio of compounds contained as volatile substances, and the area Since at least one piece of information on the position information of the volatile substance is monitored, the state of the plant can be diagnosed. Therefore, the plant diagnosis apparatus 1 according to the present embodiment can comprehensively evaluate the state of the entire cultivation area based on the volatile substances in the cultivation area, and can perform accurate diagnosis based on biological information based on the volatile substances. Cultivation management can be derived, and non-destructive and non-contact on-site measurement can be performed when producing plants. Therefore, the plant diagnostic apparatus 1 according to the present embodiment can capture and integrate metabolism in real time, and can manage the plant cultivation from a macro viewpoint.

[Pesticide identification device]
Next, a description will be given of a first embodiment of a disease and pest discrimination apparatus according to the present invention.
In the description of the pest identification apparatus according to the present embodiment, the same elements as those in the plant diagnostic apparatus 1 described above are denoted by the same reference numerals, and the description thereof is omitted.

  The pest identification apparatus according to the present embodiment is a volatile product emitted from a plant 2 invaded by a pest that inhibits the growth of the plant 2 in an area 3 where one or more plants 2 to be tested are grown. Monitor at least one of the concentration of the substance, the type of volatile substance, the mixing ratio of the compounds contained as volatile substances, and the location information of the volatile substance in the area 3 to identify the pests in the area 3 It is to discriminate. The pests include at least one of microorganisms and insects. As with the plant diagnosis apparatus 1, monitoring is performed by monitoring means, and diagnosis can be performed by diagnostic means. That is, the discrimination device also has a monitoring unit and a diagnostic unit.

  That is, the above-described plant diagnostic apparatus 1 and the pest-identifying apparatus according to this embodiment are configured so that the above-described plant diagnostic apparatus 1 monitors volatile substances emitted from the plant 2 and determines the state of the plant 2. The only difference is that the pest determination apparatus according to the present embodiment monitors the volatile substances emitted from the plant 2 invaded by the pests and discriminates the pests while making a diagnosis. Other elements are exactly the same. Therefore, in the following description, a different configuration will be described.

  As described above, the pest identification apparatus according to the present embodiment monitors the volatile substances emitted from the plant 2 invaded by the pests attached to the plant 2. Here, being invaded by a pest means, for example, that the plant 2 is eaten by an insect or infected with a pathogen. In these cases, the plant 2 biosynthesizes substances that repel insects and sterilize pathogenic bacteria. The substance biosynthesized in this way is called phytoalexin or the like, and may contain volatile substances. Therefore, the pest discrimination apparatus according to the present embodiment detects pests that are biosynthesized as phytoalexin and is a volatile substance, and performs pest discrimination. Examples of volatile substances detected by the pest-identifying apparatus include flavonoids, terpenoids (particularly sesquiterpenes), fatty acid (furan) derivatives, and the like. Pterocarpan derivatives pisatin, phaseolin, safynol safynol, tomato rishitin, potato phytuberin, convolvulaceae There is a sweet potato, ipomeamarone. In addition, for example, 15 compounds are known for rice, in which 2 types of firlactone, 7 types of oryzalexin, and 5 types of phytocasan are added with sakuranetin. Furthermore, phytoncide is a volatile substance that is released when plants are damaged and has bactericidal power. Examples of the phytoncide include camphor, allyl isothiocyanate, catechin, granyl acetate, thymol, vanillin, diterpenoid, rosmarinic acid, velbenone, cineol, hinokitiol, α-pinene, limonene, casinomol, picipheric acid, asalon and the like.

The pest identification apparatus according to the present embodiment monitors volatile substances emitted from the plant 2 invaded by the pest. Therefore, according to the pest identification apparatus according to the present invention, it is possible to evaluate the overall state of the cultivation area based on the volatile substances in the cultivation area, and from the ecological viewpoint of the reaction of the plant to the pest. It can be viewed from multiple angles. Moreover, according to the pest identification apparatus according to the present invention, it is possible to efficiently identify (specify) a pest. Therefore, according to the pest identification apparatus according to the present invention, it is possible to quickly cope with the pest. That is, the pest identification apparatus according to the present embodiment can perform a bird's-eye evaluation of the state of the entire cultivation area based on the volatile substances in the cultivation area. When there is a problem of providing a pest and disease pesticide detection device that can be grasped and can discriminate a pest that inhibits plant growth, this can be solved.

[First Embodiment of Plant Diagnosis Method]
Next, a first embodiment of the plant diagnosis method according to the present invention will be described.
In the description of the plant diagnosis method according to the first embodiment of the present invention, the same elements as those of the plant diagnosis apparatus 1 according to the first embodiment described above are denoted by the same reference numerals, and the description thereof is omitted. .

  In the plant diagnosis method according to the first embodiment of the present invention, first, in the area 3 where one or more plants to be examined are grown, the concentration of the volatile substance emitted from the plant 2, the volatile substance At least one of the following types, the mixing ratio of the compound contained as the volatile substance, and the positional information of the volatile substance in the area 3 are monitored. Next, based on the monitored information, the state of the plant in the area 3 is diagnosed.

Here, the monitoring described above includes a detection step, a coding step, and an identification map creation step, and these steps are preferably performed according to this procedure.
The detection step is a step of detecting one or more volatile substances in the area 3 by the sensor 4 provided in the area 3.
The encoding step is a step of encoding molecular information related to the volatile material based on the volatile material detected in the detection step.
The identification map creating step is a step of creating an identification map for identifying the type of the volatile substance detected by the sensor 4 based on the molecular information encoded in the encoding step.

  When the above-described steps are performed according to this procedure, an identification map (cluster map, see FIG. 3) can be created based on the detected volatile substance. In other words, if these steps are performed in this procedure, the concentration of the volatile substance, the type of the volatile substance, the mixing ratio of the compound contained as the volatile substance, and the position information of the volatile substance in the area 3 are grasped. be able to. Note that the position information of the volatile substance can be grasped by using the position information of the sensor 4 that has detected the volatile substance as described above.

  The diagnosis in the plant diagnosis method according to the present embodiment includes the concentration of the volatile substance detected by the sensor 4, the type of the volatile substance identified based on the identification map, and the compound contained as the volatile substance. A diagnosis step of diagnosing the state of the plant in the area 3 using at least one of the mixing ratio and the positional information of the volatile substance in the area 3 may be included. If this diagnostic step is included, the state of the plant 2 detected by the sensor 4 at a specific position can be diagnosed more accurately.

  Furthermore, the detection step in the plant diagnosis method according to the present embodiment may include a visualization step of displaying the distribution of the detected volatile substance in the image in which the area 3 is copied. If this visualization step is included, the user can intuitively and easily grasp the distribution of volatile substances.

  According to the plant diagnosis method according to the present embodiment described above, the concentration of volatile substances emitted from plants, the type of volatile substances, the mixing ratio of compounds contained as volatile substances, and volatilization within the area. Since at least one piece of information on the position information of the sex substance is monitored, the state of the plant can be diagnosed. Therefore, according to the plant diagnosis method according to the present embodiment, the state of the entire cultivation area can be comprehensively evaluated based on the volatile substance in the cultivation area, and accurate diagnosis can be performed based on biological information based on the volatile substance. It is possible to derive cultivation management and to perform non-destructive and non-contact on-site measurement when producing plants. Therefore, the plant diagnosis method according to the present embodiment can grasp and integrate metabolism in real time, and can cultivate and manage plants from a macro viewpoint.

[Disease detection method]
Next, a first embodiment of the pest identification method according to the present invention will be described.
In the description of the pest determination method according to the present embodiment, the same elements as those in the plant diagnosis apparatus 1, the plant diagnosis method, and the pest determination apparatus described above are denoted by the same reference numerals, and the description thereof is omitted. .

  The pest identification method according to the present embodiment is a volatile property emitted from a plant 2 invaded by a pest that inhibits the growth of the plant 2 in an area 3 where one or more plants 2 to be tested are grown. Monitor at least one of the concentration of the substance, the type of volatile substance, the mixing ratio of the compounds contained as volatile substances, and the location information of the volatile substance in the area 3 to identify the pests in the area 3 It is to discriminate.

  That is, the above-described plant diagnosis method and the pest determination method according to the present embodiment are such that the above-described plant diagnosis method monitors a volatile substance emitted from a plant and diagnoses the state of the plant. On the other hand, the pest determination method according to the present embodiment is different only in that the volatile substance emitted from the plant 2 invaded by the pest is monitored and the pest is determined. Is exactly the same. Therefore, in the following description, a different configuration will be described.

As described above, the pest identification method according to the present embodiment monitors a volatile substance emitted from the plant 2 invaded by the pest. Therefore, according to the method for distinguishing pests according to the present embodiment, it is possible to comprehensively evaluate the state of the entire cultivation area based on the volatile substances in the cultivation area, and to analyze the plant reaction to the pests from an ecological viewpoint. It can be grasped from many aspects. In addition, according to the pest identification method according to the present embodiment, it is possible to efficiently identify (specify) a pest. Therefore, according to the pest determination method according to the present embodiment, it is possible to quickly cope with the pest. That is, the pest identification method according to the present embodiment can evaluate the overall state of the cultivation area based on the volatile substances in the cultivation area, and also has various aspects from the ecological viewpoint of the reaction of the plant to the pest. When there is a problem of providing a method for discriminating pests that can be perceived and that can discriminate pests that inhibit plant growth, this can be solved.

[Second Embodiment of Plant Diagnosis Device]
Next, a second embodiment of the plant diagnostic apparatus according to the present invention will be described.
In the description of the plant diagnostic apparatus according to the second embodiment of the present invention, the same elements as those of the plant diagnostic apparatus 1 according to the first embodiment described above are denoted by the same reference numerals, and the description thereof is omitted. .

  The plant diagnostic apparatus according to the second embodiment includes a concentration of a volatile substance emitted from the plant 2, a type of the volatile substance, volatilization in an area 3 where one or more plants 2 to be examined are grown. Monitoring means for monitoring at least one of the mixing ratio of the compound contained as the volatile substance and the positional information of the volatile substance in the area 3, and in the area 3 based on the information monitored by the monitoring means And a diagnostic means for diagnosing the water state in the plant body. The monitoring unit and the diagnostic unit in the second embodiment can be the same as those of the diagnostic apparatus 1 according to the first embodiment.

  That is, the plant diagnosis apparatus according to the second embodiment monitors the volatile substances emitted from the plant 2 and diagnoses the moisture state in the plant body in the area 3. The plant diagnosis apparatus according to the first embodiment, which includes, as specific examples, a stage (initial stage) in which changes with time associated with the growth of the plant 2 are small (initial stage), an advanced stage (medium stage), and a further advanced stage (harvest stage) 1 and different. Therefore, in the following description, a different configuration will be described.

  In the plant diagnostic apparatus according to the second embodiment, any of the volatile substances exemplified in the first embodiment and the volatile substances exemplified in the discrimination apparatus can be detected by the detection means. For example, it is preferable to detect a monoterpene synthetic substance, for example. As the monoterpene synthetic substance, for example, a peryl compound is suitable, and in particular, perylaldehyde, peryl alcohol, perilaketone, perillaric acid, perillartin and the like are suitable. The amount of volatile substances such as monoterpenes in plants that are released from the foliage to the atmosphere may vary during the day (under light irradiation). The amount of emission and the variation pattern may differ between favorable environmental conditions and other environmental conditions. As specifically described in the items of the examples, for example, when the water supply condition to the plant is different, the amount of emission of the volatile substance obtained by monitoring and the variation pattern are different. Therefore, it is possible to evaluate the moisture state in the plant body by grasping the release amount and fluctuation pattern of volatile substances such as monoterpenes. For example, perilla produces a large amount of peryl compound, so that it is relatively easy to detect and quantify with a monitoring means. Therefore, in perilla, it is preferable to use the release amount and variation pattern of the peryl compound as an evaluation index.

  Thus, according to the plant diagnostic apparatus according to the second embodiment, the concentration of volatile substances such as peryl compounds emitted from plants, the type of volatile substances, and the mixing ratio of compounds contained as volatile substances And at least one of the positional information of the volatile substances in the area is monitored by the monitoring means. At this time, the monitoring means stores the information obtained by the monitoring (specifically, in the case of the present embodiment, the emission amount and fluctuation pattern of volatile substances) in a storage medium such as an HDD. . Then, the diagnostic means includes information on good environmental conditions (volatile substance release amount and fluctuation pattern) stored in advance in an HDD or the like, and the monitored information (volatile substance release amount and fluctuation pattern) By contrasting, it can be diagnosed whether the moisture state in a plant body is favorable. Therefore, the plant diagnostic apparatus according to the second embodiment can comprehensively evaluate the state of the entire cultivation area (moisture state in the plant body) based on the volatile substance in the cultivation area, and is based on the volatile substance. Accurate diagnosis and cultivation management can be derived from the biological information, and non-destructive and non-contact on-site measurement can be performed when producing plants. Therefore, the plant diagnostic apparatus 1 according to the second embodiment can grasp and integrate metabolism in real time, and can cultivate and manage plants from a macro viewpoint.

[Second Embodiment of Plant Diagnosis Method]
Next, a second embodiment of the plant diagnosis method according to the present invention will be described.
In the description of the plant diagnosis method according to the second embodiment of the present invention, the same elements as those of the plant diagnosis device 1 and diagnosis method according to the first embodiment and the plant diagnosis device according to the second embodiment described above. Are denoted by the same reference numerals, and the description thereof is omitted.

  In the method for diagnosing a plant according to the second embodiment of the present invention, first, a volatile substance emitted from the plant 2 (for example, as described above) in the area 3 where one or more plants to be examined are grown. In addition, at least one piece of information on the concentration of the monoterpene synthesis material), the type of the volatile substance, the mixing ratio of the compound contained as the volatile substance, and the position information of the volatile substance in the above-mentioned area 3 Monitor. Next, based on the monitored information, the water state in the plant body in the above-described area 3 is diagnosed.

  The monitoring in the plant diagnosis method according to the second embodiment includes a detection step, a coding step, and an identification map creation step, as in the plant diagnosis method according to the first embodiment. Can be performed by this procedure. Moreover, a diagnostic process can also be performed similarly to the diagnostic method of the plant which concerns on 1st Embodiment.

  Here, in the plant diagnosis method according to the second embodiment as well, whether the moisture state in the plant body is good by grasping the release amount and variation pattern of volatile substances such as monoterpenes in the plant body as described above. It is possible to evaluate whether or not. Since details of this embodiment have already been described, description thereof is omitted here.

  According to the plant diagnostic method according to the second embodiment described above, the concentration of volatile substances emitted from plants, the type of volatile substances, the mixing ratio of compounds contained as volatile substances, and the area By monitoring at least one piece of positional information of the volatile substance and grasping the emission amount and fluctuation pattern of the volatile substance, the state of the plant (the water state in the plant body) can be diagnosed. Therefore, according to the plant diagnosis method according to the second embodiment, the state of the entire cultivation area (moisture state in the plant body) can be comprehensively evaluated based on the volatile substance in the cultivation area, and the volatile substance Therefore, accurate diagnosis and cultivation management can be derived from the biological information based on the information, and non-destructive and non-contact on-site measurement can be performed when producing plants. Therefore, the plant diagnosis method according to the present embodiment can grasp and integrate metabolism in real time, and can cultivate and manage plants from a macro viewpoint.

  Hereinafter, the plant diagnosis method and diagnosis apparatus, and the pest determination method and determination apparatus according to the present invention will be specifically described with reference to examples.

[1] Drought stress and VOC monitoring on plants Perilla frutescens is known to release peryl compounds such as perilaldehyde, peryl alcohol, and perillyl acetate as volatile organic compounds (VOC). . Therefore, it was thought that these peryl compounds could be used as the target of VOC monitoring, and perilla was selected as the test target in the examples.

The perilla was raised under the following conditions. First, a 55-hole plug tray (nursery seedling tray) is filled with a culture medium, seeded, air temperature 23 ° C., humidity 70-80%, CO ₂ concentration 380-500 ppm, photon amount 250 μmol / m ² / s, white fluorescent light source Was grown for 4 months under the condition of 16 hours of day length. The plant height was kept below 25 cm by branching and pruning (cutting back).

In the measurement of peryl aldehyde, first, irrigation was performed, and the medium on the 1st and 2nd days was maintained in a wet state, and water was not given thereafter. As a result, the medium transiently lost water on the third day, and the medium became dry on the fourth day. Perylaldehyde was measured for a total of 5 days.
The perilla leaves 1 to 2 days after irrigation and the perilla leaves 3 to 4 days after drying of the medium were collected for a genetic experiment described below. In addition, the collected perilla leaves are frozen with liquid nitrogen immediately after collection and stocked at −80 ° C., so that RNA degradation by ribonuclease (RNase) is minimized before RNA extraction operation for analysis. I tried to keep it to the limit.
In addition, the water potential (Wet) of the medium and perilla leaves on the first and second days after irrigation, and the water potential (Dry) of the medium and perilla leaves on the third and fourth days when the medium is dried are measured. did. The water potential was measured by using a water potential measurement device (Decagon Devices, Inc., WP4), collecting soil and plant leaves, immediately putting them into the device, and equilibrating the water at room temperature. (N = 3). The average value (MPa) and standard error of three perilla individuals were obtained for each of Wet and Dry. Table 1 shows the results.

Moreover, VOC monitoring was performed using a gas sensor until 5 days passed immediately after irrigation. In monitoring VOC, the following gas sensor and gas chromatograph mass spectrometer (GC-MS) were used.
The gas sensor used was TGS2600 manufactured by Figaro Engineering Co., Ltd., the data logger used GL820 manufactured by Graphtec Co., Ltd., and the CO ₂ and temperature / humidity data logger used SD800 manufactured by Extech.
Solid phase micro extraction (SPME) fiber uses DVB / CAR / PDMS manufactured by Sigma-Aldrich Japan LLC, GC-MS uses QP2010 manufactured by Shimadzu Corporation, and the column is Agilent Technologies Inc. Company DB-WAX was used.

  The gas sensors described above were prepared with a molecular filter that selectively binds (adsorbs) with perylaldehyde, peryl alcohol, and perillyl acetate, and with a gas sensor that does not incorporate such a molecular filter. The molecular filter was prepared as follows by mixing each reagent with the following composition.

<< Composition of molecular filter >>
Solvent: acetonitrile (5 mL)
Monomer: Methacrylic acid (1.5 mM)
Template: perillaldehyde, perillic alcohol or perillyl acetate (1.5 mM)
Cross-linking agent: trimethylolpropane trimethacrylate (12 mL)
Polymerization initiator: Azobisisobutyronitrile (25 mg)

The reagent was placed in a reagent bottle and stirred for 20 minutes at room temperature, and then polymerized by heating at 90 ° C. for 8 hours to solidify, thereby obtaining a molecular template polymer. As described above, three types of molecules serving as templates were prepared, and three types of molecular template polymers were obtained for each template.
The obtained molecular template polymer was ground in a mortar and then classified with a sieve having an opening of 100 μm to obtain a powder having a particle size of 100 μm or less. The obtained powder was washed with ethanol and then vacuum dried at 60 ° C. to remove the template. Hereinafter, the powder thus obtained is referred to as MIP (Molecular Imprinted Polymer) powder.

And the adsorption | suction characteristic of perillaldehyde, perillic alcohol, and perillyl acetate with respect to three types of MIP powder was investigated as follows. That is, for each type of MIP powder, the rate of change (removal rate) from that without MIP powder was determined by the following formula.

Rate of change = (V _out −V ₀ ) / V ₀

Note that V _out is a response value of the gas sensor in the state with or without MIP powder, and V ₀ is an initial value.

Further, when the response value in the state with MIP powder is subtracted from the response value in the state without MIP powder, the difference becomes the removal amount of perillaldehyde, peryl alcohol and perillyl acetate removed by the MIP powder. The removal rate described above can be restated as the adsorption rate (adsorption characteristics) of perillaldehyde, peryl alcohol, and perillyl acetate with respect to the MIP powder.
In the confirmation performed this time, perylaldehyde removal rate (adsorption rate) of MIP powder using perilaldehyde as a template was 96.26%, and permaldehyde removal rate (adsorption rate) of MIP powder using peryl alcohol as a template. ) Was 90.53%, and the perityl acetate removal rate (adsorption rate) of the MIP powder using perillyl acetate as a template was 89.67%. It should be noted that the removal (adsorption) of the target substance by each MIP powder was confirmed to be specific or selective because no significant effect was observed even when different MIP powders adsorbed different template molecules.

  From this result, when the MIP powder produced as described above is used, certain stress (specifically, drying stress) is given to the perilla, thereby causing a specific VOC (specifically, It has been confirmed that it is possible to specifically and selectively monitor perylaldehyde, perillic alcohol and perillyl acetate.

[2] Conditions for VOC monitoring The above three types of MIP powders are mixed and placed in a gas washing bottle, and in order from the side of the tail, a dry tube for VOC sampling (Perma Pure dryer manufactured by GL Sciences Inc .; model MD-110- 48P), a gas cleaning bottle (containing three types of mixed MIP powder), a gas sensor, a suction pump (MV-6005VP manufactured by AS ONE Co., Ltd.), and GC-MS were connected to form a VOC measurement system related to path 1.
In the same configuration, in order from the side of the perimeter, it is connected to a dry tube, a gas cleaning bottle (without MIP powder mixed with three types), a gas sensor, a suction pump (MV-6005VP manufactured by ASONE Corporation), GC-MS, and path 2 The VOC measurement system which concerns on this was comprised.
A data logger was connected to the gas sensor. The dry tube was constantly purged with dry air and the MIP powder was replaced in 24 hours.

Then, while growing the perilla under the above-mentioned growth conditions, the VOC measurement system according to pathways 1 and 2 is used to monitor the peryl compound that is VOC (specifically perylaldehyde, peryl alcohol, and perillyl acetate). It was. The average of the response values of the gas sensor was obtained for each of the paths 1 and 2, the difference between the average values was obtained, and this difference was used as the peryl compound response value. VOC was measured three times for the same perilla at different times under the same growth conditions and measurement conditions. The first time was from February 2 to February 6, the second time was from February 23 to February 27, and the third time was from March 9 to March 13.
The result is shown in FIG. FIG. 4 is a graph showing the daily fluctuation of the peryl compound response value. In FIG. 4, the horizontal axis represents the number of days elapsed (days), and the vertical axis represents the peryl compound response value (average value) (unit: arbitrary unit (au)).
For comparison with the daily fluctuation of the peryl compound response value, FIG. 5 shows the daily fluctuation of the total VOC equivalent value. In FIG. 5, the horizontal axis represents the number of days elapsed (day), and the vertical axis represents the peryl compound response value (average value) (unit: arbitrary unit (au)). The total VOC equivalent value is obtained by simply adding the gas sensor response values to VOC including hydrogen, alcohols, and peryl compounds, ammonia, hydrogen sulfide, organic solvent, trimethylamine, and methyl mercaptan.

As shown in FIG. 4, on the first to second days after normal irrigation (normal watering), the concentration of the peryl compound was strong in the first, second, and third times. However, on the 3rd to 5th days (under water stress conditions) when the medium was dried, the concentration of the peryl compound was strong at the first time, the second time, and the third time.
On the other hand, as shown in FIG. 5, the total VOC equivalent value tends to decrease with the passage of time in the first time, the second time, and the third time, that is, whether it is normal watering or water stress conditions. Regardless of whether it is lower, the total VOC equivalent value tended to decrease, and did not fluctuate as much as the peryl compound. Further, no correlation could be found between the peryl compound response value and the total VOC equivalent value.

  From this, it is confirmed that (1) the state of plants such as perilla (for example, the water state in the body of plants) can be diagnosed by monitoring VOCs such as peryl compounds using a sensor or the like. did it. (2) In addition, grasp the “behavioral change” such that the concentration of peryl compound decreases when the medium has sufficient moisture, and the concentration of peryl compound increases when the medium does not have enough moisture. It was also found that if such a change in behavior was detected, it was possible to take measures such as immediately supplying water to the medium. (3) Furthermore, as shown in FIG. 4, it was confirmed that the variation pattern in the elapsed days of the peryl compound response value changes each time the first time, the second time, and the third time. This shows the possibility that water stress tolerance has been achieved by repeatedly applying water stress of drying (deficient in water). It has been confirmed by visual observation that perillas that have been repeatedly subjected to water stress are difficult to wither. (4) In addition, such a change in the fluctuation pattern indicates that it is possible to grasp the initial, middle and harvest periods of the perilla of the plant.

[3] Analysis of gene expression From the above study, physical changes in the accumulated substances in the plant and volatile substances that volatilize from the plant occur due to environmental changes such as water stress, leading to changes in the volatilization amount of metabolites. It is assumed that On the other hand, as described above, the change in the volatilization amount of such a metabolite can be grasped by VOC monitoring.
The change in the volatilization amount of the metabolite described above is likely to reflect the change in the synthesis amount of the volatile substance in the living body, and the change is that the expression amount of the gene changes in accordance with the environmental change. It is thought that it is the most likely cause. In other words, a change in the expression level of the gene leads to a change in the synthesis and accumulation amount of the metabolite, which is also reflected in the volatilization amount of the metabolite.
That is, the results of VOC monitoring capture changes in the amount of metabolites volatilized from the plant. From the results of VOC monitoring, changes in synthesis and accumulation of metabolites in the plant and changes in gene expression. If it can be estimated, it is considered that changes in expression traits such as height, color, and taste caused by changes in gene expression can also be estimated.

  Based on the above considerations, gene expression was analyzed using perilla leaves collected for genetic experiments in [1]. In other words, in the perilla leaves monitored in [1] and [2], we analyzed how the expression level of genes related to the perylaldehyde biosynthetic terminal pathway changed by genetic engineering techniques. . Various commercial kits (Qiagen, Takara Bio) were used for RNA extraction, cDNA synthesis, and quantitative PCR according to genetic engineering techniques.

  The genes to be analyzed are limonene synthase (sometimes referred to herein as gene H) and limonene hydroxylase (sometimes referred to herein as gene R), and the expression levels of the genes of these enzymes Was measured by quantitative PCR (Polymerase Chain Reaction). Limonene synthase acts on geranyl pyrophosphate, a metabolite from the perilla mevalonate synthesis pathway to produce limonene ((-)-limonene), and limonene hydroxylase acts on this limonene. It is an enzyme that produces peryl alcohol. The produced peryl alcohol is oxidized to peryl aldehyde.

The gene for limonene synthase is Yuba, A., Yazaki, K., Tabata, M., Honda, G. and Croteau, R., "cDNA cloning, characterization, and functional expression of 4S-(-)-limonene synthase from perilla frutescens ", Arch. Biochem. Biophys. 332, 280-287 (1996) and is registered with GenBank with accession number D49368.
The gene for limonene hydroxylase is Mau, CJ, Karp, F., Ito, M., Honda, G. and Croteau, RB, "A candidate cDNA clone for (-)-limonene-7-hydroxylase from Perilla frutescens ", Phytochemistry 71 (4), 373-379 (2010), and registered under GenBank accession number GQ120438.
And the actin gene which is a constitutive expression gene was selected as a standard at the time of comparing the gene expression level between various samples. The actin gene is Gong, Z., Yamazaki, M., Sugiyama, M., Tanaka, Y. and Saito, K., "Cloning and molecular analysis of structural genes involved in anthocyanin biosynthesis and expressed in a forma-specific. manner in Perilla frutescens ", Plant Mol. Biol. 35 (6), 915-927 (1997), registered in GenBank with accession number AB002819.

[3-1] Extraction of RNA RNA is extracted from a sample by using RNeasy (registered trademark) Plant Mini Kit (manufactured by Qiagen) with reference to the instruction manual attached to the kit. Performed at ~ 14.

(Step 1)
The perilla leaves (100 mg or less) stocked at -80 ° C. in [1] above were immersed in liquid nitrogen and then made into a fine powder in liquid nitrogen using a mortar and pestle.
(Step 2)
After transferring the powdered tissue and liquid nitrogen to a 2 ml microcentrifuge tube (RNase free, separately prepared) cooled with liquid nitrogen, the liquid nitrogen was evaporated while taking care not to thaw the tissue.
(Step 3)
450 μl of Buffer RLT was added to a maximum of 100 mg of powdered tissue and vortexed vigorously (stirred vigorously).
(Step 4)
Lysate was added to a QIAshredder spin column (light purple) set in a 2 ml collection tube and centrifuged at maximum speed for 2 minutes.
(Step 5)
350 μl of the filtrate supernatant from QIAshredder was transferred to a new microcentrifuge tube (not supplied), taking care not to disturb the cell debris pellet in the collection tube.
(Step 6)
175 μl of ethanol (96-100%) was added to the clarified lysate and mixed immediately by pipetting.
(Step 7)
500 μl containing the formed precipitate was applied to an RNeasy spin column (pink) set in a 2 ml collection tube.
(Step 8)
The RNeasy spin column was centrifuged at 10,000 rpm or higher for 15 seconds, and the filtrate was discarded.
(Step 9)
700 μl of Buffer RW1 was added to the RNeasy spin column, then washed by centrifugation at 10,000 rpm or more for 15 seconds, and the filtrate was discarded.
(Step 10)
After adding 500 μl of Buffer RPE to the RNeasy spin column, it was washed by centrifugation at 10,000 rpm or more for 15 seconds, and the filtrate was discarded.
(Step 11)
After adding 500 μl of Buffer RPE to the RNeasy spin column, it was washed by centrifugation at 10,000 rpm or more for 2 minutes, and the filtrate was discarded.
(Step 12)
The RNeasy spin column was transferred to a new 2 ml collection tube (attached) and centrifuged at maximum speed for 1 minute.
(Step 13)
The RNeasy spin column was set in a new 1.5 ml collection tube (attached) and 50 μl of RNase free water was added directly to the spin column membrane.
(Step 14)
Centrifugation was performed at 10,000 rpm or more for 1 minute to elute RNA.

[3-2] Synthesis of cDNA cDNA synthesis was carried out using the QuantiTect (registered trademark) Reverse Transcription Kit (manufactured by Qiagen) with reference to the instruction manual attached to the Kit in the following steps 1 to 8. went.

(Step 1)
The RNA template, gDNA Wipeout Buffer, Quantitative Reverse Transscriptase, Quantscript RT Buffer, RTP Primer Mix, and RNase-free water were thawed on ice, then mixed by tapping and spin down.
(Step 2)
According to Table 2 below, a genomic DNA removal reaction solution was prepared on ice and mixed, and then cooled on ice.
(Step 3)
Next, the genomic DNA removal reaction solution that had been refrigerated in Step 2 was incubated at 42 ° C. for 2 minutes, and then placed on ice.
(Step 4)
According to Table 3 below, a “reverse transcription reaction master mix” was prepared on ice and mixed, and then kept on ice.
(Step 5)
“RNA template from step 3 (14 μl)” was added to each tube containing the reverse transcription reaction master mix and mixed, and then kept on ice.
(Step 6)
The solution obtained in step 5 was incubated at 42 ° C. for 30 minutes.
(Step 7)
In order to inactivate Quantitative Reverse Transscriptase, it was incubated at 95 ° C. for 3 minutes.
(Step 8)
The reverse transcription reaction solution thus obtained was stored at -20 ° C.

[3-3] Quantitative PCR
Primer used for quantitative PCR is Eurofin Genomics Co., Ltd. (Operon Biotechnology Co., Ltd.) HP primer design site ([URL] http://www.operon.com/technical/pcr#primer#design#tool.aspx) After preparation and selection in, primer synthesis was commissioned to the Japan Genetic Research Institute (HPLC purification grade). The base sequence of the designed primer is shown below.

(Gene H amplification primer)
5'forward primer 1: ttccttttggaatgcggac (SEQ ID NO: 1 in the sequence listing)
3'reverse primer 2: tccccatcaccatcttcac (SEQ ID NO: 2 in the sequence listing)

(Gene R amplification primer)
5'forward primer 3: ccctccattcccattaatccc (SEQ ID NO: 3 in the sequence listing)
3'reverse primer 4: tcccttcccagagaccaaac (SEQ ID NO: 4 in the sequence listing)

(Primer for gene expression of constant expression)
5'forward primer 5: aggcaaacagagagaaaatgac (SEQ ID NO: 5 in the sequence listing)
3'reverse primer 6: caccagaatcgagcacaatac (SEQ ID NO: 6 in the sequence listing)

  In quantitative PCR, SYBR (registered trademark) Premix Ex Taq (Tli RNase H Plus) manufactured by Takara Bio Inc. was used as a PCR reagent. In addition, quantitative detection of the amount of amplification for each PCR was performed using a Light Cycler 3.0 system manufactured by Roche Diagnostics. Quantitative PCR was performed in the following steps 1 to 3 with reference to the PCR reagent and each instruction manual attached to the system.

(Step 1)
The reverse transcription reaction solution was melted to prepare a reaction solution having the composition shown in Table 4 below.
(Step 2)
Each solution was encapsulated in Light Cycler Capillaries (20 μl).
(Step 3)
Quantitative PCR was performed under the conditions shown in Table 5 below (the number of Stage2 cycles was changed as appropriate).

[3-4] Results and Discussion By the method described above, a verification test was performed on the difference in gene expression due to the growth process of perilla leaves and the difference in gene expression due to moisture environment (dry / wet). The results and discussion are described below.

(1) Difference in gene expression level due to leaf growth process Using the detected amount of actin gene expression as a reference amount, and using the number of cycles (Cq value) at which the PCR of each target gene reached a certain fluorescence intensity, Differences in gene expression levels during the growth process were compared.
As a result, the expression level ratio of gene R (“adult leaves” / “leaves during development”) is 0.3, and the expression level ratio of gene H (“adult leaves” / “leaves during development”) is 0. It was.
Therefore, it was considered that the biosynthetic terminal pathway of perillaldehyde has declined in adult leaves.

(2) Difference in gene expression level due to moisture environment (dry / wet) Using the detected amount of actin gene expression as a reference amount, the number of cycles (Cq value) at which PCR of genes H and R reached a certain fluorescence intensity was used. Thus, the difference in gene expression level depending on the water environment (dry / wet) was compared.
As a result, the genes H and R are both first, second, third, and water stress times under water stress conditions (dry condition) compared to those with normal irrigation (wet condition, normal watering). Each time, the number of cycles required for amplification until the fluorescence intensity was saturated increased. This result shows that the expression level of the gene decreases as the number of water stresses is repeated. In addition, in both genes H and R, the difference in the number of cycles required for amplification between the first to third samples of water stress was large. This result shows that the degree of decrease in the expression level varies.

As a result, the expression ratio of gene R (“adult (wet)” / “adult (dry)”) was 64.9, and the expression ratio of gene H (“adult (wet)” / “adult) (Dry) ") was 2.9.
That is, the expression level of gene R in adult leaves (dry) is only 1 / 64.9 of the expression level of gene R in adult leaves (wet), and the expression level of gene H in adult leaves (dry) is It was confirmed that there was only 1 / 2.9 of the expression level of gene H in leaves (wet).
Therefore, it was considered that the biosynthetic terminal pathway of perillaldehyde was weakened in the dry state.

(3) Summary As described above, according to the present invention, it is possible to diagnose the state of a plant (for example, the water state in the plant body) by monitoring the concentration of a volatile substance emitted from the plant. Was confirmed. Moreover, according to this invention, based on the volatile substance of a cultivation area, the state of the whole cultivation area can be evaluated in a bird's-eye view, and accurate diagnosis and cultivation management can be derived from biological information based on a volatile substance. It was confirmed that on-site measurement can be performed by non-destructive and non-contact when producing plants.

DESCRIPTION OF SYMBOLS 1 Plant diagnostic device 2 Plant 3 Area 4 Sensor 5 Measurement control device

Claims (10)

In an area where one or more plants to be tested are grown, the concentration of volatile substances emitted from the plants, the type of the volatile substances, the mixing ratio of the compounds contained as the volatile substances, and Monitoring at least one piece of positional information of the volatile substance in the area, diagnosing the state of the plant in the area ,
The monitoring is
A detection step of detecting one or more volatile substances in the area by a sensor provided in the area in a non-destructive and non-contact manner with the plant;
Based on the volatile substance detected in the detection step, the sensor encodes molecular information related to the volatile substance, and sends the information to the measurement control device;
An identification map creating step in which the measurement control device creates an identification map for identifying the type of the volatile substance based on the molecular information coded in the coding step. Diagnosis method.   2. The plant diagnosis method according to claim 1, wherein the volatile substance is at least one of a metabolic intermediate, a metabolite, and a degradation product of the metabolite. The plant diagnostic method according to claim 1 or 2 , wherein the sensor includes a molecular template polymer capable of specifically binding to perillaldehyde. The diagnosis is
The concentration of the volatile substance detected by the sensor, the type of the volatile substance identified based on the identification map, the mixing ratio of the compound contained as the volatile substance, and the mixture in the area The diagnostic process of diagnosing the state of the plant in the area using at least one piece of information of the position information of the volatile substance, according to any one of claims 1 to 3 . Plant diagnostic method. Said detecting step, in an image in which the area is photographed, according to any one of claims 1 to 4, characterized in that it comprises a visualization step of displaying the detected distribution of the volatiles Plant diagnostic method. In an area where one or more plants to be tested are grown, the concentration of volatile substances emitted from the plants, the type of the volatile substances, the mixing ratio of the compounds contained as the volatile substances, and Monitoring means for monitoring at least one piece of positional information of the volatile substance in the area;
Have a, a diagnostic means for diagnosing the condition of the plant in the zone based on the information the is monitored by the monitoring means,
The monitoring means comprises:
Detecting means for detecting one or more volatile substances in the area by a sensor provided in the area in a non-destructive and non-contact manner with the plant;
Based on the volatile substance detected by the detection means, the sensor encodes molecular information related to the volatile substance and transmits the molecular information to the measurement control device;
Based on the encoded molecular information by the coding means, wherein the measurement control device characterized in that it have a, an identification map creating means for creating an identification map for identifying a type of the volatile substance Plant diagnostic equipment. The plant diagnostic apparatus according to claim 6 , wherein the volatile substance is at least one of a metabolic intermediate, a metabolite, and a metabolite degradation product. The plant diagnostic apparatus according to claim 6 or 7 , wherein the sensor includes a molecular template polymer that can specifically bind to perillaldehyde. The concentration of the volatile substance detected by the sensor, the type of the volatile substance identified based on the identification map, the mixing ratio of the compound contained as the volatile substance, and the mixture in the area The diagnostic means for diagnosing the state of the plant in the area by using at least one piece of information of the position information of the volatile substance. The method according to any one of claims 6 to 8 , Plant diagnostic equipment. The said detection means has a visualization means which displays distribution of the detected said volatile substance in the image in which the said area was copied, The any one of Claim 6 to 9 characterized by the above-mentioned. Plant diagnostic equipment.

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