AU2009226465B2

AU2009226465B2 - Plucking propriety assessment method, plucking propriety assessment apparatus and plucking propriety assessment system for tea leaf, and computer-usable medium.

Info

Publication number: AU2009226465B2
Application number: AU2009226465A
Authority: AU
Inventors: Masahiko Arai; Hitoshi Iryo; Byungdug Jun; Jong-Hwan Kim; Kenji Torao
Original assignee: Ito En Ltd; Nagasaki University NUC
Current assignee: Ito En Ltd; Nagasaki University NUC
Priority date: 2008-03-21
Filing date: 2009-03-19
Publication date: 2011-11-17
Anticipated expiration: 2029-03-19
Also published as: AU2009226465A1; JP5361862B2; JPWO2009116613A1; CN101971006B; WO2009116613A1; CN101971006A

Abstract

A vegetation index is calculated using optical data of image information of tea leaves, and the fitness-for-plucking of tea leaves is evaluated for evaluation item(s) using the calculated vegetation index based on the correlation between the vegetation index and at least one of the evaluation items including total nitrogen, the fiver level, the bud weight, the ratio of the number of opened buds to the total number of buds, and the number of buds with open leaves, to determine if the tea leaves are fit for plucking. The system of evaluating the fitness-for-plucking of tea leaves includes a photographic device (1) for creating the image information of tea leaves and an information processing section (2) for calculating the vegetation index and evaluating the fitness-for-plucking of tea leaves for the evaluation item(s) using the calculated vegetation index, and evaluates the fitness-for-plucking using a database for determining the correlation between the evaluation item(s) and the vegetation index.

Description

DESCRIPTION PLUCKING PROPRIETY ASSESSMENT METHOD, PLUCKING PROPRIETY ASSESSMENT APPARATUS AND PLUCKING PROPRIETY ASSESSMENT SYSTEM FOR TEA LEAFE, AND COMPUTER-USABLE MEDIUM Technical Field [00011 The present invention relates to a plucking propriety assessment method, a plucking propriety assessment apparatus and a plucking propriety assessment system for tea leaves that suitability for plucking can be easily determined by a non-contact and non-destructive technique, for raw tea leaves to be used for food and beverage manufacturing, that is, shots of tea plants to be plucked in tea bush, and a computer-usable medium for performing the plucking propriety assessment. In particular, the present invention relates to a plucking propriety assessment method, a plucking propriety assessment apparatus and a plucking propriety assessment system for tea leaves, that perform measurement by image photographing which can detect the growing conditions and the properties applicable as a quality indicator of new shoots of tea plants, and that are capable of determining if it is a time when plucking of tea leaves provides favorable shoots as a raw material for producing intended tea product or not, and a computer-usable medium for performing the plucking propriety assessment. Background Art [00021 In producing tea such as green tea and black tea, raw tea leaves plucked from tea plants in a tea plantation, that is, flesh shoots of tea plants are used. Since the flesh shoots, that are parts to be plucked, of tea plants grow everyday, the quality of raw tea leaves significantly varies by a small difference in the time when they are plucked. Therefore, the market price of raw tea leaves or crude tea obtained by primary processing the raw tea leaves significantly varies depending on the time of plucking, and thus the timing of plucking new shoots in a tea plantation is quite important for producer and seller of fresh tea leaves and crude tea. In addition, setting for the primary processing of raw tea leaves has to be appropriately changed depending on the quality of raw tea leaves, and thus the quality of fresh tea leaves has to be previously understood. Therefore, it is important to evaluate in a short time the quality of tea leaves to be plucked, in order to improve production efficiency. [0003] Conventionally, the time of plucking raw tea leaves is determined mainly based on the experience of an expert. If a person who is not an expert has to determine, the plucking time is determined using, as an objective criterion, a weight of shoots measured by plucking shoots in a certain area of a tea plantation (shoots weight) or a ratio of banjhi shoots to a total number of shoots (rate of banjhi shoot). [0004] On the other hand, as a method for chemically evaluating the quality of plucked raw tea leaves, Patent Documents 1 and 2 listed below propose a method in which plucked raw tea leaves are dried or chopped, then contents of nitrogen, fiber and the like are measured as chemical components relating to quality of tea leaves are measured and used for the evaluation, using near infrared reflectance spectroscopy. Patent Document 1: Japanese Patent Application Laid Open No. 03-179239 Patent Document 2: Japanese Patent Application Laid Open No. 08-114543 Disclosure of the Invention 2 Problems to be Solved by the Invention [0005] However, in the method of determination using the raw tea leaves plucked in a certain area, work time is necessary for transportation to the area for measurement, measurement work, sorting and the like of the plucked tea leaves, which causes a long time for obtaining a result so that rapid determination is impossible. Therefore, it is difficult to rapidly determine in a large tea plantation or at a distant place. In addition, there may be a case where the plucked raw tea leaves can not be efficiently utilized. Further, since the evaluation is performed based on the sampled area, the evaluation result does not necessarily meets for the actual conditions of the whole tea plantation having a broad area. [00061 The method proposed in Patent Documents 1 and 2 described above also requires time and effort for measuring chemical components in the raw tea leaves, and then requires an increased amount of sample to be measured in order to reduce the error due to variations of plucked raw tea leaves, for accurate determination. Therefore, it is still difficult to make a rapid determination for a wide tea bush. [0007] An object of the invention is to provide a plucking propriety assessment method, a plucking propriety assessment apparatus and a plucking propriety assessment system for tea leaves, which are capable of easily determining in a short time if the new shoots of tea plants are suitable for plucking or not, and a computer usable medium for performing the plucking propriety assessment. (0008] In addition, an object of the invention is to provide a plucking propriety assessment method, a plucking propriety assessment apparatus and a plucking propriety 3 C\NRPortbiDCC\MAS\3916043_1 DOC-1/27/201) -4 assessment system for tea leaves, that are capable of determining if new shoots of tea plants are suitable for plucking or not, by a non-contact and non-destructive technique without a need of sampling that may spoil the 5 plucked tea leaves, and a computer-useable medium for performing the plucking propriety assessment for the tea leaves. [0008A] 10 In one aspect the invention provides a plucking propriety assessment method for tea leaves, comprising: calculating a vegetation index using optical data contained in image information of tea leaves; and evaluating suitability for plucking of the tea leaves 15 with respect to at least one evaluation item selected from the group consisting of shoots weight and rate of banjhi shoot, with use of the calculated vegetation index, based on a correlation between said at least one evaluation item and the vegetation index, wherein the correlation is represented 20 with a value X of vegetation index and a value y of evaluation item by the relational formula for the shoots weight: y = e x log (x + f) + g, and, the relational formula for the rate of banjhi shoot: x = hy 3 + iy 2 jy + k, where e, f, g, h, I, j and k in the formulae are constants. 25 [0008B] The invention also provides a plucking propriety assessment method for tea leaves, comprising: calculating a vegetation index using optical data 30 contained in image information for tea leaves; and evaluating suitability for plucking of the tea leaves with respect to at least one evaluation item selected from C:\NRPoibPDCC\MAS\3916M3.DOC-(V27/201l -5 the group consisting of total nitrogen, fiber content, shoots weight, rate of banjhi shoot, and number of opened leaves, with use of the calculated vegetation index, based on a correlation between said at least one evaluation item 5 and the vegetation index, wherein an opportune time for plucking is predicted, based on the evaluated suitability for plucking with respect to said at least one evaluation item, by using a standard variation per day with respect to said evaluation item. 10 [0008C] The invention also provides a plucking propriety assessment system for tea leaves, comprising: a photographing device configured to generate image 15 information of tea leaves; and an information processing unit configured to calculate a vegetation index with use of optical data contained in the image information, and to evaluate suitability for plucking of the tea leaves with respect to at least one evaluation 20 item selected from the group consisting of shoots weight and rate of banjhi shoot, with use of the calculated vegetation index, wherein the information processing unit is capable of evaluating the suitability for plucking of the tea leaves 25 with respect to said at least one evaluation item, using a database having data defining a correlation between said at least one evaluation item and the vegetation index, wherein the correlation is represented with a value X of vegetation index and a value y of evaluation item by the relational 30 formula for the shoots weight: y = e x log (x + f) + g, and, the relational formula for the rate of banjhi shoot: x = hy 3 + iy 2 + jy + k, where e, f, g, h, I, j and k in the formulae CANRPonbI\DCC\MASV19I(6A3.I DOC-li27/2I I -6 are constants. [0008D] The invention also provides a plucking propriety assessment system for tea leaves, comprising: 5 a photographing device configured to generate image information of tea leaves; and an information processing unit configured to calculate a vegetation index with use of optical data contained in the image information, and to evaluate suitability for plucking 10 of the tea leaves with respect to at least one evaluation item selected from the group consisting of total nitrogen, fiber content, shoots weight, rate of banjhi shoot, and number of opened leaves, with use of the calculated vegetation index, 15 wherein the information processing unit is capable of evaluating the suitability for plucking of the tea leaves with respect to said at least one evaluation item, using a database having data defining a correlation between said at least one evaluation item and the vegetation index, and is 20 capable of predicting an opportune time for plucking, based on the evaluated suitability for plucking with respect to said at least one evaluation item, by using a standard variation per day with respect to said evaluation item. 25 [0008E] The invention also provides a plucking propriety assessment system for tea leaves, comprising: a photographing device configured to generate image information of tea leaves; 30 a database having data defining a correlation between C:\NRPorblDCC\MAS\3916(W43_.DC-lf27/201i -6A vegetation index and at least one evaluation item selected from the group consisting of shoots weight and rate of banjhi shoot; and an information processing unit configured to calculate 5 the vegetation index with use of optical data contained in the image information and to evaluate suitability for plucking of the tea leaves with respect to said at least one evaluation item, with use of the calculated vegetation index, based on the correlation between said at least one 10 evaluation item and the vegetation index in the database, wherein the correlation is represented with a value X of vegetation index and a value y of evaluation item by the relational formula for the shoots weight: y = e x log (x + f) + g, and, the relational formula for the rate of banjhi 15 shoot: x = hy3 + iy2 + jy + k, where e, f, g, h, I, j and k in the formulae are constants. [0008F] The invention also provides a plucking propriety 20 assessment system for tea leaves, comprising: a photographing device configured to generate image information of tea leaves; a database having data defining a correlation between vegetation index and at least one evaluation item selected 25 from the group consisting of total nitrogen, fiber content, shoots weight, rate of banjhi shoot, and number of opened leaves, and an information processing unit configured to calculate the vegetation index with use of optical data contained in 30 the image information, to evaluate suitability for plucking of the tea leaves with respect to said at least one evaluation item, with use of the calculated vegetation C:\NRPorl\DCC\MASU9 6U4 I.DOC-I0/2,2011 - 6B index, based on the correlation between said at least one evaluation item and the vegetation index in the database, and to predict an opportune time for plucking, based on the evaluated suitability for plucking with respect to said at 5 least one evaluation item, by using a standard variation per day with respect to said evaluation item. [0008G] The invention also provides a plucking propriety 10 assessment apparatus for tea leaves, comprising: an input unit configured to get image information of tea leaves; an arithmetic processing unit configured to calculate a vegetation index with use of optical data contained in the 15 image information of the tea leaves obtained by the input unit and to evaluate suitability for plucking of the tea leaves with respect to at least one evaluation item selected from the group consisting of total nitrogen, fiber content, shoots weight, rate of banjhi shoot, and number of opened 20 leaves, with use of the calculated vegetation index, the arithmetic processing unit being capable of evaluating the suitability for plucking of the tea leaves with respect to said at least one evaluation item with use of a database having data defining a correlation between said at least one 25 evaluation item and the vegetation index, and capable of predicting an opportune time for plucking, based on the evaluated suitability for plucking with respect to said at least one evaluation item, by using a standard variation per day with respect to said evaluation item; and 30 a display unit configured to display the suitability for plucking of the tea leaves evaluated by the arithmetic processing unit.

C:\NRPonbTDCC\MA5W396(M3_I.DOC-IW27/20II - 6C [0008H] The invention also provides a computer-usable medium having a program code that can be read by a computer to make 5 the computer serve as a plucking propriety assessment apparatus for tea leaves capable of performing assessment of plucking propriety for tea leaves, with use of a database having data defining a correlation between a vegetation index and at least one evaluation item selected from the 10 group consisting of total nitrogen, fiber content, shoots weight, rate of banjhi shoot, and number of opened leaves, wherein the program code comprises: a first program code that can be read by a computer to make the computer perform calculation of a vegetation index, 15 using optical data contained in image information of the tea leaves; and a second program code that can be read by a computer to make the computer perform evaluation of suitability for plucking of the tea leaves with respect to at least one 20 evaluation item of the database, using the calculated vegetation index, based on the correlation between said evaluation item and the vegetation index in the database, and to make prediction of an opportune time for plucking, based on the evaluated suitability for plucking with respect 25 to said at least one evaluation item, by using a standard variation per day with respect to said evaluation item. [00081 The invention also provides a computer-useable medium 30 having: a program code that can be read by a computer to make the computer server as a plucking propriety assessment C:\RPortb\DCC\MASt391(043_1 DOC.1U2712011 -6D apparatus for tea leaves capable of assessing plucking propriety for tea leaves; and a database which stores data defining a correlation between a vegetation index and at least one evaluation item 5 selected from the group consisting of shoots weight and rate of banjhi shoot, wherein the correlation is represented with a value X of vegetation index and a value y of evaluation item by the relational formula for the shoots weight: y = e x log (x + f) + g, and, the relational formula for the rate 10 of banjhi shoot: x = hy 3 + iy 2 + jy + k, where e, f, g, h, I, j and k in the formulae are constants, and the program code comprises: a first program code that can be read by a computer to make the computer perform calculation of a vegetation index, 15 using optical data contained in image information of the tea leaves; and a second program code that can be read by a computer to make the computer perform evaluation of suitability for plucking of the tea leaves with respect to said at least one 20 evaluation item, using the calculated vegetation index, based on the correlation between said evaluation item and the vegetation index in the database. [0008J] 25 The invention also provides a computer-usable medium having: a program code that can be read by a computer to make the computer sever as a plucking propriety assessment apparatus for tea leaves capable of assessing plucking 30 propriety for tea leaves; and a database which stores data defining a correlation between a vegetation index and at least one evaluation item C:NRPonbl\DCC\MAS\3916043_1 DOC.IV27/2011 - 6E selected from the group consisting of total nitrogen, fiber content, shoots weight, rate of banjhi shoot, and number of opened leaves, wherein the program code comprises: a first program code that can be read by a computer to 5 make the computer perform calculation of a vegetation index, using optical data contained in image information of the tea leaves; and a second program code that can be read by a computer to make the computer perform evaluation of suitability for 10 plucking of the tea leaves with respect to said at least one evaluation item, using the calculated vegetation index, based on the correlation between said evaluation item and the vegetation index in the database, and perform prediction of an opportune time for plucking, based on the evaluated 15 suitability for plucking with respect to said at least one evaluation item, by using a standard variation per day with respect to said evaluation item. [0009] 20 Deleted [0010] Deleted [0011] Deleted 25 [0012] Deleted [0013] Deleted [0014] 30 Deleted [0015] According to embodiments of the present invention, it C:\NRPonblDCC\MAS\3916(43_[.DOC-102lW2/I I - 6F may be possible to evaluate suitability for plucking of new shoots of tea plants and to determine easily in a short time if the new shoots are in the suitable term for plucking or not, by a non-contact and non-destructive measures using a 5 photographed image of tea bush. Therefore, judgment on plucking may be performed accurately and rapidly for each section of a tea bush having a broad area, and thus, tea leaves having a target quality can be efficiently harvested. In addition, the raw tea leaves harvested may be homogenous, 10 and production may be stabilized and production efficiency can be improved by planning for harvest. Since troublesome and time-consuming work such as sampling and component analysis of samples may be eliminated, the effort related to judgment on plucking may be reduced. 15 The invention is further described by way of example only with reference to the accompanying drawings. Brief Description of the Drawings [0016] 20 [FIG. 1] FIG. 1 is a graph showing a correlation between NDVI obtained from image information and total nitrogen of tea leaves; [FIG. 2] FIG. 2 is a graph showing a correlation between NDVI obtained from image information and fiber content of tea leaves; [FIG. 3] FIG. 3 is a graph showing a correlation between NDVI obtained from image information and shoots weight in tea leaves; [FIG. 4] FIG. 4 is a graph showing a correlation between NDVI obtained from image information and rate of banjhi shoot in tea leaves; [FIG. 5] FIG. 5 is a graph showing a correlation between NDVI obtained from image information and the number of opened leaves among tea leaves; [FIG. 6] FIG. 6 is a graph showing variation of the correlation between NDVI and total nitrogen content of tea leaves according to plucking seasons; [FIG. 7] FIG. 7 is a graph showing variation of the correlation between NDVI and fiber content of tea leaves according to plucking seasons; [FIG. 8] FIG. 8 is a graph showing a relationship between NDVI and illuminance at the time of photographing; [FIG. 9] FIG. 9 is a graph showing a relationship between NDVI and shooting angle of the image; (FIG. 10] FIG. 10 is a graph showing a correlation between NDVI obtained from image information photographed under dark condition and fiber content of tea leaves; [FIG. 11] FIG. 11 is a schematic configuration view showing an embodiment of the plucking propriety assessment system for tea leaves; [FIG. 12] FIG. 12 is a flow chart schematically showing an example of a plucking propriety assessment method; [FIG. 13] FIG. 13 is a flow chart showing an example of a procedure for calculation of the vegetation index; [FIG. 14] FIG. 14 is a flow chart showing an example of a procedure for correction of the vegetation index; 7 [FIG. 15] FIG. 15 is a flow chart showing an exampLe of a procedure for evaluation with respect to an evaluation item; and [FIG. 16] FIG. 16 is a flow chart showing an example of a procedure for judgment of a proper plucking term. Best Modes for Carrying out the Invention [0017] Amounts of various components in tea leaves vary depending on growth of tea shoots plucked, and a quality required for fresh tea leaves used to produce tea products varies depending on a type and a rank of product to be produced. Therefore, a pluck time of tea leaves has to be determined in such a way that plucked tea leaves having a quality favorable for an intended product to be produced can be obtained with a large crop yield. Such an opportune time for plucking can be determined through check and observation of a tea bush, based on objective evaluation items, without relying on expert skills. However, in a tea plantation having a broad area, since environmental conditions such as sunshine and the like vary by location, a long time is required for determining the opportune time for plucking through observation of each of sections, so that the opportunity of plucking may be lost. [0018] Remote sensing for determining growing conditions using photographed images of crops that are shot using an aircraft or the like has been studied as a method of checking the growing conditions of crops cultivated in a field of broad area. In this connection, it has been attempted to evaluate growing conditions of crops using various vegetation indices that are calculated based on optical data of visible light and near-infrared light detected by taking a photograph. At present, this method is limitedly applicable to only a part of crops including paddy and wheat. If the remote sensing is applicable for 8 judgment on the time to pluck tea leaves, it is expected that a proper term for plucking can be efficiently determined also in a tea bush having a broad area. However, as it can be appreciated from the facts that the new shoots part has to be distinguished from the old leaves part because tea plants are of perennials and tea leaves to be harvested are new shoots, criterion for harvest time of paddy or wheat significantly varies from that for the pluck time of tea leaves. Therefore, the method applied to cereal cannot be similarly applied to plucking of tea leaves. In regard to plucking of tea leaves, analysis items that should be collected from the image information and a method of using the analysis items are completely unknown. Therefore, it is necessary to find image information necessary for deciding the proper term for plucking, and to study measures for evaluation and judgment which makes possible to obtain raw tea leaves having a required quality with high accuracy. [0019] Therefore, the inventors of the present application have generated a variety of image information by taking photographs of tea bushes, and then repeatedly studied about whether or not optical data contained in the image information measured by taking a photograph have a relationship with evaluation items which have been used for judgment on plucking of the tea leaves, with criterion for determining to pluck, with chemical analysis data of fresh tea leaves, or the like. As a result of above, it has been found that there exists a correlation that allows for evaluation of suitability for plucking of tea leaves and decision of a proper term for plucking, based on the image information of photograph, and then it has been realized to provide a method and a system capable of objective assessment for tea leaves and decision of the pluck time through remote sensing based on the correlation. Hereinbelow, a plucking propriety assessment method and a plucking propriety assessment system for tea leaves based 9 on image information according to the present invention will be described in detail. (0020] Since optical data contained in the image information relates to types of light detected by the photographing device, the image information is generated using a photographing device capable of measuring in a wavelength range corresponding to the required optical data. In the general remote sensing, detection data in wavelength ranges such as visible light (400 to 700 nm) and near-infrared light (700 to 1300 nm) are used. And, also in the present invention, image information obtained by detecting such light can be used for assessment of plucking propriety for tea leaves. In order to evaluate growth activity of a plant using image information, a plant activity level has been indicated by a numerical value calculated using optical data contained in image information. More specifically, vegetation indices including NDVI, SAVI, MSAVI, TSAVI, EVI, WDVI, and RVI that are calculated using detection data of red light and near-infrared light have been devised. Such vegetation indices can be used also in evaluation of suitability for plucking and decision of proper pluck term according to the invention. In particular, it has been found that a Normalized Difference Vegetation Index (NDVI) that can be calculated using reflectance of red light (600 to 700 nm) and near-infrared light is quite useful, and that numerical evaluation using a vegetation index is possible with respect to the evaluation items used as indicators in assessment of plucking propriety for tea leaves. Specifically, as a result of a study based on chemical analysis data of tea leaves, it has been recognized that a total nitrogen content and a fiber content of tea leaves highly correlate with the NDVI obtained from the image information of tea leaves. Accordingly, it has been found that the proper term for plucking can be decided by evaluating the total nitrogen content and the fiber 10 content based on that correlation. Moreover, it has been also recognized that rate of banjhi shoot to the total, shoots weight, and the number of opened leaves, which are conventional evaluation items for suitability for plucking based on observation of tea leaves, correlate with the NDVI, and it has been found that those correlations can be used for evaluation of suitability for plucking of tea leaves. Evaluation items such as the rate of banjhi shoot, shoots weight and the like are items which are used by a plucker to objectively determine whether or not to pluck the shoot, based on visual observation at the plucking of tea leaves. Therefore, the presence of correlation between those items and a vegetation index means that, based on that correlation, anyone can evaluate tea leaves and determine if the tea leaves are ready for plucking similarly to an expert, and it is therefore quite important. In other words, determination of whether the tea leaves are ready for plucking or not and prediction of the opportune time for plucking can be conducted in short time for tea plantation of a broad area without damaging the tea leaves, by using image information obtained by taking a photographic image. Hereinbelow, referring to FIGS. 1 to 5, a correlation of a vegetation index obtained from image information of tea leaves with each of evaluation items for tea leaves will be described. Here, it is noted that the NDVI which has the highest correlation with each of the evaluation items will be used as a vegetation index in the following description, and that the other vegetation indices such as the RVI, etc. also have similar correlations. [00211 FIG. 1 is a graph showing a relationship between NDVI and total nitrogen contained in tea leaves [wt%] (x: NDVI, y: total nitrogen) . A correlation can be clearly found between the total nitrogen content in tea leaves and the NDVI, and the correlation can be expressed by a relational formula (1): y = ax + b (in the formula, a = 11 5.96, b = 9.23) (R 2 = 0.56). According to chemical analysis of tea leaves, it is found that the content of amino acids in tea leaves increases as the new shoots grow, and a rank of resultant tea product depends on the amino acids content in tea leaves. Accordingly, suitability for plucking of tea leaves correlates with the amino acids content, and then correlates with the total nitrogen content. Therefore, based on the above relationship between the NDVI and the total nitrogen content, the suitability for plucking of tea leaves can be evaluated and whether the tea leaves are favorable for plucking or not can be judged. Specifically, a value of total nitrogen content is calculated from the relational formula (1), using the NDVI value obtained from image information. Then this value is compared with a range of total nitrogen content in tea leaves suitable for plucking (an adequate range), and whether the tea leaves are suitable for plucking or not can be judged depending on whether the value is within the range or not. Alternatively, an adequate range of NDVI corresponding to the adequate range of total nitrogen may be previously set based on the correlation above, and then whether the tea leaves are suitable for plucking or not can be judged by directly comparing the NDVI value obtained from image information with the set range. In addition, if the tea leaves are judged as being not suitable for plucking through the comparison, a difference of the value of total nitrogen (or NDVI) from the adequate range thereof may be calculated, and a ratio of the obtained difference to its standard variation per day may be calculated, whereby the number of days before reaching the proper term for plucking (or a day when tea leaves are in growing conditions favorable for plucking) can be calculated. Therefore, by adding the calculated number of days to the date of photographing, an opportune time for plucking can be predicted. The standard variation per day of the total nitrogen content is about -0.09%/day. The value of total 12 nitrogen content of tea leaves to be determined as suitable for plucking is in a range of about 3.4 to 6.5 wt% and a part of this range can be set as an adequate range corresponding to an intended quality rank of tea product. For example, the adequate range of total nitrogen content can be set to a higher range: 5.4 to 6.5 wt% in a case where tea leaves are plucked for refined green tea (GYOKURO) or powdered refined green tea (MATCHA), a range: 4.5 to 5.4 wt% for medium grade tea (SENCHA), and a lower range: 3.4 to 4.5 wt% for tea leaves for a general rank of tea leaves. And an adequate range of NDVI value can also be set correspondingly. [0022] FIG. 2 is a graph showing a relationship between NDVI and a content of fiber contained in tea leaves [wt%, dry matter basis] (x: NDVI, y: fiber content). A correlation can also be clearly found between the content of fiber (neutral detergent fiber) in tea leaves and the NDVI, and the correlation can be expressed by a relational formula (2): y = cx + d (in the formula, c = 33.97, d = 4.44) (R 2 = 0.66). According to chemical analysis of tea leaves, it is found that the suitability for plucking of tea leaves correlates with the fiber content as well, and the fiber content increases as the new shoots grow. Accordingly, the fiber content negatively correlates with a quality as SENCHA or medium grade tea. Therefore, based on the above-mentioned relationship between the NDVI and the fiber content, a fiber content is calculated from the NDVI value obtained from image information, this content is then compared with an adequate range of fiber content in tea leaves, and propriety of plucking for tea leaves can be determined, depending on whether the comparison makes a hit or not. Alternatively, an adequate range of NDVI corresponding to the adequate range of the fiber content may be previously set based on the correlation mentioned above, and then whether the tea leaves are suitable for plucking or not can be determined by directly 13 comparing the NDVI value obtained from image information with the set range. In addition, if the tea leaves are judged as being not suitable for plucking through the comparison, a difference of the fiber content (or NDVI) from the adequate range thereof may be calculated, and a ratio of the obtained difference to its standard variation per day may be calculated, whereby the number of days before reaching the proper term for plucking can be calculated. Therefore, by adding the number of days to the date of photographing, an opportune time for plucking can be predicted. The standard variation per day of fiber content is generally about 0.5 to 0.7%/day. The fiber content in tea leaves to be determined as favorable for plucking is generally in a range of about 10 to 35 wt%, and a part of this range can be set as an adequate range corresponding to a quality of intended tea product. For example, the adequate range of fiber content can be set to a lower range: 10 to 20 wt% in a case where tea leaves are plucked for a high rank, and a higher range: 20 to 35 wt% for tea leaves for a general rank. And an adequate range of NDVI can also be set correspondingly. [0023] FIG. 3 is a graph showing a relationship between NDVI and shoots weight (x: NDVI, y: shoots weight [g/400 cm 2 ]) . The shoots weight is an area-averaged weight value that indicates a mass of new shoots of tea leaves to be plucked in a section of a certain area in tea bushes. It corresponds to a crop yield of tea leaves per area and increases as the new shoots grow. That is, the shoots weight is an indicator of a crop yield of tea leaves as well as an indicator of growth level of new shoots. Quality of tea leaves varies as the new shoots grow, and contents of amino acids, caffeine, tannin, for example, decrease as the new shoots grow. On the contrary, a content of sugar increases as the new shoots grow. Therefore, a growth level favorable for plucking varies depending on a type and a rank of a tea product to be 14 produced, and thus the date of plucking has to be determined in such a manner that the new shoots on that day are at a favorable growth level corresponding to the quality required for tea leaves. Therefore, the shoots weight per a certain area as an indicator of a growth level is an important evaluation item to determine the date of plucking. According to FIG. 3, a correlation between the shoots weight and the NDVT can be clearly found, and the correlation can be expressed by a relational formula (3): y = e x log(x + f) + g (in the formula, e = 47.44, f = -0.3, g = 65.77) (R 2 = 0.63). Therefore, based on the relationship between the NDVI and the shots weight, a shoots weight is calculated from the NDVI value obtained from image information, the shoots weight is then compared with an adequate range of shoots weight of tea leaves suitable for plucking, and whether the tea leaves are ready for plucking or not can be determined, depending on whether the comparison makes a hit or not. Alternatively, an adequate range of NDVI corresponding to the adequate range of the shoos weight may be previously set based on the above correlation, and whether the tea leaves are suitable for plucking or not can be then determined by directly comparing the NDVI value obtained from image information with the set range. In addition, if the tea leaves are judged as being not suitable for plucking through the comparison, a difference of the shoots weight (or NDVI) from the adequate range thereof may be calculated, and a ratio of said difference to its standard variation per day may be calculated, whereby the number of days before reaching the proper pluck term can be calculated. Therefore, by adding said number of days to the date of photographing, an opportune time for plucking can be predicted. The standard variation of shoots weight per day is about 2 g/day- 400 2 cm2. The shoots weight of tea leaves to be determined as suitable for plucking is generally in a range of about 10 to 50 g/400 cm 2 , and a part of this range can be set as an 15 adequate range corresponding to an intended quality rank of product. For example, the adequate range of shoots weight per area can be set to a lower range: 10 to 25 g/400 cm2 in a case where tea leaves are plucked for a high rank, and a higher range: 25 to 50 g/400 cm 2 for tea leaves for a general rank. [00241 FIG. 4 is a graph showing a relationship between NDVI and rate of banjhi shoot [%] (x: NDVI, y: rate of banjhi shoot). The rate of banjhi shoot means a ratio of banjhi shoots among all new shoots in a section of a certain area in tea bushes, and the banjhi shoot means a shoot in a condition where a new shoot has grown to complete continuous development of new leaves and a banjhi bud appears. That is, the rate of banjhi shoot is an average value in area that indicates a growth level of new shoots, and it increases as the new shoots grow. Since the quality of tea leaves varies as the new shoots growth, the date of plucking can be determined corresponding to a quality required for the tea leaves, in such a manner that tea leaves to be plucked are in a favorable growth level on that day, using the rate of banjhi shoot as an indicator of a growth level similarly to the shoots weight as described above. In FIG. 4, a correlation between rate of banjhi shoot and NDVI can be clearly found and the correlation can be expressed by a relational formula (4): x = hy 3 + iy 2 + jy + k (in the formula, h = 0.60 x 10~ 6 , i = -0.80 x 10-4, j = 0.42 x 10-2, k = 0.64) (R 2 = 0.62). Therefore, based on the relational formula between the NDVI and the rate of banjhi shoot described above, a rate of banjhi shoot is calculated from the NDVI value obtained from image information, and this value is compared with the rate of banjhi shoot of tea leaves suitable for plucking, whereby it is judged whether the tea leaves are suitable for plucking or not, depending on whether the comparison makes a hit or not. Alternatively, an adequate range of NDVI corresponding to the adequate range of rate 16 of banjhi shoot may be previously set based on the correlation above, and then suitability for plucking can be determined by directly comparing the NDVI value obtained from image information with the set range. In addition, if the tea leaves are judged as being not suitable for plucking through the comparison, a difference of the rate of banjhi shoot from the adequate range thereof may be calculated, and a ratio of said difference to its standard variation per day may be calculated, whereby the number of days before reaching the proper term for plucking can be calculated. Therefore, by adding the number of days to the date of photographing, an opportune time for plucking can be predicted. The standard variation per day of rate of banjhi shoot is about 5 to 6%/day. The rate of banjhi shoot of tea leaves to be determined as favorable for plucking is in a range of about 30 to 90%, and a part of this range can be set as an adequate range corresponding to an intended quality rank of product. For example, the adequate range of rate of banjhi shoot can be set to a lower range: 30 to 50% in a case where tea leaves are plucked for a high rank, and a higher range: 50 to 90% for tea leaves for a general rank. [0025] FIG. 5 is a graph showing a relationship between NDVI and the number of opened leaves [unit: leaf] (x: NDVI, y: number of opened leaves). The number of opened leaves means an average of the numbers of leaves developed in opened leaf condition that one shoot has, taken for all new shoots in a section of a certain area in tea bushes, and it increases as the new shoots grow. Since the quality of tea leaves varies as the new shoots growth, a date of plucking can be determined in such a manner that tea leaves to be plucked are in a favorable growth level on that day, corresponding to the quality required for tea leaves, using the number of opened leaves as an indicator of a growth level similarly to the shoots weight as described above. In FIG. 5, a correlation between the 17 number of opened leaves and the NDVI can be clearly found, and the correlation can be expressed by a relational formula (5): y = mx + n (in the formula, m = 5.53, n = 1.15) (R 2 = 0.66). Therefore, based on the relationship between NDVI and number of opened leaves, the number of opened leaves is calculated from the NDVI value obtained from image information, and the number of opened leaves is compared with an adequate range of the number of opened leaves of suitable tea leaves for plucking, whereby it can be judged whether the tea leaves are suitable for plucking or not, depending on whether the comparison makes a hit or not. Alternatively, an adequate range of NDVI corresponding to the adequate range of the number of opened leaves may be previously set based on the correlation, and then the propriety of plucking can be judged by directly comparing the NDVI value obtained from image information with the set range. In addition, if the tea leaves are judged as being not suitable for plucking through the comparison, a difference of the number of opened leaves (or NDVI) from the adequate range thereof may be calculated, and a ratio of said difference to its standard variation per day may be calculated, whereby the number of days before reaching the proper pluck term can be calculated. Therefore, by adding the number of days to the date of photographing, an opportune time for plucking can be predicted. The standard variation of the number of opened leaves per day is about 0.05 to 0.2/day. However, since the number of opened leaves in regard to the tea leaves to be determined as suitable for plucking varies depending on a location environment of tea bushes or the like, individual check with previously collecting basic data of each tea bush is desirable. The number of opened leaves in the shoots favorable for plucking is generally in a range of about 2 to 6, and a part of this range can be set as an adequate range corresponding to an intended quality rank, for each tea plantation. For example, in a certain tea plantation, the adequate range of the number 18 of opened leaves can be set to a lower range: 3 to 4 when tea leaves are plucked for a high rank, and set in another one to a higher range: 4 to 5 for tea leaves for a general rank. [0026] The correlations shown in FIGS. 1 to 5 are results obtained for the first flush of tea leaves of YABUKITA species. New shoots of tea plants can be plucked for a plurality of times in a year and it is known that the contents of components contained in tea leaves change as a plucking season proceeds from the first flush through the second flush, to the third flush, etc. Since the ratio of the first flush tea leaves among annual green tea products in Japan is a little more than 40% by crop amount, and a little more than 70% by amount of money, it is quite important for producers to know growing conditions of the first flush tea leaves. However, importance of the second and the third flushes of tea leaves also increases with increasing demand in recent years, and thus decision of pluck time has to be made with taking into consideration the growth difference corresponding to their plucking season. In addition, the contents of components contained in tea leaves are slightly different with the variety of tea plants. Although the ratio of YABUKITA species among tea plantations in Japan is about 75% of the total area, the ratio of other types than YABUKITA species increases as demands of cultivar varieties specific to various functional components are increasing. Therefore, growing conditions have to also be recognized corresponding to the varieties of tea plants, upon deciding the time for plucking. [0027] Differences by plucking season, variety of tea plants, location environment and the like of tea leaves to be plucked appears as variation of constants a, b, c, ... n in the relational formulae (1) to (5). However, the correlation similar to that described above is commonly 19 maintained even when plucking season, variety or the like changes. For example, in regard to the relationship between NDVI and total nitrogen content, comparison of the first flush tea leaves with the second flush tea leaves provides a correlation as shown in FIG. 6 (second flush tea leaves: a = -4.18, b = 6.92). In comparison relating to the relationship between NDVI and fiber content, the relationships are provided as shown in FIG. 7 (second flush tea leaves: c = 38.7, d = 2.00). Therefore, the constants in the relational formulae expressing the correlations with respective evaluation items are handled as variables that vary depending on the varieties and the plucking seasons, and arithmetic processing using the relational formulae are performed with the constants of the relational formulae which are set according to data of variety and plucking season provided as initial conditions of tea leaves to be evaluated, whereby evaluation of plucking propriety and judgment on plucking of tea leaves can be performed considering varieties and plucking season. In accordance with the above, upon evaluating the suitability for plucking of tea leaves using the image information, the constants in each relational formula are previously set referring to data of the variety of tea plants and the plucking season of tea leaves to be plucked. The value of each standard variation per day is changed similarly, depending on the variety and the plucking season. [0028] Correlations similar to those shown in FIGS. 1 to 7 that allow for evaluation of suitability for plucking of tea leaves can be also found in items such as contents of components including amino acid, tannin and caffeine and leaf color. Basic data of these items may be collected similarly to the way described above to set correlations with a vegetation index as relational formulae so that these items can be used for assessment of plucking propriety for tea leaves. 20 [0029] Since the image information is affected by photographing conditions, correction of data with photographing conditions is required for the image information, depending on the photographing situation. First, since taking a image of tea bush is performed in the open air, and since the sunshine condition always changes, illuminance at the time of photographing affects the image information. Using image generation data obtained in one day in the same tea bush, the relationship between illuminance at the time of photographing the image and NDVI is investigated to find a correlation shown in FIG. 8 (x: illuminance [lx], y: NDVI) . The correlation can be expressed by a relational formula (6): y = px + q (in the formula, p = 5 x 10-7, q = 0.69) (R 2 = 0.84). Therefore, it is preferable to measure the illuminance at the time of photographing and to correct the data by using the illuminance, and then the NDVI is preferably obtained from the corrected one to use for conducting a judgment on the plucking. In order to improve precision in correcting of image information, a gray reflector can be used as a reference. Specifically, the image of tea bush is taken with a gray reflector in a field of shot so that both of the tea bush and the gray reflector appear in one shot of image. In accordance with the above, optical data obtained from the image of the gray reflector is possibly used as a reference to check the correction if it is appropriate or not, and to improve the precision of evaluation. In this connection, it is important to adjust stop down of lens and shutter speed (exposure time) of a photographing device in order to obtain high quality image information, that is similar to the case of general photographing. A detected value of light intensity that is basic optical data contained in the image information varies according to the exposing conditions of the photographing device (stop down of lens and shutter speed). Therefore, if exposing conditions vary, the optical data 21 has to be standardized from the detected value to an actual value (or converted to a value detected within an exposure time, for example) for calculating the vegetation index. In order to simplify such processing as much as possible, exposing conditions used as standard may be previously determined. Also, data offset due to individual difference of respective photographing device or the like is desirably corrected appropriately for each device. [0030] In a tea plantation, tea plants typically grow on ridges each having a width of 1.5 to 1.8 m and a height (difference in level) of 0.3 to 1 m, and a shooting position of images upon close distance photographing can be set in a range from upside through horizontal direction and to obliquely downside. However, the shooting position is preferably set in a range from upside of a crown surface to horizontal direction because the imaging subjects are new shoots extending upwardly from the crown surfaces of tea plants. If old leaves or shaded parts under the crown surfaces are taken into the image, the image information is affected so that a correlation of the evaluation items with NDVI described above is easily lowered. Therefore, shooting the image from obliquely upward is considered to be appropriate. The relationship between NDVI obtained from image and the shooting angle of image is investigated by close distance photographing of the same tea bush while changing the shooting angle, to obtain a graph shown in FIG. 9 (x: shooting angle [*], y: NDVI). The shooting angle and NDVI have a correlation and the correlation can be expressed by a relational formula (7): y = rx 2 + sx + t (in the formula, r = -0.0001, s = 0.0069, t = 0.72) (R 2 = 0.99). Therefore, it is preferable to measure the shooting angle at the time of photographing and to correct NDVI by the shooting angle, and the corrected one is then preferably used to judgment on the plucking. In this connection, it can be seen from FIG. 9 22 that an offset of actually measured data with respect to the relational formula (7) is smaller in a case where the shooting angle is smaller. The reason for this is considered because the other parts than new shoots of tea plants can be easily excluded from the matters appeared in the image at such an angle. Therefore, in order to improve precision of image information, it is efficient to take the image at a shooting angle that is set in such a manner that the other parts than the new shoots can be excluded from the captured matters as much as possible. It is preferable to position the photographing device at an obliquely upward location where the shooting angle is in a range of 0 to 10* (excepting 0*) with respect to the crown surfaces. The crown surfaces of tea plants are often formed in a shallow curved surface, and the reference level of the shooting angle of this case is defined to be a plane passing the apexes of the crown surfaces. Therefore, the crown surface mentioned as the reference of shooting angle according to the present invention means a horizontal plane passing the apexes of the crown surfaces in the case where the tea bushes are on a level ground, or it means, if the tea bushes are on a sloping place, a plane passing the apexes of the crown surfaces and parallel to the sloping ground surface. [0031] If conducting a long distance photographing by using a satellite, aircraft, or the like, the image is taken from the upside and the NDVI value is corrected depending on the shooting angle. [0032] In the outdoor photographing in sunlight, weather and solar orientation change over time so that photographing conditions including illuminance change depending on the date and time of photographing, and according to these changes, the vegetation index calculated from optical data vary. Therefore, photographing in sunlight in daytime (i.e. under bright 23 condition) easily provide an error in correction of the vegetation index, and thus there is a limitation to improve accuracy of the vegetation index obtained by correlation. As to this fact, if a light source is changed from sunlight to artificial light and photographing is performed in nighttime (i.e. under dark condition), the variation of the photographing conditions can be diminished and the accuracy of the vegetation index obtained from optical data can be improved. In this case, the artificial light used for photographing may be any light including light of a wavelength that can be used to calculate the vegetation index, that is, light including red light and near-infrared light of a wavelength of 600 to 1300 nm, and thus a generally used illuminating lamp for photography, artificial sunlight illuminating lamp or the like may be used as a light source. If irradiation light specific to red light and near-infrared light is used, photographing can be specific to required optical data only so that precision of the vegetation index can be improved. As a light source for irradiating light having such a wavelength, a lamp for red and near-infrared light, LED, or the like can be illustrate as examples. Upon photographing, if a distance between the light source and the tea leaves that are the photographing subjects, an irradiating angle, and illuminance are set to be constant, it is favorable for improving precision of the vegetation index after correction. Therefore, it is preferable to use a fixing device for positioning a light source with respect to the tea leaves and the photographing device as needed. With a configuration using a black-out curtain, a closure plate, or the like to cover around the illuminating lamp and the photographing device so as to define a region for irradiating tea leaves to be a certain area, variation of illuminance can be suppressed, and thus reliability of data can be improved. With this configuration, a broad area cannot be photographed but the photographing is possible not only in nighttime but also 24 in daytime. Therefore, data can be collected regularly and reliably even in daytime by photographing a black-out region under dark condition using artificial light. [00331 FIG. 10 is a graph showing a result examining a relationship between vegetation index and an evaluation item of tea leaves, based on the vegetation index calculated from optical data obtained by photographing with irradiating light under dark condition. In this graph, optical data obtained by photographing (shooting angle: 200) tea leaves of the fourth flush season (autumn tea) of YABUKITA tea, using an artificial sunlight illuminating lamp (illumination of wavelength similar to that of sunlight) in nighttime, is used to calculate the NDVI as a vegetation index and to measure a content of fiber contained in tea leaves [wt%, dry matter basis] as an evaluation item. In the graph of FIG. 10 (x: NDVI, y: fiber content), a correlation similar to that in the case under bright condition can be seen between the fiber content (neutral detergent fiber) in tea leaves and the NDVI, and the correlation can be expressed by the relational formula (2): y = cx + d (in the formula, c = 74.20, d = -22.16) (R 2 = 0.86). Therefore, similarly to the case under bright condition, the suitability for plucking of tea leaves can be evaluated based on the relationship between the NDVI and the fiber content, and it is then possible to judge whether the plucking is proper or not, by comparing the NDVI value with the adequate range thereof. In addition, if the tea leaves are judged as not suitable for plucking, an opportune time for plucking can be similarly predicted. [0034] As to the other evaluation items, correlations similar to the case under bright condition can be found between the vegetation index and the evaluation items of tea leaves under dark condition. Therefore, similarly to the case under bright condition (sunlight), the 25 suitability for plucking of tea leaves can be evaluated by using the relational formula between the vegetation index and either of total nitrogen content, shoots weight, rate of banjhi shoot, or number of opened leaves, and by using its constants, and it is then possible to judge whether the plucking is proper or not by comparing the evaluation item with its adequate range. In addition, if the tea leaves are judged as not suitable for plucking, an opportune time for plucking can be predicted similarly. [0035] Even upon photographing under dark condition, a vegetation index calculated from optical data varies depending on photographing conditions including illuminance and shooting angle, which have correlations similarly to those shown in FIGS. 8 and 9. Therefore, the vegetation index can be similarly corrected by the illuminance data and the angle data. (0036] Irradiation light is different under bright condition and dark condition. As can be seen from FIG. 10, relational formula between a vegetation index and an evaluation item and its constants vary due to a difference of irradiation light. Therefore, the relational formulae between the vegetation index and the evaluation items and their constants are determined based on the distinction of bright/dark conditions (i.e. distinction of sunlight/artificial light = difference of wavelength distributions), depending on the type of tea plants and the plucking season. In regard to artificial light, light distribution of irradiation light may vary with respective illuminating devices, and illuminance or the like may vary between the center and the circumference of the irradiation. Therefore, factors affecting the relational formulae and their constants include the standard of the irradiating device and the irradiation conditions. Thus, the setting of the irradiating device (such as standard and irradiation conditions) has to also be considered when 26 the relational formulae and their constants are determined based on the distinction of bright/dark conditions. In order to prevent the data from being complicated due to difference of irradiation light under dark condition and to prevent variation of vegetation index to be calculated, standard of irradiation light used under dark condition is desirably uniformed. Further, it can also be easily appreciated that the constants of the relational formulae vary depending on the measured/detected wavelength by the photographing device that takes reflected light from tea leaves. Therefore, the setting (such as detection conditions of wavelength and the like) of the detecting unit has to be considered when the relational formulae and their constants are determined. To uniform the setting of the detecting unit in the photographing device is useful for preventing the data from being complicated and to prevent variation of a vegetation index under either of bright/dark condition when the relational formulae and their constants are determined. (0037] An embodiment of a plucking propriety assessment system for tea leaves that is capable of performing judgment on plucking of tea leaves, using the correlation described above, will be described below, referring to the drawings. [0038] FIG. 11 is a schematic configuration view showing an embodiment of a plucking propriety assessment system according to the invention. The plucking propriety assessment system comprises: a photographing unit 1 configured to take image information of tea leaves; an information processing unit 2 configured to evaluate suitability for plucking of the tea leaves, using the image information taken by the photographing unit 1 to judge if it is in a proper term for plucking or not; and an output unit 3 configured to output results of the evaluation and the judgment on the proper term for 27 plucking, conducted by the information processing unit 2. The photographing unit 1 may be in a form for close distance photographing, or in a form to be mounted on flying means such as an aircraft or a satellite for long distance photographing. Alternatively, both forms may be combined to use. In the drawing, close distance photographing at the shooting angle of 0 with respect to the crown surface is shown. The close distance photographing can be performed using a photographing device la for fixed point observation, which is fixed using a pole for a frost protection fan or the like, or using a photographing device lb for moving observation in which the photographing device is appropriately moved to a shooting position around the tea bush and positioned by hand, a tripod or the like, for example. Upon photographing under dark condition, a light source lc for irradiating artificial light including light having wavelength range of red light and near-infrared light to the tea leaves. The light source 1c need not be particularly limited as long as it can irradiate artificial light to tea leaves with preferable illuminance. The light source lc may be fixed in a tea plantation, may be installed at the time of photographing, or may be mounted on the photographing device la or lb for close distance photographing. When the light source 1c is used, it is preferable to position the light source lc considering illuminance, irradiating direction and the like. [0039] In the reflected light that is sunlight or artificial light reflected by tea leaves, difference in intensity appears significantly in red light and near infrared light due to light absorption characteristic of chlorophyll. In the remote sensing, this intensity difference is utilized to calculate a vegetation index such as an NDVI from reflectance factors of the both lights. Specifically, optical data used from image 28 information by the information processing unit 2 is reflected light data in the range of red light and near infrared light, and thus the wavelength range of artificial light irradiated from the light source lc and the wavelength range of the light extracted/detected from the reflected light by the photographing devices la and lb are only required to include red light and near-infrared light, in the photographing unit 1. Therefore, as a photographing device la or lb, not only a dedicated device for remote sensing but also a digital camera or a mobile terminal such as a mobile phone provided with a camera mounted with an equipment capable of detecting required optical data can be used. Specifically, by equipping a digital camera having a CCD image sensor with a specific optical filter, for example, red light and near-infrared light can be detected. As a practical example, a near infrared sensor having a detection range of 760 to 900 nn and a red sensor having a detection range of 600 to 660 nm are used in the embodiment shown in FIG. 11. As a light source 1c, for example, an artificial sunlight lump, or a red light lump, an LED, or the like that can irradiate red light and near-infrared light can be appropriately selected from various irradiating device and used. [0040] Image information generated by the photographing unit includes an image that can be sectionalized into a plurality of regions and that can be handled for respective regions, and optical data related to red light and near-infrared light corresponding to respective regions of the image. The image information is transmitted from the photographing unit 1 to the information processing unit 2 by a data supply instrument. As the data supply instrument, communication through wired or wireless communication link and write/read of information through a recording medium such as a floppy disk and a flash memory, for example, can be used. [0041] 29 The information processing unit 2 includes: an input unit 2a; an arithmetic processing unit 2b; a display unit 2c; and memory unit 2d. The input unit 2a includes a receiving unit or a read unit for obtaining image information generated by the photographing unit 1 directly by communication or indirectly through a recording medium, and the obtained image information is stored in the memory unit 2d as needed. The input unit 2a can be equipped with a keyboard or the like enabling manual input or correction of data, so as to allow for input or correction in regard to: setting of initial conditions such as variety of plants and plucking season, and intended use such as a product rank; distinction of bright/dark condition and photographing conditions related to optical data to be used; selection of an evaluation item; specification of an image region to be evaluated and judged; and the like, which are to be used in operation of evaluation and judgment as needed. [0042] If initial conditions and an image region on which evaluation and judgment is to be performed are specified, the arithmetic processing unit 2b retrieves optical data of red light and near-infrared light corresponding to the specified region in the photographed image from the image information. The arithmetic processing unit 2b appropriately standardize the optical data and then performs arithmetic processing for calculating a vegetation index such as an NDVI using the optical data, and appropriately correct the result depending on photographing conditions, based on distinction of bright/dark condition. Further, if an evaluation item is specified, the arithmetic processing unit 2b refers a database, based on distinction of bright/dark condition, so as to obtain data related to the correlation required for evaluation of tea leaves and judgment on the proper term for plucking, or specifically, a relational formula expressing correlation of the evaluation item with the 30 vegetation index and constants of the relational formula, according to the initial conditions. The arithmetic processing unit 2b then evaluates the tea leaves of the specified region in the photographed image regarding the evaluation item, using the relational formula and the calculated vegetation index. That means, the arithmetic processing unit 2b determines a value of the evaluation item corresponding to the calculated vegetation index, based on the relational formula of the evaluation item, and then judges whether it is in the proper term for plucking or not, by comparing the determined value with a numerical value(s) (adequate range) of the evaluation item favorable for plucking. Alternatively, the arithmetic processing unit 2b determines a numerical value(s) (adequate range) of vegetation index corresponding to the numerical value(s) (adequate range) of the evaluation item favorable for plucking, based on the relational formula, and compares it determined with the calculated vegetation index. [0043] The database is not particularly limited as long as it holds data required for evaluation of tea leaves and judgment on plucking, and it may be previously mounted on the information processing unit 2 as a dedicated device or may be formed by directly reading from a recording medium in which the data is recorded or indirectly obtaining from a remote database through a communication network and storing or updating in the memory unit 2d. The data held by the database includes: relational formulae expressing the correlations between respective evaluation items and a vegetation index as shown in FIGS. 1 to 5 and 10; constants data (a, b, ... , n) for setting appropriate values as constants of respective relational formulae according to initial conditions as shown in FIGS. 6 and 7, and standard variation of respective evaluation items per day; correction data for correcting the vegetation index obtained through arithmetic processing, depending on 31 photographing conditions; and the like. The constant data include numerical values of the constants of relational formulae regarding the respective evaluation items in a form corresponding to respective initial conditions including a variety of tea plants, plucking season and the like, based on the setting of the photographing system (setting of the irradiating device and the detecting unit described above) and distinction of bright/dark condition, and they are configured so that, if respective initial conditions are determined, the corresponding constants are allowed to be set to the relational formulae. If the settings of the photographing system is uniformed, the configuration of the constants data can be simplified. The correction data include data such as relational formulae and constants (p, q, r, s, t) for correcting about affections on vegetation index by photographing conditions such as illuminance, stopping down, shutter speed and shooting angle as shown in FIGS. 8 and 9, and they are configured to set the relational formulae for correcting depending on respective photographing conditions, based on distinction of bright/dark condition. [0044] Data including the optical data read from the image information by the arithmetic processing unit 2b, the calculated vegetation index, and the results of evaluation of suitability for plucking of tea leaves and judgment on the plucking are displayed on the display unit 2c. Such data may be output to the output unit 3 by a data supply instrument or may be stored in the memory unit 2d, as needed. Plucking work in each tea plantation is determined to start in accordance with the data supplied to the output unit 3. For the data supply instrument, communication through wired or wireless communication link and write/read of information through a recording medium such as a floppy disk and flash memory, for example can be used. For the display unit 2c, a display for providing data through screen display or a printer for providing 32 data as printing on a recordable material such as a paper or the like may be used. The output unit 3 may be configured by a terminal which can be arbitrarily selected from a mobile terminal such as a mobile computer 3a, mobile phone 3b and the like, and a fixed terminal 3c such as a desktop personal computer, facsimile and a printer, and the supplied data is arbitrarily displayed, printed or stored by the output unit 3. [0045] The plucking propriety assessment system for tea leaves described above may be configured by a single apparatus for assessing plucking propriety for tea leaves in which the photographing unit 1, the information processing unit 2 and the output unit 3 are integrated. For example, a mobile phone provided with a camera, or a mobile computer provided with a camera may be used as a base and a function for performing the method of plucking propriety assessment for tea leaves may be provided thereto. Alternatively, an apparatus for assessing plucking propriety for tea leaves may be configured only by the information processing unit 2 and provided so that a user can appropriately add or remove the photographing unit 1 and the output unit 3 as needed. [0046] An embodiment of the method of assessing plucking propriety for tea leaves, conducted by using the plucking propriety assessment system as described above will be described below, referring to the drawings. A program code for causing a computer to perform the method to be described below can be provided as an application software recorded in a recording medium and usable by a computer, or as signal distribution transmittable to another computer through wired or wireless communication link. [0047] FIG. 12 is a flow chart schematically showing the procedures of the method of plucking propriety assessment for tea leaves. In the method, a numerical conversion in 33 which a vegetation index is calculated from image information of tea leaves, and evaluation and judgment for checking if it is a proper term for plucking of tea leaves or not, using the calculated vegetation index, are schematically performed. In this embodiment, an NDVI is used as the vegetation index, but other vegetation indices such as RVI or the like also may be used. [0048] In the plucking propriety assessment for tea leaves, first, image information generated by photographing a tea bush is input (step Sl), and a vegetation index is calculated from optical data included in the image information (step S2) . The calculated vegetation index is corrected to a vegetation index of predetermined photographing conditions according to the photographed conditions (step S3), and, using the calculated and corrected vegetation index, suitability for plucking of tea leaves as a numerical value is evaluated with respect to the evaluation item, based on a relationship between the vegetation index and the evaluation item (step S4). It is checked whether judgment of plucking propriety is to be performed or not (step S5), and whether it is the proper term for plucking of the tea leaves or not is judged with respect to the evaluation item, using the evaluated numerical value (step S6) . If the operator is an expert for plucking, the judgment on the proper pluck term with the evaluation value in the step S6 can be eliminated, and the method can finish after the check in the step S5. [0049] As the image information input in the step Sl, photographing conditions regarding the photographing device including stopping down of lens, shutter speed, shooting angle, and presence of a gray reflector image for reference, and the photographing conditions regarding the environment including distinction of bright/dark condition (distinction of irradiation light) and illuminance at the 34 time of photographing are obtained as reference information at the same time, and they are used in the calculation of the vegetation index in step S2 or in the correction in step S3. Also in evaluation in the step S4, the correlation of the vegetation index with the evaluation item can be set by reading the relational formula between the vegetation index and the evaluation item and the constants according to the initial conditions, based on the distinction of bright/dark condition. [0050] Specifically describing the step S2, steps shown in FIG. 13 are included in it. As optical data related to a reflected light intensity, a detected value of the near infrared sensor IR and a detected value of the red sensor R are read from the image information (step S21) . At this time, if the image positions with respect to the near infrared data and the red data are displaced from one another due to the photographing device or the like, the displacement is appropriately corrected, and, if a gray reflector image for reference is included, a detected value IRG of the near-infrared sensor and the detected value RG of the red sensor are read for the image region of the gray reflector. On each of the detected values IR, R, IRG, and RG, standardization processing based on the exposure time (standardized value = detected value/exposure time t, IR +- IR/t, R +- R/t, IRG +- IRG/t, RG +- RG/t) is performed (step S22), presence of a gray reflector image is checked (step S23), if a gray reflector image is present, the corrected values of near-infrared intensity and red intensity are calculated using those values (IR' = IR/IRG, R' = R/RG) (step S24), and the vegetation index is calculated by calculation using the intensity values (step S25). The calculation for calculating an NDVI as the vegetation index is NDVI = (IR' - R')/(IR' + R'), and the calculation when a gray reflector image is not present is NDVI = (IR - R)/(IR + R). By specifying a part of regions in the image, the 35 vegetation index based on optical data of the specified region is obtained (step S26) . If photographing is performed under dark condition, image range from which optical data can be obtained, that is, a range from which data is read in the step S21 and in which a region is specified in the step S26, is limited to the image portion where light is irradiated. (0051] The vegetation index calculated in the step S2 is corrected, depending on the distinction of bright/dark condition, through steps shown in FIG. 14. First, presence of illuminance data at the time of photographing is checked (step S31), the illuminance data is input if it is present (step S32), and correction is performed according to FIG. 8 and the relational formula (6) under bright condition, or according to a similar corresponding relational formula under dark condition (step S33). In addition, presence of shooting angle data of image is checked (step S34), the shooting angle data is input if it is present (step S35), and correction is performed according to FIG. 9 and the relational formula (7) under bright condition, or according to a similar corresponding relational formula under dark condition (step S36) . That means, the relational formulae (6) and (7) for correction used in the steps S33 and S36 and their constants are obtained with distinction of bright/dark condition. The vegetation index obtained in that way is used for evaluation of suitability for plucking of tea leaves. [0052] The evaluation of suitability for plucking of tea leaves (step S4) is performed as follows. First, as shown in FIG. 15, a plucking season is input (step S41) and a variety of tea plants are input (step S42) as a setting of initial conditions of tea leaves to be evaluated. Then, an evaluation item to be evaluated is selected (step S43). The number of the evaluation item may be one or more. If the evaluation item is selected, determination of a 36 relational formula used for evaluation is performed for each evaluation item, depending on the distinction of bright/dark condition. Specifically, depending on the input plucking season and variety of tea plants and selected evaluation item, a relational formula and its constants used for evaluation of the selected evaluation item are read from the database, and a relational formula used for calculating an evaluation value is determined (step S44). Based on the relational formula, evaluation is performed (step S45) using the vegetation index corrected in the step S3 (steps 31 to 36). In this embodiment, by assigning the vegetation index to the relational formula, the value of the evaluation item (evaluation value) corresponding to the vegetation index is calculated and the value is used for the judgment on the proper term for plucking (step S6) . If a plurality of evaluation items are selected in the step S43, values corresponding to respective evaluation items are calculated. The evaluation value can be calculated for all evaluation items. [00531 In the judgment on the proper term for plucking (step S6), first, either the evaluation item or the intended use of tea leaves are selected to be used for judgment (step S61) as shown in FIG. 16. If it is selected to judge by the intended use of tea leaves, a specific intended use related to a product variety such as refined green tea or powdered refined green tea, or a product rank such as high grade or moderate grade, is input (step S62). According to the input specific intended use, an adequate range of the evaluation item is read from the database and set as a criterion (step S63). On the other hand, if it is selected to judge by the evaluation item in step S61, a target value of the evaluation item is input (step S64), and then an adequate range is set using the target value as a criterion. The form of judgment may be such a way that start or end of 37 the proper pluck term is determined using the maximum or the minimum of the adequate range to judge by either one, or such a way that whether it is during the proper pluck term or not is determined using both of the maximum and the minimum. The start of the proper pluck term is determined using the minimum of the adequate range regarding fiber content, shoots weight, rate of banjhi shoot and number of opened leaves, and using the maximum of the adequate range regarding total nitrogen content. On the other hand, the end of the proper pluck term is determined using the maximum of the adequate range regarding fiber content, shoots weight, rate of banjhi shoot and number of opened leaves, and using the minimum of the adequate range regarding total nitrogen content. Therefore, it may be preferably configured to input also the form of judgment when an intended use or a target value is input in the step 62 or the step 64. [0054] Thereafter, based on the adequate range set in the step S63 or S64, the evaluation value of the evaluation item obtained in the step S45 is compared with the adequate range to judge if the value is in the adequate range or not (step S65), and whether tea leaves are suitable for plucking or not is determined (steps S65 and S66). If the tea leaves are judged as unsuitable for plucking (step S67), an opportune time for plucking can be predicted, based on a difference D between the adequate range of the evaluation item and the evaluation value (step S68). This prediction can be performed by reading a standard variation V per day of the evaluation item from the database, and estimating the opportune time for plucking as being a date that is D/V days after the date of photographing the image, for example. Such a configuration is also possible as to arbitrarily select whether the prediction is to be performed or not. [0055] If the calculation of evaluation values (step S45) 38 and the judgment of whether the evaluation values are in adequate ranges or not (step S65) are performed for a plurality of evaluation items, judgment of whether tea leaves are ready for plucking or not is conducted for each of the evaluation items. Regarding display of the results, priorities may be arbitrarily specified for the evaluation items and then the results of evaluation and judgment may be displayed in the order of the priorities. Alternatively, the ratio of the number of items for which the tea leaves are judged as being suitable for plucking, among all evaluation items may be displayed as a level of propriety. [0056] Data used in the steps described above and various data obtained by arithmetic processing and the like may be output after: a process of an image such as magnifying, minifying, or trimming; a change of output form to an image such as a synthetic image or images for each band; or a process of distributing data in an image such as a histogram, as needed. [0057] The embodiment is described above related to green tea. However, it is noted that the correlation of each of total nitrogen content, fiber content, shoots weight, rate of banjhi shoot and number of opened leaves with a vegetation index can be similarly seen even when the variety of tea plants is different. Therefore, for a variety of tea plants used to produce black tea, oolong tea or the like, it is also possible to know a growth level of new shoots of tea plants by generating correlation data by measuring the evaluation item and calculating the vegetation index as described above. Even when black tea, oolong tea or the like is produced, the pluck time is determined related to the growth level of tea leaves. Therefore, by applying the present invention to plucking of tea leaves for black tea, oolong tea or the like and setting the adequate range of the evaluation item 39 C:\NRPonbhDCC\MAS39 1643_IDOC-W27/2011 -40 in the proper term for plucking, propriety for tea leaves can be assessed using the vegetation index so that whether it is a favorable time for plucking can be determined and a pluck time can be predicted. 5 Industrial Applicability [0058] With a non-contact and non-destructive measure using a photographed image of tea bushes, a method of plucking propriety assessment for tea leaves which is capable of 10 easily determining if it is a favorable time for plucking new shoots of tea plants or not in a short time is provided, and judgment on plucking can be conducted accurately and rapidly for each section of tea bushes having a broad area. Accordingly, tea leaves having a target quality can be 15 efficiently harvested, plucked fresh tea leaves can be homogeneous and a plan for plucking can be set. Therefore, production efficiency of tea products can be improved, product quality and homogeneity can be further improved, and the present invention contributes to stabilization of 20 production and supply of tea products. In addition, since troublesome and time-consuming work such as sampling and component analysis of samples can be eliminated, labor related to judgment on plucking can be reduced, and thus it is useful for improving economic efficiency in tea 25 production. Throughout this specification and the claims which follow, unless the context requires otherwise, the word "comprise", and variations such as "comprises" and "comprising", will be understood to imply the inclusion of a 30 stated integer or step or group of integers or steps but not the exclusion of any other integer or step or group of integers or steps.

C:\NRPonb\DCCMAS\3916W43_1 DOC-IV27/NIl -41 The reference in this specification to any prior publication (or information derived from it), or to any matter which is known, is not, and should not be taken as an acknowledgment or admission or any form of suggestion that 5 that prior publication (or information derived from it) or known matter forms part of the common general knowledge in the field of endeavour to which this specification relates.

Claims

1. A plucking propriety assessment method for tea leaves, comprising: 5 calculating a vegetation index using optical data contained in image information of tea leaves; and evaluating suitability for plucking of the tea leaves with respect to at least one evaluation item selected from the group consisting of shoots weight and rate of banjhi 10 shoot, with use of the calculated vegetation index, based on a correlation between said at least one evaluation item and the vegetation index, wherein the correlation is represented with a value X of vegetation index and a value y of evaluation item by the relational formula for the shoots 15 weight: y = e x log (x + f) + g, and, the relational formula for the rate of banjhi shoot: x = hy 3 + iy2 jy + k, where e, f, g, h, I, j and k in the formulae are constants.

2. A plucking propriety assessment method for tea leaves, 20 comprising: calculating a vegetation index using optical data contained in image information for tea leaves; and evaluating suitability for plucking of the tea leaves with respect to at least one evaluation item selected from 25 the group consisting of total nitrogen, fiber content, shoots weight, rate of banjhi shoot, and number of opened leaves, with use of the calculated vegetation index, based on a correlation between said at least one evaluation item and the vegetation index, wherein an opportune time for 30 plucking is predicted, based on the evaluated suitability for plucking with respect to said at least one evaluation item, by using a standard variation per day with respect to C:NPonb\DCC\MASU91643.1 DOC-10/27/20fl -43 said evaluation item.

3. The plucking propriety assessment method for tea leaves, as set forth in claim 1 or 2, wherein the optical 5 data is data of reflected light that is reflected from the tea leaves in the range of red light and the range of near infrared light, and the vegetation index is a Normalized Difference Vegetation Index. 10

4. The plucking propriety assessment method for tea leaves, as set forth in any one of claims 1 to 3, wherein the image information of the tea leaves is generated by photographing under bright condition using sunlight or under dark condition using artificial light irradiation. 15

5. The plucking propriety assessment method for tea leaves, as set forth in any one of claims 1 to 4, wherein the correlation between the evaluation item and the vegetation index is expressed by a relational formula having 20 a constant that is determined in accordance with a variety of tea plant and a plucking season, based on distinction of bright/dark condition under which the image information is generated. 25

6. The plucking propriety assessment method for tea leaves, as set forth in any one of claims 1 to 5, wherein the image information is sectionalized into a plurality of regions and configured to allow for calculation of the vegetation index for one region specified among said 30 plurality of regions.

7. The plucking propriety assessment method for tea C\NRPortb\DCC\MAS\3916(43.1 DOC-1V271201l -44 leaves, as set forth in any one of claims 1 to 6, further comprising: correcting the calculated vegetation index based on at least one of illuminance, stopping down of lens, shutter speed, and reference image information of a gray 5 reflector at the time of generating the image information.

8. The plucking propriety assessment method for tea leaves, as set forth in any one of claims 1 to 7, wherein, in the step of evaluating the suitability for plucking of 10 the tea leaves, a value of the evaluation item corresponding to vegetation index is calculated according to the correlation and the calculated value is compared with an adequate range of the evaluation item, or 15 a range of the vegetation index corresponding to the adequate range of the evaluation item is calculated according to the correlation and the calculated range is compared with the vegetation index, wherein it is judged whether the tea leaves are in a 20 proper term for plucking or not, based on either of the comparisons.

9. The plucking propriety assessment method for tea leaves, as set forth in any one of claims 1 to 8, wherein 25 the image information is generated by photographing at a shooting angle of 0 to 100 (excepting 00) with respect to a crown surface.

10. A plucking propriety assessment system for tea leaves, 30 comprising: a photographing device configured to generate image information of tea leaves; and C:NRPonb\DCC\MA5\391643_1 DOC.1/27/2011 -45 an information processing unit configured to calculate a vegetation index with use of optical data contained in the image information, and to evaluate suitability for plucking of the tea leaves with respect to at least one evaluation 5 item selected from the group consisting of shoots weight and rate of banjhi shoot, with use of the calculated vegetation index, wherein the information processing unit is capable of evaluating the suitability for plucking of the tea leaves 10 with respect to said at least one evaluation item, using a database having data defining a correlation between said at least one evaluation item and the vegetation index, wherein the correlation is represented with a value X of vegetation index and a value y of evaluation item by the relational 15 formula for the shoots weight: y = e x log (x + f) + g, and, the relational formula for the rate of banjhi shoot: x = hy 3 + iy 2 + jy + k, where e, f, g, h, I, j and k in the formulae are constants. 20

11. A plucking propriety assessment system for tea leaves, comprising: a photographing device configured to generate image information of tea leaves; and an information processing unit configured to calculate 25 a vegetation index with use of optical data contained in the image information, and to evaluate suitability for plucking of the tea leaves with respect to at least one evaluation item selected from the group consisting of total nitrogen, fiber content, shoots weight, rate of banjhi shoot, and 30 number of opened leaves, with use of the calculated vegetation index, wherein the information processing unit is capable of C :\NRorb\CC\MAS\3916 3_IDOC-l 27/2011 -46 evaluating the suitability for plucking of the tea leaves with respect to said at least one evaluation item, using a database having data defining a correlation between said at least one evaluation item and the vegetation index, and is 5 capable of predicting an opportune time for plucking, based on the evaluated suitability for plucking with respect to said at least one evaluation item, by using a standard variation per day with respect to said evaluation item. 10

12. A plucking propriety assessment system for tea leaves, comprising: a photographing device configured to generate image information of tea leaves; a database having data defining a correlation between 15 vegetation index and at least one evaluation item selected from the group consisting of shoots weight and rate of banjhi shoot; and an information processing unit configured to calculate the vegetation index with use of optical data contained in 20 the image information and to evaluate suitability for plucking of the tea leaves with respect to said at least one evaluation item, with use of the calculated vegetation index, based on the correlation between said at least one evaluation item and the vegetation index in the database, 25 wherein the correlation is represented with a value X of vegetation index and a value y of evaluation item by the relational formula for the shoots weight: y = e x log (x + f) + g, and, the relational formula for the rate of banjhi shoot: x = hy 3 + iy 2 + jy + k, where e, f, g, h, I, j and k 30 in the formulae are constants.

13. A plucking propriety assessment system for tea leaves, C :NRPonb\DCC\MAS\3916043.1 DOC- M/22011 -47 comprising: a photographing device configured to generate image information of tea leaves; a database having data defining a correlation between 5 vegetation index and at least one evaluation item selected from the group consisting of total nitrogen, fiber content, shoots weight, rate of banjhi shoot, and number of opened leaves, and an information processing unit configured to calculate 10 the vegetation index with use of optical data contained in the image information, to evaluate suitability for plucking of the tea leaves with respect to said at least one evaluation item, with use of the calculated vegetation index, based on the correlation between said at least one 15 evaluation item and the vegetation index in the database, and to predict an opportune time for plucking, based on the evaluated suitability for plucking with respect to said at least one evaluation item, by using a standard variation per day with respect to said evaluation item. 20

14. The plucking propriety assessment system for tea leaves, as set forth in any one of claims 10 to 13, further comprising: an information supply instrument configured to supply 25 the image information generated by the photographing device to the processing device, wherein the information supply instrument includes: a wireless or wired communication device; or an information record device and an information read 30 device allowing for write/read of information through a recording medium between the photographing device and the processing device. C:\NR~onbDCC\AS3 16043_ .DOC-I(V27/201 1 -48

15. A plucking propriety assessment apparatus for tea leaves, comprising: an input unit configured to get image information of 5 tea leaves; an arithmetic processing unit configured to calculate a vegetation index with use of optical data contained in the image information of the tea leaves obtained by the input unit and to evaluate suitability for plucking of the tea 10 leaves with respect to at least one evaluation item selected from the group consisting of total nitrogen, fiber content, shoots weight, rate of banjhi shoot, and number of opened leaves, with use of the calculated vegetation index, the arithmetic processing unit being capable of evaluating the 15 suitability for plucking of the tea leaves with respect to said at least one evaluation item with use of a database having data defining a correlation between said at least one evaluation item and the vegetation index, and capable of predicting an opportune time for plucking, based on the 20 evaluated suitability for plucking with respect to said at least one evaluation item, by using a standard variation per day with respect to said evaluation item; and a display unit configured to display the suitability for plucking of the tea leaves evaluated by the arithmetic 25 processing unit.

16. A computer-usable medium having a program code that can be read by a computer to make the computer serve as a plucking propriety assessment apparatus for tea leaves 30 capable of performing assessment of plucking propriety for tea leaves, with use of a database having data defining a correlation between a vegetation index and at least one C:WRPonblDCC\MAS\W16(43 1.DOC.W27/20II -49 evaluation item selected from the group consisting of total nitrogen, fiber content, shoots weight, rate of banjhi shoot, and number of opened leaves, wherein the program code comprises: 5 a first program code that can be read by a computer to make the computer perform calculation of a vegetation index, using optical data contained in image information of the tea leaves; and a second program code that can be read by a computer to 10 make the computer perform evaluation of suitability for plucking of the tea leaves with respect to at least one evaluation item of the database, using the calculated vegetation index, based on the correlation between said evaluation item and the vegetation index in the database, 15 and to make prediction of an opportune time for plucking, based on the evaluated suitability for plucking with respect to said at least one evaluation item, by using a standard variation per day with respect to said evaluation item. 20

17. A computer-useable medium having: a program code that can be read by a computer to make the computer server as a plucking propriety assessment apparatus for tea leaves capable of assessing plucking propriety for tea leaves; and 25 a database which stores data defining a correlation between a vegetation index and at least one evaluation item selected from the group consisting of shoots weight and rate of banjhi shoot, wherein the correlation is represented with a value X of vegetation index and a value y of evaluation 30 item by the relational formula for the shoots weight: y = e x log (x + f) + g, and, the relational formula for the rate of banjhi shoot: x = hy 3 + iy 2 + jy + k, where e, f, g, h, I, C:NRPortbl\DCCMAS\3916043_ DOC-IW27/2011 -50 j and k in the formulae are constants, and the program code comprises: a first program code that can be read by a computer to make the computer perform calculation of a vegetation index, 5 using optical data contained in image information of the tea leaves; and a second program code that can be read by a computer to make the computer perform evaluation of suitability for plucking of the tea leaves with respect to said at least one 10 evaluation item, using the calculated vegetation index, based on the correlation between said evaluation item and the vegetation index in the database.

18. A computer-usable medium having: 15 a program code that can be read by a computer to make the computer sever as a plucking propriety assessment apparatus for tea leaves capable of assessing plucking propriety for tea leaves; and a database which stores data defining a correlation 20 between a vegetation index and at least one evaluation item selected from the group consisting of total nitrogen, fiber content, shoots weight, rate of banjhi shoot, and number of opened leaves, wherein the program code comprises: a first program code that can be read by a computer to 25 make the computer perform calculation of a vegetation index, using optical data contained in image information of the tea leaves; and a second program code that can be read by a computer to make the computer perform evaluation of suitability for 30 plucking of the tea leaves with respect to said at least one evaluation item, using the calculated vegetation index, based on the correlation between said evaluation item and C:\NRPonb\DCC\MAS\3916043_1.DOC-(v27/20l -51 the vegetation index in the database, and perform prediction of an opportune time for plucking, based on the evaluated suitability for plucking with respect to said at least one evaluation item, by using a standard variation per day with 5 respect to said evaluation item.

19. The computer-useable medium as set forth in any one of claims 16 to 18, further comprising a third program code that can be read by the computer to make the computer output 10 the evaluated suitability for plucking of the tea leaves.

20. A plucking propriety assessment method for tea leaves substantially as hereinbefore described, with reference to the accompanying drawings. 15

21. A plucking propriety assessment system for tea leaves substantially as hereinbefore described, with reference to the accompanying drawings. 20

22. A plucking propriety assessment apparatus for tea leaves substantially as hereinbefore described, with reference to the accompanying drawings.

23. A computer-usable medium substantially as hereinbefore 25 described, with reference to the accompanying drawings.