JPH0792433B2 - Measuring method for sugar content of fruits and vegetables and sugar content measuring device - Google Patents
Measuring method for sugar content of fruits and vegetables and sugar content measuring deviceInfo
- Publication number
- JPH0792433B2 JPH0792433B2 JP40460290A JP40460290A JPH0792433B2 JP H0792433 B2 JPH0792433 B2 JP H0792433B2 JP 40460290 A JP40460290 A JP 40460290A JP 40460290 A JP40460290 A JP 40460290A JP H0792433 B2 JPH0792433 B2 JP H0792433B2
- Authority
- JP
- Japan
- Prior art keywords
- wavelength
- sugar
- sugar content
- fruits
- absorbance
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related
Links
- 235000000346 sugar Nutrition 0.000 title claims description 135
- 235000012055 fruits and vegetables Nutrition 0.000 title claims description 48
- 238000000034 method Methods 0.000 title claims description 21
- 238000002835 absorbance Methods 0.000 claims description 54
- 238000005259 measurement Methods 0.000 claims description 19
- 238000004364 calculation method Methods 0.000 claims description 17
- 230000001678 irradiating effect Effects 0.000 claims description 4
- 241000220225 Malus Species 0.000 description 34
- 235000010724 Wisteria floribunda Nutrition 0.000 description 11
- 235000021016 apples Nutrition 0.000 description 11
- 238000004458 analytical method Methods 0.000 description 10
- 238000010586 diagram Methods 0.000 description 9
- 235000013399 edible fruits Nutrition 0.000 description 8
- 238000001228 spectrum Methods 0.000 description 8
- 238000012360 testing method Methods 0.000 description 7
- 238000011088 calibration curve Methods 0.000 description 6
- 238000010521 absorption reaction Methods 0.000 description 4
- 238000007796 conventional method Methods 0.000 description 4
- 238000012364 cultivation method Methods 0.000 description 4
- 239000007864 aqueous solution Substances 0.000 description 3
- 238000002474 experimental method Methods 0.000 description 3
- 238000007689 inspection Methods 0.000 description 3
- 229930091371 Fructose Natural products 0.000 description 2
- 239000005715 Fructose Substances 0.000 description 2
- RFSUNEUAIZKAJO-ARQDHWQXSA-N Fructose Chemical compound OC[C@H]1O[C@](O)(CO)[C@@H](O)[C@@H]1O RFSUNEUAIZKAJO-ARQDHWQXSA-N 0.000 description 2
- WQZGKKKJIJFFOK-GASJEMHNSA-N Glucose Natural products OC[C@H]1OC(O)[C@H](O)[C@@H](O)[C@@H]1O WQZGKKKJIJFFOK-GASJEMHNSA-N 0.000 description 2
- CZMRCDWAGMRECN-UGDNZRGBSA-N Sucrose Chemical compound O[C@H]1[C@H](O)[C@@H](CO)O[C@@]1(CO)O[C@@H]1[C@H](O)[C@@H](O)[C@H](O)[C@@H](CO)O1 CZMRCDWAGMRECN-UGDNZRGBSA-N 0.000 description 2
- 229930006000 Sucrose Natural products 0.000 description 2
- 238000000862 absorption spectrum Methods 0.000 description 2
- 238000007405 data analysis Methods 0.000 description 2
- 230000001066 destructive effect Effects 0.000 description 2
- 239000008103 glucose Substances 0.000 description 2
- 238000002329 infrared spectrum Methods 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 239000000203 mixture Substances 0.000 description 2
- 239000005720 sucrose Substances 0.000 description 2
- 150000008163 sugars Chemical class 0.000 description 2
- 238000004497 NIR spectroscopy Methods 0.000 description 1
- 230000002411 adverse Effects 0.000 description 1
- WQZGKKKJIJFFOK-VFUOTHLCSA-N beta-D-glucose Chemical compound OC[C@H]1O[C@@H](O)[C@H](O)[C@@H](O)[C@@H]1O WQZGKKKJIJFFOK-VFUOTHLCSA-N 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000000691 measurement method Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000003908 quality control method Methods 0.000 description 1
- 238000000611 regression analysis Methods 0.000 description 1
- 239000000243 solution Substances 0.000 description 1
- 235000013311 vegetables Nutrition 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/02—Food
- G01N33/025—Fruits or vegetables
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/3563—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light for analysing solids; Preparation of samples therefor
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/359—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using near infrared light
Description
【０００１】[0001]
【産業上の利用分野】本発明は、主にりんご青果物にお
いて、青果物に光を照射して得られる青果物からの反射
光から、青果物の糖度を非破壊的に測定する青果物の糖
度測定方法及び糖度測定装置に係り、特に、近赤外領域
の波長に対する吸光度を測定し、この測定値から青果物
の糖度を測定する青果物の糖度測定方法及び糖度測定装
置に関する。BACKGROUND OF THE INVENTION The present invention is mainly applied to apples and fruits.
In addition, the present invention relates to a sugar content measuring method and sugar content measuring device for fruits and vegetables for nondestructively measuring the sugar content of fruits and vegetables from the reflected light from the fruits and vegetables obtained by irradiating the fruits and vegetables with light, and in particular, the absorbance for wavelengths in the near infrared region. The present invention relates to a method for measuring the sugar content of fruits and vegetables and a sugar content measuring device for measuring the sugar content of fruits and vegetables based on the measured value.
【０００２】[0002]
【従来の技術】一般に、野菜や果物等の青果物の糖度
は、青果物を品質をみるうえで重要な要素になっている
が、この糖度は、被検対象の青果物を切り取ってこれを
化学的に分析すること等により測定される。ところが、
この方法は、破壊検査であり、検査にも長時間を要する
ことから、近年においては、青果物の光学的特性に基づ
いた非破壊検査に着目し、短時間で多くの被検対象を検
査して、青果物の品質管理等の用に供することができる
ような方法が開発されている。そして、最近では、近赤
外領域の波長の光を用いて青果物の糖度を測定する方法
が研究されている。2. Description of the Related Art Generally, the sugar content of fruits and vegetables such as vegetables and fruits is an important factor in observing the quality of fruits and vegetables. This sugar content is obtained by cutting out the fruits and vegetables to be inspected chemically. It is measured by analysis and the like. However,
This method is a destructive inspection, and since it also takes a long time to perform the inspection, in recent years, many non-destructive inspections have been focused on based on the optical characteristics of fruits and vegetables to inspect many test objects in a short time. , A method that can be used for quality control of fruits and vegetables has been developed. Recently, a method of measuring the sugar content of fruits and vegetables using light having a wavelength in the near infrared region has been studied.
【０００３】従来、近赤外領域の波長の光を用いた青果
物の糖度測定方法としては、例えば、特開平１−３０１
１４７号公報に掲載されたものが知られている。これ
は、被検対象の青果物からの反射光を受光し、３．０μ
ｍ以下の近赤外領域に含まれる少なくとも３種の波長
（λ1，λ2，λ3）に対応する反射強度を測定し、これ
から各波長における反射率（Ｒ1（λ1），Ｒ2（λ2），
Ｒ3（λ3））を算出し、これらの反射率を用いて、以下
の数式２により、糖度を算出するものである。A conventional method for measuring the sugar content of fruits and vegetables using light having a wavelength in the near infrared region is, for example, JP-A-1-301.
The one disclosed in Japanese Patent Publication No. 147 is known. This receives the reflected light from the fruits and vegetables under test,
The reflection intensities corresponding to at least three kinds of wavelengths (λ1, λ2, λ3) included in the near-infrared region of m or less are measured, and the reflectance (R1 (λ1), R2 (λ2),
R3 (λ3)) is calculated, and the sugar content is calculated by the following mathematical formula 2 using these reflectances.
【０００４】Ｃ＝ａ0＋ａ1Ｒ1（λ1）＋ａ2Ｒ2（λ2）
＋ａ3Ｒ3（λ3）（数式２）C = a0 + a1R1 (λ1) + a2R2 (λ2)
+ A3R3 (λ3) (Formula 2)
【０００５】ここで、少なくとも３種の異なる波長は、
０．９０〜１．１０μｍ，１．１１〜１．３１μｍ，
１．２４〜１．４４μｍ，１．３５〜１．５５μｍ，
１．５８〜１．７８μｍ，１．７２〜１．９２μｍのい
ずれかの範囲に包含されるものである。また、ａ0，ａ
1，ａ2，ａ3は、充分に多い母集団において測定された
反射率及び実測糖度を用いて最小二乗法で決定された係
数である。Here, at least three different wavelengths are
0.90 to 1.10 μm, 1.11 to 1.31 μm,
1.25 to 1.44 μm, 1.35 to 1.55 μm,
It is included in any range of 1.58 to 1.78 μm and 1.72 to 1.92 μm. Also, a0, a
1, a2 and a3 are coefficients determined by the least squares method using the reflectance and the actually measured sugar content in a sufficiently large population.
【０００６】[0006]
【発明が解決しようとする課題】 しかしながら、上記従来の糖度測定方法にあっては、被
検対象ごとに上記いずれかの範囲に包含する適正な波長
（λ1，λ2，λ3）を選択してから、測定を行なわなけ
ればならないので、それだけ、波長の選択作業が煩雑に
なっているとともに、波長が変わるたびに式も変わるの
でその計算作業が煩雑になってしまい、測定が煩雑にな
っているという問題があった。即ち、例えば、青果物と
して、りんごの例で説明すると、りんごの種類（例え
ば、「ふじ」，「スターキング」等）が異なる毎に、波
長を設定し直さなければならないし、種類毎に式（検量
線）が違ってしまう。However, in the above-mentioned conventional sugar content measuring method, after selecting an appropriate wavelength (λ1, λ2, λ3) included in any of the above ranges for each test object, Since the measurement has to be performed, the wavelength selection work is complicated, and the formula is changed each time the wavelength is changed, so the calculation work is complicated and the measurement is complicated. There was a problem. That is, for example, as an example of fruits and vegetables, an apple will be described. For each type of apple (for example, "Fuji", "Starking", etc.), the wavelength must be reset, and the formula ( The calibration curve is different.
【０００７】また、上記糖度の算出においては、原スペ
クトルの微弱信号を取り出すことにより反射率を求める
ことになるので、微弱信号であることからノイズを直接
データに含み易くその影響が大きいものになり、そのた
め、仮に、最適な波長を選択できたとしても、糖度の測
定精度に悪影響が出て、必ずしも、正確な品質判定に供
されていないという問題があった。Further, in calculating the sugar content, since the reflectance is obtained by extracting the weak signal of the original spectrum, since it is a weak signal, noise is likely to be directly included in the data and its influence is large. Therefore, even if the optimum wavelength can be selected, there is a problem that the measurement accuracy of the sugar content is adversely affected and that the quality determination is not always performed accurately.
【０００８】本発明は、上記の問題点にかんがみてなさ
れたもので、特に青果物のりんごにおいて、糖度の算出
式を固定化できるようにするとともに、糖度の推定精度
の向上を図る点にある。The present invention has been made in view of the above problems.
In particular, apples of fruits and vegetables can fix the formula for calculating the sugar content and improve the accuracy of sugar content estimation.
【０００９】[0009]
【課題を解決するための手段】このような課題を解決す
るための本発明の技術的手段は、The technical means of the present invention for solving such a problem are as follows:
【００１０】被検対象の青果物からの反射光を受光し、
２５００ｎｍ以下の近赤外領域の波長に対する吸光度を
測定し、この測定値から青果物の糖度を測定する糖度測
定方法において、糖に帰属する９１２ｎｍの波長の吸光
度と、糖へ帰属しないとされる８８８ｎｍの波長の吸光
度とを測定し、これらの吸光度の二次微分値を演算し、
この演算結果に基づいて青果物の糖度を算出する青果物
の糖度測定方法にある。Receiving the reflected light from the fruits and vegetables to be inspected,
In the sugar content measuring method of measuring the absorbance for wavelengths in the near-infrared region of 2500 nm or less and measuring the sugar content of fruits and vegetables from this measurement value, the absorbance at the wavelength of 912 nm that is attributed to sugar and that of 888 nm that is not attributed to sugar Measure the absorbance of the wavelength, calculate the second derivative of these absorbances,
This is a method for measuring the sugar content of fruits and vegetables, which calculates the sugar content of fruits and vegetables based on the result of this calculation.
【００１１】また、被検対象の青果物に２５００ｎｍ以
下の近赤外領域の波長の光を含む光を照射する光源部
と、この青果物からの反射光を受光する受光部と、照射
光及び反射光のいずれかを糖に帰属する９１２ｎｍの波
長の光及び糖へ帰属しないとされる８８８ｎｍの波長の
光に分光する分光器と、受光部が受光した反射光から糖
に帰属する９１２ｎｍの波長の吸光度及び糖へ帰属しな
いとされる８８８ｎｍの波長の吸光度を算出する吸光度
算出部と、これらの吸光度の二次微分値を演算する二次
微分演算部と、この演算された二次微分値を用いて、以
下の数式１により、青果物の糖度を演算する糖度演算部
とを備えた青果物の糖度測定装置にある。数式１におい
て、λは波長、Ａ１（λ１）は糖に帰属する波長λ１
（９１２ｎｍ）の吸光度、Ａ２（λ２）は糖へ帰属しな
いとされる波長λ２（８８８ｎｍ）の吸光度、Ｋ０，Ｋ
１，Ｋ２は、充分に多い母集団において測定された吸光
度及び実測糖度を用いて最小二乗法で決定された係数で
ある。Further, a light source section for irradiating the fruits and vegetables to be inspected with light including light having a wavelength in the near-infrared region of 2500 nm or less, a light receiving section for receiving reflected light from the fruits and vegetables, irradiation light and reflected light A spectroscope for splitting any of the above into light having a wavelength of 912 nm that is attributed to sugar and light having a wavelength of 888 nm that is not attributed to sugar, and the absorbance of the wavelength of 912 nm that is attributed to sugar from the reflected light received by the light receiving unit. And an absorbance calculator that calculates the absorbance at a wavelength of 888 nm that is not attributed to sugar, a secondary differential calculator that calculates the secondary differential values of these absorbances, and the calculated secondary differential value. A sugar content measuring device for fruits and vegetables is provided with a sugar content calculating unit for calculating the sugar content of fruits and vegetables according to the following formula 1. Formula 1 Smell
Te, λ is the wavelength, A1 (λ1) wavelength λ1 is that attributable to the sugar
Absorbance at (912 nm), A2 (λ2) is the absorbance at wavelength λ2 (888 nm) which is considered not to belong to sugar, K0, K
1, K2 is a coefficient determined by the least squares method using the measured absorbance and the actually measured sugar content in a sufficiently large population.
【００１２】[0012]
【００１３】[0013]
【００１４】[0014]
【数２】 Ｃ：糖度 λ：波長 Ａ1（λ1）：波長λ1における吸光度 Ａ2（λ2）：波長λ2における吸光度 Ｋ０，Ｋ１，Ｋ２：係数[Equation 2] C: sugar content λ: wavelength A 1 (λ 1 ): absorbance at wavelength λ 1 A 2 (λ 2 ): absorbance at wavelength λ 2 K0, K1, K2: coefficients
【００１５】[0015]
【作用】上記構成からなる糖度測定方法及び糖度測定装
置によれば、特に被検対象としてりんご青果物に適用さ
れ、青果物からの反射光を受光すれば、糖に帰属する９
１２ｎｍの波長の吸光度と、糖へ帰属しないとされる８
８８ｎｍの波長の吸光度、即ち、糖と所定の関係にある
要素に帰属する波長の吸光度とが測定され、これらの吸
光度の二次微分値が演算され、この演算結果に基づいて
青果物の糖度が算出される。[Function] A sugar content measuring method and a sugar content measuring device having the above-mentioned constitution
According to Oki, it is applied to apples and fruits as a test subject, and if reflected light from the fruits and vegetables is received, it is attributed to sugar.
Absorbance at a wavelength of 12 nm and not attributed to sugar 8
The absorbance at a wavelength of 88 nm, that is, the absorbance at a wavelength belonging to an element having a predetermined relationship with sugar is measured, the second derivative of these absorbances is calculated, and the sugar content of fruits and vegetables is calculated based on this calculation result. To be done.
【００１６】この場合、二次微分値を用いて演算するの
でバックグラウンドによるノイズが消去されたデータに
加工され、より精度の高い測定ができる。また、上記２
種類の波長の吸光度のデータは吸収に由来するものが異
なるため、互いに一次独立のデータとして取り扱うこと
ができる。In this case, since the calculation is performed using the secondary differential value, the noise due to the background is processed into data in which the measurement is performed with higher accuracy. Also, the above 2
Since the data of the absorbances of the different wavelengths differ from those derived from absorption, they can be treated as first-order independent data.
【００１７】[0017]
【実施例】以下、添付図面に基づいて本発明の実施例に
係る青果物の糖度測定方法及び糖度測定装置について説
明する。実施例に係る青果物の糖度測定方法は実施例に
係る糖度測定装置を用いて実施されるので、この糖度測
定装置の作用とともに説明する。DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS A sugar content measuring method and sugar content measuring apparatus for fruits and vegetables according to embodiments of the present invention will be described below with reference to the accompanying drawings. Since the method for measuring the sugar content of fruits and vegetables according to the embodiment is carried out by using the sugar content measuring device according to the embodiment, it will be described together with the operation of the sugar content measuring device.
【００１８】実施例に係る青果物の糖度測定装置は、青
果物としてりんご果実の糖度を測定するものであり、図
１及び図２に示すように、ベルトコンベア２等によって
順次搬送されるりんごを、測定位置に位置したとき、そ
のりんごの糖度を測定するものである。この糖度測定装
置は、測定位置において被検対象１のりんごに光を照射
する照射部３を備えている。この照射部３は、被検対象
１のりんごに２５００ｎｍ以下の近赤外領域の波長の光
を含む光を照射する光源部４と、光源部４からの照射光
を、後述する、糖に帰属する波長の光、及び、糖と所定
の関係にある要素に帰属する波長の光に分光するモノク
ロメータ等の分光器５とを備えている。The sugar content measuring device for fruits and vegetables according to the embodiment is for measuring the sugar content of apple fruits as fruits and vegetables. As shown in FIGS. 1 and 2, the apples sequentially conveyed by the belt conveyor 2 and the like are measured. When located in position, it measures the sugar content of the apple. This sugar content measuring device includes an irradiation unit 3 that irradiates the apple of the subject 1 with light at the measurement position. The irradiation unit 3 includes a light source unit 4 for irradiating the apple of the test subject 1 with light including a light having a wavelength in the near-infrared region of 2500 nm or less, and irradiation light from the light source unit 4 to the sugar, which will be described later. And a spectroscope 5 such as a monochromator for splitting into light having a wavelength corresponding to an element having a predetermined relationship with sugar.
【００１９】また、この糖度測定装置は、測定位置にお
いて、被検対象１から反射される反射光を受光し、電気
信号に変換してＡ／Ｄ変換する受光部６と、受光部６か
らの信号に基づいて、表示部７の表示制御及び選別機８
の駆動制御をする制御部１０とを備えている。Further, the sugar content measuring device receives the reflected light reflected from the object 1 to be inspected at the measurement position, converts it into an electric signal and performs A / D conversion, and a light receiving part 6 from the light receiving part 6. Based on the signal, the display control of the display unit 7 and the sorting machine 8
And a control unit 10 for controlling the drive of the.
【００２０】制御部１０は、図２に示すように、受光部
６からの信号から糖に帰属する波長の吸光度及び糖と所
定の関係にある要素に帰属する波長の吸光度を算出する
吸光度算出部１１と、これらの吸光度の二次微分値を演
算する二次微分演算部１２と、この演算された二次微分
値を用いて青果物の糖度を演算する糖度演算部１３と、
この糖度演算部１３の演算結果に基づいて糖度の等級を
判定する判定部１４とを備えている。各部の機能は例え
ばマイクロプロセッサの機能によって実現される。As shown in FIG. 2, the control unit 10 calculates the absorbance of the wavelength attributed to the sugar and the absorbance of the wavelength attributed to the element having a predetermined relationship with the sugar from the signal from the light receiving unit 6. 11, a secondary differential calculation unit 12 that calculates a secondary differential value of these absorbances, and a sugar content calculation unit 13 that calculates the sugar content of fruits and vegetables using the calculated secondary differential value,
The determination unit 14 determines the sugar content grade based on the calculation result of the sugar content calculation unit 13. The function of each unit is realized by the function of a microprocessor, for example.
【００２１】上記糖度演算部１３は、以下の数式１によ
り糖度演算する機能を備えている。The sugar content calculating unit 13 has a function of calculating the sugar content by the following mathematical formula 1.
【００２２】[0022]
【数３】 Ｃ：糖度 λ：波長 Ａ1（λ1）：波長λ1における吸光度 Ａ2（λ2）：波長λ2における吸光度 Ｋ０，Ｋ１，Ｋ２：係数[Equation 3] C: sugar content λ: wavelength A 1 (λ 1 ): absorbance at wavelength λ 1 A 2 (λ 2 ): absorbance at wavelength λ 2 K0, K1, K2: coefficients
【００２３】数式１において、λは波長、Ａ1（λ1）は
糖に帰属する波長λ1の吸光度、Ａ2（λ2）は糖と所定
の関係にある要素に帰属する波長λ2の吸光度、Ｋ0，Ｋ
1，Ｋ2は、充分に多い母集団において測定された吸光度
及び実測糖度を用いて最小二乗法で決定された係数であ
る。In Equation 1, λ is the wavelength, A1 (λ1) is the absorbance of the wavelength λ1 attributed to the sugar, A2 (λ2) is the absorbance of the wavelength λ2 attributed to the element having a predetermined relationship with the sugar, K0, K
1, K2 is a coefficient determined by the least squares method using the measured absorbance and the actually measured sugar content in a sufficiently large population.
【００２４】判定部１４は、上記演算糖度が、例えば糖
度の高いものから順にランクづけされたＡ，Ｂ，Ｃラン
クの３段階のうち、どのランクに所属するかを判定する
機能を備えている。The determination section 14 has a function of determining which rank the A, B, and C ranks of the calculated sugar content belong to, for example, the ones having the highest sugar content. .
【００２５】上記表示部７は、糖度演算部１３で演算さ
れた糖度を表示するディスプレイ１５を備えているとと
もに、例えばＡ，Ｂ，Ｃランクに夫々対応する色分けさ
れたランプ１６を有し、判定部１４の判定結果に基づい
て対応するランプを点灯させる機能を備えている。The display unit 7 is provided with a display 15 for displaying the sugar content calculated by the sugar content calculation unit 13, and also has, for example, color-coded lamps 16 corresponding to A, B, and C ranks, respectively. It has a function of turning on the corresponding lamp based on the determination result of the unit 14.
【００２６】上記選別機８は、判定部１４の判定結果に
基づいて、例えばＡ，Ｂ，Ｃランクにランクづけされた
りんごを、例えば、ベルトコンベア２の径路を変更する
手段等によりランクごとに仕分する機能を備えている。The sorting machine 8 sorts the apples ranked A, B, and C based on the judgment result of the judging section 14 into each rank by, for example, a means for changing the path of the belt conveyor 2. It has the function of sorting.
【００２７】また、制御部１０は、測定位置にあるりん
ごの測定中に、糖に帰属する波長の光と、糖と所定の関
係にある要素に帰属する波長の光とを順に照射しうるよ
うに分光器５を制御する機能を備えている。Further, the control unit 10 can sequentially irradiate the light having the wavelength attributed to the sugar and the light having the wavelength attributed to the element having a predetermined relationship with the sugar during the measurement of the apple at the measurement position. And has a function of controlling the spectroscope 5.
【００２８】次に、照射光の波長について詳しく説明す
る。実施例においては、上記糖に帰属する波長として、
９１２ｎｍを用いている。これは、糖に帰属する吸収波
長を周知の帰属表に基づいて選択してある。一般に、近
赤外領域での振動数は、赤外領域に存在する基準振動の
倍音、または結合音となっている。ここで、波長９１２
ｎｍは、Ｃ−Ｈ基の第３倍音に帰属する。Next, the wavelength of the irradiation light will be described in detail. In Examples, as the wavelength attributed to the sugar,
912 nm is used. In this, the absorption wavelength attributed to sugar is selected based on a well-known attribution table. Generally, the frequency in the near-infrared region is the overtone or the combined sound of the reference vibration existing in the infrared region. Where the wavelength 912
nm belongs to the third overtone of the CH group.
【００２９】この選択にあたっては、予め、以下の実験
により、帰属関係を確認した。先ず、数十個のりんごの
サンプルを用いて、近赤外スペクトルデータ解析を行な
う。例えば、これらのスペクトルの二次微分スペクトル
の値と手分析値（実測値）との間で回帰分析を行ない、
負の相関係数を示す波長の中から統計的に有意な波長を
いくつか選択し、次に、これらの波長の糖への帰属を確
認し、そのうえで、９１２ｎｍを最適なものとして選択
した。図３は、りんごの種類「ふじ」における糖度の相
関図である。ここで、９１２ｎｍ以外の波長は、糖に帰
属しない波長であったり（例えば、７７４ｎｍ，１０３
２ｎｍ，１１７６ｎｍにはＣ−Ｈ基，Ｏ−Ｈ基以外の吸
収が見られる。）、あるいは、統計的に比較して不利で
あったりすることから、選択から外した。また、「ふ
じ」のみならず、「スターキング」，「ふじとスターキ
ングの混合」等、他のサンプルについても同様の実験を
行なって、９１２ｎｍが最適な波長であることを確認し
た。Prior to this selection, the relationship of membership was confirmed by the following experiment. First, near infrared spectrum data analysis is performed using several tens of apple samples. For example, perform a regression analysis between the value of the second derivative spectrum of these spectra and the manual analysis value (actual measurement value),
Several statistically significant wavelengths were selected from those showing a negative correlation coefficient, then the assignment of these wavelengths to sugars was confirmed, and then 912 nm was selected as the optimal one. FIG. 3 is a correlation diagram of the sugar content in the apple type “Fuji”. Here, the wavelengths other than 912 nm are wavelengths that do not belong to sugar (for example, 774 nm, 103
Absorption other than C—H groups and O—H groups is observed at 2 nm and 1176 nm. ), Or because it is disadvantageous in comparison with statistics, it was excluded from the selection. Further, similar experiments were conducted not only for "Fuji" but also for other samples such as "Starking" and "Fuji and Starking", and it was confirmed that 912 nm was the optimum wavelength.
【００３０】更に、波長９１２ｎｍが、糖に帰属する波
長であることを以下の実験で確認した。りんご果実にお
ける糖は、主にショ糖、果糖、ブドウ糖の３種類である
ことから、これについて水溶液を作製し、近赤外分光分
析を行なって吸収波長を解析した。各波長における相関
係数は図４乃至図６のようになる。これらの測定値から
も分かるように波長９１２ｎｍは相関が高く糖に由来す
るものであることが分かる。尚、物理的に糖濃度と正の
相関を持つスペクトル値の二次微分値をとると、この値
は負の値となるので、濃度とは負の相関を示すことにな
る。従って、図４乃至図６において、正の相関を示す波
長は、糖には無関係な波長であると判断される。Further, it was confirmed in the following experiment that the wavelength of 912 nm is the wavelength belonging to sugar. Since sugars in apple fruits are mainly of three types, sucrose, fructose, and glucose, an aqueous solution was prepared for this and the absorption wavelength was analyzed by performing near-infrared spectroscopy. The correlation coefficient at each wavelength is as shown in FIGS. As can be seen from these measured values, it can be seen that the wavelength of 912 nm has a high correlation and is derived from sugar. When the second derivative of the spectrum value that physically has a positive correlation with the sugar concentration is obtained, this value becomes a negative value, so that it shows a negative correlation with the concentration. Therefore, in FIGS. 4 to 6, the wavelength showing a positive correlation is judged to be a wavelength unrelated to sugar.
【００３１】次に、実施例においては、糖と所定の関係
にある要素に帰属する波長として、８８８ｎｍを用いて
いる。これは、上記と同様の近赤外スペクトルデータ解
析により、統計的に相関の高い有意な波長をいくつか選
択し、これらのうちから糖へ帰属しないとされる波長を
選択してある。Next, in the examples, 888 nm is used as a wavelength attributed to an element having a predetermined relationship with sugar. In this, the same infrared spectrum data analysis as described above was used to select some significant wavelengths having a high statistical correlation, and from these, wavelengths that were not considered to belong to sugar were selected.
【００３２】従って、この実施例に係る糖度測定装置
は、以下のように作用する。ベルトコンベア２で搬送さ
れたりんごが測定位置に至ると、照射部３から被検対象
１のりんごへ向けて、糖に帰属する波長の光、及び、糖
と所定の関係にある要素に帰属する波長の光が照射され
る。そして、測定位置において、被検対象１から反射さ
れる反射光が受光部６に受光され、制御部１０へ電気信
号として出力される。制御部１０においては、吸光度算
出部１１が、受光部６からの信号から糖に帰属する波長
の吸光度及び糖と所定の関係にある要素に帰属する波長
の吸光度を算出し、二次微分演算部１２がこれらの吸光
度の二次微分値を演算し、糖度演算部１３がこの演算さ
れた二次微分値を用いて青果物の糖度を演算する。この
演算結果は表示部７に表示される。Therefore, the sugar content measuring apparatus according to this embodiment operates as follows. When the apple conveyed by the belt conveyor 2 reaches the measurement position, it is attributed from the irradiation unit 3 to the apple of the object to be inspected 1 with light having a wavelength belonging to sugar and an element having a predetermined relationship with sugar. Light of a wavelength is emitted. Then, at the measurement position, the reflected light reflected from the test object 1 is received by the light receiving section 6 and output to the control section 10 as an electric signal. In the control unit 10, the absorbance calculation unit 11 calculates the absorbance of the wavelength attributed to the sugar and the absorbance of the wavelength attributed to the element having a predetermined relationship with the sugar from the signal from the light receiving unit 6, and the second derivative operation unit. 12 calculates the secondary differential value of these absorbances, and the sugar content calculating unit 13 calculates the sugar content of fruits and vegetables using the calculated secondary differential value. The calculation result is displayed on the display unit 7.
【００３３】この場合、二次微分値を用いて演算するの
で、原スペクトルをデータとする場合に比較して、バッ
クグラウンドによるノイズが消去されたデータとするこ
とができ、それだけ、糖度の推定精度が向上する。尚、
図７にりんご果実の近赤外吸収スペクトルを示す。
（ａ）は原スペクトルで、（ｂ）は二次微分スペクトル
である。In this case, since the calculation is performed using the second derivative, compared to the case where the original spectrum is used as the data, it is possible to obtain the data in which the noise due to the background is eliminated, and the estimation accuracy of the sugar content is as much as that. Is improved. still,
Figure 7 shows the near-infrared absorption spectrum of apple fruits.
(A) is an original spectrum and (b) is a second derivative spectrum.
【００３４】また、この場合、式は、糖に帰属する波長
の吸光度と、糖と所定の関係にある要素に帰属する波長
の吸光度とを用いていることから、互いに一次独立の関
係にある２変数の検量線になり、それだけ、精度の高い
糖度を算出できる。Further, in this case, since the formula uses the absorbance at the wavelength attributed to the sugar and the absorbance at the wavelength attributed to the element having a predetermined relationship with the sugar, they are in a primary independent relationship with each other. It becomes a calibration curve of variables, and the sugar content can be calculated with high accuracy.
【００３５】更に、糖に帰属する波長及び糖と所定の関
係にある要素に帰属する波長を予め定めたので、測定す
るりんごの種類，産地や栽培方法が異なっても、同一の
検量線を用いて糖度の測定をすることが可能になる。従
って、種類，産地や栽培方法が異なっても、逐一測定波
長を選択しなくても良く、それだけ、測定作業の効率化
が図られる。Further, since the wavelength attributed to sugar and the wavelength attributed to the element having a predetermined relationship with sugar are predetermined, the same calibration curve is used even if the kind of apple to be measured, the place of origin and the cultivation method are different. Therefore, it becomes possible to measure the sugar content. Therefore, even if the type, production area, and cultivation method are different, it is not necessary to select the measurement wavelength one by one, and the efficiency of the measurement work can be improved accordingly.
【００３６】次に、上記装置による実験結果を示す。図
８は、りんごの種類「ふじ」において、検体４０個を測
定したときの、ＮＩＲ値（上記数式１で演算された推定
糖度）と手分析値（実測値）との相関を示すグラフであ
る。この場合、相関係数は０．９４となり、非常に高い
値を示す。Next, experimental results obtained by the above apparatus will be shown. FIG. 8 is a graph showing the correlation between the NIR value (estimated sugar content calculated by the above formula 1) and the manual analysis value (actual measurement value) when 40 samples were measured in the apple type “Fuji”. . In this case, the correlation coefficient is 0.94, which is a very high value.
【００３７】これを従来方法と比較してみる。図９は、
波長９１２ｎｍと波長８８８ｎｍにおける吸光度を用
い、従来の方法と同様の方法によって、りんごの種類
「ふじ」において、検体４０個を測定したときの、ＮＩ
Ｒ値と手分析値との相関を示すグラフである。これによ
れば、相関係数が０．６６と低いものになっている。そ
のため、本実施例の測定方法が、上記のバックグラウン
ドによるノイズの影響を低減させること等により、精度
の向上が図られていることが知られる。This will be compared with the conventional method. Figure 9
Using the absorbances at the wavelengths of 912 nm and 888 nm, the NI of the 40 types of apples of "Fuji" was measured by the same method as the conventional method.
It is a graph which shows the correlation of R value and a manual analysis value. According to this, the correlation coefficient is as low as 0.66. Therefore, it is known that the measurement method of the present embodiment improves accuracy by reducing the influence of noise due to the above background.
【００３８】また、図１０は、りんごの種類「スターキ
ング」において、検体４０個を測定したときの、ＮＩＲ
値と手分析値との相関を示すグラフである。図１１は、
りんごの種類「ふじ」と「スターキング」との混合にお
いて、検体８０個を測定したときの、ＮＩＲ値と手分析
値との相関を示すグラフである。この図から他の種類に
おいても高い相関をうることができることが分かる。即
ち、予め普遍的に定めた波長における吸光度を算出する
ようにしているので、測定するりんごが異なっても、逐
一測定波長を選択して検量線を決定し直さなくても良
く、同一検量線を用いて測定することが可能になる。FIG. 10 shows the NIR when 40 samples were measured in the apple type “Starking”.
It is a graph which shows the correlation of a value and a manual analysis value. FIG. 11 shows
It is a graph which shows the correlation of a NIR value and a manual analysis value when 80 samples are measured in the mixture of apple types "Fuji" and "Starking". From this figure, it can be seen that high correlation can be obtained in other types. That is, since the absorbance at a wavelength universally determined in advance is calculated, even if the apples to be measured are different, it is not necessary to select the measurement wavelength one by one and redetermine the calibration curve. It becomes possible to measure using.
【００３９】そして、判定部１４においては、上記演算
された糖度が、例えばＡ，Ｂ，Ｃランクの３段階のう
ち、どのランクに所属するかが判定される。また、この
判定結果は、上記表示部７のランプ１６に表示される。
更に。上記選別機８は、判定部１４の判定結果に基づい
て、例えばＡ，Ｂ，Ｃランクにランクづけされたりんご
を、ランクごとに仕分する。Then, the judging unit 14 judges to which rank the calculated sugar content belongs, for example, of the three ranks A, B and C. Further, the result of this determination is displayed on the lamp 16 of the display unit 7.
Furthermore. The sorter 8 sorts apples ranked, for example, A, B, and C ranks according to the determination result of the determination unit 14 for each rank.
【００４０】[0040]
【００４１】[0041]
【発明の効果】以上説明したように、本発明の青果物の
糖度測定方法及び糖度測定装置によれば、糖に帰属する
９１２ｎｍの波長の吸光度と、糖へ帰属しないとされる
８８８ｎｍの波長の吸光度とを測定し、これらの吸光度
の二次微分値を演算し、この演算結果に基づいて青果物
の糖度を算出するので、二次微分値を用いることから原
スペクトルをデータとする場合に比較して、バックグラ
ウンドによるノイズが消去されたデータとすることがで
き、それだけ、糖度の推定精度を向上させることができ
る。特に、青果物としてのりんごにおいて極めて有用に
なる。As described above, according to the sugar content measuring method and sugar content measuring apparatus of the present invention, the absorbance at a wavelength of 912 nm which is attributed to sugar and the absorbance at a wavelength of 888 nm which is not attributed to sugar are obtained. Is measured, and the second derivative of these absorbances is calculated, and the sugar content of fruits and vegetables is calculated based on this calculation result, so compared to the case where the original spectrum is used as data, since the second derivative is used. The data obtained by eliminating the noise due to the background can be improved, and the estimation accuracy of the sugar content can be improved accordingly. In particular, it becomes extremely useful in apples as fruits and vegetables.
【００４２】また、糖に帰属する９１２ｎｍの波長の吸
光度と、糖へ帰属しないとされる８８８ｎｍの波長の吸
光度とを用いることになるので、互いに一次独立の関係
にある２変数の固定の検量線を作成することができ、そ
れだけ、精度の高い糖度を算出できる。Further, since the absorbance at the wavelength of 912 nm that is attributed to sugar and the absorbance at the wavelength of 888 nm that is not attributed to sugar are used, a fixed calibration curve of two variables that are linearly independent of each other is used. Can be created, and the sugar content can be calculated with high accuracy.
【００４３】更に、糖に帰属する波長を９１２ｎｍに固
定し、糖へ帰属しないとされる波長を８８８ｎｍに固定
したので、特にりんごである青果物において、測定する
青果物の種類，産地や栽培方法などが異なっても、同一
の検量線を用いて糖度の測定をすることが可能になる。
従って、種類，産地や栽培方法などが異なっても、従来
のように逐一測定波長を選択しなくても良く、それだ
け、測定作業の効率化を図ることができる。Furthermore, since the wavelength attributed to sugar was fixed at 912 nm and the wavelength not attributed to sugar was fixed at 888 nm, the types of fruits and vegetables to be measured, the place of origin, the cultivation method, etc., were measured especially for fruits and vegetables that are apples. Even if they are different, it becomes possible to measure the sugar content using the same calibration curve.
Therefore, even if the type, production area, cultivation method, etc. are different, it is not necessary to select the measurement wavelength one by one as in the conventional case, and the efficiency of the measurement work can be improved accordingly.
【００４４】即ち、本発明によれば、特にりんご青果物
の糖度に有効な波長を、波長の帰属を考慮して決定した
ので、良好な精度で非破壊で青果物の糖度を測定でき
る。これにより、青果物の選別ラインに導入することに
より、青果物の全数検査を可能にすることができる。That is, according to the present invention, since the wavelength effective for the sugar content of apples and fruits is determined in consideration of the attribution of wavelength, the sugar content of fruits and vegetables can be measured non-destructively with good accuracy. With this, by introducing it into the selection line for fruits and vegetables, it is possible to inspect all fruits and vegetables.
【図１】本発明の実施例に係る糖度測定装置を示すブロ
ック図である。FIG. 1 is a block diagram showing a sugar content measuring apparatus according to an embodiment of the present invention.
【図２】本発明の実施例に係る糖度測定装置の要部を示
すブロック図である。FIG. 2 is a block diagram showing a main part of a sugar content measuring apparatus according to an embodiment of the present invention.
【図３】りんご「ふじ」における糖度の相関図である。FIG. 3 is a correlation diagram of sugar content in apple “Fuji”.
【図４】ショ糖水溶液の相関図である。FIG. 4 is a correlation diagram of an aqueous sucrose solution.
【図５】果糖水溶液の相関図である。FIG. 5 is a correlation diagram of a fructose aqueous solution.
【図６】ブドウ糖水溶液の相関図である。FIG. 6 is a correlation diagram of a glucose aqueous solution.
【図７】りんご果実の近赤外吸収スペクトルを示す図で
ある。FIG. 7 is a diagram showing a near-infrared absorption spectrum of apple fruits.
【図８】りんご「ふじ」におけるＮＩＲ値と手分析値と
の相関を示すグラフである。FIG. 8 is a graph showing the correlation between the NIR value and the manual analysis value of apple “Fuji”.
【図９】従来の方法と同様の方法によって測定したりん
ご「ふじ」におけるＮＩＲ値と手分析値との相関を示す
グラフである。FIG. 9 is a graph showing the correlation between the NIR value and the manual analysis value of apple “Fuji” measured by the same method as the conventional method.
【図１０】りんご「スターキング」におけるＮＩＲ値と
手分析値との相関を示すグラフである。FIG. 10 is a graph showing the correlation between the NIR value and the manual analysis value in the apple “Starking”.
【図１１】りんごの種類「ふじ」と「スターキング」と
の混合におけるＮＩＲ値と手分析値との相関を示す図で
ある。FIG. 11 is a diagram showing a correlation between an NIR value and a manual analysis value in a mixture of apple types “Fuji” and “Starking”.
１ 被検対象 ３ 照射部 ４ 光源 ５ 分光器 ６ 受光部 ７ 表示部 ８ 選別機 １０ 制御部 １１ 吸光度算出部 １２ 二次微分演算部 １３ 糖度演算部 １４ 判定部 DESCRIPTION OF SYMBOLS 1 Test object 3 Irradiation part 4 Light source 5 Spectroscope 6 Light receiving part 7 Display part 8 Sorting machine 10 Control part 11 Absorbance calculation part 12 Second derivative calculation part 13 Sugar content calculation part 14 Judgment part
───────────────────────────────────────────────────── フロントページの続き (72)発明者 篠木 藤敏 青森県青森市大字八ツ役字芦谷202−４ 青森県産業技術開発センター 内 (72)発明者 対馬 武夫 青森県弘前市大字金属町５番地１ 東和電 機工業株式会社 内 (56)参考文献 特開 昭64−28544（ＪＰ，Ａ) 特開 平２−271254（ＪＰ，Ａ) 特開 平１−301147（ＪＰ，Ａ) 特開 平１−131436（ＪＰ，Ａ) 特開 平３−15741（ＪＰ，Ａ) ─────────────────────────────────────────────────── ─── Continuation of the front page (72) Inventor Fujitoshi Shino Aomori City, Aomori Prefecture Yatsu Yatsu, Ashiya 202-4 Aomori Industrial Technology Development Center (72) Inventor Takeo Tsushima 5 Hirosaki City, Aomori Prefecture Address 1 Towa Denki Kogyo Co., Ltd. (56) Reference JP-A 64-28544 (JP, A) JP-A 2-271254 (JP, A) JP-A 1-301147 (JP, A) JP-A 1-131436 (JP, A) JP-A-3-15741 (JP, A)
Claims (2)
２５００ｎｍ以下の近赤外領域の波長に対する吸光度を
測定し、この測定値から青果物の糖度を測定する糖度測
定方法において、糖に帰属する９１２ｎｍの波長の吸光
度と、糖へ帰属しないとされる８８８ｎｍの波長の吸光
度とを測定し、これらの吸光度の二次微分値を演算し、
この演算結果に基づいて青果物の糖度を算出することを
特徴とする青果物の糖度測定方法。1. Receiving reflected light from the fruits and vegetables to be inspected,
In the sugar content measuring method of measuring the absorbance for wavelengths in the near-infrared region of 2500 nm or less and measuring the sugar content of fruits and vegetables from this measurement value, the absorbance at the wavelength of 912 nm that is attributed to sugar and that of 888 nm that is not attributed to sugar Measure the absorbance of the wavelength, calculate the second derivative of these absorbances,
A method for measuring the sugar content of fruits and vegetables, which comprises calculating the sugar content of fruits and vegetables based on the result of this calculation.
赤外領域の波長の光を含む光を照射する光源部と、この
青果物からの反射光を受光する受光部と、照射光及び反
射光のいずれかを糖に帰属する９１２ｎｍの波長の光及
び糖へ帰属しないとされる８８８ｎｍの波長の光に分光
する分光器と、受光部が受光した反射光から糖に帰属す
る９１２ｎｍの波長の吸光度及び糖へ帰属しないとされ
る８８８ｎｍの波長の吸光度を算出する吸光度算出部
と、これらの吸光度の二次微分値を演算する二次微分演
算部と、この演算された二次微分値を用いて、以下の数
式１により、青果物の糖度を演算する糖度演算部とを備
えたことを特徴とする青果物の糖度測定装置。 数式１において、λは波長、Ａ１（λ１）は糖に帰属す
る波長λ１（９１２ｎｍ）の吸光度、Ａ２（λ２）は糖
へ帰属しないとされる波長λ２（８８８ｎｍ）の吸光
度、Ｋ０，Ｋ１，Ｋ２は、充分に多い母集団において測
定された吸光度及び実測糖度を用いて最小二乗法で決定
された係数である。 【数１】 Ｃ：糖度 λ：波長 Ａ1（λ1）：波長λ1における吸光度 Ａ2（λ2）：波長λ2における吸光度 Ｋ０，Ｋ１，Ｋ２：係数2. A light source section for irradiating the fruits and vegetables to be inspected with light containing light having a wavelength in the near infrared region of 2500 nm or less, a light receiving section for receiving reflected light from the fruits and vegetables, and irradiation light and reflected light. A spectroscope for splitting any of the above into light having a wavelength of 912 nm that is attributed to sugar and light having a wavelength of 888 nm that is not attributed to sugar, and the absorbance of the wavelength of 912 nm that is attributed to sugar from the reflected light received by the light receiving unit. And an absorbance calculator that calculates the absorbance at a wavelength of 888 nm that is not attributed to sugar, a secondary differential calculator that calculates the secondary differential values of these absorbances, and the calculated secondary differential value. A sugar content measuring device for fruits and vegetables, comprising: a sugar content calculating unit that calculates the sugar content of fruits and vegetables according to the following formula 1. In Formula 1, λ is the wavelength, A1 (λ1) is the absorbance of the wavelength λ1 (912 nm) that belongs to the sugar, A2 (λ2) is the absorbance of the wavelength λ2 (888 nm) that does not belong to the sugar, K0, K1, K2 Is the coefficient determined by the least squares method using the measured absorbance and the measured sugar content in a sufficiently large population. [Equation 1] C: sugar content λ: wavelength A 1 (λ 1 ): absorbance at wavelength λ 1 A 2 (λ 2 ): absorbance at wavelength λ 2 K0, K1, K2: coefficients
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP40460290A JPH0792433B2 (en) | 1990-12-03 | 1990-12-03 | Measuring method for sugar content of fruits and vegetables and sugar content measuring device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP40460290A JPH0792433B2 (en) | 1990-12-03 | 1990-12-03 | Measuring method for sugar content of fruits and vegetables and sugar content measuring device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| JPH04208842A JPH04208842A (en) | 1992-07-30 |
| JPH0792433B2 true JPH0792433B2 (en) | 1995-10-09 |
Family
ID=18514266
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP40460290A Expired - Fee Related JPH0792433B2 (en) | 1990-12-03 | 1990-12-03 | Measuring method for sugar content of fruits and vegetables and sugar content measuring device |
Country Status (1)
| Country | Link |
|---|---|
| JP (1) | JPH0792433B2 (en) |
Families Citing this family (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH0868751A (en) * | 1994-08-30 | 1996-03-12 | Sumitomo Metal Mining Co Ltd | Non-destructive measurement of sugar content of fruit |
| US5708271A (en) * | 1994-12-28 | 1998-01-13 | Sumitomo Metal Mining Co., Ltd. | Non-destructive sugar content measuring apparatus |
| US5726750A (en) * | 1995-06-29 | 1998-03-10 | Sumitomo Metal Mining Co., Ltd. | Non-destructive taste characteristics measuring apparatus and tray used in the apparatus |
| US5844678A (en) * | 1995-06-29 | 1998-12-01 | Sumitomo Metal Mining Co. Ltd. | Non-destructive taste characteristics measuring apparatus and tray used in the apparatus |
| JP2002014042A (en) | 2000-04-24 | 2002-01-18 | Sumitomo Metal Mining Co Ltd | Nondestructive sugar-level measuring apparatus |
| JP4674309B2 (en) * | 2005-08-18 | 2011-04-20 | 国立大学法人三重大学 | Food taste information acquisition device |
| WO2011074217A1 (en) * | 2009-12-18 | 2011-06-23 | パナソニック株式会社 | Component concentration meter, component concentration measurement method, shipping inspection system, and health management system |
| JP5626982B2 (en) * | 2010-10-01 | 2014-11-19 | ヤンマー株式会社 | Quality assessment method for fruits and vegetables |
| JP2013113617A (en) * | 2011-11-25 | 2013-06-10 | Sumitomo Electric Ind Ltd | Component amount measuring method |
| JP6744015B2 (en) * | 2016-02-19 | 2020-08-19 | 株式会社ハウス食品分析テクノサービス | Method for estimating the time when foreign matter is mixed |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPS6428544A (en) * | 1987-07-23 | 1989-01-31 | Mitsui Mining & Smelting Co | Method and apparatus for measuring quality of fruit |
| JPH01301147A (en) * | 1988-05-28 | 1989-12-05 | Mitsui Mining & Smelting Co Ltd | Method and device for measuring quality of vegitable and fruit |
| JPH0629851B2 (en) * | 1989-04-13 | 1994-04-20 | 株式会社ニレコ | Eating value estimation method |
-
1990
- 1990-12-03 JP JP40460290A patent/JPH0792433B2/en not_active Expired - Fee Related
Also Published As
| Publication number | Publication date |
|---|---|
| JPH04208842A (en) | 1992-07-30 |
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