JP6403872B2 - Fruit and vegetable inspection equipment - Google Patents
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- 238000007689 inspection Methods 0.000 title claims description 133
- 235000012055 fruits and vegetables Nutrition 0.000 title claims description 128
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 57
- 238000003384 imaging method Methods 0.000 claims description 43
- 238000010521 absorption reaction Methods 0.000 claims description 38
- 235000013399 edible fruits Nutrition 0.000 claims description 23
- 238000004458 analytical method Methods 0.000 claims description 21
- 230000005856 abnormality Effects 0.000 claims description 13
- 230000001678 irradiating effect Effects 0.000 claims description 4
- 235000013311 vegetables Nutrition 0.000 claims 4
- 235000020971 citrus fruits Nutrition 0.000 description 8
- 208000024891 symptom Diseases 0.000 description 7
- 240000006829 Ficus sundaica Species 0.000 description 6
- 238000010586 diagram Methods 0.000 description 6
- 238000010191 image analysis Methods 0.000 description 6
- 241001672694 Citrus reticulata Species 0.000 description 5
- 238000002835 absorbance Methods 0.000 description 5
- 238000000034 method Methods 0.000 description 5
- 244000144730 Amygdalus persica Species 0.000 description 4
- 235000006040 Prunus persica var persica Nutrition 0.000 description 4
- 241000220324 Pyrus Species 0.000 description 4
- 235000021017 pears Nutrition 0.000 description 4
- 206010052428 Wound Diseases 0.000 description 3
- 208000027418 Wounds and injury Diseases 0.000 description 3
- 238000001228 spectrum Methods 0.000 description 3
- 241000894006 Bacteria Species 0.000 description 2
- 241000207199 Citrus Species 0.000 description 2
- 244000061508 Eriobotrya japonica Species 0.000 description 2
- 235000009008 Eriobotrya japonica Nutrition 0.000 description 2
- 229910000530 Gallium indium arsenide Inorganic materials 0.000 description 2
- 244000141359 Malus pumila Species 0.000 description 2
- 230000002159 abnormal effect Effects 0.000 description 2
- 235000021016 apples Nutrition 0.000 description 2
- 230000004069 differentiation Effects 0.000 description 2
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 2
- 238000001035 drying Methods 0.000 description 2
- 229910052736 halogen Inorganic materials 0.000 description 2
- 150000002367 halogens Chemical class 0.000 description 2
- 235000021018 plums Nutrition 0.000 description 2
- 235000002233 Penicillium roqueforti Nutrition 0.000 description 1
- 230000000740 bleeding effect Effects 0.000 description 1
- 239000003086 colorant Substances 0.000 description 1
- 230000006378 damage Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000002950 deficient Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 230000006866 deterioration Effects 0.000 description 1
- 201000010099 disease Diseases 0.000 description 1
- 238000005286 illumination Methods 0.000 description 1
- 230000031700 light absorption Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000035945 sensitivity Effects 0.000 description 1
- 230000003595 spectral effect Effects 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 239000002344 surface layer Substances 0.000 description 1
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- 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
- G01N21/3554—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light for determining moisture content
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- 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
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- 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
- G01N21/84—Systems specially adapted for particular applications
- G01N21/85—Investigating moving fluids or granular solids
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- Physics & Mathematics (AREA)
- Spectroscopy & Molecular Physics (AREA)
- General Health & Medical Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- Life Sciences & Earth Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Health & Medical Sciences (AREA)
- Investigating Or Analysing Materials By Optical Means (AREA)
- Investigating Materials By The Use Of Optical Means Adapted For Particular Applications (AREA)
Description
本発明は、例えば、柑橘類の果皮表面に現れる水腐れや、果皮の異常乾燥など、青果物の果皮表面及び果皮内部の異常の有無を検査するための青果物検査装置に関する。 The present invention relates to a fruit and vegetable inspection apparatus for inspecting the presence or absence of abnormality in the fruit skin surface and inside the fruit skin, such as water rot appearing on the citrus fruit skin surface or abnormal drying of the fruit skin.
柑橘類では、果皮に傷が付いた際に、その傷から菌が入り込み、雨や露などにより長期にわたり果皮表面が濡れた状態となり、また、２５度前後の環境温度の条件下において、水腐れ病と呼ばれる症状が現れることがある。 In citrus fruits, when the skin is damaged, bacteria enter the skin and the surface of the skin becomes wet for a long time due to rain, dew, etc. Also, water rot disease under conditions of ambient temperature around 25 degrees Symptoms called may appear.
水腐れの具体的症状としては、柑橘類の果皮が膨潤したような状態となり、発生部位から腐敗が果皮の広範囲に拡大し、カビが生じたり、乾燥腐れとなったりすることもある。 As specific symptoms of water rot, the citrus peel becomes swollen, and the rot spreads from the generation site to a wide area of the peel, causing mold or dry rot.
このため、水腐れの生じた柑橘類を、正常品と混載梱包した場合、正常品まで腐敗させてしまう恐れがあることから、商品の品質を確保するためにも、水腐れの生じた個体を、選果段階で排除することが望まれている。 For this reason, when citrus fruits with water rot are mixed and packed with normal products, there is a risk of rot to normal products, so in order to ensure the quality of the product, It is desired to eliminate it at the selection stage.
水腐れの初期症状とも言える果皮の傷、特に発生直後の生傷については、特許文献１，２に開示されるように、紫外線照射により、可視領域の蛍光を発する物質由来の特定蛍光波長を検出することによる画像検査が行われている。 For the wounds of the skin, which can be said to be the initial symptom of water rot, especially for wounds immediately after the occurrence, as disclosed in Patent Documents 1 and 2, a specific fluorescence wavelength derived from a substance emitting fluorescence in the visible region is detected by ultraviolet irradiation. Image inspection is performed.
このような水腐れ、カビ及び乾燥腐れの初期症状である果皮の傷を検出することで、選果工程において不良品の流出をある程度防ぐことはできるが、例えば、選果工程の時点で既に水腐れが生じてしまっている青果物の場合、水腐れが進むにつれて果皮が膨らむことで、果皮表面の傷が隠れてしまい、特許文献１，２に開示されるような画像検査では水腐れの生じた青果物を検出することができないことがある。 By detecting such scratches on the skin, which are the initial symptoms of water rot, mold and dry rot, it is possible to prevent defective products from leaking to some extent in the fruit selection process. In the case of fruits and vegetables that have rotted, the skin swells as water rot progresses, so that the skin surface scratches are hidden, and water rot has occurred in the image inspection disclosed in Patent Documents 1 and 2. Fruits and vegetables may not be detected.
また、水腐れ、カビ及び乾燥腐れの有無を検査する方法としては、例えば、特許文献３に開示されるように、青果物に対して、ハロゲンランプ等の照明ランプより光を照射し、青果物からの反射光を撮像用カメラによって撮像することで、青果物の変色又は腐敗した部分の有無を検出する方法が知られている。 In addition, as a method for inspecting the presence of water rot, mold and dry rot, for example, as disclosed in Patent Document 3, the fruit and vegetables are irradiated with light from an illumination lamp such as a halogen lamp, There is known a method for detecting the presence or absence of a discolored or corrupt portion of fruit and vegetables by imaging reflected light with an imaging camera.
また、特許文献４に開示されるように、青果物の下方から投光手段により検査用光を照射するとともに、上方に配置されたＣＣＤカメラにより青果物を撮像し、画像に含まれる３原色（Ｒ，Ｇ，Ｂ）の各々が示す画像信号を利用して、腐敗部の存否により透過光の光量の差が画像信号の差異として現れやすいＲ信号と、現れにくいＧ信号、Ｂ信号との差分値に基づき、腐敗部の存否を検出する方法も知られている。 Further, as disclosed in Patent Document 4, the light for inspection is irradiated from below the fruits and vegetables by the light projecting means, and the fruits and vegetables are picked up by the CCD camera disposed above, and the three primary colors (R, R, G, B) are used to obtain the difference value between the R signal, in which the difference in the amount of transmitted light is likely to appear as a difference in the image signal, and the G signal, B signal, which are difficult to appear, depending on the presence or absence of the decayed portion. Based on this, a method for detecting the presence or absence of a rot portion is also known.
しかしながら、特許文献３に開示された方法では、撮像用カメラにより撮像された画像の彩度、色度、明度を用いて検査を行うため、柑橘類の青カビなどのように可視光に変化を生じる不良については適しているが、水腐れや乾燥腐れのように、正常部位と腐敗部位とに彩度、色度、明度の差がほとんど生じない場合には、正確な判別が困難であり、腐敗品を正常品と判断してしまうことがあった。 However, in the method disclosed in Patent Document 3, since the inspection is performed using the saturation, chromaticity, and brightness of the image captured by the imaging camera, a defect that causes a change in visible light such as citrus blue mold. However, when there is almost no difference in saturation, chromaticity, and lightness between normal and rotting parts, such as water rot and dry rot, it is difficult to make an accurate determination. May be judged as a normal product.
また、特許文献４に開示された水腐れ検出方法では、ＣＣＤカメラにより可視光に基づく画像を撮影しており、画像に含まれるＲ信号は、約５５０ｎｍ〜７００ｎｍの波長域の平均的な光量を検出しているに過ぎない。 Further, in the water rot detection method disclosed in Patent Document 4, an image based on visible light is taken by a CCD camera, and an R signal included in the image has an average light amount in a wavelength range of about 550 nm to 700 nm. It is only detecting.
このため、近年の市場で要求されるような直径１０ｍｍ程度の微小な水腐れや乾燥腐れなどを検出するには感度が低く、充分な検査を行うことができない。 For this reason, the sensitivity is low to detect minute water rot or dry rot of about 10 mm in diameter as required in the recent market, and sufficient inspection cannot be performed.
本発明では、このような現状に鑑み、青果物の果皮表面及び果皮内部に存在する腐敗部や傷などの異常を正確に検出し、また、微小な水腐れであっても検出することができる青果物検査装置を提供することを目的とする。 In the present invention, in view of the current situation, fruits and vegetables that can accurately detect abnormalities such as rot and scratches existing on the surface and inside of the skin of fruits and vegetables, and can detect even minute water rot. An object is to provide an inspection device.
本発明は、前述するような従来技術における課題を解決するために発明されたものであって、本発明の青果物検査装置は、
青果物の異常の有無を判別するための青果物検査装置であって、
前記青果物に対して検査光を照射する投光手段と、
前記検査光により前記青果物を撮像する撮像手段と、
前記撮像手段により撮像された前記青果物の検査画像に基づき、前記青果物の異常の有無を検出する解析手段と、を備え、
前記投光手段は、少なくとも水の吸収波長を含む光が照射可能であり、
前記解析手段は、前記水の吸収波長の光に基づく検査画像を用いて、前記青果物の異常の有無を検出するように構成されていることを特徴とする。The present invention was invented in order to solve the problems in the prior art as described above.
A fruit and vegetable inspection apparatus for determining the presence or absence of abnormality of fruit and vegetables,
A light projecting means for irradiating the fruit and vegetables with inspection light;
Imaging means for imaging the fruits and vegetables with the inspection light;
Analysis means for detecting the presence or absence of abnormality of the fruits and vegetables based on the inspection image of the fruits and vegetables imaged by the imaging means,
The light projecting means can be irradiated with light including at least the absorption wavelength of water,
The analysis means is configured to detect the presence or absence of abnormality of the fruits and vegetables using an inspection image based on the light having an absorption wavelength of water.
この場合、前記撮像手段が、撮像素子としてＩｎＧａＡｓフォトダイオードを用いていることが好ましい。 In this case, it is preferable that the imaging means uses an InGaAs photodiode as an imaging element.
また、前記撮像手段は、前記投光手段から照射された検査光が前記青果物に反射した反射光により、前記青果物の検査画像を撮像することができる。 Further, the imaging means can take an inspection image of the fruits and vegetables with reflected light obtained by reflecting the inspection light emitted from the light projecting means on the fruits and vegetables.
また、前記撮像手段は、前記投光手段から照射された検査光が前記青果物を透過した透過光により、前記青果物の検査画像を撮像することができる。 Further, the imaging means can take an inspection image of the fruits and vegetables with transmitted light obtained by transmitting the inspection light emitted from the light projecting means through the fruits and vegetables.
また、本発明の青果物検査装置では、前記青果物の異常として、前記青果物の果皮表層及び／又は果皮下に現れる水分の増減に関連する障害を検出することができる。 Moreover, in the fruit and vegetable inspection apparatus of this invention, the disorder | damage | failure related to the increase / decrease in the water | moisture content which appears on the fruit skin surface layer and / or under the fruit skin as said fruit and fruit abnormality can be detected.
本発明によれば、水の吸収波長の光に基づく検査画像を用いることによって、可視光に基づく画像では判別しにくい、青果物の水腐れなどであっても、正常部位と腐敗部位とに明らかなコントラストを生じさせ、容易かつ正確に判別することができる。 According to the present invention, by using an inspection image based on light having an absorption wavelength of water, even in the case of water rot of fruits and vegetables, which is difficult to discriminate in an image based on visible light, it is clear that the normal portion and the rotting portion. Contrast is generated and can be easily and accurately determined.
以下、本発明の実施の形態（実施例）を図面に基づいてより詳細に説明する。 Hereinafter, embodiments (examples) of the present invention will be described in more detail with reference to the drawings.
図１は、本発明の青果物検査装置の一実施例における構成を説明するための概略構成図である。 FIG. 1 is a schematic configuration diagram for explaining the configuration of an embodiment of the fruit and vegetable inspection apparatus of the present invention.
図１に示すように、本実施例の青果物検査装置１０は、被測定対象である青果物Ｓに検査光を照射する投光手段１２と、青果物Ｓに反射した検査光（反射光）により青果物Ｓを撮像する撮像手段１４と、撮像手段１４により撮像された青果物Ｓの検査画像に基づき青果物Ｓの腐敗部位を検出する解析手段１６とを備えている。 As shown in FIG. 1, the fruit and vegetable inspection apparatus 10 of the present embodiment includes a light projecting unit 12 that irradiates inspection light onto the fruit and vegetable S to be measured, and an inspection light (reflected light) reflected by the fruit and vegetable S. Imaging means 14 for picking up images of the fruits and vegetables S, and analysis means 16 for detecting the rot portion of the fruits and vegetables S based on the inspection image of the fruits and vegetables S taken by the imaging means 14.
なお、本実施例において、青果物Ｓとしては、特に限定されるものではないが、例えば、蜜柑や橘などの柑橘類、梨、桃、ビワ、スモモ、リンゴなどとすることができる。 In the present embodiment, the fruits and vegetables S are not particularly limited, but can be, for example, citrus fruits such as mandarin oranges and citrus fruits, pears, peaches, loquats, plums, and apples.
また、このような青果類Ｓとした場合、本実施例の青果物検査装置１０では、例えば、柑橘類などに見られる水腐れ、梨などに見られる水果、桃、ビワ、スモモ、リンゴなどに見られる押せ痕などを検査することができる。 Further, in the case of such fruits and vegetables S, in the fruits and vegetables inspection apparatus 10 of this embodiment, for example, water rot found in citrus fruits, water fruits found in pears, peaches, loquats, plums, apples, etc. It is possible to inspect the press marks.
ここで「水腐れ」とは、上述するように、果皮に傷が付いた際に、その傷から菌が入り込み、雨や露などにより長期にわたり果皮表面が濡れた状態で、２５度前後の環境温度の条件下において現れる、果皮が膨潤したような状態となる症状である。 Here, “water rot” means that when the skin is damaged, as described above, bacteria enter the wound, and the surface of the skin is wet for a long time due to rain or dew. It is a symptom that appears as if the pericarp swells, appearing under temperature conditions.
また、「水果」とは、果肉が水浸した状態となる症状である。程度が酷くなると果肉が褐色を帯びた状態となる。 In addition, “water fruit” is a symptom in which the pulp is immersed in water. When the degree becomes severe, the pulp becomes brownish.
また、「押せ痕」とは、青果物同士の接触などによって青果物表面に局部的な圧力が加わることで、青果物の果肉組織が破壊され、果皮と果肉の間に果肉組織から染み出した水分が存在する状態（いわば、人体でいう内出血の状態）が現れる症状である。 In addition, “pressing marks” are the result of local pressure being applied to the surface of fruits and vegetables by contact between the fruits and vegetables, destroying the flesh tissue of the fruits and vegetables, and moisture exuded from the flesh tissue between the peel and the flesh. This is a symptom in which a state to perform (in other words, a state of internal bleeding in the human body) appears.
なお、本実施例の青果物検査装置１０は、このような障害の検査に限らず、例えば、果肉細胞が破壊されることで果皮表層及び／又は果皮下に現れる、水分の増減に関連する障害全般について検査することが可能である。 The fruit and vegetable inspection apparatus 10 according to the present embodiment is not limited to the inspection of such a failure, but, for example, is a general failure related to the increase or decrease of water that appears in the skin surface and / or under the skin when the pulp cell is destroyed. It is possible to check for.
投光手段１２としては、９００ｎｍ〜２０００ｎｍの近赤外光であって、水の吸収波長を含む光を照射可能なものであれば特に限定されるものではなく、例えば、ハロゲンランプやＬＥＤ光源を用いることができる。なお、ＬＥＤ光源としては、白色光を照射するものであってもよいが、特定波長の光のみを照射するものとすることもできる。 The light projecting means 12 is not particularly limited as long as it is near infrared light of 900 nm to 2000 nm and can irradiate light including the absorption wavelength of water. For example, a halogen lamp or LED light source is used. Can be used. The LED light source may be one that emits white light, but may be one that emits only light of a specific wavelength.
なお、水の吸収波長としては、９６０ｎｍ、１１５０ｎｍ、１４５０ｎｍ、１９４０ｎｍが知られているが、水の吸収波長は特定波長ではなく、広い波長帯として存在していることから、水による吸収が確認できれば、多少前後した波長を利用しても構わない。 In addition, although the absorption wavelength of water is known as 960 nm, 1150 nm, 1450 nm, and 1940 nm, since the absorption wavelength of water is not a specific wavelength but exists as a wide wavelength band, if absorption by water can be confirmed A wavelength slightly around may be used.
撮像手段１４としては、投光手段１２により照射された波長の検査光に基づく画像を撮像可能なものであれば特に限定されるものではなく、エリアカメラ、ラインカメラ、イメージング分光器、マルチバンドカメラなどを用いることができる。特に、撮像手段１４の撮像素子として、９００ｎｍ〜２０００ｎｍの近赤外光を検出することができる、例えば、ＩｎＧａＡｓ、Ｇｅ、ＰｂＳなどのフォトダイオードを用いたものであることが好ましい。 The imaging unit 14 is not particularly limited as long as it can capture an image based on the inspection light having the wavelength irradiated by the light projecting unit 12, and is not limited to an area camera, a line camera, an imaging spectrometer, and a multiband camera. Etc. can be used. In particular, it is preferable to use a photodiode such as InGaAs, Ge, or PbS that can detect near-infrared light of 900 nm to 2000 nm as the imaging device of the imaging unit 14.
なお、青果物Ｓと撮像手段１４との間に、所定の波長の光のみを透過するバンドパスフィルタ１８を設けることもできる。 Note that a band-pass filter 18 that transmits only light of a predetermined wavelength may be provided between the fruit and vegetables S and the imaging unit 14.
このように構成することで、撮像手段１４が必要な波長の光だけを受光することができ、画像解析に不要な波長の光を受光しないため、ノイズを低減することができる。 With this configuration, the imaging unit 14 can receive only light having a necessary wavelength and does not receive light having a wavelength unnecessary for image analysis, so that noise can be reduced.
本実施例の青果物検査装置１０では、青果物Ｓに対して投光手段１２より検査光を照射するとともに、青果物Ｓからの反射光を用いて撮像手段１４により青果物Ｓを撮像して検査画像を取得している。 In the fruit and vegetable inspection apparatus 10 of the present embodiment, the fruit and vegetables S are irradiated with inspection light from the light projecting means 12 and the fruit and vegetables S are picked up by the imaging means 14 using the reflected light from the fruits and vegetables S to obtain an inspection image. doing.
検査画像の各画素値は、撮像手段１４が受光した検査光の光量Ｌに基づいて決定することもできるが、本実施例では、下記式（１）で表すように、青果物Ｓからの反射光と、あらかじめ取得している入射光を照射し得られた標準体（例えば、グレーチャートなど）からの反射光との比率として算出された青果物Ｓの反射比に基づいて検査画像の各画素値を決定している。なお、下記式（２）で表すように、算出された反射比から見かけ上の吸光度に基づき画素値を決定するようにしてもよい。 Each pixel value of the inspection image can be determined based on the light amount L of the inspection light received by the imaging unit 14, but in this embodiment, the reflected light from the fruits and vegetables S is expressed by the following equation (1). And each pixel value of the inspection image based on the reflection ratio of the fruits and vegetables S calculated as a ratio to the reflected light from a standard body (for example, a gray chart) obtained by irradiating incident light acquired in advance. Has been decided. In addition, as represented by the following formula (2), the pixel value may be determined based on the apparent absorbance from the calculated reflection ratio.
このように、標準体からの反射光Ｒｒを基準とすることで、例えば、投光手段１２が経年劣化するなどして光量が低下した場合にも、反射比Ｒはほぼ変動なく測定することができるため、長期間安定した検査を行うことができる。 In this way, by using the reflected light Rr from the standard as a reference, the reflection ratio R can be measured with almost no variation even when the light amount is reduced due to, for example, deterioration of the light projecting means 12. Therefore, a stable inspection can be performed for a long time.
なお、反射比Ｒや見かけ上の吸光度Ａに基づく検査画像の各画素値の決定は、例えば、以下のようにして行うことができる。 The determination of each pixel value of the inspection image based on the reflection ratio R and the apparent absorbance A can be performed as follows, for example.
例えば、８ビット画像の場合、画素値は０〜２５５の値となるため、想定される反射比Ｒの最低値（撮像手段１４の性能などに基づき適宜設定）が「０」、反射比Ｒの最高値である１が「２５５」となるように、各画素の反射比Ｒを換算すればよい。 For example, in the case of an 8-bit image, the pixel value is a value from 0 to 255. Therefore, the assumed minimum value of the reflection ratio R (appropriately set based on the performance of the imaging unit 14) is “0”, and the reflection ratio R is The reflection ratio R of each pixel may be converted so that 1 which is the maximum value becomes “255”.
そして、この検査画像を、解析手段１６により後述するように画像解析することで、青果物Ｓの腐敗部位を検出することができる。 The inspection image is analyzed by the analysis unit 16 as will be described later, so that the rot portion of the fruits and vegetables S can be detected.
解析手段１６における画像解析では、（１）複数の波長の光に基づく検査画像の比（２）複数の波長の光に基づく検査画像の差分（３）水の吸収波長の光に基づく検査画像の２次微分のいずれかを行うことによって、検査画像における腐敗部位を明瞭にした解析画像を生成し、腐敗部位を検出している。 In the image analysis in the analysis means 16, (1) the ratio of inspection images based on light of a plurality of wavelengths (2) difference of inspection images based on light of a plurality of wavelengths (3) inspection image based on light of absorption wavelength of water By performing any of the second order differentiation, an analysis image in which the corruption site in the inspection image is clarified is generated, and the corruption site is detected.
なお、これらの画像解析は、青果物Ｓの腐敗部位が、正常部位と比べて水分量が多くなることから、水の吸収波長の光が腐敗部位に吸収され、撮像手段１４により撮像した際に、正常部位と比べて腐敗部位の光量が低下することに基づいている。 In addition, these image analyzes, because the amount of water in the rot portion of the fruits and vegetables S is larger than that in the normal portion, the light of the absorption wavelength of water is absorbed by the rot portion, and when imaged by the imaging means 14, This is based on the fact that the amount of light at the decayed portion is reduced as compared with the normal portion.
以下、各画像解析について詳細に説明する。 Hereinafter, each image analysis will be described in detail.
（１）複数の波長の光に基づく検査画像の比では、水の吸収波長λ1の光に基づく検査画像と、基準とする所定の吸収波長λ2の光に基づく検査画像とを用いて、下記式（３）に示すように、画素毎に光量の比を取ることにより、腐敗部位を特定している。(1) In the ratio of inspection images based on light of a plurality of wavelengths, an inspection image based on light having a water absorption wavelength λ 1 and an inspection image based on light having a predetermined absorption wavelength λ 2 as a reference are used. As shown in the following formula (3), the decaying part is specified by taking a light quantity ratio for each pixel.
ここで、Ｘは光量Ｌ、反射比Ｒ、見かけ上の吸光度Ａのいずれかである。 Here, X is any one of the light quantity L, the reflection ratio R, and the apparent absorbance A.
図２に、検査画像の比をとった場合の解析画像の一例を示す。 FIG. 2 shows an example of an analysis image when the ratio of inspection images is taken.
図２（ａ）は、青果物Ｓを可視光により撮像したグレースケール画像、図２（ｂ）は、図２（ａ）の青果物Ｓについて、水の吸収波長として１２００ｎｍの光に基づく検査画像と、基準とする所定の吸収波長の光として１０３０ｎｍの光に基づく検査画像との比をとった場合の解析画像である。 FIG. 2 (a) is a grayscale image obtained by imaging the fruits and vegetables S with visible light, and FIG. 2 (b) is an inspection image based on 1200 nm light as the water absorption wavelength for the fruits and vegetables S in FIG. 2 (a). It is an analysis image at the time of taking a ratio with the inspection image based on the light of 1030 nm as light of the predetermined absorption wavelength used as a standard.
図２（ａ）に示すように、可視光により撮像した場合には、正常部位Ｘと腐敗部位Ｙにおいて彩度、色度、明度にほとんど差が生じていないが、図２（ｂ）に示すように、検査画像の比較を行うことによって、正常部位Ｘと腐敗部位Ｙとに明らかなコントラストが生じ、腐敗部位Ｙの有無を容易に、かつ、確実に判別することができる。 As shown in FIG. 2A, when imaging is performed with visible light, there is almost no difference in saturation, chromaticity, and lightness between the normal site X and the rotting site Y, but as shown in FIG. Thus, by comparing the inspection images, a clear contrast is generated between the normal site X and the rot site Y, and the presence or absence of the rot site Y can be easily and reliably determined.
（２）複数の波長の光に基づく検査画像の差では、水の吸収波長λ1の光に基づく検査画像と、基準とする所定の吸収波長λ2の光に基づく検査画像とを用いて、下記式（４）に示すように、画素毎に光量の差を取ることにより、腐敗部位を特定している。(2) In the difference between the inspection images based on the light having a plurality of wavelengths, the inspection image based on the light having the water absorption wavelength λ 1 and the inspection image based on the light having the reference absorption wavelength λ 2 are used. As shown in the following formula (4), the decaying part is specified by taking a difference in light quantity for each pixel.
ここで、Ｘは光量Ｌ、反射比Ｒ、見かけ上の吸光度Ａのいずれかである。 Here, X is any one of the light quantity L, the reflection ratio R, and the apparent absorbance A.
図３に、検査画像の差をとった場合の解析画像の一例を示す。 FIG. 3 shows an example of an analysis image when a difference between inspection images is taken.
図３（ａ）は、青果物Ｓを可視光により撮像したグレースケール画像、図３（ｂ）は、図３（ａ）の青果物Ｓについて、水の吸収波長として１１６０ｎｍの光に基づく検査画像と、基準とする所定の吸収波長の光として１１３５ｎｍの光に基づく検査画像との差をとった場合の解析画像である。 3 (a) is a grayscale image obtained by imaging the fruits and vegetables S with visible light, FIG. 3 (b) is an inspection image based on light of 1160 nm as the water absorption wavelength for the fruits and vegetables S in FIG. 3 (a), It is an analysis image at the time of taking the difference with the test | inspection image based on the light of 1135 nm as light of the predetermined | prescribed absorption wavelength used as a reference | standard.
図３（ａ）に示すように、可視光により撮像した場合には、正常部位Ｘと腐敗部位Ｙにおいて彩度、色度、明度にほとんど差が生じていないが、図３（ｂ）に示すように、検査画像の比較を行うことによって、正常部位Ｘと腐敗部位Ｙとに明らかなコントラストが生じ、腐敗部位Ｙの有無を容易に、かつ、確実に判別することができる。 As shown in FIG. 3A, when imaging is performed with visible light, there is almost no difference in saturation, chromaticity, and lightness between the normal site X and the rotting site Y, but as shown in FIG. Thus, by comparing the inspection images, a clear contrast is generated between the normal site X and the rot site Y, and the presence or absence of the rot site Y can be easily and reliably determined.
また、検査画像の２次微分では、水の吸収波長の光に基づく検査画像と、その前後の波長の光に基づく検査画像とを用いて、画素毎に光量の２次微分を取ることにより、腐敗部位を特定している。 Further, in the second derivative of the inspection image, by using the inspection image based on the light of the absorption wavelength of water and the inspection image based on the light of the wavelength before and after that, by taking the second derivative of the light amount for each pixel, The site of corruption is identified.
なお、２次微分の計算は、近似式を用いることができる。 An approximate expression can be used for the calculation of the second derivative.
具体的には、吸収波長λBの光に基づく検査画像Ｂと、水の吸収波長λBよりも所定波長短い波長λAの光に基づく検査画像Ａと、吸収波長λBよりも所定波長長い波長λCの光に基づく検査画像Ｃとを用いて、画素毎に下記式（５）の計算を行うことにより解析画像Ｄを得ることができる。
ＰD＝ＰA−２×ＰB−ＰC （５）
上記式（５）において、ＰA：検査画像Ａの画素信号ＰB：検査画像Ｂの画素信号ＰC：検査画像Ｃの画素信号ＰD：解析画像Ｄの画素信号である。Specifically, the inspection image B based on light absorption wavelength lambda B, the inspection image A than the absorption wavelength lambda B of water based on light of a predetermined wavelength shorter wavelength lambda A, longer predetermined wavelength than the absorption wavelength lambda B The analysis image D can be obtained by performing the calculation of the following formula (5) for each pixel using the inspection image C based on the light of the wavelength λ C.
P D = P A −2 × P B −P C (5)
In the above formula (5), P A : pixel signal P B of the inspection image A: pixel signal P C of the inspection image B: pixel signal P D of the inspection image C: pixel signal of the analysis image D
各画素について、このように計算を行うことによって、水の吸収波長の光に基づく検査画像の２次微分を取った解析画像を生成することができる。 By performing the calculation for each pixel in this manner, an analysis image obtained by taking the second derivative of the inspection image based on the light having the absorption wavelength of water can be generated.
なお、本実施例では、説明を簡便にするために、１台の投光手段１２と、１台の撮像手段１４を備えた構成としているが、複数台の投光手段１２を備えてもよいし、また、複数台の撮像手段１４を備えてもよい。 In the present embodiment, in order to simplify the description, a single light projecting unit 12 and a single image capturing unit 14 are provided. However, a plurality of light projecting units 12 may be provided. In addition, a plurality of imaging means 14 may be provided.
図４に、検査画像の２次微分を取った場合の解析画像の一例を示す。 FIG. 4 shows an example of an analysis image when taking the second derivative of the inspection image.
図４（ａ）は、青果物Ｓを可視光により撮像したグレースケール画像、図４（ｂ）は、図４（ａ）の青果物Ｓについて、水の吸収波長として１２００ｎｍの光に基づく検査画像の２次微分を取った解析画像である。 4A is a grayscale image obtained by imaging the fruits and vegetables S with visible light, and FIG. 4B is an inspection image 2 based on 1200 nm light as the water absorption wavelength for the fruits and vegetables S in FIG. 4A. It is the analysis image which took the second derivative.
図４（ａ）に示すように、可視光により撮像した場合には、正常部位Ｘと腐敗部位Ｙとにおいて彩度、色度、明度にほとんど差が生じていないが、図４（ｂ）に示すように、検査画像の比較を行うことによって、正常部位Ｘと腐敗部位Ｙとに明らかなコントラストが生じ、腐敗部位Ｙの有無を容易に、かつ、確実に判別することができる。 As shown in FIG. 4A, when imaging is performed with visible light, there is almost no difference in saturation, chromaticity, and lightness between the normal site X and the rotting site Y, but FIG. As shown, by comparing the inspection images, a clear contrast occurs between the normal site X and the rot site Y, and the presence or absence of the rot site Y can be easily and reliably determined.
なお、本実施例では、青果物の異常として水腐れが生じたものについての一例に基づいて説明したが、青果物の果皮に乾燥腐れが生じた場合であっても、正常部位とは異なるスペクトルを得ることができることから、同様に画像解析を行うことで、青果物の異常を検出することができる。 In addition, although the present Example demonstrated based on an example about what the water rot produced as abnormality of fruit and vegetables, even if it is a case where dry rot has arisen in the fruit and skin of fruit and vegetables, a spectrum different from a normal site | part is obtained. Therefore, it is possible to detect abnormalities in fruits and vegetables by performing image analysis in the same manner.
図５は、図１の青果物検査装置１０を用いて、正常な青果物、水腐れを有する青果物、乾燥腐れを有する青果物について測定を行った際のスペクトルデータである。なお、図５に示すスペクトルデータは、波長２５ｎｍ間隔において吸光度を２次微分処理したものである。 FIG. 5 shows spectrum data obtained by measuring normal fruits and vegetables, fruits and vegetables having water rot, and fruits and vegetables having dry rot using the fruit and vegetable inspection apparatus 10 of FIG. Note that the spectral data shown in FIG. 5 is obtained by subjecting absorbance to second-order differentiation processing at intervals of a wavelength of 25 nm.
図５に示すように、水腐れを有する青果物は、正常な青果物と比べ、水の吸収波長である９６０ｎｍ前後、１１５０ｎｍ前後において吸収の増加が見られる。 As shown in FIG. 5, the fruits and vegetables with water rot show an increase in absorption at around 960 nm and around 1150 nm, which are the absorption wavelengths of water, compared to normal fruits and vegetables.
また、乾燥腐れを有する青果物については、正常な青果物と比べ、水の吸収波長である９６０ｎｍ前後、１１５０ｎｍ前後において吸収の低下が見られる。 Moreover, about the fruits and vegetables which have dry rot, compared with normal fruits and vegetables, the fall of absorption is seen in the water absorption wavelength around 960 nm and around 1150 nm.
すなわち、水の吸収波長の光に基づく検査画像を用い、検査光の吸収の度合いの変化を見ることによって、青果物の水腐れなどの異常を検出できることがわかる。 That is, it can be seen that abnormalities such as water rot of fruits and vegetables can be detected by using a test image based on light having an absorption wavelength of water and observing a change in the degree of absorption of the test light.
一方で、青果物の果皮に異常乾燥が生じている場合には、正常な青果物と比べ、水の吸収波長の光が吸収されないことになる。このため、正常な青果物と、果皮に異常乾燥が生じた青果物とを判別することが可能である。 On the other hand, when abnormal drying occurs in the fruit and fruit skin, light having an absorption wavelength of water is not absorbed as compared with normal fruit and vegetables. For this reason, it is possible to discriminate between normal fruits and vegetables and fruits and vegetables whose skins are abnormally dried.
図６は、本発明の青果物検査装置の別の実施例における構成を説明するための概略構成図である。 FIG. 6 is a schematic configuration diagram for explaining a configuration in another embodiment of the fruit and vegetable inspection apparatus of the present invention.
図６に示す青果物検査装置１０は、基本的には図１〜５に示した青果物検査装置１０と同様な構成であり、同じ構成部材には、同じ符号を付してその詳細な説明を省略する。 The fruit and vegetable inspection apparatus 10 shown in FIG. 6 has basically the same configuration as the fruit and vegetable inspection apparatus 10 shown in FIGS. 1 to 5, and the same components are denoted by the same reference numerals and detailed description thereof is omitted. To do.
図１に示す青果物検査装置１０では、青果物Ｓに対して投光手段１２と撮像手段１４を同じ方向に配置し、反射光によって青果物Ｓを撮像しているが、この実施例の青果物検査装置１０では、投光手段１２により照射された検査光が青果物Ｓを透過して、この透過光を用いて撮像手段１４により青果物Ｓの検査画像を撮像している。 In the fruit and vegetable inspection apparatus 10 shown in FIG. 1, the light projecting means 12 and the imaging means 14 are arranged in the same direction with respect to the fruit and vegetables S, and the fruit and vegetables S are imaged by reflected light. Then, the inspection light irradiated by the light projecting means 12 passes through the fruits and vegetables S, and an inspection image of the fruits and vegetables S is picked up by the imaging means 14 using the transmitted light.
このように、透過光に基づく検査画像を用いた場合であっても、上述するように、反射光に基づく検査画像を用いた場合と同様に、画像解析を行うことによって、青果物Ｓの正常部位と腐敗部位とを判別することができる。 Thus, even when the inspection image based on the transmitted light is used, as described above, by performing image analysis as in the case of using the inspection image based on the reflected light, the normal part of the fruits and vegetables S And rot sites can be discriminated.
なお、本実施例では、透過光のみにより検査画像を撮像しているが、上述する実施例と組み合わせることで、透過光と反射光の両方を用いて検査画像を撮像しても構わない。 In this embodiment, the inspection image is picked up only by the transmitted light. However, the inspection image may be picked up by using both the transmitted light and the reflected light in combination with the above-described embodiment.
図７は、本発明の青果物検査装置のさらに別の実施例における構成を説明するための概略構成図である。 FIG. 7 is a schematic configuration diagram for explaining a configuration in still another embodiment of the fruit and vegetable inspection apparatus of the present invention.
図７に示す青果物検査装置１０は、基本的には図１〜６に示した青果物検査装置１０と同様な構成であり、同じ構成部材には、同じ符号を付してその詳細な説明を省略する。 The fruit and vegetable inspection apparatus 10 shown in FIG. 7 has basically the same configuration as the fruit and vegetable inspection apparatus 10 shown in FIGS. 1 to 6, and the same components are denoted by the same reference numerals and detailed description thereof is omitted. To do.
図１〜６に示す青果物検査装置１０では、静止状態の青果物Ｓに対して投光手段１２から検査光を照射し、この検査光に基づく検査画像を撮像手段１４によって撮像するように構成しているが、この実施例の青果物検査装置１０では、搬送手段２０によって一方向に搬送される青果物Ｓに対して検査光を照射し、検査画像を撮像するように構成している。 The fruit and vegetable inspection apparatus 10 shown in FIGS. 1 to 6 is configured such that inspection light is irradiated from the light projecting unit 12 to the stationary fruit and vegetable S, and an inspection image based on the inspection light is captured by the imaging unit 14. However, in the fruit and vegetable inspection apparatus 10 of this embodiment, the inspection light is irradiated to the fruit and vegetables S conveyed in one direction by the conveying means 20 and an inspection image is taken.
このように、インラインで青果物検査を行うように構成することによって、大量の青果物を効率よく検査することができる。 In this way, a large amount of fruits and vegetables can be efficiently inspected by configuring so as to inspect the fruits and vegetables in-line.
なお、搬送手段２０によって青果物Ｓを搬送しながら検査を行う場合には、図７に示すように、搬送方向の両側方に反射鏡２２を設けることで、青果物Ｓの側面部を反射鏡に映すことで、撮像手段１４によって青果物Ｓ全体を撮像するように構成することが好ましい。 When the inspection is performed while the fruits and vegetables S are transported by the transport means 20, as shown in FIG. 7, the side surfaces of the fruits and vegetables S are reflected on the reflectors by providing the reflecting mirrors 22 on both sides in the transport direction. Thus, it is preferable that the entire image of the fruits and vegetables S be imaged by the imaging unit 14.
図８〜１２では、図１に示す青果物検査装置１０を用いて、青果物Ｓについて検査を行った際の可視画像と検査画像の例を示す。 8 to 12 show examples of visible images and inspection images when the fruits and vegetables S are inspected by using the fruits and vegetables inspection apparatus 10 shown in FIG.
図８は、青果物Ｓとして、カビが生じた蜜柑について検査を行ったもので、図８（ａ）は可視画像、図８（ｂ）は検査画像である。 8A and 8B show a test for mandarin oranges having mold as the fruits and vegetables S. FIG. 8A shows a visible image and FIG. 8B shows an inspection image.
可視画像において上部に現れているカビが、検査画像では、白く確認することができる。 Mold appearing at the top in the visible image can be confirmed to be white in the inspection image.
図９は、青果物Ｓとして、果皮表面に乾燥キズが生じた蜜柑について検査を行ったもので、図９（ａ）は可視画像、図９（ｂ）は検査画像である。 FIG. 9 shows an inspection of mandarin oranges having dried scratches on the surface of fruits and vegetables S. FIG. 9A shows a visible image and FIG. 9B shows an inspection image.
可視画像において下部に現れている乾燥キズが、検査画像では、白く確認することができる。 Dry scratches appearing at the bottom of the visible image can be confirmed to be white in the inspection image.
図８のカビ、図９の乾燥キズのように、果皮表層若しくは果皮下の水分が減少している場合には、近赤外光の吸収率が低いため、検査画像のような赤外画像には、白く現れる。 When the moisture on the skin surface or under the skin is reduced, such as the mold in FIG. 8 and the dry scratch in FIG. 9, the absorption rate of near-infrared light is low. Appears white.
図１０は、青果物Ｓとして、いわゆる押せ痕が生じた桃について検査を行ったもので、図１０（ａ）は可視画像、図１０（ｂ）は検査画像、図１０（ｃ）は果皮をむいて果皮内部を確認できる状態にした青果物Ｓの可視画像である。 FIG. 10 shows an inspection of peaches with so-called press marks as fruits and vegetables S. FIG. 10 (a) shows a visible image, FIG. 10 (b) shows an inspection image, and FIG. 10 (c) peels the skin. It is the visible image of the fruit and vegetables S made into the state which can confirm the inside of a fruit skin.
可視画像では確認が困難な押せ痕（図１０（ｃ）において色が濃くなっている箇所）について、検査画像では黒く確認することができる。 A pressing mark that is difficult to confirm in the visible image (a portion where the color is dark in FIG. 10C) can be confirmed black in the inspection image.
図１１は、青果物Ｓとして、水果が生じた梨について検査を行った者で、図１１（ａ）は可視画像、図１１（ｂ）は検査画像、図１１（ｃ）は果皮をむいて果皮内部を確認できる状態にした青果物Ｓの可視画像である。 FIG. 11 is a person who inspected pears with water fruits as fruits and vegetables S, FIG. 11 (a) is a visible image, FIG. 11 (b) is an inspection image, and FIG. 11 (c) is a peeled peel. It is the visible image of the fruit and vegetables S which made the state which can confirm the inside.
可視画像では確認が困難な水果（図１１（ｃ）において色が濃くなっている箇所）について、検査画像では黒く確認することができる。 Water fruits that are difficult to confirm in the visible image (locations where the color is dark in FIG. 11C) can be confirmed black in the inspection image.
図１０の押せ痕、図１１の水果のように、果皮表層若しくは果皮下の水分が増加している場合には、近赤外光の吸収率が高いため、検査画像のような赤外画像には、黒く現れる。 When the moisture on the skin surface or under the skin is increased, such as the pressing mark in FIG. 10 and the water fruit in FIG. 11, the absorption rate of near-infrared light is high. Appears black.
以上、本発明の好ましい実施例を説明したが、本発明はこれに限定されることはなく、例えば、複数の波長の光に基づく検査画像の比較として、２つの波長の光に基づく検査画像を用いて画像解析を行っているが、３つ以上の波長の光に基づく検査画像を用いて画像解析を行うようにしてもよいなど、本発明の目的を逸脱しない範囲で種々の変更が可能である。 The preferred embodiment of the present invention has been described above, but the present invention is not limited to this. For example, an inspection image based on light of two wavelengths is used as a comparison of inspection images based on light of a plurality of wavelengths. However, various modifications are possible without departing from the object of the present invention, such as image analysis using inspection images based on light of three or more wavelengths. is there.
１０ 青果物検査装置
１２ 投光手段
１４ 撮像手段
１６ 解析手段
１８ バンドパスフィルタ
２０ 搬送手段
２２ 反射鏡DESCRIPTION OF SYMBOLS 10 Fruit and vegetable inspection apparatus 12 Light projection means 14 Imaging means 16 Analysis means 18 Band pass filter 20 Conveyance means 22 Reflecting mirror
Claims (3)
前記青果物に対して検査光を照射する投光手段と、
前記検査光により前記青果物を撮像する撮像手段と、
前記撮像手段により撮像された前記青果物の検査画像に基づき、前記青果物の異常の有無を検出する解析手段と、を備え、
前記投光手段は、少なくとも水の吸収波長を含む光が照射可能であり、
前記解析手段は、前記水の吸収波長の光に基づく検査画像を用いて、前記青果物の異常の有無を検出するように構成され、
前記撮像手段は、前記投光手段から照射された検査光が前記青果物に反射した反射光により、前記青果物の検査画像を撮像し、
前記青果物からの反射光Ｒｓと、あらかじめ取得した入射光を照射し得られた標準体からの反射光Ｒｒとの比率として算出された前記青果物の反射比Ｒ、すなわち、下記式（１）を算出し、
前記反射比Ｒの最低値が前記検査画像の画素値の最低値となり、前記反射比Ｒの最高値が前記画素値の最高値となるように換算することにより、前記検査画像の各画素値を決定することを特徴とする青果物検査装置。
A light projecting means for irradiating the fruit and vegetables with inspection light;
Imaging means for imaging the fruits and vegetables with the inspection light;
Analysis means for detecting the presence or absence of abnormality of the fruits and vegetables based on the inspection image of the fruits and vegetables imaged by the imaging means,
The light projecting means can be irradiated with light including at least the absorption wavelength of water,
The analysis means is configured to detect the presence or absence of abnormality of the fruits and vegetables using an inspection image based on light of the water absorption wavelength.
The imaging means captures an inspection image of the fruits and vegetables with the reflected light reflected from the fruits and vegetables by the inspection light emitted from the light projecting means,
And the reflected light Rs from the previous SL fruits or vegetables, the reflection ratio of the fruits or vegetables which are calculated as the ratio of the reflected light Rr from a standard body that is obtained by irradiating the incident light previously acquired R, i.e., the following equation (1) Calculate
By converting the minimum value of the reflection ratio R to be the minimum value of the pixel value of the inspection image and the maximum value of the reflection ratio R to be the maximum value of the pixel value, each pixel value of the inspection image is converted. A fruit and vegetable inspection apparatus characterized by deciding.
The fruit and vegetable inspection apparatus according to claim 1 or 2 , wherein the abnormality of the fruit or vegetable is an obstacle related to an increase or decrease in moisture appearing on a skin layer and / or under the skin of the fruit or vegetable.
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