CN109540894A - A kind of lossless rapid detection method of cured tobacco leaf maturity - Google Patents
A kind of lossless rapid detection method of cured tobacco leaf maturity Download PDFInfo
- Publication number
- CN109540894A CN109540894A CN201811541440.2A CN201811541440A CN109540894A CN 109540894 A CN109540894 A CN 109540894A CN 201811541440 A CN201811541440 A CN 201811541440A CN 109540894 A CN109540894 A CN 109540894A
- Authority
- CN
- China
- Prior art keywords
- tobacco leaf
- value
- maturity
- leaf
- detection position
- 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.)
- Pending
Links
Classifications
-
- 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
-
- 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
- G01N2021/8466—Investigation of vegetal material, e.g. leaves, plants, fruits
Landscapes
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Manufacture Of Tobacco Products (AREA)
Abstract
The present invention provides a kind of lossless rapid detection methods of cured tobacco leaf maturity, and the tobacco leaf color image information of tobacco leaf to be detected is acquired by image capture device；Tobacco leaf color image information is subjected to image procossing, determines the tobacco leaf detection position in tobacco leaf color image information, obtains the rgb value of image in tobacco leaf detection position；From R value is extracted in tobacco leaf detection position in the rgb value of image, brings R value into maturity calculation formula: in mature angle value=18*R/255, obtaining the mature angle value of tobacco leaf test section.This method index is clear, it is objective with judgment method to measure, scientific quantification Maturity of Tobacco Leaf index, it is easy to operate and control, using this method judge in, upper tobacco leaf harvest maturity, it is unified to harvest eye, toasting difficulty reduces, cured tobacco leaf blue veins, green piece and dust ratio substantially reduce, and roasting rear tobacco rate, first-class cigarette ratio and average price are significantly increased, and roasting rear quality and economic characters are better than conventional harvesting.Suitable for tobacco planting and processing enterprise.
Description
Technical field
The present invention relates to the tobacco leaf maturation detection techniques of tobacco business, specially using tobacco leaf color-gamut value carry out at
Ripe degree detection, specially a kind of lossless rapid detection method of cured tobacco leaf maturity.
Background technique
Tobacco is the important industrial crops in China.Maturity of Tobacco Leaf is to influence quality of tobacco, and then influence tobacco articles valence
The key factor of value.The maturity of tobacco leaf is to measure the first element of quality of tobacco, is the core of quality of tobacco, with tobacco leaf
Color is closely related.It studies and production practices is thought, the good tobacco leaf intrinsic chemical ingredient of maturity is coordinated, aroma quality is good,
Perfume quantity foot.From the point of view of baking, the good tobacco leaf of maturity is easy baking, and upper medium grade cigarette ratio is high after baking, planting benefit
It is good.The purpose of mature harvesting is exactly the interior quality and appearance ratings quality in order to guarantee and improve tobacco leaf in fact, is had more first-class
Cigarette increases benefit.Maturation harvesting is to produce one of key link and key technology of sound tobacco.Currently, grasping and judging field
Between Maturity of Tobacco Leaf to timely collecting and science modulation be of great significance.Currently, shortage system, standard are evaluated to Maturity of Tobacco Leaf
True quantitative study is the bottleneck for restricting China's quality of tobacco and improving.Tobacco harvest is mainly carried out using artificial method, have through
After the tobacco grower tested can be with the maturity of accurate judgement tobacco leaf, then carry out tobacco leaf picking harvest.Currently, Maturity of Tobacco Leaf judgement is normal
Have with method: 1. being judged by long-term production experience；2. mentioning the last week picking tobacco sample carries out chemical composition analysis
Judge, it is common in U.S.；3. being judged by the method for colorimetric card colorimetric；In existing Maturity of Tobacco Leaf judgment method,
There is very big subjectivity, lacks the accuracy of judgement；And lack unified quantitative criteria, therefore existing error is larger.
Summary of the invention
To solve above-mentioned the shortcomings of the prior art and defect, the present invention provides a kind of cured tobacco leaf maturity is lossless
Rapid detection method, this method index are clear, it is objective with judgment method to measure, and scientific quantification Maturity of Tobacco Leaf index is easy to
It operation and grasps, specifically, the present invention is implemented as follows: a kind of lossless rapid detection method of cured tobacco leaf maturity, including
Following steps: S1, the tobacco leaf color image information that tobacco leaf to be detected is acquired by image capture device；S2, by tobacco leaf cromogram
As information progress image procossing, determines the tobacco leaf detection position in tobacco leaf color image information, obtain and scheme in tobacco leaf detection position
The rgb value of picture；S3, from tobacco leaf detection position in the rgb value of image extract R value, bring R value into maturity calculation formula: at
In ripe angle value=18*R/255, the mature angle value of tobacco leaf test section is obtained；Whether the resulting mature angle value of S4, measuring process S3 is in
Within the scope of ripeness standard value, if so, tobacco leaf to be detected is maturation, if it has not, judging that mature angle value is more than or less than mature mark
Quasi- value range, is less than, then tobacco leaf to be detected is prematurity, is greater than, then tobacco leaf to be detected is postmaturity.
Further, the tobacco leaf color image information of tobacco leaf to be detected is acquired in the step S1 by image capture device
Comprising steps of image capture device in a natural environment illuminance acquired at 300-1000lx tobacco leaf to be detected tobacco leaf it is color
Color image information；Or illuminance in the 1800-2200lx and under conditions of WHITE TONE value is in 5500-6000K indoors
Acquire the tobacco leaf color image information of tobacco leaf to be detected.
Further, described image acquisition equipment is IP Camera, smart phone or digital camera, described image acquisition
Parameter setting when equipment acquires are as follows: shutter 1/125 second, aperture F8, sensitivity ISO200.
Further, the method for the tobacco leaf detection position in the step S2 in determining tobacco leaf color image information includes:
Judge the direction of tobacco leaf in tobacco leaf color image information and determines tobacco leaf top, middle part region；Extract tobacco leaf top or cigarette
High wide rectangular, the round or elliptical image-region in 2-8cm, obtains tobacco leaf detection position in leaf central part region.
Further, the method for the rgb value of image in tobacco leaf detection position being obtained in the step S2 includes: to examine tobacco leaf
The color mode surveyed in the image-region at position is converted to RGB mode, and color mixing processing is made, and is schemed after extracting color mixing processing
As the color information rgb value at regional center position.
Further, the color mixing processing includes: that the image information of tobacco leaf detection position is carried out mosaic processing,
The mosaic processing is handled by 20~100 grid sizes.
Further, when the tobacco leaf detection position is upper leaf, mosaic processing is handled by 100 grid sizes；
When the tobacco leaf detection position is middle leaf, mosaic processing is handled by 50 grid sizes；The tobacco leaf detection position is
When inferior leads, mosaic processing is handled by 20 grid sizes.
Further, the ripeness standard value range are as follows: when the tobacco leaf detection position is upper leaf, ripeness standard value model
Enclose is 6.68 ± 1.55；When the tobacco leaf detection position is middle leaf, ripeness standard value range is 6.17 ± 1.12；The tobacco leaf
When detection position is inferior leads, ripeness standard value range is 8.35 ± 1.02.
Further, maturity calculation formula is maturation angle value=10*R/255 in the step S3, obtains tobacco leaf test section
Maturity；The ripeness standard value range are as follows: when the tobacco leaf detection position is upper leaf, ripeness standard value range is 3.71
±1；When the tobacco leaf detection position is middle leaf, ripeness standard value range is 3.43 ± 1.5.
Further, the method for the mature angle value of tobacco leaf test section is obtained in the step S3 are as follows: from tobacco leaf detection position
G value is extracted in the rgb value of image, is brought G value into maturity calculation formula: in mature angle value=10* (255-G)/255, being obtained cigarette
The mature angle value of leaf test section, the ripeness standard value range are as follows: when the tobacco leaf detection position is upper leaf, ripeness standard value
Range is 5.77+0.6；When the tobacco leaf detection position is middle leaf, ripeness standard value range is 5.93 ± 0.25.
The working principle of the invention and beneficial effect introduction: being handled by photo, extracts the image of tobacco leaf key position
Color-gamut value obtains the maturity formed under unified quantization after processing, obtains after through a scientific and reasonable setting
Maturity examination criteria value be compared, can be obtained the maturity testing result of the tobacco leaf, this method without picking tobacco leaf,
Without destroying tobacco leaf, thus reach non-destructive testing, meanwhile, the examination criteria value range obtained by quantification treatment being capable of science
Effectively reach detection method, the detection method precisely, high reliablity, rapidly effectively.Using this method judge in, upper tobacco leaf
Harvest maturity, it is unified to harvest eye, thus realize that the difficulty of baking tobacco leaves reduces, cured tobacco leaf blue veins, green piece and dust ratio
Example substantially reduces, the effect that roasting rear tobacco rate, first-class cigarette ratio and average price are significantly increased, so that quality and economy after tobacco leaf is roasting
Character is better than conventional harvesting.Suitable for tobacco planting and processing enterprise.
Detailed description of the invention
Fig. 1 is Maturity of Flue-cured Tobacco color gamut value measurement point distribution schematic diagram in embodiment 3；
Fig. 2 is each maturity V value trend chart of tobacco leaf middle leaf to be detected in embodiment 3；
Fig. 3 is each maturity V value trend chart of tobacco leaf upper leaf to be detected in embodiment 3；
Specific embodiment
In order to make the objectives, technical solutions and advantages of the present invention clearer, With reference to embodiment and join
According to attached drawing, the present invention is described in more detail.It should be understood that these descriptions are merely illustrative, and it is not intended to limit this hair
Bright range.In addition, in the following description, descriptions of well-known structures and technologies are omitted, to avoid this is unnecessarily obscured
The concept of invention.
A kind of embodiment 1: lossless rapid detection method of cured tobacco leaf maturity, comprising the following steps:
S1, the tobacco leaf color image information that tobacco leaf to be detected is acquired by image capture device；Image information data transmission
To processor or Intelligent treatment equipment,
S2, tobacco leaf color image information is subjected to image procossing, determines the tobacco leaf test section in tobacco leaf color image information
Position obtains the rgb value of image in tobacco leaf detection position；If tobacco leaf color image information is not RGB color mode, can be by existing
Means are converted to RGB color mode, and extract rgb value information by processor or Intelligent treatment equipment or software；
S3, from R value is extracted in tobacco leaf detection position in the rgb value of image, bring R value into maturity calculation formula: mature
In angle value=18*R/255, the mature angle value of tobacco leaf test section is obtained；
Whether the resulting mature angle value of S4, measuring process S3 is within the scope of ripeness standard value, if so, tobacco leaf to be detected
Being less than for maturation if it has not, judging that mature angle value is more than or less than ripeness standard value range, then tobacco leaf to be detected is prematurity,
It is greater than, then tobacco leaf to be detected is postmaturity, that is, completes the detection of Maturity of Tobacco Leaf.
Actual use example up successively detects above the tobacco leaf of every plant of tobacco in one mu of tobacco leaf Tanaka under leaf bar
Maturity of Tobacco Leaf, by image capture device alignment tobacco leaf carry out tobacco leaf color image information acquisition, be then sent to intelligence
Processing equipment is detected, and is completed to detect according to above-mentioned steps, is shown that the Maturity of Tobacco Leaf meets picking condition, then continue up
A piece of tobacco leaf carries out identical maturity detection, successively until reaching that maturity is below standard, then records below standard tobacco leaf institute
In height, the tobacco leaf lower than the height can be picked, to realize scientific, accurately high Mature Tobacco Leaves picking.
Embodiment 2: on the basis of embodiment 1, image capture device in a natural environment illuminance in 300-1000lx
The tobacco leaf color image information of lower acquisition tobacco leaf to be detected；Or indoors illuminance in the 1800-2200lx and WHITE TONE
The tobacco leaf color image information of tobacco leaf to be detected is acquired under conditions of value is in 5500-6000K；Image capture device is taken the photograph for network
As head, smart phone or digital camera, described image acquires parameter setting when equipment acquisition are as follows: and shutter 1/125 second, aperture
F8, sensitivity ISO200.After unified standard, to the specific unified quantization function of subsequent testing result, the accurate of detected value is ensured
Degree.
Embodiment 3: detection test
Before the harvesting of tobacco leaf normal mature, chosen from transplanting time and the consistent tobacco field of cultivation management measure representative strong
Undercure, maturation, overdone tobacco leaf, wherein inferior leads take the 4th leaf position, and middle leaf takes the 12nd leaf position, and upper leaf takes the 15th leaf position, each portion
Position maturity sense organ judgment criteria: lower two canopy leaf mature characteristics: blade face falls Huang 6 into left and right, and whole to present greenish-yellow, master pulse bleaches,
Offshoot is green white, and fine hair partial exfoliation, blade tip leaf margin is slightly sagging, and there is clear and melodious sound in when picking, and section is smooth, without stem skin.On time
Between calculate, 15-20 days after binding.Waist leaf mature characteristic: blade face fall Huang 8 at left and right, color is pale yellow, master pulse bleach it is shinny, branch
Arteries and veins bleaches, and fine hair falls off, and blade tip leaf margin is sagging, and 90 ° of cauline leaf angle, there is clear and melodious sound in when picking, and section is smooth, without stem skin.
It temporally calculates, 30-40 days after binding.Upper two canopies mature characteristic: blade face falls Huang 9 into left and right, and color is yellowish, the milky white hair of master pulse
Bright, offshoot is entirely white, and fine hair falls off, and there is fold on blade face, and yellow-white maturation patch is obvious, and cauline leaf angle is greater than 90 °, picks Shi Youqing
Loud and clear sound, section is smooth, without stem skin.It temporally calculates, 50-60 days after binding.Each position meets the above mature characteristic
It is considered as climax leaves, mature characteristic majority is incongruent to be considered as undercure leaf, is considered as overdone leaf more than the position majority mature characteristic.
It is placed under white background and specific environment and takes pictures.Photo environment setting are as follows: under natural conditions, fine day or cloudy weather 9-10
Point, illuminance avoid sun light direct beam on tobacco leaf in 300-1000lx；Under indoor conditions, colour temperature 5500-6000K, illumination
2000 ± 200lx, around without the bad color for influencing color judgement.Camera setting are as follows: manual mode, shutter 1/125 second, aperture
F8, sensitivity ISO200.
Undercure, maturation, overdone 5 width of tobacco leaf picture are selected in each position respectively, using professional image software to captured
Picture handled, every tobacco leaf blade tip, Ye Zhong, phyllopodium master pulse two point side-draw are observed, observation point distribution is as shown in Figure 1.
Observation procedure are as follows: determine substantially observation position first, secondly with W/H 6-7cm elliptical marquee (or round, rectangular),
And mosaic filter (or colour mixture processing), cell size are added to selected section in frame are as follows: lower two canopies 20 are rectangular, 50 side of waist leaf
Shape, upper two canopy 100 are rectangular；Mosaic centre of figure position in frame is sampled using suction pipe finally, measures and records rgb value.
Set the maturity V value of various combination.For ease of understanding, setting maturity V value range between 0-10, get over by V value
Greatly, maturity is higher.This experiment is based on R, G, B three primary colors, the photograph of the tobacco sample material by above-mentioned various maturity
The color color value at piece and each position is as reference standard, after extracting each position numerical value, obtains eight groups of calculating by calculating
Formula can embody the mature angle value of tobacco leaf: V1=10*R/255, V2=10* (255-G)/255, V3=5* (R+255- well
G)/25, V4=18*R/255, V5=10*B/255, V6=10* (255-B)/255, V7=5* (255-G+255-B)/255, V8
=(V1+V2)/2.
By taking middle leaf as an example, from underdone to overdone, the maturity V value variation respectively combined is as shown in Figure 2.It can from Fig. 2
Out, the variation tendency of V4, V2, V1 tri- combinations is obvious, very poor more than 1, can be used as alternative.
By taking upper leaf as an example, from underdone to overdone, the V value variation tendency respectively combined is as shown in Figure 3.From figure 3, it can be seen that
It is equally that tri- V value variations of V4, V1 are obvious, V2 is relatively flat in the variation tendency of upper leaf maturation to overdone.
In synthesis, upper tobacco leaf underdone to overdone variation tendency, from the point of view of very poor size, V4 > V1 > V2 is first
Select V4.Further to grasp the otherness that V value changes between different parts, need to detect each position V value conspicuousness.Different parts
Differing maturity V4 value conspicuousness testing result such as following table 1-3.
1 inferior leads differing maturity V4 value Multiple range test of table
Dependent variable: VAR00002
* the significance of the equal value difference of is 0.01.
2 middle leaf differing maturity V4 value Multiple range test of table
Dependent variable: VAR00004
* the significance of the equal value difference of is 0.01.
3 upper leaf differing maturity V4 value Multiple range test of table
Dependent variable: VAR00006
Testing result is shown, for inferior leads, middle leaf, with the raising of maturity, extremely significant variation is presented in V4 value；
For upper leaf, it is underdone, mature between V4 value variation and its significant, though mature, overdone V4 value changes not up to extremely significant water
It is flat, but reached the level of signifiance.Speculate reason, may sufficiently be stayed with upper leaf maturity support it is related.To sum up, V4 value can be made
For the index for evaluating different parts differing maturity color gamut value.In conjunction with different parts climax leaves V4 value and standard deviation, it is believed that
Inferior leads V4 value in 8.35 ± 1.02 ranges, middle leaf V4 value in 6.17 ± 1.12 ranges, upper leaf V4 value 6.68 ±
In 1.55 ranges, reach ripeness standard.Lower than this range, maturity is still not enough to reach mature harvesting standard；Higher than this model
It encloses, needs to adopt as early as possible roasting, prevent from mature excessively baking withered.
Embodiment 4: on the basis of embodiment 3, when the tobacco leaf detection position is upper leaf, mosaic processing presses 100
Grid size is handled；When the tobacco leaf detection position is middle leaf, mosaic processing is handled by 50 grid sizes；Institute
State tobacco leaf detection position be inferior leads when, mosaic processing is handled by 20 grid sizes.The ripeness standard value range are as follows:
When the tobacco leaf detection position is upper leaf, ripeness standard value range is 6.68 ± 1.55；The tobacco leaf detection position is middle part
Ye Shi, ripeness standard value range are 6.17 ± 1.12；When the tobacco leaf detection position is inferior leads, ripeness standard value range is
8.35±1.02。
Embodiment 5: on the basis of embodiment 1, maturity calculation formula is maturation angle value=10*R/ in the step S3
255, obtain the maturity of tobacco leaf test section；The ripeness standard value range are as follows: mature when the tobacco leaf detection position is upper leaf
Standard value range is 3.71 ± 1；When the tobacco leaf detection position is middle leaf, ripeness standard value range is 3.43 ± 1.5.
Embodiment 6: on the basis of embodiment 1, the method for the mature angle value of tobacco leaf test section is obtained in the step S3 are as follows:
From G value is extracted in tobacco leaf detection position in the rgb value of image, G value is brought into maturity calculation formula: mature angle value=10*
In (255-G)/255, the mature angle value of tobacco leaf test section, the ripeness standard value range are obtained are as follows: the tobacco leaf detection position is
When upper leaf, ripeness standard value range is 5.77+0.6；When the tobacco leaf detection position is middle leaf, ripeness standard value range is
5.93±0.25。
Claims (10)
1. a kind of lossless rapid detection method of cured tobacco leaf maturity, which comprises the following steps:
S1, the tobacco leaf color image information that tobacco leaf to be detected is acquired by image capture device；
S2, tobacco leaf color image information is subjected to image procossing, determines the tobacco leaf detection position in tobacco leaf color image information, obtains
Take the rgb value of image in tobacco leaf detection position；
S3, from tobacco leaf detection position in the rgb value of image extract R value, bring R value into maturity calculation formula: mature angle value
In=18*R/255, the mature angle value of tobacco leaf test section is obtained；
Whether the resulting mature angle value of S4, measuring process S3 is within the scope of ripeness standard value, if so, tobacco leaf to be detected be at
It is ripe, if it has not, judging that mature angle value is more than or less than ripeness standard value range, it is less than, then tobacco leaf to be detected is prematurity, greatly
In then tobacco leaf to be detected is postmaturity.
2. the lossless rapid detection method of cured tobacco leaf maturity according to claim 1, which is characterized in that the step S1
In by image capture device acquire tobacco leaf to be detected tobacco leaf color image information comprising steps of image capture device in nature
Illuminance acquires the tobacco leaf color image information of tobacco leaf to be detected at 300-1000lx under environment；Or illuminance exists indoors
The tobacco leaf cromogram of tobacco leaf to be detected is acquired in 1800-2200lx and under conditions of WHITE TONE value is in 5500-6000K
As information.
3. the lossless rapid detection method of cured tobacco leaf maturity according to claim 2, which is characterized in that described image is adopted
Integrate equipment as IP Camera, smart phone or digital camera, described image acquires parameter setting when equipment acquisition are as follows: shutter
1/125 second, aperture F8, sensitivity ISO200.
4. the lossless rapid detection method of cured tobacco leaf maturity according to claim 1, which is characterized in that the step S2
The method of tobacco leaf detection position in middle determining tobacco leaf color image information includes: to judge tobacco leaf in tobacco leaf color image information
Direction simultaneously determines tobacco leaf top, middle part region；It extracts high wide in 2-8cm in region in the middle part of tobacco leaf top or tobacco leaf
Rectangular, round or elliptical image-region, obtain tobacco leaf detection position.
5. the lossless rapid detection method of cured tobacco leaf maturity according to claim 1, which is characterized in that the step S2
The middle method for obtaining the rgb value of image in tobacco leaf detection position includes: by the color mould in the image-region of tobacco leaf detection position
Formula is converted to RGB mode, and color mixing processing is made, and extracts the color information in image-region centre after color mixing processing
Rgb value.
6. the lossless rapid detection method of cured tobacco leaf maturity according to claim 5, which is characterized in that the color is mixed
Conjunction processing includes: that the image information of tobacco leaf detection position is carried out mosaic processing, and the mosaic processing presses 20~100 grids
Size is handled.
7. the lossless rapid detection method of cured tobacco leaf maturity according to claim 6, which is characterized in that the tobacco leaf inspection
When survey position is upper leaf, mosaic processing is handled by 100 grid sizes；When the tobacco leaf detection position is middle leaf,
Mosaic processing is handled by 50 grid sizes；When the tobacco leaf detection position is inferior leads, mosaic processing presses 20 grids
Size is handled.
8. the lossless rapid detection method of cured tobacco leaf maturity according to claim 1, which is characterized in that the mature mark
Quasi- value range are as follows: when the tobacco leaf detection position is upper leaf, ripeness standard value range is 6.68 ± 1.55；The tobacco leaf detection
When position is middle leaf, ripeness standard value range is 6.17 ± 1.12；When the tobacco leaf detection position is inferior leads, ripeness standard
Being worth range is 8.35 ± 1.02.
9. the lossless rapid detection method of cured tobacco leaf maturity according to claim 1, which is characterized in that the step S3
Middle maturity calculation formula is maturation angle value=10*R/255, obtains the maturity of tobacco leaf test section；The ripeness standard value range
Are as follows: when the tobacco leaf detection position is upper leaf, ripeness standard value range is 3.71 ± 1；The tobacco leaf detection position is middle part
Ye Shi, ripeness standard value range are 3.43 ± 1.5.
10. the lossless rapid detection method of cured tobacco leaf maturity according to claim 1, which is characterized in that the step
The method of the mature angle value of tobacco leaf test section is obtained in S3 are as follows: from G value is extracted in tobacco leaf detection position in the rgb value of image, by G value
It brings maturity calculation formula into: in mature angle value=10* (255-G)/255, obtaining the mature angle value of tobacco leaf test section, the maturation
Standard value range are as follows: when the tobacco leaf detection position is upper leaf, ripeness standard value range is 5.77+0.6；The tobacco leaf detection
When position is middle leaf, ripeness standard value range is 5.93 ± 0.25.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811541440.2A CN109540894A (en) | 2018-12-17 | 2018-12-17 | A kind of lossless rapid detection method of cured tobacco leaf maturity |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811541440.2A CN109540894A (en) | 2018-12-17 | 2018-12-17 | A kind of lossless rapid detection method of cured tobacco leaf maturity |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109540894A true CN109540894A (en) | 2019-03-29 |
Family
ID=65854835
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811541440.2A Pending CN109540894A (en) | 2018-12-17 | 2018-12-17 | A kind of lossless rapid detection method of cured tobacco leaf maturity |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109540894A (en) |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110082399A (en) * | 2019-04-25 | 2019-08-02 | 云南中烟工业有限责任公司 | A kind of fast non-destructive detection method of fresh tobacco leaves total reducing sugar |
| CN110412026A (en) * | 2019-08-13 | 2019-11-05 | 张家口卷烟厂有限责任公司 | A kind of tobacco aromaticss preparation accuracy method for quickly detecting |
| CN112926648A (en) * | 2021-02-24 | 2021-06-08 | 北京优创新港科技股份有限公司 | Method and device for detecting abnormality of tobacco leaf tip in tobacco leaf baking process |
| CN113919442A (en) * | 2021-02-24 | 2022-01-11 | 北京优创新港科技股份有限公司 | Tobacco maturity state recognition model based on convolutional neural network |
| CN114609135A (en) * | 2022-02-24 | 2022-06-10 | 河南中烟工业有限责任公司 | BP neural network-based flue-cured tobacco leaf field maturity mobile phone intelligent discrimination method |
| CN115067529A (en) * | 2022-07-28 | 2022-09-20 | 青岛海尔空调器有限总公司 | Tobacco curing equipment and tobacco curing method |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102323221A (en) * | 2011-05-31 | 2012-01-18 | 河南农业大学 | Tobacco maturity detection method and device |
| CN102445276A (en) * | 2011-09-26 | 2012-05-09 | 黑龙江省科学院自然与生态研究所 | Preparation method for nitrogen fertilizer management leaf color chart of flue-cured tobacco |
| CN102998438A (en) * | 2012-12-13 | 2013-03-27 | 广东中烟工业有限责任公司 | Maturity analysis and judgment method for field tobacco leaves |
| JP2013068457A (en) * | 2011-09-21 | 2013-04-18 | Jsv Co Ltd | Rgb skin color analyzer for animal or plant |
| CN103245618A (en) * | 2013-05-24 | 2013-08-14 | 贵州省烟草科学研究院 | Method for quick nondestructive detection on maturity of organic flue-cured tobacco leaves |
| CN103278458A (en) * | 2013-05-24 | 2013-09-04 | 贵州省烟草科学研究院 | Quick nondestructive test method for harvest maturity of flue-cured tobaccos |
| CN104899424A (en) * | 2015-05-07 | 2015-09-09 | 中国烟草总公司郑州烟草研究院 | Microscopic feature based method for objectively testing ripeness and leaf structure of flue-cured tobacco leaves |
| US20150257352A1 (en) * | 2014-03-12 | 2015-09-17 | Syngenta Participations Ag | Pepper Plants Producing Fruits With Extreme Dark Green Color |
-
2018
- 2018-12-17 CN CN201811541440.2A patent/CN109540894A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102323221A (en) * | 2011-05-31 | 2012-01-18 | 河南农业大学 | Tobacco maturity detection method and device |
| JP2013068457A (en) * | 2011-09-21 | 2013-04-18 | Jsv Co Ltd | Rgb skin color analyzer for animal or plant |
| CN102445276A (en) * | 2011-09-26 | 2012-05-09 | 黑龙江省科学院自然与生态研究所 | Preparation method for nitrogen fertilizer management leaf color chart of flue-cured tobacco |
| CN102998438A (en) * | 2012-12-13 | 2013-03-27 | 广东中烟工业有限责任公司 | Maturity analysis and judgment method for field tobacco leaves |
| CN103245618A (en) * | 2013-05-24 | 2013-08-14 | 贵州省烟草科学研究院 | Method for quick nondestructive detection on maturity of organic flue-cured tobacco leaves |
| CN103278458A (en) * | 2013-05-24 | 2013-09-04 | 贵州省烟草科学研究院 | Quick nondestructive test method for harvest maturity of flue-cured tobaccos |
| US20150257352A1 (en) * | 2014-03-12 | 2015-09-17 | Syngenta Participations Ag | Pepper Plants Producing Fruits With Extreme Dark Green Color |
| CN104899424A (en) * | 2015-05-07 | 2015-09-09 | 中国烟草总公司郑州烟草研究院 | Microscopic feature based method for objectively testing ripeness and leaf structure of flue-cured tobacco leaves |
Non-Patent Citations (3)
| Title |
|---|
| QIANG WANG 等: "Design of a tobacco leaf maturity degree detection device based on image processing technology", 《MATERIALS, MANUFACTURING TECHNOLOGY,ELECTRONICS AND INFORMATION SCIENCE》 * |
| 刘剑君 等: "基于数字图像数据的烤烟成熟度指数研究", 《中国烟草学报》 * |
| 罗斐 等: "《烟叶密集烘烤问答》", 31 May 2014, 中国科学技术大学出版社 * |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110082399A (en) * | 2019-04-25 | 2019-08-02 | 云南中烟工业有限责任公司 | A kind of fast non-destructive detection method of fresh tobacco leaves total reducing sugar |
| CN110412026A (en) * | 2019-08-13 | 2019-11-05 | 张家口卷烟厂有限责任公司 | A kind of tobacco aromaticss preparation accuracy method for quickly detecting |
| CN112926648A (en) * | 2021-02-24 | 2021-06-08 | 北京优创新港科技股份有限公司 | Method and device for detecting abnormality of tobacco leaf tip in tobacco leaf baking process |
| CN112926648B (en) * | 2021-02-24 | 2021-11-16 | 北京优创新港科技股份有限公司 | Method and device for detecting abnormality of tobacco leaf tip in tobacco leaf baking process |
| CN113919442A (en) * | 2021-02-24 | 2022-01-11 | 北京优创新港科技股份有限公司 | Tobacco maturity state recognition model based on convolutional neural network |
| CN114609135A (en) * | 2022-02-24 | 2022-06-10 | 河南中烟工业有限责任公司 | BP neural network-based flue-cured tobacco leaf field maturity mobile phone intelligent discrimination method |
| CN115067529A (en) * | 2022-07-28 | 2022-09-20 | 青岛海尔空调器有限总公司 | Tobacco curing equipment and tobacco curing method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109540894A (en) | A kind of lossless rapid detection method of cured tobacco leaf maturity | |
| CN103278458B (en) | A kind of fast non-destructive detection method of flue-cured tobacco harvest maturity | |
| CN102323221B (en) | Tobacco maturity detection method and device | |
| CN106841051B (en) | A kind of crop nitrogen nutrition detection method based on visual image fusion value | |
| CN105651713B (en) | A kind of green vegetables leaf chlorophyll quantitative detecting method based on computer image analysis | |
| CN109029588A (en) | A kind of Grain Growth Situation prediction technique based on climatic effect | |
| Karcher et al. | Digital image analysis in turfgrass research | |
| CN105021617B (en) | Whole strain chlorophyll content of rice measurement apparatus and method based on high light spectrum image-forming | |
| Ishak et al. | Image based modeling for oil palm fruit maturity prediction | |
| Kodani et al. | Seasonal patterns of canopy structure, biochemistry and spectral reflectance in a broad-leaved deciduous Fagus crenata canopy | |
| CN108710766A (en) | A kind of hothouse plants liquid manure machine tune fertilizer calculation method of parameters based on growth model | |
| CN107229999A (en) | Method, system, computer device and readable storage medium for predicting crop yield | |
| CN107767364A (en) | The method that trees canopy surface temperature is precisely extracted based on thermal-induced imagery | |
| CN111199192A (en) | Method for detecting integral maturity of field red globe grapes by adopting parallel line sampling | |
| CN106442329A (en) | Winter wheat leaf area index estimation method based on canopy image parameters | |
| CN102279160A (en) | Method for evaluating quality of famous green tea | |
| CN205484051U (en) | Detection apparatus for citrus canker | |
| CN103245618B (en) | A kind of fast non-destructive detection method of organic cured tobacco leaf degree of ripeness | |
| CN112715159A (en) | Automatic citrus picking method and device based on mechanical arm | |
| CN104720813B (en) | Obtaining method of standard color atla for representing complexion and application of obtaining method | |
| CN108120802B (en) | Quantitative prediction method for flue-cured tobacco maturity field investigation for determining appropriate harvesting period of tobacco leaves | |
| CN112837301A (en) | Method for judging color and color impurity degree of dry tea leaves | |
| CN106248591B (en) | Device for distinguishing maturity degree of tobacco leaves and distinguishing method thereof | |
| CN115134384A (en) | Power machine manufacturing management system based on intelligent agriculture | |
| Pasinetti et al. | How water affects growing plants: an experimental set-up based on 2D vision and on-the-edge sensing |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20190329 |