CN106644998A - Novel fruit thinning method - Google Patents
Novel fruit thinning method Download PDFInfo
- Publication number
- CN106644998A CN106644998A CN201610881157.9A CN201610881157A CN106644998A CN 106644998 A CN106644998 A CN 106644998A CN 201610881157 A CN201610881157 A CN 201610881157A CN 106644998 A CN106644998 A CN 106644998A
- Authority
- CN
- China
- Prior art keywords
- fruit
- carpopodium
- sucrose
- near infrared
- concentration
- 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.)
- Granted
Links
- 235000013399 edible fruits Nutrition 0.000 title claims abstract description 99
- 238000000034 method Methods 0.000 title claims abstract description 30
- 229930006000 Sucrose Natural products 0.000 claims abstract description 65
- 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 claims abstract description 62
- 239000005720 sucrose Substances 0.000 claims abstract description 53
- 240000003768 Solanum lycopersicum Species 0.000 claims abstract description 32
- 235000007688 Lycopersicon esculentum Nutrition 0.000 claims abstract description 28
- 238000002329 infrared spectrum Methods 0.000 claims abstract description 17
- 241000196324 Embryophyta Species 0.000 claims abstract description 6
- 244000061458 Solanum melongena Species 0.000 claims abstract description 3
- 235000002597 Solanum melongena Nutrition 0.000 claims abstract description 3
- 240000004160 Capsicum annuum Species 0.000 claims abstract 2
- 235000008534 Capsicum annuum var annuum Nutrition 0.000 claims abstract 2
- 229960004793 sucrose Drugs 0.000 claims description 58
- 235000013311 vegetables Nutrition 0.000 claims description 14
- 238000001514 detection method Methods 0.000 claims description 8
- 238000001228 spectrum Methods 0.000 claims description 7
- 238000010219 correlation analysis Methods 0.000 claims description 3
- 230000000875 corresponding effect Effects 0.000 claims description 3
- 239000000284 extract Substances 0.000 claims description 3
- 125000000185 sucrose group Chemical group 0.000 claims description 3
- 238000004497 NIR spectroscopy Methods 0.000 abstract description 7
- 230000012010 growth Effects 0.000 description 12
- 238000004519 manufacturing process Methods 0.000 description 8
- 238000009395 breeding Methods 0.000 description 5
- 230000001488 breeding effect Effects 0.000 description 5
- 240000000111 Saccharum officinarum Species 0.000 description 3
- 235000007201 Saccharum officinarum Nutrition 0.000 description 3
- 230000003698 anagen phase Effects 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 210000003608 fece Anatomy 0.000 description 3
- 239000010871 livestock manure Substances 0.000 description 3
- 238000011161 development Methods 0.000 description 2
- 230000018109 developmental process Effects 0.000 description 2
- 244000037666 field crops Species 0.000 description 2
- 238000003898 horticulture Methods 0.000 description 2
- 239000007788 liquid Substances 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 241000607479 Yersinia pestis Species 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000012512 characterization method Methods 0.000 description 1
- 238000000205 computational method Methods 0.000 description 1
- 230000003750 conditioning effect Effects 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 201000010099 disease Diseases 0.000 description 1
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000004720 fertilization Effects 0.000 description 1
- 238000003306 harvesting Methods 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 239000002932 luster Substances 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 235000015097 nutrients Nutrition 0.000 description 1
- 238000013138 pruning Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 230000002792 vascular Effects 0.000 description 1
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
- G01N21/17—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
-
- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01G—HORTICULTURE; CULTIVATION OF VEGETABLES, FLOWERS, RICE, FRUIT, VINES, HOPS OR SEAWEED; FORESTRY; WATERING
- A01G22/00—Cultivation of specific crops or plants not otherwise provided for
Landscapes
- Physics & Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Chemical & Material Sciences (AREA)
- Environmental Sciences (AREA)
- Health & Medical Sciences (AREA)
- Botany (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Investigating Or Analysing Materials By Optical Means (AREA)
- Cultivation Of Plants (AREA)
Abstract
The invention discloses a novel fruit thinning method. A near-infrared spectroscopy is utilized to scan sucrose solutions of different concentrations, characteristic wavelengths are extracted, a mathematical equation of sucrose concentration and near infrared spectrum reflection strength under the characteristic wavelengths is established, and thus a method for detecting content of sucrose in carpopodium of a fruit is obtained by adopting the near-infrared spectroscopy. The near-infrared spectroscopy is adopted to scan the carpopodium of the primarily-born fruit on the plant to obtain near-infrared spectrum data, and the concentration of the sucrose in the carpopodium is obtained according to the mathematical equation in the first step; the concentration of the sucrose in the carpopodium is compared with the concentration of sucrose in carpopodium of an adjacent fruit, and the fruit with the lowest concentration of the sucrose in the carpopodium is selected to thin fruits. According to the method, the fruit thinning effectiveness can be improved, and the method can be applied to fruit thinning of tomatoes, sweet peppers and eggplants and the like.
Description
Technical field
The invention belongs to facilities horticulture cultivation field, and in particular to one kind is accurately positioned greenhouse kind using near infrared spectrum
The technology of eggplant vegetables and fruits position.
Background technology
Facilities horticulture quickly grows in China, develop into from 1.03 ten thousand hectares of nineteen eighty-two 2015 410.9 ten thousand hectares, always
Area ranks first in the world.At present tomato pruning technique is mainly transplanted from field production technology in China's facility cultivation, i.e.,
By the experience of the producer, select to need the fruit for removing to carry out vegetables and fruits, this method tool needs the producer to give birth to tamato fruit
The very deep understanding of long law of development, and with subjectivity and randomness.But land for growing field crops tomato cultivation exists with greenhouse tomato cultivation
Many differences, following 3 aspects are specifically mainly reflected in：
1) facility cultivation medium temperature chamber tomato breeding time remote super large field.In current Production of Large Fields, due to the restriction of breeding time,
Breeding time terminates tomato typically after the harvesting of 3-4 fruit branches.And the breeding time of greenhouse tomato can extend to 270 days in North China
Left and right,
2) microclimate environment of suitable tomato growth in greenhouse is createed by facility in facility cultivation, makes tomato in optimal
Upgrowth situation in.And environment conditioning cannot be carried out in field production, therefore tomato is made often in unfavorable growing environment.
3) at present in facility cultivation mostly using soilless culture, nutrient solution pouring pattern, and fertilising is adopted in field production
Base manure and the mode topdressed.In state of the facility cultivation medium temperature chamber tomato in waning without liquid manure, and Jing often locates in field production
Wane under state in liquid manure.
Compared with field production, the tomato of facility cultivation is in optimal upgrowth situation, and with longer breeding time,
The dynamic rule in source storehouse has very big difference with field production.Therefore the vegetables and fruits method in land for growing field crops is simply transplanted to into facility cultivation
In, it is impossible to enough give full play of the growth potential of Tomato in Protected Cultivation.
Therefore hothouse production person frequently encounters following situation when vegetables and fruits are carried out：In Autumn cultivation, each fruit ear
Need to stay 3 fruits on request, but there are 4 fruits on fruit ear at present, and in the same size, this when is which fruit of the removal actually
For this problem, the present invention establishes a kind of method of greenhouse tomato vegetables and fruits by research.
The quality of fruit growth depends primarily on the amount that assimilation products distributes to fruit, the input of assimilation products amount number take
Certainly in Sink strength.At present the computational methods of greenhouse tomato Sink strength are the letter of fruit growth speed under potential growth state
Number.This method can be very good the upgrowth situation for explaining greenhouse tomato fruit.But exist following not enough：First, fruit growth
Speed needs practical measurement to obtain, it is difficult to look-ahead, with hysteresis quality.Secondly, the S-type life of growth of greenhouse tomato fruit
It is long, can be divided into following growth phase, slow growth phase, exponential growth and linear growth rank according to growth rate
Section.In different growth phases, there is very big difference in fruit growth speed, cause Sink strength to be difficult to accurate calculating.Therefore compel
Being essential will seek a kind of method for being capable of accurate Characterization Sink strength.
Greenhouse tomato assimilation products is mainly transported in fruit by the vascular bundle of bast in the form of sucrose from blade,
Assimilation products is more to the assimilation products that single fruit is transported, then the cane sugar content at this fruit carpopodium position is higher, then fruit
It is real better with regard to what is grown.Therefore the height of cane sugar content becomes an effectively evaluating of following fruit growth quality in carpopodium
Standard.
Increasing research at present thinks that near infrared spectrum can be with the sucrose in Accurate Determining plant, with lossless, real
When advantage, therefore the present invention initially sets up the detection model using near infrared ray carpopodium cane sugar content, by detection
The cane sugar content that model inspection carpopodium goes out, with the upgrowth situation of the following fruit of height prediction of cane sugar content.By comparing acquisition
Carpopodium at cane sugar content, remove carpopodium in cane sugar content low fruit, provide guidance for greenhouse tomato vegetables and fruits.
The content of the invention
It is an object of the invention to provide a kind of new fruit thinning method, to improve the validity of vegetables and fruits.
In order to solve above technical problem, the present invention is according to sucrose concentration and near infrared spectrum reflected intensity under specific wavelength
Closely related the characteristics of, a kind of tomato fruit thinning method based near infrared spectrum is devised, concrete technical scheme is as follows：
A kind of new fruit thinning method, it is characterised in that comprise the following steps：
Step one, using near infrared spectrometer the sucrose solution of variable concentrations is scanned, and extracts characteristic wavelength, sets up characteristic wave
The math equation of long lower sucrose concentration and near infrared spectrum reflected intensity, fruit is determined so as to obtain using near infrared spectrometer
The detection method of cane sugar content in carpopodium；
Step 2, the carpopodium of fruit of tentatively bearing fruit on plant is scanned using near infrared spectrometer, obtains near infrared spectrum number
According to according to sucrose concentration in the math equation acquisition carpopodium described in step one；
Step 3, sucrose concentration in the carpopodium is compared with sucrose concentration in the carpopodium of adjacent fruit, chooses
The minimum fruit of sucrose concentration is removed and carries out vegetables and fruits in carpopodium.
Math equation in the step one to set up process as follows：
Process 2.1, using near infrared spectrometer the sucrose solution that concentration is 10%, 20%, 30%, 40% is scanned respectively,
Obtain spectrum picture；
Process 2.2, using ENVI software processing spectrum pictures, extracts text data, using SPSS softwares to different characteristic
The relation of sucrose concentration and corresponding activity carries out correlation analysis under wavelength；The characteristic wavelength be 927.61 nanometers,
1129.52 nanometer, 1316.69 nanometers；
Process 2.3, using the relation between the reflected intensity and concentration under the characteristic wavelength sucrose concentration mathematics is drawn
Equation：
Y=-72.9377-0.004*X1+0.031*X2-0.0051*X3
Y is sucrose concentration X1, X2, X3Respectively wavelength 927.61, the reflected intensity under 1129.52,1316.69.
The detection method of cane sugar content is comprised the following steps in carpopodium in the step one：
Step 3.1, the carpopodium of fruit of tentatively bearing fruit on plant is scanned using near infrared spectrometer, obtains carpopodium near infrared light
Spectrogram picture；
Step 3.2, is analyzed to the carpopodium near infrared spectrum image, obtains the reflected intensity of each characteristic wavelength, generation
Enter the math equation, calculate sucrose concentration in fruit carpopodium；
Step 3.3, to tentatively bearing fruit, the sucrose concentration in fruit carpopodium is compared, minimum with sucrose concentration in carpopodium
Fruit is vegetables and fruits object。
The present invention has beneficial effect.
The near infrared spectroscopy that the present invention is adopted is more succinct, efficient, and has perspective.Traditional fruit thinning method is needed according to people
Subjective judgement, will development it is normal, carpopodium is slightly long, and uniform in size consistent, the bud green fruit of color and luster is stayed, and dredges and goes fertilization bad,
Outwardly, really push up in the middle of fruit ear to the especially short or elongated fruit of borough chief, carpopodium, and modest fruit, lopsided fruit and
Disease pest fruit；And after the near infrared spectroscopy that the present invention is adopted only needs to be scanned carpopodium using near infrared spectrometer
Compared according to equation and judged.Compare with traditional fruit thinning method, the near infrared spectroscopy that the present invention is adopted is more succinct efficient,
It is easy to operation.Near infrared spectroscopy has fully taken into account the developmental potentiality of fruit, it is to avoid will develop the more preferable fruit of later but quality
It is real to reject.
Specific embodiment
Below by taking the fruit thinning of greenhouse tomato as an example, technical scheme is described in further detail.One kind is based on
The fruit thinning method of near infrared spectrum, it includes three below step：
The first step, obtains the detection method for determining cane sugar content.
The sucrose solution of variable concentrations is scanned using near infrared spectrometer, characteristic wavelength is extracted, sugarcane under characteristic wavelength is set up
The math equation of sugared concentration and near infrared spectrum reflected intensity, obtains and determines sugarcane in greenhouse tomato carpopodium using near infrared spectrometer
The detection method of sugared content；
Second step, obtains the sucrose concentration in tomato carpopodium.
The carpopodium of fruit of tentatively bearing fruit on greenhouse tomato plant is scanned using near infrared spectrometer, near-infrared in carpopodium is obtained
The reflected intensity of spectrum, according to the math equation set up above the sucrose concentration in tomato carpopodium is obtained.
3rd step, compares and judges.
Tentatively bear fruit on the greenhouse tomato plant of the acquisition of foundation the sucrose concentration of carpopodium, and with adjacent fruit carpopodium
Sucrose concentration is compared, and choosing the minimum fruit of sucrose concentration in carpopodium carries out vegetables and fruits.
The acquisition of parameter in the present invention：
1. the near infrared spectrum test of sucrose concentration is designed, characteristic wavelength is extracted, and it is dense with different sucrose under specific wavelength
The reflected intensity of degree is independent variable, and sucrose concentration sets up the number for determining cane sugar content in greenhouse tomato carpopodium as dependent variable
Equation is learned, according to the equation vegetables and fruits are carried out.
2. concrete grammar
2.1 set up math equation
1) sucrose solution that concentration is 10%, 20%, 30%, 40% is scanned respectively using near infrared spectrometer, obtain light
Spectrogram picture.
2) using ENVI software processing spectrum pictures, text data is extracted, using SPSS softwares to sucrose under different wave length
The relation of concentration and corresponding activity carries out correlation analysis, and it is 927.61,1129.52,1316.69 to select characteristic wavelength.
3) polynomial function is calculated using the data under three characteristic wavelengths：
Y=-72.9377-0.004*X1+0.031*X2-0.0051*X3
Wherein, Y is sucrose concentration X1, X2, X3Respectively wavelength 927.61, the activity under 1129.52,1316.69.
2.2 determine the sucrose concentration in tomato carpopodium
The carpopodium of fruit of tentatively bearing fruit on greenhouse tomato plant is scanned using near infrared spectrometer, atlas of near infrared spectra is obtained
Picture, chooses the region of formed objects on carpopodium spectrum picture, takes the mean value of reflected intensity under each characteristic wavelength on the region,
Bring the sucrose concentration that the math equation set up above is obtained in tomato carpopodium into.
The selection of 2.3 fruit thinnings
According to the sucrose concentration of carpopodium of tentatively bearing fruit on the greenhouse tomato plant for obtaining, and with sugarcane in adjacent fruit carpopodium
Sugared concentration is compared, and choosing the minimum fruit of sucrose concentration in carpopodium carries out vegetables and fruits.
Claims (4)
1. a kind of new fruit thinning method, it is characterised in that comprise the following steps：
Step one, using near infrared spectrometer the sucrose solution of variable concentrations is scanned, and characteristic wavelength is extracted, under setting up characteristic wavelength
The math equation of sucrose concentration and near infrared spectrum reflected intensity, so as to obtain the carpopodium that fruit is determined using near infrared spectrometer
The detection method of interior cane sugar content；
Step 2, the carpopodium of fruit of tentatively bearing fruit on plant is scanned using near infrared spectrometer, obtains near infrared spectrum data, according to
Sucrose concentration in the carpopodium is obtained according to the math equation described in step one；
Step 3, sucrose concentration in the carpopodium is compared with sucrose concentration in the carpopodium of adjacent fruit, chooses carpopodium
The minimum fruit of interior sucrose concentration is removed and carries out vegetables and fruits.
2. a kind of new fruit thinning method according to claim 1, it is characterised in that the math equation in the step one
Set up process as follows：
Process 2.1, using near infrared spectrometer the sucrose solution that concentration is 10%, 20%, 30%, 40% is scanned respectively, is obtained
Spectrum picture；
Process 2.2, using ENVI software processing spectrum pictures, extracts text data, using SPSS softwares to different characteristic wavelength
The relation of lower sucrose concentration and corresponding activity carries out correlation analysis；The characteristic wavelength be 927.61 nanometers, 1129.52
Nanometer, 1316.69 nanometers；
Process 2.3, using the relation between the reflected intensity and concentration under the characteristic wavelength sucrose concentration math equation is drawn：
Y=-72.9377-0.004*X1+0.031*X2-0.0051*X3
Y is sucrose concentration X1, and X2, X3 is respectively the reflected intensity under wavelength 927.61,1129.52,1316.69.
3. a kind of new fruit thinning method according to claim 1, it is characterised in that sucrose contains in carpopodium in the step one
The detection method of amount is comprised the following steps：
Step 3.1, the carpopodium of fruit of tentatively bearing fruit on plant is scanned using near infrared spectrometer, obtains carpopodium atlas of near infrared spectra
Picture；
Step 3.2, is analyzed to the carpopodium near infrared spectrum image, obtains the reflected intensity of each characteristic wavelength, substitutes into institute
Math equation is stated, sucrose concentration in fruit carpopodium is calculated；
Step 3.3, to tentatively bearing fruit, the sucrose concentration in fruit carpopodium is compared, with the fruit that sucrose concentration in carpopodium is minimum
For vegetables and fruits object.
4. a kind of new fruit thinning method according to claim 1, it is characterised in that the fruit is tomato, pimento, eggplant
In any one.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610881157.9A CN106644998B (en) | 2016-10-09 | 2016-10-09 | A kind of fruit thinning method based near infrared spectrum |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610881157.9A CN106644998B (en) | 2016-10-09 | 2016-10-09 | A kind of fruit thinning method based near infrared spectrum |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106644998A true CN106644998A (en) | 2017-05-10 |
| CN106644998B CN106644998B (en) | 2019-06-25 |
Family
ID=58854295
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610881157.9A Expired - Fee Related CN106644998B (en) | 2016-10-09 | 2016-10-09 | A kind of fruit thinning method based near infrared spectrum |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106644998B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108184564A (en) * | 2017-12-28 | 2018-06-22 | 江苏大学 | A kind of method for building greenhouse solanaceous vegetables crop assimilation products distribution model |
| CN111912815A (en) * | 2019-12-20 | 2020-11-10 | 南开大学 | Near infrared spectrum analysis method for evaluating quality of oil crops |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2001305055A (en) * | 2000-04-24 | 2001-10-31 | Sumitomo Metal Mining Co Ltd | Calibrator for nondestructive transmission photometry device, calibration method using it, and nondestructive transmission photometry device comprising it |
| CN2779390Y (en) * | 2004-09-08 | 2006-05-10 | 江苏大学 | Diffuse reflection detector for near infrared konfyt acidity analysis |
| WO2007044486A1 (en) * | 2005-10-13 | 2007-04-19 | Baylor University | Spectroscopic determination of sucrose |
| CN101393122A (en) * | 2008-10-31 | 2009-03-25 | 中国农业大学 | Honey quality rapid detection method |
-
2016
- 2016-10-09 CN CN201610881157.9A patent/CN106644998B/en not_active Expired - Fee Related
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2001305055A (en) * | 2000-04-24 | 2001-10-31 | Sumitomo Metal Mining Co Ltd | Calibrator for nondestructive transmission photometry device, calibration method using it, and nondestructive transmission photometry device comprising it |
| CN2779390Y (en) * | 2004-09-08 | 2006-05-10 | 江苏大学 | Diffuse reflection detector for near infrared konfyt acidity analysis |
| WO2007044486A1 (en) * | 2005-10-13 | 2007-04-19 | Baylor University | Spectroscopic determination of sucrose |
| CN101393122A (en) * | 2008-10-31 | 2009-03-25 | 中国农业大学 | Honey quality rapid detection method |
Non-Patent Citations (1)
| Title |
|---|
| 王亚红等: "基于PCＲ和PLS的蔗糖浓度透反射测量方法研究", 《激光与红外》 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108184564A (en) * | 2017-12-28 | 2018-06-22 | 江苏大学 | A kind of method for building greenhouse solanaceous vegetables crop assimilation products distribution model |
| WO2019127624A1 (en) * | 2017-12-28 | 2019-07-04 | 江苏大学 | Method for building assimilate allocation model of greenhouse solanaceous vegetables |
| CN111912815A (en) * | 2019-12-20 | 2020-11-10 | 南开大学 | Near infrared spectrum analysis method for evaluating quality of oil crops |
| CN111912815B (en) * | 2019-12-20 | 2023-03-14 | 南开大学 | Near infrared spectrum analysis method for evaluating quality of oil crops |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106644998B (en) | 2019-06-25 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| EP3211987B1 (en) | Method for providing a three-dimensional assessment of water movement through soil and across a field and associated system | |
| Dambergs et al. | A review of the state of the art, limitations, and perspectives of infrared spectroscopy for the analysis of wine grapes, must, and grapevine tissue | |
| Peirs et al. | Effect of natural variability among apples on the accuracy of VIS-NIR calibration models for optimal harvest date predictions | |
| Meléndez et al. | Modelling phenolic and technological maturities of grapes by means of the multivariate relation between organoleptic and physicochemical properties | |
| Pérez-Marín et al. | Postharvest shelf-life discrimination of nectarines produced under different irrigation strategies using NIR-spectroscopy | |
| CN108519339B (en) | WT-L SSVR-based leaf cadmium content Vis-NIR spectral feature modeling method | |
| Bonora et al. | A new simple modeling approach for the early prediction of harvest date and yield in nectarines | |
| Giuffrida et al. | A simple model for nondestructive leaf area estimation in bedding plants | |
| Acharya et al. | Robustness of Tomato Quality Evaluation Using a Portable Vis‐SWNIRS for Dry Matter and Colour | |
| Salinas et al. | Fruit growth model, thermal requirements and fruit size determinants in papaya cultivars grown under subtropical conditions | |
| González-Fernández et al. | Relationship between physical and chemical parameters for four commercial grape varieties from the Bierzo region (Spain) | |
| Olfati et al. | An estimation of individual leaf area in cabbage and broccoli using non-destructive methods. | |
| CN106644998B (en) | A kind of fruit thinning method based near infrared spectrum | |
| Wu et al. | Study on CAT activity of tomato leaf cells under salt stress based on microhyperspectral imaging and transfer learning algorithm | |
| CN109142238A (en) | A kind of cotton phosphorus nourishing fast diagnosis method | |
| Travers | Dry matter and fruit quality: manipulation in the field and evaluation with NIR spectroscopy | |
| Walsh et al. | Use of near infra-red spectroscopy in evaluation of source-sink manipulation to increase the soluble sugar content of stonefruit | |
| Walsh et al. | In-field monitoring of mango fruit dry matter for maturity estimation | |
| CN102939865B (en) | Method for judging nitrogen nutrition of tomato with nitrate nitrogen concentration of leaf stalk | |
| Lafond | Rapid Diagnosis of the Nitrogen Status of the Wild Lowbush Blueberry | |
| Navarrete | Characterizing grapevine canopy architecture | |
| Chen et al. | The application of optical nondestructive testing for fresh berry fruits | |
| Mania et al. | VICMOTO: Physical modeling and numerical simulation applied to vineyard | |
| US20220142036A1 (en) | Method for determining the topo-climatic characteristics of a geographic area | |
| Martinez-Nolasco et al. | Validation of Aeroponic Cultivation of Jalapeño Pepper (Capsicum annuum L.) through Thermal and Morphometric Characterization of Roots and Leaves |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20190625 Termination date: 20201009 |
|
| CF01 | Termination of patent right due to non-payment of annual fee |