Banga et al., 2018 - Google Patents
Techniques for insect detection in stored food grains: An overviewBanga et al., 2018
View PDF- Document ID
- 14640497443357333179
- Author
- Banga K
- Kotwaliwale N
- Mohapatra D
- Giri S
- Publication year
- Publication venue
- Food Control
External Links
Snippet
Insects cause a major loss in stored food grains. Besides, pestilential activities of insects in stored food grains affect the marketability as well as the nutritional values. Early detection and monitoring of insects in the stored food grains become necessary for applying corrective …
- 241000238631 Hexapoda 0 title abstract description 193
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 infra-red, visible or ultra-violet 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 infra-red light
- G01N21/359—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infra-red light using near infra-red light
-
- 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 infra-red, visible or ultra-violet 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 infra-red light
- G01N21/3577—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infra-red light for analysing liquids, e.g. polluted water
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by the preceding groups
- G01N33/02—Investigating or analysing materials by specific methods not covered by the preceding groups food
- G01N33/025—Fruits or vegetables
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet 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
- G01N21/314—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry with comparison of measurements at specific and non-specific wavelengths
- G01N2021/3155—Measuring in two spectral ranges, e.g. UV and visible
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by the preceding groups
- G01N33/48—Investigating or analysing materials by specific methods not covered by the preceding groups biological material, e.g. blood, urine; Haemocytometers
- G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
- G01N29/44—Processing the detected response signal, e.g. electronic circuits specially adapted therefor
- G01N29/46—Processing the detected response signal, e.g. electronic circuits specially adapted therefor by spectral analysis, e.g. Fourier analysis or wavelet analysis
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Banga et al. | Techniques for insect detection in stored food grains: An overview | |
| Johnson | An overview of near-infrared spectroscopy (NIRS) for the detection of insect pests in stored grains | |
| Nicolaï et al. | Nondestructive measurement of fruit and vegetable quality | |
| Jia et al. | Advances in electronic nose development for application to agricultural products | |
| Chelladurai et al. | Detection of Callosobruchus maculatus (F.) infestation in soybean using soft X-ray and NIR hyperspectral imaging techniques | |
| Wen et al. | Rapid detection and classification of citrus fruits infestation by Bactrocera dorsalis (Hendel) based on electronic nose | |
| Singh et al. | Detection of insect-damaged wheat kernels using near-infrared hyperspectral imaging | |
| Moscetti et al. | Nondestructive detection of insect infested chestnuts based on NIR spectroscopy | |
| Ali et al. | Electronic nose as a tool for early detection of diseases and quality monitoring in fresh postharvest produce: A comprehensive review | |
| Srivastava et al. | Non-destructive sensing methods for quality assessment of on-tree fruits: a review | |
| Perez-Mendoza et al. | Detection of insect fragments in wheat flour by near-infrared spectroscopy | |
| Xiaobo et al. | Non-invasive sensing for food reassurance | |
| Srivastava et al. | Data processing approaches and strategies for non-destructive fruits quality inspection and authentication: a review | |
| Dutta et al. | Image processing based classification of grapes after pesticide exposure | |
| Khaled et al. | Non-destructive detection of codling moth infestation in apples using acoustic impulse response signals | |
| Shah et al. | Imaging techniques for the detection of stored product pests | |
| CN104990888A (en) | Method for detecting insect pests in stored grains by means of terahertz imaging technology | |
| Ekramirad et al. | Development of pattern recognition and classification models for the detection of vibro-acoustic emissions from codling moth infested apples | |
| Valenta et al. | Fruit ripening signals and cues in a Madagascan dry forest: haptic indicators reliably indicate fruit ripeness to dichromatic lemurs | |
| Pasikatan et al. | Sorting systems based on optical methods for detecting and removing seeds infested internally by insects or fungi: a review | |
| Ekramirad et al. | A review of non-destructive methods for detection of insect infestation in fruits and vegetables | |
| Qi et al. | Application of nondestructive techniques for peach (Prunus persica) quality inspection: A review | |
| Xing et al. | Detecting internal insect infestation in tart cherry using transmittance spectroscopy | |
| Aboonajmi et al. | Quality assessment methods and postharvest handling of fresh poultry eggs | |
| Ekramirad et al. | Low frequency signal patterns for codling moth larvae activity in apples |