Method for judging rotten blueberries based on low-field nuclear magnetic resonance technology

A low-field nuclear magnetic resonance and blueberry technology, applied in neural learning methods, image analysis, image enhancement, etc., can solve the problems of poor detection efficiency of mild rot diseases, etc., and achieve the effect of simple pre-processing

Active Publication Date: 2019-07-12
SHENYANG AGRI UNIV
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Problems solved by technology

[0004] The purpose of the present invention is to solve the problem that when the blueberry rot occurs, due to its darker color, the detection efficiency of the slight rot is not good; and it is not affected by the position of the blueberry, and the internal rot can also be detected

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  • Method for judging rotten blueberries based on low-field nuclear magnetic resonance technology
  • Method for judging rotten blueberries based on low-field nuclear magnetic resonance technology
  • Method for judging rotten blueberries based on low-field nuclear magnetic resonance technology

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Embodiment 1

[0055] The experimental blueberry variety is "Meideng", and the healthy blueberry samples and the rotten blueberry samples are first placed in a refrigerator (model SC-350, Qingdao Haier Special Refrigerator Co., Ltd.) with a temperature setting of 0±0.5°C for 4 hours. , to exclude the field heat of blueberries. Then the blueberries were stored at room temperature for 2 hours before nuclear magnetic resonance experiments. The CPMG parameters are set as follows: the repeated sampling waiting time TW is set to 1200ms, the center frequency SF 1 21MHZ, offset frequency O 1 65146516.16HZ, repeated sampling times NS is 4 times, 90°pulse RF pulse width P 1 =17μs, 180°pulse RF pulse width P 2 = 35.04 μs. The proton density image parameters are set as follows: repeat waiting time T R 1000ms, echo time T E 18.2ms, the time TI-IR of the magnetization vector zero crossing point is 20ms, the thickness of the selected layer is 1.0mm, the number of layers is set to 2, and the layer wid...

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Abstract

The invention relates to a method for judging rotten blueberries based on a low-field nuclear magnetic resonance technology, and belongs to the field of agricultural product detection. The method comprises: firstly, collecting relaxation spectrum information of blueberries to be detected through a low-field nuclear magnetic resonance system, obtaining transverse relaxation time and signal amplitudes, and obtaining 6 transverse relaxation signal variables in total; collecting a proton density weighted image of the cross section of the blueberry to be detected by using a low-field nuclear magnetic resonance system to obtain five characteristic variables, namely a mean value, a gray scale number, correlation, inertia and a gray scale average; taking the six transverse relaxation signal variables and the five characteristic variables as input vectors, inputting the input vectors into a BPNN model, and judging rotten blueberries. According to the method for judging the rotten blueberries, when the rotten blueberries are detected through the low-field nuclear magnetic resonance technology, the method is not influenced by unobvious rotting characteristic and placement directions of the blueberries with the deep color, multi-layer imaging can be further conducted on the interiors of the blueberries, and internal tissue changes caused in the blueberry rotting process are explored.

Description

technical field [0001] The invention relates to a method for discriminating rotten blueberries based on low-field nuclear magnetic resonance technology, belonging to the field of agricultural product detection. Background technique [0002] Blueberry (Blueberry) is rich in various nutrients and nutrients, including anthocyanins, flavonols, and vitamins, and is very popular among consumers. However, the blueberry fruit is extremely perishable after picking, and it is not resistant to storage. Rotten blueberries can also cause greater damage to other stored blueberries by infecting them. Traditional rotten blueberry detection mainly relies on manual sorting, but there are problems such as monotonous work, strong subjectivity, time-consuming, difficult to quantify, and internal rot that cannot be identified by naked eyes; the detection of physical and chemical indicators is destructive, and there are cumbersome pretreatment of samples to be tested. There are problems such as ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T7/136G06T5/40G06N3/08
CPCG06T7/0002G06T7/136G06N3/084G06T5/40G06T2207/10088G06T2207/20081Y02A90/30
Inventor 田有文乔世成宋士媛
Owner SHENYANG AGRI UNIV
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