Method for acquiring high-throughput phenotypic information of flammulina velutipes

A high-throughput, Flammulina velutipes technology, applied in image analysis, image enhancement, instruments, etc., can solve problems such as intelligent algorithms that are rarely studied, and achieve the effect of reducing manual operations and improving accuracy and reliability

Active Publication Date: 2020-09-18
ZHEJIANG ACADEMY OF AGRICULTURE SCIENCES
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Problems solved by technology

However, in the field of Flammulina velutipes breeding and phenotyping research, manual detection and analysis are mainly used at present. High-thro

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  • Method for acquiring high-throughput phenotypic information of flammulina velutipes
  • Method for acquiring high-throughput phenotypic information of flammulina velutipes
  • Method for acquiring high-throughput phenotypic information of flammulina velutipes

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Embodiment

[0060] Such as figure 2 As shown in a and b, the fruiting body of Flammulina velutipes on the right side has been cut from the cap insertion point into two parts, the cap and the stalk, and scanned into an image. Apply RGB multi-channel grayscale processing and binary image visual analysis algorithm to obtain the polygonal coordinate group of the graphic boundary, wherein the aspect ratio of the upper graphic is greater than 5:1, and it is determined to be a fungus; the lower graphic aspect ratio is less than 5: 1. Determined as a cap. Using the OpenCV library function to calculate the area of ​​the cap graphic is S=4.69cm 2 , the minimum circumscribed circle area S C =5.86cm 2 , the calculated near-round ratio C = 0.80. Using the OpenCV library function to calculate the cap center point coordinates (G) and the insertion point coordinates (P), the distance from G to P is obtained as the center axis distance M = 4.08mm. Perform the above operations on the standard fruitin...

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Abstract

The invention discloses a method for acquiring high-throughput phenotypic information of flammulina velutipes. According to the method, flammulina velutipes sporocarp sampling, image scanning, machinevision recognition and an artificial intelligence algorithm are adopted; the pileus nearly-circular rate, the pileus area, the pileus attachment point and the middle axle distance of the flammulina velutipes sporocarp are automatically calculated on a large scale through a sporocarp cutting and scanning image; an image segmentation cutting method is used for automatically measuring the length andwidth data of mushroom stems on a large scale, and the standard color distance between flammulina velutipes pilei and the mushroom stems is automatically measured on a large scale based on standard flammulina velutipes sporocarp image color information, so that flammulina velutipes sporocarp phenotypic information is obtained on a large scale. According to the method, a machine vision recognitionalgorithm and a deep learning model are adopted, so that manual operation in flammulina velutipes breeding work is reduced, errors and random errors of a measurement system are reduced, and the reliability of test data is improved.

Description

technical field [0001] The invention belongs to the technical field of Flammulina velutipes breeding, and in particular relates to a method for acquiring high-throughput phenotypic information of Flammulina velutipes. Background technique [0002] Flammulina velutipes (English name: Enoki, Gold mushroom) is a fungus belonging to the family Trichomonas genus Chrysanthemum. It is a kind of edible fungus widely cultivated in the world, and its domestic production and sales rank among the most edible fungi. Compared with other edible fungi, Flammulina velutipes has a higher amino acid content, especially the highest content of lysine, and is known as "medicine and food fungus". Due to the small size of Flammulina velutipes, they are not picky about nutrients, but they are not picky about the temperature and humidity, light and CO of the growth environment. 2 The concentration requirement is high, so the most suitable production method is industrial cultivation production, and i...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06T7/10G06T7/62G06T7/90
CPCG06T7/0002G06T7/10G06T7/62G06T7/90G06T2207/10024G06T2207/30188G06T2207/20081
Inventor 张小斌朱怡航沈颖越顾清金群力郑可锋
Owner ZHEJIANG ACADEMY OF AGRICULTURE SCIENCES
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