12 results about "Unfertilized Eggs" patented technology

A method for processing a plurality of bird eggs, particularly unfertilized eggs, comprising: a step of transporting a first egg (E1) having a first eggshell color and a second egg (E2) having a second eggshell color along a transport path, wherein the first eggshell color is different from the second eggshell color; a step of illuminating the first egg (E1) with an illumination beam (B) of infrared light, wherein at least a portion of the light is transmitted through the egg (E1) and detected by a near-infrared light detector (5); a step of illuminating the second egg (E2) with an illumination beam (B) of near-infrared light, wherein at least a portion of the light is transmitted through the egg (E2) and detected by a near-infrared light detector (5); and to determine the shell condition of each egg (E1, E2), the step of processing the light detection result of the infrared light detector (5) is included, and the detection of the illumination and / or transmitted light of the eggs (E1, E2) is performed under substantially the same illumination and / or detection conditions, respectively.

Methods for improving parthenogenesis efficiency by DWT1 and BABY BOOM transcription factors in plants are provided. A rice embryo trigger transcription factor BABY BOOM1 can initiate embryogenesis when expressed in the unfertilized egg cell through a process called parthenogenesis (Khanday et al., 2019. Nature 565: 91-95). The parthenogenesis efficiency by BABY BBOM1 itself is 10-29%. This invention describes methods of high frequency of parthenogenesis by simultaneous expression of BABY BOOM and DWT1 transcription factors. When BABY BOOM1 and DWT1 are expressed together through egg cell-specific promoters, parthenogenesis efficiencies of up to 90% are achieved. These high parthenogenesis efficiencies are a prerequisite for field applications of synthetic apomixis in crop plants.

Method for processing a plurality of avian eggs, in particular unfertilized eggs, including: -conveying at least a first egg (E1) having a first eggshell color and a second egg (E2) having a second egg shell color along a conveying path, the first egg shell color being different from the second egg shell color; -illuminating the first egg (E1) with an illumination beam (B) of near infrared light, wherein at least part of the light is transmitted through the egg (E1) and is detected by a near infrared light detector (5); -illuminating the second egg (E2) with the illumination beam (B) of near infrared light, wherein at least part of the light is transmitted through the egg (E2) and is detected by the near infrared light detector (5); processing light detection results of the infrared light detector (5) for determining a condition of the shell of each of the eggs (E1, E2); wherein the illuminating of the eggs (E1, E2) and / or the detection of transmitted light is carried out under substantially the same illumination and / or detection conditions, respectively.

The application relates to a Chinese soft-shelled turtle egg hatching method and relates to the technical field of aquaculture. The hatching method comprises the following steps: wrapping collected turtle eggs with yellow sand and storing the turtle eggs; temporarily storing the stored turtle eggs and removing unfertilized eggs after development; wrapping the fertilized eggs with a hatching medium, wherein the hatching medium comprises the following raw materials in parts by weight: 5-10 parts of yellow sand, 2-5 parts of vermiculite and 1-3 parts of organic modified montmorillonite; arranging the fertilized eggs into a hatching layer; and hatching the hatching layer in a hatching environment with a temperature of 28-32 DEG C and a humidity of 60-80%, to obtain juvenile turtles. The application uses the adsorption of organic modified montmorillonite to preserve the moisture in the yellow sand. The organic modified montmorillonite has good air permeability, and even if the moisture is preserved, there will be no odor or mildew, so that the oxygen required for the hatching of the fertilized eggs can be ensured, the fertilized eggs can develop healthily, the physical quality of the hatched juvenile turtles is better, and the juvenile turtles are more likely to survive when released.

The present invention provides a primer set and method for analyzing the nanos1 gene of Macrobrachium rosenbergii, relating to the biotechnology field of reproductive-related genes in Macrobrachium rosenbergii. The Nanos1 gene obtained by the present invention has a cDNA sequence of 2811 base pairs (bp) long, encoding 243 amino acids. Nanos1 is specifically expressed in the ovary, and the expression level of nanso1 mRNA is highest in unfertilized eggs, significantly higher than after fertilization and at all stages of embryonic development. During embryonic development, expression is highest during fertilization, significantly higher than during the cleavage stage and extremely significantly higher than during the late embryonic development stage. The gene's expression level during the cleavage stage is significantly higher than from the blastocyst stage to the larvae stage; however, the expression level is lower and does not differ between the blastocyst stage and the larvae stage. Nanos1 mRNA is expressed in the cytoplasm of oogonia and primary oocytes (Oc1, Oc2, Oc3, and Oc4). Nanos1 is closely related to the development of female germ cells in Macrobrachium rosenbergii and plays an important role in the reproductive development of Macrobrachium rosenbergii, providing a theoretical basis and ideas for research on reproductive development and sex identification in Macrobrachium rosenbergii.

Method for treating a plurality of poultry eggs, in particular unfertilized eggs, comprising:-conveying each egg (E) along a conveying path; -generating a plurality of images of each egg (E) from different sides of the egg using the illumination light (B); and processing the plurality of images of each egg (E) by a digital image processor (8), determining the quality of the egg using the trained learning model, and outputting the determined quality of the egg, for example for classifying the egg.

1. A method for processing a plurality of avian eggs, particularly unfertilized eggs, comprising the steps of: - conveying each egg (E) along a conveying path; - generating a plurality of images of each egg (E) from different sides of the egg using illumination light (B); a digital image processor (8) processing a plurality of images of each egg (E) and determining the mass of the egg using the trained learning model and outputting the determined egg mass, for example for classifying the egg; A method comprising:

The invention discloses a hatching egg incubation and fertilization rate detection system based on a YOLO algorithm and photoelectric acquisition, and the system comprises a control module which is used for obtaining a corresponding hatching egg detection image through the combination of the YOLO algorithm, carrying out the detection and analysis through a suitable model, and rapidly and accurately distinguishing a fertilized egg from an unfertilized egg; the shading module is used for forming a dark environment in the hatching egg detection process to avoid interference of other light rays; the image acquisition module is used for acquiring a hatching egg detection image irradiated by the LED light and transmitting the hatching egg detection image to the control module; the illumination module is used for providing hatching light in the vertical direction for the hatching eggs to be detected; and the conveying module is used for driving the hatching eggs to be detected to enter the shading module for shooting and collecting the detection images.

Methods and systems are described for classifying unfertilized eggs. For example, using control circuitry, first images of fertilized eggs can be received, and the first images can be labeled with known classifications. Using the control circuitry, an artificial neural network can be trained to detect the known classifications based on the first images of the fertilized eggs and a second image can be received of an unfertilized egg with an unknown classification. Using the control circuitry, the second image can be input into the trained artificial neural network and a prediction from the trained artificial neural network can be received that the second image corresponds to one or more of the known classifications.

The invention relates to the technical field of eel culture, and discloses a device and method for removing unfertilized eel eggs based on machine vision, and the device comprises a recognition control assembly, a moving assembly, an egg disc positioning assembly and an eel egg removing assembly. The roe tray positioning assembly comprises roe trays used for storing to-be-screened ricefield eel roes and a roe tray placing platform used for fixing the roe trays, a roe tray pushing mechanism used for pushing the roe trays to the roe tray placing platform is arranged on one side of the roe tray placing platform, and the recognition control assembly is arranged above the roe tray placing platform. The eel egg removing assembly is fixed to the moving assembly, the eel egg removing assembly comprises egg sucking pipes which are in one-to-one correspondence with eel eggs on an egg disc, the egg sucking pipes are evenly distributed at the bottom of a negative pressure cavity, and the negative pressure cavity is connected with an air pump through a negative pressure pipe. The egg suction pipe is controlled to accurately remove eggs once, so that the working efficiency is high, the hatching rate is greatly improved, and the economic benefit of ricefield eel culture is guaranteed.

Method for processing a plurality of avian eggs, in particular unfertilized eggs, including: -conveying each egg (E) along a conveying path; -generating a plurality of images of each egg (E) from different sides of the egg using illumination light (B); and processing the plurality of images of each egg (E), by a digital image processor (8), utilizing a trained learning model to determine a mass of the egg, and outputting the determined mass of the egg, for example for classifying the egg.

Methods and systems are described for predicting probabilities of unfertilized eggs becoming blastocysts. For example, a method can include a trained machine-learning model receiving images of unfertilized eggs. The trained machine-learning model can determine predictions for each of the unfertilized eggs becoming blastocysts based at least on the appearance of the unfertilized eggs in the images. The predictions can be provided by the trained machine-learning model. Based on the predictions, a distribution of the unfertilized eggs into cohorts can be determined, including. Then, based on the cohorts, a second prediction of a cohort producing at least one blastocysts can be determined.