Provided is a method for marking a product for human or animal use with an XRF identifiable mark, the method including forming on at least a region of the product a pattern of at least one FDA-grade material identifiable by XRF, the pattern being optionally at least partially invisible to the naked human eye and having a predefined identifiable characteristic, wherein the product is selected from food products, therapeutics and cosmetics.

Shown herein is a method of automated noninvasive determining the fertility of a bird's egg (14), comprising the following steps: conveying a plurality of bird eggs (14) sequentially or in parallel into an NMR apparatus (18), subjecting the bird eggs (14) to an NMR measurement, such as to generate a .sub.3-D NMR image of at least a part of each of said eggs (14), said .sub.3-D NMR image having a spatial resolution in at least one dimension of 1.0 mm or less, preferably of 0.50 mm or less, wherein said part of the egg (14) includes the germinal disc of the respective egg (14), determining a prediction of the fertility according to at least one of the following two procedures: (i) deriving at least one feature from each of said .sub.3-D NMR images, and employing said at least one feature in a feature-based classifier for determining a prediction of the fertility, and (ii) using a deep learning algorithm, and in particular a deep learning algorithm based on convolutional neural networks, generative adversarial networks, recurrent neural networks or long short-term memory networks.

Shown herein is a method of automated noninvasive determining the fertility of a bird's egg (14), comprising the following steps: conveying a plurality of bird eggs (14) sequentially or in parallel into an NMR apparatus (18), subjecting the bird eggs (14) to an NMR measurement, such as to generate a .sub.3-D NMR image of at least a part of each of said eggs (14), said .sub.3-D NMR image having a spatial resolution in at least one dimension of 1.0 mm or less, preferably of 0.50 mm or less, wherein said part of the egg (14) includes the germinal disc of the respective egg (14), determining a prediction of the fertility according to at least one of the following two procedures: (i) deriving at least one feature from each of said .sub.3-D NMR images, and employing said at least one feature in a feature-based classifier for determining a prediction of the fertility, and (ii) using a deep learning algorithm, and in particular a deep learning algorithm based on convolutional neural networks, generative adversarial networks, recurrent neural networks or long short-term memory networks.

Disclosed herein is a method of automated noninvasive determining the sex of an embryo of a bird's egg (14) as well as a corresponding apparatus. The method comprises the following steps: conveying a plurality of bird eggs (14) sequentially or in parallel into an NMR apparatus (18), subjecting the bird eggs (14) to an NMR measurement, to thereby determine, for each of said eggs (14), one or more NMR parameters associated with the egg (14) selected from the group consisting of a Ti relaxation time, a T2 relaxation time and a diffusion coefficient, forwarding said one or more NMR parameters, or parameters derived therefrom, to a classification module (38), said classification module (38) configured for determining, based on said one or more NMR parameters or parameters derived therefrom, a prediction of the sex of the embryo of the associated egg (14), and conveying said plurality of bird eggs (14) out of said NMR apparatus (18) and sorting the eggs (14) according to the sex prediction provided by said classification module (38).

Disclosed herein is a method of automated noninvasive determining the sex of an embryo of a bird's egg (14) as well as a corresponding apparatus. The method comprises the following steps: conveying a plurality of bird eggs (14) sequentially or in parallel into an NMR apparatus (18), subjecting the bird eggs (14) to an NMR measurement, to thereby determine, for each of said eggs (14), one or more NMR parameters associated with the egg (14) selected from the group consisting of a Ti relaxation time, a T2 relaxation time and a diffusion coefficient, forwarding said one or more NMR parameters, or parameters derived therefrom, to a classification module (38), said classification module (38) configured for determining, based on said one or more NMR parameters or parameters derived therefrom, a prediction of the sex of the embryo of the associated egg (14), and conveying said plurality of bird eggs (14) out of said NMR apparatus (18) and sorting the eggs (14) according to the sex prediction provided by said classification module (38).

The invention relates to a method for classifying spectra of objects having complex information content after recording of the spectra involving the use of a method for preprocessing data and of a method, associated with the data preprocessing, for classification with the calculation of a classifier. After the recording of the spectra and the preprocessing of the spectra, a multiple classification method is thereby performed with at least two different methods for the data preprocessing of the spectra and the method, assigned to the respective data preprocessing, for classification. After the recording and the data preprocessing of the spectra, the following steps are thereby carried out: a calculation of multiple classifiers of the series per type of data preprocessing; a determination of the classifiers of the series with iterative adjustment and validation; a calculation of probabilities of the class association, with all classifiers of the series or classifiers being equally incorporated into the determination of a classification result.

Disclosed is a method for non-destructive detection of egg freshness based on Raman spectroscopy technology, which belongs to the field of food detection. Partial least squares regression models are built using Raman spectroscopic data and measured values of physicochemical indexes for egg freshness, which can be used to predict egg freshness based on Raman spectrum of egg shell surface. The Raman spectroscopic data are collected in the waveband of 100-3000 cm.sup.−1. The physicochemical indexes used in the invention include the Haugh unit, the albumen pH, the air chamber diameter and the air chamber height. By using the partial least squares model, values of physicochemical index for egg freshness can be obtained from Raman spectra collected on egg shell surfaces, thus achieving the goal of non-destructive detection of egg freshness.

Disclosed is a method for non-destructive detection of egg freshness based on Raman spectroscopy technology, which belongs to the field of food detection. Partial least squares regression models are built using Raman spectroscopic data and measured values of physicochemical indexes for egg freshness, which can be used to predict egg freshness based on Raman spectrum of egg shell surface. The Raman spectroscopic data are collected in the waveband of 100-3000 cm.sup.−1. The physicochemical indexes used in the invention include the Haugh unit, the albumen pH, the air chamber diameter and the air chamber height. By using the partial least squares model, values of physicochemical index for egg freshness can be obtained from Raman spectra collected on egg shell surfaces, thus achieving the goal of non-destructive detection of egg freshness.

A dorsal aortic injection method of chicken embryos for improving transgenic efficiency, comprising the following steps: injecting adeno-associated virus particles into the dorsal aorta of each 2.5-day-old chicken embryo outside eggshell, individually transferring the injected chicken embryos into their recipient eggshells (coming from double yolk eggs), and proceeding to hatch. The disclosure realizes the outside-eggshell injection of the chicken embryo dorsal aorta through the modified dorsal aortic injection method, improves the accuracy of injection, and also realizes the direct observation of the development process of the chicken embryos. The survival rate of embryos, hatch rate and the efficiency of transgene expression in the modified dorsal aortic injection group are significantly higher than those in the subgerminal cavity injection group and the classic dorsal aortic injection group, indicating that the modified method improves the hatch rate of transgenic chicken embryos and EGFP expression efficiency.

An information processing apparatus according to the present technology includes an acquisition section and a prediction section. The acquisition section acquires a plurality of chronologically captured observation images of a fertilized egg, and culture environment information regarding the fertilized egg. Using the plurality of observation images and the culture environment information, the prediction section predicts a period of time necessary until the fertilized egg reaches a specified form of development, and a quality of the fertilized egg in the form of development.