78 results about "Food Analysis" patented technology

The present disclosure provides methods and systems for providing personalized food and health management recommendations. The method may include mapping a food product by abstracting information from data related to the food product to develop a food product ontology. The method may include collecting and aggregating a plurality of data sets related to food, health, or nutritional information of a user. The plurality of data sets may be provided in two or more different formats from multiple sources. The method may include converting the plurality of data sets into a standardized format that may be individualized for the user. The method may include applying a predictive model to the food body and the plurality of data sets of the user in the standardized format to determine an impact of food consumption of the user body.

The invention relates to the technical field of medical health monitoring and evaluation, and discloses a method and system for evaluating and monitoring the nutrition risk of a cancer palliative treatment patient, and the method comprises the steps: obtaining a daily diet image of the cancer patient through an image device, recognizing the type of food in the daily diet image, recognizing the weight of food in the daily diet image, and calculating the nutrition risk of the cancer palliative treatment patient; analyzing diner actions in the daily diet image; the daily diet condition of the cancer patient is analyzed according to the food category, the food weight, the diner action and the target food, the nutrition change item of the initial nutrition condition is determined according to the daily diet condition, and the nutrition risk condition of the cancer patient is identified according to the nutrition change item; determining target monitoring equipment of the cancer patient from non-image equipment; and constructing a nutrition risk sequence of the nutrition risk level, analyzing the nutrition risk trend of the cancer patient by using the nutrition risk sequence, and determining a nutrition risk monitoring result of the cancer patient. The convenience of nutrition risk assessment of the patient can be improved.

The invention provides an article adulteration detection method and system based on stable isotope and electronic equipment, and relates to the technical field of food analysis and detection.The method comprises the steps that a target sample and a control sample of an article to be detected are obtained, and article quality pretreatment is conducted on the target sample and the control sample; carrying out doped sample merging on the target sample and the contrast sample after article quality pretreatment to obtain a doped sample to be detected; wherein the doping sample combination type comprises combination of the same total amount and different proportions and combination of the same proportion and different total amount; performing identification pretreatment on the to-be-detected doped samples, and performing isotope determination on the to-be-detected doped samples subjected to identification pretreatment to obtain various isotope values of specified types corresponding to different to-be-detected doped samples; and performing principal component analysis and / or clustering analysis on the various isotope values of the specified type based on the doping sample combination type to obtain an article adulteration result. According to the invention, the accuracy of article adulteration detection is improved.

The invention relates to the field of marine organism ingestion, in particular to a multi-dimensional analysis and evaluation method for molecular feeding habits of coral reef phytophagous fishes, which comprises the following steps of: determining a specific primer aiming at complex characteristics of mixed food residues in a gastric substance sample, and performing multiple PCR (Polymerase Chain Reaction) amplification on a target gene to obtain DNA (Deoxyribose Nucleic Acid) bar code sequence data of a target fish food source; performing multi-stage comparative analysis on the DNA bar code sequence data and sequence data in a DNA reference database; constructing a molecular characteristic sequence map of different species in the gastric contents according to an analysis result; and according to the molecular characteristic sequence map, determining a feeding preference index of the target fish so as to evaluate the regulation and control capability of the population structure of the target fish on the growth of the macroalgae in the coral reef ecosystem. According to the method, the feeding habit composition of the coral reef phytophagous fishes can be comprehensively analyzed, a scientific basis is provided for protection and management of a coral reef ecological system, and the efficiency of feeding habit analysis and the accuracy of ecological evaluation are effectively improved.

Techniques disclosed herein relate to food analysis and glucose level management. In some examples, the techniques involve determining a consumption of a first food item by a user, receiving data indicative of a glucose level of the user, determining an effect of the first food item on the glucose level of the user based on a change of the glucose level of the user, and storing the effect of the first food item on the glucose level of the user to a database that includes data indicating effects of individual food items on the glucose level of the user. In some examples, the techniques also involve providing one or more recommendations for managing the glucose level of the user based on the data in the database and a food item consumed by the user.

The invention discloses a method for simultaneously detecting 37 phenolic substances in a plant based on HPLC (High Performance Liquid Chromatography). HPLC-PDA (Personal Digital Assistant) is adopted for separation and detection; the detection conditions are as follows: the chromatographic column is a PFP chromatographic column; the detection wavelengths are 280 nm, 330 nm and 360 nm; the flow velocity is 0.5 to 0.8 mL / min; the sample size is 8-12 [mu] L; the column temperature is 28-32 DEG C; the mobile phase A is an aqueous solution containing 0.3% by mass of formic acid, and the mobile phase B is methanol; the elution gradient is 0-10 min, and the elution gradient is 5-10% B; in 10-16 min, 10%-25% of B is obtained; after 16 to 25 minutes, 25 to 40 percent of B is obtained; 25 to 50 minutes, 40 to 60 percent of B is adopted; and 60-67% of B is carried out in 50-55 min. The method is suitable for plant sample detection, is especially suitable for sea-buckthorn sample detection, can be applied to multiple fields of food analysis, plant research, component development and the like, and has wide application value.

The invention relates to the technical field of food detection, and discloses an information processing method based on food detection. According to the method, food components are analyzed through a spectrograph and a chromatographic instrument, data and images of food analysis are recorded, missing values, abnormal values and repeated data are removed from the recorded food data through an algorithm formula, the data of different dimensions are converted into a unified standard, and the data are normalized to eliminate the influence of the dimensions. Extracting a color histogram and texture features from the processed food data, selecting features which have the greatest influence on the model by applying a principal component analysis method, selecting a support vector machine algorithm according to data features, performing model training by using a labeled data set, adjusting parameter optimization performance, and evaluating the generalization ability of the model by using a cross validation method. Evaluating the performance and classification effect of the model, detecting food through the trained model, summarizing detection results, generating a detection analysis report, and outputting the detection analysis report to a display end.

The invention provides a flavor analysis method, device and equipment, a storage medium and a program product, and relates to the technical field of food analysis, the flavor analysis method comprises the following steps: in response to a received flavor improvement instruction for a to-be-analyzed object, obtaining flavor collection data of the to-be-analyzed object and a to-be-improved flavor, the flavor acquisition data comprises attribute data, metabolome data and sensory evaluation data; according to the flavor acquisition data, determining a causal relationship among a basic node corresponding to the attribute data, a metabolome node corresponding to the metabolome data and a flavor node corresponding to the sensory evaluation data, and node values of non-observation influence nodes corresponding to the metabolome node and the flavor node respectively; and based on the to-be-improved flavor, the causal relationship and the node value, determining a key reason node influencing the to-be-improved flavor. According to the method, the key reason node influencing the to-be-improved flavor can be more accurately determined, so that the flavor of the to-be-analyzed object can be improved according to the key reason node.

The application discloses a kind of based on GC-IMS pure milk flavor sensory digitalization fast evaluation method, belong to food analysis and evaluation technical field.The pure milk sample to be measured is detected by headspace sampling using GC-IMS, and a fingerprint spectrum is obtained.The fingerprint spectrum data or characteristic volatile component data is input into the OPLS-DA model, and the preference degree of pure milk is evaluated according to the clustering result.The construction method of OPLS-DA model is as follows: different pure milk samples are selected, and CATA sensory evaluation method is used for sensory evaluation of pure milk samples.Different pure milk samples are detected by headspace sampling using GC-IMS, and a fingerprint spectrum is obtained.Partial least squares-discriminant analysis method is used for regression modeling using fingerprint spectrum data or characteristic volatile component data to obtain OPLS-DA model.The application uses GC-IMS to digitally and quickly evaluate the flavor of pure milk, which has high sensitivity, does not require sample enrichment and concentration, saves detection time, and avoids tedious pretreatment process.

The invention is applicable to the technical field of food analysis, and provides a method for identifying the content of camellia oil in plant blend oil based on deep learning, which comprises the following steps: collecting or preparing standard samples of pure edible plant oil and mixed oil with different concentration ratios for constructing an identification model; performing Raman spectrum detection to obtain original Raman spectrum data of the standard sample; preprocessing the original Raman spectrum data to obtain expanded Raman spectrum data after preprocessing; carrying out spectrum dimension reduction on the expanded Raman spectrum data so as to visualize the similarity and the difference of the pure oil sample; identifying related spectral variables of the camellia oil by adopting a spectral variable selection method, then constructing an extreme learning machine model by using the selected variables, and identifying the content of the camellia oil in the to-be-detected sample; and finally, introducing a to-be-detected sample into the three deep learning models, sequentially judging, and identifying the content of the camellia oil in the to-be-detected mixed oil sample.

The invention relates to the field of food analysis, in particular to a method and device for detecting a solvent in edible vegetable oil, terminal equipment and a medium. The invention provides a method for detecting a solvent in edible vegetable oil. The method comprises the following steps: determining an edible vegetable oil sample by using a low-field nuclear magnetic resonance analyzer to obtain a determination result; processing the measurement result to obtain parameter data; based on the parameter data, constructing a quantitative detection model of the solvent in the edible vegetable oil; and quantitatively detecting the residual solvent in the edible vegetable oil to be detected by using the quantitative detection model. Modeling is carried out based on specific parameter data, the residual content of the solvent in the edible vegetable oil can be accurately detected according to the quantitative detection model, the whole detection process is easy to operate and low in cost, and the method is suitable for rapid real-time detection in factories and has wide application prospects in the field of detection of the solvent residues of the edible vegetable oil.

The invention discloses a GC-IMS-based pure milk flavor sensory digitalization rapid evaluation method, and belongs to the technical field of food analysis and evaluation. The method comprises the following steps: detecting a pure milk sample to be detected by GC-IMS through headspace sampling to obtain a fingerprint spectrum, substituting fingerprint spectrum data or characteristic volatile component data into an OPLS-DA model, and evaluating the preference degree of the pure milk according to a clustering result; the construction method of the OPLS-DA model comprises the following steps: selecting different pure milk samples, and carrying out sensory evaluation on the pure milk samples by adopting a CATA sensory evaluation method; the method comprises the following steps: detecting different pure milk samples through headspace sampling by using GC-IMS to obtain a fingerprint spectrum, and performing regression modeling by using a partial least squares-discriminant analysis method by using fingerprint spectrum data or characteristic volatile component data to construct and obtain an OPLS-DA (Optical Partial Least Squares-Discriminant Analysis) model. According to the invention, GC-IMS is adopted to carry out digital rapid evaluation on the pure milk flavor sense organ, the sensitivity is extremely high, a sample does not need to be enriched and concentrated, the detection time is saved, and a tedious pretreatment process is avoided.

The application is suitable for the field of analog enzyme technology, and provides a light-controlled zein-based dual-enzyme-activity analog enzyme and a preparation method thereof.The preparation method comprises the following steps: under water bath conditions, dissolving zein in an alkaline aqueous solution and incubating; adding a hydroxylamine solution to the solution obtained in step S1 and continuing to react; and after the reaction is completed, obtaining the light-controlled zein-based dual-enzyme-activity analog enzyme.The application uses zein as a raw material, is modified by hydroxylamine, does not need any metal component to participate, has light-controlled switchable dual-enzyme activity, exhibits oxidase-like activity under visible light irradiation, presents peroxidase-like activity in dark conditions, and can realize reversible switching of the two enzyme activities by regulating light, effectively overcomes the problems that traditional artificial analog enzymes depend on metal ions, multiple enzyme activities coexist, interfere with each other and are difficult to accurately control, can be used for colorimetric detection of total antioxidant capacity, can be used for colorimetric detection of glucose in cascade reaction with glucose oxidase, has the advantages of simple operation, rapid response, high sensitivity, good selectivity, low cost and the like, and has a good application prospect in the fields of food analysis, clinical diagnosis and the like.

The invention belongs to the field of food analysis, and particularly discloses a fluorescent paper chip for detecting staphylococcus aureus as well as a preparation method and application of the fluorescent paper chip. The preparation method comprises the following steps: firstly, pre-assembling a template bacterial solution, a functional monomer and a fluorescent monomer, then adding a cross-linking agent to carry out polymerization reaction, and after elution, synthesizing the fluorescent molecularly imprinted nanoparticles taking staphylococcus aureus as the template, and immobilizing the fluorescent molecular imprinting nanoparticles on the surface of the paper chip by a covalent immobilization method to obtain the fluorescent paper chip. When bacterial strains are detected, staphylococcus aureus is sensitively and rapidly recognized according to the quenching rate of fluorescence, the method has the advantages of being easy to operate, good in selectivity, low in cost and the like, food can be rapidly and timely detected, and a new thought and a novel strategy are provided for detecting pathogenic bacteria in the food.

1. Name of the product in this design: Graphical User Interface for Food Analysis in Electronic Devices. 2. Intended use of this design: for use in an electronic device. 3. The key design feature of this product is its graphical user interface. 4. The image or photograph that best illustrates the design's key features: the front view. 5. Electronic devices are designed in a conventional way, so other views are omitted. 6. Purpose of the graphical user interface: Used for AI food expert analysis; the main view adds a food identification result page, clicking "AI" displays the interface change state (Figure 1) during food expert analysis, and after the analysis is completed, the interface change state (Figure 2) displays the results of the food expert analysis, clicking "More Nutrients" displays the interface change state (Figure 3).

The invention belongs to the technical field of food analysis, and particularly relates to a method for extracting raffinose from cottonseed processing waste liquid. According to the method, the raffinose in the cottonseed processing waste liquid is directly extracted by using an aqueous solution, sephadex LH-20 is used as a column chromatography filler, the molecular sieve effect is utilized, water or ethanol water is used as an eluent, and the raffinose and substances with different molecular weights such as cottonseed protein, salt and cane sugar are eluted in sequence, so that the raffinose is purified. The method is simple in process flow, does not need to add harmful solvents such as acid, alkali and methanol into the system, and has the advantages of simplicity, rapidness and easiness in industrial production.

The invention discloses a method for rapidly detecting monosaccharide composition in polysaccharide, and relates to the technical field of food analysis. The method comprises the following steps: firstly hydrolyzing polysaccharide by adopting TFA, then derivatizing PMP, and finally analyzing the monosaccharide composition of the derivatized polysaccharide hydrolysate by adopting UHPLC QQQ MS (Ultra High Performance Liquid Chromatography QQQ Mass Spectrometry). According to the method provided by the invention, the detection analysis of 18 monosaccharides can be quickly completed within 7 minutes, and the detection limit is also lower than that of a mainstream monosaccharide detection method HPAEC-PAD.

The invention discloses a method for identifying high-quality pepper based on differential volatile compounds and application of the method, and relates to the technical field of food analysis and detection. The method comprises the following steps: carrying out qualitative analysis and quantitative analysis on the volatile compounds in the high-quality pepper based on the combination of ultrafast gas phase electronic nose analysis and headspace gas chromatography-ion mobility spectrometry analysis; analyzing the difference of the volatile compounds in the high-quality pepper by combining principal component analysis and partial least square discriminant analysis; the ultra-fast gas phase electronic nose analysis comprises first sample pretreatment and gas phase electronic nose analysis, and the headspace gas chromatography-ion mobility spectrometry analysis comprises second sample pretreatment, gas chromatography separation and ion mobility spectrometry analysis; the producing area of high-quality pepper is selected from Guizhou province. The method can quickly, comprehensively and systematically reveal flavor characteristics of different varieties of high-quality peppers, and provides a scientific theoretical basis for variety selection, dominant breeding, processing raw material optimization and flavor quality comprehensive evaluation of the high-quality peppers.

The invention discloses a processing method and system for analyzing and displaying food performance evaluation data. The method comprises the following steps: obtaining to-be-processed food evaluation information; preprocessing the to-be-processed food evaluation information to obtain target evaluation feature information; the target evaluation feature information comprises first evaluation feature information and second evaluation feature information; and performing analysis conversion processing on the target evaluation feature information to obtain target food analysis display information.

The invention relates to preparation of an aluminosilicate unfired ceramic membrane-coated MOF (Metal Organic Framework) material for food safety analysis. The preparation method comprises the following steps: by taking a powder silicon-aluminum source after ball milling as an aluminosilicate source and 0.8-3 mol / L sodium hydroxide as an exciting agent, stirring for 5-60 minutes, pouring into a mold, curing at 40-100 DEG C, demolding, and drying for 4-48 hours to obtain an unfired ceramic membrane matrix; the preparation method comprises the following steps: adding PVP (Polyvinyl Pyrrolidone) into an MOF material prepared by a hydrothermal method at the hydrothermal temperature of 120-150 DEG C and the drying temperature of 60-90 DEG C to prepare slurry, uniformly coating a baking-free ceramic membrane with the slurry with the thickness of 1-3mm, and drying to obtain the aluminosilicate baking-free ceramic coated MOF material for food harmful impurity sample analysis.

The present invention relates to the technical field of food analysis, and provides a food nutrition assessment method based on adaptive fusion and feature enhancement, including: extracting multi-scale features from a target image of a target object to be assessed, obtaining multi-scale features of the target image, wherein the target image includes an RGB image and a depth image; determining detail enhancement features corresponding to the target scale features according to the target scale features and the scale features with a scale greater than the target scale features in the multi-scale features, wherein the target scale features are features of any scale in the multi-scale features; fusing the detail enhancement features of different target images to obtain multi-scale fusion features; determining semantic enhancement features corresponding to the fusion features of the target scale according to the fusion features of the target scale and the fusion features of a smaller scale; and determining the numerical value of the mapped nutrient according to the semantic enhancement features. This is to solve the problem of low accuracy of the method for food nutrition assessment based on images in the related art.

The invention belongs to the technical field of food analysis and detection, and particularly relates to a method for simultaneously detecting carbonyl compounds in fermented soya beans. In order to solve the technical problem that the carbonyl compounds in the fermented soya beans cannot be accurately, precisely, simply and conveniently detected at the same time in the existing detection technology, the pretreatment conditions of the fermented soya beans are optimized, so that the extraction efficiency of the carbonyl compounds in the fermented soya bean extracting solution is higher; reacting a derivatization reagent 3-nitrophenylhydrazine hydrochloride with volatile and non-volatile acids and volatile and non-volatile aldehyde compounds in the fermented soya bean extracting solution under the action of catalysts N-(3-dimethylaminopropyl)-N '-ethylcarbodiimide hydrochloride and pyridine to obtain a derivatization reaction product; and finally, determining the 19 carbonyl compounds in the fermented soya beans by using an ultra-high performance liquid chromatography-tandem mass spectrometry method. The detection method disclosed by the invention is high in sensitivity and low in detection limit, can efficiently and accurately detect the carbonyl compounds in the fermented soya beans at the same time, and has important significance on flavor quality evaluation of the fermented soya beans.

The invention relates to the technical field of food analytical chemistry, and particularly discloses a method for analyzing volatile components in rice, which comprises the following steps: S1, aging a fiber head: aging a solid phase microextraction fiber head at a gas chromatography sample inlet at 270 DEG C for 30 minutes; s2, sample preparation: weighing 3g of a rice sample, putting the rice sample into a headspace sample injection bottle, adding 6mL of water, and sealing the headspace sample injection bottle; s3, headspace balancing: stirring and balancing the sealed sample injection bottle at the temperature of 80 DEG C at the speed of 250 rpm; s4, headspace extraction: placing the aged fiber head at a position 3 cm above the headspace of the sample, and carrying out adsorption extraction for 30 minutes; s5, thermal desorption: inserting the extracted fiber head into a GC-MS (Gas Chromatography-Mass Spectrometer) sample inlet, and desorbing for 6 minutes at 230 DEG C; and S6, performing chromatographic analysis on the desorbed sample. The method is simple, convenient and rapid to operate, capable of completing large-scale detection in a short time and wide in application range.

The invention discloses a method for the detection of sialate glycosyl casein glycomacropeptide by boronate affinity column enrichment-liquid chromatography-tandem mass spectrometry using phenylboric acid modified mesoporous silica as packing material, which belongs to the field of food analysis and detection. The method includes the following steps: (1) sample preparation; (2) enrichment and purification of boronate affinity column; (3) liquid chromatography-tandem mass spectrometry detection. The invention makes use of the affinity property of phenylboric acid to the special sugar group sialic acid on the serine and threonine residues in casein glycogiant peptide, regulates the adsorption and elution of casein glycogiant peptide with sialic acid group by changing pH. Combined with the high sensitivity and accuracy of liquid chromatography tandem mass spectrometry, it can be used for qualitative and quantitative analysis of casein glycomacropeptide with sialate glycol-group in phenylketonuria special medical formulations with complex matrix.

This invention discloses a 3,6-bis(4-boronic acid phenyl)carbazole compound in the field of organic chemistry, its preparation method, and its application in glucose detection. The invention efficiently synthesizes the target product through a five-step reaction involving Suzuki coupling, N-alkylation, boron esterification, and deprotection. This compound exhibits high fluorescence quantum yield, good water solubility and stability, and simple synthesis. In a DMSO / H2O mixed solvent, it can specifically bind with glucose to form a boron ester. The fluorescence intensity decreases with increasing glucose concentration through an intramolecular charge transfer effect, achieving highly sensitive, highly selective, non-enzymatic glucose detection in aqueous phase. This solves the problems of poor stability, high cost, and complex operation associated with traditional enzymatic methods, and is suitable for clinical blood glucose monitoring, food analysis, and environmental monitoring.

The present invention belongs to the technical field of food analysis, and specifically relates to a smooth taste evaluation model of milk tea based on oral tribology, a construction method and an application. The present invention conducts sensory evaluation on milk tea samples, and at the same time uses a rheometer to detect the friction coefficient of the milk tea samples, and correlates and analyzes the corresponding relationship between the smoothness score of the milk tea samples and the change law of the friction coefficient of the milk tea samples with the shear rate, so as to construct a smooth taste evaluation model of milk tea based on oral tribology. When using this model to evaluate milk tea, it can quickly, conveniently, accurately, stably and reliably predict the smoothness of milk tea products, meeting the actual needs of the milk tea beverage market.

The invention belongs to the technical field of food analysis and detection, and particularly discloses a method for rapidly detecting tartaric acid in wine based on a molecularly imprinted polymer (MIP) modified carbon fiber electrode. According to the method, a tartaric acid molecularly imprinted polymer layer is constructed on the surface of a carbon fiber electrode by adopting an electrochemical polymerization technology, and high-sensitivity and high-selectivity detection of tartaric acid is realized in a potential range of-0.5 to + 0.6 V (vs.Ag / AgCl) in combination with a differential pulse voltammetry (DPV). The modified electrode has excellent conductivity and specific recognition capability, the detection limit is as low as 0.05 [mu] mol / L, and the linear range is 1-800 [mu] mol / L. The method is simple and convenient to operate, the single detection only needs 20 seconds, the relative standard deviation is less than 3.5%, the recovery rate reaches 95-102%, the method can be directly applied to stock solution detection of complex wine matrixes (such as dry red wine, dry white wine and sweet wine), complex pretreatment is not needed, and an efficient and reliable analysis means is provided for wine brewing process monitoring and quality evaluation.

The present invention relates to a chewing system used in food analysis for performing a chewing test on a food sample in order to determine a textural property of a solid food throughout the oral process, wherein said system is integrable into all texture analyzers operating on a load-cell basis.

The application belongs to the technical field of food analysis, and discloses a comprehensive quality evaluation method of hot and spicy seasoning. The application firstly organically fuses the absolute content of key flavor substances determined by a GC-MS internal standard method, the total content of capsaicin substances determined by HPLC, and the total content of amides determined by ultraviolet spectrophotometry, constructs a comprehensive quality index (CQI), overcomes the defects of one-sidedness of single index evaluation, can scientifically distinguish the comprehensive quality differences of non-balanced samples such as "high spiciness and low fragrance" and "high numbness and low spiciness", and the evaluation result has high correlation with the comprehensive satisfaction of experts' senses.

The invention relates to the technical field of food analysis, and provides a method for analyzing the sensitization effect of natural carbohydrate chains on food allergens, which comprises the following steps: extracting and purifying tropomyosin freeze-dried powder in food muscle tissues, identifying the types of carbohydrate chains in the tropomyosin freeze-dried powder, and analyzing the types of glucosidic bonds; removing an N-carbohydrate chain and an O-carbohydrate chain in the tropomyosin freeze-dried powder by using one or more of a PNGase F enzyme removal method, a beta-elimination method and a trifluoromethanesulfonic acid method, so as to obtain a deglycoprotein; a phenol-sulfuric acid method, SDS-PAGE (Sodium Dodecyl Sulfate Polyacrylamide Gel Electrophoresis) and PAS (Polyacrylamide Sulfate) dyeing are used for evaluating the anti An in vitro test and an in vivo test are used to evaluate the effect of the desugaring treatment on the allergenicity of tropomyosin. By analyzing the regulation influence of the natural carbohydrate chain on the allergenicity of the penaeus chinensis tropomyosin, a foundation is laid for deep research on the allergenicity of the penaeus chinensis tropomyosin, and an innovative perspective of analyzing the allergenicity characteristics of the penaeus chinensis tropomyosin is provided.