Patent classifications
G01N33/10
Quantitative liquid texture measurement apparatus and methods
A photo acoustic non-destructive measurement apparatus and method for quantitatively measuring texture of a liquid. The apparatus includes a laser generating tool, an acoustic capturing device, and a data processing unit. The laser generating tool directs a laser towards a surface of a liquid contained in a container and creates pressure waves that propagate through the air and produce an acoustic signal. The acoustic capturing device records and forwards the signal to a data processing unit. The data processing unit further comprises a digital signal processing module that processes the received acoustic signal. A statistical processing module further filters the acoustic signal from the data processing unit and generates a quantitative acoustic model for texture attributes such as hardness and fracturability. The quantitative model is correlated with a qualitative texture measurement from a descriptive expert panel. Textures of liquids are quantitatively measured with the quantitative acoustic model.
Quantitative texture measurement apparatus and method
A non-destructive measurement apparatus and method for quantitatively measuring texture of a food snack is disclosed. The apparatus includes a laser generating tool, an ultrasound excitation device, an acoustic capturing device, an ultrasound capturing device and a data processing unit. The laser generating tool and the ultrasound excitation tool direct energy towards a food snack placed on a surface and produce an acoustic signal and an ultrasound signal. The data processing unit further comprises a digital signal processing module that processes the received acoustic signal and ultrasound signal. A statistical processing module further filters the acoustic signal from the data processing unit and generates a quantitative acoustic model for texture attributes such as hardness and fracturability. The quantitative model is correlated with a qualitative texture measurement from a descriptive expert panel. Texture of food snacks are quantitatively measured with the quantitative acoustic model.
Quantitative texture measurement apparatus and method
A non-destructive measurement apparatus and method for quantitatively measuring texture of a food snack is disclosed. The apparatus includes a laser generating tool, an ultrasound excitation device, an acoustic capturing device, an ultrasound capturing device and a data processing unit. The laser generating tool and the ultrasound excitation tool direct energy towards a food snack placed on a surface and produce an acoustic signal and an ultrasound signal. The data processing unit further comprises a digital signal processing module that processes the received acoustic signal and ultrasound signal. A statistical processing module further filters the acoustic signal from the data processing unit and generates a quantitative acoustic model for texture attributes such as hardness and fracturability. The quantitative model is correlated with a qualitative texture measurement from a descriptive expert panel. Texture of food snacks are quantitatively measured with the quantitative acoustic model.
METHOD FOR OPERATING A DOUGH-KNEADING DEVICE AND KNEADING DEVICE
When operating a dough-kneading device, a momentary torque acting on kneading tool of the dough-kneading device, a momentary speed and a momentary rotational position of the kneading tool are measured. From the measurement values, a dough elasticity parameter and a dough viscosity parameter are determined as actual dough parameters. Dough-status data is then output based on the measurement data and the determined actual dough parameters. From the measurement values, dough parameters can therefore directly be concluded, which represent a measure on the one hand for the viscosity and, on the other hand, for the elasticity of the dough. An objective monitoring of the kneaded dough is therefore possible. In addition or as an alternative, an expected kneading period until reaching a maximum torque is determined.
NON-DESTRUCTIVE ASSAY FOR SOYBEAN SEEDS USING NEAR INFRARED ANALYSIS
Disclosed are methods and systems for spectral imaging of soybean samples to accurately and non-destructively measure the amount of sucrosyl-oligosaccharide in the soybean samples. Populations containing modified and unmodified soybean seeds and having varying amounts of sucrosyl-oligosaccharides, oil or protein can be sorted and separated and further used in soybean processing or breeding.
Measuring device and method for a contactless analysis of a food product in a production line
The invention relates to a device and a method for a contactless analysis of a product, in particular for the contactless analysis of a dough product. The device comprises a distance sensor configured for measuring a distance between the device and the product, and a nozzle configured for directing a jet of pressurized fluid to a position on a surface of said product. The distance sensor is arranged for measuring the distance between the device and the position of the surface where the jet of pressurized fluid is directed to. Preferably, the distance sensor is at least partially arranged in the nozzle, preferably substantially in the center of said nozzle.
Measuring device and method for a contactless analysis of a food product in a production line
The invention relates to a device and a method for a contactless analysis of a product, in particular for the contactless analysis of a dough product. The device comprises a distance sensor configured for measuring a distance between the device and the product, and a nozzle configured for directing a jet of pressurized fluid to a position on a surface of said product. The distance sensor is arranged for measuring the distance between the device and the position of the surface where the jet of pressurized fluid is directed to. Preferably, the distance sensor is at least partially arranged in the nozzle, preferably substantially in the center of said nozzle.
NON-DESTRUCTIVE ASSAY FOR SOYBEAN SEEDS USING NEAR INFRARED ANALYSIS
Disclosed are methods and systems for spectral imaging of soybean samples to accurately and non-destructively measure the amount of sucrosyl-oligosaccharide in the soybean samples. Populations containing modified and unmodified soybean seeds and having varying amounts of sucrosyl-oligosaccharides, oil or protein can be sorted and separated and further used in soybean processing or breeding.
X-RAY SCREENING SYSTEM AND METHOD
An x-ray screening system includes a plurality of x-ray screening devices each for scanning at least one object of interest. Each screening device emits x-rays which pass through the object of interest and which are detected by a group of detectors including at least one detector to provide measured x-ray energy signals. At least one central processor is in data communication with each screening device for receiving the measured x-ray energy signals from each screening device automatically and in real-time. The at least one processor automatically analyzes the measured x-ray energy signals in real-time to determine at least one property of the object of interest and determining whether the at least one property indicates that at least a portion of the object of interest is composed of a material of interest. The material of interest may be a potentially dangerous material.
GRAIN MOISTURE METER NETWORKED TO SMARTPHONES
An assembly (decoupled grain sampler and moisture content reader) for measuring grain moisture and sharing the grain moisture information with a database, other framers, and merchants, including a grain receiving chamber, at least one plate capacitor operationally connected to the grain receiving chamber, a capacitance to digital converter (or similar device) operationally connected to the at least one plate capacitor, a microprocessor operationally connected to the oscillator, a user interface operationally connected to the microprocessor, a smartphone app in operational communication with the microprocessor, and a transceiver operationally connected to the microprocessor and the smartphone app.