Based on counts detected by a photon counting detector, a characteristic of X-ray attenuation amounts μt is acquired for each X-ray energy bin. This characteristic is defined by a plurality of mutually different known thicknesses t and linear attenuation coefficients in the X-ray transmission direction. This substance is composed of a material which is included in an object and which is the same in type as the object or which can be regarded as being similar to the object in terms of the effective atomic number. Correcting data for replacing the characteristic of the X-ray attenuation amounts μt by a linear target characteristic are calculated. The linear target characteristic is set to pass through the origin of a two-dimensional coordinate having a lateral axis assigned to thicknesses t and a longitudinal axis assigned to the X-ray attenuation amounts μt. The correcting data are calculated for each X-ray energy bin.

Based on counts detected by a photon counting detector, a characteristic of X-ray attenuation amounts μt is acquired for each X-ray energy bin. This characteristic is defined by a plurality of mutually different known thicknesses t and linear attenuation coefficients in the X-ray transmission direction. This substance is composed of a material which is included in an object and which is the same in type as the object or which can be regarded as being similar to the object in terms of the effective atomic number. Correcting data for replacing the characteristic of the X-ray attenuation amounts μt by a linear target characteristic are calculated. The linear target characteristic is set to pass through the origin of a two-dimensional coordinate having a lateral axis assigned to thicknesses t and a longitudinal axis assigned to the X-ray attenuation amounts μt. The correcting data are calculated for each X-ray energy bin.

A device for spectroscopically analysing a grain sample may include a first infrared analysis module, a second fluorescence analysis module, a third specific weight analysis module and a processing module. Each of the first and second modules may include a measurement chamber, an excitation submodule to emit at least one electromagnetic radiation towards at least a portion of the sample, a measurement submodule, and a draining system. The third analysis module may include a container, and a measurement submodule to measure a specific weight of the sample. A processing module may be connected to each of the modules and may include a memory to receive data transmitted by a communication network, the data including electromagnetic spectra acquired and specific weights measured, and a processor to couple the data received in the memory and to determine an indicator of quality of the sample from the coupled data.

A device for spectroscopically analysing a grain sample may include a first infrared analysis module, a second fluorescence analysis module, a third specific weight analysis module and a processing module. Each of the first and second modules may include a measurement chamber, an excitation submodule to emit at least one electromagnetic radiation towards at least a portion of the sample, a measurement submodule, and a draining system. The third analysis module may include a container, and a measurement submodule to measure a specific weight of the sample. A processing module may be connected to each of the modules and may include a memory to receive data transmitted by a communication network, the data including electromagnetic spectra acquired and specific weights measured, and a processor to couple the data received in the memory and to determine an indicator of quality of the sample from the coupled data.

Embodiments of systems and approaches for managing post-harvest crop quality and pests are described. Such a system may include a plurality of edge devices each comprising sensor components and collectively forming a mesh network, for measuring the local physical environment within stored crops and, for example, transmitting the measurements to a service from within the crop storage area. In certain embodiments, such a system may be used to manage post-harvest crops and storage areas—for example, approaches are described for determining fumigation treatment duration, determining phosphine dosage, determining heat treatment duration, and determining safe storage time for crops.

Disclosed herein is a method of assessing rheology characteristics of vital wheat gluten to determine how to improve the quality of VWG product and the choice of VWG for a particular product.

Disclosed herein is a method of assessing rheology characteristics of vital wheat gluten to determine how to improve the quality of VWG product and the choice of VWG for a particular product.

A photo acoustic non-destructive measurement apparatus and method for quantitatively measuring texture of a food snack is disclosed. 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 food snack placed on a surface 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. Texture of food snacks are quantitatively measured with the quantitative acoustic model.

A photo acoustic non-destructive measurement apparatus and method for quantitatively measuring texture of a food snack is disclosed. 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 food snack placed on a surface 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. Texture of food snacks are quantitatively measured with the quantitative acoustic model.

A food processing system is disclosed. The food processing system includes a food scaling portion, a food bagging portion and a chute portion connecting the food scaling portion to the food bagging portion. The food processing system also includes a foreign object sensor arranged about the chute portion. The foreign object sensor and the chute portion cooperatively form a foreign object sensing zone within a passage formed by the chute portion that extends along a portion of a length of the chute portion. The food processing system also includes at least one sensor testing conduit extending through one or both of the food scaling portion and the chute portion. An exit opening of the at least one sensor testing conduit is arranged in an opposing relationship with respect to the foreign object sensing zone. A foreign object sensor apparatus for detecting non-foodstuff material is also disclosed. A method is also disclosed.