Tenova systems : Thermal Analysis of Foods

Tenova systems : Thermal Analysis of Foods: Many food products can be analyzed by thermal analysis as to certain effects and properties, among which the more important are marked wit...

Tenova systems : Cold Chain RFID Market Is Growing at a 29.1% CAGR ...

Tenova systems : Cold Chain RFID Market Is Growing at a 29.1% CAGR ...: The global cold chain monitoring with RFID market is expected to grow at a CAGR of 29.1% forecast to 2022. Among the various pro...

Thermal Analysis of Foods

Many food products can be analyzed by thermal analysis as to certain effects and properties, among which the more important are marked with a spot.

For this experiment, seeds available commercially from a health food store were used.

Conditions

Measuring cell: DSC20

Pan: Aluminum standard, 40 µl, hermetically sealed

Reference: About 40 µl in a sealed pan

Sample preparation: The seeds are milled, aqueous extraction performed at pH 4.5, centrifuged, and the supernatant discarded. The residue is subjected to re-extraction at pH 8.5, the supernatant is evaporated under vacuum until the dry substance content is obtained.

DSC measurement: Heating performed from 30 °C to 110 °C at 5 K/min

Interpretation

Four vegetable proteins of different types were studied in the untreated state. Each of the four curves shows an endothermic peak between 72 °C and 100 °C, which is typical for protein denaturation. A difference is seen in the heat stability and enthalpy of denaturation of the proteins.

The sample weight was comparable for all the samples, as well as the protein concentrations. Thus the peak integrals were in direct correspondence to the specific reaction enthalpies.

The highest temperature sensitivity was seen with spelt, which also has the greatest enthalpy of denaturation. Wheat proteins already undergo denaturation to a great extent at 86 °C, soybean protein remains intact in the main, at this point, and only at 88 °C is it denatured to any significant degree.

Grain and oilseed proteins have enthalpies of denaturation within a range of 3-10 J/g protein. The enthalpy changes with respect to the protein phase. Thus in the native condition of a grain or oilseed the enthalpy of denaturation is lower than when it has been dissolved in aqueous solution.

DSC measurement of denatured protein fraction in processed samples of protein is of better quality if the enthalpy of denaturation of native protein is higher.

The heating rate can be freely selected with DSC which could improve the measurement as well as the detection of the reactions. With a higher rate of heating, the detected signal becomes larger with a larger measured peak. The peak area calculated remains the same under the same conditions of reaction. However, if the rate of heating is high the reaction occurs at elevated temperatures. Cold Chain MOnitoring Is very important in this case. 

DSC can identify vegetable proteins but this is not likely to be widely used in practice, and is also made more difficult by the fact that the reaction enthalpy differs with the protein type and growth conditions. Thus a reference in the form of a native protein must be used when the degree of denaturation is being assessed.

The DSC curve provides a fingerprint of each sample of protein which is characteristic of the condition of the protein in the fraction.

Evaluation

Conclusion

These measurements illustrate that DSC can be used to analyze any product that contains protein. This is more applicable to animal proteins because of their higher concentration of protein (in animal muscle), the greater sensitivity of measurement and their natural state of occurrence in a watery environment.

This information has been sourced, reviewed and adapted from materials provided by Mettler Toledo - Thermal Analysis.

For more information on this source, please visit Mettler Toledo - Thermal Analysis.

Cold Chain RFID Market Is Growing at a 29.1% CAGR During 2018 – 2022; Cold Chain RFID Market Opportunities and Demand by 2022

The global cold chain monitoring with RFID market is expected to grow at a CAGR of 29.1% forecast to 2022. Among the various products, the tags segment accounted for largest share in the global cold chain RFID market. The software and services product segment is expected to witness a considerable growth during the forecast period. The growing demand for real time temperature monitoring in cold chain logistic is expected to boost the growth of the global cold chain with  RFID market during the forecast period.

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The RFID technology in cold chain monitoring is used for tracing and tracking contents, location expiration, and manufacture dates. The data gathered by RFID can be transmitted to the authorities. The food and beverages segment accounted for the largest market share in the global cold chain RFID market in 2015. The pharmaceutical and biomedical segment is expected to witness growth at the fastest rate during the forecast period, owing to the increasing demand of RFID in pharmaceuticals cold chain supply from developing countries, such as India and China. The growing global fisheries import and export is laying ample opportunities for the growth of the cold chain RFID market.

The stringent government mandates for food safety has led to the requirement of specific humidity, temperature, and light requirements while handling food, beverages, and pharmaceuticals products. The producers, transporters, distributors, and warehouse operators are now forced to keep the entire supply chain details for these products. The stringent regulations in developed countries has also forced the major pharmaceuticals, food and beverages exporter countries in Asia-Pacific to follow the mandates, as it is applicable for the entire supply chain. This is driving the growth of the cold chain RFID market in Asia-Pacific.

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Some of the major companies operating in the global cold chain RFID market include Alien Technology, Checkpoint Systems Inc., Impinj Inc., Nedap N.V., RFID4U (eSmart Source, Inc.), Invengo Technology BV, GAO RFID Inc., Tenova Systems,  Avery Dennison Corporation, and Sato Holdings Corporation.





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Industrial Internet of Thing (IIoT) Platform in Reality and its Digital Transformation.

These are the Analysis done by Tenova Systems about the IIOT platform and its adoptions 

One of the greatest challenges companies are facing now are the adoption of right technologies in Internet of Things (IoT) platform. Building a right business case is the main challenges faced by companies and eventually to derive the financials and the funding. Mainly many of the companies don’t know exactly what they want from the Internet of things. They know that can improve their organizations asset reliability,  , increased product quality, remote monitoring, optimized production operations. These can be defined as new technology or upgrade of old technologies.

Introducing as a new technology initiative for the old use cases will be much more acceptable and chances of convincing the management for the financial proposals. Currently the industry has been successfully implemented in connecting assets in mining equipment, packaging equipment, test equipment, motor automation, cold chain management, etc.

Any way management believes that this new IIoT technology will enable them to improved asset monitoring and production performance. Even though management is trying to figure out the areas of benefits in the asset monitoring and production performance. On

IIoT Adoption and Challenges

It is now inevitable for the organizations to embrace modern technologies and platforms that enables more flexible and data analytics. In this scenario rich and scalable  IIoT platform is required to bring together application development capabilities, cloud, connectivity and data analytics capabilities. Now days the interest and intentions to invest in IIT platform technologies has increased.

Many companies are planning to invest in IIot Platform to automate their business process. This greatly increase the acceptance of the IIot platform interest. Now a days implementation of IIoT technology is considering as an advantage of early adopter. Now days the main problem companies facing are securing the budget and building a business case.

The gap in the industries for the adoption of IIoT is the cultural and maturity of the organization which operating in the specific industry. For decades industries companies have less focused on improving the productivity, safety, energy efficiency, and reliability and most of the IIOT business case is based on saving the previously mentioned areas. But currently this is done by traditional technologies and methodologies like Six Sigma, Business Intelligence, ERP etc.

Currently companies are left with two choices.

1.       Build a business case with IIOT and secure funding and early adoption of the technologies.

2.       Do nothing and wait and test for the  success of IIOT and implement at a later stage.