Spoil Detection Based Smart Label Market by Type (Fish, Meat, Vegetables, Dairy Products), and Geography (North America, Europe, APAC, Row) - Global Forecast to 2020
The use of spoil detection-based smart labels is an ideal way to detect the spoilage of food materials. These labels respond to variations in food materials in terms of temperature, growth of micro-organisms, moisture, and others. A smart label is an identification slip, which is usually applied on the food material or its packaging, in order to detect the freshness of the same. These labels are of immense use in the food and beverage industry, as by using such labels consumers and vendors can easily gauge the freshness of the food material. To minimize food wastage, various international and regional governing bodies are encouraging the use of these labels in the food and beverage industry.
Spoil detection-based smart labels have applications mainly in food and beverage and healthcare industries. These labels are used in food materials to monitor their degree of freshness. Food can be lost or spoiled during the supply chain, from initial agricultural production to final household consumption. The labels are the ideal products to trace such loss and reduce the wastage of food materials.
Spoil detection-based smart labels are used as color indicator smart labels, time and temperature indicator labels, carbon dioxide indicators, and others. Various new technologies related to spoil detection-based smart labels are being introduced in the marketplace. However, the trend of integrating sensors such as RFID with Spoil Detection Based Smart Labels is expected to be introduced in market in the coming years. This integration would lead to the usage of spoil detection-based smart labels in supply chain management, in order to manage the distribution and supply of food materials.
There are various factors present in the market which are driving or restraining the growth of Spoil Detection Based Smart Labels. Ability of runtime detection of degree of freshness of food material and increased customer preference for hygiene of food material is driving the spoil detection-based smart label industry. However, the lack of uniform standards and form factor of label are hindering the growth of this market. Spoil detection-based smart label market has opportunities in supply chain management of food and pharmaceutical industry. In addition, integration of sensors in these labels can improve the market penetration of Spoil Detection Based Smart Labels in various industry verticals such as, healthcare, automotive and chemical.
The major players in this market include – SATO Holding AG., Thinfilm Electronics ASA, Zebra Technologies, Smartrac N.V., Invengo Information Technologies Co. Ltd., and Muhlbauer Holdings AG & Co. KGAA. This report describes the value chain for the Spoil Detection Based Smart Label market by considering all the major stakeholders in the market and their roles in the analysis. The report also provides a detailed impact analysis of the Drivers, Restrains and Opportunities of the market and company profiles of key industry players.
Based on type
The spoil detection-based smart label market is segmented on the basis of type of material.
Based on geography
This report is global study of hearth market by focusing of Americas. For the comparison geographical segments such as North Americas, Europe, APAC (Excluding Japan), Japan, and Rest of the World are studied.
The report covers the market data and information with regards to the market drivers, trends, and opportunities, key players, and competitive outlook. This report also makes way for market tables to cover the sub-segments. In addition, it profiles ten companies, which include overview, products and services, financials, strategy, SWOT analysis, and recent developments.
Reasons to buy the report
The information published in this report can be used by OEMs, System Integrators, and Supply Chain Vendors to strategies their business plan. The market potential given in this report is backed with quantitative and qualitative data. Hence M&A activities can be planned with the help of this report.
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