**Abstract**

Food waste is a global problem caused in large part by premature food spoilage. Seafood is especially prone to food waste because it spoils easily. Of the annual 4.7 billion pounds of seafood destined for U.S. markets between 2009 and 2013, 40 to 47 percent ended up as waste. This problem is due in large part to a lack of available technologies to enable rapid, accurate, and reliable valorization of food products from boat or farm to table. Fortunately, recent advancements in spectral sensing technologies and spectroscopic analyses show promise for addressing this problem. Not only could these advancements help to solve hunger issues in impoverished regions of the globe, but they could also benefit the average consumer by enabling intelligent pricing of food products based on projected shelf life. Additional technologies that enforce trust and compliance (e.g., blockchain) could further serve to prevent food fraud by maintaining records of spoilage conditions and other quality validation at all points along the food supply chain and provide improved transparency as regards contract performance and attribution of liability. In this chapter we discuss technologies that have enabled the development of hand-held spectroscopic devices for detecting food spoilage. We also discuss some of the analytical methods used to classify and quantify spoilage based on spectral measurements.

**Keywords:** Spoilage, valorization, spectroscopy, hyperspectral imaging, artificial intelligence

## **1. Introduction**

Food waste is a significant problem in both developed and developing economies [1]. The global seafood industry faces unprecedented challenges as demand increases, consumer preferences change, and expectations of quality increase. Consumers are demanding more transparency and a commitment to sustainability while access to at-capacity or overfished fishery resources is strained and food production and retail profit margins are thin. Global food supply chains can be a cause of improper food storage, which leads to by-product waste. Whether through a lack of quality control or a hold in the distribution process, food spoilage can occur even before the product reaches markets. Approximately 35% of fish are lost to waste

globally with between 30% and 35% loss in most regions of the world [2]. Seafood's perishability is largely to blame.

A major goal to improve the overall valorization of food and reduce agro-food waste or diversion to by-products is earlier and rapid detection of spoilage. Like medical evaluations for disease, early detection can lead to quicker response from manufacturers or consumers to increase the shelf life of food products. Microbiologists and food scientists have developed a variety of methods to detect surface microbials and pathogenic microorganisms including culturing and colonycounting methods, polymerase chain reaction (PCR)-based amplification for DNA analysis, immunoassay analysis, chromatography, and mass spectrometry [3, 4]. Unfortunately, these techniques have limited versatility and restrictive methodologies that are not practical with on-site and on-demand food quality and safety control [3–5]. However, spectroscopic technologies have shown great promise for enabling early detection of spoilage to help minimize food waste.

Another problem affecting consumers and contributing to global food waste is the lack of transparent pricing for food products as a function of shelf life. Alongside government and industry regulation, intelligent dynamic pricing based on projected shelf life at retail and other upstream points along the supply chain can encourage efforts to reduce waste. This requires new tools for tracking food products at all points along the supply chain. These tools must be easy to incorporate, objective, verifiable, and provide data on quality, provenance, and freshness.

A pioneer in the development of food quality and traceability technologies, SafetySpect is developing a new handheld quality, adulteration, and traceability (QAT) scanner to address many of these issues. Utilizing hyperspectral multi-mode technology to provide species identification and direct measurements of freshness/ spoilage in a handheld device can address challenges of waste and mislabeling. In seafood and meat processing, distribution, and storage supply chains in developed and developing economies, this is likely to meaningfully decrease food waste and increase sustainable access to safe, healthy, and nutritious foods. It will also decrease costs and increase profit within supply chains by providing better attribution of liability and verification of supply contract performance. This transparency will provide incentives to upstream supply chain participants to improve operational methods that can result in the degradation of product or unnecessary, accelerated spoilage.

#### **1.1 Current trends for examining fish quality**

The main approach to improving valorization and by-product management is early detection of spoilage. A common method for detecting spoilage in fish is the Torry Freshness Score [6]. This systematic scoring method was developed in the UK to provide an objective assessment of fish quality. It uses the human senses to examine specific parts of the fish. For example, an evaluator will observe gill odors, skin tension, opaqueness of the eyes, and overall smell of the fish and provide a freshness rating between 0 (lowest) to 10 (highest). However, this manual approach to evaluating fish samples is time consuming and may be more susceptible to evaluator bias or human error. This motivates the development of technologies that enable rapid evaluation of fish quality with minimal human interpretation.

Spectroscopic approaches offer a robust, non-destructive means of detecting and evaluating the extent of food quality issues. In recent decades, advancements in micro-electro-mechanical systems (MEMS) and micro-electro-opto-mechanical systems (MEOMS) have enabled the development of miniaturized spectroscopic devices that can be used for analysis at all points along the food supply chain, from farm fields to distribution centers to retail markets. Hyperspectral imaging (HSI)

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*Advanced Optical Technologies in Food Quality and Waste Management*

**2. Spectroscopy and hyperspectral imaging technologies**

combines spectroscopy and imaging to enable evaluation of an object's spectroscopic composition at a high spatial resolution, thus providing a more comprehensive evaluation tool for any given sample [7–9]. As the scale and complexity of food supply networks continues to grow, there is an ever increasing need for low-cost, portable, analytical devices to combat the corresponding growth in vulnerability of food products to adulteration, contamination, and fraud [10]. In the next section, we discuss a variety of technologies that have enabled the recent development of portable and handheld spectroscopic devices that can and have been used for

One of the most common approaches used for quality control of food products involves the analysis of vibrational spectra via infrared spectroscopy. The spectral peaks and valleys formed by the fundamental vibrational modes (and their harmonics) of key structures within organic molecules can be used to detect the presence of abnormalities or measure the abundances of specific chemical components. The near infrared (NIR) and mid-infrared (MIR) spectral regions are of high

The rapid proliferation of visible digital camera technology over the past few decades is due in large part to the use of inexpensive silicon-based detectors which can sense wavelengths in the visible region and in the infrared region up to about 1050 nm. For longer wavelengths, however, detectors composed of different materials are required. Indium gallium arsenide (InGaAs) detectors have become the dominant technology for detectors on the market, surpassing germanium (Ge), lead sulfide (PbS), and lead selenide (PbSe) detectors [11]. Unfortunately, these detectors are generally more costly than silicon-based detectors. Furthermore, for wavelengths beyond 1700 nm, the noise in these detectors becomes so high that cooling is required to keep it to a manageable level [12]. To minimize the cost of these more expensive detectors, developers of handheld infrared spectrometers have sought to

simplify detector designs by reducing the number of elements required.

NIRS covers the approximate wavelength spectrum of 780 to 2500 nm. Within this range lie signals from the vibration of organic chemical bonds such as oxygenhydrogen (O-H), carbon-hydrogen (C-H), nitrogen-hydrogen (N-H), and sulfurhydrogen (S-H), as well as their overtones [13]. Instrument cost and robustness is generally better for NIR than for MIR [14]. However, NIR spectral peaks tend to be weak and broad with significant overlapping of absorption peaks because of a combination of vibrational spectra from multiple chemical bonds, making straightforward interpretation difficult, if not impossible [15]. Spectral preprocessing techniques (e.g., smoothing, detrending, and taking derivatives) and multivariate statistical methods (e.g., nonlinear partial least squares, Fisher determinant analysis, and artificial neural networks) are invoked to extract the information hidden in the spectra. Despite these disadvantages, the advantage in terms of lower cost, increased safety for the environment and operators, and superior chemical

*DOI: http://dx.doi.org/10.5772/intechopen.97624*

evaluating the quality of food products.

interest in food analysis applications.

*2.1.1.1 Near-infrared spectroscopy (NIRS)*

**2.1 Infrared spectroscopy**

*2.1.1 Infrared detectors*

#### *Advanced Optical Technologies in Food Quality and Waste Management DOI: http://dx.doi.org/10.5772/intechopen.97624*

combines spectroscopy and imaging to enable evaluation of an object's spectroscopic composition at a high spatial resolution, thus providing a more comprehensive evaluation tool for any given sample [7–9]. As the scale and complexity of food supply networks continues to grow, there is an ever increasing need for low-cost, portable, analytical devices to combat the corresponding growth in vulnerability of food products to adulteration, contamination, and fraud [10]. In the next section, we discuss a variety of technologies that have enabled the recent development of portable and handheld spectroscopic devices that can and have been used for evaluating the quality of food products.
