Wenxiu Wang

A portable nondestructive detection device of quality and nutritional parameters of meat using Vis/NIR spectroscopy

The improvement of living standards has urged consumers to pay more attention to the quality and nutrition of meat, so the development of nondestructive detection device for quality and nutritional parameters is commercioganic undoubtedly. In this research, a portable device equipped with visible (Vis) and near-infrared (NIR) spectrometers, tungsten halogen lamp, optical fiber, ring light guide and embedded computer was developed to realize simultaneous and fast detection of color (L*, a*, b*), pH, total volatile basic nitrogen (TVB-N), intramuscular fat (IF), protein and water content in pork. The wavelengths of dual-band spectrometers were 400~1100 nm and 940~1650 nm respectively and the tungsten halogen lamp cooperated with ring light guide to form a ring light source and provide appropriate illumination intensity for sample. Software was self-developed to control the functionality of dual-band spectrometers, set spectrometer parameters, acquire and process Vis/NIR spectroscopy and display the prediction results in real time. In order to obtain a robust and accurate prediction model, fresh longissimus dorsi meat was bought and placed in the refrigerator for 12 days to get pork samples with different freshness degrees. Besides, pork meat from three different parts including longissimus dorsi, haunch and lean meat was collected for the determination of IF, protein and water to make the reference values have a wider distribution range. After acquisition of Vis/NIR spectra, data from 400~1100 nm were pretreated with Savitzky-Golay (S-G) filter and standard normal variables transform (SNVT) and spectrum data from 940~1650 nm were preprocessed with SNVT. The anomalous were eliminated by Monte Carlo method based on model cluster analysis and then partial least square regression (PLSR) models based on single band (400~1100 nm or 940~1650 nm) and dual-band were established and compared. The results showed the optimal models for each parameter were built with correlation coefficients in prediction set of 0.9101, 0.9121, 0.8873, 0.9094, 0.9378, 0.9348, 0.9342 and 0.8882, respectively. It indicated this innovative and practical device can be a promising technology for nondestructive, fast and accurate detection of nutritional parameters in meat.

Spectral Detection Techniques for Non-Destructively Monitoring the Quality, Safety, and Classification of Fresh Red Meat

Red meat is an important source of nutrients and plays a significant role in human diet. With the development of people’s living standard and relative change of dietary structure in recent years, people propose more requirements for meat. Quality, safety, and classification are three crucial themes related with meat and they are important issues for consumers, retailers, as well as the whole meat industry. However, most of the traditional analytical methods for meat evaluation are time-consuming, laborious, tedious, and destructive, which make them inappropriate for fast analysis and early detection, especially under fast-paced production and processing environment. In contrast to conventional approaches, spectral techniques including near infrared spectroscopy (NIRS), hyperspectral imaging (HSI), and Raman spectroscopy (RS) have emerged and considered as promising tools for meat assessment. The innovative optical sensing techniques can facilitate simple, fast, accurate, and simultaneous measurements of multiple meat attributes. Recently, these techniques have achieved rapid development and attracted more attention of the public. Hence, the goal of this article is to give an overview of the current progress of the spectral techniques for evaluation of fresh red meat (pork, beef, and lamb). The spectral techniques are described in terms of their basic working principle, fundamental configurations, analysis process, as well as applications on meat inspection. In addition, the problems to be tackled and future potential trends of these spectral methods are also discussed in this paper.

A portable device for detecting fruit quality by diffuse reflectance Vis/NIR spectroscopy

Soluble solid content (SSC) is a major quality parameter to fruit, which has influence on its flavor or texture. Some researches on the on-line non-invasion detection of fruit quality were published. However, consumers desire portable devices currently. This study aimed to develop a portable device for accurate, real-time and nondestructive determination of quality factors of fruit based on diffuse reflectance Vis/NIR spectroscopy (520-950 nm). The hardware of the device consisted of four units: light source unit, spectral acquisition unit, central processing unit, display unit. Halogen lamp was chosen as light source. When working, its hand-held probe was in contact with the surface of fruit samples thus forming dark environment to shield the interferential light outside. Diffuse reflectance light was collected and measured by spectrometer (USB4000). ARM (Advanced RISC Machines), as central processing unit, controlled all parts in device and analyzed spectral data. Liquid Crystal Display (LCD) touch screen was used to interface with users. To validate its reliability and stability, 63 apples were tested in experiment, 47 of which were chosen as calibration set, while others as prediction set. Their SSC reference values were measured by refractometer. At the same time, samples spectral data acquired by portable device were processed by standard normalized variables (SNV) and Savitzky-Golay filter (S-G) to eliminate the spectra noise. Then partial least squares regression (PLSR) was applied to build prediction models, and the best predictions results was achieved with correlation coefficient (r) of 0.855 and standard error of 0.6033° Brix. The results demonstrated that this device was feasible to quantitatively analyze soluble solid content of apple.