Feed-Forward Prediction of Product Qualities in Enzymatic Protein Hydrolysis of Poultry By-products: a Spectroscopic Approach

A portable dry film FTIR instrument for industrial food and bioprocess applications

The main objective of this study was to design, build, and test a compact, multi-well, portable dry film FTIR system for industrial food and bioprocess applications. The system features dry film sampling on a circular rotating disc comprising 31 wells, a design that was chosen to simplify potential automation and robotic sample handling at a later stage. Calibration models for average molecular weight (AMW, 200 samples) and collagen content (68 samples) were developed from the measurements of industrially produced protein hydrolysate samples in a controlled laboratory environment. Similarly, calibration models for the prediction of lactate content in samples from cultivation media (59 samples) were also developed. The portable dry film FTIR system showed reliable model characteristics which were benchmarked with a benchtop FTIR system. Subsequently, the portable dry film FTIR system was deployed in a bioprocessing plant, and protein hydrolysate samples were measured at-line in an industrial environment. This industrial testing involved building a calibration model for predicting AMW using 60 protein hydrolysate samples measured at-line using the portable dry film FTIR system and subsequent model validation using a test set of 26 samples. The industrial calibration in terms of coefficient of determination (R2 = 0.94), root mean square of cross-validation (RMSECV = 194 g mol-1), and root mean square of prediction (RMSEP = 162 g mol-1) demonstrated low prediction errors as compared to benchtop FTIR measurements, with no statistical difference between the calibration models of the two FTIR systems. This is to the authors' knowledge the first study for developing and employing a portable dry film FTIR system in the enzymatic protein hydrolysis industry for successful at-line measurements of protein hydrolysate samples. The study therefore suggests that the portable dry film FTIR instrument has huge potential for in/at-line applications in the food and bioprocessing industries.

In-line Raman spectroscopy for characterization of an industrial poultry raw material stream

In this work, we evaluated the feasibility of Raman spectroscopy as an in-line raw material characterization tool for industrial process control of the hydrolysis of poultry rest raw material. We established calibrations (N = 59) for fat, protein, ash (proxy for bone) and hydroxyproline (proxy for collagen) in ground poultry rest raw material. Calibrations were established in the laboratory using poultry samples with high compositional variation. Samples were measured using a wide area illumination Raman probe at varying working distance (6 cm, 9 cm, 12 cm) and probe tilt angle (0°, 30°) to mimic expected in-line variations in the measurement situation. These moderate variations did not significantly affect performance for any analytes. The obtained calibrations were tested in-line with continuous measurements of the ground poultry by-product stream at a commercial hydrolysis facility over the course of two days. Measurements were acquired under demanding conditions, e.g. large variations in working distance. Reasonable estimates of compositional trends were obtained. Validation samples (N = 19) were also reasonably well predicted, with RMSEPcorr = [0.14, 1.37, 2.36, 1.51]% for hydroxyproline, protein, fat and ash, respectively. However, there were indications that further calibration development and robustification of pre-processing would be advantageous, particularly with respect to hydroxyproline and protein models. It is the authors' impression that with such efforts, potentially in combination with development of practical measurement setup, the use of Raman spectroscopy as a process control tool for the hydrolysis of poultry rest raw materials is within reach.

The role of biospectroscopy and chemometrics as enabling technologies for upcycling of raw materials from the food industry

It is important to utilize the entire animal in meat and fish production to ensure sustainability. Rest raw materials, such as bones, heads, trimmings, and skin, contain essential nutrients that can be transformed into high-value products. Enzymatic protein hydrolysis (EPH) is a bioprocess that can upcycle these materials to create valuable proteins and fats. This paper focuses on the role of spectroscopy and chemometrics in characterizing the quality of the resulting protein product and understanding how raw material quality and processing affect it. The article presents recent developments in chemical characterisation and process modelling, with a focus on rest raw materials from poultry and salmon production. Even if some of the technology is relatively mature and implemented in many laboratories and industries, there are still open challenges and research questions. The main challenges are related to the transition of technology and insights from laboratory to industrial scale, and the link between peptide composition and critical product quality attributes.

Encoder-decoder neural networks for predicting future FTIR spectra - application to enzymatic protein hydrolysis

In the process of converting food-processing by-products to value-added ingredients, fine grained control of the raw materials, enzymes and process conditions ensures the best possible yield and economic return. However, when raw material batches lack good characterization and contain high batch variation, online or at-line monitoring of the enzymatic reactions would be beneficial. We investigate the potential of deep neural networks in predicting the future state of enzymatic hydrolysis as described by Fourier-transform infrared spectra of the hydrolysates. Combined with predictions of average molecular weight, this provides a flexible and transparent tool for process monitoring and control, enabling proactive adaption of process parameters.

Enzymatic Chicken Pulp Promotes Appetite, Digestive Enzyme Activity, and Growth in Litopenaeus vannamei

Enzymatic chicken pulp (ECP) is an animal protein source that has been proven to be of excellent nutritional content and good quality for the majority of aquatic organisms because of its quality protein, small peptides, palatability, vitamins, and minerals. An 8-week nutritional trial was conducted to assess the effects of an ECP-based diet on the growth performance, digestive enzyme activity, and gene mRNA expression of Pacific white shrimp (Litopenaeus vannamei). Fish soluble pulp (FSP) served as the control group while in the experimental groups, and ECPs with three protein contents were used to replace FSP in equal amounts, named ECP1, ECP2, and ECP3, respectively. No significant difference in weight gain rate, specific growth rate, survival rate, or feed conversion ratio was observed (p > 0.05) between the groups. Ash content in the Pacific shrimp’s whole body was significantly higher in the ECP1 and ECP3 groups compared to the other groups (p < 0.05). Intestinal amylase and protease activities were the highest in the ECP1 and ECP2 groups, respectively (p < 0.05). With respect to gene mRNA expression, neuropeptide Y, excitatory amino acid transporter, and fatty acid transport protein 4 were significantly high in the ECP1 group (p < 0.05). In conclusion, these three ECPs have their advantages to replace FSP in shrimp feed, but ECP1 is more effective if the effects of digestive enzyme activity, appetite, and expression of growth-related genes are considered.

Assessment of chicken intestinal hydrolysates as a new protein source to replace fishmeal on the growth performance, antioxidant capacity and intestinal health of common carp (Cyprinus carpio)

Promoting circular economy by transforming food residues into alternative high-value protein sources for aquaculture feed is a new way to develop alternative raw materials for fishmeal. This study systematically evaluated the effects of chicken intestinal hydrolysates (CIH) on the intestinal immune health of common carp through growth performance, antioxidant capacity, and intestinal immunity analysis in order to replace fishmeal. Five iso-nitrogenous and iso-lipidic experimental feeds were formulated to replace 0% (CIH-0), 25% (CIH-25), 50% (CIH-50), 75% (CIH-75) and 100% (CIH-100) of the fishmeal with CIH. Each experimental diet was fed to triplicate groups of 30 carp for 8 weeks. The results revealed that no significant differences in the final body weight, weight gain rate, feed coefficient radio, feed intake and protein efficiency ratio were found among the CIH-0, CIH-25, and CIH-50 groups, while the final body weight and weight gain rate in the CIH-75 and CIH-100 groups were significantly decreased and the feed coefficient radio was significantly increased. The aspartate aminotransferase of all CIH groups were significantly decrease, and the total protein, albumin did not differ among the CIH-0, CIH-25, CIH-50, and CIH-75 groups. The trypsin content was significantly increased in the CIH-75 and CIH-100 groups. No significant differences in the antioxidant index (catalase, glutathione peroxidase and malonaldehyde) were found among all CIH groups compared with the CIH-0 group. The expression levels of pro-inflammatory cytokines IL-1β and TNF-α were significantly down-regulated in the CIH-50 group and anti-inflammatory cytokines IL-10 and TGF-β2 were significantly up-regulated in the CIH-50 and CIH-75 groups. No significant differences in the expression levels of claudin-1, claudin-7 and claudin-11 were observed between the CIH-0 and CIH-50 groups, while the expression levels of ZO-1, occludin and MLCK were significantly up-regulated in the CIH-50 group compared with the CIH-0 group. The expression level of claudin-1 was down-regulated in the CIH-75 and CIH-100 groups. Hence, the study demonstrated the potential of CIH as a novel protein source for replacing fishmeal, and replacing 50% of fishmeal with CIH did not significantly influence the growth performance, immune responses, and intestinal barrier of common carp (Cyprinus carpio).

Feasibility of In-Line Raman Spectroscopy for Quality Assessment in Food Industry: How Fast Can We Go?

Raman spectroscopy is a viable tool within process analytical technologies due to recent technological advances. In this article, we evaluate the feasibility of Raman spectroscopy for in-line applications in the food industry by estimating the concentration of the fatty acids EPA + DHA in ground salmon samples (n = 63) and residual bone concentration in samples of mechanically recovered ground chicken (n = 66). The samples were measured under industry like conditions: They moved on a conveyor belt through a dark cabinet where they were scanned with a wide area illumination standoff Raman probe. Such a setup should be able to handle relevant industrial conveyor belt speeds, and it was studied how different speeds (i.e., exposure times) influenced the signal-to-noise ratio (SNR) of the Raman spectra as well as the corresponding model performance. For all samples we applied speeds that resulted in 1 s, 2 s, 4 s, and 10 s exposure times. Samples were scanned in both heterogenous and homogenous state. The slowest speed (10 s exposure) yielded prediction errors (RMSECV) of 0.41%EPA + DHA and 0.59% ash for the salmon and chicken data sets, respectively. The more in-line relevant exposure time of 1 s resulted in increased RMSECV values, 0.84% EPA + DHA and 0.84% ash, respectively. The increase in prediction error correlated closely with the decrease in SNR. Further improvements of model performance were possible through different noise reduction strategies. Model performance for homogenous and heterogenous samples was similar, suggesting that the presented Raman scanning approach has the potential to work well also on intact heterogenous foods. The estimation errors obtained at these high speeds are likely acceptable for industrial use, but successful strategies to increase SNR will be key for widespread in-line use in the food industry.

The fourth industrial revolution in the food industry-Part I: Industry 4.0 technologies

Climate change, the growth in world population, high levels of food waste and food loss, and the risk of new disease or pandemic outbreaks are examples of the many challenges that threaten future food sustainability and the security of the planet and urgently need to be addressed. The fourth industrial revolution, or Industry 4.0, has been gaining momentum since 2015, being a significant driver for sustainable development and a successful catalyst to tackle critical global challenges. This review paper summarizes the most relevant food Industry 4.0 technologies including, among others, digital technologies (e.g., artificial intelligence, big data analytics, Internet of Things, and blockchain) and other technological advances (e.g., smart sensors, robotics, digital twins, and cyber-physical systems). Moreover, insights into the new food trends (such as 3D printed foods) that have emerged as a result of the Industry 4.0 technological revolution will also be discussed in Part II of this work. The Industry 4.0 technologies have significantly modified the food industry and led to substantial consequences for the environment, economics, and human health. Despite the importance of each of the technologies mentioned above, ground-breaking sustainable solutions could only emerge by combining many technologies simultaneously. The Food Industry 4.0 era has been characterized by new challenges, opportunities, and trends that have reshaped current strategies and prospects for food production and consumption patterns, paving the way for the move toward Industry 5.0.

Potentiality of Nanoenzymes for Cancer Treatment and Other Diseases: Current Status and Future Challenges

Studies from past years have observed various enzymes that are artificial, which are issued to mimic naturally occurring enzymes based on their function and structure. The nanozymes possess nanomaterials that resemble natural enzymes and are considered an innovative class. This innovative class has achieved a brilliant response from various developments and researchers owing to this unique property. In this regard, numerous nanomaterials are inspected as natural enzyme mimics for multiple types of applications, such as imaging, water treatment, therapeutics, and sensing. Nanozymes have nanomaterial properties occurring with an inheritance that provides a single substitute and multiple platforms. Nanozymes can be controlled remotely via stimuli including heat, light, magnetic field, and ultrasound. Collectively, these all can be used to increase the therapeutic as well as diagnostic efficacies. These nanozymes have major biomedical applications including cancer therapy and diagnosis, medical diagnostics, and bio sensing. We summarized and emphasized the latest progress of nanozymes, including their biomedical mechanisms and applications involving synergistic and remote control nanozymes. Finally, we cover the challenges and limitations of further improving therapeutic applications and provide a future direction for using engineered nanozymes with enhanced biomedical and diagnostic applications.

Assessment of Bulk Composition of Heterogeneous Food Matrices Using Raman Spectroscopy

Raman spectroscopy (RS) has for decades been considered a promising tool for food analysis, but widespread adoption has been held back by, e.g., high instrument costs and sampling limitations regarding heterogeneous samples. The aim of the present study was to use wide area RS in conjunction with surface scanning to overcome the obstacle of heterogeneity. Four different food matrices were scanned (intact and homogenized pork and by-products from salmon and poultry processing) and the bulk chemical parameters such as fat and protein content were estimated using partial least squares regression (PLSR). The performance of PLSR models from RS was compared with near-infrared spectroscopy (NIRS). Good to excellent results were obtained with PLSR models from RS for estimation of fat content in all food matrices (coefficient of determination for cross-validation (R²_CV) from 0.73 to 0.96 and root mean square error of cross-validation (RMSECV) from 0.43% to 2.06%). Poor to very good PLSR models were obtained for estimation of protein content in salmon and poultry by-product using RS (R²_CV from 0.56 to 0.92 and RMSECV from 0.85% to 0.94%). The performance of RS was similar to NIRS for all analyses. This work demonstrates the applicability of RS to analyze bulk composition in heterogeneous food matrices and paves way for future applications of RS in routine food analyses.

Exploring Effects of Protease Choice and Protease Combinations in Enzymatic Protein Hydrolysis of Poultry By-Products

A study of the effects of single and combined protease hydrolysis on myofibrillar versus collagenous proteins of poultry by-products has been conducted. The aim was to contribute with knowledge for increased value creation of all constituents of these complex by-products. A rational approach was implemented for selecting proteases exhibiting the most different activity towards the major protein-rich constituents of mechanically deboned chicken residue (MDCR). An initial activity screening of 18 proteases on chicken meat, turkey tendons and MDCR was conducted. Based on weight yield, size exclusion chromatography (SEC) and SDS-PAGE, stem Bromelain and Endocut-02 were selected. Studies on hydrolysis of four different poultry by-products at 40 °C, evaluated by protein yield, SEC, and SDS-PAGE, indicate that the proteases’ selectivity difference can be utilized in tailor-making hydrolysates, enriched in either meat- and collagen-derived peptides or gelatin. Three modes of stem Bromelain and Endocut-02 combinations during hydrolysis of MDCR were performed and compared with single protease hydrolysis. All modes of the protease combinations resulted in a similar approximately 15% increase in product yield, with products exhibiting similar SEC and SDS-PAGE profiles. This shows that irrespective of the modes of combination, the use of more than one enzyme in hydrolysis of collagen-rich material can provide means to increase the total protein yield and ultimately contribute to increased value creation of poultry by-products.

Development of an on-line Raman spectral analytical method for monitoring and endpoint determination of the Cornu Caprae Hircus hydrolysis process

OBJECTIVES

Cornu Caprae Hircus (goat horn, GH), a medicinal animal horn, is frequently used in traditional Chinese medicine, and hydrolysis is one of the most important processes for GH pretreatment in pharmaceutical manufacturing. In this study, on-line Raman spectroscopy was applied to monitor the GH hydrolysis process by the development of partial least squares (PLS) calibration models for different groups of amino acids.

METHODS

Three steps were considered in model development. In the first step, design of experiments (DOE)-based preprocessing method selection was conducted. In the second step, the optimal spectral co-addition number was determined. In the third step, sample selection or reconstruction methods based on hierarchical clustering analysis (HCA) were used to extract or reconstruct representative calibration sets from the pool of hydrolysis process samples and investigated for their ability to improve model performance.

KEY FINDINGS

This study has shown the feasibility of using on-line Raman spectral analysis for monitoring the GH hydrolysis process based on the designed measurement system and appropriate model development steps.

CONCLUSIONS

The proposed Raman-based calibration models are expected to be used in GH hydrolysis process monitoring, leading to more rapid material information acquisition, deeper process understanding, more accurate endpoint determination and thus better product quality consistency.

Development of Nanozymes for Food Quality and Safety Detection: Principles and Recent Applications

The public concerns about agrifood safety call for innovative and reformative analytical techniques to meet the inspection requirements of high sensitivity, specificity, and reproducibility. Enzyme-mimetic nanomaterials or nanozymes, which combine enzyme-like properties with nanoscale features, emerge as an excellent tool for quality and safety detection in the agrifood sector, due to not only their robust capacity in detection but also their attraction in future-oriented exploitations. However, in-depth understanding about the fundamental principles of nanozymes for food quality and safety detection remains limited, which makes their applications largely empirical. This review provides a comprehensive overview of the principles, designs, and applications of nanozyme-based detection technique in the agrifood industry. The discussion mainly involves three mimicking types, that is, peroxidase, oxidase, and catalase-like nanozymes, capable of detecting major agrifood analytes. The current principles and strategies are classified and then discussed in details through discriminating the roles of nanozymes in diverse detection platforms. Thereafter, recent applications of nanozymes in detecting various endogenous ingredients and exogenous contaminants in foods are reviewed, and the outlook of profound developments are explained. Evidenced by the increasing publications, nanozyme-based detection techniques are narrowing the gap to practical-oriented food analytical methods, while some challenges in optimization of nanozymes, diversification of recognition-to-signal manners, and sustainability of methodology need to conquer in the future.