Optimization of Processing Parameters for Continuous Microwave Drying of Crab Apple Slices via Response Surface Methodology.

To improve product quality and obtain suitable processing parameters for crab apple slices (CASs) produced by continuous microwave drying (CMD), the effects of processing parameters, including slice thickness, microwave power, air velocity, and conveyor belt speed, on the evaluation indexes in terms of temperature, moisture content, color (L*, a*, b*), hardness, brittleness, and total phenolic content of CASs were investigated via the response surface method. The results indicated that microwave power has the greatest effect on the evaluation indexes applied to the CASs under CMD, followed by air velocity, slice thickness, and conveyor belt speed. To produce the desired product quality, the appropriate parameters for CMD of CASs were optimized as 1.25 mm slice thickness, 14,630 W microwave power, 0.50 m·s-1 air velocity, and 0.33 m·min-1 conveyor belt speed. Following that, the moisture content under CMD was found to be 13.53%, the desired color, hardness 0.79 g, brittleness 12.97 (number of peaks), and the total phenolic content 5.48 mg·g-1. This research provides a theoretical framework for optimizing the processing parameters of CASs using the response surface method.

Evaluation and Defect Detection in L-Shaped GFRP Laminates by Infrared Thermography.

Glass fiber-reinforced polymer (GFRP) laminates are used in many applications because of their availability, high mechanical properties, and cost-effectiveness. Fiber defects in the form of waviness or wrinkles can occur during the production of multilayered laminates. When curved laminates of significant thickness are produced, the likelihood of such defects increases. Studies have confirmed that fiber deformation during manufacture leads to a reduction in the mechanical properties of laminates. Therefore, early detection of such defects is essential. The main part of this paper deals with research into the possibility of using active infrared thermography to detect wrinkles in curved multilayered GFRP laminates. The size of the artificial wrinkles was assessed by analyzing scans and microimages. The shape deformations of the samples were evaluated by comparing the samples with the mold and the assumed nominal shape. The influence of the out-of-autoclave manufacturing process on the reduction in wrinkles formed without significantly affecting the internal structure of the laminate is presented in this work. This research demonstrated the ability to detect wrinkles in thick curved laminates using active infrared thermography. However, it also showed how the interpretation of the thermographic results is affected by the curvature of the structure, the lack of uniform heating, and the configuration of the thermographic setup.

Dynamic Interplay between Microbiota Shifts and Differential Metabolites during Dairy Processing and Storage.

Due to the intricate complexity of the original microbiota, residual heat-resistant enzymes, and chemical components, identifying the essential factors that affect dairy quality using traditional methods is challenging. In this study, raw milk, pasteurized milk, and ultra-heat-treated (UHT) milk samples were collectively analyzed using metagenomic next-generation sequencing (mNGS), high-throughput liquid chromatography-mass spectrometry (LC-MS), and gas chromatography-mass spectrometry (GC-MS). The results revealed that raw milk and its corresponding heated dairy products exhibited different trends in terms of microbiota shifts and metabolite changes during storage. Via the analysis of differences in microbiota and correlation analysis of the microorganisms present in differential metabolites in refrigerated pasteurized milk, the top three differential microorganisms with increased abundance, Microbacterium (p < 0.01), unclassified Actinomycetia class (p < 0.05), and Micrococcus (p < 0.01), were detected; these were highly correlated with certain metabolites in pasteurized milk (r > 0.8). This indicated that these genera were the main proliferating microorganisms and were the primary genera involved in the metabolism of pasteurized milk during refrigeration-based storage. Microorganisms with decreased abundance were classified into two categories based on correlation analysis with certain metabolites. It was speculated that the heat-resistant enzyme system of a group of microorganisms with high correlation (r > 0.8), such as Pseudomonas and Acinetobacter, was the main factor causing milk spoilage and that the group with lower correlation (r < 0.3) had a lower impact on the storage process of pasteurized dairy products. By comparing the metabolic pathway results based on metagenomic and metabolite annotation, it was proposed that protein degradation may be associated with microbial growth, whereas lipid degradation may be linked to raw milk's initial heat-resistant enzymes. By leveraging the synergy of metagenomics and metabolomics, the interacting factors determining the quality evolution of dairy products were systematically investigated, providing a novel perspective for controlling dairy processing and storage effectively.

Optimal Ways of Safflower Oil Production with Improvement of Press Equipment.

This study aims to improve press equipment for safflower oil production by using a mechanism that optimizes pressure distribution within screw turns. A detailed analysis of the main components of the produced safflower oil was performed, encompassing both quantitative and qualitative assessments. Through the exploration of dependencies governing the safflower oil pressing process on the screw press, the optimal parameters were determined. As a result of the research, the optimal diaphragm gap between the gape cylinder and the pressing screw was determined, with the optimal oil yield percentage achieved at ω = 6.2 rad/s and δ = 5 mm. The study also compared the performance of the existing Dream Modern ODM-01 screw press and its upgraded version by analyzing the extracted oil. The results reveal changes in the quantitative and qualitative composition of the main oil components following the operation of the existing and the modernized screw presses. For instance, the amount of unsaturated fatty acids, such as oleic acid (7.7 ± 0.566%), linoleic acid (85.3 ± 1.185%), and linolenic acid (1.2 ± 0.223%), increased. There was an increase in the presence of inorganic substances in safflower oil: iron (0.023 ± 0.031 mg/kg), phosphorus (0.086 ± 0.059 mg/kg), silicium (0.136 ± 0.075 mg/kg), and others. The findings of this study hold significant commercial value and offer promising prospects for global market implementation.

Use of spectroscopic process analytical technology for rapid quality evaluation during preparation of CHO cell culture media.

Media preparation parameters contribute significantly to media quality, cell culture performance, productivity, and product quality. Establishing proper media preparation procedures is critical for ensuring a robust CHO cell culture process. Process analytical technology (PAT) enables unique ways to quantify assessments and improve media quality. Here, cell culture media were prepared under a wide range of temperatures (40-80°C) and pH (7.6-10.0). Media quality profiles were compared using three real-time PATs: Fourier-transform infrared (FTIR) spectroscopy, Raman spectroscopy, and excitation-emission matrix (EEM) spectroscopy. FTIR and Raman spectroscopies identified shifts in media quality under high preparation temperature (80°C) and at differing preparation pH which negatively impacted monoclonal antibody (mAb) production. In fed-batch processes for production of three different mAbs, viable cell density (VCD) and cell viability were mostly unaffected under all media preparation temperatures, while titer and cell specific productivity of mAb decreased when cultured in basal and feed media prepared at 80°C. High feed preparation pH alone was tolerated but cell growth and productivity profiles deviated from the control condition. Further, charge variants (main, acidic, basic species) and glycosylation (G0F, afucosylation, and high mannose) were examined. Statistically significant differences were observed for one or more of these quality attributes with any shifts in media preparation. In this study, we demonstrated strong associations between media preparation conditions and cell growth, productivity, and product quality. The rapid evaluation of media by PAT implementation enabled more comprehensive understanding of different parameters on media quality and consequential effects on CHO cell culture.

Improving the microbiological safety and quality of aquatic products using nonthermal processing.

Spoilage and deterioration of aquatic products during storage are inevitable, posing significant challenges to their suitability for consumption and the sustainability of the aquatic products supply chain. Research on the nonthermal processing of fruit juices, probiotics, dairy products, and meat has demonstrated positive outcomes in preserving quality. This review examines specific spoilage bacteria species and mechanisms for various aquatic products and discusses the principles, characteristics, and applications of six nonthermal processing methods for bacterial inhibition to maintain microbiological safety and physicochemical quality. The primary spoilage bacteria groups differ among fish, crustaceans, and shellfish based on storage conditions and durations. Four metabolic pathways utilized by spoilage microorganisms-peptides and amino acids, nitrogen compounds, nucleotides, and carbohydrates-are crucial in explaining spoilage. Nonthermal processing techniques, such as ultrahigh pressure, irradiation, magnetic/electric fields, plasma, and ultrasound, can inactivate microorganisms, thereby enhancing microbiological safety, physicochemical quality, and shelf life. Future research may integrate nonthermal processing with other technologies (e.g., modified atmosphere packaging and omics) to elucidate mechanisms of spoilage and improve the storage quality of aquatic products.

Behavioral decision-making of government, agricultural product producers, and consumers on agricultural product quality and safety regulation in a digital environment.

The quality and safety of agricultural products are related to people's lives and health, economic development, and social stability, and have always been a hot issue of concern to the government and society. The rapid development of digital traceability technology in the digital environment has brought new opportunities for the supervision of agricultural product quality and safety, but the frequent occurrence of agricultural product safety incidents in recent years has exposed many problems such as the lack of governmental supervision, unstandardized production process of enterprises, and weak consumer awareness. To improve the cooperation efficiency of stakeholders and ensure the quality and safety of agricultural products, this paper proposes a dynamic model based on evolutionary game theory. The model incorporates the government, agricultural product producers, and farmers, and evaluates the stability and effectiveness of the system under different circumstances. The results of the study show that there are multiple evolutionary stabilization strategies in the tripartite evolutionary game model of agricultural product quality and safety supervision, and there are corresponding evolutionary stabilization conditions. There are several factors affecting the stability of the system, the most important of which are government regulation, severe penalties for agricultural product producers, and incentives. When these factors reach a certain threshold, the stakeholder cooperation mechanism can establish an evolutionarily stable strategy. This study contributes to the understanding of the operational mechanism of stakeholder cooperation in agricultural product quality and safety regulation in the digital environment and provides decision support and policy recommendations for stakeholders to promote the sustainable development and optimization of agricultural product quality and safety regulation.

Physiologically Based Biopharmaceutics Modeling (PBBM): Best Practices for Drug Product Quality, Regulatory and Industry Perspectives: 2023 Workshop Summary Report.

Physiologically based biopharmaceutics modeling (PBBM) is used to elevate drug product quality by providing a more accurate and holistic understanding of how drugs interact with the human body. These models are based on the integration of physiological, pharmacological, and pharmaceutical data to simulate and predict drug behavior in vivo. Effective utilization of PBBM requires a consistent approach to model development, verification, validation, and application. Currently, only one country has a draft guidance document for PBBM, whereas other major regulatory authorities have had limited experience with the review of PBBM. To address this gap, industry submitted confidential PBBM case studies to be reviewed by the regulatory agencies; software companies committed to training. PBBM cases were independently and collaboratively discussed by regulators, and academic colleagues participated in some of the discussions. Successful bioequivalence "safe space" industry case examples are also presented. Overall, six regulatory agencies were involved in the case study exercises, including ANVISA, FDA, Health Canada, MHRA, PMDA, and EMA (experts from Belgium, Germany, Norway, Portugal, Spain, and Sweden), and we believe this is the first time such a collaboration has taken place. The outcomes were presented at this workshop, together with a participant survey on the utility and experience with PBBM submissions, to discuss the best scientific practices for developing, validating, and applying PBBMs. The PBBM case studies enabled industry to receive constructive feedback from global regulators and highlighted clear direction for future PBBM submissions for regulatory consideration.

Determination of performance response of broilers to fermented tropical leaf meal supplementation using meta-analytical method.

Fermented tropical leaf meals (FTLM) are currently added to chicken feed to improve chicken productivity due to their reported nutritional and medicinal benefits. However, the effects of FTLM on broiler productivity and health are less clear. Thus, this meta-analysis was designed to assess the effects of FTLM on the performance outcomes of broilers Eleven controlled studies were retrieved and used to explore the impacts of dietary FTLM supplementation on growth performance [feed intake (FI), feed conversion ratio (FCR), average daily gain (ADG)], blood lipids, slaughter performance (abdominal fat, breast and thigh muscles weight), meat quality [pH, drip loss, shear force, lightness (L*), redness (a*), and yellowness (b*)], and intestinal histomorphology [villus height (VH), crypt depth (CD) and VH/CD values] of broilers. Subgroup and meta-regression analyses of the effects of moderators (i.e., leaf meal type, supplementation level, broiler strains, rearing phase, and fermentation microbes) on the growth performance of broilers were also assessed. Results show that dietary FTLM supplementation increased FI [standardised mean difference (SMD) = 0.11; 95% confidence interval (CI): 0.02, 0.20; P < 0.0001], improved ADG (SMD = 0.33; 95% CI: 0.23, 0.43; P < 0.0001) and FCR (SMD = - 0.21; 95% CI: - 0.30, - 0.11; P < 0.0001) in broilers. In addition, FTLM enhanced slaughter performance, meat quality, and intestinal histomorphology of broilers. Broilers fed 0-5 g/kg feed FTLM had better FI, FCR, and ADG than the controls taking significant heterogeneity into account. Meta-regression revealed that analysed moderators influenced growth performance results and accounted for some of the sources of heterogeneity. It can be concluded that up to 5 g/kg of FTLM can be added to broiler feed to improve growth performance, intestinal histomorphology, slaughter performance, and meat quality without adverse effects on dressing percentage and blood lipid profiles.

Improvement of the drying quality of blueberries by catalytic infrared blanching combined with ultrasound pretreatment.

This paper investigated the effect of catalytic infrared blanching combined with ultrasound pretreatment on quality and waxy structure of blueberries. Different blueberry samples were prepared, including control (untreated) and samples treated by hot water blanching (HB), catalytic infrared blanching (CIB), ultrasound-catalytic infrared blanching (US-CIB), and catalytic infrared blanching-ultrasound (CIB-US). The effect of different pretreatments on the microstructure of blueberry epidermis was studied. The drying time of blueberries after HB, US-CIB, and CIB-US was decreased by 11.61%, 17.54%, and 17.27%, respectively, compared with control (33.75 h), and drying efficiency was significantly improved. Blueberries after pretreatments had higher content of polyphenol and anthocyanin, with an increase of 29.51-44.21% in phenol and 8.81-20.80% in anthocyanin, the antioxidant capacity of blueberries was also better than control and CIB enhanced the antioxidant capacity of blueberries. CIB-US can be used as an efficient pretreatment method for blueberry drying.

Artificial Intelligence-Assisted RFID Tag-Integrated Multi-Sensor for Quality Assessment and Sensing.

Radio frequency identification (RFID) is well known as an identification, track, and trace approach and is considered to be the key physical layer technology for the industrial internet of things (IIoT). However, IIoT systems have to introduce additional complex sensor networks for pervasive monitoring, and there are still challenges related to item-level sensing and data recording. To overcome the shortage, this work proposes an artificial intelligence (AI)-assisted RFID-based multi-sensing technology. Both passive and semi-passive RFID tag-integrated multi-sensors are developed. The main contributions and the novelty of this investigation are as follows. A UHF RFID tag-integrated multi-sensor with a boosted charge pump is proposed; it enables high RF signal sensitivity and a long operational range. The whole hardware design, including the antenna and energy harvester, are studied. Moreover, a demonstration with real-world ham product sensing data is conducted. This work also proposes and successfully demonstrates the integration of machine learning algorithms, specifically the NARX neural network, with RFID sensing data for food product quality assessment and sensing (QAS). This application of machine learning to RFID-generated data for quality assessment is also a novel aspect of the research. The deployment of an autoregressive model with an exogenous input (NARX) neural network model, tailored for nonlinear processes, emerges as the most effective, achieving a root mean square error (RMSE) of 0.007 and an R-squared value of 0.99 for ham product QAS. By deploying the technology, low-cost, timely, and flexible product QAS can be achieved in manufacturing industries, which helps product quality improvement and the optimization of the manufacturing line and supply chain.

An innovative hybrid modeling approach for simultaneous prediction of cell culture process dynamics and product quality.

The use of hybrid models is extensively described in the literature to predict the process evolution in cell cultures. These models combine mechanistic and machine learning methods, allowing the prediction of complex process behavior, in the presence of many process variables, without the need to collect a large amount of data. Hybrid models cannot be directly used to predict final product critical quality attributes, or CQAs, because they are usually measured only at the end of the process, and more mechanistic knowledge is needed for many classes of CQAs. The historical models can instead predict the CQAs better; however, they cannot directly relate manipulated process parameters to final CQAs, as they require knowledge of the process evolution. In this work, we propose an innovative modeling approach based on combining a hybrid propagation model with a historical data-driven model, that is, the combined hybrid model, for simultaneous prediction of full process dynamics and CQAs. The performance of the combined hybrid model was evaluated on an industrial dataset and compared to classical black-box models, which directly relate manipulated process parameters to CQAs. The proposed combined hybrid model outperforms the black-box model by 33% on average in predicting the CQAs while requiring only around half of the data for model training to match performance. Thus, in terms of model accuracy and experimental costs, the combined hybrid model in this study provides a promising platform for process optimization applications.

A Direct Comparison of rAAV5 Variants Derived from the Baculovirus Expression System Using LC-MS Workflows Demonstrates Key Differences in Overall Production Yield, Product Quality and Vector Efficiency.

Gene therapy holds great promise for the treatment of severe diseases, and adeno-associated virus (AAV) vectors have emerged as valuable tools in this field. However, challenges such as immunogenicity and high production costs complicate the commercial viability of AAV-based therapies. To overcome these barriers, improvements in production yield, driven through the availability of robust and sensitive characterization techniques that allow for the monitoring of critical quality attributes to deepen product and process understanding are crucial. Among the main attributes affecting viral production and performance, the ratio between empty and full capsids along with capsid protein stoichiometry are emerging as potential parameters affecting product quality and safety. This study focused on the production of AAV vectors using the baculovirus expression vector system (BEVS) in Sf9 cells and the complete characterization of AAV5 variants using novel liquid chromatography and mass spectrometry techniques (LC-MS) that, up to this point, had only been applied to reference commercially produced virions. When comparing virions produced using ATG, CTG or ACG start codons of the cap gene, we determined that although ACG was the most productive in terms of virus yield, it was also the least effective in transducing mammalian cells. This correlated with a low VP1/VP2 ratio and a higher percentage of empty capsids. Overall, this study provides insights into the impact of translational start codon modifications during rAAV5 production using the BEVS, the associated relationship with capsid packaging, capsid protein stoichiometry and potency. The developed characterization workflow using LC-MS offers a comprehensive and transferable analysis of AAV-based gene therapies, with the potential to aid in process optimization and facilitate the large-scale commercial manufacturing of these promising treatments.

How to Evaluate If Microorganisms Isolated From Sterile Drug Production Environments Monitoring Are Undesirable.

This study addresses the identification of undesirable microorganisms (MOs) recovered during the environmental monitoring in manufacture of sterile medicinal products. We developed a methodology evaluation based on a decision tree; then, such approach was applied to hypothetical scenarios of uncommon MOs isolation in sterile drugs production settings. The scenarios were formulated on the basis of our field experience, in terms of both MOs selection and types of sampling site. The MOs were chosen in order to include emerging pathogens and MOs responsible for drug recall, and several sampling sites were considered for their detection (air, surfaces, and personnel). The classification of the unusual MOs revealed that most of them were undesirable, because they represented the loss of environmental control or a potential impact on the quality of the product. In some cases, the uncommon MOs were not considered as undesirable. Therefore, our results demonstrated the importance of a methodology, also in terms of recovery rate of unusual MOs and of the threshold probability for the unacceptability (e.g., 1% or 5%). The proposed methodology allowed an easy and documented evaluation for the undesirable MOs isolated from the environment of the analyzed settings for sterile drugs production.

Carbon tax vs. carbon trading in China: which is better for promoting sustainable development of remanufacturing companies?

To accelerate achieving carbon neutrality, the promotion of low-carbon development in the manufacturing industry has been facilitated by the government's implementation of policies such as carbon taxation and carbon emissions trading. These measures have been put in place to reduce carbon emissions and enhance sustainability within the manufacturing sector. Remanufacturing is an important direction for the low-carbon transformation of enterprises, and improving remanufactured product quality is crucial to the sustainability of remanufacturing enterprises. To elucidate the influence of policies aimed at reducing carbon emissions on the quality of remanufactured products, we developed a game model involving three key players: the original equipment manufacturer (OEM), the remanufacturer (IR), and retailers. This model was constructed based on the heterogeneous consumer demand for both new and remanufactured products. The study delved into the effects of various governmental policies aimed at reducing carbon emissions on the quality-related decisions made by remanufacturing enterprises. Our primary focus was on the implementation of two specific policies: a high-level carbon taxation policy and a carbon trading policy characterized by elevated carbon pricing. These policies create a favorable environment for remanufacturers (IR) to enhance the quality of their products. The sales of remanufactured products are influenced by the purchasing preferences of consumers, and carbon reduction policies can be effective in reducing the total environmental impact of manufacturing. Carbon trading policy is most conducive to environmental protection and achieves a win-win situation for economic and environmental benefits for OEMs and IRs when the carbon tax per unit is compared with the carbon trading price. Hence, this situation is favorable for the sustainable growth of existing remanufacturing businesses. Consequently, the government's requirement for subsidies to enhance the quality of remanufactured products and boost the competitiveness of IRs in the market becomes less pronounced.

Brown sugar as a carbon source can make agricultural organic waste compost enter the secondary thermophilic stage and promote compost decomposition.

To enhance the efficiency of composting agricultural organic waste (AOW), this study aimed to examine the impact of inoculating tomato straw compost with two distinct microbial agents: ZymoZone (ZZ), a composite microbial agent derived from the straw compost and Effective Microorganisms (EM), a commercial microbial agent. Furthermore, in order to reactivate the microorganisms within the compost during the initial high temperature phase, 10% brown sugar was introduced as a carbon source. The objective of this addition was to assess its influence on the composting process. The findings revealed that compared to the control (CK) group, the ZZ and EM treatments extended the first high-temperature phase by 2 and 1 day, respectively. Furthermore, with the addition of 10% brown sugar, the ZZ and EM treatments remained in the second high-temperature phase for 8 and 7 days, respectively, while the CK treatment had already entered the cooling stage by then. Notably, the inoculation of microbial agents and the addition of brown sugar substantially augmented the activity of lignocellulose-related hydrolases, thereby promoting the degradation of lignocellulose in the ZZ and EM treatment groups. This was confirmed by FTIR analysis, which demonstrated that the addition of microbial agents facilitated the degradation of specific substances, leading to reduced absorbance in the corresponding spectra. XRD analysis further indicated a notable reduction in cellulose crystallinity for both the ZZ (8.00%) and EM (7.73%) treatments. Hence, the incorporation of microbial agents and brown sugar in tomato straw compost effectively enhances the composting process and improves the quality of compost products.

Development of bioreactor scale-down model using orthogonal projections to latent structures method and CO2 supplementation.

Scale-down model qualification is an important step for developing a large-scale cell culture process to enhance process understanding and support process characterization studies. Traditionally, only harvest data are used to show consistency between small-scale and large-scale bioreactor performance, allowing attributes that are dynamic over the cell culture period to be overlooked. A novel statistical method, orthogonal projections to latent structures (OPLS) analysis, can be utilized to compare time-course cell culture data across scales. Here we describe an example where OPLS is used to identify gaps between small-scale and large-scale bioreactor performances. In this case, differences in the partial pressure of carbon dioxide (pCO2) and lactate profiles were observed between small- and large-scale bioreactors, which were linked to differences in the product-quality attributes fragments and galactosylation. An improved small-scale model was developed, leading to improved consistency in the process performance and product qualities across scales and qualification of the scale-down model for regulatory submissions. This new statistical approach can provide valuable insights into process understanding and process scale-up.

A tailored lectin microarray for rapid glycan profiling of therapeutic monoclonal antibodies.

Glycosylation plays a crucial role in determining the quality and efficacy of therapeutic antibodies. This necessitates a thorough analysis and monitoring process to ensure consistent product quality during manufacturing. In this study, we introduce a custom-designed lectin microarray featuring nine distinct lectins: rPhoSL, rOTH3, RCA120, rMan2, MAL_I, rPSL1a, PHAE, rMOA, and PHAL. These lectins have been specifically tailored to selectively bind to common N-glycan epitopes found in therapeutic IgG antibodies. By utilizing intact glycoprotein samples, our nine-lectin microarray provides a high-throughput platform for rapid glycan profiling, enabling comparative analysis of glycosylation patterns. Our results demonstrate the practical utility of this microarray in assessing glycosylation across various manufacturing batches or between biosimilar and innovator products. This capacity empowers informed decision-making in the development and production of therapeutic antibodies.

Incidence of traffic light labelling on noncommunicable diseases: a roadmap for achieving sustainable development.

The production and diversity of the supply of food products has grown exponentially in recent decades, along with the increase in cardiovascular diseases associated with poor diet. Among the factors, one of the most important is the lack of information for the consumer when purchasing. The present work evaluates the impact of implementing the traffic light labelling of foods in reducing deaths due to Noncommunicable Diseases (NCD). Econometric techniques of two-way effects panel data from 21 Ecuadorian provinces taken from official sources for the analysis period 2010-2019. For Ecuador, a favourable impact was found in the reduction of the NCD mortality rate, especially in the last three years; in 2017, it was reduced by 0.129%, in 2018 by 0.305%, and in 2019 by 0.289%. An implication of economic policy is the advertising regulation of products that may affect health, strengthening surveillance and sanctioning companies that fail to comply with the regulation.

Microbial agents obtained from tomato straw composting effectively promote tomato straw compost maturation and improve compost quality.

Appropriate management of agricultural organic waste (AOW) presents a significant obstacle in the endeavor to attain sustainable agricultural development. The proper management of AOW is a necessity for sustainable agricultural development. This can be done skillfully by incorporating microbial agents in the composting procedure. In this study, we isolated relevant bacteria strains from tomato straw AOW, which demonstrated efficient degradation of lignocellulose without any antagonistic effects in them. These strains were then combined to create a composite microbial agent called Zyco Shield (ZS). The performance of ZS was compared with a commercially effective microorganism (EM) and a control CK. The results indicate that the ZS treatment significantly prolonged the elevated temperature phase of the tomato straw pile, showing considerable degradation of lignocellulosic material. This substantial degradation did not happen in the EM and CK treatments. Moreover, there was a temperature rise of 4-6 â„ƒ in 2 days of thermophilic phase, which was not the case in the EM and CK treatments. Furthermore, the inoculation of ZS substantially enhanced the degradation of organic waste derived from tomato straw. This method increased the nutrient content of the resulting compost and elevated the enzymatic activity of lignocellulose-degrading enzymes, while reducing the urease enzyme activity within the pile. The concentrations of NH4+-N and NO3--N showed increases of (2.13% and 47.51%), (14.81% and 32.17%) respectively, which is again very different from the results of the EM and CK treatments. To some extent, the alterations observed in the microbial community and the abundance of functional microorganisms provide indirect evidence supporting the fact that the addition of ZS microbial agent facilitates the composting process of tomato straw. Moreover, we confirmed the degradation process of tomato straw through X-ray diffraction, Fourier infrared spectroscopy, and by scanning electron microscopy to analyze the role of ZS microbial inoculum composting. Consequently, reinoculation compost strains improves agricultural waste composting efficiency and enhances product quality.