IMPACT OF MICROWAVE-BASED DRYING ON SALMONELLA INACTIVATION KINETICS, ANTIOXIDANT PROPERTIES AND QUALITY OF RED PEPPER (CAPSICUM ANNUUM) By Natoavina Faliarizao A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of Food Science – Master of Science 2024 ABSTRACT The increasing number of outbreaks and recalls related to pathogen contamination of low- moisture foods, including spices, have raised concerns about their safety. The WHO has determined that red pepper poses the highest risk of Salmonella contamination. However, there is limited data on Salmonella thermal inactivation kinetics of red chili peppers. Microwave (MW) drying is an energy-efficient technique that can have a significant impact on various quality aspects of red pepper quality. This thesis investigated that the survival of S. Montevideo in red chili peppers decreased with increasing aw and treatment temperature over time (P < 0.05) and the moisture conditions played a key role in accurately describing Salmonella lethality using the log- linear Biglow model. In addition, modeling using non-isothermal temperature conditions has been shown to better describe the lethality of S. Montevideo than its counterpart. For MW drying, higher MW power (240W) resulted in lower Salmonella survival over time (P < 0.05). MW drying achieved similar quality retention to traditional drying technologies, including total phenolic, ABTS value and total capsaicinoids. Overall, the MW drying at 240W was observed to better retain the color properties and acceptable total phenolics and antioxidant capacity. This study is a first step in predicting Salmonella reduction in spices during commercial processing where temperature and air temperature change over time. This study is a first step for the development of an MW drying system to reduce Salmonella contamination levels in dried red chili peppers to reduce the use of traditional decontamination processes and improve the quality retention. ACKNOWLEDGEMENTS First, I want to thank God for providing me with the health, bravery, and strength I needed to finish my master's thesis. I am incredibly appreciative to my advisor, Dr. Kirk Dolan for his constant support and direction during my time at MSU. I could not have accomplished this goal without his mentoring. I am also appreciative of the dedication and important contribution made by my committee members, Drs. Teresa Bergholz and Jeffrey Swada, whose viewpoints have had a significant impact on my research abilities and critical thinking. We would especially like to thank Dr. Muhammad Siddiq for his help with data analysis and experimental design. . I would like to thank Michael James and Dr. Bradley Marks from the Department of Biosystems and Agricultural Engineering (BAE) at Michigan State University for allowing me to use the pilot plant for my research. I am grateful to the Fulbright Foreign Student Exchange for supporting my master’s program at Michigan State University. I am also grateful to my fellow Food Science and BAE students and lab mates, especially Yawei, Hazel, Dimple, Jun, De’Anthony, and Narindra, for their support and for making the lab a fun environment. Finally, I express my gratitude to my family and friends for their unwavering support and motivation to strive for excellence, even in the face of distance. My late brother Tsoa inspired me on this journey, and I dedicated this work to him. iii TABLE OF CONTENTS CHAPTER 1: INTRODUCTION ................................................................................................... 1 CHAPTER 2: LITERATURE REVIEW ........................................................................................ 3 2.1. Red chili peppers and its significance .................................................................................. 3 2.2. Global production and trade ................................................................................................. 4 2.3. Role of water activity (aw) in low-moisture food preservation ............................................ 6 2.4. Risks associated with consumption of contaminated spices and herbs ................................ 8 2.4.1. Foodborne pathogens commonly found in spices ......................................................... 8 2.4.2. Sources and contamination routes of foodborne pathogens .......................................... 9 2.5. Pathogen survival during thermal processing .....................................................................11 2.6. Mitigation strategies for foodborne pathogen in spices ..................................................... 13 2.7. Traditional drying methods for red chili peppers ............................................................... 17 2.8. Novel drying technologies of red chili peppers ................................................................. 18 2.9. Impact of drying on color, texture, and density ................................................................. 20 2.10. Effect of drying on antioxidant capacity of red chili peppers .......................................... 21 2.11. Microwave (MW) processing and equipment .................................................................. 22 2.12. Advantages and limitation of MW drying ........................................................................ 24 2.13. Mechanism of pathogen inactivation during MW drying ................................................ 26 CHAPTER 3: MODELING SALMONELLA INACTIVATION OF CHILI PEPPERS DURING MICROWAVE DRYING ............................................................................................ 27 3.1. Introduction ........................................................................................................................ 27 3.2. Materials and Methods ....................................................................................................... 29 3.2.1. Overview of the study.................................................................................................. 29 3.2.2. Red chili peppers ......................................................................................................... 30 3.2.3. Inoculum preparation and inoculation procedures ...................................................... 30 3.2.4. Equilibration of samples at target water activity ......................................................... 32 3.2.5. Heat treatment procedure for thermal inactivation kinetic data collection ................. 33 3.2.6. MW drying .................................................................................................................. 34 3.2.7. Survivor recovery and enumeration ............................................................................ 34 3.2.8. Mathematical modelling .............................................................................................. 35 3.2.9. Model validation .......................................................................................................... 39 3.2.10. Statistical analyses ..................................................................................................... 40 3.3. Results and Discussion ....................................................................................................... 41 3.3.1. Initial population of S. Montevideo ............................................................................. 41 3.3.2. Effect of water activity on Salmonella thermal resistance .......................................... 41 3.3.3. Mathematical modeling for in-container thermal treatments ...................................... 44 3.3.4. Residual analysis ......................................................................................................... 51 3.3.5. Validation of estimated model parameters in MW drying .......................................... 53 3.3.6. Significance of considering moisture condition in pathogen inactivation models ...... 61 3.4. Summary and Recommendations ....................................................................................... 62 iv CHAPTER 4: IMPACT OF SPECIFIC MICROWAVE POWER INPUT ON COLOR, ANTIOXIDANT ACTIVITY AND PHYSICOCHEMICAL PROPERTIES OF RED CHILI PEPPERS ........................................................................................................ 64 4.1. Introduction ........................................................................................................................ 64 4.2. Materials and Methods ....................................................................................................... 65 4.2.1. Materials ...................................................................................................................... 65 4.2.2. Chili pepper drying ...................................................................................................... 66 4.2.3. Moisture content and drying kinetics .......................................................................... 68 4.2.4. Color evaluation of chili peppers ................................................................................. 69 4.2.5. ASTA color value ........................................................................................................ 70 4.2.6. Texture (hardness) measurement ................................................................................. 70 4.2.7. Loose and packed bulk density measurement ............................................................. 70 4.2.8. pH ................................................................................................................................ 71 4.2.9. Total phenolics ............................................................................................................ 71 4.2.10. Antioxidant properties ............................................................................................... 71 4.2.11. Capsaicinoids ............................................................................................................. 74 4.2.12. Statistical analyses ..................................................................................................... 74 4.3. Results and Discussion ....................................................................................................... 75 4.3.1. Moisture content and drying kinetics .......................................................................... 75 4.3.2. Color quality ................................................................................................................ 78 4.3.3. Texture (hardness) ....................................................................................................... 81 4.3.4. Loose and packed densities ......................................................................................... 82 4.3.5. pH ................................................................................................................................ 83 4.3.6. Total phenolic content (TPC) ...................................................................................... 84 4.3.7. Antioxidant properties ................................................................................................. 85 4.3.8. Capsaicinoids content .................................................................................................. 90 4.4. Summary and Recommendations ....................................................................................... 91 BIBLIOGRAPHY ......................................................................................................................... 92 APPENDIX ..................................................................................................................................115 v CHAPTER 1: INTRODUCTION Spices and herbs are commercially important due to their global production, trade, economic importance and world-wide utilization. Red chili peppers are a spice with great culinary importance and health benefits. According to the FAO, total global production of dry chilies was 4.9 million metric tons (MMT) in 2022 (FAO, 2023). However, there is a heightened concern for the safety of low-moisture foods as the number of outbreaks and recalls related to Salmonella contamination in low-moisture foods, including spices, has been increasing. Although spices, such as red chili peppers (Capsicum spp.), have antioxidant and antimicrobial properties, the World Health Organization ranked red chili peppers as the spice with the highest risk of Salmonella contamination. In addition, rather limited data are available on Salmonella inactivation in red chili peppers during the drying process. Microwave (MW) drying is a promising technique that can have a significant impact on various aspects of red pepper quality. Studies have shown that drying red peppers with microwaves can improve its bioactive properties, antioxidant capacity, and phenolic compounds (Ahmed, 2024). In addition, MW drying has been found to improve the antioxidant and antimicrobial activity of peppers, which is due to the preservation of important compounds during the drying process (Salamatullah et al., 2022). Furthermore, the use of microwave drying has been associated with accelerated drying times and improved color properties of red peppers, indicating the efficiency in maintaining the quality characteristics of the product (Won et al., 2014). This is consistent with findings that microwave vacuum drying shortens drying time while preserving the color of dried peppers (Maurya et al., 2018). In addition, MW drying has been shown to significantly increase the phenolic content of peppers compared to other drying methods, highlighting its potential to increase the nutritional value of red peppers (Özcan and Uslu, 2022). 1 However, there is limited data on Salmonella inactivation in red chili peppers during the drying process. This study aims to evaluate Salmonella lethality during MW drying of fresh chili pepper slices and evaluate quality, antioxidant and physicochemical properties of the resulting dried product. The flowchart in Appendix Figure A.1 shows the overall study design for research undertaken as a part of this thesis. The analytical work consists of two main objectives: 1) processing and quality assessment (physical and chemical properties influenced by drying technologies) and 2) microbial quality assessment (Salmonella thermal inactivation kinetics and modeling kinetics). This study demonstrated the importance of MW power level for drying red chili peppers and its impact on Salmonella inactivation. 2 CHAPTER 2: LITERATURE REVIEW 2.1. Red chili peppers and its significance Spices and herbs are of vital importance due to their global production, trade, and economic significance. Spices are defined as aromatic vegetable substances, whether whole, broken, or ground, which are primarily used for flavoring rather than nutritional value in food. The dried red fruit of any variety of Capsicum frutescens L or Capsicum annuum L is referred to as red pepper capsicum or cayenne, respectively. Its color ranges from red to brown-red, and its pungency is sharp. The main active component that gives this product its pungency is capsaicin. The pungency rating (Scoville units), moisture, and total and acid insoluble ash are used to assess the quality characteristics (FDA, 1980). Red chili peppers (Capsicum annuum) have been the subject of numerous studies focusing on their antioxidant properties, phenolic profiles, and vitamin C content (Deepa et al., 2007; Kim et al., 2014). Red chili peppers contain several bioactive compounds including capsaicin, dihydrocapsaicin, nordihydrocapsaicin, homocapsaicin, and homodihydrocapsaicin, all of which have potential health benefits (Lu et al., 2017). Zheng et al. (2016) reviewed the potential anticarcinogenic properties of red chili peppers, particularly for lung cancer, breast cancer, and gastric cancer. A study by Arimboor et al. (2015) focused on extracting and enhancing bioactive compounds from red chili peppers to improve their bioavailability and stability. Exploring the potential inhibitory effects of natural anti-browning agents on polyphenol oxidase from red chili peppers has also been investigated, highlighting the diverse applications of these bioactive compounds (Hoo et al., 2022; Lim and Wong, 2019). Overall, red chili peppers are a spice with great culinary importance and health benefits. In addition, they have numerous bioactive properties and can be used as inhibitors for the processing of organic foods. 3 The production of red chili peppers is affected by multiple agronomic factors, such as potassium fertilizer, insecticides, fungicides, and other agronomic practices (Purwasih et al., 2020). Red chili peppers have little price volatility, and price changes are impacted by the degree of volatility from the day before (Kusnaman et al., 2023). Different chili pepper cultivars have been examined for their antioxidant profiles, revealing cultivar-dependent variability in bioactive compound levels (Ramírez-Aragón et al., 2022). Concerning functional quality, treatments with blue light-emitting diodes (LEDs) have been shown to boost capsaicinoids production and color development in chili peppers (Gangadhar et al., 2012). To ensure consistent quality, appropriate pre- and post-harvest good agricultural practices must be employed. Kirchner et al. (2021) reported that numerous factors such as the type of spice, environmental conditions, and local growing practices can influence the risk of contamination. 2.2. Global production and trade According to the FAO data, the total world production of dry chilies was 4.9 million metric tons (MMT) in 2022, as shown in Figure 2.1. In about two decades since 2001, the global production of dry chilies showed an increase of 96% when comparing to 2.5 MMT in the year 2001 (FAO, 2023). The global production of dry chilies has shown significantly higher growth since 2011 than that in the preceding decade (2001-2011). These production trends clearly demonstrate the economic significance of this important spice crop. The total area harvested globally for dry chilies was 1.65 million hectares in 2022, which was lower than 1.73 million hectares in 2001. The total area harvested since 2001 has shown mixed trends and has remained fairly flat, ranging from the lowest of 1.56 million hectares to the highest of 1.82 million hectares in 2020 and 2016/2017, respectively. These trends for area harvested show that increases in dry 4 chili production have been realized primarily as a result of plant breeding and genetic interventions and improvements in agronomic practices. Figure 2.1. Dry chili word production (bars) and area harvested (lines) from 2001 to 2022. Table 2.1 shows top-10 dry chili producing, exporting and importing countries. India, with 1,874,000 metric tons, was the top dry chilies producing country in 2022, representing 38.2% of the total world production. Bangladesh was the only other country with greater than 10% share of the total world production. Together, India and Bangladesh accounted for greater than 50% of the global production of dry chilies. India was also the top-most exported of dry chilies, with 406,063 metric tons in 2022, which was equivalent to 41.5% of total global exports of red chilies (Table 2.1). China was also a major dry chilies exporting country, with 248,477 metric tons that accounted for 25.4% of total global exports. The rest of countries in the top-10 list exported between 0.8% and 8.5% of total global exports. Among dry chili importers, the U.S.A. led all countries with 176,351 metric tons or 17.5% of global imports share, followed by China (135,485 metric tones, 5 13.4% share). The remaining eight countries in the list imported between 2.5% and 8.2% of total global imports (Table 2.1). Table 2.1. Top-10 dry chilies producing, exporting and importing countries in 2022. Producers Metric tons %1 Exporters Metric tons %1 Importers Metric tons %1 1,874,000 38.2 India 176,351 17.5 India 12.7 China 624,825 135,485 13.4 Bangladesh 6.7 Spain 329,378 8.2 83,149 Ethiopia 6.7 Mexico 327,384 7.0 70,341 Thailand 6.5 Peru 318,063 5.1 51,458 China 2.9 Tunisia 144,160 4.8 48,166 Pakistan 4.7 47,704 2.9 Myanmar 142,459 Myanmar 4.4 44,035 2.7 Uzbekistan 133,412 Benin 3.3 33,287 2.7 Thailand Côte d'Ivoire 131,083 Ghana 2.5 25,434 2.2 Netherlands 108,170 1Percentage of world total Source: created from the database of FAO (2023) 41.5 U.S.A. 25.4 China 8.5 Thailand 4.5 Spain 4.4 Malaysia 1.6 Indonesia 1.4 Sri Lanka 1.2 Mexico 1.0 Bangladesh 0.8 Germany 406,063 248,477 82,894 44,022 43,467 15,590 13,230 11,775 9,579 8,274 2.3. Role of water activity (aw) in low-moisture food preservation In most foods, especially fruits and vegetables, water is the most prevalent component. Water activity (aw) is vital in food science and microbiology since it specifically influences the stability, shelf life, and safety of different food products (Figure 2.2). Unlike moisture content alone, aw plays a key part in determining the microbial development, texture, flavor, chemical reactivity, and enzymatic activity of foods (Fontana, 2001). In simple terms, aw implies the availability of free water within the system for chemical and biological reactions (Fontana, 2001). This dimensionless parameter ranges from 0 to 1, where 0 represents dry conditions and 1 represents clean water under standard conditions (Rahman and Sablani, 2002). Controlling aw is critical to prevent microbial growth and enzymatic reactions, subsequently ensuring the safety and shelf life of food (Fontana, 2001). To determine aw, methods such as dew point technique, electronic sensors or other advanced approaches that assess the energy state of water within the system are utilized (Fontana, 6 2001; Rahman and Sablani, 2002). This measure is important within the field of food preservation because it can be used to optimize the shelf life and quality of different foods by controlling aw (Fontana, 2001). The aw in each food is measured by the vapor pressure of the water within the product (P) compared to the vapor pressure of pure (P0) water at the same temperature. This relationship is expressed by the following equation: (3.1) Figure 2.2 shows the relationship between aw and the pace of deteriorative reactions in food. To prevent microbiological decay, it is significant to lower aw below 0.7. However, even though microbial deterioration is averted below aw = 0.7, achieving successful preservation of a food product through dehydration requires reducing aw to 0.3 to prevent other deteriorative reactions (Toledo et al., 2018). Dehydration of food can be used to reduce weight or volume and preserve a variety of food products. However, dehydration alone might not inactivate pathogens, and additional preservation method(s) may be necessary. Although live microorganisms can no longer grow in properly dehydrated products, they can grow and cause illness in humans when used as ingredients in finished products. For instance, Salmonella found in spices used to prepare sausages and other raw products led to a massive recall due to safety concerns (Gieraltowski et al., 2012). To ensure safety, food products that may contain pathogens must be appropriately treated before drying to eliminate pathogenic microorganisms (Toledo et al., 2018). 7 0wPaERHP== Figure 2.2. Relationship between aw and deteriorative effects on foods. Source: Labuza et al. (1972) 2.4. Risks associated with consumption of contaminated spices and herbs 2.4.1. Foodborne pathogens commonly found in spices Spices are known to carry a risk to human health due to potential contamination during various stages of production by various pathogens including gram-negative bacteria such as Salmonella, E. coli and gram-positive bacteria such as C. perfringens, and B. cereus (Mathot et al., 2020). While the low-moisture content of dried spices can inhibit the growth of most non-spore- forming microorganisms, Salmonella is able to survive in such conditions, which makes the control or inactivation of pathogens crucial (Erdoğdu and Ekiz, 2011). Salmonella, a pathogenic gram-negative bacterium, is known for its ability to survive in dry environments including spices (György et al., 2021). Salmonella serotypes typically cause gastroenteritis, primarily affecting gastro-intestinal infections; whereas enteric fever can be caused by Typhi and Paratyphi serotypes, which can also impact other tissues and organs (Crump and Mintz, 2010). According to a risk assessment study by the World Health Organization (WHO), 8 unprocessed red chili peppers have the highest risk of Salmonella contamination in spices and herbs (WHO, 2022). B. cereus, commonly found in raw materials such as vegetables, starch, and spices, can cause outbreaks when it grows in food due to its exponential growth potential (Mathot et al., 2020). B. cereus can produce toxins, including heat-stable emetic toxin in cereal-based foods such as cakes and pasta, and diarrheagenic toxin during gastrointestinal growth. Foods that have been inadequately processed or stored, including low-moisture foods such as spices, can typically harbor B. cereus spores. (Beuchat et al., 2013). Similarly, C. perfringens present in the natural environment, have been linked to foodborne outbreaks (Mathot et al., 2020). C. perfringens spores are resistant to cooking temperatures and can produce enterotoxin when they sporulate in the gastrointestinal (GI) tract. They are found in dried herbs and spices and potentially cause an infectious dose when added to cooked meat dishes during refrigeration or storage (Beuchat et al., 2013). For red chili peppers in particular, ground and crushed product forms are used as an ingredient in meat products and cheese, increasing the risk of food poisoning. Furthermore, spices can also be contaminated with mycotoxins, which can pose serious health risks to consumers (Do et al., 2015; Nguegwouo et al., 2018). The presence of mycotoxins in medicinal herbs and spices can lead to significant health problems despite their potential benefits (Do et al., 2015). Therefore, effective decontamination methods and stringent quality control measures are needed to ensure food safety (Erdoğdu and Ekiz, 2011; Altay et al., 2018). 2.4.2. Sources and contamination routes of foodborne pathogens Spices can be contaminated at various pre- and post-harvest stages, including field growth, harvest, processing, and distribution, leading to potential health risks. Soil and plant microflora can introduce bacteria such as Salmonella, B. cereus, and C. perfringens to spices (Fiedler et al., 9 2019). Additionally, the use of manure as organic fertilizer may further contribute to pathogen introduction (Fiedler et al., 2019). The presence of animal and insect debris in spices can also serve as vectors of pathogens, indicating poor hygienic and quality control practices (Székács et al., 2018). Inadequate drying and storage conditions may result in mold growth, mycotoxin production, and microbial survival and proliferation, all of which can pose a myriad of health hazards (Tajkarimi et al., 2010; Pickova et al., 2020). Furthermore, processing (not done using good manufacturing practices or GMPs) and unsafe distribution practices can lead to cross- contamination and adulteration, introducing pathogens and reducing traceability (Gottardi et al., 2016). The microbiological quality of spices is a significant food safety concern, with studies reporting the presence of pathogens and development of high resistance to antimicrobials in retail market spices (Costa et al., 2020; Bello and Bello, 2022). The occurrence of mycotoxins in spices further emphasizes the need for monitoring and prevention strategies to ensure food safety (Iha and Trucksess, 2019). Moreover, the survival of bacterial spores during processing and storage highlights the challenges in maintaining the safe microbiological quality of spices (Witkowska et al., 2011). Although spices possess antimicrobial properties, spice-based products can harbor foodborne pathogens. The occurrence and antimicrobial resistance of bacteria in spice market have been documented, indicating that spices are potential sources of Salmonella-related foodborne diseases (Zweifel and Stephan, 2012). Soil conditions, irrigation water, and contact with improperly composted manure/feces have been identified as potential preharvest sources of foodborne pathogens, emphasizing the need to consider the entire supply chain in ensuring food safety (Williams et al., 2015). Additionally, the survival rate of virulent coagulase-negative Staphylococci in pasteurized spiced beverages has been studied, highlighting the importance of 10 understanding the survival dynamics of specific pathogens in spiced food products (Fowoyo, 2020). Climatic factors, such as temperature and precipitation, have been identified as influential in affecting the prevalence of foodborne pathogens in the environment, including on fruit and vegetable farms (Strawn et al., 2013). Moreover, the presence of certain minerals, such as calcium and magnesium in spices, has been found to stimulate the growth of foodborne pathogenic microorganisms, e.g., B. cereus and C. perfringens (García-Galdeano et al., 2021). Furthermore, the microbiological quality of retail spices has been highlighted as a concern, with spices rarely being free from microbial contamination, except those that undergo industrial processing (Costa et al., 2020). Unsanitary processing conditions, disregard for workers’ hygiene and sub-optimal packaging and storage are frequently observed in many developing countries, especially at small- scale farms and facilities. 2.5. Pathogen survival during thermal processing Factors influencing foodborne pathogen survival in spices are multifaceted and encompass various aspects of proliferation and growth. Spices have been recognized for their potential as antimicrobial agents against foodborne and human pathogens (Liu et al., 2017). The antimicrobial properties of spices, such as cinnamon, have been attributed to their ability to act against foodborne pathogens and spoilage bacteria, thereby increasing the safety and shelf life of food products (Nabavi et al., 2015). However, a number of factors, such as the type of organism, the type of produce, the climatic conditions in the field, and the physiological state of the plant and pathogen, affect the survival and growth of pathogens in spices (Alegbeleye et al., 2018). Additionally, the survival of microorganisms in spices is attributed to their high resistance to stress conditions, including pH variations, heat, and low aw (György et al., 2021). 11 The survival of foodborne pathogens in spices during thermal processing is influenced by numerous factors. Low aw in dry foods, including spices, poses a challenge in eliminating pathogens without compromising quality (Beuchat et al., 2013). Additionally, the resistance of Salmonella to heat increases with decreasing moisture, emphasizing the impact of aw on pathogen survival (Podolak et al., 2010). The presence of antimicrobial-resistant Salmonella strains in spice shipments highlights the potential risk associated with these products (Van Doren et al., 2013). Additionally, Van Doren et al. (2013) reported that the prevalence of Salmonella was higher in shipments of ground/cracked chili peppers and coriander than in shipments of the same whole spices. Resistance to desiccation stress and the capacity to evolve sophisticated survival and persistence strategies are two additional factors that impact the survival and persistence of pathogens in spices (Chen and Meng, 2021; Zweifel and Stephan, 2012). Moreover, the presence of bacterial spores in spices, which can withstand thermal treatments, poses a risk for non- thermally processed food in which they are used as ingredients, signifying the need for effective pathogen inactivation methods during processing (Mathot et al., 2020). In addition, the effect of combined hyperosmotic and acid shock conditions on the proteome of L. monocytogenes sheds light on the complex stress responses of pathogens that may impact their ability to survive heat processing (Zhang et al., 2019). The occurrence of bacteria, including E. coli and Salmonella spp., in retail market spices underscores the potential for contamination and the need for effective thermal processing methods to ensure food safety (Costa et al., 2020). Good agricultural, harvesting, and manufacturing practices are essential to ensure the safety of spices (Kirchner et al., 2021). The temperature and relative humidity conditions during the storage of processed food are critical in preventing spore 12 germination and growth, emphasizing the importance of good manufacturing practices and validated treatment methods (Mathot et al., 2020). The use of treatments such as irradiation, ethylene oxide, and steam treatments has been effective in controlling pathogens in spices (Sádecká, 2007; Waje et al., 2008a,b). However, the impact of processes such as ethylene oxide treatment on spice quality and sensory integrity during pathogen inactivation underscores the need to ensure effective pathogen reduction while preserving the sensory attributes of spices (Duncan et al., 2017) (Table 2.2). The persistence of foodborne pathogens in spices when subjected to heat treatment is determined by numerous factors, such as aw, antimicrobial resistance, desiccation stress, and the intricate stress responses unveiled by the pathogen. Appropriate thermal processing methods are essential to mitigate the risk of pathogen survival while preserving the quality and safety of spices. 2.6. Mitigation strategies for foodborne pathogen in spices An overview of the thermal processing technologies used to decontaminate spices is shown in Table 2.2. Food processing technologies such as thermal processing play a crucial role in the preservation and enhancement of spices. The use of thermal processing of spices has shown promise in potentiating the antioxidant content and health-promoting properties of spices (Hester et al., 2019). Thermal processing, such as drying, not only preserves the product but it also has a positive impact on the quality of spices (Calín-Sánchez et al., 2020). However, it is essential to consider the impact of thermal decontamination processes on the sensory properties and quality of herbs and spices, as particular care needs to be taken to avoid severe effects on these aspects (Eliasson et al., 2015). 13 For microbial decontamination of spices, studies have compared different thermal technologies such as infrared and microwave (MW) heating, highlighting the need for alternative methods to ensure microbial safety (Eliasson et al., 2015). Furthermore, the use of ultraviolet (UV) and far-infrared radiation for decontamination of spices has been explored, suggesting the potential for alternative to thermal decontamination methods (Erdoğdu and Ekiz, 2011). Low-moisture content in spices presents a challenge for the thermal process control, as the time required to achieve the desired thermal inactivation of microorganisms increases sharply with reduced moisture content and aw (Villa-Rojas et al., 2013). The heat treatment applied during spice processing may lead to the degradation of certain beneficial bioactive compounds and the formation of others, affecting the overall quality of the spices (Rivera-Pérez and Romero-González, 2021). Vacuum-assisted steam pasteurization has been proposed to improve the safety and quality of low aw products, although the specific process parameters associated with inactivation on whole spices were not well described (Newkirk et al., 2018). Shah et al. (2017) investigated a vacuum-steam pasteurization technology to inactivate Salmonella Enteritidis PT30 on whole peppercorns, which resulted in the inactivation of 6.1 log10 CFU/g of Salmonella. The authors did not examine changes in sensory properties and quality parameters of peppercorns. 14 Table 2.2. Overview of advantages and limitations of thermal processing of spices. Thermal process Steam heating Log reduction (log10 CFU/g) 5-log reduction of Effectively utilized Disadvantages Advantages for decontamination in the Modified Atmosphere Packaging (MAP) industries. Elevated energy usage, intricate machinery, Modifications to color, perception, and decrease in volatile compounds. Salmonella spp., L. monocytogenes, E. coli O157 in black peppercorns 6.1-log reduction of S. Enteritidis PT30 3- to 4-log reduction Salmonella after 4 to 6 hours of drying and up to 7-log reduction after 24 hours 3.2-log reduction of bacterial spores in paprika powder 1-log reduction of yeast and mold counts for dried turmeric powder Salmonella and 0.7-log reduction of E. faecium at 45 seconds 4.8-log reduction of Salmonella and 2.7-log reduction of E. faecium at 55 seconds. Greater than 6.5-log reduction at 65 seconds Greater that 3.3–5.5- log reduction of E. faecium References Zhou et al. (2019) ; Shah et al. (2017) Gradl et al. (2015) Ban and Kang (2016); Behera et al. (2017); Jeevitha et al. (2016); Eliasson et al. (2015) Verma et al. (2021) Mostafavi et al. (2012) ; Schottroff et al. (2021) Xie (2022) ; Chen et al. (2021) ; ASTA (2017) Drying Less expensive than alternative methods in terms of technology. Ensuring sufficient inactivation of the pathogen is a time- consuming procedure. Microwave heating Radio frequency (RF) heating Compared to Uneven cooking and the formation of cold spots After 60 minutes, significant decrease in moisture content and total phenolics in pepper and cumin. A reduction in DPPH. dependent dielectric characteristics of food can have an impact on the heating uniformity and processing time. traditional heat treatments, solid food preserves more vitamins, minerals, and aromatic compounds. Lowered the microbial load to a standard level. Uniform and rapid heating of semi-solid or solid samples. Reduced microbial load to standard levels without significantly altering moisture content or product quality Gamma irradiation More efficient than Lack of consumer thermal treatment in terms of bacteria decontamination. Minimal effects on quality. acceptance as a result of fear surrounding nuclear technologies. The temperature- 1-log reduction of Fumigation Highly effective for whole spices and seeds Extended treatment 5-log reduction of duration Potential for chemical residues to produce carcinogenic compounds Additional step to eliminate the sanitizing agent Salmonella in whole black peppercorn treated by ethylene oxide fumigation at 53°C and RH 50% 15 Previous research on temperature-dependent nutritional content and antioxidant activities of spices have demonstrated the impact of heat treatment on the properties of spices, indicating the need for careful temperature control during processing to retain the beneficial compounds in spices (Manga et al., 2020; Zagórska et al., 2023). Jeong and Kang (2014) studied the dielectric properties of red and black pepper powders to maximize moisture content for radiofrequency (RF) heating. They found that the heating rate for red and black pepper increased with increasing moisture content to 19.1% and 17.2%, respectively, but decreased dramatically at higher moisture contents. The time required to reduce pathogens by 7 log10 CFU/g was inversely correlated with the higher heating rate. The color and concentration of volatile flavor components in powdered red and black pepper with different moisture content were not affected by RF heating. Cryogenic grinding has also been identified as a technique for preserving volatile content in spices, highlighting the importance of temperature reduction to preserve the aroma and quality of spices during processing (Saxena et al., 2018). Song et al. (2014) used a 27.12 MHz RF heating unit to measure the degree of thermal inactivation after inoculation of black and red peppers with E. coli O157:H7 and S. Typhimurium. Application of black pepper heated for 50 seconds to Salmonella and E. coli resulted in an average log reduction of 2.80 and 4.29 log10 CFU/g, respectively. For the two pathogens, heating red peppers with RF for 40 seconds inactivated the bacteria by 3.38 log10 CFU/g and more than 5 log10 CFU/g, respectively. Gradl et al. (2015) established a connection between the aw of ginger during drying and the decline in Salmonella population. Once the aw fell below a certain value, Salmonella populations experienced little or no decline, but declined rapidly when aw was above 0.4. A slow drying rate was found to kill more Salmonella than a fast-drying rate when drying was performed at 51 °C (124 °F) and 60 °C (140 °F). Duncan et al. (2017) examined the effects of three Salmonella 16 inactivation techniques on spices to determine any damage to organoleptic properties. Many studies have generally shown the importance of considering the effects on the flavor and aroma of the spice as well as the quality parameters of the spice when developing successful intervention strategies. 2.7. Traditional drying methods for red chili peppers The drying process is pivotal for reducing moisture content, extending shelf life, and preserving sensory and nutritional attributes of chilies (Arifin et al., 2018). Extensive research has focused on traditional drying techniques for red chili peppers, given their importance in maintaining the products quality and bioactive compounds including sun-drying, convective hot- air drying, and infrared (IR) drying (Magied et al., 2014; Kim et al., 2017; Tunde-Akintunde, 2010). IR drying is a method suitable for employment in small-scale processing facilities. Radiative energy is exchanged from the heating component to the product surface without warming the encompassing air. The level of IR radiation can be balanced through the voltage controller, whereas intermittent IR drying can be executed by turning the timer relay handle (Rahaman, 2007). Renate et al. (2022) demonstrated that combining sun-drying and fanning (forced air) produced vibrant red chili flakes, and artificial drying with a forced-air tray dryer, along with sun- drying, mitigated color, and vitamin C changes in the flakes. Naemsai et al. (2019) reported that a large-scale solar-assisted heat pump dryer reduced the drying time for 300 kg of chili peppers from 5 to 3 days. Blanching, as a pretreatment method for red chili pepper drying, has also been studied (Owusu-Kwarteng et al., 2017). Marwati et al. (2021) found that a cabinet dryer yielded the lowest moisture content compared to sun-drying under shade and without shade. Tunde-Akintunde (2010) reported higher nutritional content in solar-dried peppers, while oven-dried samples had the lowest 17 vitamin A and C contents. It was also observed that pretreatment of soaking peppers in 70° Brix sucrose solution for 5 hours significantly reduced the drying time (by 33.3% to 41.7%) as compared to other pretreatments or untreated peppers. Drying at different temperatures affects chili pepper color, and mathematical modeling has been used to understand drying kinetics (Andrade et al., 2019). Vitamin B6 degradation during drying emphasizes the need to optimize methods to minimize nutrient loss (Arifin and Djaeni, 2017). The drying process also influences capsaicinoid content, with a high linear correlation between fresh and dried red peppers, indicating the potential impact of drying on compound concentration (Ryu et al., 2017). Optimal drying performance for chili peppers was observed at 70 °C, while 35 °C processing favored the retention of bioactive compounds such as capsaicin and vitamin C (Ajuebor et al., 2022). Overall, traditional drying methods for red chili peppers are crucial for preserving quality, bioactive compounds, and nutritional attributes. The choice of drying method, temperature, and pretreatments significantly affects drying kinetics, color, bioactive compound content, and nutrient retention. Further research and process optimization are essential to ensure the preservation of the quality and bioactive compounds of red chili peppers. 2.8. Novel drying technologies of red chili peppers A pivotal step that has a considerable impact on the safety and quality of spices is drying them to lower their aw significantly. Wei et al. (2017) explored innovative drying procedures, which punctuate the significance of conserving the quality of spices and herbs using innovative methods. The significance of processing technology in conserving sensitive qualities was underscored by Saxena et al. (2018), who found cryogenic grinding as a technique for better aroma retention and quality in Indian spices. Schweiggert et al. (2005) examined the possibility of heat treatment in conserving the quality of spice products by examining peroxidase, polyphenol oxidase, and 18 lipoxygenase enzymes activities in paprika and chili powder following thermal treatment, which was effective in inactivating these enzymes. The significance of safety through applicable processing and storage is emphasized in determining aflatoxin levels in organic spices and herbs by Tosun and Arslan (2013). Beyond that, Bourdoux et al. (2016) reviewed drying technologies for microbial safety in fruits and vegetables, emphasizing the potential of arising technologies for bacteria and virus inactivation during drying. For red chili peppers, various technologies aim to optimize the drying process and save important quality attributes. Osmo-sonication pretreatment, developed by Majumder et al. (2023), expedited air dehumidification, enhancing the drying process. The study of Arifin and Djaeni (2018) on the thermal degradation kinetics of capsaicin during drying emphasized the understanding of bioactive compound behavior for applicable temperature and method selection. Kim et al. (2017) explored combined effect of chlorine dioxide and hot-air drying resulting in more than 4.5-log reduction of B. cereus spores in red chili peppers and highlighting the potential of combined treatments for enhancing safety. Zhao et al. (2013) investigated the impact of osmosis pretreatment on drying characteristics, offering insight into drying behavior and quality attributes. Ajuebor et al. (2022) worked on drying process optimization and contributed to understanding of chili pepper drying behavior and quality attribute optimization. Modern drying technologies, including osmo-sonication pretreatment, thermal degradation kinetics analysis, and combined treatments, are improving red chili pepper drying methods, enhancing efficiency and product quality. These studies emphasized the need for applicable techniques to retain flavor, aroma, and bioactive compounds, underlining the critical role of processing methods in safety and quality. Therefore, selecting drying and processing techniques is pivotal for preserving sensory attributes and safety, contributing to high-quality spice products. In recent years, food drying technologies 19 have been shifting towards improved drying techniques that offer enhanced efficiency, better quality, and reduced energy consumption. Examples of such technologies include freeze-drying, vacuum drying, and MW drying. 2.9. Impact of drying on color, texture, and density The variable effects that drying methods have on the color, density, and texture of red chili peppers has been the subject of much investigation. Color, rehydration ratio, and texture (hardness) are just a few of the physical features that Magied and Ali (2017) investigated and found to be significantly impacted by both conventional drying at 60 °C and sun drying at 45 °C. Rybak et al. (2022) provided insights into how different drying techniques affect chili pepper texture and color, by studying the effects of thermal and non-thermal technologies on red bell pepper drying kinetics. Furthermore, to elucidate the relationship between drying techniques and color preservation, Andrade et al. (2019) investigated the drying kinetics of red and yellow chili peppers at different temperatures by mathematical modeling of the process parameters. Drying methods are known to alter not only the physical attributes of red chili peppers but also their bioactive components (Figure 2.3). Díaz-Maroto et al. (2002), investigated the effect of different drying techniques on aromatic profile of bay leaves and concluded that air- and oven- drying produce comparable outcomes in terms of maintaining volatiles, whereas freeze-drying reduced the overall aroma but increases the concentration of some constituents such as eugenol. Examining the quality of red chili peppers under different drying methods, Magied et al. (2014) discovered that the drying procedure affected the bioactive content of the peppers. It has been demonstrated that capsaicin, a bioactive component of red chili peppers, is important from a health perspective and may potentially offer some cancer-prevention benefits (Kaefer and Milner, 2008). 20 Figure 2.3. Impact of drying methods on the preservation of bioactive compounds in chili peppers. Source: Montoya-Ballesteros et al. (2014) Gómez-García and Ochoa-Alejo (2013) conducted a comprehensive study of carotenoid biosynthesis in chili peppers, providing insight into how drying techniques impact the carotenoid concentration and ultimately determine the red color of the plant. By utilizing diverse drying and milling techniques to maintain an optimum color of the paprika, Topuz and Özdemir (2003) highlighted the significance of drying techniques in hue preservation. In summary, physical characteristics, bioactive substances, and carotenoid content are all involved in the complex mechanism of how drying techniques affect the color, texture, and density of red chili peppers. Maintaining the quality of dried red chili peppers requires an understanding of this influence. 2.10. Effect of drying on antioxidant capacity of red chili peppers The antioxidant properties of food products are important from a health beneficial perspective. A variety of factors influence the effect of drying on antioxidant capacity of red chili 21 peppers. Zhou et al. (2016) indicated that heat-air and infrared drying techniques cause a decrease in capsaicinoids and total phenolic compounds, which alters the antioxidant ability. Additionally, the drying process increased ascorbic acid composition while decreased total phenolic content of red chili peppers, hence lowering its overall antioxidant capacity (Chamikara et al., 2016). According to Chen et al. (2022), oxygen, light, temperature, and moisture are known to deteriorate carotenoids, phenolic compounds, and other antioxidants during storage. Ramírez-Aragón et al. (2022) indicated that cultivar specificity potentially influenced the antioxidant profile and capsaicin concentration of various chili pepper varieties. Moreover, the pungency of chili peppers is attributed to varying quantities of capsaicinoid present in various species exhibiting the influence of cultivar on antioxidant capacity (Qanytah et al., 2022). It is noteworthy that red chili peppers contain antioxidant components potentially able to block polyphenol oxidase activity in fruits and vegetables contributing to prevent browning (Hoo et al., 2022). Furthermore, the bioactive compounds in red chilies, including capsaicin and ascorbic acid, are impacted by drying parameters such as temperature and drying time. This highlighted the key role that drying played in preserving bioactive compounds and, as a result, the antioxidant potential of red chili peppers (Ajuebor et al., 2022). Overall, antioxidant properties of red chili peppers are affected by an array of factors particularly cultivar, drying method, storage environment, and bioactive components. 2.11. Microwave (MW) processing and equipment MW-based processing has received significant attention due to its potential in various fields such as food processing, chemistry, materials science, and metallurgical processes. The advantages of MW processing include rapid and non-contact heating, selective and volumetric heating, quick starting and stopping, high safety, and environmental friendliness (Lu et al., 2021). MW heating 22 has been shown to significantly reduce deteriorative reactions and improve product quality or material properties, making it an efficient and rapid heating source (Kappe, 2013). In contrast to thermal radiation, the heating effect of MWs largely depends on the chemical composition of the irradiated material. MWs interact primarily with polar molecules and charged particles. In food, the most important interaction occurs with water molecules. This is essentially a dielectric heating phenomenon (Figure 2.4). This is a result of the dielectric phenomenon of MW heating in the material as MWs penetrate the material and generate heat (Berk, 2018). In the context of food processing, MW heating is used in various process flows, although it does not yet occupy a significant place in industrial applications (Vadivambal and Jayas, 2008). Intermittent microwave vacuum drying (IMVD) is an updated technique for highly efficient processing of fruits such as lychee (Cao et al., 2019). In addition, MW energy is often used in the processing of starchy foods such as potato starch and gravy (Ma et al., 2015). In the field of chemistry, the importance of efficient mixing and internal temperature control in MW-heated reactions has been highlighted (Herrero et al., 2007). Furthermore, MW heating has been used for the synthesis of complex functional oxides, demonstrating their versatility in chemical processes (Prado-Gonjal et al., 2015). The influence of MW heating on the granule state and thermal properties of potato starch was also investigated, highlighting its importance in the field of materials engineering (Ma et al., 2015). MW processing has shown enormous potential in various fields, offering advantages such as rapid and selective heating. However, for the solution to be used commercially on a large scale, challenges related to energy efficiency and heating uniformity must be overcome. 23 Figure 2.4. Schematic representation of the (A) Microwave (MW) drying ) principle ‒ polar molecules form the purple oval; (B) Hot air drying (HAD), MW hot air drying (MW-HAD), and MW drying temperature distribution. Source: An et al. (2022) 2.12. Advantages and limitation of MW drying MW and RF energy have the fundamental advantage of heating a material internally, eliminating the need for contact or convective heat transfer from the outside. Compared to the other food ingredients, water has a higher dielectric constant (around 8). Foods with high moisture content therefore absorb more MW or RF energy, which speeds up the drying process. Free water absorbs more energy than absorbed water and can therefore be removed more effectively. The depth to which the MW or RF energy penetrates (i.e., 37% decrease in radiation intensity) is inversely related to the loss factor and is related to the square root of the dielectric constant and the free space wavelength. For MW at 915 MHz and 2450 MHz, the typical penetration depths are 13 cm and 4.9 cm, respectively. The wavelengths that correlate with the above frequencies are 7:05 m, 3:28 cm and 12:03 cm, in that order (Saravacos and Kostaropoulos, 2002). The center of the material will overheat compared to the outer surface if the piece is smaller than the wavelength, 24 which is an important consideration in drying applications. Wet material that internally absorbs MW or RF energy experiences an increase in temperature and vapor pressure. This causes the product to expand and accelerates the drying process with convection or vacuum drying. According to Saravacos and Kostaropoulos (2002), MW or RF energy can be used before, during and after drying. According to Kostaropoulos and Saravacos (1995), a short MW pretreatment was found to improve the moisture permeability of grape skins and facilitate drying by sun or convection. When MW energy is applied to food gels and other food materials prior to conventional drying, a comparable result has been observed (Drouzas et al. 1997). In food materials, MW energy enhances the vacuum and freeze-drying processes and greatly raises the effective moisture diffusivity through enhanced energy (heat) absorption within the product or the formation of a porous structure (puffing) in the material (Drouzas et al., 1999). According to Saravacos and Kostaropoulos (2002), MW energy can reduce the residual moisture of some vegetables (e.g., green onions) from 5 to 10 percent faster than convective drying. Uneven heating is one of the major disadvantages of MW cooking as it can result in “hot and cold spots” in the food product. The thermophysical properties of the food product and the distribution of absorbed MW energy determine the temperature distribution in MW-heated foods. The electric and magnetic fields in the MW cavity or applicator, the dielectric properties of the food, and the MW frequency all influence the MW heating distribution in the food. The oven design (e.g., heating element type) can regulate the electromagnetic field pattern including the dimensions and shape of the cavity or applicator and the design of the waveguide system. Moving conveyors in industrial equipment and mode stirrers are other aspects of heating uniformity improvement techniques that can lead to improved process efficiency. There are some patents and methods for stimulating the MWs to produce a more consistent field pattern. Rotating turntables 25 and mode stirrers can theoretically produce more uniform heating patterns in the oven, but proper food and packaging design and optimization of relevant oven parameters are still required (Hebbar and Rastogi, 2012). 2.13. Mechanism of pathogen inactivation during MW drying The main source of pathogen inactivation during MW processing is thermal effects, which include the denaturation of proteins, nucleic acids and enzymes by heat from electromagnetic waves and food contact. Elevated temperatures can denature enzymes, disrupting their primary, secondary, and tertiary protein structures. As a result, the enzymes lose their active centers, which impairs some biochemical processes necessary for the survival of the microorganism. In addition, elevated temperatures also destroy nucleic acids, most commonly DNA (Dev et al., 2012). In addition, it was found that microbial destruction occurred faster with MW heating than with thermal heating, suggesting that MWs have more severe effects (Duhan et al., 2017). In liquid media, the inactivation of bacteria by MW treatment was significantly greater than in solid media, and higher MW power resulted in a faster rate of microbial inactivation (Kernou et al., 2022). In addition to thermal effects, non-thermal effects have been particularly investigated during MW processing (Shamis et al., 2012). The electric field primarily causes a non-thermal effect on microorganisms and enzyme inactivation. Non-thermal effects affect the integrity of cell membranes and the release of intracellular proteins in microorganisms (Guo et al., 2020). The dielectric breakdown of the cell membrane occurs when the electrical strength is high enough and the transmembrane potential is above a critical value. This leads to pore formation, increased permeability and ultimately irreversible loss of cell integrity (Kozempel et al., 2000; Zimmermann et al., 1994). Overall, MW drying alone does not guarantee a 5-log reduction but can potentially be employed as a mitigation strategy to reduce Salmonella levels in dried chili peppers. 26 CHAPTER 3: MODELING SALMONELLA INACTIVATION OF CHILI PEPPERS DURING MICROWAVE DRYING 3.1. Introduction Red chili pepper, a widely consumed spice, has been associated with potential food safety concerns due to microbial contamination. Studies have found varying levels of bacterial contamination in both fresh and packaged red pepper samples. While Salmonella was not detected in some studies (Erdem et al., 2013; Jeong et al., 2010), other pathogens such as B. cereus and E. coli were present in some samples (Jeong et al., 2010). Certain strains of Salmonella can survive in spices for extended periods of time and may grow in contaminated prepared foods at higher temperatures (Urabe et al., 2008). Additionally, red pepper is the spice with the highest risk of contaminating people with Salmonella, according to the World Health Organization (WHO, 2022). Thus, it is crucial to establish appropriate handling, storage, and pathogen mitigation strategies for red chili pepper products to ensure food safety. Heat treatments are widely used to reduce microbial loads in foods. Studies have shown the effectiveness of techniques such as ohmic heating and hydrogen peroxide vapor in reducing Salmonella concentrations in various food matrices (Li et al., 2018; Song and Kang, 2022). Strategies such as chlorine dioxide treatment have shown promise in reducing Salmonella levels on chili peppers, highlighting the importance of exploring different approaches to improving food safety (Malka and Park, 2022). Chlorine dioxide (ClO2) gas treatment followed by drying effectively reduced S. Typhimurium on chili peppers to undetectable levels (Lee et al., 2018). For beef jerky, marination and drying temperature influenced Salmonella inactivation, with acetic acid treatment enhancing the effect (Yoon et al., 2009). In Roma tomatoes, pre-drying treatments like organic acid dipping improved Salmonella destruction during dehydration, with ascorbic acid being most effective (Yoon et al., 2004). For fresh-cut peppers, Salmonella enterica fate was 27 modeled as a function of temperature and relative humidity, showing growth dependence on initial concentration, temperature, and humidity (Ferreira et al., 2020). For MW heating, Osaili et al. (2021) found that MW heating at 220-660W effectively inactivated Salmonella spp., E. coli O157:H7, and L. monocytogenes in tahini paste at a fixed aw, with higher power levels and longer exposure times producing better results. Handayani et al. (2022) compared sun and MW drying, determining that MW drying resulted in faster drying rates and higher diffusivity values. Although potential improvements in chili pepper quality and drying efficiency through MW drying have been reported, data on Salmonella inactivation are limited. Therefore, understanding the dynamics of Salmonella inactivation during MW drying of red chili peppers, influenced by factors such as aw, can provide valuable insights for developing targeted interventions to reduce the risk of foodborne illnesses associated with this pathogen (Allard et al., 2012). Smith et al. (2014) found that the rate of desiccation or hydration did not affect thermal resistance; rather, the aw at the time of thermal treatment was the determining factor. Different modeling approaches have been developed to assess the impact of aw on thermal inactivation, with the modified Bigelow model showing superior predictive ability (Smith et al., 2016). Overall, this study provides a better understanding of the fate of Salmonella during MW drying using predictive modeling and the effect of aw on their thermal resistance. 28 3.2. Materials and Methods 3.2.1. Overview of the study The aim of this study was to evaluate Salmonella inactivation during MW drying of red chili peppers using a predictive model to predict the inactivation kinetics during drying. The study had two objectives: (1) to estimate the Salmonella inactivation kinetics of red chili (Capsicum annuum) in small, sealed aluminium test cells heated in water baths, and (2) to predict Salmonella lethality during MW drying of fresh red chili usingth estimated parameters from objective 1. The following diagram shows the procedure for developing a model to predict Salmonella lethality during MW drying of red chili (Figure 3.1). Inoculum preparation and inoculation aw equilibration Data gathering for thermal inactivation kinetics Scaled sensitivity coefficient (SSC) analysis Thermal resistance parameter estimation Model residual analysis for model validation Data gathering for MW drying Model testing for MW drying Figure 3.1.3. Flowchart of data processing for prediction of Salmonella inactivation during MW drying of red chili. 29 3.2.2. Red chili peppers The chili pepper flakes used for thermal inactivation kinetic estimation study were obtained from Regal Spices (Lancaster, PA, USA). To confirm the absence of Salmonella, approximately 1-g sample of chili pepper flakes was incubated in 500 mL of Luria-Bertani (LB) broth (Neogen, Lansing, MI, USA) at 37 °C for 24 hours. Following the incubation time, the mixture was placed in soybean tryptic medium (TSA) containing 0.05% ammonium citrate and 0.03% sodium thiosulfate referred as modified TSA (Sigma Aldrich, St. Louis, MO, USA); this is later referred to as modified TSA. The plates were then kept in an incubator at 37 °C for 48 hours. The characteristic black precipitate that formed amid the Salmonella colonies on the modified TSA plates made it possible to distinguish Salmonella from other contaminating bacteria. The use of non-selective differential media such as modified TSA confirmed the absence of Salmonella in the red chili pepper flake samples. For MW drying, fresh red finger chili peppers were acquired from Webstaurant (Lititz, PA, USA). The evidence of the absence of Salmonella in the red chili peppers involved incubating 1 g in 500 mL of LB broth (Sigma Aldrich, St. Louis, MO, USA) at 37 °C for 24 hours. Afterward, the admixture was plated onto modified TSA plates and incubated for 24 hours at 37 °C. Salmonella survivors was distinguished from other potential contaminating microorganisms by the characteristic black precipitate in the center of the colonies. Both the fresh and crushed dried chili peppers used in this study were not contaminated with Salmonella. 3.2.3. Inoculum preparation and inoculation procedures 3.2.3.1. Hand inoculation procedures The Salmonella enterica Montevideo strain utilized in this research was provided by Dr. Bergholz’s Lab at Michigan State University. This strain was selected because it was associated 30 with a nationwide outbreak of black and red pepper contamination that affected 272 individuals in 44 states between 2009 and 2010 (Gieraltowski et al., 2012). Tryptic soy broth (TSB) medium supplemented with 20% (v/v) glycerol was used to maintain the Salmonella cultures at −80 °C. Prior use, culture was performed twice consecutively in Luria-Bertani (LB) broth media and maintained at 37 °C for 20 hours. The culture was also placed on plates (100 × 15 mm) composed of TSA to achieve uniform growth lawn. After incubation for 24 hours at 37 °C, the bacterial lawn was collected using a sterile L- shaped pipette and suspended in 2.2 mL of 0.1% peptone water to create an inoculum. To achieve a target inoculum of ~7 log10 CFU/g for red chili peppers, 1.0 mL of the starting inoculum was used to inoculate 100 mg of pepper sample for each biological replicate. The inoculum suspension was placed in a sterile bag with the uninoculated chili peppers and shaken manually for 4-5 minutes to mix the contents. After mixing, the pepper flakes were placed in a sterile stainless-steel tray and mixed with a sterile spatula for 1 minute. To check for uniformity after inoculation, four randomly selected inoculated samples of 2.5 g each were enumerated. The inoculum was considered evenly distributed when the standard deviation (SD) of the randomly selected samples was less than 0.5 log10 CFU/g. 3.2.3.2. Surface inoculation procedures Salmonella enterica Montevideo and Salmonella Enteritidis phage type (PT) 30 (Dr. Bergholz’s Lab , Michigan State University) were used for spot inoculation of chili pepper slices in the studies. The culture was kept in tryptic soy broth supplemented with 20% (v/v) glycerol at a temperature of -80°C. Prior to use, the culture was streaked onto 100 x 15 mm TSA plates to create uniform lawns and subjected to two consecutive transfers into LB broth (at 37 °C for 20 31 hours). After incubation (24 at 37 ℃ for 24 hours), the bacterial lawn was harvested using a sterile L shaped spreader in 2.0 mL of sterile 0.1% peptone water (BD) to constitute the inoculum. Red chili peppers, with a native aw of 0.98±0.001, were sliced longitudinally prior to inoculation of each individual strain of S. Enteritidis PT 30 and S. Montevideo. To achieve ∼7 log10 CFU/g target inoculum level on the red chili pepper slices 100 µL of the initial inoculum was spot inoculated on the external surface longitudinally to inoculate one slice (~10 g), per biological replicate. The inoculated slices are dried in the biological safety cabinet for one hour until the droplets (~10 µL per droplet) were dried on the external surface (Figure 3.2). To check the homogeneity, four randomly selected inoculated slices were collected. The inoculum was considered homogeneously distributed if the standard deviation of the four samples was less than 0.5 log10 CFU/g. Collecting pathogen inoculum Placing droplets lengthwise on the chili pepper slice surface Contaminated chili pepper slice Drying in the biosafety cabinet for 1 hour Figure 3.2.4. Procedure for pathogen spot inoculation in red chili peppers. 3.2.4. Equilibration of samples at target water activity Before each heat treatment, the aw of each sample was equilibrated to a target level. The inoculated red chili peppers, weighing about 100 g, were put into 100 x 15 mm petri dishes and placed inside an aw conditioning system to control their aw. This system included a custom control operation in addition to an equilibration chamber (69 x 51 x 51 cm). The control system included a moisture monitoring device inside the chamber, solenoid faucets, an air flow system, a hydration 32 column, a desiccation column, and a computer-based monitoring operation to maintain the relative moisture level. The samples were conditioned for 2-3 days at the targeted moisture levels (33%, 50%, or 90% relative humidity). The samples were more easily fully equilibrated to the intended aw during this conditioning period, which was later confirmed using a aw meter (n=3) for each distinct target of aw. 3.2.5. Heat treatment procedure for thermal inactivation kinetic data collection The thermal inactivation kinetic data collection is based on thermal-deathtime (TDT) test that involved two factors (temperature and aw) and a full factorial design experimental setup. The three fixed aw values in this design were ~0.33, 0.50, and 0.97 at room temperature, along with three constant water-bath temperatures of 60, 65, and 70 °C. To ensure repeatability, every experiment was conducted with 3 biological replicates. The heat treatments were performed using 1-mm thick aluminum test cells as described by Chung et al. (2008) . Approximately 50-mg samples of inoculated and aw equilibrated red chili peppers were placed inside these cells. A water bath (Vesta Precision, Bellevue, WA) with a temperature setting of 60, 65, or 70 °C was also used to submerge the cells. Uninoculated samples were placed in test cells with a T-type thermocouple installed in the center of each cell to measure chili sample temperature. Time 0 for the isothermal treatment was designated by measuring the sample’s core temperature when it approached the target temperature by 0.5 °C, which is known as the come-up time (CUT) and can range from 50 to 70 seconds. Beginning with the samples taken at time 0, treated chili flakes were extracted at nine equally spaced time points. At each timepoint, three test cells (two with inoculated chili flakes, one with uninoculated flakes and a thermocouple) were removed from the water bath and immediately placed in an ice-water bath for 40 seconds to stop the thermal inactivation process. 33 3.2.6. MW drying After inoculation, approximately 40 g of chili pepper slices were placed dried in a 2450 MHz MW oven (LG Electronics, Denver, CO, USA) at power levels of 120W and 240W for 45 minutes and 18 minutes, respectively. The MW power density was 3W/g and 6W/g for 120W and 240W, respectively. These MW densities were selected based on literature review and preliminary work, in which the samples were burned before fully dried at MW density beyond 6W/g. To minimize variability due to heat uniformity in the MW, the slices were consistently placed at the same position for each treatment. The temperature data for each time point were collected using an infrared camera (TiR3FT Fluke, Everett, WA, USA) to immediately capture a thermal image (< 20 seconds) of each sample. The sampling time interval was 5 minutes for 120W and 3 minutes for 240W with 3 biological replications and 2 subsamples per replication. The infrared camera was set up on a tripod next to the oven at a vertical distance of ~30 cm above the samples (Randriamiarintsoa, 2022). The temperature data were treated with the SmartView Classic 4.4 thermal imaging software (Fluke, Everett, WA, USA) to select the surface area of the chili pepper slice and compute the average temperature. One slice was randomly picked for Salmonella survivor enumeration and another slice was selected for aw analysis using Aqualab 4TE water activity meter (Pullman, WA, USA). 3.2.7. Survivor recovery and enumeration To count the number of Salmonella survivors after thermal-deathtime (TDT) test, the heat- treated chili peppers (g) were taken from the test cells and placed in sterile 15 mL centrifuge tubes. They were then diluted with 4.5 mL of 0.1% peptone water to a dilution ratio of 1:10. The diluted samples were then homogenized using a vortex at 3000 revolutions per minute (rpm) for 60 seconds. Serial dilutions were then conducted with 0.1% peptone water in a ratio of 1 to 10. The 34 dilutions were periodically plated onto modified TSA. After the plates were incubated at 37°C for 24 hours, the number of Salmonella colonies, which are represented by black spots on the plates, was counted and log10 transformed for each biological replicate. Log reductions were calculated by subtracting the initial log population from the log survival numbers. For MW drying, approximately 2 g of red chili peppers were transferred into a sterile Whirl-Pak bag (Nasco, Madison, WI) diluted with 0.1% peptone water at 0:1 ratio and homogenized for 2 minutes using Stomacher Model 400 Circulator (Seward, Bohemia, NY, USA). The diluted samples were then plated in duplicate onto a tryptic soy agar (TSA) with ferric ammonium citrate and sodium thiosulfate. After 24 hours of incubation at 37°C, the Salmonella colonies were counted, and the populations were logarithmically transformed. To calculate log reductions, the log survival numbers for each replicate were subtracted from the log population at time 0 for that replicate, which was evaluated after CUT. 3.2.8. Mathematical modelling 3.2.8.1. Scaled sensitivity coefficient (SSC) analysis A Scaled Sensitivity Coefficient (SSC) analysis was performed to determine whether a parameter can be estimated or not, as described by Dolan and Mishra (2013). Before designing and conducting the experiment, it is recommended to plot the scaled sensitivity coefficients (X'). According to Beck and Arnold (1977), the sensitivity coefficient shows how much the response changes when the parameters are changed. For each aw, the SSC analysis was conducted based on simulated experiment. Since each experiment was conducted at a constant temperature, the SSCzT has no meaning since zT can only be estimated when the temperature changes. Therefore, to represent SSCs, a simulated 35 (hypothetical) nonisothermal experiment was performed in MATLAB. The temperature to increase linearly was set as follows: (3.1) Where Tmin = lowest temperature of the Salmonella-chili pepper sample (24.5°C) ; Tmax = highest water-bath temperature (70 °C); tmax = the duration of the longest experiment, i.e., the lowest-temperature water-bath (350 s, 3000 s, and 6000 s for aw = 0.9, aw = 0.9, and aw = 0.9, respectively ). The secant forward-difference method was used in MATLAB (Chapra, 2018). The SSC reflects the model's sensitivity to a specific parameter, measured in logN units. If the maximum absolute value of an SSC is less 5% of the maximum absolute value of logN, it signifies the parameter's insignificance to the model prediction. In such cases, the parameter is considered insensitive and is held constant, making estimation unnecessary (Dolan and Mishra, 2013). Therefore, in order for a parameter to be estimated, the SSC of the parameter must be large and uncorrelated with other SSC. If a parameter does not meet one or both of these conditions, that parameter is set to a defined value based on either the literature or a supplementary experiment. It is also possible that two parameters are highly correlated. In that case, the parameters are estimated individually instead of simultaneously. 3.2.8.2. Parameter estimation for thermal inactivation kinetics This first step focused on estimating Salmonella thermal resistance parameters (D, zT, zaw) that can be used to describe Salmonella inactivation in dynamic thermal processes including drying. For the primary model, the logarithmic-linear model according to Schaffner and Labuza (1997) was selected. Given a linear relationship between the logarithm number (logN) of survivors over time, the model can be expressed in differential form as follows: 36 minmaxminmax*()/simulatedTTtTTt=+− (3.2) For the secondary model, the D-value variation with temperature T was characterized using the Bigelow se model: (3.3) Tr represents a reference temperature that is in the range of the experimental temperatures. By inserting Eq. (3.3) in Eq. (3.2), and integrating both sides one obtains the final model for non-isothermal conditions: (3.4) Where Dr represents the D-value at the reference temperature condition Tr = 67 °C, at which the correlation between Dr and zT is the lowest. The term is the time-temperature history for a particular non-isothermal experiment. The dynamic temperature in the test cell center is denoted by T(t). To reduce the error in the Dr parameter, the reference temperature, Tr, was optimized by minimizing the absolute value of the correlation coefficient between Dr and z. At each aw, the ordinary least squares (OLS) non-linear regression was used to simultaneously estimate Dr, zT, and log N0 using all data simultaneously with full time-temperature histories in MATLAB. As an alternative to the traditional two-step approach of model fitting, the one-step approach provides more accurate estimated parameters with reduced uncertainty (Dolan and Mishra, 2013). A comparison of model fitting of isothermal conditions and nonisothermal conditions was performed to understand the impact of dynamic temperature conditions on the model accuracy. 37 (log)1dNdtD=−()10rTTTzrDTD−=()001loglog10rTTtTtzrNND−=−()010TTtTrtz− Under the isothermal conditions, the product temperature at the center of the test cell labeled T(t), was set to the target water bath temperature for each treatment. In addition, the initial population (logN0) was determined at the CUT time, when T(t) was equal to the target temperature. Under the nonisothermal conditions, T(t) changed dynamically and was measured with a thermocouple rather than being fixed to a constant value. Additionally, the logN0 corresponds to the initial population at the beginning of the experiment, i.e., before reaching the CUT. The zT-values estimated from the different constant aw datasets were used to estimate a global zaw-value for the model considering the dynamic change of aw. For this purpose, an additional term was inserted into the Biglow model in Eq. (3.4), to account for the influence of aw on Salmonella thermal resistance. The following equation represents the final model with dynamic temperature and aw conditions: The time-temperature- aw history is represented by: (3.5) (3.6) T(t) represents the dynamic temperature of the chili flakes at the center of the test cells and aw (t) represents the aw of the sample. Tr and awr are the reference temperature and reference aw optimized to minimize the error in the Dr parameter. The zaw-value and Dr were globally estimated using the nlinfit function in MATLAB i.e. all the temperature-time history data and the estimated zT-values corresponding to each aw, were used in the model. The data from the dynamic temperature conditions for all the aw were utilized for the 38 ()()001loglog10wwrrwataTtTtzazTrNNdtD−−+=−()()010wwrraTwataTtTtzz−−+ one-step approach. Subsequently, to estimate a global zT for all the aw, the previously estimated global zaw was then fixed to a constant value in Eq. (3.5). For comparison, all D-values corresponded to the D-values at the reference conditions, Tr = 67°C and awr = 0.987. The final thermal resistance parameters (Dr, zaw and zT) estimated globally, were used in the Salmonella inactivation predictive model during the dynamic process including MW drying. 3.2.8.3. Predictive model for MW drying. This section focused on predicting Salmonella inactivation during MW drying using the globally estimated thermal resistance parameters (Dr, zT, zaw) and the model in Eq. (3.6). Drying is typically a rather complex process because it involves not only a dynamic change in product temperature but also a dynamic change in product aw. Prediction error increases when a mathematical model is applied to more complex processes, which differ from the laboratory settings used to create the model's structure and determine its parameters (Pin et al., 1999). If the fitting is successful, the model would predict the Salmonella lethality similar to the observed data during MW drying. 3.2.9. Model validation Model validation is typically performed at the end of mathematical modeling and represents a critical step. First, the normality of the residuals can be confirmed using a residual histogram that overlaps with the standard error of the residuals ( ) and the probability density function of a normal distribution with mean zero. The second regression hypothesis that needs to be evaluated is the independence of the residuals. To achieve this, the residuals can be plotted against the predicted values (Georgalis et al., 2023). If the model's assumptions are correct, the plot should not reveal any clear trends. The third regression hypothesis 39 ()()2 ypredyobsSERnp−=− that needs to be evaluated is the homoscedasticity i.e., whether the variance of the residuals is constant or not. Another recommended tool for evaluating this hypothesis is a plot of residuals versus predicted values (Georgalis et al., 2023). The root mean squared error (RMSE) is the criterion used to check the goodness of fit of the models. To avoid positive and negative deviations canceling each other out, the RMSE is a measure of absolute error that squares these deviations. The parameter value that best fits the predicted values to the observed data is indicated by the lowest RMSE: (3.7) Where n stands for the number of observations, p for the number of parameters to estimate, ŷi for the predicted values and yi for the observed values. 3.2.10. Statistical analyses The temperature data obtained from the infrared camera was analyzed both spatially and temporally on the entire surface of the red chili peppers using SmartView 7.0 software (Fluke Corporation, Everett, WA, USA). The visible wavelength image was used to define the area of each chili pepper slice and the corresponding infrared image was used to analyze the average temperature within these defined areas. All statistical analyzes for bacterial enumeration were performed using SAS 9.4. ANCOVA (α=0.05) was used to determine the effect of MW power level and Salmonella strain on the survival of Salmonella using time as a covariate. 40 ()2iiyyRMSEnp−=− 3.3. Results and Discussion 3.3.1. Initial population of S. Montevideo The red chili pepper samples were free of Salmonella before inoculation and the initial aw value of the red chili peppers was 0.46. After six subsamples (~2.5 g each) were randomly selected from a single inoculated sample (100 g), the standard deviation of inoculation was found to be 0.30 log10 CFU/g, indicating that the inoculum level in all samples was consistent. The initial Salmonella population of all inoculated samples had a mean (6 standard deviation) of 6.86±0.3 log10 CFU/g. During thermal heating, the average Salmonella count in all inoculated samples was 8.83±0.5 log10 CFU/g. Xie (2022) used a similar inoculation technique with a higher initial inoculum concentration (~11 log10 CFU/g) specifically for chili peppers, cinnamon and black peppers yielded an initial Salmonella population with a standard deviation of less than 0.5 log10 CFU/g ranging from 7.5 to 9.1 log10 CFU/g. The overall results showed that spices containing substances with antimicrobial properties, such as chili peppers, can be contaminated by foodborne pathogens, including Salmonella. Low aw in low-moisture foods and ingredients, including spices, poses a challenge in eliminating pathogens without compromising quality (Beuchat et al., 2013). Additionally, the resistance of Salmonella to heat increases with decreasing moisture, emphasizing the impact of aw on pathogen survival during processing (Podolak et al., 2010). The presence of antimicrobial- resistant Salmonella strains in spice shipments highlights the potential risk associated with these products (Van Doren et al., 2013). 3.3.2. Effect of water activity on Salmonella thermal resistance The observed Salmonella reduction data (Figure 3.3) showed that the thermal-death time (TDT) is longer at lower aw. These results indicate that the Salmonella reduction decreased with 41 decreasing aw and temperature. At 65 °C, a treatment time of 100 minutes was required to achieve a 3-log reduction in initial populations at aw = 0.3. In contrast, a similar 3-log reduction was observed after just 20 minutes at aw = 0.5 and maintaining the same temperature. At the other treatment temperatures (60 °C, 70 °C), a similar trend of greater thermal resistance of Salmonella was observed in red peppers at decreased aw. A treatment temperature of up to 70 °C and a treatment time of 45 minutes were required to achieve a microbial inactivation of 2.5-log reduction at aw = 0.3. Overall, chili peppers with lower aw have Salmonella with a higher thermal resistance. Water activity is known as a key factor that impacts the thermal inactivation kinetics of Salmonella in low-moisture foods. Studies have shown that the heat inactivation of Salmonella in different food matrices, such as almond kernels, peanut butter, milk powders, ground turkey, and beef products, is affected by aw levels (Villa-Rojas et al., 2013; Ma et al., 2009; Wei et al., 2020; Carlson et al., 2005; Mogollón et al., 2009). The thermal inactivation curves of Salmonella often exhibit biphasic patterns, with rapid initial death rates followed by slower rates (Ma et al., 2009). Additionally, the total solid content and pH of food products can impact Salmonella thermal inactivation (Mogollón et al., 2009). The desiccation-adapted Salmonella spp. exhibit increased thermal resistance, with moisture and ammonia content being significant factors influencing their survival (Zhao et al., 2013). 42 (A) 60 °C aw = 0.3 aw = 0.3 aw = 0.5 aw = 0.5 aw = 0.9 aw = 0.9 / ) g U F C 0 1 g o l ( / 0 N N g o L 0 -1 -2 -3 -4 -5 0 20 40 60 80 100 120 140 Time (min) (B) 65 °C aw = 0.3 aw = 0.3 aw = 0.5 aw = 0.5 aw = 0.9 aw = 0.9 0 20 40 60 Time (min) 80 100 (C) 70 °C aw = 0.3 aw = 0.3 aw = 0.5 aw = 0.5 aw = 0.9 aw = 0.9 / ) g U F C 0 1 g o l ( / 0 N N g o L / ) g U F C 0 1 g o l ( / 0 N N g o L 0 -1 -2 -3 -4 -5 -6 0 -1 -2 -3 -4 -5 -6 -7 0 5 10 15 20 25 30 35 40 Time (min) Figure 3.3.. S. Montevideo survival curves in red chili peppers using isothermal approach at (A) 60 ℃, (B) 65 ℃, and (C) 70 ℃. 43 The type of inoculation procedure can affect the variability and repeatability of Salmonella thermal resistance (Hildebrandt et al., 2016). It has been reported that Salmonella can become quite heat resistant under low- aw stress (Puttananjaiah and Viswanath, 2022). The survival of Salmonella in different environments, such as ground pork, and peanut butter, has been studied to understand its resistance to thermal treatments (Suo et al., 2017; He et al., 2014). Mathematical models have been established to describe the thermal inactivation of pathogens, such as Salmonella, at varying temperatures and aw levels (Lambert, 2003). 3.3.3. Mathematical modeling for in-container thermal treatments 3.3.3.1 Scaled sensitivity coefficient (SSC) analyses The model parameters (Dr, z, and logN0) were found to be uncorrelated based on the SSC analyses based on nonisothermal datasets, which enabled one-step parameter estimation approach. The SSC plots (Figure 3.4) indicate that the accuracy of logN0 estimation surpassed that of Dr and z, as evidenced by the errors presented in Table 3.1. From 6.5 to 2.0 log10 CFU/g, the dependent variable logN predicted at aw = 0.9 has a total span of ~4.5 log10 CFU/g. The overall span for aw = 0.5 and 0.3 is ~2.0 log10 CFU/g (from 6.5 to 4.5) and ~1.0 log10 CFU/g (from 6.5 to 5.5), respectively. For all treatments, the parameter that is estimated with the highest accuracy is logN0 since its SSC is the largest and uncorrelated with the SSC of the other parameters. The SSC for the z- value is the next largest SSC, with a maximum absolute value of 1.0, 2.0 and 4.5 for aw = 0.3, aw = 0.5 and aw = 0.9, respectively. For the D-value, the maximum absolute values of SSC are 0.9, 1.9, 4.4, 0.9 for aw = 0.3, aw = 0.5 and aw = 0.9, respectively. The ratio of SSCs for D- and z- values was not constant throughout treatment, demonstrating noncorrelation (Figure 3.4). 44 (A) (D) (B) (E) (C) (F) Figure 3.4.5. Scaled Sensitivity Coefficients (SSC) analyses of iso-moisture thermal resistance experiments of red chili peppers at (A) aw = 0.3, (B) aw = 0.5, (C) aw = 0.9 and ratio SSC D- value/SSC z-value for: (D) aw = 0.3, (E) aw = 0.5 and (F) aw = 0.9. 45 3.3.3.2. Parameter estimation of thermal inactivation kinetics The outcomes of the ordinary least square (OLS) analysis for the in-container iso-moisture data are displayed in Table 3.1. Fitting error accumulation is avoided by applying a one-step regression analysis to all of the isothermal data (Valdramidis et al., 2005). The optimal reference temperature was 67 °C, which was close to the upper end of the temperature range in this study. At aw of 0.3, varying heating time points show a minimal impact on the S. Montevideo inactivation, with a D67 ℃ of 26.09 min. As the aw increases to 0.5, there is a noticeable decrease in microbial population at 67°C throughout the treatment time, resulting in D67℃ of 6.35 min. However, at a aw of 0.9, the impact of temperature becomes more pronounced, with the lowest microbial population and highest D67 ℃-value observed at 70°C which is 0.24 min. The results suggested that, at higher aw level, temperature plays a crucial role in significantly reducing the microbial load. For instance, from aw = 0.3 to aw = 0.9, the D67 ℃ decreased by over 120-fold with a z-values of 15.2 and 11.66 °C, respectively (Table 3.1). Similarly, over 9-fold decrease of D70 ℃ of S. Enteritidis PT30 in cinnamon has been observed between aw = 0.2 and aw = 0.5 (Xie et al., 2021). Although, SSC at aw = 0.3 was not the largest due to a smaller logN span, Table 3.1 has shown that more accurate D67℃- and z-value estimation is possible with slower experiments (aw = 0.3). Comparing the D67℃- and z-value SEs and RMSEs to the other treatment, they were lower. The decrease of the coefficient of correlation between D67 ℃- and z- at a longer treatment duration may provide an explanation. At aw = 0.3, the residual analysis also shows that the error's variance is equal (Figure 3.5). Slower heating rates were also demonstrated to provide more precise estimates in a prior study of the inactivation of E. coli K12 (Dolan and Mishra, 2013). 46 Table 3.1.3.The parameter estimates, relative errors, and root mean square error (RMSE) for the log-linear/modified Bigelow model for in-containerthermal treatments. Model parameters Estimate Error (%) aw 0.3 D67°C-value (min) zT (℃) logN0 at 60 ℃ (log10 CFU/g) logN0 at 65 ℃ (log10 CFU/g) logN0 at 70 ℃ (log10 CFU/g) 0.5 D67°C-value (min) zT (℃) logN0 at 60 ℃ (log10 CFU/g) logN0 at 65 ℃ (log10 CFU/g) logN0 at 70 ℃ (log10 CFU/g) 0.9 D67°C-value (min) zT (℃) logN0 at 60 ℃ (log10 CFU/g) logN0 at 65 ℃ (log10 CFU/g) logN0 at 70 ℃ (log10 CFU/g) All aw (global) D67°C-value (min) zT (℃) zaw logN0 at 60 ℃ (log10 CFU/g) logN0 at 65 ℃ (log10 CFU/g) logN0 at 70 ℃ (log10 CFU/g) RMSE (log10 CFU/g) 0.52 0.98 0.88 0.87 5.61 6.45 2.30 2.31 2.51 9.68 11.1 3.61 3.86 4.08 16.42 13.07 4.88 3.78 3.59 4.43 4.32 2.19 2.42 2.13 2.15 26.09 15.16 6.4 6.5 5.8 6.35 16.2 6.2 6.2 6.4 0.24 11.66 6.7 7.2 7.5 14.42 15.72 0.343 6.4 6.6 6.4 47 3.3.3.3. Effect of temperature variation on model performance The survival of S. Montevideo inactivation kinetics from thermal treatments was analyzed using the log-linear model and isothermal temperature profiles, in which the red chili peppers temperature throughout the treatment was assumed equal to average water-bath temperature and each replication began at the end of come-up time. For comparison purposes, the S. Montevideo inactivation treatment at aw = 0.3 was selected, in which the RMSE values for both approaches were computed (Table 3.2). For the isothermal approach, the initial population i.e., the population at come-up time (CUT) was 8.83±0.5 log10 CFU/g (Appendix Table A.2). The use of nonisothermal temperature profiles has been shown to improve the accuracy of predicting the lethality of S. Montevideo compared to its isothermal counterpart. For instance, at aw = 0.3, the RMSE was approximately 0.5 and 0.7 log10 CFU/g for isothermal and nonisothermal profiles, respectively (Table 3.2). Table 3.2.4. Parameter estimates for nonisothermal and isothermal analysis of S. Montevideo in red chili peppers for in-container thermal treatment at aw = 0.3. Analysis Model parameters Non- isothermal Estimate Error (%) RMSE (log10 CFU/g) D67°C-value (min) zT (℃) 16.54 15.16 4.80 6.45 0.5 logN0 at 60 ℃ (log10 CFU/g) logN0 at 65 ℃ (log10 CFU/g) logN0 at 70 ℃ (log10 CFU/g) Isothermal D67°C-value (min) zT (℃) logN0 at 60 ℃ (log10 CFU/g) logN0 at 65 ℃ (log10 CFU/g) logN0 at 70 ℃ (log10 CFU/g) 6.3 6.5 5.7 25.65 14.8 6.0 6.2 5.3 2.30 2.31 2.51 9.68 11.1 3.61 3.86 4.08 0.7 48 For the non-isothermal data, regression analysis using the same model was also conducted based on the isothermal data's model structure selection. Although the D67℃-value for the isothermal analysis was higher, the z-value obtained from non-isothermal approach were slightly higher compared to that from isothermal approach. In addition, the relative errors for both D and z values were smaller for the non-isothermal than isothermal approach. Furthermore, Vyazovkin and Wight, (1998), emphasized that comparison of model fitting results from isothermal and nonisothermal, highlighting the distinct advantages of nonisothermal modeling. The RMSE value for the dynamic data (0.5 log10 CFU/mL) was lower than the RMSE for the static data (0.7 log10 CFU/mL), indicating the good fit of the model to the data. In summary, the D-value and z-value were more accurately represented by the dynamic parameter results. It was shown that the model predictions for heat inactivation of L. monocytogenes under nonisothermal treatments fit the measured data well regardless of the magnitude of the thermotolerance increase, highlighting the robustness of nonisothermal prediction models in the field of food preservation (Hassani et al., 2005). Furthermore, Trevisani et al. (2017) comparison of the dynamic model's predictions and observations accurately described the linear inactivation pattern, thereby bolstering the dynamic models' effectiveness in nonisothermal settings. Since the product temperature and S. Montevideo inactivation are nonlinear, particularly at elevated temperatures and aw, it has been demonstrated that the use of nonisothermal temperature profiles improves the predictive modeling accuracy of S. Montevideo thermal inactivation in red chili peppers (Table 3.2). The results demonstrate how crucial it is to take nonisothermal conditions into account when modeling and simulating in order to increase prediction accuracy and more closely mimic real-world situations. 49 (A) (B) Figure 3.5.6. Examples of non-isothermal temperature profile (line) and Salmonella reduction (circle) at 70 ℃ for (A) aw = 0.5 and (B) aw = 0.9. It is noteworthy that using parameters estimated form isothermal experiments to predict inactivation of pathogens including Salmonella in commercial thermal processes that involve gradual warming of the cold spot may result in an uncertain underestimation of survival. Isothermal experimental parameters can be dangerous under these circumstances and at worst can be misleading or at best give an indication of the upper limit of the inactivation rate (Dolan and Mishra, 2013). When food is processed, such as during drying, dynamic moisture levels are frequently missed in isothermal experiments conducted at a single moisture level. The dynamic 50 fluctuations in moisture content that can significantly affect pathogens' resistance to heat, like Salmonella, are not considered in this method. Because of this, models constructed with these isothermal single moisture data frequently overestimate the drying process's fatal effect, which can result in mistakes that could be detrimental when validating preventive control measures. Because they do not accurately reflect actual drying conditions where both temperature and moisture are dynamic, these isothermal single moisture models are not appropriate for validating the safety of low-moisture products. Validating the models with actual survival data from the drying process, including MW-based techniques, is essential to guaranteeing the accuracy and security of the predictive models used for process validation. 3.3.4. Residual analysis For the TDT test, the histogram of the residual shows an almost normal distribution (Figure 3.6). Notably, larger residuals were observed in the first quarter of treatment, suggesting some challenges in adaptation during this period. However, at other heating times, the residuals followed an additive pattern with constant variance and a mean close to zero, which confirmed the effectiveness of the equation used to estimate S. Montevideo inactivation in red chili peppers. Furthermore, the residuals for aw = 0.9 showed good agreement with slightly larger values at the beginning and a potential positive bias in the histogram (Figure 3.6). Compared to the other two treatments, the rapid heating rate at aw = 0.9 seems to have more residual correlation (Figure 3.6). Consequently, there is space for improvement in the data and/or the model. 51 Figure 3.6.7. Histogram of the residuals at (A) aw = 0.3, (B) aw = 0.5, and (C) aw = 0.9 ; and scatter plot of the residuals at (D) aw = 0.3, (E) aw = 0.5, and (F) aw = 0.9. 52 3.3.5. Validation of estimated model parameters in MW drying The globally estimated Salmonella thermal resistance parameters (D, zT, zaw) were used to predict Salmonella inactivation during dynamic process of chili peppers particularly MW drying. The first step to achieve that is to collect the data including temperature profile of the product and the Salmonella survivors during MW. The second step consists of performing a forward problem to predict Salmonella inactivation using the modified Biglow-model in Eq. (3.5) and thermal inactivation parameters. 3.3.5.1. Temperature profile and drying kinetics The surface temperature of the product increased at the beginning of the MW drying a gradually decreased as the product moisture was decreasing over time (Figure 3.7). Drying processing ensures that water is removed, improving shelf life, and maintaining overall quality and bioactive properties. Salmonella and other foodborne pathogens, as well as mold and spoilage bacteria, are significantly influenced by the moisture content in the food (Tapia et al., 2020). In order to compare the effects of energy input on food temperature and dry kinetics, MW drying was used in this study. Research has indicated that the drying temperature of chili peppers has a major effect on their quality. For example, Getahun et al. (2020) have reported that drying temperatures below 65 °C are necessary to maintain the product's quality and structural integrity. According to Castro- Rosas et al. (2011), Salmonella can grow in peppers at 25 °C, highlighting the importance of understanding the influence of temperature on pathogen behavior. 53 ) C ° ( e r u t a r e p m e T ) C ° ( e r u t a r e p m e T 80 70 60 50 40 30 20 90 80 70 60 50 40 30 20 (A) MR MR aw aw (C) w a - o i t a r e r u t s o M i 1 0.8 0.6 0.4 0.2 0 0 10 20 30 40 50 0 10 20 30 40 50 Time (min) Time (min) (B) (D) MR MR aw aw w a 1 - o i t a r e r u t s o M i 0.8 0.6 0.4 0.2 0 0 5 10 Time (min) 15 20 0 5 10 Time (min) 15 20 Figure 3.7.8. Temperature profile of fresh red pepper slices during MW drying at (A)120W and (B) 240W; moisture ratio and water activity at (C) 120W and (D) 240W. Connecting lines were added for clarity. The temperature distribution of fresh chili peppers changed over time while they were MW dried in both the 120W (Figure 3.8) and 240W treatments (Figure 3.9). Uneven temperature distribution during MW drying causes some food materials to heat up quickly while other food materials heat up more slowly. Accordingly, it is believed that a major problem with MW heating is the uneven temperature distribution (Chandrasekaran et al., 2013). According to Vadivambal and Jayas (2010), adjusting the dielectric properties of food, using hybrid conventional and MW heating , controlling the food geometry and the spacing can improve the heat distribution. In addition, heating with lower MW power can be used for longer periods of time to reduce the heating unevenness during MW heating process (Vadivambal and Jayas, 2010). 54 Figure 3.8.9. Infrared imagery showing the temperature distribution of red chili peppers drying at 120W for 5, 25, and 45 minutes. Figure 3.9.10. Infrared imagery showing the temperature distribution of red chili peppers drying at 240W over 3 to 18 minutes. 55 When drying various fruits and vegetables, uniform temperature distribution is still a problem. Joardder et al. (2013) used thermal imaging to observe the temperature distribution in apples and found that uneven heating changes the texture and color. Cui et al.. (2005) examined carrot slices and found that there were three different drying times and a uniform temperature distribution for thicknesses of less than 8 mm. Lu et al.(1999) reported similar findings for potato slices, with temperature increasing as moisture content decreased. Singh et al. (2020) developed a computer model to predict the temperature distribution of potatoes at different microwave power levels and drying times. Each study emphasized how critical temperature distribution is to drying efficiency and product quality. Factors influencing temperature distribution include sample thickness, MW power and moisture content. Understanding these relationships can help improve MW drying processes and predict the quality and microbial safety of the final product. 3.3.5.2. Impact of MW drying on Salmonella survival Recent studies have explored various drying techniques for inactivating pathogens in food products. Hot-air drying at 104 °C and 135 °C was found to effectively reduce Salmonella in apple cubes, with Enterococcus faecium serving as a suitable surrogate (Grasso-Kelley et al., 2021). Additionally, steam treatment of broiler feed mash demonstrated Salmonella reduction, with D- values varying based on moisture content and temperature. E. faecium ATCC 8459 was identified as a suitable surrogate for on-site challenge tests (Steghöfer et al., 2020). Although, previous studies have shown interest in inactivating pathogens in low-moisture foods using MW-based technology, there is knowledge gap on Salmonella reduction during MW drying. The results from this study indicate that S. Montevideo are resistant during MW drying of chili peppers (Figure 3.10). The S. Montevideo inactivation across the treatment time was 2.16 and 2.03 log10 CFU/g for 240W and 120W, respectively. 56 (A) (B) Figure 3.10.11. S. Montevideo populations in fresh red chili peppers and the aw change during MW drying at (A) 120W and (B) 240W. The final aw range at the end of drying was between 0.4 and 0.6 due to drying non- uniformity during the process. Higher MW power resulted in lower Salmonella survival over time (P < 0 .05). The results showed a steady decline in Salmonella population and aw as drying time increased at 120W. This suggests that the drying process is slower at a lower MW power (120W), allowing for a consistent reduction in microbial load and moisture content. At 240W, a faster decrease in both parameters was observed within a shorter period of time. This shows that higher 57 MW powers can significantly accelerate the drying process, resulting in a faster reduction in Salmonella population and aw. Studies have shown that Salmonella can survive for months or even years under dry conditions, depending on the storage temperature (Hiramatsu et al., 2005; Gradl et al., 2015). It is crucial to achieve elevated temperatures at the beginning of the drying process to effectively reduce Salmonella populations (Buege et al., 2006). According to Hawaree et al. (2009), more intensive heat treatments may also be required to effectively destroy microorganisms during the drying process. Pucciarelli and Benassi (2005) demonstrated that MW heating effectively reduced Salmonella Enteritidis in raw poultry, with higher power levels achieving greater reductions. LiCari and Potter (1970) observed that while spray drying at commercial temperatures substantially reduced Salmonella in skim milk, however, it did not completely eliminate the pathogen. Phungamngoen et al. (2011) compared hot air drying, vacuum drying, and low-pressure superheated steam drying for cabbage, which achieved the highest Salmonella inactivation Although temperature is essential, other factor may affect the Salmonella thermal resistance during dynamic process such as MW drying. Li et al. (2014) found that local microenvironments in low- and intermediate-moisture foods significantly affected Salmonella survival and thermal inactivation. It has been observed that Salmonella can tolerate dry environments. Studies have also shown that Salmonella on dry surfaces can resist inactivation by dry heat (Gruzdev et al., 2011). Additionally, the type of inoculum used may influence how long Salmonella survives drying; Salmonella cultured on agar has been observed to survive longer than planktonic cells when stored in dry conditions (Bowman et al., 2015). Furthermore, lower 58 treatment air speed in the oven increased the survival of pathogens such as L. monocytogenes when drying apple slices (Randriamiarintsoa et al., 2024). Overall, MW drying alone does not guarantee a 5-log reduction, but it can be used as a mitigation strategy to reduce Salmonella levels in dried chili peppers. Lee et al. (2018) found that chlorine dioxide gas treatment followed by drying effectively reduced S. Typhimurium in chili peppers. Shirkole et al. (2020) demonstrated that combined MW-infrared heating successfully inactivated S. Typhimurium and Aspergillus flavus in paprika. Kim et al. (2017) showed that aqueous chlorine dioxide treatment followed by hot-air drying effectively eliminated B. cereus spores on red chili peppers. Ha and Kang (2013) reported that simultaneous near-infrared heating and UV irradiation achieved significant reductions in S. Typhimurium and E. coli O157:H7 in red pepper powder, primarily through cell envelope damage. In addition, a review of novel drying techniques, including supercritical CO2, microwave, and radio frequency drying, highlighted their potential for microbial control in fresh foods (Wang et al., 2023). All these studies emphasized the importance of maintaining product quality during treatment. These findings suggest that combined drying and inactivation methods can effectively reduce pathogen populations in chili peppers while preserving the sensory attributes. 3.3.5.3. Application of the model parameters in MW drying The application of the model parameters from the thermal inactivation kinetics in predictive model D (T, aw) of the dynamic process resulted in good prediction of Salmonella inactivation (Figure 3.11, RMSE= 0.69-0.73 log(CFU/g)). As expected, the global model parameters (D67℃ = 14.42 min, zT = 15.72, and zaw = 0.343) predicted the Salmonella inactivation during MW drying of fresh red chili peppers. Although temperature distribution is known to be a problem in MW heating, the model was able to provide a satisfactory prediction of the 59 experimental data using the product surface temperature and aw data. For instance, the RMSE for 120W and 240W are 0.69 and 0.70 log10 CFU/g, respectively. Casulli et al. (2021) evaluated multiple primary and secondary models describing Enterococcus faecium lethality during dry roasting of peanuts, considering factors such as temperature, moisture content, and aw. Combining the modified Bigelow model with the primary log-linear model produced acceptable predictions of Salmonella inactivation under dynamic temperature and moisture conditions, such as MW drying of chili pepper. During MW drying, the models exhibited non-logarithmic linearity behavior as a function of aw. For both MW power (120W and 240W), the data showed log-linear models at higher temperature and aw values at the beginning of the drying process, and a tailing effect was observed at lower temperature and aw values. Mattick et al. (2001) found comparable trends for the inactivation of S. Typhimurium DT104 at aw = 0.9 across a temperature range of 55, 70, and 80 °C. It was observed that the steepness of the curve increased with temperature and the tailing effect decreased at higher temperatures. Humpheson et al. (1998) pointed out similar biphasic thermal inactivation kinetics of Salmonella, linking the tailing effect to the heat shock protein synthesis. In addition, Wang et al. (2024) highlighted the importance of uneven spatial distribution of spores and plasma and presented a lattice model based on percolation theory (as described by Boettcher et al. (2012)) to explain tailing in cold atmospheric plasma sterilization. Therefore, the nonuniformity of temperature and heat shock protein syntheses could potentially explain the presence of tailing during Salmonella inactivation kinetics during MW drying of chili peppers. 60 (A) (C) RMSE= 0.6932 RMSE= 0.7315 (B) RMSE=0.7012 Figure 3.11.12. Predicted and observed Salmonella survival during MW drying at (A) 120W, (B) 240W and (C) combined. 3.3.6. Significance of considering moisture condition in pathogen inactivation models Food drying is a common example of a multivariable, nonlinear, dynamically complex process that requires a lot of control and results in increased time-efficiency and mass change. Min et al. (2002) demonstrated that increasing aw enhances the effectiveness of pulsed electric field treatment in inactivating Enterobacter cloacae in chocolate liquor. Lang et al. (2017) developed models for heat inactivation of foodborne pathogens in milk powder, emphasizing aw as a crucial parameter in thermal decontamination. Carlson et al. (2005) found that decreasing meat aw from 61 0.99 to 0.95 reduced the rate of Salmonella thermal inactivation by 64% in ground turkey. Smith (2014) investigated thermal resistance of Salmonella in wheat flour, concluding that product aw at the time of thermal treatment, rather than desiccation or hydration history, determines pathogen resistance. Hildebrandt et al. (2024) demonstrated that single-level moisture-based prediction models, which resulted in overestimation of Salmonella lethality in baking of crackers, are inappropriate for describing inactivation in dynamically changing temperature and moisture. These studies collectively underscored the importance of considering aw in pathogen inactivation models, as it significantly influences the effectiveness of various decontamination methods across different food matrices. 3.4. Summary and Recommendations The use of small food samples in sealed test cells with constant aw to estimate Salmonella inactivation parameters under nonisothermal conditions gave good results in predicting a different MW-drying process, where both temperature and aw were changing simultaneously. This research showed that the Salmonella inactivation during MW drying of fresh chili peppers was described by the modified Biglow-model considering aw, using the global model parameters : D67℃ = 14.42 min, zT = 15.72, and zaw = 0.343. It is noteworthy that higher MW power levels do not necessarily lead to a greater inactivation of foodborne pathogen. Our study found that there is no significant difference in Salmonella reduction at the end of MW drying at 120W and 240W. Although higher MW power results in faster drying rates and shorter drying times, it is associated with low penetration, uneven internal temperature and moisture distribution (An et al., 2024). In addition, Motevali et al. (2011) found that as MW power increases, energy loss increases and energy efficiency decreases. Furthermore, the majority of current MW drying research is conducted in laboratory settings. Broadly speaking, it is best to treat the energy efficiency measured in 62 laboratory and energy efficiency measured at an industrial scale differently. There is limited data available about the industrial use of MW drying. The current study’s results hold promise that adequately designed, nonisothermal experiments can help predict commercial conditions. Future studies should focus on addressing the challenges faced by MW drying technology, including uneven heating, low penetration and control difficulties in achieving widespread implementation. To develop a predictive model for pathogen inactivation in dynamic process systems, it is recommended to consider the dynamic actual temperature conditions, dynamic product moisture conditions and other relevant data in the model. Simultaneous single-stage nonlinear regression for parameter estimation offers following advantages over two-stage regression: (1) accurate description of dynamic commercial processes because it uses the entire temperature history rather than assuming a constant temperature, (2) simpler experimental setups without immediate heating of the product, and (3) fewer experiments may be required for similar or greater accuracy. However, disadvantages may include problems with the convergence of nonlinear regression parameters, an increase in mathematical complexity, and the inability to recognize the shape of the dependent variable under constant conditions (Dolan and Mishra, 2013). Examples of non- isothermal experiments are explained in the following model categories. 63 CHAPTER 4: IMPACT OF SPECIFIC MICROWAVE POWER INPUT ON COLOR, ANTIOXIDANT ACTIVITY AND PHYSICOCHEMICAL PROPERTIES OF RED CHILI PEPPERS 4.1. Introduction Microwave (MW) drying has emerged as a significant technology in the food industry, offering advantages over traditional convective drying methods. It provides faster processing times, improved product quality, and increased energy efficiency (Wray and Ramaswamy, 2015; Kumar, 2015). The technique utilizes electromagnetic waves for volumetric heating, resulting in reduced drying times and enhanced convenience for consumers (Kumar, 2015). MW-convective drying combines MW and convective heating, further improving drying efficiency and food quality (Kumar and Karim, 2019). Recent research has focused on mathematical modeling and experimental investigations to optimize process parameters and scale up the technology for industrial applications (Kumar and Karim, 2019). While MW drying shows promise in preserving food materials and meeting modern consumer demands, further research is needed to address challenges and fully realize its potential in commercial settings. Red chili peppers have significant importance in the food industry due to their diverse properties and applications. They are widely used as flavoring agents and natural preservatives, owing to their antimicrobial and antifungal properties (Omolo et al., 2014). Chili peppers are rich in vitamins, minerals, and bioactive compounds like capsaicinoids, carotenoids, and phenolics, which contribute to their antioxidant, anti-inflammatory, and chemopreventive effects (Idrees et al., 2020; Pinto et al., 2013). These functional properties make chili peppers valuable in food, pharmaceutical, and cosmetic industries. The impact of drying techniques on the total phenolic content, antioxidant activity, and functional attributes of red chili peppers is a crucial area of research in food science and flavor 64 development. Several studies have reported the effects of different drying methods on the quality of red chili peppers. For example, Zhou et al. (2016) observed that the antioxidant capacity of red pepper during the drying process was associated with a decrease in total phenolic compounds and capsaicinoids (Zhou et al., 2016; Ajuebor et al., 2022) highlighted those drying treatments preserved the protein and carbohydrate contents in dried chili peppers while reducing the microbial load to acceptable levels (Ajuebor et al., 2022). Additionally, Yap et al. (2022) found that although the total flavonoid contents decreased during drying, both the total phenolic contents and capsaicinoids increased at higher temperatures. MW-assisted drying of food products offers significant advantages over conventional hot air drying, including reduced drying time and improved quality attributes. MW drying can decrease drying time by up to 80% for various fruits and vegetables (Askari et al., 2009). MW drying tends to increase product porosity and prevent color damage during the process (Krokida and Maroulis, 1999). While MW drying generally enhances optical, mechanical, and rehydration properties for most fruits and vegetables, some products like mushrooms may experience negative effects (Askari et al., 2009). Therefore, careful control of MW power is crucial, as high power can lead to charring (Ahrné et al., 2007). This chapter investigates the quality, antioxidant and physicochemical properties of dried chili pepper under different MW energy inputs and compares with conventional drying methods. 4.2. Materials and Methods 4.2.1. Materials Fresh red chili peppers (Capsicum annuum) were procured from Webstaurant (Lititz, PA, USA). The samples were carefully selected based on maturity and inspected for defects, followed by a thorough washing process. Subsequently, they were stored at - 4°C until processed. 65 For the study, various analytical grade chemicals and reagents were obtained from Sigma- Aldrich (St. Louis, MO, USA). These chemicals and reagents included 2,2′-azino-bis (3- ethylbenzo thiazoline-6-sulphonic acid) diammonium salt (ABTS), 2,2′-azobis(2- amidinopropane) dihydrochloride (AAPH), 2,2-diphenyl-1-picrylhydrazyl free radical (DPPH), 2,6 dichloro indophenol sodium salt dye, 6-hydroxy-2,5,7,8-tetramethylchroman-2-carboxylic acid (Trolox), ascorbic acid, β-carotene, fluorescein, Folin-Ciocalteu reagent, gallic acid, hexane, methanol, mono- and di-basic sodium phosphate, sodium sulfate and sulfuric acid.4.2.2. MW drying procedures. 4.2.2. Chili pepper drying 4.2.2.1. MW drying Before undergoing an array of drying processes, the fresh chili peppers were sliced longitudinally using a clean stainless-steel knife. For four different drying techniques, the sliced peppers were spread out on a single layer to dry. The chili pepper slices were dried in an LG 2450 MHz MW oven (LG Electronics, Denver, CO, USA) at five power levels (120W, 240W, MW 360W, MW 480W, MW 600W). These power levels corresponded to power densities of 3, 6, 9, 12, and 15 W/g of the chili pepper slices, respectively. The MW radiation interacted with the water molecules in the chili pepper slices, causing them to vibrate and generate heat, removing moisture through evaporation. The drying times and power-density/g for each power level (120W, 240W, MW 360W, MW 480W, MW 600W) were 45, 18, 13, 10.5 and 7 minutes and 3W/g, 6W/g, 9W /g, 12W/g, and 15W/g, respectively. After dehydration, the samples from treatments were pulverized using a grinder (Krups, Millville, NJ, USA) to traverse US Sieve No. 40 with a 0.5 mm mesh size and stored at -20°C in 3-mil polyethylene bags until analysis. 66 4.2.2.2. Hot air-drying In this drying method, the process was conducted in a cabinet convective-air food dehydrator (The Sausage Maker, Buffalo, NY, USA). The drying temperature was set to 60±2°C, which means that the temperature was maintained between 58°C and 62°C throughout the drying process. The hot air was circulated continuously within the dehydrator to ensure even drying of the chili pepper slices. The hot air-drying process took about 10 hours to complete, during which the chili pepper slices lost their moisture content through evaporation. 4.2.2.3. Vacuum drying Chili pepper slices were dehydrated in a vacuum oven (Cascade Sciences, Hillsboro, OR, USA). The temperature setting of the vacuum oven was set to 60±2°C, which is the same temperature range as the hot air-drying method. However, the vacuum pressure inside the oven was set to 700 mm Hg, which is equivalent to approximately 93.3 kPa or 0.93 bar. The lower pressure inside the vacuum oven facilitated the removal of moisture from the chili pepper slices by lowering the boiling point of water. The vacuum drying process took a total of 8 hours to complete, during which the chili pepper slices lost their moisture content through evaporation under reduced pressure conditions. 4.2.2.4. Infrared (IR) drying Chili pepper slices were dried using a custom-designed infrared heating equipment including two 40-watt infrared lights installed on an adjustable assembly for height. The samples were put beneath the infrared lights in circular metal trays so they would receive a homogeneous treatment. The distance between the samples and the IR heat source was maintained at ~11 cm. The infrared drying process took a total of 4 hours to complete, during which the chili pepper slices 67 were subjected to infrared radiation, causing the water molecules within the slices to vibrate and generate heat, leading to the removal of moisture through evaporation. 4.2.2.5. Freeze drying A Harvest Right pilot-scale freeze dryer was used to freeze-dry slices of chili peppers (Salt Lake City, UT, USA). The freeze-drying process involved setting the chamber vacuum to a low pressure of 0.05 torr, which is equivalent to approximately 0.067 millibar or 0.067 hectopascals. Additionally, the condenser temperature was set to ‒48.8°C, which is a temperature low enough to freeze and sublimate the water content from the chili pepper slices. The freeze-drying process took a total of 11 hours to complete, during which the chili pepper slices were dried through the process of sublimation, where the frozen water in the slices directly transitioned from a solid state to a gaseous state, bypassing the liquid phase. 4.2.3. Moisture content and drying kinetics The following equation (Getahun et al., 2021) was used to determine the moisture content of red chili peppers at each drying time: (4.1) where W(t) is the weight of moisture at each time point (g), Wd is the weight of the dry matter (g), and Md is the moisture content on a dry basis (%). The moisture ratio (MR) of the chili was calculated as follows: (4.2) where Me is the product's equilibrium moisture content, Mo is its initial moisture content, and M is the product's instantaneous moisture content. According to Evin (2012), the moisture ratio 68 ()tdddWWMW−=MReoeMMMM−=− can be expressed as Md/Mo, where here Me is smaller than M and Mo for longer drying times. One way to report the drying rate (DR) is as follows: (4.3) where t is the drying time, Mt and Mt+1 are the moisture content at t and moisture content at t+1, respectively. 4.2.4. Color evaluation of chili peppers The instrumental color of the chili peppers was measured with a Spectrophotometer (ColorFlex EZ, HunterLab, Reston, VA) both prior to and following drying. L-lightness, a-redness, and b-yellowness, which are measured CIELab parameters, were used to quantify this evolution. Prior to taking measurements, the colorimeter instrument was calibrated using a white and a black standard tile consecutively. For all treatments, approximately 10 g of chili peppers was measured twice, and the mean values were noted. From the Hunter L*, a*, and b* values, total color difference (ΔE*), hue angle (ho), and chroma (c*)values were computed using the following formulas (Lozano and Ibraz, 1997): (4.4) (4.5) (4.6) To measure the browning index (BI) in red pepper, the method described by Lee et al. (1991) was used. Water-soluble pigments were extracted from 100 mg of dried red chili pepper with 50 mL of distilled water. The mixture was axially shaken at 25 °C for 2 hours. The resulting solution was then centrifuged at 25 °C and 8,000 rpm for 8 minutes. To remove suspended 69 1DRtttMMM+−=222(*)(*)(*)ELab=++()1*Hue Angle *obhtana−=()()()22Chroma C * *ab=+ particles, the supernatant was filtered through Whatman number 4 filter paper (pore size 20–25 μm). Finally, the absorbance of the filtrate was measured at 420nm using a spectrophotometer. 4.2.5. ASTA color value The American Spice Trade Association (ASTA) color value was measured using the AOAC method with a small modification (AOAC-Method-971.26 2000). The dried chili pepper (~0.1 g) was extracted with 20 mL of acetone and then shaken in a water bath at 25 °C and 140 rpm for 3 hours. Furthermore, the extract was diluted 5 times with acetone and the absorbance was measured at 460 nm. The ASTA color value was determined using the following equation: (4.7) where If is a correction factor for the apparatus, obtained by dividing the theoretical absorbance of standard color solution by its actual absorbance at 460 nm. 4.2.6. Texture (hardness) measurement The textural properties of red chili peppers were evaluated using a TA.XTplusC Texture Analyzer (Stable Micro Systems, Godalming, UK). Cylindrical samples were subjected to a double compression cycle using a 2 mm diameter cylindrical probe. The analysis parameters were set to a pre-test speed of 2.5 mm/second, a 12 mm compression distance, a 15 g trigger force, and the measurements were performed in triplicate. The textural attribute quantified included the force needed to puncture the chili pepper skin referred to as hardness. This instrumental approach provided an objective characterization of the textural characteristics of the red chili pepper samples under different drying procedures. The hardness values were expressed in Newton force (N-force). 4.2.7. Loose and packed bulk density measurement The loose and packed bulk density of dried red chili pepper was measured using the method described by CRA (1998) with modification. A 100 mg sample of dried red chili pepper was 70 460*16.41*ASTA color value ()AbsorbanceatnmIfSampleweightg= transferred to a 10 mL graduated cylinder and its volume recorded before and after compaction (i.e., tapping for 5 seconds).4.2.9. pH measurement 4.2.8. pH The pH value of samples of dried red chili powder was determined using an Oakton pH meter (Eutech Instruments, Singapore). For sample preparation, 0.25 g of the dehydrated red chili pepper powder was accurately weighed and dissolved in 25 mL of distilled water. Prior to measuring the pH, the pH meter was calibrated with different pH buffers according to the manufacturer's instructions to ensure accurate readings. The prepared sample solution was then analyzed by immersing the pH electrode into the solution, and the pH value was recorded once the reading stabilized. All measurements were performed in triplicate to ensure reproducibility and reliability of the results. 4.2.9. Total phenolics The method established by Singleton and Rossi (1965) was followed to determine the total phenolics. Briefly, 20 mL of methanol-80 were combined with chili powder (~1g), and the mixture was shaken on a water-bath shaker for one hour before being centrifuged at 10,000 × g for ten minutes. After centrifuging (10,000 × g for 5 minutes) and vortexing (1 minute) with 10 mL of methanol-80, the residues were extracted twice from the supernatant. Following a combination of the three supernatants, phenolics were measured and the findings were represented as mg gallic acid equivalent (GAE), as mg GAE/100 g. 4.2.10. Antioxidant properties The procedure for extracting samples for antioxidant analyses stayed the same as that used for total phenolics (Figure 4.1). For all the tests that followed, antioxidant capabilities were represented as μmol Trolox equivalent (TE)/g db. 71 4.2.10.1. ABTS assay According to Re et al., 1999, the ABTS+ radical cation decolorization experiment was slightly modified to evaluate the ABTS antioxidant activity of chili powder. Briefly, ABTS radical cation (ABTS+) stock solution was created by mixing a 7 mM ABTS solution with 2.45 mM potassium persulphate in a 1:1 ratio and letting the mixture stand in the dark for 12–16 hours. Methanol-80 was added to this solution to dilute it until the absorbance at 734 nm was 0.700±0.020. Six minutes after mixing 30 μL of the sample, standard, or blank with 3 mL of the ABTS+ working solution, a spectrophotometer was used to measure the absorbance at 734 nm. Methanol-80 was used to run the blank, and 0.3–1.5 mM Trolox solution was used to create a standard curve. 4.2.10.2. DPPH assay For the DPPH radical scavenging activity assessment of chili peppers, the DPPH solution in methanol was used in accordance with the procedure described by Brand-Williams et al. (1995). In brief, ten parts methanol-80 were combined with one part stock solution of DPPH (0.24 g/100 mL methanol) to create a working solution that had an absorbance of 1.10±0.02 at 515 nm. After blending 0.6 mL of blank, standard, or sample mixture with 3.0 mL of DPPH working solution, the mixture was placed in the dark for 20 minutes, and the absorbance at 515 nm was measured. The methanol-80 blank was utilized to compute the radical scavenging activity through the use of a standard curve made using a 50–250 μM Trolox solution. 4.2.10.3. FRAP assay Benzie and Strain's (1996) protocol was used to evaluate the ferric reducing ability of the chili peppers after drying. Stock solution combining 10 mM TPTZ solution, 20 mM FeCl3⋅6H2O solution, 300 mM acetate buffer in 40 mM HCl was prepared. TPTZ solution, ferric chloride 72 solution and acetate buffer were combined at a 10:1:1 ratio to create a fresh working solution. After mixing 0.3 mL of the working solution with 3 mL of the blank, standard, or samples, the mixture was incubated for 5 minutes, and the absorbance was measured at 595 nm. The blank and standard curves were prepared using Methanol-80 and Trolox (50–250 μM), respectively. Figure 4.1.13. Flowchart of the experimental procedure for antioxidant properties, total carotenoids, and total phenolics. Source: Gonçalves et al. (2020) 73 4.2.11. Capsaicinoids For capsaicinoid extraction, 5 mL of methanol was added to a 10 mL vial containing a dried chili pepper sample (∼0.25 g). After the suspension was sonicated for 20 minutes in an ultrasonic bath, it was centrifuged for 10 minutes at 18,000 × g and 1°C. The extracts were then passed through a Millipore nylon filter with a pore size of 0.45 μm (Bedford, MA, USA).A procedure based on spectrophotometry was used to verify whether capsaicinoids were changing during the drying treatments (González-Zamora et al., 2015). Because of their similar molecular structures, the maximum absorption wavelengths of 280.8 and 279.6 nm for capsaicin and dihydrocapsaicin, respectively, are nearly identical, which makes identification of capsaicin rather difficult. 4.2.12. Statistical analyses All experiments were performed with 3 replicates. JMP 9.0 software (SAS Institute, Inc., Cary, North Carolina, USA) was used for data analysis. To evaluate how drying methods affected the physico-chemical and antioxidative qualities of chili pepper powders, one-way analysis of variance (ANOVA) was used. Tukey's HSD test was utilized to do significant difference comparisons, with a statistical significance threshold of P < 0.05. 74 4.3. Results and Discussion 4.3.1. Moisture content and drying kinetics The drying kinetics curve of red chili peppers is shown in Figure 4.2. As the drying time increased, the moisture content progressively decreased until it reached 2 percent (dry basis). Drying times for the different drying techniques ranged from 7 to 680 minutes (Figure 4.2), with MW drying at 600W and hot-air drying (HD) giving the lowest and highest drying times, respectively. Compared to HD (680 min), the drying time of MW drying at 120W was almost 90%shorter (70 min). The moisture was removed more quickly because the MW was able to increase the temperature of the material by promoting vibration and friction of the water molecules. MW drying is a quick and effective way to remove moisture from food. These results suggested that using a MW can dramatically reduce drying time compared to traditional methods. For example, one study found that combining MW and hot-air drying reduced drying time by 80-90%, resulting in a higher quality end product. Additionally, MW drying can help maintain food quality while reducing overall drying time. (Mazı and San, 2023; Altan and Maskan, 2005; Hazervazifeh et al., 2016). Drying rate curves generated by different MW powers, ranging from 120W to 600W are shown in Figure 4.3. The kinetics of drying red peppers showed that the moisture content decreased rapidly at the beginning of the MW drying process and then progressively decreased until drying was completed. Statistical analysis showed that the drying rate was the same for all other MW powers in the range of 120W to 600W. In fact, the moisture content of red peppers dried at 240W power had stabilized at 20.49 percent after 18 minutes. It was notable to observe that the drying process stabilized at an average moisture content of 10% at MW powers of 360W, 460W and 600W after 6 minutes, 7.05 minutes and 10 minutes, respectively. As shown in Figure 4.3, the 75 drying time of red peppers decreased with the amount of energy input (Appendix Table A.3). The results were consistent with those reported by Kumar et al. (2014) had discovered. which showed that as MW power increased, the time it took for ginger slices to reach moisture balance decreased (6%). It should be noted that 120W and 240W were the best power settings for drying red peppers as there is little to no burning of the dried product. The results of the research showed that using a MW can significantly reduce the time needed to dry materials to equilibrium moisture content compared to using a traditional method. MW drying works on a different principle than heat source drying. Conventional drying involves the transfer of heat to the material's surface via conduction, convection, radiation, and/or internal conduction. MWs are used to dry materials by penetrating the material and interacting with polar molecules such as water. Due to their dipolar nature, water molecules rotate in the direction of the very high-frequency alternating electric field. This rotation causes heat to be generated inside the material due to the friction of the molecules. Because food contains a lot of water, MWs can produce a large amount of volumetric heat. Warm water accelerates the rate of diffusion and creates a pressure gradient that makes it easier to expel moisture from inside a material. Advantages of MW drying over convection drying included 25 to 90% faster drying times and 4 to 8 times faster drying rates. The direct interaction of energy with water molecules makes MW drying efficient because it reduces the need to transfer heat from the surface of the product to its interior. This effect increases the driving force for moisture transport by creating increased internal vapor pressure directed outward (Feng et al., 2012). 76 Figure 4.2.14. Moisture ratio curves of HD: (A) Hot-air drying, IR: Infrared drying and MW 120W and (B) MW 240W, MW 360W, MW 480W, MW 600W. 77 Figure 4.3.15. Drying rate curves of (A) HD: Hot-air drying, IR: Infrared drying and MW 120W and for (B) MW 240W, MW 360W, MW 480W, MW 600W. 4.3.2. Color quality Figure 4.4 shows how different MW power impacted the appearance and color of red chili pepper fruit. The apparent quality and consumer acceptance of dry foods are significantly influenced by the color attribute (An et al., 2022), including spices and seasonings. 78 Figure 4.4.16. Appearance of fresh and MW dried red chili peppers at different energy inputs. The color of red chili peppers could be assessed using the American Spice Trade Association's ASTA color value, which measures the extractable color of peppers and other oleoresins. Red chili pepper dried at lower MW power have higher ASTA color value, indicating better color retention. The lowest BI was observed at freeze-dried red chili pepper (0.10) followed by the sample dried with MW at 120W (0.13) (Table 4.1). Fresh red pepper fruits have L*, a* and b* values of 40.50, 37.57 and 42.75, respectively . Except for freeze drying , vacuum drying , and infrared drying, where the values increased, the L*, a*, and b* values of the dried sample decreased compared to the fresh sample. This can be explained by the changing pigment concentration and water content of the material during drying (Liu et al., 2022; Chen et al., 2017). When drying red peppers using different techniques, the color values L*, a* and b* showed significant differences (P < 0.05). The reason for the high L* value in vacuum drying could be due to the effective retention of carotenoids by the method. The primary pigment responsible for the red color of red pepper fruits are carotenoids, which are broken down by the heat treatment applied to them (Hnin et al., 2021). Overall, the best MW drying method for color preservation of red chili peppers is MW drying at 240W. Greater color quality degradation and higher browning index (BI) were observed for red chili pepper dried at higher MW power (480W and 600W).The total color difference (ΔE) indicates the degree of color deviation between fresh and dried samples. If ΔE was more than 5, it was 79 considered that there was a noticeable difference (Ann et al., 2022). The highest ΔE indicating the highest color loss was observed when MW drying at 600W whereas the lowest ΔE was shown for 240W MW power (Figure 4.5). Similarly, MW-dried sample at 600W presented the highest BI. For all treatments, the hue angle was around 0.6o which is characteristic of the color red. The highest value of chroma for the MW drying was observed at 240W indicating a high color intensity (Figure 4.5). Intermittent MW drying at lower power levels (150-300W) resulted in higher color quality for both organic and conventional sweet red peppers (Arslan et al., 2020). Table 4.1.5. Color properties of dried red chili peppers as affected by drying techniques. Drying method MW drying: 120W 240W 360W 480W 600W Traditional drying: Drying time (min) Hunter color values a* L* b* ASTA color value 45 18 13 10.5 7 36.95±1.37bc 36.13±1.76c 39.22±1.17cde 36.74±2.01c 31.23±1.01ab 26.84±1.38a 27.14±2.21a 35.17±3.65bc 64.22±5.82bc 40.66±2.01cd 67.66±5.66bcd 22.55±2.48b 25.99±2.89ab 46.30±7.01ab 43.98±7.06a 16.89±1.16a 19.81±1.65a 47.56±2.30a 16.86±11.01a 18.88±1.52a 240 660 480 600 39.67±0.70cd 46.67±1.50d 66.08±5.58bcd Infra-red 44.48±0.44d 44.71±0.23cd 74.75±8.52d Freez 76.09±5.15d 47.26±4.95d 44.38±1.13d Vacuum 37.69±8.31cd 73.82±3.05cd 36.59±4.56c Hot-air Data are mean±SD of 3 replicate. Mean sharing the same letters in the column (separately for MW and traditional drying methods) are not significantly different using Tukey’s HSD (P > 0.05). ASTA=American Spice Trade Association 44.53±1.29e 43.46±0.33de 45.46±3.92e 37.82±3.49cd 80 ) o ( e g n a l e u H 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 e u a v l a m o r h C 80 70 60 50 40 30 20 10 0 (A) c (C) bc abc abc a ab ab ab abc a h s e r F W 0 2 1 W 0 4 2 W 0 6 3 W 0 8 4 W 0 0 6 R I D F D V D H (B) bcd bcd b bcd cd d bc a a a b b b a a a a a a h s e r F W 0 2 1 W 0 4 2 W 0 6 3 W 0 8 4 W 0 0 6 R I D F D V D H (D) d cd bc ab a a a a a E Δ 40 35 30 25 20 15 10 5 0 0.8 0.7 0.6 0.5 I B 0.4 0.3 0.2 0.1 0 h s e r F W 0 2 1 W 0 4 2 W 0 6 3 W 0 8 4 W 0 0 6 R I D F D V D H W 0 2 1 W 0 4 2 W 0 6 3 W 0 8 4 W 0 0 6 R I D F D V D H Figure 4.5. 17. Color characteristics of dried red chili peppers for different drying methods: (A) hue angle, (B) Chroma value, (C) Color change, and browning index (BI). 4.3.3. Texture (hardness) The hardness of the sample was indicated by the maximum force (Table 4.2). The area under the force curve and displacement was related to the work done by the puncture force. Hot- air-dried samples showed the highest hardness force values, which is attributed to the dense structure and surface hardening resulting from the adhesion force between cells that form a compact tissue after dehydration. The lowest hardness was found for 480W MW dried of samples (4.48 N-force), followed by 600W MW dried samples (4.62 N-force), 240W MW dried samples (5.5 N-force), 360W MW dried samples (6.3 N-force), however, hardness was not significantly 81 different across all samples. The hot-air dried samples were the only one that differed significancy in hardness as compared to 240W, 480W and 600 MW dried samples. MW-vacuum drying, especially when combined with far-infrared radiation, resulted in shorter drying times and better quality in terms of color, texture, and rehydration ability compared to MW-vacuum drying alone (Saengrayap et al., 2015). Table 4.2.6. Physico–chemical properties of red chili peppers as affected by drying methods. Drying method pH Hardness (N-force) Packed bulk density (g/mL) Loose bulk density (g/mL) MW drying: 120W 240W 360W 480W 600W Traditional drying: 5.08±0.04c 5.06±0.02bc 4.95±0.02ab 4.85±0.01a 4.95±0.07ab 9.84±1.96ab 5.50±0.73a 6.31±0.11ab 4.48±1.09a 4.63±0.68a 0.43.±0.01d 0.43±0.02d 0.33±0.00ab 0.33±0.01ab 0.36±0.04bc 0.5±0.02c 0.54±0.01c 0.39±0.02ab 0.38±0.01ab 0.43±0.02b Infra-red Freeze Vacuum Hot-ai 0.53±0.01c 0.34±0.03a 0.37±0.01a 0.49±0.02c Data are mean±SD of 3 replicate. Mean sharing the same letters in the column (separately for MW and traditional drying methods) are not significantly different using Tukey’s HSD (P > 0.05) 5.22±0.03de 5.22±0.05de 5.23±0.02e 5.32±0.05e 8.79±1.77ab 9.52±2.05ab 9.74±0.72ab 11.2±4.79b 0.44±0.03d 0.28±0.03a 0.29±0.02ab 0.42±0.02cd 4.3.4. Loose and packed densities Red chili pepper dried with MW at 240W showed the lowest loose and packed bulk density values (0.34 and 0.28 g/mL, respectively), suggesting a lighter product (Table 4.2). In contrast, other drying methods resulted in higher bulk density values, possibly due to significant shrinkage during the drying process. The bulk density of MW ranged between 0.33-0.43 g/mL and 0.38-0.54 g/mL for packed and look bulk density, respectively. A correlation can be drawn between bulk density (both packed and loose) and solubility, with lower density products demonstrating higher solubility (Sogi et al. 2013). After hot-air drying and grinding, the packed bulk density of hot pepper powder varied between 0.58–0 .52 g/m3 for 10 minutes drying at 80°C and 95°C, 82 respectively. The loose bulk density varied between 0.39 and 0.49 g/m3 at 85 °C and 90 °C drying for 10 minutes (Adamu et al., 2021). The bulk densities in the current study were similar to those documented in previous studies. According to Krokida and Maroulis (1999), MW-dried food products tend to have increased product porosity during the process. Kim et al. (2018) found that the freeze drying and MW drying showed higher solubility in chili pepper powder. The results indicate that the freeze-drying chili pepper and the sample dried at 600W MW power have the lowest bulk density, indicating high porosity and solubility. 4.3.5. pH The pH value of dried red chili peppers is a crucial factor for the shelf life and preservation. The pH range of the dried peppers was 4.85–5.32 (Table 4.2). The hot-air drying peppers had the highest pH, followed by vacuum-dried, frozen-dried, and infrared-dried samples. It was shown that different drying techniques had a significant impact on the pH of the final product (P< 0.05). The Maillard reaction between acid and proteins, which can be caused by the heat, could lead to a slight reduction in acidity. Based on statistical analysis, it was found that MW-dried red peppers had significantly lower acidity levels than traditionally dried samples (P > 0.05). The MW drying at 600W for dried peppers gave the highest pH, while the MW drying at 480W gave the lowest. Kim et al. (2018) reported similar finding while comparing different drying methods for chili pepper. Their results showed that the pH value of hot-air dried and freeze-dried chili pepper powder was 5.02 and 5.38 respectively, which were lower than that of the MW dried pepper powder (pH 5.44). Therefore, MW drying resulted in dried chili pepper with slightly lower acidic pH compared to other traditional drying methods. 83 4.3.6. Total phenolic content (TPC) Red pepper TPCs from five different drying techniques ‒ MW, infrared, hot-air, freeze and vacuum drying ‒ are shown in Figure 4.6. For fresh red peppers, the TPC ranged from 497.37±7.36 mg GAE/g dm to 530.07±27.32 mg GAE/g dm for dried red peppers. The highest levels of TPC were achieved by freeze drying and vacuum drying. For conventional drying, phenolic concentrations varied from 498.4±18.71 to 528±25.4 mg GAE/g. The TPC for MW drying showed fluctuations between 497.73±7.36 and 537±15.59 mg GAE/g for phenolic concentrations, with the highest TPC being achieved by MW drying at 240W. This variation in TPC could be attributed to changes in the temperature used in relation to the drying time. It was observed that since chili peppers dry rather quickly, raising the drying temperature can shorten the time they are exposed to heat; however, it also accelerates the breakdown of the bioactive ingredients. Based on TPC results from MW drying, it was observed that 120W of power produced a lower TPC. The findings show that TPC values rise to their maximum level as power is increased, reaching their maximum value at the highest MW powers (600W). When dried peppers are heated in the MW at high power (480W and 600W), there is an increase in TPC. This could be due to the formation of browning rather than bioactive compounds. Numerous studies have found that metabolites formed as a result of Maillard reaction upon heating can interfere with the measurement of phenolic compounds and the assessment of antioxidant activity (Pérez-Burillo et al., 2019; Navarro Mondaca et al., 2017). In ginger, MW drying at higher power levels (385W- 800W) increased TPC and antioxidant activity up to 1.5-fold compared to convective drying (Kubra and Rao, 2012). TPC elevated MW power may have increased because of the temperature and vapor pressure that MW produce, which may have broken down cell walls and released more 84 phenolic compounds that are easier to extract (Dong et al., 2019). For celery, coriander, and parsley leaves, MW drying significantly reduced drying time and generally maintained or improved phenolic content and antioxidant capacity, although optimal conditions varied depending on herb species (Mouhoubi et al., 2022). For clove tissue, MW drying was most effective in maintaining antioxidant and antibacterial properties compared to oven and air drying (Tan and Karim, 2018). The statistical analysis indicated the TPCs of the conventional and MW drying methods are not statistically significant (P > 0.05). Therefore, during MW drying, the total TPC of the red chili pepper are preserved to a greater degree even at higher MW power. a a a a a a a a a ) b d g g m / ( s c i l o n e h P . T 580 560 540 520 500 480 460 440 W 0 2 1 W 0 4 2 W 0 6 3 W 0 8 4 W 0 0 6 R I D F D V D H Figure 4.6.18. Impact of MW and conventional drying methods on the total phenolics of dried red chili peppers. 4.3.7. Antioxidant properties 4.3.7.1. ABTS assay The antioxidant properties of the dried red pepper samples varied for the ABTS assay and ranged from 164.3 to 203.8 μmol TE/g db (Figure 4.7). The MW dried sample at power levels 480W and 360W showed greater ability to scavenge ABTS radicals than the other samples. MW 85 drying had the lowest ABTS value, which was 120W. However, the use of heat during the drying process did not significantly change the ability of red pepper powder to scavenge ABTS radicals (P > 0.05). Le (2012) reported that the ABT scavenging activities of dehydrated mango ranged from 164.3 to 73.8 μmol TE/g db. According to Soong and Barlow (2004), the dried mango flesh had an antioxidant activity of 27.1 μmol/g db ascorbic acid equivalent. The values obtained for the Trolox equivalent of antioxidant capacity are within a narrow range of previously published results. Xu et al. (2020) also found that freeze drying and hot-air drying had the highest and lowest effects, respectively, on the antioxidant activity of cabbage. The ABTS radical scavenging capacity increased for freeze drying in contrast to the fresh sample. Xu et al. (2020) also found that the dried okra had a higher ABTS radical scavenging rate (97.22±0.39%) compared to the fresh sample (71.11±2.15%). One explanation could be that during freeze drying, the formation and sublimation of the ice crystals in the cell matrix led to cell destruction, which increased the content of extractable antioxidants. It is interesting to note that the antioxidant capacity and polyphenol content of tart cherries changed in a comparable manner under different drying conditions. It can therefore be concluded that the antioxidant potential of raw materials is mainly determined by the native content of polyphenols (Wojdyło et al., 2014). In addition, Deng et al. (2019) also showed that antioxidant activity and TPC were positively correlated. It can be concluded that the ability of dried chili peppers to scavenge ABTS was influenced by its total phenolic content. Another explanation could be that the genus Capsicum has high antioxidant activity, due to high content of carotenoids, ascorbic acid and α-tocopherol (Hanson et al., 2004). 86 4.3.7.2. DPPH assay The drying methods used had a significant impact on the antioxidant capacity determined by the DPPH radical scavenging capacity assay (Figure 4.7). Samples with 120W MW drying had the highest DPPH values, followed by samples from hot-air drying, freeze drying, and vacuum drying. Samples with 600W MW drying had the lowest ability to scavenge DPPH radicals. A lower DPPH value was observed with increasing MW power (P < 0.05). In powdered dehydrated red peppers, DPPH antioxidant activities ranged from 101 to 202.3 μmol TE/g db. (P < 0.05). A lower DPPH value was observed with increasing MW power (P < 0.05). According to Alam et al. (2013), the DPPH method evaluates the ability of an antioxidant to scavenge free radicals due to the reduction of metal complexes by antioxidants. Therefore, the primary antioxidant capacity in this work could be attributed to the natural antioxidants such as polyphenols, ascorbic acid, flavonoids and β-carotene. These natural antioxidants were broken down more easily at higher MW powers. This could also explain why the DPPH antioxidant levels of products MW-dried at higher power (360W, 480W and 500W) were lower than those using traditional methods. In traditional Mexican herbs, MW drying preserved antioxidant properties and inhibitory activity better than conventional drying (Jiménez-García et al., 2020). For Moringa oleifera leaves, MW drying at higher powers increased total phenolic content, DPPH radical scavenging activity, and quercetin content compared to conventional, sun, and infra-red drying methods (Potisate, 2015). Hence, the effects of MW drying on DPPH scavenging content appear to vary depending on the specific spice and drying conditions, with some spices showing improved retention of antioxidant properties while others experiencing losses. For red chili pepper, lower MW power drying presented similar DPPH value as conventional drying methods including freeze drying. 87 4.3.7.3. FRAP assay Statistical analysis showed that MW energy input has an influence on FRAP values (P > 0.05).The results of the study indicate that the chili pepper dried at 120W and 240W had strong antioxidant properties (Figure 4.7). The results of FRAP measurements of antioxidant activity covering a larger range of 200–1400 μmol TE/g have been reported. While the Trolox equivalent values of the FRAP were not as high as those of the ABTS or DPPH test methods, the overall trend was similar to the DPPHs. The higher MW powers (360W, 480W and 600W) were found to be the most damaging MW drying settings for the FRAP and DPPH values in chili peppers. The lowest FRAP value was obtained from the MW drying at 360W (201.9 μmol TE /g db). For fruits and vegetables such as tomatoes, mangoes, bananas, and pineapples, MW drying caused a 14–56% loss in FRAP values, which was higher than tunnel drying (6–13% loss) (Mongi et al., 2015). The vacuum-dried samples had the highest FRAP value at 1520.15 μmol/g db, followed by the freeze-dried samples at 1497.06 μmol/g db. Hence, the vacuum- and freeze-dried samples had the best FRAP value preservation. However, the MW-dried sample at 120W showed superior FRAP value than conventional drying methods for red chili peppers including infra-red drying, and hot-air drying. 88 ) b d g E T / l o m µ ( S T B A ) b d g E T / l o m µ ( H P P D 250 200 150 100 50 0 250 200 150 100 50 0 ) b d g E T / l o m µ ( P A R F 1800 1600 1400 1200 1000 800 600 400 200 0 (A) a a a a a a a a a W 0 2 1 W 0 4 2 W 0 6 3 W 0 8 4 W 0 0 6 R I D F D V D H (B) c c b ab a c c c c W 0 2 1 W 0 4 2 W 0 6 3 W 0 8 4 W 0 0 6 R I D F D V D H (C) cd b d d b bc a a W 0 8 4 W 0 0 6 a W 0 6 3 W 0 2 1 W 0 4 2 R I D F D V D H Figure 4.7.19. Impact of MW and conventional drying methods on dried red chili pepper antioxidant activity: (A) ABTS, (B) DPPH, and (C) FRAP. 89 4.3.8. Capsaicinoids content The total capsaicinoid content of red chili peppers using different methods were not significantly different (P < 0.05). Similar results were reported by Maurya et al. (2018), who found no differences in the capsaicin content of five varieties of fresh peppers compared to their blanched and sun-dried counterparts. However, according to Topuz and Ozdemir (2004), the capsaicinoids of pepper fruits decreased significantly after drying in the sun. Capsaicinoids can be lost during the drying process due to oxidation by peroxidase activity besides that heat used during drying (Bernal et al., 1993). It is believed that interference from other substances in the extract causes the spectrophotometric estimate of capsaicinoids to be erroneous. On the other hand, a previous study (Gibbs and O'Garro, 2004) found that colorimetric and chromatographic techniques of analyzing capsaicinoids showed an important level of agreement. Although spectrophotometric methods are somewhat less accurate and repeatable than HPLC measurements, these methods can still be used to determine the total amount of capsaicinoids, although their effectiveness is limited due to the presence of carotenoids and chlorophylls. Therefore, standardized and repeatable procedures are required for this type of testing (González-Zamora et al. 2015). 90 4.4. Summary and Recommendations It has been shown that MW drying can result in reduced drying times and high color retention of red peppers, indicating the potential to maintain the quality characteristics of the product. Overall, the chili peppers dried at low MW powers (120W-240W) exhibit better retention of color parameters and lower color probability. Higher ΔE values and BI were observed at high power levels (480W–600 W). Furthermore, MW power levels have been demonstrated to influence the bioactive properties and antioxidant capacity of red chili peppers. The results show that TPC and ABTS activity did not change significantly across drying methods. However, the antioxidant activities estimated by DPPH and FRAP assays were negatively affected by increasing WM power. By investigating the interplay between MW drying, drying kinetics, and the bioactive properties of red pepper, this study provides valuable insights to the field of food science. MW power density was found to play a key role in maintaining the color properties and antioxidant capacity of chili peppers during MW drying. Overall, MW drying with energy input (120W-240W) not only provided similar quality of dried chili peppers but also significantly shortened the drying time compared to traditional methods. Future work in this area could focus on examining the combined effects of MW-based drying and other novel processing techniques. For example, discover how the combination of MW drying, and high vacuum can lead to innovative approaches that improve product safety and quality. 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Food Research International, 45, 765-769. 114 APPENDIX Red chili pepper PROCESSING AND QUALITY EVALUATION MICROBIAL QUALITY EVALUATION Physical and chemical properties as affected by drying technologies Thermal inactivation kinetics of Salmonella and modeling kinetics g n i y r d r i a - t o H g n i y r d d e r a r f n I g n i y r d e z e e r F g n i y r d m u u c a V * g n i y r d e v a w o r c i M Inoculation aw equilibration (24-48 hours) aw = 0.33 aw = 0.50 aw = 0.97 Quality analyses C ° 0 6 C ° 5 6 C C ° ° 0 7 7 C C ° ° 0 0 6 6 C C ° ° 5 5 6 6 C ° 0 7 C ° 0 7 C ° 0 6 C ° 0 6 C ° 5 6 C ° 0 7 y t i c a p a c t n a d i x o ti n A t n e t n o c c i l o n e h P s r e t e m a r a p r o o C l s e s y l a n a w a d n a C M i s d o n i c i a s p a c l a t o t d n a H p y t i s n e d k l u b d e k c a p d n a e s o o L Salmonella enumeration Parameter estimation Model testing (forward problem) Figure A1.20. Flow diagram highlighting the analyses and data collection conducted during this study. 115 Table A2.7. Come-up time (CUT) and Salmonella reduction at CUT. aw 0.3 0.5 0.9 Temperature (℃) CUT (s) Initial population (log10 CFU/g) Log reduction at CUT (log10 CFU/g) 60 65 70 60 65 70 60 65 70 80 80 100 80 80 100 80 80 100 6.63±0.16 6.50±0.12 6.47±0.24 6.49±0.51 6.64±0.41 6.74±0.29 7.43±0.16 7.60±0.55 7.29±0.27 0.08±0.14 0.07±0.36 0.47±0.48 0.13±0.26 0.33±0.77 0.82±0.14 0.68±0.32 0.29±0.39 0.36±0.48 Table A3.8. Parameters for calculation of specific energy for MW drying. Power(W) Mass (g) Duration (min) 120 240 360 480 600 40 40 40 40 40 45 18 14 9 6 Specific energy (W.[g-pepper]−1) 3 6 9 12 15 116 HD IR MW 120W 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0 -0.1 0.2 0.4 0.6 0.8 1 Moisture ratio MW 240W MW 360W MW 480W MW 600W 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 i ) n m g ( / e t a r g n y r D i i ) n m g ( / e t a r g n y r D i 0 -0.1 0.2 0.4 0.6 0.8 1 Moisture ratio Figure A2.21. Moisture ratio curves and drying curves for Hot-air drying (HD), Infrared (IR) drying and microwave (MW) dryings. 117 (A) 70 ℃ at aw = 0.97 0 20 40 60 Time (s) 80 100 120 (B) 70 ℃ at aw = 0.5 0 200 400 600 800 1000 1200 Time (s) (C) 70 ℃ at aw = 0.3 ) C ⁰ ( e r u t a r e p m e T ) C ⁰ ( e r u t a r e p m e T ) C ⁰ ( e r u t a r e p m e T 80 70 60 50 40 30 20 10 0 80 70 60 50 40 30 20 10 0 80 70 60 50 40 30 20 10 0 0 1000 2000 3000 4000 5000 Time (s) Figure A3.22. Temperature-history of Salmonella inactivation at 70 ℃ at variable aw. 118 (A) 65 ℃ at aw = 0.97 0 50 100 150 200 250 Time (s) (B) 65 ℃ at aw = 0.5 0 500 1000 1500 Time (s) (C) 65 ℃ at aw = 0.3 ) C ⁰ ( e r u t a r e p m e T ) C ⁰ ( e r u t a r e p m e T ) C ⁰ ( e r u t a r e p m e T 70 60 50 40 30 20 10 0 70 60 50 40 30 20 10 0 70 60 50 40 30 20 10 0 0 2000 4000 6000 Time (s) Figure A4.23. Temperature-history of Salmonella inactivation at 65 ℃ at variable aw. 119 (A) 60 ℃ at aw = 0.97 0 100 200 Time (s) 300 400 (B) 60 ℃ at aw = 0.5 0 1000 2000 3000 Time (s) (C) 60 ℃ at aw = 0.3 ) C ⁰ ( e r u t a r e p m e T ) C ⁰ ( e r u t a r e p m e T ) C ⁰ ( e r u t a r e p m e T 60 50 40 30 20 10 0 60 50 40 30 20 10 0 60 50 40 30 20 10 0 0 2000 4000 6000 8000 Time (s) Figure A5.24. Temperature-history of Salmonella inactivation at 60 ℃ at variable aw. 120 Table A4.9 S. Montevideo reduction during TDT experiments at different aw. Temperature (⁰C) Time (s) aw 0.3 60 65 70 0.5 60 65 0 80 1580 3080 4580 6080 7580 0 80 1280 2480 3680 4880 6080 0 100 700 1300 1900 2500 3100 0 80 680 1280 1880 2480 3080 0 80 380 680 980 1280 1580 Survivors (log10 CFU/g) 3 2 1 6.8 6.5 6.5 6.5 6.6 6.6 5.7 6.0 5.5 5.3 5.6 5.0 5.1 4.9 4.9 4.2 4.0 4.6 4.1 4.7 LOD 6.6 6.4 6.5 6.6 6.1 7 5.6 5.5 5.7 5 5.1 5 4.5 3.8 4.2 4.1 3.3 2.8 3.6 3.3 3 6.5 6.7 6.2 6.4 5.7 5.8 5 5 3.6 4 3.6 2.8 2.4 3.4 1.9 3.5 3.4 3.2 1.9 2.7 LOD 6.5 6.0 7.0 6.5 6.0 6.6 5.3 6.0 5.3 4.9 4.1 5.0 5.3 2.8 4.3 LOD 3.2 3.8 LOD 2.2 2.9 6.2 6.8 7.0 6.4 5.6 6.9 3.6 4.4 6.0 3.8 4.4 5.9 2.8 1.8 5.5 3.9 3.6 5.3 3.4 2.4 LOD 121 Table A4 (cont’d) 70 0.9 60 65 70 0 100 280 460 640 820 1000 0 60 120 180 240 300 360 0 30 90 120 150 180 210 0 20 30 40 50 60 70 7.1 6.3 4.5 4.7 5.0 2.8 2.5 7.6 6.7 6.8 5.3 4.5 3.4 3.7 7.4 7.2 5.9 4.6 5.1 3.4 LOD 7.6 6.7 6.4 5.7 3.8 LOD 1.1 6.5 5.5 3.6 2.5 1.7 4.2 LOD 7.5 6.6 5.9 5.4 LOD 3.9 LOD 8.2 7.5 7.0 LOD LOD LOD LOD 7.3 7.0 5.4 4.9 3.5 2.3 LOD 6.7 6.0 5.8 5.5 4.7 4.6 LOD 7.3 6.2 5.5 5.3 4.1 2.4 2.1 7.2 7.2 6.9 5.2 4.4 LOD LOD 7.0 7.1 6.0 3.3 3.9 2.9 LOD 122 Table A5.10Lab-devived data collection for S. Montevideo reduction during MW drying. MW power (W) Time (min) 120 240 0 5 10 15 20 25 30 35 40 45 0 3 6 9 12 15 18 Population (log10 CFU/g) 2 1 7.8 7.8 5.6 6.1 6.1 5.4 6.3 6.0 5.6 5.2 4.1 5.5 4.8 6.1 4.5 5.4 5.7 4.6 5.5 4.7 7.9 7.8 5.8 5.5 5.2 5.7 6.1 5.2 5.7 5.7 5.6 6.0 3.7 5.5 3 7.6 6.4 6.5 6.8 6.7 6.3 5.4 5.5 6.8 4.7 7.8 6.6 5.9 6.0 6.4 5.4 4.6 Temperature (C) aw 1 3 3 2 2 24.5 77 1 24.5 0.980 0.977 0.981 24.5 74.6 63.3 0.983 0.996 0.992 73.2 63.75 74.4 0.977 0.982 0.994 55.9 65.06 56.8 0.924 0.981 0.973 62.7 71.97 65.6 0.979 0.980 0.952 58 54.39 61.5 0.795 0.853 0.904 66.5 59.56 61.2 0.857 0.740 0.786 60.2 57.11 58.9 0.792 0.683 0.439 53.8 50.72 50.8 0.715 0.581 0.643 56.8 51.47 52.2 0.603 0.453 0.497 0.980 24.5 77.2 67.17 81.5 0.974 0.996 0.997 76.7 0.966 0.982 0.983 67.1 0.904 62.8 69.06 65.5 0.881 74.3 62.67 70.3 0.822 0.712 0.581 67.1 63.25 69.8 0.807 0.456 61.7 68.61 51.1 0.344 0.605 0.496 0.58 24.5 0.98 0.98 24.5 0.92 77 123