IMPACT OF SEASONAL CHANGES IN PASTURE-RAISING SYSTEMS ON EGG NUTRITION By Rachel Van Duinen A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of Food Science—Master of Science 2025 ABSTRACT Pasture-raised egg production is increasingly recognized for its alignment with regenerative agriculture, emphasizing biodiversity, soil health, and ethical animal husbandry. These systems allow laying hens to forage on diverse plant species and insects, which can significantly improve the nutrient composition of eggs compared to conventional grain-based systems. However, the nutrient profile of pasture-raised eggs may fluctuate due to seasonal variation in forage availability, quality, and environmental conditions. This study aimed to evaluate how seasonal changes, specifically late spring through early winter, affect the nutrient density of eggs produced in a pasture-based system in Southern Ohio. Monthly collections of forage, soil, and eggs were conducted from May to December 2022. Nutrient composition of egg yolks was assessed using gas chromatography–mass spectrometry (GC-MS), liquid chromatography, spectrophotometry, and inductively coupled plasma optical emission spectroscopy (ICP-OES). Nutrients analyzed included carotenoids, vitamins A and E, total phenolics, and fatty acids. Findings revealed that forage quality, as measured by total digestible nutrients (TDN), peaked in October, aligning with increased deposition of omega-3 fatty acids and fat-soluble antioxidants in egg yolks during fall months. Principal component and random forest analyses identified September to November as the separated time period yielding the most nutrient-dense eggs. This research supports the role of pasture-raised systems in delivering nutrient-rich animal products and highlights the need for seasonal considerations in both consumer education and on-farm management strategies. This thesis is dedicated to my younger self. Rachel, you always have— and always will—carry the ability to accomplish greatness. iii ACKNOWLEDGMENTS I would first like to express my deepest gratitude to my advisor, Dr. Jenifer Fenton, for the incredible support and mentorship you’ve offered me. Thank you for taking a chance on me during my sophomore year of undergrad and again when welcoming me into your lab as a graduate student. Your guidance has been invaluable—not only in my academic and career development but also in helping me grow as a person. Your advice on professionalism, relationships, and life has shaped who I am today. I am beyond thankful for your mentorship, and I will deeply miss being a part of your lab family. I would also like to thank my committee members, Dr. Jason Rowntree and Dr. Emily Mayhew. Dr. Rowntree, thank you for pushing me to think deeper about my work and for providing guidance on the regenerative agriculture portion of my thesis. I am especially grateful for the opportunities you gave me to work on additional projects, where I was able to learn more about cattle systems, and the hands-on skills involved in farm-based research. Dr. Mayhew, thank you for your kindness, your help with my academic planning, and your thoughtful feedback on my thesis work. Also, I would like to thank Dr. Jennifer Ekstrom for providing me with strong academic guidance and for supporting me through my first teaching assistantship position. A heartfelt thank you to our collaborators at Greenacres and colleagues who helped make this project possible. Chad Bitler, thank you for facilitating this research and for your enthusiastic support. Jennifer Mansfield and the research team at Greenacres, thank you for collecting samples, sharing data, and ensuring safe transport of the eggs—your diligence and responsiveness were truly appreciated. We are extremely fortunate to have had such wonderful research partners. I would also like to thank Dr. Lucas Krusinski and Dr. Eric Gurzell for their guidance throughout this process. Dr. Krusinski, thank you for mentoring me through data analysis and iv scientific writing. Your feedback and the path you laid as a former Ph.D. student have helped shape my own journey—and will continue to help future graduate students. Dr. Gurzell, thank you for your consistent support in the lab, especially with GC-MS maintenance, and for letting me help teach senior students fatty acid techniques. Your day-to-day mentorship meant so much. To my friends and lab family—thank you. Selin, I am forever grateful for the two years you spent training me in lab methods, GC-MS, project management, and statistics. Your patience, mentorship, and friendship made all the difference in my success. Vanessa, thank you for guiding me through both undergrad and grad school and for being the big sister I didn’t know I needed. Julianna and Veronica—thank you for being the best homework buddies and friends. Julianna, you made grad school fun, and I loved doing research and traveling with you. Veronica, thank you for helping me with R and for supporting me during my teaching assistantship. Sidney and Kayla— thank you for your encouragement, lab support, and friendship. Lauren, thank you for your friendship, wisdom, and eagerness to learn. Mentoring you on your project made me a better student and a better educator. You’re all not just colleagues but lifelong friends and collaborators. I will miss our Dairy Store trips! To my parents—Mom (Nancy), Dad (David), and stepmom (Claudine)—thank you for your endless love and belief in me. To my sister Gabrielle, thank you for being my biggest supporter and for our long phone calls that always kept me grounded. To my brothers, John, William, and Bryce—thank you for always pushing me to do better. To my grandparents: Grandpa Wayne, thank you for showing me what true passion for science and teaching looks like. Grandpa Marvin and Grandma Ruth, thank you for always hyping me up, believing in me, and providing unwavering emotional and financial support. To my chosen family—Alyssa (Sheldon) and Makenna (Nadav)—thank you for always sticking by me. Your friendship carries me through each v day. Finally, to my boyfriend Emerson, you have been the most supportive partner I could ever ask for. When I was struggling, you stepped up—caring for our home, our kitties, and for me—so I could keep going, and I will always be grateful for your unwavering love and support. Thank you all. vi TABLE OF CONTENTS CHAPTER I: LITTERATURE REVIEW — NUTRITIONAL IMPLICATIONS OF PASTURE-RAISED EGG PRODUCTION ..........................................................................1 1.1 Introduction ..............................................................................................................1 1.2 How Pasture-Raised Eggs Align with Human Health .............................................2 1.3 Overview of Fatty Acids and Antioxidants in Egg Yolks .......................................4 1.4 Nutrient Differences Between Egg Production Systems .........................................6 1.5 Influences of Yolk Nutrition ....................................................................................7 1.6 Seasonal Variability in Pasture-Raised Egg Nutrition ...........................................10 1.7 Poultry Welfare and Environmental Considerations in Pasture Systems ..............12 1.8 Conclusion .............................................................................................................15 CHAPTER II: GRAZING SEASON IMPACTS THE FATTY ACID AND NUTRIENT PROFILE OF EGGS ON A SOUTHERN OHIO PASTURE-RAISING SYSTEM FOR LAYER HENS ........................................................................................................................18 2.1 Abstract ..................................................................................................................18 2.2 Introduction ............................................................................................................19 2.3 Materials and Methods ...........................................................................................21 2.4 Results ....................................................................................................................31 2.5 Discussion ..............................................................................................................47 2.6 Conclusions ............................................................................................................53 CHAPTER III: CONCLUSIONS AND FUTURE DIRECTIONS54 3.1 Conclusions ............................................................................................................54 3.2 Future Directions ...................................................................................................55 BIBLIOGRAPHY ..................................................................................................................57 APPENDIX: SUPPLEMENTAL INFORMATION AND DATA .....................................68 vii CHAPTER I: LITTERATURE REVIEW — NUTRITIONAL IMPLICATIONS OF PASTURE-RAISED EGG PRODUCTION 1.1 Introduction Eggs are one of the most widely consumed animal-derived foods globally and are a staple in many diets due to their affordability, versatility, and dense nutrient profile (Farrell, 2013; Headey & Alderman, 2019). They provide high-quality protein, essential fatty acids, fat-soluble vitamins, and carotenoids, making them an important dietary component for human health (Nimalaratne & Wu, 2015; Usturoi et al., 2025). Because eggs are a primary source of these essential nutrients, they have the potential to play a significant role in dietary modifications aimed at improving overall health outcomes (Cartoni Mancinelli et al., 2022; Headey & Alderman, 2019). The nutritional composition of eggs is influenced by various factors, including the hen's diet, production system, and environmental conditions (Lantzouraki, 2020). Research has shown that pasture-raised eggs, in particular, have enhanced fatty acid and antioxidant profiles compared to conventional eggs (Ben-Noun, 2019; Sergin et al., 2021). This improvement is especially relevant for correcting dietary imbalances in the modern American diet, which is often high in saturated fat and has an unfavorable n-6:n-3 ratio (Simopoulos, 2008). By focusing on improving the fatty acid composition of eggs through production methods, eggs could serve as a key food in dietary strategies aimed at reducing chronic inflammation and improving cardiovascular health (Mwai, 2021; Wang et al., 2024). Eggs from different production systems vary significantly in nutrient composition (Ben-Noun, 2019). Conventional egg production relies on grain-based diets, typically composed of corn and soy, which are rich in omega-6 polyunsaturated fatty acids (n-6 PUFAs) but lack beneficial omega- 3 (n-3) PUFAs and antioxidants (Clancy, 2006). In contrast, pasture-raised egg systems provide 1 hens with access to forage, insects, and diverse plant species, producing eggs with significantly improved nutrient profiles (Sergin et al., 2021). Compared to conventional eggs, pasture-raised eggs have been shown to contain twice the vitamin E content and up to 2.5 times more n-3 PUFAs, resulting in a more favorable n-6:n-3 ratio (Sergin et al., 2021). This is particularly relevant for cardiovascular health, as an excessive n-6:n-3 ratio has been linked to chronic inflammation and metabolic diseases (Simopoulos, 2008; Wang et al., 2024). 1.2 How Pasture-Raised Eggs Align with Human Health 1.2.1 Health Rationale The American diet is characterized by a high intake of saturated fat and an imbalanced n-6:n- 3 ratio, which has been linked to increased inflammation and chronic disease risk (Mariamenatu & Abdu, 2021; Simopoulos, 2008). Because eggs are widely consumed and serve as a staple protein source, they represent an ideal food for improving dietary fatty acid profiles (Ben-Noun, 2019). By enhancing the nutrient composition of eggs, specifically increasing omega-3 content and optimizing the n-6:n-3 ratio, producers can contribute to improved public health outcomes (Patel et al., 2022; Usturoi et al., 2025). By modifying feed and forage access, producers can create a more favorable lipid profile in eggs, offering a simple and effective dietary intervention to address nutritional imbalances in the modern diet (Patel et al., 2022). The bioavailability of these nutrients is crucial, as their dietary sources vary in absorption efficiency (Zaheer, 2017). Eggs, due to their high natural fat content, enhance the absorption of fat-soluble nutrients such as carotenoids (Schweiggert & Carle, 2017). This is because eggs contain a naturally high fat content, which facilitates the absorption of fat-soluble nutrients like carotenoids, whereas forage species, despite being rich in these compounds, lack sufficient fat content to optimize their bioavailability (Moreno et al., 2016; Ren et al., 2010). Therefore, 2 improving the nutrient content of eggs through hen dietary interventions can provide a more accessible and bioavailable source of these essential nutrients (Goldberg et al., 2016; Vlaicu & Untea, 2024). 1.2.2 Fatty Acids, Phytochemicals, and Human Health Fatty acids and phytochemicals found in eggs have distinct health benefits that support cardiovascular, neurological, and metabolic functions (Saidaiah et al., 2024). These compounds originate from different dietary sources and play key roles in biological processes, making them crucial for maintaining health. Fatty acids are essential components of cell membranes and play a fundamental role in energy metabolism and inflammatory responses (Simopoulos, 2008). Omega-3 fatty acids, including alpha-linolenic acid (ALA), eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA), are known for their cardioprotective effects, reducing triglyceride levels, lowering blood pressure, and supporting cognitive function (D’Angelo et al., 2020). ALA, primarily found in plant sources such as flaxseed and leafy greens, is converted in the body to EPA and DHA, although the conversion is limited (Management et al., 2023). EPA and DHA, which are mainly derived from marine sources, are crucial for brain development and neuroprotection (Simopoulos, 2008). In contrast, omega-6 fatty acids, such as linoleic acid (LA) and arachidonic acid (AA), are commonly found in vegetable oils and grains. While they are essential for inflammatory and immune responses, an excessively high n-6:n-3 ratio has been associated with chronic inflammation, emphasizing the importance of dietary balance (Harris et al., 2009; Oluwole et al., 2019). Carotenoids are pigmented compounds found in plants that function as antioxidants and serve as precursors to vitamin A (Zielińska-Dawidziak et al., 2024). Lutein and zeaxanthin, concentrated in leafy greens and egg yolks, play a critical role in eye health by reducing the risk of age-related 3 macular degeneration and filtering harmful blue light (Lantzouraki, 2020). β-Carotene, present in carrots, sweet potatoes, and forage plants, is converted into retinol (vitamin A), which is essential for immune function, vision, and cellular differentiation (Zielińska-Dawidziak et al., 2024). Unlike direct vitamin A sources, β-carotene requires enzymatic conversion, making dietary intake an important determinant of its bioavailability (D'Archivio et al., 2010). Phenolic compounds, including flavonoids and polyphenols, are bioactive compounds found in plant-based foods such as fruits, vegetables, and forage crops. Unlike carotenoids, phenolics are non-nutritive but exert significant health benefits through their antioxidant and anti-inflammatory properties (D'Archivio et al., 2010). These compounds protect cells from oxidative stress by scavenging reactive oxygen species (ROS), reducing the risk of chronic diseases such as cardiovascular disease and cancer (Sergin et al., 2022). A key factor influencing the bioactivity of these compounds is their dietary source and matrix. Pasture-raised eggs deliver a superior antioxidant and fatty acid profile due to hens' access to nutrient-dense forages rich in omega-3s, carotenoids, and polyphenols (Krusinski, Maciel, et al., 2022). As a result, pasture-raised eggs serve as a valuable dietary source of bioavailable fatty acids and phytochemicals, contributing to improved cardiovascular, cognitive, and metabolic health (Sergin et al., 2022). 1.3 Overview of Fatty Acids and Antioxidants in Egg Yolks Egg yolks contain a rich profile of fatty acids, antioxidants, and essential vitamins, all of which contribute to their nutritional value. The fatty acid composition of egg yolks is predominantly made up of monounsaturated fatty acids (MUFAs), which account for approximately 45% of total lipids, with oleic acid (C18:1) being the most abundant MUFA (Agriculture, 2019). Saturated fatty acids (SFAs) represent a slightly lower proportion, while polyunsaturated fatty acids (PUFAs), 4 including omega-6 and omega-3 fatty acids, make up the smallest fraction of total lipid content and is subject to variation (Agriculture, 2019). Among the omega-3 fatty acids present in egg yolks are alpha-linolenic acid (ALA), eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA). The proportions of these fatty acids vary based on the hen’s diet, with ALA typically being the most prevalent in pasture-raised eggs. On average, a conventional egg contains about 30–50 mg of total omega-3s, while pasture- raised or enriched eggs may contain upwards of 150–200 mg per egg, depending on feed composition and access to forages (Sergin et al., 2021; Sergin et al., 2022). DHA is particularly important for human health, and its concentration in enriched or pasture-raised eggs can range from 50–150 mg per yolk, compared to less than 20 mg in conventional systems (Sergin et al., 2021; Sergin et al., 2022). Egg yolks are a valuable dietary source of several fat-soluble nutrients, particularly carotenoids and vitamins A and E. According to USDA reference values, conventional egg yolks contain approximately 371 µg of retinol (preformed vitamin A) and 2.58 mg of vitamin E (α-tocopherol) per yolk. In addition, they provide a modest amount of provitamin A carotenoids, with a combined concentration of approximately 126 µg of total carotene (including β-carotene and α-carotene), which can be enzymatically converted into retinol in the human body (Agriculture, 2019). Small amounts of phenolic compounds may also be present, though these are typically limited due to their hydrophilic structure, which reduces deposition into the lipid-dense yolk matrix (Agriculture, 2019; Sergin et al., 2021). Cholesterol levels in eggs remain relatively stable, typically ranging from 180–230 mg per egg, regardless of dietary modifications (Attia et al., 2022). While feed modifications can influence 5 yolk fatty acid and antioxidant levels, cholesterol is regulated metabolically and not directly by diet (Vlaicu et al., 2021). Eggs serve as a nutrient-dense source of essential fatty acids, vitamins, and antioxidants, making them a key component of a balanced diet. However, their nutritional composition can be significantly influenced by modifying hen diets, particularly when they have access to forages rich in bioactive compounds. 1.4 Nutrient Differences Between Egg Production Systems While eggs naturally contain essential fatty acids, vitamins, and antioxidants, significant differences in nutrient composition have been observed between various egg production systems. Studies comparing conventionally produced, cage-free, organic, and pasture-raised eggs offer superior levels of omega-3s, carotenoids, vitamin A, and vitamin E (Oke & Onagbesan, 2013; Sergin et al., 2022). These differences are largely attributed to dietary access. Conventionally raised hens are typically fed corn- and soy-based rations, which are high in omega-6 fatty acids and low in omega- 3s—leading to an unfavorable n-6:n-3 ratio in the yolk. These eggs may contain as little as 30 mg of total omega-3s and a n-6:n-3 ratio exceeding 15:1 (Sergin et al., 2022). Cage-free and organic systems may incorporate minor dietary variations, but they do not consistently provide the forage access necessary to significantly enhance bioactive nutrient content (Bist et al., 2024; Nopparatmaitree et al., 2022). In contrast, pasture-raised systems allow hens to forage freely, granting access to a diverse range of plants, insects, and soil-based nutrients (Bist et al., 2024). Carotenoid-rich forage species, such as clover, alfalfa, and grasses, contribute to deeper yolk pigmentation, while access to fresh vegetation increases vitamin E concentrations (Krusinski, Maciel, et al., 2022). Notably, pasture- 6 raised is the only system that mandates outdoor access for hens, unlike cage-free or free-range models where such access is not always enforced (Humane, 2014). As a result, pasture-raised eggs often contain 2 to 3 times more total omega-3 fatty acids than conventional eggs (H. Karsten et al., 2010). In some cases, pasture-raised eggs contain over 100 mg of DHA per yolk, contributing to a significantly lower n-6:n-3 ratio, often approaching 2:1 to 4:1 (H. Karsten et al., 2010; Sergin et al., 2021; Sergin et al., 2022). Pasture-raised eggs have also been shown to contain over 60 µg/g of total carotenoids, compared to as low as 15 µg/g in conventional eggs (Sergin et al., 2021; Sergin et al., 2022). Vitamin E content was also markedly higher, with pasture-raised eggs containing up to 2 to 3 times the amount of alpha-tocopherol compared to conventional production systems (Sergin et al., 2021; Sergin et al., 2022). This distinction highlights the nutritional significance of studying pasture-raised eggs, particularly due to their hens’ enhanced access to natural dietary inputs (Sergin et al., 2022). As nutrient composition is strongly influenced by production system, pasture-based models offer a unique opportunity to improve egg quality through exposure to forage-rich environments (Cristea et al., 2024). By increasing access to bioactive compounds such as carotenoids, vitamin E, and omega-3 fatty acids, pasture-raising practices contribute to eggs with superior nutritional value and potential health benefits for consumers (Oke & Onagbesan, 2013; Zielińska-Dawidziak et al., 2024). 1.5 Influences of Yolk Nutrition 1.5.1 Diet is the largest influence of nutrient variations Compared to conventionally produced eggs, pasture-raised eggs have been shown to contain higher levels of omega-3 fatty acids, ALA, DHA, and EPA, as a result of the hens’ access to diverse forage species (Sergin et al., 2021). These beneficial fatty acids are primarily derived from 7 omega-3-rich plants such as clover and alfalfa, which are abundant in pasture environments (Javed et al., 2025). Hen diet remains the most critical determinant of egg nutrient composition. Commercial poultry diets, typically composed of corn and soybean meal, provide energy and protein but are deficient in omega-3 fatty acids and antioxidant compounds (Zielińska-Dawidziak et al., 2024) . In contrast, pasture-raised hens consume a variety of forage species that serve as natural sources of phytochemicals, enhancing the nutritional profile of their eggs. Forage plants such as clover, alfalfa, and mixed grasses are rich in bioactive compounds like carotenoids, polyphenols, and flavonoids. These act as antioxidants, protecting egg yolks from oxidative degradation and contributing to a superior nutritional profile (Lantzouraki, 2020). Carotenoids such as lutein and zeaxanthin, in particular, contribute to yolk pigmentation and serve as precursors to vitamin A, which supports vision and immune function (Dansou et al., 2023). Polyphenols, meanwhile, have been associated with anti-inflammatory activity and cellular protection against oxidative stress, potentially contributing to the enhanced health benefits of pasture-raised eggs (Sergin et al., 2022). In addition to forage-derived nutrients, hens may be provided with specialized supplemental feeds to further optimize egg composition. Standard layer rations typically include corn, wheat, and soybean meal, which provide protein and essential amino acids (Bist et al., 2024). However, feed additives such as flaxseed, fish oil, and microalgae are often incorporated to improve omega- 3 content. Flaxseed is a rich source of ALA, a short-chain omega-3 that can be endogenously converted to DHA and EPA, while fish oil and microalgae directly supply long-chain omega-3s (Javed et al., 2025; Panaite et al., 2021). Additional strategies to enhance egg quality include incorporating antioxidant-rich ingredients like marigold petals and red pepper into hen diets (Matache et al., 2024). These 8 ingredients are high in carotenoids and have been shown to increase their deposition in yolks, further improving pigmentation and nutritional value (Panaite et al., 2021). 1.5.2 Other Influence in Egg Production Beyond diet, factors such as hen breed, age, and laying cycle have been proposed to influence egg nutrient composition. While some studies have suggested that breed may affect omega-3 deposition and antioxidant content due to differences in metabolism or feed utilization efficiency, current evidence remains mixed (Attia et al., 2022; Kojima et al., 2022). Breed-specific effects appear to play a more substantial role in eggshell characteristics and production rate than in yolk nutrient composition (Henry, 2019). Hen age is another important factor. Younger hens typically produce eggs with higher concentrations of vitamins and essential fatty acids. As hens age, nutrient density in eggs tends to decline, likely due to age-related changes in nutrient absorption and allocation (Gao et al., 2021). Moreover, during the hen’s laying cycle, especially in its early stages, lipid metabolism is more efficient, contributing to richer yolk lipid profiles than those produced later in the cycle (Usturoi et al., 2025). Environmental factors such as temperature and seasonal variation significantly influence egg nutrient composition by affecting hen metabolism and nutrient allocation (Pawar et al., 2016). The optimal laying temperature for hens ranges between 16°C and 22°C. When temperatures rise above this range, heat stress often reduces feed intake, resulting in lower deposition of omega-3 fatty acids, antioxidants, and vitamin E in yolks (Saleh et al., 2021; Usturoi et al., 2025). Conversely, cold stress in winter redirects metabolic energy toward thermoregulation, compromising nutrient transfer to eggs (Evaris et al., 2019; Pawar et al., 2016). To mitigate these seasonal effects, 9 producers may adjust feed formulations throughout the year to help maintain consistent yolk quality. 1.6 Seasonal Variability in Pasture-Raised Egg Nutrition 1.6.1 Defining Seasonal Variations Seasonal variation significantly influences the nutrient composition of pasture-raised eggs due to fluctuations in forage availability, plant maturity, and environmental conditions. As in beef and dairy production, seasonal changes in pasture quality affect the fatty acid, antioxidant, and vitamin content of animal-derived foods, including eggs (Krusinski, Maciel, et al., 2022). These fluctuations are driven by plant growth stages, regrowth cycles, temperature, and precipitation, which collectively alter the nutrient density of the forages hens consume. Forage is most nutrient-rich in its early growth stages, when leaf-to-stem ratios are high, resulting in greater concentrations of ALA, carotenoids, and vitamins (Chatzidimitriou, 2020). As plants mature, they lignify, reducing digestibility and nutrient availability. These changes, well- studied in ruminant nutrition, appear to apply similarly to poultry, where early growth enhances the deposition of omega-3s and antioxidants in eggs (Fleming et al., 2024). Environmental conditions such as heat and rainfall significantly influence the nutrient composition of pasture-based systems. High summer temperatures accelerate plant senescence, leading to increased lignification and fiber content, while reducing concentrations of essential fatty acids and antioxidant compounds in forage (Bal & Minhas, 2017). In contrast, spring and early autumn rainfall promotes lush forage growth with a higher leaf-to-stem ratio, improving the availability of carotenoids and vitamins in pasture (Bist et al., 2024; Oke & Onagbesan, 2013). However, excessive moisture can result in leaching vital nutrients such as nitrogen and reduce 10 overall forage quality, potentially introducing microbial risks that impact both hen health and egg composition (Nardone & Valfrè, 1999). In temperate regions, regrowth cycles further shape forage lipid profiles. ALA and total fatty acids tend to peak during early growth, decline during mid-season, and rise again with late- season regrowth (Chatzidimitriou, 2020). Optimizing grazing schedules and supplemental feeding can help maintain a consistent nutrient profile in eggs year-round. Seasonal nutrient shifts reinforce the importance of adaptive pasture management and dietary supplementation strategies to ensure consistent nutrient quality in pasture-raised eggs throughout the year. 1.6.2 Forage Composition and Nutrient Profiles Across Time The nutrient composition of forage varies significantly across plant species and evolves throughout the grazing season. Grasses, legumes, and forbs offer distinct profiles of crude protein, fiber, and fatty acids, directly influencing poultry diets and consequently, egg composition (Jaramillo et al., 2021). Plant maturity is a critical factor affecting digestibility and nutrient value; younger forages tend to have higher protein and lower fiber levels, making them more suitable for nutrient absorption (Spencer, 2013). As plants mature, lignin and fiber increase, reducing the bioavailability of essential nutrients. Among forage species, legumes like alfalfa and clover provide rich sources of polyunsaturated fatty acids and protein, whereas grasses such as orchard grass and fescue contribute more structural carbohydrates but are lower in lipid content (Turner et al., 2014; Van Keuren & Matches, 1988). These differences highlight the importance of forage diversity and grazing timing to enhance the nutrient density of pasture-raised eggs throughout the production season. 11 1.6.3 Conserved Forages and Layer Hen Feeds When fresh pasture is unavailable, producers turn to conserved forages (e.g., hay, haylage, silage) and formulated layer hen feeds to support egg production and maintain nutrient quality. However, due to their monogastric digestive systems, hens are less able to extract nutrients from high-fiber forages compared to ruminants (Kutlu & Özen, 2009; Röhe & Zentek, 2021). As a result, commercial layer diets rely on grains, oilseeds, fishmeal, and more recently, microalgae or flaxseed to enhance omega-3 content (Fraeye et al., 2012). These feed formulations can be specifically designed to boost omega-3 fatty acid deposition in egg yolks, a strategy not possible in beef systems where grain-feeding often reduces omega-3 levels in meat (H. Karsten et al., 2010; van Vliet, Provenza, et al., 2021). Studies have shown that supplementing hen diets with fish oil or algae leads to significantly higher levels of DHA and EPA in eggs, maintaining their health benefits even outside of grazing seasons (Fraeye et al., 2012) . Understanding the species-specific nutritional demands of poultry versus ruminants is critical. Strategic supplementation ensures that even in the absence of fresh pasture, the nutritional quality of pasture-raised eggs can be preserved year-round. 1.7 Poultry Welfare and Environmental Considerations in Pasture Systems 1.7.1 Regenerative Agriculture and Pasture-Raised Systems Regenerative agriculture is an ecological farming approach focused on restoring soil health, enhancing biodiversity, and promoting self-sustaining agroecosystems. Techniques such as rotational grazing, cover cropping, and reduced chemical inputs improve carbon sequestration, water retention, and nutrient cycling, thereby supporting long-term ecosystem resilience and productivity (Atapattu et al., 2025; Krusinski, Sergin, et al., 2022). 12 Pasture-raised poultry systems align with regenerative principles by integrating hens into a biodiverse landscape. Rotational foraging prevents overgrazing and supports nutrient renewal in the soil. Moreover, Hens also assist with pest control and soil aeration while enriching soil through manure, enhancing microbial activity and fertility (Bilenky et al., 2024; Haschke et al., 2023). By embedding poultry in regenerative systems, producers can simultaneously improve environmental outcomes and egg quality. However, maintaining pasture quality during seasonal transitions is a challenge, requiring adaptive management and nutritional supplementation (Caradus et al., 2024; Porras, 2024). 1.7.2 Production Scale and Economic Pressures Pasture-raised egg systems generally operate on a smaller production scale compared to industrial cage-based or cage-free systems. These systems require more land, labor, and management per bird, resulting in higher operational costs structural difference contributes to the premium price of pasture-raised eggs and limits their scalability in conventional supply chains (Meeh et al., 2014). Recent market fluctuations, driven in part by the 2022–2023 outbreak of highly pathogenic avian influenza (HPAI), have further exposed vulnerabilities in the egg supply chain. Widespread culling of hens led to egg shortages and record-high prices in the United States (Caputo et al., 2023; Ufer, 2025). In this context, pasture-based systems offer potential value by supporting local food networks and distributing production risks. Localized pasture-based systems offer potential stability by supporting local networks and distributing production risks (Meyer et al., 2021; Watson, 2020). 13 1.7.3 Seasonal Variation and Environmental Uncertainty Despite their potential, pasture-raised systems face unique environmental challenges, particularly related to seasonal variation. Pasture quality fluctuates across the year due to temperature, precipitation, and plant maturity cycles, affecting the availability of key nutrients such as omega-3 fatty acids and carotenoids (Evaris et al., 2019). During non-growing seasons or extreme weather events, producers often struggle to maintain consistent egg nutrient profiles, especially when hens cannot access fresh forage (Cornell, 2020; Meeh et al., 2014). This variability also raises questions about labeling accuracy and consumer expectations, especially as pasture-raised eggs grow in popularity. To date, little research has explored how specific climates or regions influence nutrient outcomes in pasture-raised systems. 1.7.4 Research Gaps and Objectives Although previous studies have consistently demonstrated the superior nutrient profiles of pasture-raised eggs compared to those from conventional systems, most research has evaluated these differences at isolated time points, without considering seasonal fluctuations in forage quality or environmental stressors (H. Karsten et al., 2010). Consequently, our understanding of how dynamic environmental and ecological conditions affect the nutrient composition of pasture-raised eggs remains limited. A major gap lies in the lack of data on seasonal variation in forage-derived nutrients—such as carotenoids, omega-3 fatty acids, and antioxidants—and their relationship to the deposition of these compounds in egg yolks. While the responsiveness of egg nutrient profiles to hen diet is well-documented, fewer studies have examined this relationship across multiple months within a grazing season, particularly in the context of pasture-based systems that vary significantly in plant composition, climate, and management strategies (Fraeye et al., 2012). 14 Additionally, most existing literature has focused on nutrient enhancement through feed supplementation rather than environmental variability (Omri et al., 2019). This presents a further limitation, especially as pasture-raising systems grow in popularity as part of regenerative agriculture and local food economies, where nutrient inputs are more dependent on natural forage systems and less on processed feed (Krusinski, Maciel, et al., 2022). There is also a lack of data on how such seasonal nutrient variability may affect compliance with nutritional labeling standards or influence consumer health benefits. Lastly, with the rising cost of eggs due to market disruptions like avian influenza, there is renewed interest in small-scale, local pasture-based production (Ufer, 2025). Yet, no current research thoroughly documents how seasonal nutrient variation in pasture-raised eggs occurs in specific regions, such as the Midwestern or Northeastern U.S., limiting the scalability and optimization of these systems 1.8 Conclusion This chapter has reviewed the current scientific understanding of the nutritional composition of eggs and the many factors that influence yolk quality, including production system, hen diet, forage access, and environmental conditions. Numerous studies have shown that pasture-raised eggs are consistently higher in omega-3 fatty acids, carotenoids, and antioxidants compared to conventionally produced eggs, largely due to hen access to diverse, nutrient-dense forages (Fraeye et al., 2012; H. Karsten et al., 2010). However, these nutrient advantages are not constant. The composition of forages—and therefore the nutrient intake of pasture-raised hens—varies throughout the grazing season due to plant maturity, species composition, temperature, and rainfall (Chatzidimitriou, 2020; Evaris et al., 2019). While some studies have explored the relationship between forage diversity and egg 15 nutrient enrichment, most have focused on dietary supplementation strategies and do not account for seasonal or regional variation (Omri et al., 2019). Pasture-based systems, while nutritionally and ecologically promising, also face practical challenges. These include their smaller production scale, dependence on environmental conditions, and management limitations during non-grazing periods (Bilenky et al., 2024; Meeh et al., 2014). Yet, they also offer a resilient and localized alternative to large-scale egg production; especially in light of recent supply chain disruptions linked to avian flu outbreaks and rising egg prices (Meyer et al., 2021; Ufer, 2025). As demand for nutrient-dense and locally produced foods grows, understanding how to optimize egg quality within these systems becomes increasingly important. Despite consistent findings that pasture-raised eggs are more nutrient-dense than conventionally produced eggs, the majority of existing studies capture nutrient data at only one point in time (Anderson, 2011; H. Karsten et al., 2010). Few have evaluated how seasonal variation in pasture quality—driven by changes in plant maturity, temperature, rainfall, and soil nutrients— impacts egg nutrition over time (Chatzidimitriou, 2020; Evaris et al., 2019). While the effect of hen diet on egg nutrient content is well established, the role of environmental conditions and forage dynamics throughout a grazing season remains largely unexamined in poultry systems (Fraeye et al., 2012). This presents a critical research gap, particularly as regenerative, low-input production models gain traction (Atapattu et al., 2025). Therefore, the purpose of the following study is to examine how seasonal changes in pasture conditions influence the nutritional composition of eggs in a pasture-based laying system. Through monthly sampling of forage, soil, and eggs, this study seeks to identify patterns in nutrient deposition across a full grazing season and assess how these variations align with changes in environmental and agricultural factors. This work builds on existing research in ruminant systems 16 and regenerative agriculture, and applies it to poultry systems: helping define optimal pasture- based practices for consistent and nutrient-dense egg production. 17 CHAPTER II: GRAZING SEASON IMPACTS THE FATTY ACID AND NUTRIENT PROFILE OF EGGS ON A SOUTHERN OHIO PASTURE- RAISING SYSTEM FOR LAYER HENS 2.1 Abstract Interest in regenerative poultry farming continues to grow, particularly due to its emphasis on soil conservation, biodiversity, and the natural interactions between hens and their surroundings. Access to pasture allows chickens to consume a diverse range of plants and insects, potentially enhancing the nutritional value of their eggs. However, nutrient composition fluctuates throughout the year as environmental conditions change. Objective: This study examined how seasonal changes in climate, soil composition, and forage availability influence the nutritional profile of eggs in a pasture-based laying system in Southern Ohio. Methods: Monthly collections of forage (n=3) and eggs (n=24, pooled into 12 replicates) occurred from May to December. Fatty acid composition was assessed using gas chromatography-mass spectrometry, while carotenoid and phenolic levels were measured colorimetrically. Vitamin and mineral content were analyzed through liquid chromatography and Inductively Coupled Plasma Optical Emission Spectroscopy. Results: Pasture quality, assessed by total digestible nutrients (TDN), peaked in October. Egg protein quality met USDA “Grade AA” standards every month except August (p > 0.001). The highest yolk pigmentation score was recorded in December (9.5 ± 1.3; p < 0.001). Vitamin A levels were significantly greater in late summer (p < 0.001), while vitamin E gradually increased across the season, reaching its highest value in November (118.1 ± 24.0 µg/g fresh yolk; p < 0.001). Carotenoid concentrations were elevated in mid-summer and late autumn (p < 0.001). Total omega-3 fatty acids were significantly higher in September and October than in mid-summer and late fall, while the n-6:n-3 ratio was lowest in early summer and fall compared to July (p < 0.001). 18 Principal component and random forest analyses demonstrated that eggs produced from September to November contained higher levels of vitamins A and E, greater essential omega-3 fatty acids, and a more favorable n-6:n-3 balance than eggs from other months. Conclusions: Significant seasonal shifts were observed in the fatty acid and antioxidant composition of pasture-raised eggs, with fall months yielding eggs with superior nutritional quality. These findings may assist consumers and producers in making informed decisions regarding the seasonal variation in pasture-raised egg nutrient composition. 2.2 Introduction Pasture-raised egg farming has gained significant attention due to its emphasis on animal welfare, sustainability, and the production of nutrient-dense eggs, distinguishing it from conventional farming systems that rely heavily on confined animal operations and grain-based feed (H.D. Karsten et al., 2010). In a recent survey of U.S. consumers, 86% of respondents had purchased at least one animal product with welfare associated labels, such as “pasture-raised” (Thibault et al., 2022). This reflects a broader trend of prioritizing foods produced with improved environmental and ethical farming practices. Moreover, pasture-raised egg production is aligned with regenerative agricultural practices which focus on fostering a symbiotic relationship between chickens, forage, and the environment. These systems emphasize soil health, biodiversity, and ecological cycles while reducing the negative environmental impacts of conventional farming (Undersander D., 2014). Finally, hens in pasture-raising systems have access to a variety of plants and insects, contributing valuable nutrients that are otherwise absent or limited in conventional feed. Hens in these systems obtain nutrients directly from their environment, primarily through forage, making the nutrient composition of the pasture a critical determinant of egg quality and production. 19 Eggs from pasture-raised systems offer significant nutritional advantages over those produced in conventional systems, such as cage-free or caged systems, where hens are not required to have outdoor access (H.D. Karsten et al., 2010; Meng et al., 2014; Sergin et al., 2021; Sergin et al., 2022; Yenice et al., 2016). Pasture-raised eggs are generally more nutrient-dense compared to eggs from conventional caging systems, with one study reporting twice the vitamin E content and 2.5 times more omega-3 (n-3) fatty acids, contributing to a more favorable omega-6:omega-3 ratio (H.D. Karsten et al., 2010). The increased antioxidant, omega-3 fatty acid, and vitamin content in pasture-raised eggs is beneficial for human health, as consuming these nutrients supports immune function, reduces inflammatory cardiovascular diseases, and mitigates the harmful effects of oxidative stress (Jain et al., 2015; Réhault-Godbert et al., 2019; Simopoulos, 2008). These benefits are largely attributed to the inclusion of forages in the hens' diet, which have a higher antioxidant and polyunsaturated fat content—particularly n-3 fatty acids—compared to conventional corn- and soy-based feeds that are usually lower in antioxidants and higher in omega-6 (n-6) fatty acids. Moreover, the nutrient profile of eggs is highly responsive to dietary changes (H.D. Karsten et al., 2010; Krusinski, Maciel, et al., 2022). Despite the benefits of pasture-based systems, seasonal variations in forage quality and composition significantly influence the nutrient profile of pasture-raised eggs. As plants mature, the leaf-to-stem ratio decreases, increasing acid detergent fiber (ADF) and neutral detergent fiber (NDF) while reducing digestible protein—essential for productive laying systems (Alex Rocateli, 2017). Lower total digestible nutrients (TDN), a key indicator of pasture quality, can negatively impact hens’ growth, egg production, and nutrient absorption (Dillard, 2019). For example, alfalfa is associated with higher forage phenolic content, and orchard grass is linked to lower total forage carotenoids (Krusinski, Maciel, et al., 2022). Chickens preferences influence forage consumption, 20 where grass species, orchard grass and alfalfa have demonstrated highest palatability (Wood, 1956) Additionally, environmental factors such as rainfall, temperature, and soil conditions further influence forage quality (Alex Rocateli, 2017; Extension, 2023). Excessive rainfall can leach nutrients from plants, while prolonged high temperatures accelerate the degradation of fatty acids and antioxidants like vitamin E and carotenoids (Extension, 2023). This variability highlights the importance of understanding how seasonal changes in forage quality impact the nutrient profile of eggs. While the effect of hen diet on egg nutrient composition is well documented, little research has focused on how seasonal variations in forage impact the nutrient profile of eggs in pasture- raised systems. Understanding these dynamics is crucial, as they could inform best practices for improving egg quality year-round in pasture-based systems. Therefore, the objective of this study was to document changes in the nutrient composition of forage and eggs in a Southern Ohio pasture-based system for layer hens across a grazing season. Further, we investigated how changes in egg nutrient composition connect to variations in weather, soil quality, and forage availability and composition and determined important discriminating factors in egg nutrient composition across the year. 2.3 Materials and Methods 2.3.1 Chemicals A gas chromatography–mass spectrometry (GC-MS) reference standard curve was created using the Supelco 37 Component FAME Mix (Sigma-Aldrich, St. Louis, MO, USA), along with individual standards, including mead acid, docosatetraenoic acid (DTA), n-3 docosapentaenoic acid (DPA), n-6 DPA, and palmitelaidic acid (Cayman Chemical, Ann Arbor, MI, USA). Branch chain fatty acids (BCFAs) were quantified using Mixture BR 3 (Larodan AB, Solna, Sweden), 21 while conjugated linoleic acid (CLA) isomers were quantified using the CLA reference standard UC-59M (Nu-Chek Prep, Elysian, MN, USA). Dichloromethane was obtained from VWR Chemicals (Radnor, PA, USA). All other chemicals were purchased from Sigma-Aldrich (St. Louis, MO, USA), unless otherwise noted. All reagents used were HPLC grade unless otherwise noted, with isooctane being GC grade. 2.3.1 Diet Characteristics and Sample Collection This study was conducted across one grazing season (May-December 2022) at a privately managed farm in Southern Ohio (39.22°N, 84.34°W; 269 m elevation), where laying hens were rotated every 4 weeks between three 0.25 acre2 (1011.71 m2) fenced pastures. The farm was independently operated for production and not managed for research. Samples were collected during routine farm operations without experimental intervention or animal monitoring. As no animal handling or manipulation occurred, IACUC approval was not required. From May to September, the flock consisted of approximately 300 Comet hens; hens were around one year old at the start of collection. However, the flock size was drastically reduced by September due to predation and a high mortality rate. In response to these losses, Black Sex-linked hens, at an age of 16 weeks, were introduced in October, replacing the Comet hens. In rotation with grass-fed cattle, hens were rotated every 4 weeks across three fresh pastures. In addition, hens had free access to a standard layer hen feed all season (Table 1). The layer hen feed was sampled three times from a well-mixed bin of feed at the beginning and end of the grazing season each year for a total of n = 6 replicates. Layer hen feed samples were freeze-dried and ground with dry ice to pass a 1 mm screen in a Wiley mill (Arthur H. Thomas, Philadelphia, PA, USA) and stored at −80 °C. A total of 8 collections of forage, soil, eggs, and weather data were conducted from May to December, at 4-week intervals. Each month, before hens were given access to the pasture, forage 22 height and composition were assessed. Ten hoops (1/2 m2) were randomly tossed across the pasture, and species percent coverage and pre-graze forage height were recorded from the center of each hoop. The same method was used to measure post-graze height after the hens were moved off the pasture, providing an estimate of forage intake across the month. Then, when the hens were given access to the pasture, forage and soil samples were collected. To collect the forage, nine randomly selected 0.25 m2 quadrats were clipped to a 1 cm stubble and thoroughly mixed. This process was repeated 3 times to create n = 3 replicates of forage per month. Forage samples were promptly placed in a –20 °C freezer until delivery to the laboratory. Then, forage samples were freeze-dried and ground with dry ice to pass a 1 mm screen in a Wiley mill (Arthur H. Thomas, Philadelphia, PA, USA) and stored at -80 °C under nitrogen. At the same time, soil samples were collected. Using a soil probe, 15-20 subsamples were randomly taken in a zig-zag fashion from the pasture area and mixed in a bucket. This process was repeated 3 times to create n = 3 replicates of soil per month. After the hens had access to the pasture for several days, 36 eggs were randomly collected and, upon arrival at the laboratory, n = 24 eggs were randomly chosen for analysis. Finally, weather data, including daily, monthly, and 30-year normal average temperature and total precipitation, was obtained from the U.S. Department of Commerce National Centers for Environmental Information (U.S. Department of Commerce, 2022). 23 Table 1. Composition of the layer hen feed Guaranteed Analysis Crude Protein (Min) Lysine (Min) Methionine (Min) Crude Fat (Min) Crude Fiber (Max) Calcium (Min) Calcium (Max) Phosphorus (Min) Salt (Min) Salt (Max) Selenium (Min) Vitamin A (Min) Vitamin D3 (Min) 16.00% 0.85% 0.35% 3.50% 9.00% 3.25% 3.75% 0.70% 0.25% 0.75% 0.30 ppm 882.00 IU/100 g 331.00 IU/100 g Nutrition Requirement1 15.00% 0.69% 0.30% ND ND 3.25% ND 0.15% 0.60 ppm 3,000.00 IU/100 g 300.00 IU/100 g Ingredients: Wheat Midds, Oats, Barley, Organic Non-GMO Soybean Meal, Calcium Carbonate, Fish Meal, Kelp Meal, Salt, Monocalcium Phosphate, Brewers Grain Yeast, Lactobacillus acidophilus, Enterococcus faecium, Aspergillus oryzae, Bacillus subtilis, Bacillus licheniformis, Yucca schidigera, DL-Methionine, Vitamin A Supplement, Vitamin D3 Supplement, Vitamin E Supplement, Menadione Sodium Bisulfite Complex, Niacin, Riboflavin, D-Calcium Pantothenate, Pyridoxine Hydrochloride, Folic Acid, Zinc Amino Acid Chelate, Potassium Amino Acid Complex, Magnesium Amino Acid Chelate, Manganese Amino Acid Chelate, Copper Amino Acid Chelate, Vitamin B12 Supplement, Ferrous Sulfate, Manganese Oxide, Copper Sulfate, Sodium Selenite, Zinc Oxide, Choline Chloride, Ethylenediamine Dihydroiodide, Selenium Yeast. 1Represents layer hen intake requirements defined by the Nutrient Requirements of Poultry: Ninth Revised Edition, 1994 (Council). ND, not defined; IU, international unit. 2.3.3 Soil Analysis Soil samples were analyzed under the organic matter and general soil profile packages at a commercial laboratory provided through Michigan State University (East Lansing, MI, USA). Soil pH was assessed using a standard pH meter. Additionally, organic matter and ash content were determined using the loss on ignition (LOI) method using a muffle furnace. Mineral content was 24 assessed after the LOI ash product for Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES) quantification. 2.3.4 Forage and Layer Hen Feed Proximate Analysis Forage and layer hen feed proximate analysis was conducted at the DairyOne Forage Laboratory in Ithaca, N, USA. Forage and feed moisture content was assessed using a forced air oven adapted from AOAC 991.01 and AOAC 930.15 methods, respectively (AOAC, 2023). Crude protein (CP), ADF, lignin, crude fat, and ash content were assessed using AOAC methods 990.03, 973.18, 973.18, and 954.02, respectively (AOAC, 2023). Forage and feed NDF content was assessed based on methods adapted from Van Soest et al (Van Soest et al., 1991). For the starch analysis, forage and feed samples were enzymatically digested into glucose using glucoamylase, then the resulting glucose was quantified indirectly using hydrogen peroxide equivalents measured by the YSI 2700 Select Biochemistry Analyzer. Metabolizable energy, digestible energy (DE), and TDN were calculated using the following equations (Council, 2001): TDN!"(%) = CP + nonfiber carbohydrates + (crude fat ∙ 2.25) + NDF − 7 DE (Mcal kg)⁄ = TDN(%) ∙ 0.04409 ME (Mcal kg)⁄ = DE (Mcal kg)⁄ ∙ 1.01 2.3.5 Egg Physical Characteristics Egg physical characteristics were measured according as previously reported (Sergin et al., 2021; Sergin et al., 2022). Egg, yolk, and shell weight were recorded, and albumen weight was determined by subtraction. Albumen height was determined using a micrometer. Haugh units were determined from the recorded egg weight and albumen height (Haugh unit = 100 x log (albumen height (mm) + 7.57 – 1.7 x egg weight0.37) (Eisen et al., 1962b). A colorimeter was used to quantify yolk color using the L*a*b (L* scale quantifies whiteness, a*, redness, and yellowness) (Spada et 25 al., 2016). Yolk color was also rated from 1 to 14 using the DSM yolk color fan (DSM Nutritional Products, Basel, Switzerland) (1 for pale yellow-16 for deep orange). Lastly, yolks were freeze- dried, powdered, and kept under nitrogen at -80 °C. Every two egg yolks were thoroughly mixed, creating n=12 replicates per month for subsequent analyses. 2.3.6 Fatty Acid Analysis Briefly, a modified version of the microwave-assisted extraction method by Bronkema et al (Bronkema et al., 2019) was used to extract fatty acids using 400 mg of egg yolk, forage, or layer hen feed samples and 8 mL of a 4:1 (v/v) ethyl acetate:methanol solution with 0.1% butylatedhydroxy toluene(BHT) as an antioxidant. Fatty acids were extracted in a CEM Mars 6 microwave (CEM Corp., Matthews, NC, USA) using the following microwave parameters: 55 °C for 15minuteswith an initial ramp of 2minutesat 400 W maximum power. Samples were then filtered and prepared as previously described to obtain the extracted oil (Sergin et al., 2021; Sergin et al., 2022). Methylation described by Sergin et al (Sergin et al., 2021) modified from Jenkins (Jenkins, 1993) was conducted for the creation of fatty acid methyl esters (FAMEs). Two milligrams of extracted oil were combined with 500 µL toluene and 20 µg of methyl-12-tridecenoate (U-35M, Nu-Chek Prep, Elysian, MN, USA) as an internal standard. Base-catalyzed methylation was conducted using 2 mL of anhydrous potassium methoxide (0.5 N) at 50 °C for 10 min. Then, acid- catalyzed methylation was conducted using 3 mL of methanolic HCl (5%) at 80 °C for 10 min. Two mL of HPLC water were added, then FAMEs were extracted twice using 2 mL of hexane. Extracted FAMEs were resuspended in 1 mL of isooctane and stored at -20 °C until GC-MS analysis. 26 FAMEs were separated using the HP-88 column (100 m, 0.25 mm inner diameter, 0.2 µm film thickness; Agilent Technologies, Santa Clara, CA) on a Perkin Elmer 680/600 GC-MS (Waltham, MA, USA) in the electron impact (EI) mode with helium as the carrier gas (1 mL/min). For improved separation of fatty acid isomers, column temperature parameters described by Kramer et al. (Kramer et al., 2008) were used as follows: initial temperature of 80 °C for 4 min, ramp at a rate of 13.0 °C/min to 175 °C, held for 27 min, ramp at a rate of 4.0 °C/min to 215 °C, and held for 35minutes. Two different injections with a 1 µL injection volume and 250 °C injection temperature were conducted to capture both lower- and higher-concentration analytes. These were a 30:1 split injection and a splitless injection (0.75 minutes splitless hold time, 40 mL/min flow exiting the vent). Regarding MS settings, electron energy was 70 eV, and the transfer line and ion source temperature were set to 180 °C. MS data were recorded in full scan mode (m/z 70-400). For identification of FAMEs, data were analyzed using MassLynx (4.1 SCN 714; Waters Corp., Milford, MA, USA). Retention time and EI mass fragmentation of each analyte were compared to those in our reference standard (described in section 2.1). Fatty acids not included in the reference standard were identified by elution order as reported by Kramer et al. (Kramer et al., 2008) and confirmed with EI mass fragmentation. Fatty acids were quantified using extracted ion chromatograms of the respective quantitative ions utilizing a standard curve constructed from our reference and internal standard. To calculate each FAME concentration, the internal standard peak area and analyte peak area in each sample were compared to those of the standard curve. Fatty acids were reported as percent of total fatty acids quantified and in g amounts per 100 g of egg yolk. 27 2.3.7 Phenolic Analysis Briefly, two extractions, first with 20 mL of a methanol:distilled water:acetic acid solvent [80:18:2 (v/v/v)], and second with 20 mL of an acetone:distilled water:acetic acid solvent [80:18:2 (v/v/v)], were used to extract phenolic compounds from 2 g of lyophilized egg yolk sample, ground forage, or ground layer hen feed. Tubes were shaken and centrifuged (840 g, 4 °C) and supernatants were combined following the addition of each solvent as previously described (Sergin et al., 2021; Sergin et al., 2022). Then, 100 μL Folin-Ciocalteu reagent and 800 μL 5% sodium bicarbonate were added to a gallic acid standard curve (1 mg/mL to 0.002 mg/mL) and to a 100 μL portion of the supernatant. These samples were heated at 40 °C for 30 min, cooled at room temperature for 10 min, and were plated in triplicate in a 96-well plate. Samples were then scanned in a microplate reader (Bio-Tek, Winooski, VT, USA) at 765 nm, compared against the standard curve, and reported as mg of gallic acid equivalents (GAE) per g of fresh egg yolk, forage, or feed. 2.3.8 Carotenoid Analysis For egg yolks, 0.5 g of lyophilized egg yolk sample was combined with 5 mL of cold acetone (0.05% BHT) and homogenized. Samples were vortexed for 2 min, then ultrasonicated in a water bath for 5 min, and centrifuged for 15minutes (1200 g, 4 °C). The supernatant was evaluated in a UV-Vis Double Beam Spectrophotometer (VWR, Radnor, PA, USA) at 450 nm against an acetone blank. Total carotenoid content was calculated according to Biehler et al (Biehler et al., 2010). using an ε of 140663 L/mol for beta-carotene in acetone and was expressed as µg of beta-carotene per g of fresh egg yolk. For the forage and layer hen feed, in a conical tube, 2 g of ground sample were combined with 20 mL of 70% aqueous acetone. The tubes were shaken for 30minutesand centrifuged for 20minutesat 840 g and 4 °C. The supernatant was recovered in a new tube. The extraction was 28 repeated with an additional 20 mL of 70% aqueous acetone and the supernatants were pooled. Using the spectrophotometer, carotenoid and chlorophyll content of the supernatants were assessed in glass cuvettes at three wavelengths (663, 646, and 470 nm). Chlorophyll A, chlorophyll B, and total carotenoids were calculated using the following equations where A# = Absorbance# %& : Chlorophyll A (C() = 11.75 ∙ A))* − 2.35 ∙ A)+, Chlorophyll B (C-) = 18.61 ∙ A)+,  −  3.96 ∙ A))* Total Carotenoids = 1000 ∙ A+./  −  2.27 ∗ C(  −  81.4 ∙ C- 227 2.3.9 Vitamin A and E Analysis Vitamin content of egg yolk, forage, and layer hen feed samples was assessed using the Veterinary Diagnostic Laboratory at Michigan State University (East Lansing, MI) using AOAC official method 2001.13 (AOAC, 2023). Briefly, lipid content was saponified using a potassium hydroxide solution in ethanol to reduce vitamin esters to their alcohol form. Vitamins were then extracted using hexane phase separation. Then, the extracted hexane layer was evaporated, and the residual vitamins were resuspended in acetonitrile:methylene chloride:methanol (70:20:10, v/v/v) for chromatographic analysis using an Acquity BEH C182, 1.7mm, 2.1 x 50 mm analytical column in a Waters Acuity system while using the Waters Empower Pro Chromatography Manger software. Vitamin quantification was assessed using the ApexTract method of Empower Pro using a calibration curve created using retinol, beta-carotene, and alpha-tocopherol standards (Sigma Aldrich, St. Louis, MO). 2.3.10 Mineral Analysis For egg yolks, 0.10 g of powdered yolk was predigested in borosilicate glass tubes with 3 mL of a concentrated ultrapure nitric and perchloric acid mixture (60:40 v/v) for 16 hours at room 29 temperature. Samples were then heated incrementally in a digestion block to 120 ºC for 4 h, followed by 2 h at 120 ºC with an additional 2 mL of nitric acid. The temperature was then increased to 145 ºC for 2 h and finally to 190 ºC to evaporate remaining liquid. Digested samples were resuspended in 10 mL ultrapure water and analyzed using Inductively coupled plasma-atomic emission spectrometry (ICP-AES) (Thermo iCAP 6500 Series) with quality control standards for every 10 samples. Yttrium (0.50 μg/mL, final concentration) was added as an internal standard to ensure accuracy and correct for matrix interference. For the forage and layer hen feed, 0.5 g of forage and layer hen feed samples were digested in 10 mL of a 4:1 (v/v) nitric:hydrochloric acid solution, followed by an additional 10-minute digestion with 1 mL of 30% hydrogen peroxide. Digestions were performed using a CEM Mars 6 microwave system (CEM Corp., Matthews, NC, USA) under the following parameters: a 10- minute ramp to 135 °C held for 3minutesat 1500 W, followed by a 12-min ramp to 200 °C held for 15minutesat 1600 W. Post-digestion, vessels were diluted to 50 mL, and aliquots were analyzed for mineral content using ICP-OES with a Thermo iCAP Pro XP radial spectrometer. For water analysis, 35 µL of concentrated nitric acid was added to 14 mL of water, mixed, and aspirated for ICP-OES measurement. 2.3.11 Egg Yolk Cholesterol Analysis Briefly, cholesterol was extracted from 0.5 g of freeze-dried powdered egg yolk by dilution using 9 mL of 2% (w/v) NaCl. Each replicate was vortexed for two minutes and shaken at 37 °C for 2 h. After solubilization, 0.5 mL of the solution was further diluted in 9.5 mL of 2% (w/v) and vortexed for 1 min. Then, the extraction solution was filtered through a 0.45 µm syringe filter to isolate cholesterol. 50 µl of the filtered, diluted, solution was calculated to contain 3-6 µg of 30 cholesterol. Quantification of the extracted cholesterol was determined colorimetrically following instructions using Cholesterol Quantification Assay kit (catalog: CS0005-1KT) produced by Sigma-Aldrich (Burlington, MA). 2.3.12 Statistical Analysis Means and standard deviations for each characteristic were calculated by month. To assess if egg yolk and forage nutrient content differed by month across the season, a one-way analysis of variance (ANOVA) and Tukey’s Honestly Significant Difference (HSD) test for significance was carried out using RStudio (R Core Team, Vienna, Austria). Results were considered significant at p < 0.05. Values under the limit of detection (LOD) were treated as zeroes. Additionally, a Spearman correlation analysis was carried out to explore how different factors were connected using the RStudio packages: ggplot2, reshape2, Hmisc, RColorBrewer, corrplot, showtext, readxl. Further, MetaboAnalyst 5.0 (metaboanalsyt.ca) was used to carry out sparse partial least squares discriminant analysis (sPLS-DA) to visualize monthly groupings. Random forest (RF) analysis was to identify which nutrients were the strongest predictors for the separation of each month using 500 trees using OOB values with randomness (van Vliet, Bain, et al., 2021). Both analyses were conducted using yolk and forage antioxidants (total phenolics, total carotenoids, beta-carotene, vitamin A, and vitamin E) and fatty acids (% of total), and yolk cholesterol, with no data transformation or normalization necessary. Yolk mineral content was excluded from the sPLS-DA and RF analyses, as the minerals contributed minimally to the daily recommended intake for essential minerals, making them insignificant for this analysis. 2.4 Results 2.4.1 Weather 31 The daily and monthly average temperature and total precipitation are shown in Figure 1. From May to December 2022 in Southern Ohio, daily temperatures followed expected seasonal patterns, increasing after May, peaking in July and August, and gradually decreasing as the season progressed. The monthly average temperature was closely aligned with the 30-year normal. The highest total precipitation was recorded in May and September. The monthly average precipitation differed from the 30-year normal throughout the season. The months of May, August, and September experienced higher total precipitation compared to the normal, while July and October had notably lower amounts. Figure 1. Weather trends across the 2022 grazing season. (A) Daily average temperatures and total precipitation (B) Monthly average temperature and total precipitation and their comparison to the 30-year normal. *Signifies average monthly total precipitation that is greater than three standard deviations from the 30-year normal. 2.4.2 Soil Composition Changes in the soil composition are shown in Table 2. Across the laying season, the soil pH and mineral content were sufficient to maintain forage quality (Kathrin Olson-Rutz, 2017). While several characteristics remained relatively stable across the season, such as pH, lime index, and organic matter, the mineral content fluctuated by month. 32 Additionally, several trends were observed when comparing soil characteristics with forage mineral content (Appendix Table A1). For example, phosphorus levels in the soil generally decreased over the season, dropping from 18.00 ppm in May to 5.00 ppm in August, before rising again in November (p < 0.001). The forage phosphorus levels followed a similar pattern, decreasing from 0.04% in May to 0.03% by November (p = 0.035). Table 2. Characteristics of the soil by month1 Parameter May Jun Jul Aug Sept Oct Nov Dec pH 6.40 ± 0.01 6.70 ± 0.26 6.77 ± 0.32 6.43 ± 0.32 6.57 ± 0.15 6.73 ± 0.21 6.53 ± 0.15 6.23 ± 0.06 p- value2 0.088 Lime index 70.00 ± 0.01 c 70.00 ± 0.01 c 70.00 ± 0.01 c 69.00 ± 0.01 d 71.00 ± 0.01 b 71.00 ± 0.01 b 72.33 ± 0.58 a 69.00 ± 0.01 d <0.001 Phosphorus (ppm) 18.00 ± 4.36 bc 13.67 ± 3.51 cd 14.67 ± 1.53 cd 5.00 ± 1.73 e 7.00 ± 1.00 de 13.33 ± 3.21 cd 47.33 ± 3.51 a 24.33 ± 1.15 b <0.001 Potassium (ppm) 164.00 ± 30.51 b 71.67 ± 18.50 b 210.67 ± 51.19 ab 100.33 ± 26.16 b 97.00 ± 16.46 b 197.33 ± 12.66 ab 326.33 ± 121.71 a 157.33 ± 34.67 b <0.001 Magnesium (ppm) 228.33 ± 16.20 ab 160.67 ± 7.77 c 231.67 ± 13.58 a 192.67 ± 13.05 abc 195.33 ± 14.50 abc 237.67 ± 35.57 a 221.67 ± 6.35 ab 181.67 ± 15.37 bc <0.001 Calcium (ppm) 1413.33 ± 73.33 ab 1591.33 ± 102.05 ab 1706.67 ± 154.78 a 1564.33 ± 249.5 ab 1387.33 ± 93.11 ab 1680.33 ± 178.21 a 1552.00 ± 27.87 ab 1237.67 ± 21.55 b 0.008 Cation exchange capacity (meq/100 g) 9.40 ± 0.44 ab 9.50 ± 0.52 ab 11.00 ± 0.78 a 10.50 ± 0.72 ab 8.83 ± 0.55 b 10.90 ± 1.23 a 10.43 ± 0.42 ab 9.33 ± 0.25 ab 0.007 % of Exchangeable bases % Potassium 4.50 ± 0.98 ab 1.97 ± 0.55 b 5.00 ± 1.59 ab 2.60 ± 0.30 ab 2.87 ± 0.64 b 4.67 ± 0.25 ab 7.93 ± 2.63 a 4.97 ± 0.93 ab 0.001 % Magnesium 20.27 ± 0.50 a 14.13 ± 0.58 c 17.57 ± 0.21 ab 16.73 ± 1.95 bc 18.43 ± 0.81 ab 18.13 ± 1.07 ab 17.70 ± 0.98 ab 18.33 ± 0.90 ab <0.001 % Calcium 75.23 ± 0.55 cd 83.90 ± 1.13 a 77.47 ± 1.72 bcd 80.63 ± 1.67 ab 78.67 ± 0.99 bc 77.20 ± 0.95 bcd 74.33 ± 1.76 d 76.40 ± 1.82 cd <0.001 Organic matter (%) 4.47 ± 0.21 ab 4.23 ± 0.35 ab 4.23 ± 0.06 ab 4.70 ± 0.20 a 4.47 ± 0.06 ab 4.67 ± 0.12 a 4.13 ± 0.15 b 4.03 ± 0.15 b 0.003 1Means ± standard deviation (n = 3 soil samples per month) 2 Results of one-way ANOVA. a-e, Means within a row with different letters significantly differ (p < 0.05). ppm, parts per million. 2.4.3 Forage Composition and Height 33 The forage composition varied greatly across the laying season (Figure 2). The pasture featured a diverse mix of species, with the most prevalent being clover (Trifolium repens), fescue (Festuca), thistle (Cirsium), smartweed (Persicaria lapathifolia), and aster (Tripolium pannonicum). Additionally, the months with highest seasonal temperatures, July, and August, had the most plant diversity despite the impact of seasonal changes on the forage height. The difference between pre- and post-graze heights varied throughout the year. During peak summer, post-graze heights were especially low (e.g., June’s drop from 59.1 cm to 6.2 cm). From September to December, forage consumption also shifted, leading to smaller differences between pre- and post- graze heights and a reduced variety of forage as the season was ending. 34 Figure 2. Monthly Forage Composition and Estimated Hen Forage Intake. (A) Illustrates the proportion and types of species that make up the monthly forage composition. (B) Height of forage before and after the hens grazed representing intake estimates across the year. *Pre-Graze height data not available 35 2.4.4 Forage and Layer Hen Feed Nutrient Composition Proximate analysis values for monthly forage and feed are displayed in Figure 3 and Appendix Table A1. In this study, the highest crude protein (CP) levels were observed in July (17.30 % DM) and October (17.40%), with lower levels in August (12.10 %) and December (12.47 %) (p = 0.003). Throughout the grazing season, ADF values ranged from 36% to 45% DM, with the lowest values in the early season and the highest in August, indicating increasing plant maturity by the end of summer (p < 0.001). Within this pasture raising system, TDN ranged widely across the grazing season from 47 to 61% DM (p < 0.018). Low quality forage TDN values fall within 45-52% DM, while mid quality forage ranges 52-58% DM, and high-quality forage exceeds 58% (Dillard, 2019) . Overall, the feed had a higher availability of digestible nutrients compared to the forage. Additionally, forage and feed fatty acid profiles are presented in Appendix Tables A2 and A3. Total forage fatty acids ranged from 3.625 g per 100 g in December to 14.801 g per 100 g in July (p = 0.121), whereas feed samples contained significantly more fat, averaging 164.131 g per 100 g of sample. Forage alpha-linolenic acid (ALA) content peaked in July at 6.681 g per 100 g and gradually decreased as the season progressed, reaching a low of 0.761 g per 100 g in December (p = 0.761). The feed samples contained higher total n-3 fatty acid levels (13.422 g per 100 g), nearly double the highest forage n-3 content (6.711 g per 100 g). Feed n-3 fatty acids primarily comprised docosahexaenoic acid (DHA) and DPA n-3. Forage and feed antioxidant data are detailed in Appendix Table A4. Forage carotenoid content was highest in May (765.92 µg per g) and lowest in November (73.06 µg per g) (p = 0.001) but remained significantly higher than feed carotenoid levels, which averaged 14.47 µg per g. Total forage phenolic content was generally higher than feed phenolic content, except in November. 36 Figure 3. Seasonal changes in the forage quality and proximate analysis. Means and standard error of the mean (SEM) are shown. (A) Forage proximate analysis data (B) Forage quality based on total digestible nutrients. ADF; acid detergent fiber, NDF; neutral detergent fiber, TDN; total digestible nutrients. Results of one-way ANOVA. a-e, Means within a row with different letters significantly differ p < 0.05. † Indicates Low (45%), Medium (52%), and High (58%) quality forage based on TDN (% DM) 2.4.5 Egg Characteristics Significant differences in the egg characteristics are shown in Table 3. Across the grazing season, significant differences were observed in egg weight ranging from 53 to 60 g (p = 0.004). Eggs from July and November were significantly larger compared to September (p = 0.004). The yolk fan values ranged from 7.08 in May to 9.54 in December (p < 0.001), with the highest value observed in the peak summer months and December. Based on colorimeter values, yolk colors were significantly lighter in June and September, had a more prominent yellow color in the month of October, and had strongest red influence in the month of August. Haugh units significantly varied, ranging from 61.20 in August to 88.28 in October (p < 0.001). 37 Table 3. Physical Characteristics of the Eggs by Month1 Parameter May Jun Jul Aug Sep Oct Nov Dec Egg weight (g) 56.57 ± 5.43 ab 58.16 ± 4.97 ab 60.70 ± 6.73 a 58.85 ± 9.93 ab 53.39 ± 6.69 b 57.73 ± 6.70 ab 60.38 ± 4.94 a 57.31 ± 4.24 ab p- value2 0.004 Shell weight (g) 5.53 ± 0.54 abc 5.73 ± 0.48 abc 5.75 ± 0.84 abc Yolk weight (g) 12.80 ± 1.00 cd 13.00 ± 0.90 cd 14.38 ± 2.14 ab Dried yolk weight (g) 6.58 ± 0.56 bc 6.68 ± 0.51 abc 7.32 ± 1.13 a 5.91 ± 1.05 ab 14.02 ± 1.84 abc 6.92 ± 0.91 ab 5.28 ± 0.79 c 5.45 ± 0.82 bc 5.92 ± 0.41 ab 6.12 ± 0.49 a 0.001 12.02 ± 1.88 d 6.10 ± 0.99 c 13.15 ± 1.65 bcd 6.71 ± 0.93 abc 13.88 ± 1.22 abc 7.11 ± 0.69 ab 14.73 ± 1.09 a 7.31 ± 0.61 a <0.001 <0.001 Albumin weight (g) 38.25 ± 4.79 ab 39.42 ± 4.15 ab 40.58 ± 5.08 a 38.92 ± 7.66 ab 36.10 ± 4.71 b 39.13 ± 4.92 ab 40.57 ± 3.99 a 36.46 ± 3.26 ab 0.010 Albumin height (μm) 7.28 ± 0.95 ab 6.61 ± 1.04 bc 5.85 ± 1.39 cd 4.45 ± 1.21 e 7.04 ± 1.44 ab 7.73 ± 1.13 a 6.63 ± 1.09 bc 5.55 ± 0.99 d <0.001 Haugh unit 86.21 ± 4.63 a 81.27 ± 6.60 ab 74.04 ± 12.01 b 61.20 ± 18.34 c 85.07 ± 9.43 a 88.28 ± 6.51 a 80.56 ± 7.65 ab 73.81 ± 7.35 b <0.001 Yolk color fan3 7.08 ± 1.59 d 7.96 ± 1.20 bcd 8.62 ± 1.41 abc 9.00 ± 1.38 ab 7.33 ± 1.88 cd 8.38 ± 2.79 abcd 8.79 ± 0.88 abc 9.54 ± 1.38 a <0.001 Colorimeter4 (L) 67.55 ± 3.04 ab 68.90 ± 1.86 a 68.06 ± 2.52 ab 66.71 ± 2.55 ab 68.86 ± 2.98 a 66.07 ± 3.94 b 67.68 ± 1.21 ab 65.78 ± 2.35 b <0.001 Colorimeter (a) 10.68 ± 3.27 d 14.83 ± 2.80 bc 15.86 ± 3.29 abc 19.26 ± 3.29 a 14.58 ± 5.02 c 17.74 ± 6.33 abc 18.20 ± 1.56 ab 17.34 ± 3.33 abc <0.001 Colorimeter (b) 56.53 ± 4.02 d 61.56 ± 2.94 bc 60.64 ± 2.62 c 64.60 ± 3.62 b 60.57 ± 3.78 c 69.83 ± 4.75 a 61.46 ± 3.69 bc 59.52 ± 4.10 cd <0.001 1 Means ± standard deviation (n = 24 eggs per month) 2 Results of one-way ANOVA. 3Yolk color fan was measured on a scale of 1-16 from light yellow to dark orange. a-e, Means within a row with different letters significantly differ (p < 0.05). 4 Colorimeter numerically assess color gradient (L* scale quantifies whiteness, a*, redness, and b*, yellowness) 2.4.6 Egg Yolk Antioxidants Changes in the yolk antioxidant profile can be observed in Figure 4 and Appendix Table A5. Significant changes in the yolk antioxidant profile were observed across the season based on vitamin total carotenoids, beta-carotene, and vitamin E content. Total yolk phenolic content 38 remained stable across the year, showing no apparent seasonal variations. (p = 0.019). Vitamin A levels in egg yolks gradually increased throughout the summer, peaking in September (p < 0.001), while Vitamin E rose significantly from May to November before dropping sharply in December (p < 0.001). Conversely, total carotenoid levels rose from May, peaking in August, and remained relatively high through October before stabilizing in December (p < 0.001), with similar trends observed with beta-carotene content. Figure 4. Significant changes in the yolk antioxidant profile. Monthly means and SEM are shown. (A) Changes in the vitamin A and total carotenoid content (B) Changes in yolk vitamin E content. Results of one-way ANOVA. a-e, means within a row with different letters significantly differ (p < 0.05). 2.4.7 Egg Yolk Fatty Acid Profiles Seasonal variations in yolk fatty acids are presented in Figure 5, Table 4 and Appendix A6 and A7. Significant monthly changes in fatty acid profiles were observed throughout the grazing season, with total fatty acids peaking in May at 20.84 g per 100 g and progressively declining to a low of 11.38 g per 100 g in October, before continuing to decrease through December. These values remained consistently below the expected 28.8 g per 100 g of fresh yolk (p < 0.001). Saturated fatty acids were significantly lower than expected USDA values, with total palmitic acid peaking at 4.98 g per 100 g (p < 0.001) compared to the expected 6.8 g per 100 g, while total 39 stearic acid content consistently fell below the USDA expectation of 2.42 g per 100 g of yolk (p < 0.001) (Agriculture, 2019). Across the season, cholesterol ranged from 0.809 g in May to 1.209 g per 100g in September (p < 0.001) peaking halfway through the season. Although slight variations were observed in cholesterol content, overall, the content was close to the expected USDA value of 1.08 g per 100 g of egg yolk (Agriculture, 2019). Omega-3 content varied widely throughout the grazing season, with lower levels (0.234 g to 0.516 g per 100g) observed during the late spring and summer months, followed by a significant increase to 1.349 g per 100 g in September (p < 0.001). The n-6:n-3 ratio was closest to the recommended 4:1 during the fall months (p < 0.001). As shown in Appendix Table 3, relative n- 6 content exhibited only minor fluctuations across the season, indicating that the lower ratio observed in the fall was primarily driven by the substantial increase in n-3 fatty acids rather than changes in n-6 levels. Changes across the grazing season were observed in the branched-chain (BCFA) and conjugated linoleic acid (CLA) fatty acids in Table 3 and Appendix Table A7. Branch chain fatty acids that were quantified in this pasture-raised system were C15:0-iso, C15:0- anteiso, C16:0-iso, C17:0-iso, C17:0-anteiso, C18:0-iso, and C18:0-anteiso. Total BCFA levels were significantly higher in September compared to May, July, August, October, and December, indicating a seasonal effect on BCFA production (p = 0.002). In this system, CLA was present in the egg yolks in four isomers: cis-9, trans-11, trans-10, cis-13, and trans-trans CLA. Total CLA ranged from 0.21% in May to 0.41% in October (p < 0.001) (Mir et al., 2004). 40 Figure 5. Notable Seasonal Variations in the Yolk FA Profile. Monthly means and SEM are shown. (A) Total SFA, MUFA, and PUFA values across the grazing season compared to the USDA expected value for total FA. (B) Palmitic, stearic, and total cholesterol across the season compared to expected USDA nutrient content. (C) Monthly changes in the n-6:n-3 ratio compared recommendation (Simopoulos, 2008). (D) Seasonal variations in the total and individual omega- 3 fatty acid content. SFA, saturated fatty acids; MUFA, monounsaturated fatty acids, PUFA, polyunsaturated fatty acids; † USDA Cage-Free Egg Yolk expected nutrient value (25.45 g Total Fat, 6.86 g Palmitic Acid, 0.104 g Stearic Acid, and 1.08 g per 100 g)(Agriculture, 2019). Results for the Yolk SFAs, cholesterol, and the n-6:n-3 ratio as shown as mean ± SEM. 41 Table 4. Egg yolk branched chain and conjugated linoleic fatty acids by month (g of fatty acid per 100 g of fresh egg yolk)1 May Jul Sep Oct Nov Dec p-value2 Fatty Acid CLA C14:0- iso C15:0- iso C15:0- anteiso C16:0- iso C17:0- iso C17:0- anteiso C18:0- iso C18:0- anteiso Carbon Number 9c, 11t 18:2 0.016 ± 0.002  b 0.012 ± 0.002  cd 0.022 ± 0.006  a 0.017 ± 0.003  b 0.022 ± 0.002  a 0.015 ± 0.002  bc <0.001 11t, 13c 18:2 0.009 ± 0.001  c 0.009 ± 0.001  bc 0.012 ± 0.002  a 0.01 ± 0.001 b c 0.011 ± 0.001  b 0.010 ± 0.001  bc <0.001 11t, 13t 18:2 0.032 ± 0.002  bc 0.026 ± 0.004  de 0.046 ± 0.007  a 0.033 ± 0.005  b 0.041 ± 0.003  a 0.031 ± 0.004  bcd <0.001 t, t 18:2 0.009 ± 0.001  b 0.010 ± 0.001  b 0.011 ± 0.002  a 0.009 ± 0.001  b 0.010 ± 0.001  b 0.009 ± 0.001  b <0.001 14:0 LOD LOD LOD LOD LOD LOD ND 15:0 15:0 16:0 17:0 17:0 18:0 18:0 6.812 ± 1.209  a 5.548 ± 0.539  b 6.591 ± 1.447  ab 4.206 ± 1.158  c 6.238 ± 0.677  ab 4.194 ± 0.645  c <0.001 9.667 ± 2.024  a 7.382 ± 0.818  b 7.26 ± 1.039 b 5.139 ± 1.593  c 7.311 ± 0.783  b 5.307 ± 0.881  c <0.001 3.684 ± 0.957  a 3.271 ± 0.983  ab 2.925 ± 0.649  abc 1.675 ± 0.661  e 2.907 ± 0.495  abc 1.760 ± 0.318  de <0.001 3.290 ± 0.899  a 2.996 ± 0.975  ab 2.629 ± 0.588  abc 1.457 ± 0.560  e 2.565 ± 0.45 a bc 1.588 ± 0.283  de <0.001 0.317 ± 0.072  a 0.215 ± 0.053  bcd 0.243 ± 0.067  abc 0.184 ± 0.101  cd 0.292 ± 0.059  ab 0.147 ± 0.042  d <0.001 10.596 ± 2.42 4 b 14.575 ± 5.41 6 a 11.161 ± 2.01 4 ab 8.680 ± 2.516  b 8.934 ± 1.500  b 11.291 ± 2.69 1 ab 0.006 0.083 ± 0.022  a 0.063 ± 0.015  bc 0.067 ± 0.014  ab 0.034 ± 0.015  d 0.058 ± 0.017  bc 0.034 ± 0.006  d <0.001 Total CLA 0.066 ± 0.005  cd 0.057 ± 0.007  cd 0.083 ± 0.027  a 0.069 ± 0.010  bc 0.083 ± 0.006  ab 0.065 ± 0.008  cd <0.001 Total BCFA 0.071 ± 0.005  b 0.071 ± 0.007  b 0.084 ± 0.014  a 0.072 ± 0.008  b 0.075 ± 0.004  ab 0.072 ± 0.007  b <0.001 Total isoBCFA 0.055 ± 0.004  b 0.055 ± 0.006  b 0.065 ± 0.013  a 0.056 ± 0.006  ab 0.058 ± 0.003  ab 0.057 ± 0.006  ab 0.001 Total anteisoBCFA 0.016 ± 0.001  bc 0.019 ± 0.002  a 1 Means ± standard deviation (n = 24 eggs pooled into n = 12 replicates per month) 2 Results of one-way ANOVA. a-e, Means within a row with different letters significantly differ (p < 0.05). OCFA, odd-chain fatty acids; CLA, conjugated linoleic acid; FA, fatty acids. 0.015 ± 0.002  c 0.016 ± 0.002  bc 0.015 ± 0.002  bc 0.016 ± 0.001  bc <0.001 42 2.4.8 Yolk Mineral Profile The yolk mineral profile is reported in Appendix Table A8. Seasonal changes in the yolk mineral profile were observed, with phosphorus, magnesium, and manganese generally peaking during the summer months, particularly in July (p < 0.001 for all). In contrast, sodium levels were notably higher in November and December compared to the rest of the grazing season (p < 0.001). Essential minerals, including calcium, potassium, magnesium, iron, zinc, and selenium, were insufficient throughout the season for the average yolk to be classified as a high source of nutrients (Health, 2024). 2.4.9 Correlations between yolk and forage nutrients and seasonal impacts In Figure 6, Spearman correlations were carried out across yolk nutrients, forage nutrients, individual forage species, and environmental changes to demonstrate significant relationships across the whole biosystem (p < 0.05). Yolk cholesterol content observed strong positive relationships with orchard grass, fescue, and horse nettle forage species. Yolk total carotenoid and beta-carotene content were significantly associated with the month, forage vitamin E, meadow grass, foxtail species. Rainfall displays a strong negative relationship with forage vitamin E. The yolk fan score was primarily linked to forage nutrient parameters but unexpectedly showed an inverse relationship with forage phenolics and total carotenoid content. Additionally, among the yolk nutrients most influenced by forage intake, no significant relationships were observed between their levels in the forage (n-3 PUFAs, carotenoids, vitamin E, phenolics) and their corresponding levels in the eggs. 43 Figure 6. Spearman correlation matrix illustrating significant relationships across monthly averages of egg nutrients, forage nutrients, environmental changes, and forage species parameters (p<0.05). The color intensity represents the strength of the correlation depicted: Blue represents R coefficient values between 0 to 1, while red represents values between 0 to –1. Text colors distinguish between sample type: purple for environment, blue for forage species present in the pasture, green is assigned to forage nutrients, and yellow to egg nutrients. total omega-3 fatty acids, total n-6; total omega-6 fatty acids, total SFA; total saturated fatty acids; TDN, total digestible nutrients 44 2.4.10 Yolk, Forage, and Feed Discriminant and Random Forest Analysis The sPLS-DA and random forest analysis results are presented in Figure 7 with yolk and forage PCA loadings displayed in Appendix Tables A9 and A10, respectively. (A) The sPLS-DA plot of yolk nutrients shows minimal separation between May to August and December, with noticeable differentiation observed during the fall months of September through November. (B) The forage and feed sPLS-DA scores plot indicate consistent overlap in forage nutrient profiles across all months, while feed nutrients exhibit distinct separation. (C) The random forest analysis highlights the importance of yolk nutrients in distinguishing individual months. Vitamin A and E emerged as the most discriminative variables, followed by DHA (C22:6 n-3), total n-3 fatty acids, and the n-6:n-3 ratio. These findings further confirm the separation of September through November from other seasons, driven by a lower n-6:n-3 ratio, higher levels of essential n-3 fatty acids, and elevated vitamin E and A concentrations during the fall months. (D) The forage and feed random forest analysis identified saturated fat and vitamin E as the most critical indicators of separation. The feed samples were characterized by a lower saturated fat profile and reduced vitamin E levels compared to forage. Vitamin E content was highest in the forage in December (Appendix Table A10), meanwhile vitamin E was lowest in the eggs during the same month. 45 Figure 7. System Nutrient Structure. (A) sparse Partial Least Squares Discriminant Analysis (sPLS-DA) plot using egg nutrient parameters only showing separation and clusters based on month, with some overlaps. (B) Random Forest (RF) variable importance plot showing yolk nutrient parameters that differentiate between monthly collections. (C) sPLS-DA plot using forage and feed nutrient parameters only showing separation and clusters based on month, with some overlaps.  (D) RF variable importance plot showing nutrient parameters that differentiate between monthly collections and layer hen feed. For sPLS-DA plots, elipses are representative of 95% confidence interval regions. For RF plots, the y-axis represents nutrient parameters in order of importance for monthly classification (from top to bottom). The x-axis shows mean decrease accuracy, with a higher value indicating the importance of that phytochemical in predicting groups. Total SFA; total saturated fatty acids, total MUFA; total monounsaturated fatty acids, total PUFA; total polyunsaturated fatty acids, t. carotenoids; total carotenoids, total n-3; total omega-3 fatty acids, total n-6; total omega-6 fatty acids, t. phenolics; total phenolics. 46 2.5 Discussion In the present study, we demonstrated significant changes in the nutrient profile of eggs including the fatty acid and antioxidant composition that related to seasonal fluctuations in weather, soil quality, and forage composition. The findings of this study highlight the interwoven nature of environmental factors and egg nutrient quality within free-living animal production systems. Pasture-raising systems are shaped by numerous external influences on chicken habitats, identifying factors that impact dietary preferences or the prediction of yolk nutrient deposition is challenging, emphasizing the need for this research. High forage consumption is typically expected to increase yolk levels of vitamin E, omega-3 PUFAs, carotenoids, and phenolics, as observed in grass-fed versus grain-fed systems (Krusinski et al., 2023; van Vliet, Bain, et al., 2021). However, pasture-raising systems are shaped by numerous external influences on chicken habitats and dietary patterns. Chickens are considered omnivores and cannot thrive on a forage-only diet; they prefer insect-based diets and are often consuming rocks and ground material to aid in their digestion (Belhadj Slimen et al., 2023; Kilpatrick, 2022). Their opportunistic feeding habits make it difficult to accurately measure their intake while maintaining their pastured lifestyle, which may contribute to seasonal variations in yolk nutrient profiles. Seasonal variations in the yolk fatty acid and mineral profile were likely due to diminished forage consumption and greater reliance on supplemental feed. Most notably, the n-6: n-3 ratio fluctuated across the season, ranging from 2.78 to 13.72. Eggs collected during the fall months (September–December) achieved the recommended 4:1 ratio, driven primarily by the increased n- 3 content, as linoleic levels remained relatively stable (Simopoulos, 2008). Yolk nutrient profiles during the fall particularly reflected the influence of feed, with random forest analysis revealing that total n-3 and DHA levels in yolks did not align with the seasonal high and low omega-3 density 47 observed in forage. Instead, yolks produced between September and November contained significantly higher amounts of n-3 PUFAs, vitamin E, and vitamin A, accompanied by the lowest n-6:n-3 ratio. These improvements were primarily attributed to increased feed consumption, as feed was heavily supplemented with omega-3 fatty acids and vitamin A. This disconnect between forage nutrient density and yolk deposition could reflect a combination of factors including low actual forage intake, selective foraging behavior, nutrient loss during digestion, or differential metabolic prioritization of nutrients under varying environmental conditions. Yolk CLA and BCFAs, showed seasonal patterns influenced by diet, with CLA synthesis linked to linoleic acid levels (Mir et al., 2004; Nasrollahzadeh et al., 2023; Qaisrani et al., 2015). Exposure to cattle in regenerative systems may account for the presence of uncommon BCFAs, such as C18:0-iso, which are typically found in cattle products and rarely detected in eggs (Patel et al., 2013; Ran-Ressler et al., 2014; Sergin et al., 2021; Sergin et al., 2022; Undersander D., 2014). Mineral content was relatively stable throughout the season, except for potassium, which spiked in the fall months. This increase likely reflects the layer hens’ greater reliance on feed rather than fresh forage during the colder months, as the feed contained a higher sodium concentration compared to forage. Additionally, reliance on supplemental feed is further supported by the sPLS- DA scores plot for yolk nutrients, which showed fall months clustering separately from earlier months and December, Similarly, forage and feed sPLS-DA plots demonstrated distinct groupings, suggesting feed became the primary driver of yolk nutrient changes during the fall. Additionally, weather deviations from seasonal norms—such as heavier or lighter rainfall observed in this system—may have further influenced forage quality and availability, thereby affecting hen foraging behavior and feeding preferences (Vallentine, 2000). This pattern underscores the critical 48 role of feed supplementation in meeting the nutritional needs of pasture-raised hens when environmental conditions limit forage availability. Antioxidant deposition in egg yolks reflected the interplay between forage nutrient content and environmental stress. Vitamin E levels in yolks closely mirrored forage vitamin E levels throughout most of the season, except in December, when cold stress likely redirected vitamin E toward the hens’ metabolic needs rather than yolk deposition (Kim et al., 2023). In addition to cold stress, predator disturbances may have also contributed to behavioral or metabolic changes, further affecting nutrient deposition in the eggs. Vitamin A content peaked gradually from September to December. This discrepancy may be attributed to cold stress (<16°C), as dropping temperatures prompt hens to prioritize heat generation over digestion and nutrient absorption, resulting in lower vitamin levels in eggs (Kim et al., 2023; Sahin et al., 2003). Carotenoid levels in yolks, however, remained stable even during colder months, showcasing the hens’ ability to maintain antioxidant deposition despite environmental challenges. It is also possible that differences in nutrient bioavailability and deposition efficiency, particularly under stress conditions, influenced which forage-derived compounds were absorbed and stored in yolk tissue. These findings highlight the importance of forage-derived antioxidants, particularly during the summer and early fall. Yolk color, a key quality parameter influenced by carotenoid content, fell short of consumer preferences despite seasonal variations. Consumer preferences align with the darkest values of the DSM Yolk Color Fan, which are associated with more nutrient-rich yolks (Hernandez et al., 2005). However, yolks in this system were far below consumer preferences, while also being lower than some cage-free eggs, which were given an average DSM value of 10.3 in a similar study (Bertoncelj et al., 2019; Kojima et al., 2022; Sergin et al., 2021). While differences in yolk pigmentation were observed, the reason for these changes is unclear. The introduction of Black 49 Sex-linked hens in October, replacing Comet hens, did not impact the overall trend in yolk color. Previous research has shown that while diet is the primary factor influencing yolk carotenoid content, breed may also play a role in carotenoid absorption and metabolism, potentially contributing to differences in yolk pigmentation (Kojima et al., 2022). This suggests that both forage composition and breed-specific factors could influence yolk pigmentation and should be further explored in future studies. Additionally, seasonal changes in egg white protein quality, measured by Haugh units (HU), were closely tied to temperature fluctuations. Eggs produced in this system overall met the USDA AA quality standard (HU ≥ 72), except in August, when values dropped to Grade A (Eisen et al., 1962a; Gabriela da Silva Pires et al., 2020). Lower HU values were observed during the hot summer (July–August) and cold winter (November–December) months, aligning with environmental stressors outside the optimal laying temperature range of 19–22 °C (Pawar et al., 2016). The highest HU values occurred in May and September, when temperatures were within the thermoneutral zone, highlighting the role of temperature in albumen quality and freshness (Barrett et al., 2019). Based on our results, the majority of eggs met the necessary criteria for sale under U.S. food laws. The only notable exception was albumen quality in August, where Haugh unit values fell into the USDA Grade A range rather than AA. While seasonal fluctuations in omega-3 levels were observed, these variations did not appear to impact regulatory compliance. However, such fluctuations could influence nutrient labeling or marketing claims related to omega- 3 content. Further research could assess whether seasonal shifts impact classification for commercial sale. A key limitation of free-living systems is the difficulty in controlling hen intake while adhering to pasture-raising principles, especially regarding non-pasture ingredients such as insects. 50 Free-living systems carry the difficulty in controlling hen intake while adhering to pasture-raising principles, particularly regarding non-pasture ingredients such as insects. Several insect species known to be nutrient-rich—black soldier fly larvae, crickets, mealworms, house flies, and maggots—are commonly found in Southern Ohio, particularly during the warmer months (May– September) when pasture-raised hens are actively foraging. These insects are known to contain measurable amounts of omega-3 fatty acids and can also be rich in vitamin E, and carotenoids, though their nutritional profiles vary depending on life stage and diet (Kolobe et al., 2023; Schiavone et al., 2019). While insect intake was not directly measured in this study, previous research suggests that for-age—including insects, worms, and plants—contributes approximately 5–10% of the hens’ diet in pasture-based systems (Schiavone et al., 2019). Insects likely comprise only a subset of that total, but given their nutrient density, even small amounts may meaningfully influence egg nutrient composition. The seasonal presence of these insects may help explain some of the trends in omega-3 and antioxidant levels observed in the eggs and points to an important area for future investigation. Practical challenges like predation led to the introduction of younger Black Sex-linked hens in October, replacing Comet hens and is a limitation of this study. We acknowledge that the breed change was a significant alteration in the study population and may have contributed to observed changes in egg nutrient profiles. While both breeds were managed identically and had access to the same diet, differences in nutrient metabolism, or age-related physiology could not be separated from seasonal effects, as no overlap in time points existed between the two breeds. Breed differences are generally associated more with eggshell color and production rate than with yolk nutrient profiles (Drabik et al., 2021). In addition, younger hens may exhibit different nutrient deposition patterns during their peak laying period, potentially affecting yolk composition 51 independent of diet (Henry, 2019; Zhang et al., 2023). Both Comet and Black Sex-Linked hens are active foragers in pasture systems (Alig et al., 2023). Although direct comparisons are limited, commercial brown egg layers and hybrids generally show strong foraging motivation when given pasture access, suggesting breed differences likely had minimal impact on nutrient intake (Alig et al., 2023). Previous research indicates that feed type, rather than breed, has the greatest influence on egg nutrient profiles, particularly fatty acid content (Franco et al., 2020; Romero et al., 2024). Egg (Drabik et al., 2021)composition changes may result from both seasonal cycles and hen age, though cyclic variation is primarily observed in egg physical characteristics, with little evidence supporting breed influence on nutrient content (Christians, 2002). Since this study spanned only one year, we cannot confirm whether these variations recur annually or are age-related. Future multi-year studies are needed to distinguish seasonal patterns from aging effects. Nevertheless, these challenges also highlight the adaptability of pasture-raising systems, where hens modify their reliance on forage and feed in response to environmental and seasonal changes. This emphasizes the importance of characterizing nutrient shifts across the season to optimize egg quality in free-living systems. Future research should focus on adapting pasture-based systems to different regions and climates to assess the broader applicability of these findings. As this study was conducted on a single farm in Southern Ohio, the results may not be generalizable to all pasture-raised systems. Regional variations in climate, forage composition, and management practices could influence egg nutrient profiles, necessitating multi-location studies to better understand these effects. Practical strategies to address the challenges of hen intake control, predation, and nutrient consistency will be critical for optimizing production. One example of such a strategy is targeted feed supplementation during periods of low forage quality. In this study, fall feed supplementation 52 improved yolk omega-3 and vitamin levels, demonstrating its potential as a buffer against seasonal nutrient variability. Regionally adapted approaches like this may help producers maintain consistent egg quality year-round. Additionally, the egg industry can benefit from characterizing seasonal nutrient shifts to improve year-round egg quality, offering consumers reliable access to nutrient-dense eggs. 2.6 Conclusions Seasonal environmental variations significantly influenced forage and egg nutrient profiles. Yolk n-3 fatty acids and vitamin A peaked in fall due to the forage-to-feed shift. Yolk antioxidant accumulation reflected forage quality and environmental conditions, while other nutrients like phenolics remained stable. Rotational grazing enriched egg composition by broadening the range of available nutrients, demonstrating the adaptability of pasture-raised hens to seasonal stressors and the importance of managing forage and feed intake for consistent, nutrient-dense egg production. Future directions should aim on evaluating these findings across different regions to determine how broadly applicable they are across the country. In this study, the best months to purchase pasture-raised eggs were in the fall, as nutrient profiles were at their peak due to seasonal shifts. However, the significant variation observed in nutrient profiles highlights the need for greater consistency in pasture-raised egg production. While this study underscores the importance of evaluating seasonal shifts, it also points to the necessity of refining management practices to ensure nutrient-dense eggs year-round, offering consumers more reliable options for improved dietary benefits. 53 CHAPTER III: CONCLUSIONS AND FUTURE DIRECTIONS 3.1 Conclusions This thesis investigated how seasonal variation in pasture-based egg production systems influences the nutritional composition of egg yolks. By conducting monthly sampling of forage, soil, and eggs over a full grazing season in Southern Ohio, this work provides new insight into how environmental factors affect nutrient deposition, particularly omega-3 fatty acids, carotenoids, and fat-soluble vitamins, in regenerative poultry systems. Chapter I presented a comprehensive review of the scientific literature on pasture-raised egg nutrition. It explored the roles of hen diet, forage access, and environmental conditions in shaping yolk composition and highlighted consistent findings that pasture-raised eggs contain higher levels of bioavailable nutrients than conventionally produced eggs. Importantly, this chapter also identified a key gap in the literature: the lack of research examining how these nutrient advantages fluctuate across the grazing season due to changes in pasture quality, plant diversity, and climate conditions. Chapter II addressed this gap through a field-based study that evaluated how seasonal changes in forage composition and quality impact egg nutrient density. The results revealed clear temporal patterns. Vitamin E concentrations steadily increased over the season, while vitamin A peaked in late summer. Carotenoid levels were elevated in both midsummer and late autumn, and omega-3 fatty acid content—especially alpha-linolenic acid (ALA) and docosahexaenoic acid (DHA)—was significantly higher in eggs collected during the fall. These seasonal trends aligned with improvements in pasture quality, particularly total digestible nutrients (TDN), and were confirmed through multivariate analyses that identified September to November as the period of highest egg nutrient density. 54 3.2 Future Directions Overall, this thesis underscores the importance of considering seasonal variability when measuring and marketing the nutritional value of pasture-raised eggs. While these systems offer well-documented advantages regarding animal welfare, environmental sustainability, and enhanced omega-3 and antioxidant content, their nutritional outputs are not static. The nutrient composition of eggs—particularly concerning carotenoids, vitamin E, and long-chain omega-3 fatty acids—fluctuates throughout the grazing season, influenced by forage quality, environmental conditions, and pasture management practices (Chatzidimitriou, 2020; Daley et al., 2010; Krusinski, Maciel, et al., 2022) Recognizing and accounting for these dynamics is essential to ensure consistent product quality, optimizing on-farm decision-making, and supporting transparent consumer labeling (Harmon et al., 2019; Jacob et al., 2018). Moreover, it enables producers to refine their pasture management and supplemental feeding strategies to better align with nutrient goals across different seasons. Future research should investigate adaptive management approaches, including rotational grazing that promotes high-nutrient forages throughout the year (Lagrange, 2020). 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Proximate analysis of the forage samples by month and the layer hen feed1 Parameter May Jun Jul Aug Sept Oct Nov Dec % Moisture % Dry matter (DM) Crude protein (% DM) ADF (% DM) NDF (% DM) Lignin (% DM) 86.20 ± 1.92 a 13.80 ± 1.92 c 16.37± 1.55 ab 36.07 ± 1.19 c 58.70 ± 1.73 b 4.87 ± 0.32 d 76.00 ± 3.41 b 24.00 ± 3.41 b 12.80 ± 0.62 ab 39.67 ± 1.64 bc 62.97 ± 3.30 ab 6.27 ± 1.25 bcd 75.53 ± 2.41 b 24.47 ± 2.41 b 17.30 ± 2.20 a 40.73 ± 2.84 abc 61.50 ± 2.43 ab 6.40 ± 0.92 bcd 66.93 ± 2.72 c 33.07 ± 2.72 a 12.10 ± 0.87 b 45.97 ± 0.64 a 68.10 ± 3.75 a 10.03 ± 1.89 ab 78.30 ± 2.46 b 21.70 ± 2.46 b 14.10 ± 1.00 ab 43.80 ± 4.03 ab 62.27 ± 3.96 ab 9.40 ± 2.13 abc 78.90 ± 1.57 b 21.10 ± 1.57 b 17.40 ± 1.76 a 29.80 ± 1.61 d 49.87 ± 3.32 c 5.57 ± 1.53 cd 77.47 ± 3.56 b 22.53 ± 3.56 b 14.90 ± 2.29 ab 45.60 ± 0.79 a 63.20 ± 3.85 ab 9.40 ± 2.13 a 72.57 ± 0.93 bc 27.43 ± 0.93 ab 12.47 ± 2.04 b 41.63 ± 1.07 abc 66.2 ± 0.56 ab 10.00 ± 1.22 ab p- value2 Layer Hen Feed <0.001 11.68 ± 0.5 <0.001 88.35 ± 0.54 0.003 18.02 ± 1.67 <0.001 6.65 ± 0.38 <0.001 13.28 ± 1.15 <0.001 2.32 ± 0.44 Starch (% DM) 0.37 ± 0.29 1.10 ± 0.26 1.30 ± 0.56 0.20 ± 0.00 0.50 ± 0.52 2.57 ± 2.76 1.30 ± 0.40 0.47 ± 0.25 0.183 38.82 ± 4.56 Crude fat (% DM) Ash (% DM) TDN (% DM) Metabolizable energy (mcal/kg) Calcium (% DM) Phosphorus (% DM) Magnesium (% DM) 3.27 ± 0.29 2.83 ± 0.21 3.37 ± 0.55 2.47 ± 0.47 3.33 ± 0.21 3.40 ± 0.53 2.43 ± 0.15 2.80 ± 0.46 0.024 4.50 ± 0.37 11.26 ± 1.94 ab 57.00 ± 2.00  ab 15.14 ± 4.59 a 47.33 ± 5.13  bc 11.24 ± 1.16 ab 54.33 ± 2.08  abc 9.15 ± 1.66 b 47.00 ± 3.46  c 9.35 ± 0.73 b 51.33 ± 3.2 1 bc 10.04 ± 0.26 ab 61.00 ± 2.65  a 8.77 ± 1.30 b 48.67 ± 2.89  bc 7.76 ± 0.38 b 49.33 ± 3.21  bc 0.011 0.018 12.76 ± 1.36 75.83 ± 1.72 2.19 ± 0.08 ab 1.74 ± 0.21 cd 2.09 ± 0.12 abc 1.67 ± 0.13 d 1.91 ± 0.15 bcd 2.35 ± 0.12 a 1.78 ± 0.16 bcd 1.79 ± 0.16 bcd <0.001 3.02 ± 0.07 0.42 ± 0.09 bc 0.29 ± 0.01 a 0.18 ± 0.03 b 0.33 ± 0.02 c 0.19 ± 0.01 b 0.16 ± 0.01 b 0.69 ± 0.14 a 0.30 ± 0.04 a 0.27 ± 0.02 b 0.54 ± 0.08 abc 0.17 ± 0.01 b 0.22 ± 0.04 b 0.71 ± 0.13 a 0.24 ± 0.03 ab 0.27 ± 0.03 b 0.65 ± 0.02 ab 0.30 ± 0.02 a 0.40 ± 0.09 a 0.72 ± 0.10 a 0.23 ± 0.06 ab 0.26 ± 0.05 b 0.57 ± 0.06 abc 0.22 ± 0.01 ab 0.21 ± 0.02 b 0.001 3.12 ± 0.76 <0.001 0.74 ± 0.11 <0.001 0.25 ± 0.03 1Means ± standard deviation (n = 3 forage per month, n = 6 layer hen feed samples) 2Results of one-way ANOVA to compare forage by date. a-e, Means within a row for forage samples with different letters significantly differ (p < 0.05). DM, dry matter; ADF, acid detergent fiber; NDF, neutral detergent fiber; TDN, total digestible nutrients 68 Table A1. (cont’d) Parameter May Jun Jul Aug Sept Oct Nov Dec p- value2 Layer Hen Feed Potassium (% DM) Sodium (% DM) 2.91 ± 0.42 a 1.10 ± 0.17 b 2.90 ± 0.49 a 1.09 ± 0.08 b 1.61 ± 0.34 b 2.83 ± 0.09 a 1.11 ± 0.66 b 0.83 ± 0.23 b <0.001 0.75 ± 0.13 0.01 ± 0.00 bc 0.04 ± 0.00 a 0.02 ± 0.01 b 0.02 ± 0.01 bc 0.01 ± 0.00 c 0.02 ± 0.00 bc 0.01 ± 0.01 bc 0.01 ± 0.00 bc <0.001 0.24 ± 0.06 Sulfur (% DM) 0.30 ± 0.04 a 0.15 ± 0.07 b 0.28 ± 0.05 a 0.12 ± 0.02 b 0.2 ± 0.06 ab 0.31 ± 0.04 a 0.14 ± 0.03 b 0.23 ± 0.01 ab <0.001 0.28 ± 0.05 353.67 ± 104.25 115.00 ± 19.26 21.83 ± 4.36 106.50 ± 25.25 Chloride (% DM) Iron (ppm) 0.78 ± 0.21 b 0.68 ± 0.21 b 0.88 ± 0.36 b 0.65 ± 0.09 ab 0.89 ± 0.11 b 1.23 ± 0.13 a 0.59 ± 0.24 ab 0.52 ± 0.13 b 0.015 0.44 ± 0.03 109.00 ±  56.00 b 901.00 ±  466.00 a 160.00 ±  51.00 b 526.00 ±  118.00 ab 196.00 ±  140.50 b 49.00 ±  22.00 b 409.00 ±  134.50 ab 309.00 ±  126.00 ab 0.010 Zinc (ppm) 3.00 ± 0.50 8.00 ± 1.50 8.00 ± 2.00 7.00 ± 1.50 7.00 ± 0.50 6.00 ± 1.50 7.00 ± 1.00 7.00 ± 0.50 0.170 Copper (ppm) 1.00 ± 0.00 1.50 ± 0.50 2.00 ± 0.00 2.00 ± 0.50 2.00 ± 0.00 2.00 ± 0.50 2.00 ± 0.50 2.00 ± 0.50 0.061 Manganese (ppm) 10.00 ±  3.50 c 95.00 ±  21.50 a 42.00 ±  14.00 abc 60.00 ±  12.50 ab 31.00 ±  11.50 bc 24.00 ±  8.50 c 47.00 ±  17.00 abc 73.00 ±  8.50 ab 0.012 Molybdenum (ppm) NA ± NA 0.50 ± 0.15 0.40 ± 0.15 0.40 ± 0.25 NA ± NA NA ± NA 0.40 ± 0.10 0.30 ± 0.05 0.262 2.15 ± 1.11 69 Table A2. Fatty acid analysis of the forage samples by month and the layer hen feed (g per 100g)1 Fatty Acid Carbon Number May Jun Jul Aug Sept Oct Nov Dec Caprylic 8:0 0.025 ± 0.004  a 0.041 ± 0.002  a 0.071 ± 0.011  a 0.07 ± 0.008  a 0.057 ± 0.014  a 0.056 ± 0.011  a 0.057 ± 0.007  a 0.062 ± 0.122  a p- value2 0.024 Capric 10:0 0.005 ± 0.001 0.008 ± 0.009 0.007 ± 0.002 0.007 ± 0.004 0.005 ± 0.001 0.005 ± 0.001 0.005 ± 0.001 0.034 ± 0.073 0.131 Undecanoic 11:0 0.001 ± 0.000 0.001 ± 0.000 0.001 ± 0.001 0.001 ± 0.000 0.001 ± 0.000 0.001 ± 0.000 0.001 ± 0.000 0.001 ± 0.003 0.818 Lauric 12:0 0.013 ± 0.003  a 0.047 ± 0.003  a 0.046 ± 0.023  a 0.035 ± 0.004  a 0.038 ± 0.004  a 0.037 ± 0.005  a 0.023 ± 0.005  a 0.035 ± 0.051  a 0.037 Tridecanoic 13:0 LOD 0.001 ± 0.000 LOD LOD LOD LOD LOD LOD 0.362 Myristic 14:0 0.038 ± 0.012 0.065 ± 0.027 0.054 ± 0.03 0.064 ± 0.007 0.033 ± 0.001 0.052 ± 0.006 0.067 ± 0.024 0.059 ± 0.064 0.056 Myristoleic 14:1 Pentadecanoic 15:0 LOD 0.015 ± 0.007  b LOD 0.022 ± 0.003  ab LOD 0.015 ± 0.002  b LOD 0.042 ± 0.005  a LOD 0.007 ± 0.001  b LOD 0.008 ± 0.001  b LOD 0.017 ± 0.01 a b LOD 0.006 ± 0.015  b NA 0.034 Palmitic 16:0 1.136 ± 0.500 1.533 ± 0.169 2.612 ± 0.344 2.554 ± 0.213 1.425 ± 0.263 1.722 ± 0.205 1.223 ± 0.562 0.643 ± 2.714 0.113 Palmiteladic 16:1 n-9t LOD LOD LOD LOD LOD LOD LOD LOD NA Palmitoleic 16:1 n-7 0.103 ± 0.038 0.050 ± 0.005 0.117 ± 0.021 0.055 ± 0.006 0.041 ± 0.016 0.062 ± 0.022 0.016 ± 0.009 0.011 ± 0.125 0.060 16:1 n-9 0.018 ± 0.009  c 0.059 ± 0.011  abc 0.048 ± 0.003  abc 0.127 ± 0.014  a 0.029 ± 0.003  bc 0.027 ± 0.029  abc 0.115 ± 0.027  abc 0.085 ± 0.078  ab 0.012 Heptadecanoic 17:0 0.015 ± 0.009 0.028 ± 0.003 0.045 ± 0.007 0.057 ± 0.004 0.024 ± 0.001 0.023 ± 0.003 0.028 ± 0.011 0.015 ± 0.03 0.123 Layer Hen Feed 0.168 ± 0.070 0.014 ± 0.004 0.002 ± 0.001 0.025 ± 0.010 0.002 ± 0.001 1.104 ± 0.435 LOD 0.086 ± 0.033 21.411 ± 9.568 LOD 0.082 ± 0.038 1.635 ± 0.779 0.177 ± 0.077 c10- heptadecanoic 17:1 LOD LOD LOD LOD LOD LOD LOD LOD NA LOD 18:0 Eladic Stearic 0.166 ± 0.078  a LOD 0.529 ± 0.054  a LOD 1Means ± standard deviation n = 3 forage replicates per month and layer hen feed n=6 2Results of one-way ANOVA. a-e, Means within a row with different letters significantly differ p < 0.05. SFA, saturated fatty acids; MUFA, monounsaturated fatty acids, PUFA, polyunsaturated fatty acids; OCFA, odd-chain fatty acids; FA, fatty acids. 0.222 ± 0.030  a LOD 0.296 ± 0.027  a LOD 0.459 ± 0.055  a LOD 0.399 ± 0.097  a LOD 0.349 ± 0.029  a LOD 0.223 ± 0.539  a LOD 18:1 n-9t 0.049 NA 3.461 ± 1.365 LOD 70 Table A2. (cont’d) Fatty Acid Carbon Number May Jun Jul Aug Sept Oct Nov Dec 18:1 n-9 Oleic 18:1 n-11 0.203 ± 0.080  a 0.254 ± 0.190  b 0.351 ± 0.041  a 0.467 ± 0.086  b 0.560 ± 0.051  a 0.227 ± 0.214  b 0.872 ± 0.109  a 1.247 ± 0.157  a 0.393 ± 0.032  a 0.171 ± 0.026  b 0.461 ± 0.114  a 0.057 ± 0.076  b 0.496 ± 0.18 a 0.410 ± 0.162  b 0.643 ± 0.768  a 0.248 ± 0.228  b p- value2 0.007 0.037 Linoleic 18:2 n-6 1.528 ± 0.579 1.564 ± 0.064 2.219 ± 0.31 2.917 ± 0.100 1.282 ± 0.316 1.695 ± 0.317 1.089 ± 0.16 0.799 ± 2.056 0.082 ALA GLA 18:3 n-3 4.256 ± 1.613 3.744 ± 0.252 6.681 ± 1.20 3.987 ± 0.561 3.86 ± 1.957 4.899 ± 1.670 0.940 ± 0.387 0.761 ± 8.744 0.117 18:3 n-6 LOD LOD LOD LOD LOD LOD LOD LOD NA Arachidic 20:0 0.107 ± 0.063 0.115 ± 0.014 0.146 ± 0.047 0.141 ± 0.014 0.074 ± 0.01 0.075 ± 0.015 0.082 ± 0.021 0.062 ± 0.196 0.122 Eicosenoic 20:1 n-9 0.022 ± 0.006 0.015 ± 0.002 0.026 ± 0.006 0.033 ± 0.003 0.023 ± 0.002 0.022 ± 0.003 0.018 ± 0.004 0.017 ± 0.037 0.080 Eicosedienoic 20:2 n-6 0.010 ± 0.002  ab 0.007 ± 0.001  b 0.014 ± 0.006  ab 0.018 ± 0.003  a 0.006 ± 0.002  b 0.008 ± 0.004  ab 0.004 ± 0.001  b 0.005 ± 0.002  b 0.041 Eicosatrenoic 20:3 n-3 0.018 ± 0.006 0.013 ± 0.001 0.03 ± 0.002 0.021 ± 0.005 0.020 ± 0.005 0.023 ± 0.002 0.023 ± 0.004 0.021 ± 0.037 0.075 DGLA Mead 20:3 n-6 20:9 n-9 LOD LOD LOD LOD LOD LOD LOD LOD LOD LOD LOD LOD LOD LOD LOD LOD NA NA Arachidonic 20:4 n-6 LOD 0.015 ± 0.004 0.035 ± 0.006 0.032 ± 0.005 0.023 ± 0.008 0.022 ± 0.003 0.028 ± 0.009 0.026 ± 0.044 0.078 EPA 20:5 n-3 LOD LOD LOD LOD LOD LOD LOD LOD NA Behenic 22:0 0.144 ± 0.066 0.142 ± 0.014 0.273 ± 0.017 0.260 ± 0.028 0.175 ± 0.039 0.162 ± 0.024 0.189 ± 0.024 0.157 ± 0.343 0.124 DTA DPA 22:4 n-6 LOD 22:5 n-3 LOD LOD LOD LOD LOD LOD LOD LOD LOD LOD LOD DPA 22:5 n-6 0.068 ± 0.003  b 0.056 ± 0.019  b 0.098 ± 0.005  ab 0.132 ± 0.030  a 0.080 ± 0.003  ab 0.082 ± 0.010  ab DHA 22:6 n-3 LOD LOD LOD LOD LOD LOD LOD LOD LOD LOD LOD LOD NA NA LOD 0.035 LOD NA Lignoceric 24:0 0.147 ± 0.061  a 0.131 ± 0.013  a 0.203 ± 0.089  a 0.196 ± 0.025  a 0.063 ± 0.019  a 0.057 ± 0.011  a 0.086 ± 0.016  a 0.102 ± 0.179  a 0.034 71 Layer Hen Feed 30.802 ± 16.904 9.440 ± 4.874 84.986 ± 41.376 5.530 ± 2.200 LOD 0.769 ± 0.471 0.833 ± 0.512 0.136 ± 0.110 0.070 ± 0.028 LOD LOD 0.248 ± 0.108 1.495 ± 0.903 0.738 ± 0.299 LOD 2.612 ± 1.952 0.377 ± 0.165 1.513 ± 0.856 0.489 ± 0.361 Table A2. (cont’d) Fatty Acid Carbon Number May Jun Jul Aug Sept Oct Nov Dec p- value2 Total SFA 1.798 ± 0.795 2.307 ± 0.204 3.908 ± 0.582 3.95 ± 0.311 2.348 ± 0.227 2.647 ± 0.235 2.292 ± 0.709 1.308 ± 4.284 0.131 Total MUFA 0.600 ± 0.322 0.993 ± 0.109 0.975 ± 0.178 2.142 ± 0.149 0.687 ± 0.050 0.625 ± 0.198 1.012 ± 0.348 1.000 ± 1.232 0.088 Total PUFA 5.875 ± 2.235 5.374 ± 0.225 9.087 ± 1.503 6.975 ± 0.703 5.212 ± 2.271 6.724 ± 1.966 2.252 ± 0.474 1.55 ± 10.854 0.155 Total n-6 1.601 ± 0.616 1.648 ± 0.084 2.376 ± 0.304 2.967 ± 0.139 1.324 ± 0.314 1.802 ± 0.296 1.122 ± 0.167 0.823 ± 2.102 0.084 Total n-3 4.275 ± 1.619 3.757 ± 0.253 6.711 ± 1.198 4.008 ± 0.565 3.888 ± 1.958 4.922 ± 1.669 0.970 ± 0.387 0.782 ± 8.78 0.117 n-6:n-3 ratio 0.341 ± 0.033 0.420 ± 0.041 0.341 ± 0.02 0.740 ± 0.077 0.341 ± 0.055 0.348 ± 0.043 1.322 ± 0.345 0.981 ± 0.652 0.051 Total OCFA 0.031 ± 0.015 0.051 ± 0.005 0.06 ± 0.009 0.099 ± 0.010 0.032 ± 0.002 0.031 ± 0.003 0.046 ± 0.019 0.021 ± 0.048 0.096 Total FA 8.273 ± 3.352 8.674 ± 0.537 14.801 ± 1.847 13.328 ± 0.996 8.278 ± 2.533 9.839 ± 2.32 6.237 ± 1.175 3.652 ± 16.268 0.121 Layer Hen Feed 28.111 ± 12.833 40.898 ± 26.029 95.122 ± 50.191 81.700 ± 48.876 13.422 ± 5.305 6.805 ± 3.394 0.259 ± 0.110 164.131 ± 88.932 72 Table A3. Fatty acid analysis of the forage samples by month and the layer hen feed (percent of total fatty acids)1 Fatty Acid Carbon Number May Jun Jul Aug Sept Oct Nov Dec Caprylic 8:0 Capric 10:0 Undecanoic 11:0 Lauric 12:0 0.289 ± 0.061  c 0.051 ± 0.025  b 0.008 ± 0.001 b 0.131 ± 0.025  b Tridecanoic 13:0 LOD Myristic 14:0 0.327 ± 0.084  b 0.467 ± 0.006  bc 0.084 ± 0.112  ab 0.013 ± 0.002  ab 0.506 ± 0.048  ab 0.006 ± 0.004  a 0.697 ± 0.347  ab 0.481 ± 0.159  bc 0.058 ± 0.012  b 0.010 ± 0.005  ab 0.298 ± 0.127  ab LOD 0.347 ± 0.173  b 0.551 ± 0.05 b c 0.047 ± 0.027  b 0.007 ± 0.003  b 0.249 ± 0.042  ab 0.001 ± 0.000  b 0.524 ± 0.064  ab 0.763 ± 0.275  abc 0.066 ± 0.022  b 0.009 ± 0.002  b 0.453 ± 0.142  ab 0.58 ± 0.186 b c 0.051 ± 0.02  b 0.006 ± 0.002  b 0.387 ± 0.114  ab 1.057 ± 0.176  ab 0.097 ± 0.018  b 0.014 ± 0.003  ab 0.506 ± 0.088  ab 1.262 ± 0.496  a 0.425 ± 0.401  a 0.017 ± 0.003  a 0.575 ± 0.349  a LOD LOD LOD LOD 0.027 0.399 ± 0.097  b 0.436 ± 0.073  b 1.630 ± 0.399  a 1.000 ± 0.629  ab 0.026 p- value2 0.018 0.038 0.028 0.040 Layer Hen Feed 0.175 ± 0.048 0.010 ± 0.004 0.002 ± 0.001 0.016 ± 0.004 0.002 ± 0.000 0.722 ± 0.217 Myristoleic 14:1 LOD LOD LOD LOD LOD LOD LOD LOD NA LOD Pentadecanoic 15:0 Palmitic 16:0 0.152 ± 0.030  bc 14.045 ± 0.36 3 b 0.249 ± 0.013  ab 16.756 ± 1.41 1 ab 0.114 ± 0.017  c 18.061 ± 1.27 9 ab 0.300 ± 0.033  a 20.129 ± 0.57 1 ab 0.085 ± 0.041  c 17.212 ± 1.48 6 ab 0.076 ± 0.018  c 16.759 ± 1.65 3 ab 0.351 ± 0.116  a 19.604 ± 5.46  a 0.136 ± 0.032  bc 16.591 ± 0.93 6 ab 0.005 0.017 0.057 ± 0.021 13.049 ± 0.879 Palmiteladic 16:1 n-9t LOD LOD LOD LOD LOD LOD LOD LOD NA LOD Palmitoleic 16:1 n-7 16:1 n-9 Heptadecanoic 17:0 1.158 ± 0.05  a 0.220 ± 0.014  c 0.189 ± 0.024  c 0.577 ± 0.085  bc 0.680 ± 0.091  bc 0.319 ± 0.023  bc 0.764 ± 0.073  b 0.327 ± 0.064  c 0.286 ± 0.021  bc 0.448 ± 0.031  bc 1.043 ± 0.131  bc 0.408 ± 0.021  ab 0.507 ± 0.028  bc 0.388 ± 0.101  c 0.288 ± 0.054  bc 0.628 ± 0.068  bc 0.188 ± 0.294  c 0.237 ± 0.058  c 0.260 ± 0.096  c 1.954 ± 0.183  a 0.483 ± 0.094  a 0.320 ± 0.257  bc 1.616 ± 0.865  ab 0.374 ± 0.105  bc 0.014 0.010 0.013 0.050 ± 0.005 1.006 ± 0.189 0.109 ± 0.012 c10- heptadecanoic 17:1 LOD LOD LOD LOD LOD LOD LOD LOD NA LOD Stearic 18:0 2.003 ± 0.101  c 2.563 ± 0.184  c 3.357 ± 0.262  c 3.728 ± 0.251  bc 3.922 ± 0.906  bc 3.039 ± 0.575  c 6.864 ± 0.496  a 6.103 ± 1.269  ab 0.010 2.180 ± 0.342 Eladic 18:1 n-9t LOD LOD LOD LOD LOD LOD LOD LOD NA LOD 1Means ± standard deviation n = 3 forage replicates per month and layer hen feed n=6 2Results of one-way ANOVA. a-e, Means within a row with different letters significantly differ p < 0.05. SFA, saturated fatty acids; MUFA, monounsaturated fatty acids, PUFA, polyunsaturated fatty acids; OCFA, odd-chain fatty acids; FA, fatty acids. 73 Table A3. (cont’d) Fatty Acid Carbon Number May Jun Jul Aug Sept Oct Nov Dec p- value2 Layer Hen Feed Oleic 18:1 n-9 18:1 n-11 Linoleic 18:2 n-6 ALA 18:3 n-3 2.497 ±  0.074 c 3.073 ±  0.850 b 17.021 ±  0.827 ab 51.447 ±  1.524 a 4.16 ±  0.261 bc 3.578 ±  0.811 bc 6.373 ±  0.458 abc 5.285 ±  1.163 bc 4.594 ±  0.196 bc 12.134 ±  2.992 ab 14.636 ±  5.969 a 0.006 17.793 ± 1.634 5.037 ±  0.870 ab 1.452 ±  1.310 b 9.776 ±  1.628 a 1.798 ±  0.283 b 0.589 ±  0.464 b 10.030 ±  2.703 a 2.882 ±  2.620 b 0.007 5.572 ± 0.577 18.511 ±  1.065 ab 15.243 ±  0.304 b 44.399  ± 1.974 abc 48.147 ±  3.484 abc 21.884 ±  0.885 a 29.914 ±  2.009 bcd 15.49 ±  0.642 b 46.635 ±  6.275 ab 15.935 ±  1.057 ab 50.547 ±  3.937 a 19.842 ±  2.756 ab 15.078 ±  3.279 d 21.613 ±  4.19 ab 22.263 ±  18.106 cd 0.044 0.018 50.570 ± 1.517 3.540 ± 0.780 GLA 18:3 n-6 LOD LOD LOD LOD LOD LOD LOD LOD NA LOD Arachidic 20:0 1.382 ± 0.164  a 1.348 ± 0.144  ab 0.930 ± 0.243  ab 1.123 ± 0.053  ab 0.989 ± 0.256  ab 0.642 ± 0.211  b 1.609 ± 0.224  a 1.166 ± 0.455  ab 0.031 Eicosenoic 20:1 n-9 0.267 ± 0.023  ab 0.184 ± 0.016  b 0.166 ± 0.065  b 0.235 ± 0.011  ab 0.300 ± 0.071  ab 0.193 ± 0.028  b 0.378 ± 0.056  ab 0.475 ± 0.128  a 0.038 Eicosedienoic 20:2 n-6 0.101 ± 0.017 0.076 ± 0.008 0.117 ± 0.046 0.132 ± 0.015 0.077 ± 0.042 0.086 ± 0.020 0.069 ± 0.054 0.023 ± 0.044 0.260 Eicosatrenoic 20:3 n-3 0.221 ± 0.021  ab 0.160 ± 0.009  b 0.203 ± 0.042  ab 0.159 ± 0.02  b 0.252 ± 0.09 a b 0.234 ± 0.051  ab 0.483 ± 0.109  a 0.443 ± 0.186  a 0.028 DGLA 20:3 n-6 Mead 20:9 n-9 LOD LOD LOD LOD LOD LOD LOD LOD LOD LOD LOD LOD LOD LOD LOD LOD NA NA Arachidonic 20:4 n-6 LOD 0.167 ± 0.026  b 0.238 ± 0.09 a b 0.24 ± 0.021 a b 0.312 ± 0.136  ab 0.207 ± 0.126  b 0.587 ± 0.113  a 0.675 ± 0.222  a 0.016 EPA 20:5 n-3 LOD LOD LOD LOD LOD LOD LOD LOD NA Behenic 22:0 1.872 ± 0.213  bc 1.729 ± 0.102  c 1.843 ± 0.392  bc 2.052 ± 0.105  abc 2.355 ± 0.769  abc 1.668 ± 0.484  c 3.352 ± 0.51 a b 3.982 ± 1.14  a 0.046 0.424 ± 0.088 0.466 ± 0.085 0.071 ± 0.037 0.058 ± 0.016 LOD LOD 0.155 ± 0.023 0.859 ± 0.199 0.464 ± 0.079 DTA 22:4 n-6 LOD LOD LOD LOD LOD LOD LOD LOD NA LOD 74 Table A3 (cont’d) Fatty Acid Carbon Number May Jun Jul Aug Sept Oct Nov Dec p- value2 22:5 n-3 LOD LOD LOD LOD LOD LOD LOD LOD NA DPA 22:5 n-6 0.501 ± 0.384 0.606 ± 0.207 0.667 ± 0.06 0.832 ± 0.57 0.665 ± 0.525 0.848 ± 0.226 LOD LOD 0.149 DHA 22:6 n-3 LOD LOD LOD LOD LOD LOD LOD LOD NA Lignoceric 24:0 1.678 ± 0.109  ab 1.592 ± 0.087  ab 1.300 ± 0.499  ab 1.496 ± 0.192  ab 0.850 ± 0.313  ab 0.530 ± 0.166  b 1.612 ± 0.163  ab 1.393 ± 0.833  a 0.043 Layer Hen Feed 1.374 ± 0.547 0.236 ± 0.040 0.893 ± 0.230 0.255 ± 0.101 Total SFA 22.036 ± 0.563 c 26.594 ± 0.73 bc 27.497 ± 2.555 bc 30.767 ± 0.594 abc 28.087 ± 4.015 bc 24.414 ± 3.558 bc 36.756 ± 4.371 a 34.694 ± 4.34 ab 0.013 17.375 ± 1.392 Total MUFA 7.257 ± 0.785 bc 10.987 ± 0.839 bc 7.584 ± 1.149 bc 17.569 ± 1.591 abc 8.290 ± 1.586 bc 6.350 ± 0.372 c 24.772 ± 5.831 a 19.965 ± 9.31 ab 0.009 24.888 ± 1.728 Total PUFA 71.015 ± 1.194 a 62.325 ± 1.523 abc 64.919 ± 3.704 abc 52.333 ± 1.331 bcd 63.623 ± 5.601 ab 69.374 ± 3.255 a 38.84 ± 1.643 d 45.34 ± 13.65 cd 0.013 57.738 ± 0.662 Total n-6 Total n-3 17.614 ± 1.218 19.209 ± 1.181 16.494 ± 0.224 22.430 ± 0.784 15.997 ± 0.954 17.233 ± 1.312 20.561 ± 2.886 22.455 ± 4.359 0.071 51.032 ± 1.502 51.667 ± 1.546 a 44.566 ± 1.979 abc 48.425 ± 3.48 abc 30.073 ± 2.03 bcd 46.971 ± 6.227 ab 50.781 ± 3.886 a 15.637 ± 3.209 d 22.885 ± 18.009 cd 0.018 n-6:n-3 ratio 0.341 ± 0.033 0.420 ± 0.041 0.341 ± 0.020 0.740 ± 0.077 0.341 ± 0.055 0.348 ± 0.043 1.322 ± 0.345 0.981 ± 0.652 0.051 Total OCFA 0.369 ± 0.038 c 0.592 ± 0.027 bc 0.416 ± 0.033 c 0.718 ± 0.053 ab 0.382 ± 0.097 c 0.322 ± 0.077 c 0.847 ± 0.206 a 0.529 ± 0.134 bc 0.008 0.168 ± 0.034 75 6.705 ± 1.055 7.791 ± 1.390 Table A4. Antioxidant profile of the forage by month and the layer hen feed1 Parameter May Jun Jul Aug Sept Oct Nov Dec p- value2 Layer Hen Feed Vitamin A (ng/g DM) Beta-carotene (ug/g DM) ND ND ND ND ND ND ND ND NA 10623.67 ± 767.76 NA NA NA NA NA NA 3.16 ± 3.32 5.28 ± 5.47 NA NA Vitamin E (ug/g DM) 9.90 ± 1.48 c 28.10 ± 0.97 bc 108.72 ± 56.69 ab 29.78 ± 3.86 bc 53.22 ± 20.84 bc 103.40 ± 51.02 ab 104.17 ± 25.50 ab 158.94 ± 13.34 a <0.001 11.21 ± 10.76 Chlorophyll a (ug/g DM) 2748.64 ± 195.42 a 1557.10 ± 270.13 abc 2327.67 ± 228.46 ab 1138.18 ± 166.5 bc 2614.71 ± 1121.41 ab 2278.5 ± 410.71 ab 347.74 ± 165.31 c 716.74 ± 778.80 c <0.001 17.22 ± 5.30 Chlorophyll b (ug/g DM) 976.30 ± 71.32 a 556.26 ± 117.71 abc 781.41 ± 103.01 ab 493.34 ± 5 9.05 bc 927.66 ± 324.63 ab 791.32 ± 149.99 ab 149.22 ± 15.25 c 269.51 ± 223.06 c <0.001 22.10 ± 8.25 Total Carotenoids (ug/g DM) Total phenolic content (mg/g DM) 765.92 ± 43.66 a 461.03 ± 94.35 abcd 626.32 ± 85.66 abc 270.47 ± 36.25 bcd 757.95 ± 378.49 ab 671.46 ± 113.89 abc 73.06 ± 5.80 d 219.65 ± 251.93 cd 0.001 14.47 ± 2.67 4.143 ± 0.474 a 2.284 ± 0.606 bcd 2.019 ± 0.526 bcd 1.302 ± 0.272 cd 2.571 ± 0.554 abc 3.644 ± 0.735 ab 0.546 ± 0.471 d 1.606 ± 0.493 cd 0.008 0.91 ± 0.25 1Means ± standard deviation (n = 3 forage replicates per month, n = 6 layer hen feed samples) 2Results of one-way ANOVA to compare forage by date. a-e, Means within a row for forage samples with different letters significantly differ (p < 0.05). DM, dry matter; ND, not detected; NA, value not determined for specific collection 76 Table A5. Antioxidant profile of the egg yolks by month1 Parameter May Jun Jul Aug Sept Oct Nov Dec p-value2 Vitamin A (ug/g FW) 4.04 ± 0.63 d 4.19 ± 0.38 d 6.97 ± 0.67 bc 9.03 ± 1.89 ab 10.80 ± 3.88 a 6.62 ± 1.97 c 7.77 ± 0.63 bc 2.85 ± 0.39 d <0.001 Vitamin E (ug/g FW) 4.65 ± 6.01 e 14.90 ± 19.23 de 33.52 ± 18.06 d 55.12 ± 9.79 c 68.82 ± 13.02 bc 81.42 ± 17.57 b 118.06 ± 23.89 a 25.72 ± 6.90 d <0.001 Total carotenoids (ug/g FW) 16.34 ± 7.95 c 20.64 ± 5.65 c 34.95 ± 11.74 abc 48.94 ± 12.19 a 29.92 ± 12.03 bc 44.39 ± 28.13 ab 39.59 ± 6.57 ab 49.69 ± 19.44 a <0.001 Beta carotene (ug/g FW) 14.88 ± 7.34 c 18.85 ± 5.20 c 31.75 ± 11.03 abc 44.85 ± 10.99 a 27.37 ± 11.01 bc 40.75 ± 25.93 ab 36.25 ± 6.84 ab 45.23 ± 17.72 a <0.001 Total phenolic content (mg GAE/g FW) 0.14 ± 0.02 ab 0.13 ± 0.02 ab 0.11 ± 0.01 b 0.14 ± 0.02 a 0.14 ± 0.02 a 0.14 ± 0.02 ab 0.13 ± 0.03 ab 0.14 ± 0.03 ab 0.019 1Means ± standard deviation (n = 24 eggs pooled into n = 12 replicates per month) 2Results of one-way ANOVA. a-e, Means within a row with different letters significantly differ (p < 0.05). FW, fresh weight; GAE, gallic acid equivalents 77 Table A6. Egg yolk fatty acids and cholesterol content by month (g of fatty acid per 100 g of fresh egg yolk)1 Fatty Acid Caprylic Carbon Number 8:0 Capric 10:0 Undecanoic 11:0 Lauric 12:0 Tridecanoic 13:0 Myristic 14:0 Myristoleic 14:1 Pentadecanoic 15:0 Palmitic 16:0 Palmiteladic 16:1 n-9t Palmitoleic 16:1 n-7 16:1 n-9 Heptadecanoic 17:0 c10- heptadecanoic Stearic 17:1 18:0 Eladic 18:1 n-9t p- value2 ND <0.001 May Jun Jul Aupg Sept Oct Nov Dec LOD 0.001 ± 0.001  c LOD LOD 0.002 ± 0.001  ab 0.061 ± 0.014  ab 0.010 ± 0.003  cd 0.014 ± 0.002  ab 4.939 ± 1.097  a 0.009 ± 0.002  bc 0.146 ± 0.035  a 0.492 ± 0.094  abcd 0.039 ± 0.011  ab LOD 0.001 ± 0.001 bc 0.001 ± 0.001  ab 0.000 ± 0.001  b 0.002 ± 0.001  ab 0.065 ± 0.019  a 0.015 ± 0.004  ab 0.012 ± 0.004  abc 3.7 ± 0.478  bcd 0.007 ± 0.002  c 0.078 ± 0.015  bcd 0.5 ± 0.097  abc 0.030 ± 0.003  bc LOD 0.002 ± 0.001  ab 0.000 ± 0.001  abc 0.001 ± 0.001  a 0.002 ± 0.001  a 0.05 ± 0.009  abc 0.008 ± 0.004  d 0.011 ± 0.002  bc 3.987 ± 0.388  bc 0.007 ± 0.002  c 0.093 ± 0.020  b 0.362 ± 0.103  cd 0.032 ± 0.007  bc LOD 0.002 ± 0.001  a 0.001 ± 0.001  a 0.001 ± 0.001  a 0.002 ± 0.000  ab 0.047 ± 0.009  bc 0.011 ± 0.003  bcd 0.010 ± 0.002  c 3.405 ± 0.385  cd 0.007 ± 0.001  c 0.059 ± 0.012  d 0.429 ± 0.069  bcd 0.024 ± 0.004  c LOD 0.001 ± 0.001 c LOD 0.001 ± 0.001  c LOD 0.001 ± 0.001  c LOD 0.001 ± 0.001  c LOD 0.000 ± 0.001  bc 0.002 ± 0.000  ab 0.057 ± 0.014  ab 0.014 ± 0.005  abc 0.015 ± 0.003  a 4.328 ± 0.756  ab 0.011 ± 0.004  ab 0.1 ± 0.027  b 0.556 ± 0.159  ab 0.046 ± 0.014  a LOD LOD LOD LOD LOD <0.001 LOD <0.001 0.001 ± 0.001  c 0.041 ± 0.013  c 0.013 ± 0.005  abcd 0.009 ± 0.003  c 2.956 ± 0.726  d 0.009 ± 0.002  bc 0.064 ± 0.019  cd 0.465 ± 0.143  bcd 0.028 ± 0.004  c 0.002 ± 0.000  b 0.065 ± 0.008  a 0.016 ± 0.003  a 0.015 ± 0.003  a 4.12 ± 0.65  abc 0.013 ± 0.002  a 0.09 ± 0.018  bc 0.626 ± 0.099  a 0.042 ± 0.008  a 0.001 ± 0.000  c 0.036 ± 0.007  c 0.008 ± 0.002  d 0.009 ± 0.002  c 3.052 ± 0.507  d 0.007 ± 0.002  c 0.074 ± 0.014  bcd 0.36 ± 0.084  d 0.030 ± 0.006  bc <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 LOD LOD LOD LOD LOD LOD LOD LOD ND 0.039 ± 0.008  ab 0.034 ± 0.008  abc 0.03 ± 0.009  bc 0.029 ± 0.006  bcd 0.032 ± 0.005  bc 0.026 ± 0.007  cd 0.024 ± 0.003  c 0.019 ± 0.004  d 0.044 ± 0.01  a 0.038 ± 0.017  ab 0.029 ± 0.007  c 0.036 ± 0.013  abc 0.042 ± 0.006  a 0.042 ± 0.009  a 0.03 ± 0.005  bc 0.03 ± 0.005  abcd <0.001 <0.001 1Means ± standard deviation n = 24 eggs pooled into n = 12 replicates per month 2Results of one-way ANOVA. a-e, Means within a row with different letters significantly differ p < 0.05. SFA, saturated fatty acids; MUFA, monounsaturated fatty acids, PUFA, polyunsaturated fatty acids; OCFA, odd-chain fatty acids; FA, fatty acids. 79 Table A6. (cont’d) Fatty Acid Carbon Number May Jun Jul Aug Sept Oct Nov Dec Oleic 18:1 n-9 8.466 ± 1.589 a 18:1 n-11 0.323 ± 0.060 ab Linoleic 18:2 n-6 3.405 ± 0.995 a ALA 18:3 n-3 0.130 ± 0.028 bcd GLA 18:3 n-6 0.024 ± 0.005 a Arachidic 20:0 0.008 ± 0.002 cd Eicosenoic 20:1 n-9 0.054 ± 0.006 cd Eicosedienoic 20:2 n-6 0.028 ± 0.007 c 5.424 ± 0.565  bc 0.235 ± 0.030  cd 2.016 ± 0.540  bc 0.108 ± 0.029  cde 0.016 ± 0.004  c 0.008 ± 0.002  cd 0.048 ± 0.009  de 0.020 ± 0.006  cd 6.398 ± 0.653  b 0.189 ± 0.04  cd 3.034 ± 1.176  a 0.077 ± 0.019  de 0.016 ± 0.003  c 0.008 ± 0.001  cd 0.044 ± 0.007  de 0.020 ± 0.010  cd 5.657 ± 0.73  b 0.18 ± 0.029  d 1.892 ± 0.311  bc 0.076 ± 0.014  e 0.012 ± 0.003  c 0.007 ± 0.001  d 0.040 ± 0.003  e 0.010 ± 0.001  d 6.235 ± 1.192  b 0.374 ± 0.137  a 2.666 ± 0.658  ab 0.159 ± 0.061  b 0.029 ± 0.009  a 0.014 ± 0.005  a 0.083 ± 0.020  a 0.064 ± 0.037  a 4.217 ± 1.355  c 0.27 ± 0.074  bc 1.475 ± 0.560  c 0.132 ± 0.057  bc 0.018 ± 0.005  bc 0.011 ± 0.002  ab 0.062 ± 0.009  bc 0.035 ± 0.016  bc 6.077 ± 0.758  b 0.389 ± 0.058  a 2.687 ± 0.467  ab 0.205 ± 0.056  a 0.022 ± 0.006  ab 0.014 ± 0.002  a 0.069 ± 0.009  ab 0.054 ± 0.016  ab 4.331 ± 0.713  c 0.236 ± 0.048  cd 1.604 ± 0.272  c 0.101 ± 0.027  bcde 0.016 ± 0.002  c 0.009 ± 0.001  bc 0.056 ± 0.006  cd 0.025 ± 0.008  cd p- value2 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 Eicosatrenoic 20:3 n-3 LOD LOD LOD LOD LOD LOD LOD LOD ND DGLA 20:3 n-6 0.021 ± 0.006 bcd Mead 20:9 n-9 0.006 ± 0.002 cd Arachidonic 20:4 n-6 0.236 ± 0.049 a EPA 20:5 n-3 0.007 ± 0.002 bc 0.013 ± 0.003  d 0.005 ± 0.002  cd 0.159 ± 0.04  bc 0.006 ± 0.002  bc 0.012 ± 0.004  d 0.004 ± 0.001  d 0.197 ± 0.04  ab 0.004 ± 0.002  c 0.008 ± 0.001  d 0.003 ± 0.001  d 0.139 ± 0.019  cd 0.005 ± 0.001  c 0.053 ± 0.028  a 0.016 ± 0.011  a 0.241 ± 0.056  a 0.017 ± 0.009  a 0.03 ± 0.011  bc 0.012 ± 0.005  ab 0.101 ± 0.029  d 0.012 ± 0.007  ab 0.034 ± 0.006  b 0.01 ± 0.003  bc 0.156 ± 0.029  bc 0.014 ± 0.006  a 0.017 ± 0.003  cd 0.006 ± 0.001  cd 0.105 ± 0.019  d 0.007 ± 0.002  bc <0.001 <0.001 <0.001 <0.001 Behenic 22:00 LOD DTA 22:4 n-6 LOD LOD LOD LOD LOD LOD LOD LOD LOD LOD LOD LOD LOD LOD LOD ND ND 80 Table A6. (cont’d) Fatty Acid Carbon Number May DPA 22:5 n-3 22:5 n-6 DHA 22:6 n-3 0.169 ± 0.059  cd 0.119 ± 0.042  b 0.199 ± 0.04 5 cd Jun 0.114 ± 0.04  d 0.072 ± 0.02  bc 0.114 ± 0.031  d Jul 0.085 ± 0.033  d 0.064 ± 0.015  bc 0.089 ± 0.023  d Aug 0.08 ± 0.015  d 0.043 ± 0.008  c 0.074 ± 0.012  d Sept 0.423 ± 0.232  a 0.244 ± 0.15  a 0.538 ± 0.275  a Oct 0.267 ± 0.141  bc 0.136 ± 0.037  b 0.272 ± 0.093  bc Nov 0.316 ± 0.071  ab 0.137 ± 0.038  b 0.406 ± 0.049  ab Dec 0.155 ± 0.036  cd 0.081 ± 0.025  bc 0.168 ± 0.043  cd p-value2 <0.001 <0.001 <0.001 Lignoceric 24:0 LOD LOD LOD LOD LOD LOD LOD LOD ND Total Cholesterol Total SFA Total MUFA Total cis-MUFA total trans-MUFA Total PUFA Total n-6 Total n-3 n-6:n-3 ratio Total OCFA Total OBCFA Total FA 0.809 ± 0.156 d 6.157 ± 1.396  a 9.532 ± 1.746  a 9.49 ± 1.739  a 0.042 ± 0.009  abc 4.334 ± 1.141  a 3.833 ± 1.063  a 0.516 ± 0.140  cd 7.556 ± 1.759  b 0.055 ± 0.01  ab 3.768 ± 0.340  ab 20.16 ± 3.931  a 0.931 ± 0.138 cd 4.66 ± 0.623  bcd 6.336 ± 0.612  bc 6.3 ± 0.608  bc 0.036 ± 0.006  bcd 2.639 ± 0.612  bc 2.296 ± 0.579  bc 0.354 ± 0.138  d 6.402 ± 2.575  bc 0.045 ± 0.013  bc 4.111 ± 0.773  a 13.774 ± 1.703  cde 0.990 ± 0.108 bc 5.159 ± 0.521  abc 7.129 ± 0.761  b 7.096 ± 0.755  b 0.033 ± 0.008  cd 3.609 ± 1.270  ab 3.343 ± 1.234  a 0.236 ± 0.066  d 13.924 ± 5.787  a 0.045 ± 0.007  bc 3.286 ± 0.145  c 16.025 ± 1.894  bcd 1.176 ± 0.099 a 4.264 ± 0.461  cd 6.401 ± 0.804  bc 6.375 ± 0.802  bc 0.026 ± 0.005  d 2.343 ± 0.338  c 2.104 ± 0.328  c 0.234 ± 0.051  d 8.890 ± 0.926  b 0.037 ± 0.004  c 3.58 ± 0.428  bc 13.128 ± 1.482  de 1.208 ± 0.164 a 5.433 ± 0.943  ab 7.406 ± 1.458  b 7.357 ± 1.441  b 0.049 ± 0.021  ab 4.43 ± 1.259  a 3.285 ± 0.820  a 1.349 ± 0.661  a 2.660 ± 2.427  cd 0.061 ± 0.013  a 3.294 ± 0.249  bc 17.436 ± 3.47  ab 1.153 ± 0.142 ab 3.712 ± 0.931  d 5.134 ± 1.579  c 5.089 ± 1.565  c 0.045 ± 0.015  abc 2.499 ± 0.897  bc 1.796 ± 0.643  c 0.651 ± 0.206  bc 2.607 ± 0.468  d 0.04 ± 0.01  c 3.322 ± 0.37  bc 11.485 ± 3.171  e 0.919 ± 0.112 cd 5.17 ± 0.817  abc 7.322 ± 0.87  b 7.268 ± 0.861  b 0.054 ± 0.011  a 4.042 ± 0.598  a 3.088 ± 0.502  ab 0.968 ± 0.244  ab 3.223 ± 0.587  d 0.059 ± 0.008  a 3.329 ± 0.084  bc 16.692 ± 1.939  bc 0.917 ± 0.149 cd 3.89 ± 0.649  d 5.103 ± 0.818  c 5.066 ± 0.814  c 0.037 ± 0.006  bcd 2.297 ± 0.375  c 1.85 ± 0.306  c 0.421 ± 0.072  cd 4.203 ± 0.976  cd 0.041 ± 0.007  c 3.117 ± 0.128  c 11.427 ± 1.741  e <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 81 Table A7. Egg yolk fatty acids by month (% of total fatty acids)1 Fatty Acid Caprylic Carbon Number 8:0 Capric 10:0 Undecanoic 11:0 Lauric 12:0 Tridecanoic 13:0 Myristic 14:0 Myristoleic 14:1 Pentadecanoic 15:0 Palmitic 16:0 Palmiteladic 16:1 n-9t Palmitoleic 16:1 n-7 16:1 n-9 Heptadecanoi c c10- heptadecanoic Stearic 17:0 17:1 18:0 Eladic 18:1 n-9t May Jun Jul Aug Sept Oct Nov Dec LOD 0.005 ± 0.002  c 0.001 ± 0.001  cd 0.002 ± 0.001  cd 0.009 ± 0.001  c 0.298 ± 0.066  c 0.047 ± 0.014  e 0.071 ± 0.011  b 24.562 ± 1.931  b 0.044 ± 0.006  c 0.738 ± 0.056  a 2.465 ± 0.332  cd 0.192 ± 0.030  c LOD 0.010 ± 0.002  ab 0.004 ± 0.001  a 0.003 ± 0.001  b 0.016 ± 0.002  a 0.442 ± 0.087  a 0.102 ± 0.039  a 0.080 ± 0.008  a 26.844 ± 1.482  a 0.050 ± 0.024  c 0.566 ± 0.093  bc 3.421 ± 0.990  ab 0.206 ± 0.025  bc LOD 0.010 ± 0.002  bc 0.003 ± 0.002  ab 0.004 ± 0.001  ab 0.014 ± 0.003  a 0.310 ± 0.056  c 0.047 ± 0.031 d e 0.069 ± 0.006  b 25.660 ± 2.528  ab 0.046 ± 0.009  c 0.597 ± 0.089  b 2.232 ± 0.883  d 0.196 ± 0.012  c LOD 0.012 ± 0.003  a 0.004 ± 0.001  a 0.005 ± 0.001  a 0.016 ± 0.005  a 0.354 ± 0.066  bc 0.079 ± 0.023  abcd 0.076 ± 0.007  ab 25.915 ± 1.182  ab 0.052 ± 0.014  bc 0.449 ± 0.095  c 3.141 ± 0.491  abc 0.190 ± 0.024  c LOD 0.007 ± 0.004  bc 0.002 ± 0.002  bc 0.002 ± 0.001  bc 0.011 ± 0.003  b 0.323 ± 0.045  bc 0.076 ± 0.032  bcde 0.090 ± 0.012  a 25.611 ± 2.946  ab 0.066 ± 0.012  ab 0.554 ± 0.159  b 3.112 ± 1.054  bc 0.242 ± 0.045  ab LOD 0.007 ± 0.001  bc 0.001 ± 0.001  cd 0.002 ± 0.000 cd 0.011 ± 0.003  bc 0.360 ± 0.081  bc 0.112 ± 0.037  ab 0.078 ± 0.017  ab 26.309 ± 1.942  ab 0.076 ± 0.012  a 0.567 ± 0.064  bc 3.991 ± 0.974  a 0.256 ± 0.056 a LOD 0.006 ± 0.001  c 0.001 ± 0.000  d 0.002 ± 0.000  d 0.010 ± 0.001  bc 0.398 ± 0.037  b 0.094 ± 0.008  abc 0.093 ± 0.013  a 24.553 ± 2.531  ab 0.077 ± 0.016  a 0.561 ± 0.105  bc 3.518 ± 0.336  ab 0.244 ± 0.031  ab LOD 0.008 ± 0.001  bc 0.001 ± 0.001  d 0.002 ± 0.001  cd 0.011 ± 0.001  bc 0.32 ± 0.029  c 0.064 ± 0.016  cde 0.08 ± 0.01  ab 26.786 ± 1.685  ab 0.066 ± 0.016  ab 0.652 ± 0.200  ab 3.136 ± 0.812  bc 0.260 ± 0.032  a p- value2 ND <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 0.005 <0.001 <0.001 <0.001 <0.001 LOD LOD LOD LOD LOD LOD LOD LOD ND 5.283 ± 0.487  c 0.171 ± 0.030  cd 6.123 ± 0.677  abc 0.218 ± 0.033  bc 6.829 ± 0.593  a 0.163 ± 0.059  cd 5.670 ± 1.047  bc 0.142 ± 0.035  d 5.755 ± 0.686  c 0.214 ± 0.087  bc 5.668 ± 1.117  bc 0.294 ± 0.086  a 5.348 ± 0.700  c 0.239 ± 0.038  b 6.69 ± 0.888  ab 0.264 ± 0.05  ab <0.001 <0.001 1Means ± standard deviation n = 24 eggs pooled into n = 12 replicates per month 2Results of one-way ANOVA. a-e, Means within a row with different letters significantly differ p < 0.05. SFA, saturated fatty acids; MUFA, monounsaturated fatty acids, PUFA, polyunsaturated fatty acids; CLA, conjugated linoleic acid; OCFA, odd-chain fatty acids; OCBFA, odd-chain branched fatty acids; BCFA, branch-chain fatty acids; FA, fatty acids. 82 Table A7. (cont’d) Fatty Acid Carbon Number May Jun Jul Aug Sept Oct Nov Dec Oleic 18:1 n-9 18:1 n-11 Linoleic 18:2 n-6 CLA 9c, 11t 18:2 11t, 13c 11t, 13t t, t ALA 18:3 n-3 GLA 18:3 n-6 Arachidic 20:0 Eicosenoic 20:1 n-9 Eicosedienoic 20:2 n-6 42.227 ± 2.61  ab 1.611 ± 0.096  c 16.502 ± 2.14  ab 0.081 ± 0.012  c 0.045 ± 0.012  d 0.155 ± 0.022  d 0.045 ± 0.009  c 0.589 ± 0.144  de 0.12 ± 0.016  bcd 0.042 ± 0.007  e 0.274 ± 0.036  d 0.130 ± 0.039  b 39.433 ± 2.089  bcd 1.746 ± 0.314  bc 14.578 ± 2.938  bc 0.098 ± 0.011  c 0.068 ± 0.008  bc 0.206 ± 0.022  cd 0.071 ± 0.013  ab 0.745 ± 0.147  cd 0.118 ± 0.024  cd 0.058 ± 0.007  cd 0.356 ± 0.040 c d 0.144 ± 0.048  b 40.328 ± 2.869  abc 1.156 ± 0.315  d 18.653 ± 5.979  a 0.073 ± 0.009  c 0.056 ± 0.005  cd 0.158 ± 0.023  d 0.059 ± 0.005  bc 0.484 ± 0.105  e 0.098 ± 0.006  d 0.046 ± 0.006  de 0.284 ± 0.02  d 0.120 ± 0.053  b 43.580 ± 1.806  a 1.380 ± 0.162  cd 14.180 ± 1.866  bc 0.084 ± 0.015  c 0.064 ± 0.016  bcd 0.182 ± 0.042  d 0.064 ± 0.017  abc 0.598 ± 0.114  de 0.096 ± 0.017  d 0.050 ± 0.007  de 0.306 ± 0.054  d 0.076 ± 0.023  b 35.698 ± 3.388  e 2.184 ± 0.804  ab 15.217 ± 2.840 abc 0.125 ± 0.038  b 0.076 ± 0.018  bc 0.254 ± 0.058  bc 0.062 ± 0.022  abc 0.874 ± 0.353  bc 0.150 ± 0.034  ab 0.074 ± 0.018  bc 0.434 ± 0.069  b 0.332 ± 0.174  a 36.008 ± 4.656  de 2.406 ± 0.378  a 12.469 ± 3.610  c 0.150 ± 0.026  a 0.090 ± 0.020  a 0.298 ± 0.057  a 0.081 ± 0.018  a 1.18 ± 0.249  a 0.152 ± 0.027  a 0.098 ± 0.020  a 0.546 ± 0.101  a 0.306 ± 0.092  a 36.662 ± 4.279  de 2.327 ± 0.298  a 15.669 ± 2.515  abc 0.126 ± 0.010  b 0.064 ± 0.009  cd 0.236 ± 0.018  bc 0.059 ± 0.009  bc 1.264 ± 0.246  a 0.134 ± 0.033  abc 0.076 ± 0.009  b 0.422 ± 0.033 b c 0.304 ± 0.061  a 37.911 ± 3.768  cde 2.044 ± 0.458  ab 13.834 ± 1.627  bc 0.132 ± 0.017  ab 0.081 ± 0.010  ab 0.268 ± 0.037  ab 0.078 ± 0.006  a 0.966 ± 0.107  b 0.150 ± 0.029  abc 0.084 ± 0.008  ab 0.478 ± 0.056 a b 0.225 ± 0.066  a p- value2 <0.001 <0.001 0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 Eicosatrenoic 20:3 n-3 LOD LOD LOD LOD LOD LOD LOD LOD ND DGLA 20:3 n-6 Mead 20:9 n-9 Arachidonic 20:4 n-6 EPA 20:5 n-3 0.100 ± 0.022  de 0.030 ± 0.011  cd 1.172 ± 0.167  b 0.031 ± 0.003  c 0.104 ± 0.02  de 0.035 ± 0.016  cd 1.180 ± 0.364  b 0.040 ± 0.010  c 0.074 ± 0.030  e 0.027 ± 0.010 d 1.236 ± 0.171  ab 0.026 ± 0.005  c 0.062 ± 0.010  e 0.024 ± 0.009  d 1.046 ± 0.163  bc 0.030 ± 0.008  c 0.334 ± 0.109  a 0.086 ± 0.072 a b 1.383 ± 0.333  a 0.098 ± 0.040  a 0.240 ± 0.045  ab 0.103 ± 0.055  a 0.934 ± 0.132  c 0.086 ± 0.007  a 0.217 ± 0.049  bc 0.058 ± 0.020  bc 0.907 ± 0.187  c 0.074 ± 0.019  ab 0.150 ± 0.027  cd 0.048 ± 0.018  cd 0.889 ± 0.223  c 0.056 ± 0.014  bc <0.001 <0.001 <0.001 <0.001 Behenic 22:00 LOD LOD LOD LOD LOD LOD LOD LOD ND 83 Table A7. (cont’d) Carbon Number Fatty Acid May DTA 22:4 n-6 LOD Jun LOD Jul Aug Sept LOD LOD LOD Oct LOD Nov LOD Dec p- value2 LOD ND DPA 22:5 n-3 0.869 ± 0.336  cd 0.876 ± 0.311  cd 0.487 ± 0.218  d 0.604 ± 0.165  d 2.620 ± 1.262  a 1.954 ± 0.778  a 1.771 ± 0.324  ab 22:5 n-6 0.638 ± 0.204  bcd 0.473 ± 0.122  bcd 0.408 ± 0.06 1 cd 0.320 ± 0.038  d 1.412 ± 0.788  a 1.194 ± 0.305  a 0.748 ± 0.336  b DHA 22:6 n-3 0.984 ± 0.179  bc 0.879 ± 0.267  bc 0.548 ± 0.086  c 0.567 ± 0.064  c 3.574 ± 1.401  a 2.173 ± 0.437  a 2.455 ± 0.188  a 1.318 ± 0.428  bc 0.724 ± 0.250  bc 1.482 ± 0.352  b Lignoceric 24:0 LOD C14:0-iso 14:0 LOD LOD LOD LOD LOD LOD LOD LOD LOD LOD LOD LOD LOD LOD LOD C15:0-iso 15:0 0.019 ± 0.005  bc 0.042 ± 0.019  a 0.016 ± 0.004  c 0.023 ± 0.006  bc 0.019 ± 0.003  bc 0.022 ± 0.005  b 0.017 ± 0.003  c 0.020 ± 0.004  bc C15:0- anteiso 15:0 0.010 ± 0.002  c 0.015 ± 0.002  ab 0.012 ± 0.003  bc 0.015 ± 0.004  ab 0.014 ± 0.005  ab 0.017 ± 0.004  a 0.012 ± 0.002  bc 0.016 ± 0.002  a C16:0-iso 16:0 0.048 ± 0.010  c 0.076 ± 0.013  ab 0.064 ± 0.009  bc 0.077 ± 0.016  abc 0.074 ± 0.027  abc 0.091 ± 0.022  a 0.063 ± 0.010  bc C17:0-iso 17:0 0.064 ± 0.010  d 0.100 ± 0.030  abc 0.079 ± 0.012  cd 0.095 ± 0.022  abcd 0.092 ± 0.027  bcd 0.112 ± 0.025  a 0.079 ± 0.012  cd C17:0- anteiso 17:0 0.068 ± 0.014  c 0.107 ± 0.019  ab 0.086 ± 0.013  bc 0.108 ± 0.028  ab 0.100 ± 0.025  abc 0.116 ± 0.028  a 0.084 ± 0.014  bc C18:0-iso 18:0 0.138 ± 0.034  c 0.212 ± 0.040  bc 0.186 ± 0.024  c 0.211 ± 0.045  bc 0.199 ± 0.075  bc 0.272 ± 0.065  a 0.186 ± 0.027  c C18:0- anteiso 18:0 0.139 ± 0.035  c 0.211 ± 0.039  bc 0.186 ± 0.023  c 0.211 ± 0.044  bc 0.199 ± 0.075  bc 0.271 ± 0.065  a 0.184 ± 0.026  c Total SFA Total MUFA 30.932 ±  2.591 b 47.489 ±  2.413 ab 33.948 ±  2.392 a 46.119 ±  2.659 abc 32.904 ±  2.720 ab 45.311 ±  3.698 bc 32.740 ±  1.931 ab 49.147 ±  2.236 a 31.767 ±  3.521 ab 42.484 ±  1.868 c 32.701 ±  3.615 ab 44.094 ±  4.779 bc 30.889 ±  2.907 b 44.136 ±  4.759 bc 0.087 ± 0.010  a 0.107 ± 0.015  ab 0.110 ± 0.013  a 0.257 ± 0.029  ab 0.257 ± 0.028  ab 34.496 ±  1.425 a 45.288 ±  3.592 bc <0.001 <0.001 <0.001 ND ND <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 84 Table A7. (cont’d) Carbon Number Fatty Acid May Jun Jul Aug Sept Oct Nov Dec p- value2 Total cis-MUFA 47.286 ± 2.343  ab 45.842 ± 2.605  abc 45.124 ± 3.654  bc 48.974 ± 2.261  a 42.181 ± 1.941  c 43.761 ± 4.834  bc 43.792 ± 4.711  bc 44.980 ± 3.638  bc <0.001 total trans-MUFA 0.204 ± 0.041 c d 0.265 ± 0.042  bcd 0.210 ± 0.068 c d 0.192 ± 0.043  d 0.284 ± 0.079  bc 0.372 ± 0.112  a 0.316 ± 0.065  ab 0.326 ± 0.054  ab <0.001 Total PUFA 20.64 ± 2.203  abcd 19.166 ± 2.089  cd 21.882 ± 5.833  abc 17.746 ± 1.839  d 25.702 ± 2.843  a 21.752 ± 4.498  abcd 23.990 ± 2.617  ab 19.967 ± 2.552  bcd <0.001 Total n-6 Total n-3 n-6:n-3 ratio Total CLA Total OCFA 18.446 ± 1.972  ab 16.424 ± 2.322  b 20.548 ± 6.173  a 15.875 ± 1.979  b 18.384 ± 2.209  ab 15.375 ± 3.820  b 18.375 ± 2.948  ab 16.000 ± 1.811  b <0.001 2.448 ± 0.210 b c 2.598 ± 0.794  bc 1.568 ± 0.389  c 1.802 ± 0.280  c 7.361 ± 2.662  a 5.401 ± 1.307  a 5.668 ± 0.417  a 3.841 ± 0.722  b <0.001 7.556 ± 1.759  b 6.402 ± 2.575  bc 13.924 ± 5.787  a 8.890 ± 0.926  b 2.660 ± 2.427  cd 2.607 ± 0.468  d 3.223 ± 0.587  d 4.203 ± 0.976  cd <0.001 0.328 ± 0.050 e 0.442 ± 0.036  cde 0.345 ± 0.045  de 0.390 ± 0.091  cde 0.488 ± 0.143  bcd 0.619 ± 0.120  a 0.486 ± 0.037  bc 0.557 ± 0.078  ab <0.001 0.162 ± 0.023  d 0.264 ± 0.070  ab 0.197 ± 0.034  cd 0.248 ± 0.061  abc 0.226 ± 0.058  bcd 0.266 ± 0.056  a 0.192 ± 0.032  cd 0.253 ± 0.033  ab <0.001 Total OBCFA 0.273 ± 0.046  b 0.304 ± 0.032  ab 0.285 ± 0.018  b 0.286 ± 0.020  b 0.346 ± 0.048  a 0.338 ± 0.074  a 0.344 ± 0.048  a 0.348 ± 0.038  a <0.001 Total BCFA 0.347 ± 0.065  d 0.531 ± 0.108  abc 0.442 ± 0.068  cd 0.550 ± 0.113  abc 0.469 ± 0.162  bcd 0.629 ± 0.151  a 0.440 ± 0.069  cd 0.597 ± 0.075  ab <0.001 Total isoBCFA 0.270 ± 0.050  d 0.412 ± 0.091  abc 0.343 ± 0.05  cd 0.422 ± 0.084  abcd 0.363 ± 0.143  bcd 0.496 ± 0.120  a 0.345 ± 0.053  cd 0.471 ± 0.058  ab <0.001 Total anteisoBCFA 0.078 ± 0.015  c 0.121 ± 0.019 a b 0.098 ± 0.017  bc 0.123 ± 0.031  ab 0.114 ± 0.029  ab 0.134 ± 0.032  a 0.096 ± 0.016  bc 0.126 ± 0.014  a <0.001 85 Table A8. Yolk mineral profile of the egg yolks by month1 Parameter May Jun Jul Aug Sept Oct Nov Dec p-value2 Iron (ug/g FW) 69.76 ± 7.30 abc 70.66 ± 5.39 ab 64.73 ± 6.10 bc 63.49 ± 5.37 c 71.90 ± 6.58 a 66.44 ± 5.02 abc 66.09 ± 3.51 abc 63.60 ± 4.00 c <0.001 Zinc (ug/g FW) 34.26 ± 1.68 34.80 ± 1.44 35.46 ± 1.27 34.61 ± 1.72 33.37 ± 2.27 34.77 ± 1.75 33.70 ± 1.55 34.07 ± 1.47 0.073 Copper (ug/g FW) Manganese (ug/g FW) 1.89 ± 0.14 bc 0.86 ± 0.20 a 1.83 ± 0.11 c 2.02 ± 0.13 ab 0.70 ± 0.11 ab 0.70 ± 0.08 ab Molybdenum (ug/g FW) 0.19 ± 0.07 a 0.17 ± 0.03 ab 0.12 ± 0.04 b Selenium (ug/g FW) Calcium (ug/g FW) 0.67 ± 0.13 c 1227.07 ± 69.38 0.61 ± 0.09 c 0.57 ± 0.15 c 1188.78 ± 58.28 1247.08 ± 65.68 1181.52 ± 68.76 1.94 ± 0.17 abc 0.58 ± 0.13 b 0.11 ± 0.03 b 0.71 ± 0.14 bc 2.09 ± 0.13 a 0.64 ± 0.17 b 0.20 ± 0.07 a 1.00 ± 0.15 a 1171.15 ± 74.45 2.09 ± 0.10 a 1.95 ± 0.09 abc 1.82 ± 0.13 c 0.73 ± 0.13 ab 0.87 ± 0.14 a 0.69 ± 0.09 b 0.16 ± 0.03 ab 0.13 ± 0.02 b 0.16 ± 0.03 ab 0.89 ± 0.16 a 0.87 ± 0.13 ab 0.87 ± 0.14 ab 1197.93 ± 67.25 1199.52 ± 74.92 1177.54 ± 60.02 <0.001 <0.001 <0.001 <0.001 0.101 Magnesium (ug/g FW) 115.05 ± 6.65 bc 116.36 ± 6.50 b 126.13 ± 6.63 a 120.11 ± 8.41 ab 107.66 ± 7.67 c 115.36 ± 5.27 bc 116.64 ± 5.68 b 117.18 ± 7.25 b <0.001 Potassium (ug/g FW) 1195.41 ± 69.45 ab 1191.64 ± 59.40 ab Phosphorus (ug/g FW) 5444.32 ± 106.85 bcd 5415.41 ± 39.19 cd Sulfur (ug/g FW) Sodium (ug/g FW) 1435.44 ± 40.92 489.01 ± 26.20 abc 1409.58 ± 44.86 470.05 ± 24.70 bc 1146.69 ± 120.20 b 5574.79 ± 66.39 a 1453.27 ± 39.97 481.38 ± 146.93 abc 1195.46 ± 67.51 ab 5511.99 ± 56.71 ab 1465.40 ± 44.33 411.69 ± 206.77 c 1264.26 ± 88.64 a 5386.93 ± 106.02 d 1412.41 ± 42.94 530.85 ± 38.14 abc 1248.51 ± 61.92 ab 5522.30 ± 51.21 ab 1441.20 ± 50.34 561.95 ± 26.09 ab 1155.18 ± 40.16 b 5507.46 ± 78.10 abc 1422.17 ± 60.32 579.69 ± 33.69 ab 1207.58 ± 118.01 ab 5552.88 ± 69.01 a 1441.75 ± 41.34 605.72 ± 94.76 a Aluminum (ug/g FW) 1.12 ± 0.25 cd 1.18 ± 0.18 bcd 1.31 ± 0.39 bcd 1.29 ± 0.24 bcd 1.49 ± 0.25 abc 1.67 ± 0.24 ab 1.88 ± 0.91 a 0.84 ± 0.18 d 0.009 <0.001 0.046 <0.001 <0.001 1Means ± standard deviation (n = 24 eggs pooled into n = 12 replicates per month) 2Results of one-way ANOVA. a-e, Means within a row with different letters significantly differ (p < 0.05). FW, fresh weight 86 Table A9. Yolk PCA Loadings Plot Values1 Parameter Vitamin E Vitamin A T. Cholesterol T. Carotenoids Beta-Carotene T. Phenolics C18:3 n-3 C20:5 n-3 C22:5 n-3 C22:6 n-3 Total SFA Total MUFA Total PUFA Total n-6 Total n-3 n-6:n-3 ratio PC1 -0.95147 -0.04052 -0.01465 -0.21961 -0.20195 -1.3972e-05 -0.00481 -8.6264e-05 -0.01070 -0.01341 0.00328 0.02156 -0.02276 0.00702 -0.02941 0.04024 PC2 -0.29657 0.00976 -0.00221 0.70131 0.64473 7.9297e-05 0.00076 0.00030 -0.005764 -0.011995 0.018644 0.023428 -0.046789 -0.028988 -0.017378 0.005900 1Principal Component Analysis (PCA) loadings for various yolk parameters across two principal components (PC1 and PC2). T. Cholesterol, total cholesterol, T. Carotenoids, total carotenoids, T. Phenolics; total phenolics, C18:3 n-3; ALA, C20:5 n-3; EPA, C22:5 n-3; DPA n-3, C22:6 n-3; DHA, SFA; saturated fatty acids, MUFA; monounsaturated fatty acids, PUFA; polyunsaturated fatty acids, n-6; omega-6 fatty acid, n-3; omega-3 fatty acid 87 Table A10. Forage PCA Loadings Plot Values1 Parameter C18:3 n-3 C20:5 n-3 C22:5 n-3 C22:6 n-3 Total SFA Total MUFA Total PUFA Total n-6 Total n-3 n-6:n-3 ratio Vitamin E Chlorophyll A Chlorophyll B T. Carotenoids PC1 0.07557 -0.00084 -0.00138 -0.00088 0.00014 -0.03050 0.03036 -0.04168 0.07204 -0.00904 0.01141 0.91322 0.29565 0.25281 PC2 0.02672 -0.00228 -0.00399 -0.00235 0.07726 -0.00028 -0.07698 -0.09586 0.01888 -0.01958 0.98670 0.00301 -0.06187 -0.00380 -0.00181 T. Phenolics 1.9508e-05 1Principal Component Analysis (PCA) loadings for various forage parameters across two principal components (PC1 and PC2).C18:3 n-3, alpha-linolenic acid; C20:5 n-3, eicosapentaenoic acid (EPA); C22:5 n-3, docosapentaenoic acid (DPA); C22:6 n-3, docosahexaenoic acid (DHA); SFA, saturated fatty acids; MUFA, monounsaturated fatty acids; PUFA, polyunsaturated fatty acids; n-6, omega-6 fatty acids; n-3, omega-3 fatty acids; n-6:n-3 ratio, ratio of omega-6 to omega-3 fatty acids; Vitamin E, tocopherol; T. Carotenoids, total carotenoids; T. Phenolics, total phenolics. 88