Resumen de Caracterización funcional de las variedades de la raza aviar utrerana

Antonio González Ariza

• 1. Introducción o motivación de la tesis:

  Los huevos representan una fuente importante de nutrientes que contienen proteínas, lípidos, minerales y vitaminas que permiten el desarrollo del embrión. Algunos de estos nutrientes, como las enzimas, tienen funciones multibiológicas. Como resultado, el huevo está presente en gran parte de la dieta humana en las diferentes culturas del mundo. Este valor añadido de los huevos se complementa con su amplia aplicabilidad culinaria: se pueden utilizar para preparar desayunos o comidas caseras, hornear y como ingrediente en muchas recetas culinarias.

  Actualmente, casi toda la producción avícola proviene de líneas híbridas comerciales, las cuales se caracterizan por un alto rendimiento productivo y un buen índice de conversión alimenticia. Estos genotipos presentan características de producto homogéneas que podrían no cumplir la multitud de demandas del mercado, considerando la necesidad de nuevos productos por parte de los consumidores. Adicionalmente, la obtención y producción de estas líneas altamente productivas promueve una disminución en la variabilidad genética de la especie y tiene efectos negativos en el desarrollo de prácticas sostenibles basadas en razas locales.

  La aparición de nuevas líneas comerciales de gallinas ponedoras con una capacidad productiva mucho mayor provocó el desplazamiento de las razas autóctonas a lo largo del siglo XX. En muchos casos, su hibridación con líneas más productivas relegó a las razas autóctonas, incluida la raza aviar Utrerana, a una forma secundaria de avicultura ornamental, basada en la selección morfológica y faneróptica de los animales reproductores.

  A pesar de que existe una amplia biodiversidad de especies aviares españolas de interés zootécnico, es necesario destinar proyectos para caracterizar estos genotipos y sus productos. La caracterización productiva de gallina de Utrerana se torna imprescindible para la obtención de productos diferenciados obtenidos a través de sistemas productivos sostenibles. Estas producciones avícolas sostenibles no sólo tienen un menor impacto en el medio ambiente y la salud humana, sino que también se desarrollan en el ámbito del bienestar animal.

  2.Contenido de la investigación En el primer estudio se desarrolló una caracterización morfológica de dos razas autóctonas (Utrerana y Sureña) y sus variedades. Se utilizó un análisis discriminante canónico por pasos hacia adelante para determinar los patrones de agrupación de genotipos (raza/variedad). Se reportó que las uñas blancas, el índice ocular y la longitud del dorso tienen el mayor poder discriminante en la diferenciación y caracterización morfológica de la hembra. Para los machos, el índice ocular y los colores del pico negro/córneo y blanco reportaron el mayor potencial discriminatorio. Las distancias de Mahalanobis evidencian la separación entre ambas razas y la proximidad entre sus variedades. A pesar de la capacidad de adaptación a sistemas de producción alternativos que se ha atribuido a ambas razas, las razas aviares Sureña y Utrerana difieren morfológicamente, por lo que sus métodos de adaptación también podrían hacerlo.

  El objetivo del segundo estudio fue modelar los patrones de crecimiento de las cuatro variedades de la raza aviar Utrerana. Se utilizaron los modelos Brody, Von Bertalanffy, Verhulst, Logístico y Gompertz. Para este propósito, se recogió un total de 16235 pesadas de 2004 animales, criados en sistema campero. El modelo logístico fue el más adecuado para predecir la curva de crecimiento biológico de la variedad blanca en ambos sexos, mientras que Von Bertalanffy fue el modelo que mejor se ajustó para el resto de los individuos de la raza. La variedad negra fue la de mayor peso, con valores de 2605,96 y 2032,61 g (para machos y hembras, respectivamente) para el parámetro a, mientras que el menor peso de madurez fue reportado en la variedad blanca (a = 2442,99 y 1874,24 g, para machos y hembras, respectivamente). La caracterización del crecimiento es fundamental para la conservación de la gallina Utrerana como estrategia para atender la demanda de nuevos nichos de mercado y obtener una mayor rentabilidad de este producto diferenciado.

  El tercer estudio tuvo como objetivo comparar el comportamiento de puesta de las cuatro variedades de la gallina Utrerana. Se alojó un lote de 60 gallinas Utreranas individualmente (15 por variedad), lo que permitió la trazabilidad diaria de los huevos. Para el estudio de las curvas de puesta se ajustaron siete modelos de regresión no lineal: compartimental, Gamma, lineal hiperbólico, logístico curvilíneo, McNally, Narushin-Takma y cuadrático logarítmico. Los mejores valores de ajuste fueron alcanzados por el modelo de seis parámetros de Narushin-Takma en las curvas de puesta de las variedades blanca (R2 = 0.828), franciscana (R2 = 0.888) y negra (R2 = 0.899), mientras que el modelo cuadrático logarítmico resultó el mejor modelo de ajuste para el rendimiento de puesta de la variedad perdiz (R2 = 0,917). Este estudio determinó que estos modelos ganaderos se adaptan mejor a los patrones de puesta de la raza y, por lo tanto, permiten mejorar la rentabilidad económica, que a su vez puede asegurar la conservación de estos recursos genéticos locales.

  Los objetivos del cuarto estudio fueron caracterizar la capacidad productiva de la raza Utrerana y comparar las relaciones existentes entre los parámetros que determinan la calidad interna y externa del huevo. Para ello, se realizó un análisis de correlación canónica no lineal. Dos lotes, uno compuesto por 68 gallinas Utrerana y otro por un grupo de control de gallinas Leghorn (n = 17), se alojaron individualmente para permitir la identificación individual y evaluación de las características de calidad de los huevos. Se reportaron diferencias significativas para casi todas las variables estudiadas cuando se compararon ambas razas. Los rasgos de calidad externos son mejores predictores de los rasgos internos que, al contrario. Así, los métodos descritos permiten la implementación de un método no invasivo eficaz para la determinación de la calidad interna y la clasificación de huevos, con el objetivo de satisfacer las necesidades de los consumidores.

  En el quinto estudio se midieron los rasgos de calidad interna y externa en 819 huevos puestos por gallinas de 10 genotipos diferentes: variedades blanca, franciscana, negra y perdiz de la raza Utrerana, Azul Andaluza, Española Cara Blanca, Andaluza Moñuda blanca y negra, Araucana, y gallinas del linaje Leghorn Lohmann LSL-Classic (línea híbrida comercial). Se aplicó un análisis discriminante canónico hacia delante y el método de árbol de decisión CHAID para determinar los patrones de agrupación de huevos vinculados a la calidad de estos genotipos. La calidad de los huevos de Araucana fue la más distante del resto. Además, los huevos de razas autóctonas mediterráneas presentan claros signos de diferenciación de calidad en comparación con los de Leghorn. En consecuencia, estas evidencias en cuanto a diferenciación de la calidad del huevo pueden favorecer la estandarización de productos distintivos vinculados a la raza y la variedad.

  En el sexto estudio, se comparó la composición química del cascarón, la clara y la yema del huevo de las variedades de Utrerana con la del linaje Leghorn Lohmann LSL-Classic. Se cuantificaron y evaluaron los macroelementos y microelementos de cascarón, yema y clara, carbohidratos, humedad, cenizas, proteínas, grasas (poliinsaturadas y saturadas), azúcares, colesterol y α-tocoferol. Simultáneamente, se evaluó la composición detallada de los ácidos grasos de la yema. Mientras que el contenido de calcio fue mayor en el cascarón (358,53 g / kg frente a 337,01 g / kg) y clara de huevo de Utrerana (593,75 mg / kg frente a 584,31 mg / kg), el contenido de proteína fue mayor en la yema (17,40% frente a 16,90%) y clara de Utrerana (10,60% vs 10,30%). Las yemas de Utrerana tuvieron un mayor contenido de α-tocoferol (102,00 mg frente a 88,00 mg), ácidos grasos poliinsaturados totales (19,80% frente a 16,60%) y algunos ácidos grasos monoinsaturados (C18: 1 n9: 42,68% frente a 41,31%; C16: 1 n9: 0,60% frente a 0,50%). El conocimiento de las propiedades diferenciales de los huevos en función de los animales de origen permite desarrollar correctamente un enfoque de más amplio espectro en cuanto a las necesidades del mercado.

  El séptimo estudio tuvo como objetivo comparar las propiedades sensoriales de los huevos de gallina Utrerana con los huevos comerciales y ecológicos del linaje Leghorn Lohmann LSL-Classic, a través de perfiles de libre elección. Los perfiles afines y no afines se definieron utilizando la información proporcionada por panelistas profesionales instruidos en seis sets y utilizando análisis de correlación canónica no lineal. Los observadores reportaron una apreciación significativamente mayor (p> 0.05) hacia el color de la yema, el olor, el sabor, la textura, la puntuación general y el valor visual del huevo entero y roto en el plato cuando se compararon los huevos de Utrerana con el resto de las categorías comerciales de huevos. El perfil profesional A (PPA), o perfil no afín de huevo, se constituyó por personas que consumían menos huevos y puntuó los atributos sensoriales más bajos que el perfil profesional B (PPB) o perfil afín. Además, el PPB tenía un mayor conocimiento sobre la raza Utrerana, por lo que otorgó mayor importancia al carácter ecológico y autóctono del producto. El PPA se caracterizó generalmente por mujeres menores de 20 años sin estudios superiores, mientras que el PPB comprendió hombres de 21 a 40 años con estudios secundarios.

  El objetivo del octavo estudio fue desarrollar una herramienta para validar la clasificación de la calidad del huevo de esta raza multivariedad, en función de los rasgos internos y externos relacionados con la calidad, utilizando un enfoque de análisis canónico discriminante y un árbol de decisiones CHAID de extracción de datos. Un lote de 60 gallinas Utreranas y un grupo de control de 10 gallinas Leghorn se colocaron en jaulas individuales para seguir la trazabilidad de los huevos y realizar una evaluación individual de la calidad interna y externa. Los grupos de huevos se clasificaron según su tamaño comercial (S, M, L y XL), raza de gallina ponedora y variedad. El peso de la clara, cascarón y yema presentaron la mayor capacidad discriminante para determinar las diferencias entre las categorías de calidad del huevo (Wilks’ lambda: 0,335, 0,539 y 0,566 para el peso del albumen, el peso de la cáscara y el peso de la yema, respectivamente). Las propiedades compartidas entre las variedades perdiz y franciscana pueden deberse a que sus huevos presentan yemas más pesadas y pesos totales ligeramente más bajos, mientras que las similitudes de las gallinas Utrerana blanca y Leghorn pueden atribuirse a reminiscencias de hibridación.

  Los estudios mencionados buscan la obtención de un conocimiento más profundo sobre la caracterización zoométrica, faneróptica y productiva de la raza Utrerana. Esto sienta las bases para estrategias que apunten a responder de manera más adecuada a un espectro más amplio de demandas del mercado y tendencias de los consumidores, lo que, a su vez, puede asegurar la sostenibilidad de las políticas de conservación de este recurso zoogenético.

  3.Conclusión 1. La consideración de la raza aviar Utrerana, como raza multivariedad, es productivamente ventajosa, ya que podría cubrirse una gama más amplia de demanda del mercado en términos de características organolépticas de la canal.

  2. El análisis discriminante canónico fue validado como una herramienta para realizar la selección individual y la adscripción a la raza considerando rasgos fácilmente medibles como índice ocular y la faneróptica.

  3. Los modelos no lineales son adecuados para describir el crecimiento biológico y la curva de puesta de la raza aviar Utrerana, destacando los modelos logístico y Von Bertalanffy como los mejores modelos de ajuste de crecimiento en las diferentes variedades de Utrerana. Los modelos Narushin-Takma y cuadrático logarítmico mostraron criterios aceptables de bondad de ajuste y flexibilidad para describir las curvas biológicas de puesta de la Utrerana, una raza en peligro de extinción con censos limitados y, por lo tanto, con un bajo número de observaciones disponibles.

  4. La Utrerana es una raza de crecimiento lento que se caracteriza por un claro dimorfismo sexual en términos de peso corporal, que se hace evidente a partir de los 45 días. El bajo peso adulto de los individuos hace preceptivo estimar los parámetros genéticos de crecimiento y diferenciar las características de la canal en esta raza.

  5. Aunque la línea Leghorn produce huevos más pesados, la proporción yema/albúmina es mayor en los huevos de Utrerana, principalmente en las variedades de perdiz y franciscana. La selección de líneas modernas de gallinas ponedoras ha inducido a un aumento de peso del huevo. Sin embargo, esto se ha traducido en una disminución simultánea del contenido energético del huevo, como consecuencia directa de una disminución del porcentaje de yema.

  6. La herramienta de análisis de correlación canónica no lineal permite determinar cómo los indicadores de calidad externa de los huevos pueden reportar indirectamente información sobre rasgos de calidad interna. Esto podría significar un gran avance en la identificación y tipificación de productos específicos, que puedan cubrir la demanda actual creciente de productos de calidad no convencional en los mercados, como pueden ser los huevos de la raza Utrerana.

  7. Algunas características externas, como la cromaticidad de la cáscara y el índice de forma del huevo, que son fácilmente medibles sin necesidad de romper la cáscara, pueden aportarnos una gran cantidad de información que permite la correcta clasificación de los huevos de los diferentes genotipos que conviven en el sur de España.

  8. Entre los diferentes rasgos internos relacionados con la calidad, la calidad del albumen, como las unidades Haugh y el peso, juegan un papel fundamental en la determinación de las diferencias entre los grupos de huevos. Los resultados evidenciaron grandes propiedades diferenciales de calidad cuando se compararon razas autóctonas españolas con las de líneas híbridas comerciales u otras razas nativas foráneas, como la gallina Araucana.

  9. La caracterización química de los huevos de la raza Utrerana ha revelado que estos huevos podrían considerarse alimentos funcionales. Hay pruebas que sugieren que sus beneficios fisiológicos para la salud humana pueden atribuirse principalmente a su mayor contenido en proteínas, en algunos MUFA y en el contenido total de ácidos grasos poliinsaturados.

  10. La concentración de Ca y Mg en las cáscaras de huevo de Utrerana sugiere que las estas son más fuertes y rígidas que las de Leghorn, a pesar de que presentan un peso de cáscara menor que la Leghorn.

  11. Un test de preferencia sensorial con panelistas profesionales instruidos sugirió que los atributos sensoriales en los huevos de la raza Utrerana son más apreciados que los de las categorías comerciales y ecológicas. La calidad diferenciada de este producto podría ser la clave para mejorar la rentabilidad de los sistemas de producción de huevos de Utrerana.

  12. La definición de un perfil afín a los huevos de Utrerana permite delinear estrategias potenciales para el diseño e implementación de campañas de marketing e identificar aquellos sectores en los que se debe hacer un mayor esfuerzo, con el fin de cubrir la creciente demanda de productos ligados a razas autóctonas de calidad no convencional.

  13. Los rasgos de peso juegan un papel fundamental en la determinación de la calidad comercial de los huevos. Esto puede evidenciar una falta histórica de atención comercial a los rasgos de calidad a favor de los rasgos cuantitativos.

  14. La gallina Utrerana mostró características óptimas de adaptabilidad al comportamiento anti-depredador y rusticidad. La raza debe seguir un programa de cría considerando principalmente su capacidad para poner huevos. Para ello, mediante el uso de ciertos parámetros como el pico de puesta y la persistencia, los animales pueden ser seleccionados de manera eficiente en el primer mes de puesta.

  15. Aunque las tasas de producción de huevos de la raza Utrerana son bajas, el índice de puesta de las variedades blanca, franciscana y negra de Utrerana fue aceptable hasta el final del verano. Además, la Utrerana puede presentar una mayor tolerancia al estrés térmico y adaptación a producciones alternativas, como los sistemas campero y ecológico, dado que no se encontraron diferencias significativas en el peso de la cáscara de huevo durante los primeros seis meses del año.

  16. La combinación entre el análisis discriminante canónico y los árboles de decisión CHAID de extracción de datos puede constituir una herramienta de clasificación eficiente para clasificar huevos de diferentes variedades de gallina Utrerana entre genotipos nacionales e internacionales y clasificarlos de acuerdo con su calidad comercial considerando los rasgos de calidad del huevo. Esto, a su vez, puede revelar la existencia de hibridación o posible mezcla entre razas.

  17. El estudio de las cualidades físicas, químicas y sensoriales de las variedades Utrerana reveló que comercialmente, la diferenciación de productos podría ser una oportunidad factible para los productos derivados de Utrerana y podría constituir un punto favorable al compararlos con huevos de otras razas que tradicionalmente se han vendido en el mercado.

  4. Bibliografía 1. Abdullah, M. M. H., S. Jew, and P. J. H. Jones. 2017. Health benefits and evaluation of healthcare cost savings if oils rich in monounsaturated fatty acids were substituted for conventional dietary oils in the United States. Nutrition Reviews 75:163-174.

  2. Abioja, M. O., J. A. Abiona, O. F. Akinjute, and H. T. Ojoawo. 2020. Effect of storage duration on egg quality, embryo mortality and hatchability in FUNAAB‐ɑ chickens. Journal of Animal Physiology and Animal Nutrition 00:1-10.

  3. Adams, C. J., and D. D. Bell. 1980. Predicting poultry egg production. Poultry Science 59:937-938.

  4. Adeogun, I. O., and F. O. Amole. 2004. Some quality parameters of exotic chicken eggs under different storage conditions. Bulletin of Animal Health and Production in Africa 52:43-47.

  5. Agri, E. C. D. 2021. Available online: https://ec.europa.eu/agriculture/eggs_es.

  6. Ahmed, A. M. H., A. B. Rodriguez-Navarro, M. L. Vidal, J. Gautron, J. M. García-Ruiz, and Y. Nys. 2005. Changes in eggshell mechanical properties, crystallographic texture and in matrix proteins induced by moult in hens. British Poultry Science 46:268-279.

  7. Ahn, D. U., S. Kim, and S. Hc, 1997. Effect of egg size and strain and age of hens on the solids content of chicken eggs. Poultry Science 76:914-919.

  8. Aksoy, T., D. I. Cürek, D. Narinç, and A. Önenç. Effects of season, genotype, and rearing system on broiler chickens raised in different semi-intensive systems: performance, mortality, and slaughter results. Tropical Animal and Health Production 53:1-11.

  9. Alderson, G. L. H. 2018. Conservation of breeds and maintenance of biodiversity: justification and methodology for the conservation of Animal Genetic Resources. Archivos de Zootecnia 65:300-309.

  10. Alkan, S., A. Galiç, T. Karsli, and K. Karabağ. 2015. Effects of egg weight on egg quality traits in partridge (Alectoris Chukar). Journal of Applied Animal Research 43:450-456.

  11. Anderson, K., J. Tharrington, P. Curtis, and F. Jones. 2004. Shell characteristics of eggs from historic strains of single comb white leghorn chickens and the relationship of egg shape to shell strength. International Journal of Poultry Science 3:17-19.

  12. Anton, M., V. Martinet, M. Dalgalarrondo, V. Beaumal, E. David-Briand, and H. Rabesona. 2003. Chemical and structural characterisation of low-density lipoproteins purified from hen egg yolk. Food Chemistry 83:175-183.

  13. Anuthama, K., S. Shankar, V. Ilayaraja, G. S. Kumar, and M. Rajmohan. 2011. Determining dental sex dimorphism in South Indians using discriminant function analysis. Forensic Science International 212:86-89.

  14. Anzaldua Morales, A. 1994. La Evaluación Sensorial de los Alimentos en teoría y la práctica, 1st ed. Acribia: Madrid, Spain 214.

  15. AOAC, 2000. Official Methods of Analysis, 17th ed. The Association of Official Analytical Chemists Inc.: Rockville, Maryland, USA.

  16. Araújo de Carvalho, D., A. Martínez Martínez, I. Carolino, M. C. Barros, M. E. Camacho Vallejo, F. Santos-Silva, M. J. de Oliveira Almeida, N. Carolino, J. V. Delgado Bermejo, and J. L. R. Sarmento. 2020. Diversity and Genetic Relationship of Free-Range Chickens from the Northeast Region of Brazil. Animals 10:1857.

  17. Arthur, J. A., and N. O'Sullivan. 2005. Breeding chickens to meet egg quality needs. International Hatchery Practice 19:7-9.

  18. Assefa, H., and A. Melesse. 2018. Morphological and morphometric characterization of indigenous chicken populations in Sheka Zone, South Western Ethiopia. Poultry, Fisheries and Wildlife Sciences 6:1-9.

  19. Atil, H., M. Grossman, and Ç. Takma. 2007. Comparison of growth curve models on average and individual body weights in chickens. Archiv Für Gerflügelkunde 71:1-5.

  20. Atta, M., B. Eljack, and A. Obied. 2010. Use of mathematical modeling to evaluate production performance of some commercial layer strains under Khartoum State conditions (Sudan). Animal Science Journal 1:9-22.

  21. Aygun, A. 2014. The relationship between eggshell colour and egg quality traits in table eggs. Indian Journal of Animal Research 48:290-294.

  22. Bain, M. M. 2007. Recent advances in the assessment of eggshell quality and their future application. World's Poultry Science Journal 61:268-277.

  23. Banks, M. S., W. W. Sprague, J. Schmoll, J. A. Q. Parnell, and G. D. Love. 2015. Why do animal eyes have pupils of different shapes? Science Advances 1:1500391.

  24. Barba, C., L. Fernández-Tomillo, R. Jiménez, J. Guzmán, and A. García. 2016. Environmental ecological value and conservation of local sheep breeds endangered in Andalusia. Archivos de Zootecnia 65:445-448.

  25. Barbato, G. 1990. Selection for exponential growth rate at different ages: Short term responses. Poultry Science 69:14.

  26. Barberger-Gateau, P., M. Jutand, L. Letenneur, S. Larrieu, B. Tavernier, and C. Berr. 2005. Correlates of regular fish consumption in French elderly community dwellers: data from the Three-City study. European Journal of Clinical Nutrition 59:817-825.

  27. Bárcenas, P., F. P. Elortondo, and M. Albisu. 2003. Comparison of free choice profiling, direct similarity measurements and hedonic data for ewes’ milk cheeses sensory evaluation. International Dairy Journal 13:67-77.

  28. Bárcenas, P., R. P. de San Román, F. P. Elortondo, and M. Albisu. 2001. Consumer preference structures for traditional Spanish cheeses and their relationship with sensory properties. Food Quality and Preference 12:269-279.

  29. Bathaei, S. S., and P. L. Leroy. 1998. Genetic and phenotypic aspects of the growth curve characteristics in Mehraban Iranian fat-tailed sheep. Small Ruminant Research 29:261-269.

  30. Baykalir, Y., and U. G. Simsek. 2018. Impact of Different Rearing Systems and Age on Bovans White Layer’s Performance, Egg Quality Traits and Synthesis of Heat Shock Protein 70 kDa. Annals of Animal Science 18:1045-1060.

  31. Baykara, B. 2015. Impact of evaluation methods on decision tree accuracy. Master thesis. University of Tampere, Finland.

  32. Beckmann, S., and K. Kristensen. 1994. The green consumer: some Danish evidence. Xingxiao Pinglun 1:138-145.

  33. Begli, H. E., S. Zerehdaran, S. Hassani, M. Abbasi, and A. K. Ahmadi. 2010. Heritability, genetic and phenotypic correlations of egg quality traits in Iranian native fowl. British Poultry Science 51:740-744.

  34. Bejaei, M., K. Wiseman, and K. Cheng. 2011. Influences of demographic characteristics, attitudes, and preferences of consumers on table egg consumption in British Columbia, Canada. Poultry Science 90:1088-1095.

  35. Bentabol, A., and D. Afonso. 2011. Estudio sensorial: Gofio elaborado con trigo local vs gofio elaborado con trigo foráneo. In I Cata de Gofio, Casa de la Miel, Tenerife, Spain, Cabildo de Tenerife. Centro de Conservación de la Biodiversidad Agrícola de Tenerife: Tenerife, Spain.

  36. Bettridge, J. M., A. Psifidi, Z. G. Terfa, T. T. Desta, M. Lozano-Jaramillo, T. Dessie, P. Kaiser, P. Wigley, O. Hanotte, and R. M. Christley. 2018. The role of local adaptation in sustainable production of village chickens. Nature Sustainability 1:574-582.

  37. Bílková, B., Z. Świders, L. Zita, D. Laloë, M. Charles, V. Beneš, P. Stopka, and M. Vinkler. 2018. Domestic fowl breed variation in egg white protein expression: application of proteomics and transcriptomics. Journal of Agricultural and Food Chemistry. 66:11854-11863.

  38. Biswal, S., M. Thirunavukkarasu, S. Selvam, R. Venkataramanan, and A. S. S. Pandian. 2017. Modeling lactation curve in jersey crossbred cows. Entomology and Zoology Studies 5:1282-1285.

  39. Blokhuis, H., R. Jones, R. Geers, M. Miele, and I. Veissier. 2003. Measuring and monitoring animal welfare: transparency in the food product quality chain. Animal Welfare 12:445-456.

  40. Boxall, P. C., J. P. Emunu, A. Asselin, C. Boyd, E. Goddard, and A. Neall. 2007. Consumer attitudes, willingness to pay and revealed preferences for different egg production attributes: analysis of Canadian egg consumers. Project Report, University of Alberta, Canada.

  41. Brant, A., K. Norris, and G. Chin. 1953. A spectrophotometric method for detecting blood in white-shell eggs. Poultry Science 32:357-363.

  42. Breiman, L., J. Friedman, C. J. Stone, and R. A. Olshen. 1984. Classification and regression trees. CRC press: Boca Ratón, FL, USA.

  43. Brito, N. V., J. C. Lopes, V. Ribeiro, R. Dantas, and J. V. Leite. 2021. Biometric Characterization of the Portuguese Autochthonous Hens Breeds. Animals 11:498.

  44. Brooke, M. d. L., S. Hanley, and S. Laughlin. 1999. The scaling of eye size with body mass in birds. Proceedings of the Royal Society of London. Series B: Biological Sciences 266:405-412.

  45. Brown, J. D. 2008. Effect size and eta squared. JALT Testing and Evaluation SIG News 12:38-43.

  46. Bunea, A., F. M. Copaciu, S. Pascalau, F. Dulf, D. Rugină, R. Chira, and A. Pintea. 2017. Chromatographic analysis of lypophilic compounds in eggs from organically fed hens. Journal of Applied Poultry Research 26:498-508.

  47. Burger, J. 1994. Heavy metals in avian eggshells: another excretion method. Journal of Toxicology and Environmental Health 41:207-220.

  48. Busse, M., M. L. Kernecker, J. Zscheischler, F. Zoll, and R. Siebert. 2019. Ethical concerns in poultry production: A German consumer survey about dual purpose chickens. Journal of Agricultural and Environmental Ethics 32:905-925.

  49. Cajal, J. R., and A. Francesch. 2014. Productive characterization of Sobrarbe hen. Archivos de Zootecnia 63:211-214.

  50. Campo, J. L. 2007. Las razas ganaderas de Andalucía. Consejería de Agricultura y Pesca, Sevilla, Spain Vol. II:433-439.

  51. Canales, A., V. Landi, A. Martínez, M. Macri, G. Pizarro, J. Delgado, P. Cervantes, A. Hernández, and E. Camacho. 2019. Genetic characterization of the domestic turkey of Mexican backyard. Archivos de Zootecnia 68:480-487.

  52. Cardellino, R.A. 2003. Animal genetic resources conservation and development: the role of FAO. Archivos de Zootecnia 52:185-192.

  53. Carvalho, D. A., A. Martínez Martínez, I. Carolino, M. C. Barros, M. E. Camacho Vallejo, F. Santos-Silva, M. J. Oliveira Almeida, N. Carolino, J. V. Delgado Bermejo, and J. L. Rocha Sarmento. 2020. Diversity and Genetic Relationship of Free-Range Chickens from the Northeast Region of Brazil. Animals 10:1857.

  54. Cason, J. 1990. Comparison of linear and curvilinear decreasing terms in logistic flock egg production models. Poultry Science 69:1467-1470.

  55. Cason, J., and Britton, WM, 1988. Comparison of compartmental and Adams-Bell models of poultry egg production. Poultry Science 67:213-218.

  56. Castellini, C., A. Bosco, D. Mugnai, and B. Marcella. 2010. Performance and behaviour of chickens with different growing rate reared according to the organic system. Italian Journal of Animal Science 1:290-300.

  57. Castelló, S. 1921. Type of an anuropygidious (rumpless) cock and hen breed with earrings in Chile. In: Proceedings of the First World Poultry Congress.

  58. Castillo, A., M. Gariglio, A. Franzoni, D. Soglia, S. Sartore, A. Buccioni, F. Mannelli, M. Cassandro, F. Cendron, and C. Castellini. 2021. Overview of Native Chicken Breeds in Italy: Conservation Status and Rearing Systems in Use. Animals 11:490.

  59. Cerjak, M., R. Haas, F. Brunner, and M. Tomić. 2014. What motivates consumers to buy traditional food products? Evidence from Croatia and Austria using word association and laddering interviews. British Food Journal 11-.1726-1747.

  60. Ceylan, Z., S. Gürsev, and S. Bulkan. 2018. An application of data mining in individual pension savings and investment system. European Journal of Science and Technology 1:7-11.

  61. Chan, Y. 2005. Biostatistics 303. Discriminant analysis. Singapore Medical Journal 46:54.

  62. Chromatographic analysis of lypophilic compounds in eggs from organically fed hens. Journal of Applied Poultry Research 26:498-508.

  63. Cohen, J. 1969. Statistical power analysis for the behavioral sciences. Academic Press: New York, USA 416.

  64. Cohen, J. 1977. Statistical Power Analysis for the Behavioral Sciences. Routledge. Academic Press: New York, USA.

  65. Cohen, J. 1988. Statistical power analysis for the behavioral sciences. Lawrence Earlbaum Associates. Inc., Hillsdale, NJ, USA.

  66. Conrad, Z., L. K. Johnson, J. N. Roemmich, W. Juan, and L. Jahns. 2017. Time trends and patterns of reported egg consumption in the US by sociodemographic characteristics. Nutrients 9:333.

  67. Coolican, H. 2009. Research Methods and Statistics in Psychology. Hodder Education: London, UK.

  68. Coyne, J. A., E. H. Kay, and S. Pruett‐Jones. 2008. The genetic basis of sexual dimorphism in birds. Evolution: International Journal of Organic Evolution 62:214-219.

  69. Cuadras, C. M., and J. Augé. 1981. A continuous general multivariate distribution and its properties. Communications in Statistics-Theory and Methods 10:339-353.

  70. Cubiló, M. D., M. Tor, H. Hernández, and A. Francesch. 1999. Comparative study of growth in cocks and capons of Penedesenca Negra breed. Información Técnica Económica Agraria 20:717-719.

  71. Curtis, P. A., F. A. Gardner, and D. B. Mellor. 1985. A Comparison of Selected Quality and Compositional Characteristics of Brown and White Shell Eggs: I. Shell Quality. Poultry Science 64:297-301.

  72. Dalbeck, P., and M. Cusack. 2006. Crystallography (electron backscatter diffraction) and chemistry (electron probe microanalysis) of the avian eggshell. Crystal Growth & Design 6:2558-2562.

  73. Dalle Zotte, A., E. Gleeson, D. Franco, M. Cullere, and J. M. Lorenzo. 2020. Proximate Composition, Amino Acid Profile, and Oxidative Stability of Slow-Growing Indigenous Chickens Compared with Commercial Broiler Chickens. Foods 9:546.

  74. Daoud, J. I. 2017. Multicollinearity and regression analysis. Journal of Physics: Conference Series 949:012009.

  75. Dauphin, Y., G. Luquet, A. Pérez-Huerta, and M. Salomé. 2018. Biomineralization in modern avian calcified eggshells: similarity versus diversity. Connective Tissue Research 59:67-73.

  76. Dávila, S. G., J. L. Campo, M. G. Gil, C. Castaño, and J. Santiago-Moreno. 2015. Effect of the presence of hens on roosters sperm variables. Poultry Science 94:1645-1649.

  77. Dávila, S., M. Gil, P. Resino-Talaván, and J. Campo. 2009. Evaluation of diversity between different Spanish chicken breeds, a tester line, and a White Leghorn population based on microsatellite markers. Poultry Science 88:2518-2525.

  78. De la Cruz Blanco, M., J. Ocaña, M. Rodríguez, A. Cabello, J. M. León, and J. Doctor. 2011. Estudio de la curva de crecimiento en la gallina Sureña. Feagas:158-162.

  79. De Man, J.M. 1964. Determination of the fatty acid composition of milk fat by dual column temperature programmed gas-liquid chromatography. Journal of Dairy Science 47:546-547.

  80. Del Castillo, J. 1951. Las Gallinas Utreranas. Historia y descripción de esta nueva raza. Ediciones Tipografía Moderna: Utrera, Spain.

  81. Delgado Bermejo, J. V., M. A. Martínez Martínez, G. Rodríguez Galván, A. Stemmer, F. J. Navas González, and M. E. Camacho Vallejo. 2019. Organization and Management of Conservation Programs and Research in Domestic Animal Genetic Resources. Diversity 11:235.

  82. Desta, T. 2019. Phenotypic characteristic of junglefowl and chicken. World's Poultry Science Journal 75:69-82.

  83. Dhama, K., R. Singh, K. Karthik, S. Chakraborty, R. Tiwari, M. Y. Wani, and J. Mohan. 2014. Artificial Insemination in Poultry and Possible Transmission of Infectious Pathogens: A Review. Asian Journal of Animal and Veterinary Advances 4:211-228.

  84. Di Rosa, A. R., B. Chiofalo, V. Lo Presti, V. Chiofalo, and L. Liotta. 2020. Egg quality from Siciliana and Livorno Italian autochthonous chicken breeds reared in organic system. Animals 10:864.

  85. Dijksterhuis, G. 1994. Procrustes analysis in studying sensory-instrumental relations. Food Quality and Preference 5:115-120.

  86. Ding, J., W. Yang, Y. Yang, S. Ai, X. Bai, and Y. Zhan. 2019. Variations in tree sparrow (Passer montanus) egg characteristics under environmental metal pollution. Science of The Total Environment 687:946-955.

  87. Ding, Y., X. Bu, N. Zhang, L. Li, and X. Zou. 2016. Effects of metabolizable energy and crude protein levels on laying performance, egg quality and serum biochemical indices of Fengda-1 layers. Animal Nutrition 2:93-98.

  88. Djoussé, L., and J. M. Gaziano. 2008. Egg consumption in relation to cardiovascular disease and mortality: the Physicians’ Health Study. The American Journal of Clinical Nutrition 87:964-969.

  89. Domagała, J., M. Sady, T. Grega, H. Pustkowiak, and A. Florkiewicz. 2010. The influence of cheese type and fat extraction method on the content of conjugated linoleic acid. Journal of Food Composition and Analysis 23:238-243.

  90. Dong, X., J. Dong, Y. Peng, and X. Tang. 2017. Comparative study of albumen pH and whole egg pH for the evaluation of egg freshness. Spectroscopy Letters 50:463-469.

  91. Donoghue, D. J. 2003. Antibiotic residues in poultry tissues and eggs: human health concerns? Poultry science 82:618-621.

  92. Dorji, N., and S. Sunar. 2014. Short communication Morphometric variations among five Bhutanese indigenous chickens (Gallus domesticus). Journal of Animal and Poultry Sciences 3:76-85.

  93. Dorn, S., C. A. Wascher, E. Möstl, and K. Kotrschal. 2014. Ambient temperature and air pressure modulate hormones and behaviour in Greylag geese (Anser anser) and Northern bald ibis (Geronticus eremita). Behavioural Processes 108:27-35.

  94. Dróżdż, D., K. Wystalska, K. Malińska, A. Grosser, A. Grobelak, and M. Kacprzak. 2020. Management of poultry manure in Poland - Current state and future perspectives. Journal of Environmental Management 264:110327.

  95. Dudusola, I. O. 2010. Comparative evaluation of internal and external qualities of eggs from quail and guinea fowl. International Research Journal of Plant Science 1:112-115.

  96. Duman, M., A. Şekeroğlu, A. Yıldırım, H. Eleroğlu, and Ö. Camcı. 2016. Relation between egg shape index and egg quality characteristics. European Poultry Science 80:1-9.

  97. Dvořák, P., J. Doležalová, and P. Suchý. 2009. Photocolorimetric determination of yolk colour in relation to selected quality parameters of eggs. Journal of the Science of Food and Agriculture 89:1886-1889.

  98. Eisen, E., B. Bohren, and H. McKean. 1962. The Haugh unit as a measure of egg albumen quality. Poultry Science 41:1461-1468.

  99. Emery, D. A., P. Vohra, R. A. Ernst, and S. R. Morrison. 1984. The Effect of Cyclic and Constant Ambient Temperatures on Feed Consumption, Egg Production, Egg Weight, and Shell Thickness of Hens. Poultry Science 63:2027-2035.

  100. Faitarone, A., E. Garcia, R. O. Roça, H. A. Ricardo, E. N. Andrade, K. Pelícia, and F. Vercese. 2013. Cholesterol levels and nutritional composition of commercial layers eggs fed diets with different vegetable oils. Brazilian Journal of Poultry Science 15:31-37.

  101. FAOSTAT. 2021. Production: Livestock Primary: Eggs, hen, in shell (number). FAOSTAT database. Available online: http://fenixservices.fao.dorg/faostat/stati c/documents/EI/EI_e.pdf.

  102. Farahani, S., N. Eshghi, A. Abbasi, F. Karimi, E. Malekabad, and M. Rezaei. 2015. Determination of heavy metals in albumen of hen eggs from the Markazi Province (Iran) using ICP-OES technique. Toxin Reviews 34:96-100.

  103. Faridi, A., M. Mottaghitalab, F. Rezaee, and J. France, J. 2011. Narushin-Takma models as flexible alternatives for describing economic traits in broiler breeder flocks. Poultry Science 90:507-515.

  104. Feddern, V., M. C. D. Prá, R. Mores, R. d. S. Nicoloso, A. Coldebella, and P. G. d. Abreu. 2017. Egg quality assessment at different storage conditions, seasons and laying hen strains. Ciência e Agrotecnologia 41:322-333.

  105. Fernández, M., M. Gómez, J. V. Delgado, S. Adán, and M. Jiménez. 2009. Guía de campo de las razas autóctonas españolas. Ministerio de Medio Ambiente y Medio Rural y Marino: Madrid, Spain 683-684.

  106. Fernández‐Juricic, E., M. D. Gall, T. Dolan, V. Tisdale, and G. R. Martin. 2008. The visual fields of two ground‐foraging birds, House Finches and House Sparrows, allow for simultaneous foraging and anti‐predator vigilance. Ibis 150:779-787.

  107. Fleiss, J. L., and J. Cohen. 1973. The equivalence of weighted kappa and the intraclass correlation coefficient as measures of reliability. Educational and Psychological Measurement 33:613-619.

  108. Francesch, A. 1998. Running of the local poultry breeds conservation in Catalonia. Archivos de Zootecnia 47:141-148.

  109. Francesch, A., I. Villalba, and M. Cartañà. 2011. Methodology for morphological characterization of chicken and its application to compare Penedesenca and Empordanesa breeds. Animal Genetic Resources 48:79-84.

  110. Franco, D., D. Rois, A. Arias, J. R. Justo, F. J. Marti-Quijal, S. Khubber, F. J. Barba, M. López-Pedrouso, and J. M. Lorenzo. 2020. Effect of Breed and Diet Type on the Freshness and Quality of the Eggs: A Comparison between Mos (Indigenous Galician Breed) and Isa Brown Hens. Foods 9:342.

  111. Franco, D., D. Rois, J. A. Vázquez, L. Purriños, R. González, and J. M. Lorenzo. 2012. Breed effect between Mos rooster (Galician indigenous breed) and Sasso T-44 line and finishing feed effect of commercial fodder or corn. Poultry Science 91:487-498.

  112. Frie, K. G., and C. Janssen. 2009. Social inequality, lifestyles and health-a non-linear canonical correlation analysis based on the approach of Pierre Bourdieu. International Journal of Public Health 54:213-221.

  113. Fritz, C. O., P. E. Morris, and J. J. Richler. 2012. Effect size estimates: current use, calculations, and interpretation. Journal of experimental psychology: General 141:2.

  114. Fuller, N. R., I. D. Caterson, A. Sainsbury, G. Denyer, M. Fong, J. Gerofi, K. Baqleh, K. H. Williams, N. S. Lau, and T. P. Markovic. 2015. The effect of a high-egg diet on cardiovascular risk factors in people with type 2 diabetes: the Diabetes and Egg (DIABEGG) study-a 3-mo randomized controlled trial. The American Journal of Clinical Nutrition 101:705-713.

  115. Galic, A., D. Filipovic, Z. Janjecic, D. Bedekovic, I. Kovacev, K. Copec, and S. Pliestic. 2019. Physical and mechanical characteristics of Hisex Brown hen eggs from three different housing systems. South African Journal of Animal Science 49:468-476.

  116. Galli, G. M., A. S. Da Silva, A. H. Biazus, J. H. Reis, M. M. Boiago, J. P. Topazio, M. J. Migliorini, N. S. Guarda, R. N. Moresco, A. F. Ourique, C. G. Santos, L. S. Lopes, M. D. Baldissera, and L. M. Stefani. 2018. Feed addition of curcumin to laying hens showed anticoccidial effect, and improved egg quality and animal health. Research in Veterinary Science 118:101-106.

  117. Gangnat, I. D., S. Mueller, M. Kreuzer, R. E. Messikommer, M. Siegrist, and V. H. Visschers. 2018. Swiss consumers’ willingness to pay and attitudes regarding dual-purpose poultry and eggs. Poultry Science 97:1089-1098.

  118. Garcia, C., and R. Cordero. 2006. Las Razas Autóctonas en el contexto de la Ganadería Ecológica. Dossier Ganadería Extensiva 6:32-33.

  119. Gavora, J., R. Parker, and A. I. McMillan. 1971. Mathematical model of egg production. Poultry Science 50:1306-1315.

  120. George, D., and P. Mallery. 2003. Reliability analysis. In SPSS for Windows, Step by Step: A simple guide and reference. Allyn & Bacon: Boston, MA, USA.

  121. Goldberg, E.M., D. Ryland, R. Gibson, M. Aliani, and J. D. House. 2013. Designer laying hen diets to improve egg fatty acid profile and maintain sensory quality. Food Science & Nutrition 1:324-335.

  122. Gómez-Cuello, J. E., L. M. F. Benítez R. M. P. Olivera, R. Vázquez, M. de Oca, L. D. Guerra, M. V. Navarro. 2017. A Model to Estimate the Laying Curve of White Leghorn Hens in the Last Three Years in the Province of Ciego de Avila, Cuba. Journal of Animal Production 29:42-49.

  123. González Ariza, A, F. J. Navas González, A. Arando Arbulu, J. M. León Jurado, C. J. Barba Capote, and M. E. Camacho Vallejo. 2019. Non-Parametrical Canonical Analysis of Quality-Related Characteristics of Eggs of Different Varieties of Native Hens Compared to Laying Lineage. Animals 9:153.

  124. González Ariza, A., A. Arando Arbulu, F. J. Navas González, F. A. Ruíz Morales, J. M. León Jurado, C. J. Barba Capote, and Camacho Vallejo, M.E., 2019. Sensory preference and professional profile affinity definition of endangered native breed eggs compared to commercial laying lineages’ eggs. Animals 9:920.

  125. González Ariza, A., A. Arando Arbulu, F. J. Navas González, J. V. Delgado Bermejo, and M. E. Camacho Vallejo. 2021. Discriminant Canonical Analysis as a Validation Tool for Multivariety Native Breed Egg Commercial Quality Classification. Foods 10:632.

  126. González Ariza, A., C. J. Barba, J. V. Delgado, J. M. León, A. Arando, F. J. Navas González, S. Nogales, and M. E. Camacho. 2019. Preliminary results on the reproductive characaterization of Utrerana avian breed. Actas Iberoamericanas de Conservación Animal 14:21-26.

  127. González Ariza, A., F. J. Navas González, A. Arando Arbulu, J. V. Delgado Bermejo, and M. E. Camacho Vallejo. 2021. Hen breed and variety factors as a source of variability for the chemical composition of eggs. Journal of Food Composition and Analysis 95:103673.

  128. Grashorn, M. 2016. Feed additives for influencing chicken meat and egg yolk color. In Handbook on Natural Pigments in Food and Beverages, 1st ed. Woodhead Publishing: Sawston, UK 282-302.

  129. Greenacre, M., and T. Hastie. 1987. The geometric interpretation of correspondence analysis. Journal of the American Statistical Association 82:437-447.

  130. Grobas, S., J. Méndez, R. Lázaro, C. de Blas, and G. G. Mateo. 2001. Influence of source and percentage of fat added to diet on performance and fatty acid composition of egg yolks of two strains of laying hens. Poultry Science 80:1171-1179.

  131. Guàrdia, M. D., A. P. Aguiar, A. Claret, J. Arnau, and L. Guerrero. 2010. Sensory characterization of dry-cured ham using free-choice profiling. Food Quality and Preference 21:148-155.

  132. Guo, B., S. Zhao, X. Shao, W. Ding, Z. Shi, and Z. Tang. 2019. Analyses of mathematical models for Yangzhou geese egg-laying curves. Animal Reproduction Science 203:10-24.

  133. Gupta, A., M. Singh, R. Gandhi, A. Singh, S. Dash, S. Dash. 2016. Comparison of different lactation curve models in Sahiwal cattle up to fourth parity using monthly test day milk yields. Indian Journal of Dairy Science 69:2016.

  134. Hair, J. F., W. C. Black, B. J. Babin, and R. E. Anderson. 2010. Canonical correlation: A supplement to multivariate data analysis. Multivariate data analysis: a global perspective. 7th ed. Pearson Prentice Hall Publishing: Upper Saddle River, NJ, USA.

  135. Hall, M., and C. Ross. 2007. Eye shape and activity pattern in birds. Journal of Zoology 271:437-444.

  136. Hanusova, E., C. Hrnčár, A. Hanus, and M. Oravcova. 2015. Effect of breed on some parameters of egg quality in laying hens. Acta Fytohechnica et Zootechnica 18:12-24.

  137. Hartley, H.O. 1961. The modified Gauss-Newton method for the fitting of non-linear regression functions by least squares. Technometrics 3:269-280.

  138. Hartmann, C., K. Johansson, E. Strandberg, and L. Rydhmer. 2003. Genetic correlations between the maternal genetic effect on chick weight and the direct genetic effects on egg composition traits in a White Leghorn line. Poultry Science 82:1-8.

  139. Hartmann, C., K. Johansson, E. Strandberg, and M. Wilhelmson. 2000. One-generation divergent selection on large and small yolk proportions in a White Leghorn line. British Poultry Science 41:280-286.

  140. Haunshi, S., S. Doley, and G. Kadirvel. 2010. Comparative studies on egg, meat, and semen qualities of native and improved chicken varieties developed for backyard poultry production. Tropical Animal Health and Production 42:1013-1019.

  141. Henchion, M., C. De Backer, and L. Hudders. 2017. Ethical and sustainable aspects of meat production: Consumer perceptions and system credibility. In New aspects of Meat Quality, 1st ed. Woodhead Publishing: Sawston, UK 649-666.

  142. Hernandez, J., J. Seehawer, C. Hamelin, M. Bruni, and W. Wakeman. 2001. Egg quality: The European consumer’s perception. Roche Vitamins Europe Ltd.: Basel, Switzerland.

  143. Hertzler, A. A., and F. Bruce. 2002. Cooking, recipe use and food habits of college students and nutrition educators. International Journal of Consumer Studies 26:340-345.

  144. Hester, P. 2016. Egg innovations and strategies for improvements. Academic Press: West Lafayette, IN, USA.

  145. Hill, H. 2012. Raising chickens with altitude. Barnyards and Backyards 1:16-17.

  146. Hocking, P. M., M. Bain, C. E. Channing, R. Fleming, and S. Wilson. 2003. Genetic variation for egg production, egg quality and bone strength in selected and traditional breeds of laying fowl. British Poultry Science 44:365-373.

  147. Hoffmann, I. 2011. Livestock biodiversity and sustainability. Livestock Science 139:69-79.

  148. Hotelling, H. 1935. The most predictable criterion. Journal of educational Psychology 26:13 149. Hotelling, H. 1936. Relation between two sets of variates. Biometrica 28:321-377.

  150. Hough, G., I. Wakeling, A. Mucci, E. Chambers IV, I. M. Gallardo, and L. R. Alves. 2006. Number of consumers necessary for sensory acceptability tests. Food Quality and Preference 17:522-526.

  151. Hsieh, W. W. 2000. Nonlinear canonical correlation analysis by neural networks. Neural Networks 13:1095-1105.

  152. Hui, Y., and F. Sherkat. 2005. Handbook of Food Science, Technology, and Engineering. CRC Press: Boca Ratón, FL USA.

  153. Hussain, J., K. Javed, F. Hussnain, S. Musarrat, A. Mahmud, and S. Mehmood. 2018. Quality and sensory attributes of eggs from different chicken genotypes in Pakistan. Journal of Animal and Plant Sciences 28:1609-1614.

  154. Ianni, A., D. Bartolini, F. Bennato, and G. Martino. 2021. Egg Quality from Nera Atriana, a Local Poultry Breed of the Abruzzo Region (Italy), and ISA Brown Hens Reared under Free Range Conditions. Animals 11:257.

  155. IBM Corp. 2016. IBM SPSS Statistics for Windows, 24.0; IBM Corp, Armonk, NY, USA.

  156. IBM Knowledge Center. 2019. Centroids and Projected Centroids. Available online: https://www.ibm.com/support/knowledgecenter/zh/SSLVMB_23.0.0/ spss/tutorials/overals_verd_centroids.html (accessed on 23June 2019).

  157. Ingr, I., and J. Simeonova. 1983. Rapid assessment of cholesterol in egg yolk by the Bio-La-Test [egg laying hybrids, Czechoslovakia]. Veterinarni Medicina-UVTIZ Czechoslovakia 28-97-104.

  158. Ipek, A., and A. Sozcu. 2017. Comparison of hatching egg characteristics, embryo development, yolk absorption, hatch window, and hatchability of Pekin Duck eggs of different weights. Poultry Science 96:3593-3599.

  159. Iqbal, F., E. Eyduran, N. Mikail, V. Sarıyel, Z. E. Huma, A. Aygün, I. Keskin. 2019. Bayesian approach for describing the growth of Chukar partridges. European Poultry Science 83:1612-9199.

  160. Iqbal, J., N. Mukhtar, Z. U. Rehman, S. H. Khan, T. Ahmad, M. S. Anjum, R. H. Pasha, and S. Umar. 2017. Effects of egg weight on the egg quality, chick quality, and broiler performance at the later stages of production (week 60) in broiler breeders. Journal of Applied Poultry Research 26:183-191.

  161. Islam, K., J. Khan, M. Khalil, and F. Schweigert. 2017. Physical and chemical quality of eggs from commercial chickens in Bangladesh. International Journal of Poultry Science 16:221-227.

  162. Jandacek, R. J. 2017. Linoleic acid: a nutritional quandary. Healthcare 5:25.

  163. Jasouri, M., P. Zamani, and S. Alijani. 2017. Dominance genetic and maternal effects for genetic evaluation of egg production traits in dual-purpose chickens. British Poultry Science 58:498-505.

  164. Jesuyon, O., S. Oseni. 2015. Seasonal sensitivity of genotypes in the humid tropics and its application to chicken breeding. Archives Animal Breeding 58:261-268.

  165. Jin, G. F., M. Gouda, Y. G. Jin, and M. H. Ma. 2019. Characterization and classification of volatiles from different breeds of eggs by SPME-GC-MS and chemometrics. Food Research International 116:767-777.

  166. Johnson, R. A., and D. W. Wichern 2007. Applied Multivariate Statistical Analysis. Prentice-Hall, lnc: New Jersey, USA, Vol. 1:998.

  167. Johnston, N. P., L. K. Jefferies, B. Rodriguez, and D. E. Johnston. 2011. Acceptance of brown-shelled eggs in a white-shelled egg market. Poultry Science 90:1074-1079.

  168. Jones, M. P., K. E. Pierce, and D. Ward. 2007. Avian Vision: A Review of Form and Function with Special Consideration to Birds of Prey. Journal of Exotic Pet Medicine 16:69-87.

  169. Kaplan, S., Gürcan E. K. 2018. Comparison of growth curves using non-linear regression function in Japanese quail. Journal of Applied Animal Research 46:112-117.

  170. Keener, K. M., J. D. LaCrosse, P. A. Curtis, K. E. Anderson, and B. E. Farkas. 2000. The Influence of Rapid Air Cooling and Carbon Dioxided Cooling and Subsequent Storage in Air and Carbon Dioxide on Shell Egg Quality. Poultry Science 79:1067-1071.

  171. Kennedy, O. 2007. Evaluation of the growth parameters of four strains of cockerel. The African Journal of Medical Sciences 2:17-25.

  172. Keshavarz, K. 1987. Influence of feeding a high calcium diet for various durations in prelaying period on growth and subsequent performance of white leghorn pullets. Poultry Science 66:1576-1582.

  173. Kgwatalala, P., M. Molapisi, K. Thutwa, B. Sekgopi, T. Selemoge, and S. Nsoso. 2016. Egg quality characteristics and phenotypic correlations among egg quality traits in the naked neck, normal and dwarf strains of Tswana chickens raised under intensive management system. International Journal of Environmental and Agriculture Research 8:96-105.

  174. Khattree, R., and D. N. Naik. 2000. Multivariate data reduction and discrimination with SAS software. SAS Publishing: Cary, NY, USA.

  175. Kilic, I., and E. Simsek. 2013. The effects of heat stress on egg production and quality of laying hens. Journal of Animal and Veterinary Advances 12:42-47.

  176. Kim, H. C., Y. J. Ko, and C. Jo. 2021. Potential of 2D qNMR spectroscopy for distinguishing chicken breeds based on the metabolic differences. Food Chemistry 342:128316.

  177. Knaga, S., L. Kibała, K. Kasperek, I. Rozempolska-Rucińska, M. Buza, and G. Zięba. 2019. Eggshell strength in laying hens' breeding goals-a review. Animal Science Papers & Reports 37:119-136.

  178. Kostogrys, R.B., A. Filipiak-Florkiewicz, K. Deren, A. Drahun, I. Czyzynska-Cichon, E. Cieślik, B. Szymczyk, and M. Franczyk-Zarow. 2017. Effect of dietary pomegranate seed oil on laying hen performance and physicochemical properties of eggs. Food Chemistry 221:1096-1103.

  179. Krawczyk, J. 2009. Quality of eggs from Polish native Greenleg Partridge chicken-hens maintained in organic vs. backyard production systems. Animal Science Papers and Reports 27:227-235.

  180. Krawczyk, J., L. Lewko, and J. Calik. 2020. Effect of laying hen genotype, age and some interior egg quality traits on lysozyme content. Annals of Animal Science 1:ahead-of-print.

  181. Küçükyılmaz, K., M. Bozkurt, Ç. Yamaner, M. Çınar, A. U. Çatlı, R. Konak. 2012. Effect of an organic and conventional rearing system on the mineral content of hen eggs. Food Chemistry 132:989-992.

  182. Kuo, F. L., J. Craig, and W. M. Muir. 1991. Selection and beak-trimming effects on behavior, cannibalism, and short-term production traits in White Leghorn pullets. Poultry Science 70:1057-1068.

  183. Lacin, E., A. Yildiz, N. Esenbuga, and M. Macit. 2008. Effects of differences in the initial body weight of groups on laying performance and egg quality parameters of Lohmann laying hens. Czech Journal of Animal Science 53:466-471.

  184. Lakins, D., C. Alvarado, A. Luna, S. O’keefe, J. Boyce, L. Thompson, M. Brashears, J. Brooks, and M. Brashears. 2009. Comparison of quality attributes of shell eggs subjected to directional microwave technology. Poultry Science 88:1257-1265.

  185. Lambertz, C., K. Wuthijaree, and M. Gauly. 2018. Performance, behavior, and health of male broilers and laying hens of 2 dual-purpose chicken genotypes. Poultry Science 97:3564-3576.

  186. Landers, K., Z. Howard, C. Woodward, S. Birkhold, and S. Ricke. 2005. Potential of alfalfa as an alternative molt induction diet for laying hens: Egg quality and consumer acceptability. Bioresource Technology 96:907-911.

  187. Laouadi, M., Y. A. Mennah‐Govela, N. Moula, N. A. Moussiaux, and N. Kafidi. 2020. Morphological characterization of indigenous goats in the region of Laghouat in Algeria. Archivos de zootecnia 69:272-279.

  188. Latour, M. A., E. D.Peebles, S. M. Doyle, T. Pansky, T. W. Smith, and C. R. Boyle. 1998. Broiler breeder age and dietary fat influence the yolk fatty acid profiles of fresh eggs and newly hatched chicks. Poultry Science 77:47-53.

  189. Leleu, S., W. Messens, K. De Reu, S. De Preter, L. Herman, M. Heyndrickx, J. De Baerdemaeker, C. Michiels, and M. Bain. 2011. Effect of egg washing on the cuticle quality of brown and white table eggs. Journal of Food Protection 74:1649-1654.

  190. Li, H., Z. Wang, W. Shang, X. Hu, R. Shen, C. Guo, Q. Guo, and K. Subbarao. 2019. Assessment of resistance in potato cultivars to verticillium wilt caused by Verticillium dahliae and V. nonalfalfae. Plant Disease 103:1-24.

  191. Ligda, C., and F. Casabianca. 2013. Adding value to local breeds: challenges, strategies and key factors. Animal Genetic Resources 53:107-116.

  192. Liu, J., W. Drane, X. Liu, and T. Wu. 2009. Examination of the relationships between environmental exposures to volatile organic compounds and biochemical liver tests: application of canonical correlation analysis. Environmental Research 109:193-199.

  193. Liverpool-Tasie, L. S. O., A. Sanou, and J. A. Tambo. 2019. Climate change adaptation among poultry farmers: evidence from Nigeria. Climatic Change 157:527-544.

  194. Loaiza-Echeverri, A. M., J. A. Bergmann, F. L. Toral, J. P. Osorio, A. S. Carmo, L. F. Mendonça, V. S. Moustacas, and M. Henry. 2013. Use of nonlinear models for describing scrotal circumference growth in Guzerat bulls raised under grazing conditions. Theriogenology 79:751-759.

  195. Lordelo, M., E. Fernandes, R. J. B. Bessa, and S. P. Alves. 2017. Quality of eggs from different laying hen production systems, from indigenous breeds and specialty eggs. Poultry Science 96:1485-1491.

  196. Lordelo, M., J. Cid, C. M. D. S. Cordovil, S. P. Alves, R. J. B. Bessa, and I. Carolino. 2020. A comparison between the quality of eggs from indigenous chicken breeds and that from commercial layers. Poultry Science 99:1768-1776.

  197. Lupi, T. M., S. Nogales, J. M. León, C. Barba, and J. V. Delgado. 2015. Characterization of commercial and biological growth curves in the Segureña sheep breed. Animal 9:1341-1348.

  198. Lyimo, C. M., A. Weigend, P. L. Msoffe, H. Eding, H. Simianer, S. Weigend. 2014. Global diversity and genetic contributions of chicken populations from African, Asian and European regions. Animal Genetics 45:836-848.

  199. MacFie, H. J., N. Bratchell, K. Greenhoff, and L. V. Vallis. 1989. Designs to balance the effect of order of presentation and first‐order carry‐over effects in hall tests. Journal of Sensory Studies 4:129-148.

  200. Macri, M., A. Martínez, V. Landi, A. Canales, A. Arando, J. Delgado, and M. Camacho. 2019. Diversidad genética de la raza Gallina Utrerana. Actas Iberoamericanas de Conservación Animal 13:52-59.

  201. Magothe, T. M., W. B. Muhuyi, A. K. Kahi. 2010. Influence of major genes for crested-head, frizzle-feather and naked-neck on body weights and growth patterns of indigenous chickens reared intensively in Kenya. Tropical Animal Health and Production 42:173-183.

  202. Malhotra, P., R. Singh, R. Singh. 1980. Estimating lactation curve in Karan-Swiss cattle (dairy cattle, India). Indian Journal of Animal Sciences 50:799-804.

  203. Manly, B. F., and J. A. N. Alberto. 2016. Multivariate statistical methods: a primer. CRC press, Boca Ratón, FL, USA.

  204. MAPA. 2021. Livestock: Zootecnnics: Livestock breeds: Utrerana breeds. https://www.mapa.gob.es/en/ganaderia/temas/zootecnia/razasganaderas/razas/catalogo-razas/aviar/utrerana/default.aspx.

  205. Marín Navas, C., J. V. Delgado Bermejo, A. K. McLean, J. M. León Jurado, and F. J. Navas González. 2021. Discriminant Canonical Analysis of the Contribution of Spanish and Arabian Purebred Horses to the Genetic Diversity and Population Structure of Hispano-Arabian Horses. Animals 11:269.

  206. Mata-Estrada, A., F. González-Cerón, A. Pro-Martínez, G. Torres-Hernández, J. Bautista-Ortega, C. M. Becerril-Pérez, A. J. Vargas-Galicia, and E. Sosa-Montes. 2020. Comparison of four nonlinear growth models in Creole chickens of Mexico. Poultry Science 99:1995-2000.

  207. McMillan, I. 1981. Compartmental model analysis of poultry egg production curves. Poultry Science 60:1549-1551.

  208. McNally, D. 1971. Mathematical model for poultry egg production. Biometrics 1:735-738.

  209. McNaught, A.D., Wilkinson, A., 1997. Compendium of Chemical Terminology. The Gold Book, 2nd ed. Blackwell Science: Oxford, UK.

  210. Mehlhorn, J., and S. Petow. 2020. Smaller brains in laying hens: New insights into the influence of pure breeding and housing conditions on brain size and brain composition. Poultry Science 99:3319-3327.

  211. Meulman, J. J., and W. J. Heiser. IBM SPSS Categories 21. IBM Corporation: Armonk, NY, USA 212. Michailidis, G., and J. De Leeuw. 1998. The Gifi system of descriptive multivariate analysis. Statistical Science 13:307-336.

  213. Mignon-Grasteau, S., C. Beaumont, E. Le Bihan-Duval, J. P. Poivey, H. De Rochambeau, F. H. Ricard. 1999. Genetic parameters of growth curve parameters in male and female chickens. British Poultry Science 40:44-51.

  214. Miguel, J. A., B. Asenjo, J. Ciria, and J. L. Calvo. 2009. Growth modelling in three chicken genetics types and a commercial line sasso. Effect of the type of housing. Información Técnica Económica Agraria. 105:7-16.

  215. Miguel, J., B. Asenjo, J. Ciria, and J. Calvo. 2007. Growth and lay modelling in a population of Castellana Negra native Spanish hens. British Poultry Science 48: 651-654.

  216. Miyoshi, S., K. M. Luc, K. Kuchida, and T. Mitsumoto, T. 1996. Application of non-linear models to egg production curves in chickens. Japanese Poultry Science 33: 178-184.

  217. Møller, A. P., and J. Erritzøe. 2010. Flight distance and eye size in birds. Ethology 116:458-465.

  218. Monira, K. N., M. Salahuddin, and G. Miah. 2003. Effect of Breed and Holding Period on Egg Quality Characteristics of Chicken. International Journal of Poultry Science 2:261-263.

  219. Montgomery, D. C., E. A. Peck, and G. G. Vining. 2012. Introduction to linear regression analysis. John Wiley & Sons: Hoboken, NJ, USA 672.

  220. Mordenti, A. L., N. Brogna, and A. Formigoni. 2017. Review: The link between feeding dairy cows and Parmigiano-Reggiano cheese production area. The Professional Animal Scientist 33:520-529.

  221. Mori, H., M. Takaya, K. Nishimura, and T. Goto. 2020. Breed and feed affect amino acid contents of egg yolk and eggshell color in chickens. Poultry Science 99:172-178.

  222. Mottet, A., and G. Tempio. 2017. Global poultry production: current state and future outlook and challenges. World’s Poultry Science 73:245-256.

  223. Mpenda, F. N., M. A. Schilling, Z. Campbell, E. B. Mngumi, and J. Buza. 2019. The genetic diversity of local african chickens: A potential for selection of chickens resistant to viral infections. Journal of Applied Poultry Research 28:1-12.

  224. Müller, W., J. Vergauwen, M. Eens, and J. D. Blount. 2012. Environmental effects shape the maternal transfer of carotenoids and vitamin E to the yolk. Frontiers in Zoology 9:1-11.

  225. Muriel, A. 2003. Primeros resultados de la producción de capones de la raza Extremeña Azul criados en libertad. Información Técnica Económica Agraria 24:229-231.

  226. Naderi, N., J. House, Y. Pouliot, and A. Doyen. 2017. Effects of high hydrostatic pressure processing on hen egg compounds and egg products. Comprehensice Reviews in Food Science and Food Safety 16:707-720.

  227. Nanda, M. A., K. B. Seminar, D. Nandika, and A. Maddu. 2018. Discriminant analysis as a tool for detecting the acoustic signals of termites Coptotermes curvignathus (Isoptera: Rhinotermitidae). International Journal of Technology 4:840-851.

  228. Narinç, D., F. Uckardes, and E. Aslan. 2014. Egg production curve analyses in poultry science. World's Poultry Science Journal 70:817-828.

  229. Narinç, D., Narinç N. Ö. Aygün A. 2017. Growth curve analyses in poultry science. World Poultry Science Journal 73:395-408.

  230. Narinç, D., T. Aksoy, E. Karaman, and D. Curek. 2010. Analysis of Fitting Growth Models in Medium Growing Chicken Raised Indoor System. Trends in Animal Veterinary Sciences 1:12-18.

  231. Narushin, V., and C. Takma. 2003. Sigmoid model for the evaluation of growth and production curves in laying hens. Biosystems Engineering 84:343-348.

  232. Nematinia, E., and S. Abdanan Mehdizadeh. 2018. Assessment of egg freshness by prediction of Haugh unit and albumen pH using an artificial neural network. Journal of Food Measurement and Characterization 12:1449-1459.

  233. Ning, T., S. Zhou, F. Chang, H. Shen, Z. Li, and W. Liu. 2019. Interaction of vegetation, climate and topography on evapotranspiration modelling at different time scales within the Budyko framework. Agricultural and Forest Meteorology 275:59-68.

  234. Nogales, S., J. Calderón, T. M. Lupi, M. C. Bressan, J. V. Delgado, and M. E. Camacho. 2017. A comparison of the growth performance between cattle reared in conventional systems and feral conditions. Livestock Science 206:154-160.

  235. Nowaczewski, S., T. Szablewski, R. Cegielska-Radziejewska, K. Stuper, M. Rudzinska, G. Lésnierowski, H. Kontecka, and K. Zulc. 2013. Effect of housing system and eggshell colour on biochemical and microbiological characteristics of pheasant eggs. Archiv fur Geflugelkunde 77:226-233.

  236. Nys, Y. 1986. Relationships between age, shell quality and individual rate and duration of shell formation in domestic hens. British Poultry Science 27:253-259.

  237. Ocaña, J., F. Morales, M. Morilla, A. Liñán, A. Cabello, and J. M. León. 2008. Aproximación al patrón racial de la gallina sureña. Feagas 1:38-41.

  238. Odabaşi, A., R. Miles, M. Balaban, and K. Portier. 2007. Changes in brown eggshell color as the hen ages. Poultry Science 86:356-363.

  239. Olawumi, S., and B. Christiana. 2017. Phenotypic Correlations between External and Internal Egg Quality Traits of Coturnix Quails Reared under Intensive Housing System. Journal of Applied Life Sciences International 12:1-6.

  240. Olawumi, S., and J. Ogunlade. 2008. Phenotypic correlations between some external and internal egg quality traits in the exotic Isa Brown layer breeders. Asian Journal of Poultry Science 2:30-35.

  241. Olugbemi, T., A. Sule, M. Orunmuyi, O. Daudu, and O. Olusola. 2013. Chemical analysis and consumer preference of selected poultry egg types in Zaria, Nigeria. Nigerian Journal of Animal Science 15:199-205.

  242. Orłowski, G., J. Siekiera, J. Karg, M. Tobolka, A. Wuczyński, I. Kaługa, A. Siekiera, R. Cyga-Döhner, and E. Dudzik. 2019. Calcium and metals are not evenly distributed in avian eggshells over their longitudinal section. The Auk. 136:1-14.

  243. Orozco, F. 1987. Raza Andaluza o Utrerana. Selecciones Avícolas 29:50-57.

  244. Orozco, F. 1989. Razas de Gallinas Españolas. S. A. Mundi-Prensa Libros: Madrid, Spain.

  245. Osei-Amponsah, R., B. Kayang, A. Naazie, and I. M. Arthur. 2014. Evaluation of Models to Describe Temporal Growth in Local Chickens of Ghana. Iranian Journal of Applied Animal Science 4:855-861.

  246. Otecko, N. O., I. Ogali, D. H. Mauki, S. Ogada, G. K. Moraa, J. Lichoti, B. Agwanda, M.-S. Peng, S. C. Ommeh, and Y.-P. Zhang. 2019. Phenotypic and morphometric differentiation of indigenous chickens from Kenya and other tropical countries augments perspectives for genetic resource improvement and conservation. Poultry Science 98:2747-2755.

  247. Otwinowska-Mindur, A., M. Gumułka, and J. Kania-Gierdziewicz. 2016. Mathematical models for egg production in broiler breeder hens. Annals of Animal Science 16:1185-1198.

  248. Palacios, E.Y., L. Álvarez, and J. Muñoz. 2016. Genetic diversity of Creole hens of the Colombian southwest. Archivos de Zootecnia 65:73-78.

  249. Pan, A., Q. Sun, A. M. Bernstein, M. B. Schulze, J. E. Manson, M. J. Stampfer, W. C. Willett, and F. B. Hu. 2012. Red meat consumption and mortality: results from 2 prospective cohort studies. Archives of Internal Medicine 172:555-563.

  250. Pan, Y., and R. T. Jackson. 2008. Ethnic difference in the relationship between acute inflammation and serum ferritin in US adult males. Epidemiology and Infection 136:421-431.

  251. Pasternak, H., and B. A. Shalev. 1994. The effect of a feature of regression disturbance on the efficiency of fitting growth curves. Growth, Development and Aging 58:33-39.

  252. Patbandha, T., D. Garg, D. Vaghamashi, S. Marandi, K. Ravikala, S. Patil, and S. Dash. 2018. Prediction of Market Weight in Caribro-Dhanraja Broilers with Different Plumage Colour Using Growth Traits. International Journal of Current Microbiology and Applied Sciences 7:2018.

  253. Peña-Villalobos, I., G. Piriz, V. Palma, and P. Sabat. 2017. Energetic Effects of Pre-hatch Albumen Removal on Embryonic Development and Early Ontogeny in Gallus gallus. Frontiers in Physiology 7:690.

  254. Pieruccini-Faria, F., S. E. Black, M. Masellis, E. E. Smith, Q. J. Almeida, K. Z. H. Li, L. Bherer, R. Camicioli, and M. Montero-Odasso. 2021. Gait variability across neurodegenerative and cognitive disorders: Results from the Canadian Consortium of Neurodegeneration in Aging (CCNA) and the Gait and Brain Study. Alzheimer's & Dementia 2021:1-12.

  255. Pizarro Inostroza, M. G., F. J. Navas González, V. Landi, J. M. León Jurado, J. V. Delgado Bermejo, J. Fernández Álvarez, and Martínez Martínez, M. A. 2020. Software-Automatized Individual Lactation Model Fitting, Peak and Persistence and Bayesian Criteria Comparison for Milk Yield Genetic Studies in Murciano-Granadina Goats. Mathematics 8:1505.

  256. Podkowa, P., and A. Surmacki. 2017. The importance of illumination in nest site choice and nest characteristics of cavity nesting birds. Scientific Reports 7:1-9.

  257. Poggenpoel, D. G., G. F. Ferreira, J. P. Hayes, and J. J. du Preez. 1996. Response to long‐term selection for egg production in laying hens. British Poultry Science 37:743-756.

  258. Polesel, J., D. Serraino, E. Negri, L. Barzan, E. Vaccher, M. Montella, A. Zucchetto, W. Garavello, S. Franceschi, and C. La Vecchia. 2013. Consumption of fruit, vegetables, and other food groups and the risk of nasopharyngeal carcinoma. Cancer Causes & Control 24:1157-1165.

  259. Popiela-Pleban, E., B. Króliczewska, W. Zawadzki, S. Opalinski, and T. Skiba. 2013. Effect of extruded amaranth grains on performance, egg traits, fatty acids composition, and selected blood characteristics of laying hens. Livestock Science 155:308-315.

  260. Poulsen, J., and A. French. 2008. Discriminant function analysis. San Francisco State University: San Francisco, CA, USA.

  261. Qian, F., A. A. Korat, V. Malik, and F. B. Hu. 2016. Metabolic effects of monounsaturated fatty acid-enriched diets compared with carbohydrate or polyunsaturated fatty acid-enriched diets in patients with type 2 diabetes: a systematic review and meta- analysis of randomized controlled trials. Diabetes Care 39:1448-1457.

  262. Rahimzadeh, R., M. Rokouei, H. Faraji-Arough, A. Maghsoudi, and B. Keshtegar 2017. Short-term egg production curve fitting using nonlinear models in Japanese quail. Animal Production 19:299-310.

  263. Ramayah, T., N. H. Ahmad, H. A. Halim, S. R. M. Zainal, and M. C. Lo. 2010. Discriminant analysis: An illustrated example. African Journal of Business Management 4:1654-1667.

  264. Rath, P. K., P. K. Mishra, B. K. Mallick, and N. C. Behura. 2015. Evaluation of different egg quality traits and interpretation of their mode of inheritance in White Leghorns. Veterinary World 8:449.

  265. Réhault-Godbert, S., N. Guyot, and Y. Nys. 2019. The golden egg: nutritional value, bioactivities, and emerging benefits for human health. Nutrients 11:684.

  266. Renden, J. A., G. R. McDaniel, and J. A. McGuire. 1984. Egg Characteristics and Production Efficiency of Dwarf (dw) White Leghorn Hens Divergently Selected for Body Weight. Poultry Science 63:214-221.

  267. Richardson, J. T. 2011. Eta squared and partial eta squared as measures of effect size in educational research. Educational Research Review 6:135-147.

  268. Rivero, C. J., C. López, M. Fernández, D. Rois, J. R. Justo, A. S., and L. J. 2009. Determination of the annual lay in a ex situ population of Galliña de Mos. Archivos de Zootecnia 58:525-528.

  269. Rizzi, C. 2020. Yield performance, laying behaviour traits and egg quality of purebred and hybrid hens reared under outdoor conditions. Animals 10:584.

  270. Rizzi, C. 2021. Albumen Quality of Fresh and Stored Table Eggs: Hen Genotype as a Further Chance for Consumer Choice. Animals 11:135.

  271. Rizzi, C., and A. Marangon. 2012. Quality of organic eggs of hybrid and Italian breed hens. Poultry Science 91:2330-2340.

  272. Rizzi, C., and G. Chiericato. 2010. Chemical composition of meat and egg yolk of hybrid and Italian breed hens reared using an organic production system. Poultry Science 89:1239-1251.

  273. Rizzi, C., B. Contiero, and M. Cassandro. 2013. Growth patterns of Italian local chicken populations. Poultry science 92:2226-2235.

  274. Roberts, J. R. 2004. Factors affecting egg internal quality and egg shell quality in laying hens. The Journal of Poultry Science 41:161-177.

  275. Rodriguez-Navarro, A. B., K. F. Gaines, C. S. Romanek, and G. R. Masson. 2002. Mineralization of Clapper Rail Eggshell from a Contaminated Salt Marsh System. Archives of Environmental Contamination and Toxicology 43:449-460.

  276. Rogerson, P. A. 2001. Data reduction: factor analysis and cluster analysis. Pages 192-197Sage: London. SAGE Publishing: NY, USA: 192-197.

  277. Rondoni, A., D. Asioli, and E. Millan. 2020. Consumer behaviour, perceptions, and preferences towards eggs: A review of the literature and discussion of industry implications. Trends in Food Science & Technology 106:391-401.

  278. Roy, P., D. Nei, T. Orikasa, Q. Xu, H. Okadome, N. Nakamura, and T. Shiina. 2009. A review of life cycle assessment (LCA) on some food products. Journal of Food Engineering 90:1-10.

  279. Rubio, C., S. Paz, I. Ojeda, A. Gutiérrez, D. González-Weller, A. Hardisson, A., and C. Revert. 2017. Dietary intake of metals from fresh cage-reared hens’ eggs in Tenerife, Canary Islands. Journal of Food Quality 2017:5972153.

  280. Saatci, M., T. Kirmizibayrak, A. R. Aksoy, and M. Tilki. 2005. Egg weight, shape index and hatching weight and interrelationships among these traits in native Turkish geese with different coloured feathers. Turkish Journal of Veterinary and Animal Sciences 29:353-357.

  281. Samiullah, S., A. S. Omar, J. Roberts, and K. Chousalkar. 2016. Effect of production system and flock age on eggshell and egg internal quality measurements. Poultry Science 96:246-258.

  282. Samiullah, S., J. R. Roberts, and K. Chousalkar. 2015. Eggshell color in brown-egg laying hens - a review. Poultry Science 94:2566-2575.

  283. Sánchez, L., B. Sánchez, and B. Fernández. 2000. Preservation program of the Mos chicken breed in Galicia. Archivos de Zootecnia. 49:77-80.

  284. SAS. 2014. Sas/stat r 13.2 users guide. SAS Institute Inc.: Cary, North Carolina, USA.

  285. Savegnago, R., V. Cruz, S. Ramos, S. Caetano, G. Schmidt, M. Ledur, L. El Faro, D. P. Munari. 2012. Egg production curve fitting using nonlinear models for selected and nonselected lines of White Leghorn hens. Poultry Science 91:2977-2987.

  286. Secci, G., F. Bovera, G. Parisi, and G. Moniello. 2020. Quality of Eggs and Albumen Technological Properties as Affected by Hermetia Illucens Larvae Meal in Hens’ Diet and Hen Age. Animals 10:81.

  287. Seidler, E. 2003. Egg marketing. A guide for the production and sale of eggs. FAO Agricultural Services Bulletin (FAO): Rome, Italy.

  288. Shen, T. F., W. L. Chen. 2003. The role of magnesium and calcium in eggshell formation in tsaiya ducks and leghorn hens. Asian-Australasian Journal of Animal Science 16:290-296.

  289. Silversides, F. G., and T. A. Scott. 2001. Effect of Storage and Layer Age on Quality of Eggs From Two Lines of Hens1. Poultry Science 80:1240-1245.

  290. Sirri, F., M. Zampiga, A. Berardinelli, and A. Meluzzi. 2018. Variability and interaction of some egg physical and eggshell quality attributes during the entire laying hen cycle. Poultry Science 97:1818-1823.

  291. Sirri, F., M. Zampiga, F. Soglia, A. Meluzzi, C. Cavani, and M. Petracci. 2018. Quality characterization of eggs from Romagnola hens, an Italian local breed. Poultry Science 97:4131-4136.

  292. Sirri, F., N. Iaffaldano, G. Minelli, A. Meluzzi, M. P. Rosato, and A. Franchini. 2007. Comparative Pigmentation Efficiency of High Dietary Levels of Apo-Ester and Marigold Extract on Quality Traits of Whole Liquid Egg of Two Strains of Laying Hens. The Journal of Applied Poultry Research 16:429-437.

  293. Skřivan, M., and M. Englmaierová. 2014. The deposition of carotenoids and α-tocopherol in hen eggs produced under a combination of sequential feeding and grazing. Animal Feed Science and Technology 190:79-86.

  294. Sokołowicz, Z., J. Krawczyk, and M. Dykiel. 2018. The effect of the type of alternative housing system, genotype and age of laying hens on egg quality. Annals of Animal Science 18:541.

  295. Song, K. T., S. H. Choi, and H. R. Oh. 2000. A comparison of egg quality of pheasant, chukar, quail and guinea fowl. Asian-Australasian Journal of Animal Sciences 13:986-990.

  296. Speake, B. K., P. F. Surai, R. C. Noble, J. V. Beer, and N. A. R. Wood. 1999. Differences in egg lipid and antioxidant composition between wild and captive pheasants and geese. Comparative Biochemistry and Physiology 124:101-107.

  297. Sreenivas, D., M. G. Prakash, M. Mahender, and R. N. Chatterjee. 2013. Genetic analysis of egg quality traits in White Leghorn chicken. Veterinary World 6:236-266.

  298. Sreenivas, D., M. Prakash, M. Mahender, and R. Chatterjee. 2018. Molecular genotyping of some poultry populations using microsatellite markers. Indian Journal of Poultry Science 53:251-255.

  299. Stadelman, W. J. 1977 Quality identification of shell eggs in egg science and technology. AVI Publishing Ccompany Inc. Westport, CT, USA.

  300. Stadelman, W. J., D. Newkirk, and L. Newly. Egg Science and Technology, 4th ed. CRC Press: Boca Ratón, FL, USA 592.

  301. Stefanikova, Z., L. Sevcikova, J. Jurkovicova, L. Sobotova, and L. Aghova. 2006. Positive and negative trends in university students' food intake. Bratislavske Lekarske Listy 107:217.

  302. Stevens, J. P. 2012. Applied multivariate statistics for the social sciences. Routledge: NY, USA.

  303. Stone, H., J. Sidel, S. Oliver, A. Woolsey, and R. C. Singleton. 2008. Sensory evaluation by quantitative descriptive analysis. Descriptive Sensory Analysis in Practice 28:23-34.

  304. Sun, C. J., Z. Y. Duan, L. J. Qu, J. X. Zheng, N. Yang, and G. Y. Xu. 2016. Expression analysis for candidate genes associated with eggshell mechanical property. Journal of Integrative Agriculture 15:397-402.

  305. Sun, C., J. Liu, N. Yang, and G. Xu. 2019. Egg quality and egg albumen property of domestic chicken, duck, goose, turkey, quail, and pigeon. Poultry Science 98:4516-4521.

  306. Tabachnick, B., and L. Fidell. 1989. Using Multivariate Statistics. Harper Collins Publishers: New York, USA.

  307. Tai, F., and W. Pan. 2007. Incorporating prior knowledge of gene functional groups into regularized discriminant analysis of microarray data. Bioinformatics 23:3170-3177.

  308. Tallentire, C. W., I. Leinonen, and I. Kyriazakis. 2018. Publisher Correction: Artificial selection for improved energy efficiency is reaching its limits in broiler chickens. Scientific Reports 8:4785.

  309. Tang, S., S. Chin, K. Ramasamy, W. Saad, S. T. Yong, H. Wong, and Y. Ho. 2015. Chemical compositions of egg yolks and egg quality of laying hens fed prebiotic, probiotic, and synbiotic diets. Journal of Food Science 80:1686-1695.

  310. Tariq, M., F. Iqbal, E. Eyduran, M. Bajwa, Z. Huma, and A. Waheed. 2013. Comparison of Non-Linear Functions to Describe the Growth in Mengali Sheep Breed of Balochistan. Pakistan Journal of Zoology 45:661-665.

  311. Tätte, K., A. P. Møller, and R. Mänd. 2018. Towards an integrated view of escape decisions in birds: relation between flight initiation distance and distance fled. Animal Behaviour 136:75-86.

  312. Taylor, P.S., P. H. Hemsworth, P. J. Groves, S. G. Gebhardt-Henrich, and J. L. Rault. 2017. Ranging behaviour of commercial free-range broiler chickens 1: factors related to flock variability. Animals 7:54.

  313. Tharrington, J., P. Curtis, F. Jones, and K. Anderson. 1999. Comparison of physical quality and composition of eggs from historic strains of single comb White Leghorn chickens. Poultry Science 78:591-594.

  314. The MathWorks. 2015. MATLAB, release R2015 ed. The MathWork, Inc.: Natick, MA, USA.

  315. Thompson, B. A. 1991. A primer on the logic and use of canonical correlation analysis. Measurement and Evaluation in Counseling and Development. Educational and Psychological Measurement 24:80-94.

  316. Tienhaara, A., H. Ahtiainen, and E. Pouta. 2013. Consumers as Conservers - Could Consumers’ Interest in a Specialty Product Help to Preserve Endangered Finncattle? Agroecology and Sustainable Food Systems 37:1017-1039.

  317. Toalombo Vargas, P. A., F. J. Navas González, V. Landi, J. M. León Jurado, and J. V. Delgado Bermejo. 2020. Sexual dimorphism and breed characterization of Creole hens through biometric canonical discriminant analysis across Ecuadorian agroecological areas. Animals 10:32.

  318. Toalombo, P. A., F. J. Navas-González, V. C. Andrade-Yucailla, J. V. Trujillo, V. Martinez, and J. V. Delgado. 2019. Productive and organoleptic characterization of eggs from field hens in the sierra region of Ecuador. Archivos de Zootecnia 68:412-415.

  319. Toalombo, P., C. Camacho, R. Buenaño, S. Jiménez, F. Navas-González, V. Landi, and J. Delgado. 2019. Efecto socioeconómico sobre las características fanerópticas de gallinas autóctonas de Ecuador. Archivos de Zootecnia 68:416-421.

  320. Toften, K., and T. Hammervoll. 2013. Niche marketing research: status and challenges. Marketing Intelligence & Planning 31:272-285.

  321. Topal, M., and Ş. C. Bolukbasi. 2008. Comparison of Nonlinear Growth Curve Models in Broiler Chickens. Journal of Applied Animal Research. 34:149-152.

  322. Torres, A., P. C. Muth, J. Capote, C. Rodríguez, M. Fresno, and A. Valle Zárate. 2019. Suitability of dual-purpose cockerels of 3 different genetic origins for fattening under free-range conditions. Poultry Science 98:6564-6571.

  323. Toussant, M. J., and J. D. Latshaw. 1999. Ovomucin content and composition in chicken eggs with different interior quality. Journal of the Science of Food and Agriculture 79:1666-1670.

  324. Tuiskula‐Haavisto, M., M. Honkatukia, I. Dunn, M. Bain, D.-J. De Koning, R. Preisinger, M. Schmutz, J. Arango, D. Fischer, and J. Vilkki. 2018. Validated quantitative trait loci for eggshell quality in experimental and commercial laying hens. Animal Genetics 49:329-333.

  325. Tůmová, E., L. Uhlířová, R. Tůma, D. Chodová, and L. Máchal. 2017. Age related changes in laying pattern and egg weight of different laying hen genotypes. Animal Reproduction Science 183:21-26.

  326. Tyasi, T., K. Makgowo, K. Mokoena, L. Rashijane, M. Mathapo, L. Danguru, K. Molabe, P. Bopape, N. Mathye, and D. Maluleke. 2020. Classification and regression tree (CRT) analysis to predict body weight of Potchefstroom koekoek laying hens. Advances in Animal and Veterinary Sciences 8:354-359.

  327. Ukwu, H. O., V. M. O. Okoro, and R. Nosike. 2014. Statistical modelling of body weight and linear body measurements in Nigerian indigenous chicken. IOSR Journal of Agriculture and Veterinary Science 7:27-30.

  328. Ukwu, H., C. Ezihe, S. Asaa, and M. Anyogo. 2017. Effect of egg weight on external and internal egg quality traits of Isa Brown egg layer chickens in Nigeria. Journal of Animal Science and Veterinary Medicine 2:126-132.

  329. Ureña, D., D. Colombo, M. López, and C. Ruiz. 2021. Demanda de productos animales sostenibles: leche de cabra de pastoreo. Archivos de Zootecnia 70:60-70.

  330. Usayran, N., M. T. Farran, H. H. Awadallah, I. R. Al-Hawi, R. J. Asmar, and V. M. Ashkarian. 2001. Effects of Added Dietary Fat and Phosphorus on the Performance and Egg Quality of Laying Hens Subjected to a Constant High Environmental Temperature. Poultry Science 80:1695-1701.

  331. Uusitalo, L. 1990. Consumer preferences for environmental quality and other social goals. Journal of Consumer Policy 13:231-251.

  332. Vaarst, M., S. Steenfeldt, and K. Horsted. 2015. Sustainable development perspectives of poultry production. World’s Poultry Science 71:609-620.

  333. Van der Burg, E., and G. Dijksterhuis. 1996. Generalised canonical analysis of individual sensory profiles and instrumental data. In Multivariate analysis of data in sensory science. Elsevier Science: Amsterdam, The Nederlands 221-258.

  334. Van der Burg, E., J. De Leeuw, and G. Dijksterhuis. 1994. OVERALS: Nonlinear canonical correlation with k sets of variables. Computational Statistics & Data Analysis 18:141-163.

  335. Van Dyke J. U., M. L. Beck, B. P. Jackson, and W. A. Hopkins. 2013. Interspecific differences in egg production affect egg trace element concentrations after a coal fly ash spill. Environmental Science & Technology 47:13763-13771.

  336. Van Vleck, LD. 1993. Selection index and introduction to mixed model methods for genetic improvement of animals: the green book. CRC Press: Boca Ratón, FL, USA.

  337. Vega-Plá, J., A. Martínez, J. V. Delgado, A. Arando, A. Canales, N. García, M. Gómez-Carpio, A. González, C. González-Felgueroso, V. Landi, et al. Genetic characterization of Spanish autochthonous chicken breeds using microsatellites. Poster session presented at 37th International Society for Animal Genetics Conference; July 7-12, Lleida, Spain.

  338. Verbeke, W. 2009. Stakeholder, citizen and consumer interests in farm animal welfare. Animal Welfare 18:325-333.

  339. Villalba, D., A. Francesch, A. Pons, J. Bustamante, M. Espadas, V. Santonja, and D. Cubiló. 2007. Growth and lay results obtained from a Menorca breed population. Archivos de Zootecnia 56:373-804.

  340. Wan, Y., S. Jin, C. Ma, Z. Wang, Q. Fang, and R. Jiang. 2019. Effect of strain and age on the thick-to-thin albumen ratio and egg composition traits in layer hens. Animal Production Science 59:416-419.

  341. Wang, Y., J. Bennewitz, and R. Wellmann. 2017. Novel optimum contribution selection methods accounting for conflicting objectives in breeding programs for livestock breeds with historical migration. Genetics Selection Evolution 49:1-12.

  342. Washburn, K. W. 1979. Genetic Variation in the Chemical Composition of the Egg1. Poultry Science 58:529-535.

  343. Wideman, N., C. A. O'Bryan, and P. G. Crandall. 2016. Factors affecting poultry meat colour and consumer preferences - A review. World's Poultry Science Journal 72:353-366.

  344. Williams, A. A., and G. M. Arnold. 1985. A comparison of the aromas of six coffees characterised by conventional profiling, free-choice profiling and similarity scaling methods. Journal of the Science of Food and Agriculture 36:204-214.

  345. Wilson, P.B. 2017. Recent advances in avian egg science: a review. Poultry Science 96:3747-3754.

  346. Wisely, C. E., J. A. Sayed, H. Tamez, C. Zelinka, M. H. Abdel-Rahman, A. J. Fischer, and C. M. Cebulla. 2017. The chick eye in vision research: An excellent model for the study of ocular disease. Progress in Retinal and Eye Research 61:72-97.

  347. Wood, P. 1967. Algebraic model of the lactation curve in cattle. Nature 216 5111: 164-165.

  348. Xu, H., H. Zeng, D. Zhang, X. Jia, C. Luo, M. Fang, Q. Nie, and X. Zhang, X. 2011. Polymorphisms associated with egg number at 300 days of age in chickens. Genetics and Molecular Research 10:2279-2289.

  349. Yaemkong, S., and T. N. Ngoc. 2019. Diversity of phenotypic characteristics of White Tailed-Yellow Chicken populations reared under free range system in Phitsanulok Province, Thailand. Biodiversitas 1:20.

  350. Yakubu, A., and A. Salako. 2009. Path coefficient analysis of body weight and morphological traits of Nigerian indigenous chickens. Egyptian Poultry Science 29:837-850.

  351. Yang, H., Z. Wang, and J. Lu. 2009. Study on the relationship between eggshell colors and egg quality as well as shell ultrastructure in Yangzhou chicken. African Journal of Biotechnology 8:2898-2902.

  352. Yang, N., C. Wu, and I. McMillan. 1989. New mathematical model of poultry egg production. Poultry Science 68:476-481.

  353. Yang, Y., D. Mekki, S. Liv, L.Y. Wang, J. H. Yu, and J. Y. Wang. 2006. Analysis of Fitting Growth Models in Jinghai Mixed-Sex Yellow Chicken. International Journal of Poultry Science. 5:517-521.

  354. Yimenu, S. M., J. Kim, and B. Kim. 2017. Prediction of egg freshness during storage using electronic nose. Poultry Science 96:3733-3746.

  355. Yin, J. D., X. G. Shang, D. F. Li, F. L. Wang, Y. F. Guan, and Z. Y. Wang. 2008. Effects of dietary conjugated linoleic acid on the fatty acid profile and cholesterol content of egg yolks from different breeds of Layers1. Poultry Science 87:284-290.

  356. Zanon, A., V. Beretti, P. Superchi, E. Zambini, and A. Sabbioni. 2006. Physico-chemical characteristics of eggs from two Italian autochthonous chicken breeds: Modenese and Romagnolo. World's Poultry Science Journal 62:203.

  357. Zhang, Q., J. Hu, and Z. Bai. 2020. Modified Pillai’s trace statistics for two high-dimensional sample covariance matrices. Journal of Statistical Planning and Inference 207:255-275.

  358. Zheng, Y., L. Zhao, Y. Wei, Q. Ma, C. Ji, and J. Zhang. 2020. Effects of main cereal type and feed form on production performance, egg quality and egg sanitary indices of laying hens. British Poultry Science 61:164-168. 359. Zita, L., E. Tumová, and L. Štolc. 2009. Effects of Genotype, Age and Their Interaction on Egg Quality in Brown-Egg Laying Hens. Acta Veterinaria Brno 78:85-91.

  360. Zofia, S., K. Józefa, and D. Magdalena. 2018. The effect of the type of alternative housing system, genotype and age of laying hens on egg quality. Annals of Animal Science 18:541-556.