Sexaje in ovo con Imágenes Hiperespectrales (HSI): Un método no destructivo y no invasivo
DOI:
https://doi.org/10.17268/agroind.sci.2023.03.10Palabras clave:
Avicultura, sexado in ovo, imágenes hiperespectrales, no invasivo, espectroscopíaResumen
La avicultura a nivel mundial presenta un gran desarrollo; sin embargo, una de las grandes limitaciones es la determinación del sexo del embrión in ovo, debido a que en las granjas las aves son criadas con dos propósitos, producción de huevos o producción de carne, por lo que existe una preferencia de sexos. En la línea de producción de huevo comercial se prefieren a las hembras y los machos recién nacidos se descartan, siendo sacrificados millones de pollitos a nivel mundial, generando grandes pérdidas económicas; además representa un serio problema ético y de bienestar animal, es por ello países como Francia y Alemania han decretado nuevas normativas que regulen y prohíban el sacrifico de pollitos machos. Se han propuesto múltiples técnicas ópticas y no ópticas para el sexaje in ovo, pero aún no se ha logrado desarrollar a nivel industrial y comercial. De todas las técnicas disponibles, las imágenes hiperespectrales HSI se muestra como una técnica no invasiva y no destructiva viable para el sexaje in ovo, debido a que proporciona amplia información espectral de un huevo. En este contexto, se discuten los avances y enfoques de HSI respecto a su uso potencial en el sexaje in ovo. Las HSI han demostrado precisión considerable en el sexaje, sin embargo, presenta limitaciones como la complejidad en el procesamiento de datos y el tiempo de desarrollo embrionario.
Citas
Aleynikov, A., & Osipenko, I. (2023). Information technology for culling poultry eggs before incubation based on gender. E3S Web of Conferences, 390, 03005. https://doi.org/10.1051/e3sconf/202339003005
Alin, K., Fujitani, S., Kashimori, A., Suzuki, T., Ogawa, Y., & Kondo, N. (2019). Non-invasive broiler chick embryo sexing based on opacity value of incubated eggs. Computers and Electronics in Agriculture, 158, 30–35. https://doi.org/10.1016/j.compag.2019.01.029
Amigo, J. M., Babamoradi, H., % Elcoroaristizabal, S. (2015). Hyperspectral image analysis. A tutorial. Analytica Chimica Acta, 896, 34–51. https://doi.org/10.1016/j.aca.2015.09.030
Arce, L., Gallegos, J., Garrido-Delgado, R., Medina, L. M., Sielemann, S., & Wortelmann, T. (2015). Ion Mobility Spectrometry a Versatile Analytical Tool for Metabolomics Applications in Food Science. Current Metabolomics, 2(4), 264-271. https://doi.org/10.2174/2213235X03999150212102944
Aslam, M. A., Hulst, M., Hoving-Bolink, R. A. H., Smits, M. A., de Vries, B., Weites, I., Groothuis, T. G. G., & Woelders, H. (2013). Yolk concentrations of hormones and glucose and egg weight and egg dimensions in unincubated chicken eggs, in relation to egg sex and hen body weight. General and Comparative Endocrinology, 187, 15–22. https://doi.org/10.1016/j.ygcen.2013.02.045
Bayer, E., von Meyer-Höfer, M., & Kühl, S. (2023). Hotspot analysis for organic laying hen husbandry—identification of sustainability problems as potential risk points to lose consumers’ trust. Organic Agriculture, 13(2), 261–292. https://doi.org/10.1007/s13165-023-00426-5
Bozkaya, F., Gürler, Ş., Yertürk, M., & Aydİlek, N. (2013). Isolation of DNA from embryo and chorio-allantoic membranes and sexing by PCR in Japanese quail. British Poultry Science, 54(1), 106–111. https://doi.org/10.1080/00071668.2012.760035
Bruijnis, M. R. N., Blok, V., Stassen, E. N., & Gremmen, H. G. J. (2015). Moral “Lock-In” in Responsible Innovation: The Ethical and Social Aspects of Killing Day-Old Chicks and Its Alternatives. Journal of Agricultural and Environmental Ethics, 28(5), 939–960. https://doi.org/10.1007/s10806-015-9566-7
Bundestag. (2021). Entwurf eines gesetzes zur änderung des tierschutzgesetzes – verbot des kükentötens (Alemán). https://www.bmel.de/SharedDocs/Downloads/DE/Glaeserne-Gesetze/Kabinettfassung/aenderung-tierschutzgesetz-kueken.html
Burger, J., & Geladi, P. (2005). Hyperspectral NIR image regression part I: calibration and correction. Journal of Chemometrics, 19(5–7), 355–363. https://doi.org/10.1002/cem.938
Burger, J., & Gowen, A. (2011). Data handling in hyperspectral image analysis. Chemometrics and Intelligent Laboratory Systems, 108(1), 13–22. https://doi.org/10.1016/j.chemolab.2011.04.001
Busse, M., Kernecker, M. L., Zscheischler, J., Zoll, F., & Siebert, R. (2019). Ethical Concerns in Poultry Production: A German Consumer Survey About Dual Purpose Chickens. Journal of Agricultural and Environmental Ethics, 32(5–6), 905–925. https://doi.org/10.1007/s10806-019-09806-y
Calin, M. A., Piticescu, R. R., & Parasca, S. V. (2023). Comparative analysis of denoising techniques in burn depth discrimination from burn hyperspectral images. Journal of Biophotonics, 16(7). https://doi.org/10.1002/jbio.202200374
Calle-Velásquez, C. A., Estrada Pareja, M. M., & Restrepo-Betancur, L. F. (2017). Evolución de la relación entre el consumo de huevo de gallina en el mundo (Gallus gallus domesticus) y los principales alimentos entre 1961 y 2009. Perspectivas Nutrición Humana, 18(1), 37–48. https://doi.org/10.17533/udea.penh.v18n1a04
Carrasco, O., Gomez, R. B., Chainani, A., & Roper, W. E. (2003). Hyperspectral imaging applied to medical diagnoses and food safety (N. L. Faust & W. E. Roper, Eds.; p. 215). https://doi.org/10.1117/12.502589
Clinton, M., Nandi, S., Zhao, D., Olson, S., Peterson, P., Burdon, T., & McBride, D. (2016). Real-Time Sexing of Chicken Embryos and Compatibility with in ovo Protocols. Sexual Development, 10(4), 210–216. https://doi.org/10.1159/000448502
Corion, M., Keresztes, J., De Ketelaere, B., & Saeys, W. (2022). In ovo sexing of eggs from brown breeds with a gender-specific color using visible-near-infrared spectroscopy: effect of incubation day and measurement configuration. Poultry Science, 101(5). https://doi.org/10.1016/J.PSJ.2022.101782
Corion, M., Santos, S., De Ketelaere, B., Spasic, D., Hertog, M., & Lammertyn, J. (2023). Trends in in ovo sexing technologies: insights and interpretation from papers and patents. Journal of Animal Science and Biotechnology, 14(1), 102. https://doi.org/10.1186/s40104-023-00898-1
Costanzo, A., Panseri, S., Giorgi, A., Romano, A., Caprioli, M., & Saino, N. (2016). The Odour of Sex: Sex-Related Differences in Volatile Compound Composition among Barn Swallow Eggs Carrying Embryos of Either Sex. PLOS ONE, 11(11), e0165055. https://doi.org/10.1371/journal.pone.0165055
Cozzolino, D., Williams, P. J., & Hoffman, L. C. (2023). An overview of pre-processing methods available for hyperspectral imaging applications. Microchemical Journal, 193, 109129. https://doi.org/10.1016/j.microc.2023.109129
Doran, T. J., Morris, K. R., Wise, T. G., O’Neil, T. E., Cooper, C. A., Jenkins, K. A., & Tizard, M. L. v. (2018). Sex selection in layer chickens. Animal Production Science, 58(3), 476. https://doi.org/10.1071/AN16785
Ellegren, H. (2009). Sex Determination: Two Copies for One Cock. Current Biology, 19(19), R909–R910. https://doi.org/10.1016/j.cub.2009.09.001
Ferrari, V., Calvini, R., Boom, B., Menozzi, C., Rangarajan, A. K., Maistrello, L., Offermans, P., & Ulrici, A. (2023). Evaluation of the potential of near infrared hyperspectral imaging for monitoring the invasive brown marmorated stink bug. Chemometrics and Intelligent Laboratory Systems, 234, 104751. https://doi.org/10.1016/j.chemolab.2023.104751
Fragoso, A. A. H., Capilé, K., Taconeli, C. A., de Almeida, G. C., de Freitas, P. P., & Molento, C. F. M. (2023). Animal Welfare Science: Why and for Whom? Animals, 13(11), 1833. https://doi.org/10.3390/ani13111833
Galli, R., Preusse, G., Schnabel, C., Bartels, T., Cramer, K., Krautwald-Junghanns, M.-E., Koch, E., & Steiner, G. (2018). Sexing of chicken eggs by fluorescence and Raman spectroscopy through the shell membrane. PLOS ONE, 13(2), e0192554. https://doi.org/10.1371/journal.pone.0192554
Galli, R., Preusse, G., Uckermann, O., Bartels, T., Krautwald-Junghanns, M.-E., Koch, E., & Steiner, G. (2017). In ovo sexing of chicken eggs by fluorescence spectroscopy. Analytical and Bioanalytical Chemistry, 409(5), 1185–1194. https://doi.org/10.1007/s00216-016-0116-6
Gautron, J., Réhault-Godbert, S., van de Braak, T. G. H., & Dunn, I. C. (2021). Review: What are the challenges facing the table egg industry in the next decades and what can be done to address them? Animal, 15. https://doi.org/10.1016/j.animal.2021.100282
Göhler, D., Fischer, B., & Meissner, S. (2017). In-ovo sexing of 14-day-old chicken embryos by pattern analysis in hyperspectral images (VIS/NIR spectra): A non-destructive method for layer lines with gender-specific down feather color. Poultry Science, 96(1), 1–4. https://doi.org/10.3382/PS/PEW282
Gremmen, B., Bruijnis, M. R. N., Blok, V., & Stassen, E. N. (2018). A Public Survey on Handling Male Chicks in the Dutch Egg Sector. Journal of Agricultural and Environmental Ethics, 31(1), 93–107. https://doi.org/10.1007/s10806-018-9712-0
Haas, E. N., Oliemans, E., & van Gerwen, M. A. A. M. (2021). The Need for an Alternative to Culling Day-Old Male Layer Chicks: A Survey on Awareness, Alternatives, and the Willingness to Pay for Alternatives in a Selected Population of Dutch Citizens. Frontiers in Veterinary Science, 8. https://doi.org/10.3389/fvets.2021.662197
He, L., Martins, P., Huguenin, J., Van, T.-N.-N., Manso, T., Galindo, T., Gregoire, F., Catherinot, L., Molina, F., & Espeut, J. (2019). Simple, sensitive and robust chicken specific sexing assays, compliant with large scale analysis. PLOS ONE, 14(3), e0213033. https://doi.org/10.1371/journal.pone.0213033
Jia, N., Li, B., Zhu, J., Wang, H., Zhao, Y., & Zhao, W. (2023). A Review of Key Techniques for in Ovo Sexing of Chicken Eggs. Agriculture, 13(3), 677. https://doi.org/10.3390/agriculture13030677
Kaleta, E. F., & Redmann, T. (2008). Approaches to determine the sex prior to and after incubation of chicken eggs and of day-old chicks. World’s Poultry Science Journal, 64(3), 391–399. https://doi.org/10.1017/S0043933908000111
Kamruzzaman, M., & Sun, D.-W. (2016). Introduction to Hyperspectral Imaging Technology. In Computer Vision Technology for Food Quality Evaluation (pp. 111–139). Elsevier. https://doi.org/10.1016/B978-0-12-802232-0.00005-0
Kayadan, M., & Uzun, Y. (2023). High accuracy gender determination using the egg shape index. Scientific Reports, 13(1), 504. https://doi.org/10.1038/s41598-023-27772-4
Ketelaere, B., Bamelis, F., Kemps, B., Decuypere, E., & De Baerdemaeker, J. (2004). Non-destructive measurements of the egg quality. World’s Poultry Science Journal, 60(3), 289–302. https://doi.org/10.1079/WPS200417
Khan, M. J., Khan, H. S., Yousaf, A., Khurshid, K., & Abbas, A. (2018). Modern Trends in Hyperspectral Image Analysis: A Review. IEEE Access, 6, 14118–14129. https://doi.org/10.1109/ACCESS.2018.2812999
Khwatenge, C. N., & Nahashon, S. N. (2021). Recent Advances in the Application of CRISPR/Cas9 Gene Editing System in Poultry Species. Frontiers in Genetics, 12. https://doi.org/10.3389/fgene.2021.627714
Krautwald-Junghanns, M.-E., Cramer, K., Fischer, B., Förster, A., Galli, R., Kremer, F., Mapesa, E. U., Meissner, S., Preisinger, R., Preusse, G., Schnabel, C., Steiner, G., & Bartels, T. (2018). Current approaches to avoid the culling of day-old male chicks in the layer industry, with special reference to spectroscopic methods. Poultry Science, 97(3), 749–757. https://doi.org/10.3382/ps/pex389
Kuula, J., Pölönen, I., Puupponen, H.-H., Selander, T., Reinikainen, T., Kalenius, T., & Saari, H. (2012). Using VIS/NIR and IR spectral cameras for detecting and separating crime scene details (E. M. Carapezza, Ed.; pp. 83590P-83590P – 11). https://doi.org/10.1117/12.918555
Liang, H. (2012). Advances in multispectral and hyperspectral imaging for archaeology and art conservation. Applied Physics A: Materials Science and Processing, 106(2), 309–323. https://doi.org/10.1007/S00339-011-6689-1/METRICS
Lodhi, V., Chakravarty, D., & Mitra, P. (2019). Hyperspectral Imaging System: Development Aspects and Recent Trends. Sensing and Imaging, 20(1), 35. https://doi.org/10.1007/s11220-019-0257-8
Madrigal-Portilla, J., Salas-Durán, C., & Macaya-Quirós, S. (2023). Efecto de temperatura y tiempo de almacenamiento sobre la calidad del huevo de gallinas. Agronomía Mesoamericana, 51223. https://doi.org/10.15517/am.v34i2.51223
Masary, G., & Sun, D.W. (2010). Principles of Hyperspectral Imaging Technology. In Hyperspectral Imaging for Food Quality Analysis and Control (pp. 3–43). Elsevier. https://doi.org/10.1016/B978-0-12-374753-2.10001-2
Nageswara, R. B. D. (2015). Nuclear magnetic resonance. Resonance, 20(11), 969–985. https://doi.org/10.1007/s12045-015-0265-5
Nakaguchi, V. M., & Ahamed, T. (2022). Development of an Early Embryo Detection Methodology for Quail Eggs Using a Thermal Micro Camera and the YOLO Deep Learning Algorithm. Sensors, 22(15), 5820. https://doi.org/10.3390/s22155820
Organización de las Naciones Unidas para la Alimentación y la Agricultura FAOSTAT. (2021). Cultivos y productos de ganadería. https://www.fao.org/faostat/es/#data/QCL
Pan, L., Zhang, W., Yu, M., Sun, Y., Gu, X., Ma, L., Li, Z., Hu, P., & Tu, K. (2016). Gender determination of early chicken hatching eggs embryos by hyperspectral imaging. Transactions of the Chinese Society of Agricultural Engineering, 32(1), 181–186. https://doi.org/10.11975/j.issn.1002-6819.2016.01.025
Plaza, A., Benediktsson, J. A., Boardman, J. W., Brazile, J., Bruzzone, L., Camps-Valls, G., Chanussot, J., Fauvel, M., Gamba, P., Gualtieri, A., Marconcini, M., Tilton, J. C., & Trianni, G. (2009). Recent advances in techniques for hyperspectral image processing. Remote Sensing of Environment, 113, S110–S122. https://doi.org/10.1016/j.rse.2007.07.028
Preuße, G., Porstmann, V., Bartels, T., Schnabel, C., Galli, R., Koch, E., Oelschlägel, M., Uckermann, O., & Steiner, G. (2023). Highly sensitive and quick in ovo sexing of domestic chicken eggs by two-wavelength fluorescence spectroscopy. Analytical and Bioanalytical Chemistry, 415(4), 603–613. https://doi.org/10.1007/s00216-022-04446-0
Pu, H., Wei, Q., & Sun, D.-W. (2023). Recent advances in muscle food safety evaluation: Hyperspectral imaging analyses and applications. Critical Reviews in Food Science and Nutrition, 63(10), 1297–1313. https://doi.org/10.1080/10408398.2022.2121805
Qasimi, M. I., Mohibbi, H., Nagaoka, K., & Watanabe, G. (2018). Accumulation of steroid hormones in the eggshells of Japanese quail (Coturnix coturnix japonica). General and Comparative Endocrinology, 259, 161–164. https://doi.org/10.1016/j.ygcen.2017.11.020
Reithmayer, C., Mußhoff, O., & Danne, M. (2020). Alternatives to culling male chicks – the consumer perspective. British Food Journal, 122(3), 753-765. https://doi.org/10.1108/BFJ-05-2019-0356
Rutkowska, J., Dubiec, A., & Nakagawa, S. (2014). All eggs are made equal: meta-analysis of egg sexual size dimorphism in birds. Journal of Evolutionary Biology, 27(1), 153–160. https://doi.org/10.1111/jeb.12282
Rutt, R. L., & Jakobsen, J. (2022). The ‘brother layer problem’: Routine killing, biotechnology and the pursuit of ‘ethical sustainability’ in industrial poultry. Environment and Planning E: Nature and Space, 251484862211311. https://doi.org/10.1177/25148486221131195
Saha, D., & Manickavasagan, A. (2021). Machine learning techniques for analysis of hyperspectral images to determine quality of food products: A review. Current Research in Food Science, 4, 28–44. https://doi.org/10.1016/j.crfs.2021.01.002
Schwean-Lardner, K. (2017). The effects of hatchery practices on the welfare of poultry. In Advances in Poultry Welfare. https://doi.org/10.1016/B978-0-08-100915-4.00002-6
Siche, R., Vejarano, R., Aredo, V., Velasquez, L., Saldaña, E., & Quevedo, R. (2016). Evaluation of Food Quality and Safety with Hyperspectral Imaging (HSI). Food Engineering Reviews, 8(3), 306–322. https://doi.org/10.1007/s12393-015-9137-8
Souza, A., de Oliveira Sans, E., Müller, B., & Molento, C. (2015). Broiler chicken welfare assessment in GLOBALGAP ® certified and non-certified farms in Brazil. Animal Welfare, 24(1), 45–54. https://doi.org/10.7120/09627286.24.1.045
Sporchia, F., Galli, A., Kastner, T., Pulselli, F. M., & Caro, D. (2023). The environmental footprints of the feeds used by the EU chicken meat industry. Science of The Total Environment, 886, 163960. https://doi.org/10.1016/j.scitotenv.2023.163960
Stefan, A. R. (2010). Band reduction for hyperspectral imagery processing (C. A. Bouman, I. Pollak, & P. J. Wolfe, Eds.; p. 75330W). https://doi.org/10.1117/12.837953
Steiner, G., Bartels, T., Krautwald-Junghanns, M.-E., & Koch, E. (2010). Bird sexing by Fourier transform infrared spectroscopy (A. Mahadevan-Jansen & W. Petrich, Eds.; p. 75600D). https://doi.org/10.1117/12.841627
Steiner, G., Bartels, T., Stelling, A., Krautwald-Junghanns, M. E., Fuhrmann, H., Sablinskas, V., & Koch, E. (2011). Gender determination of fertilized unincubated chicken eggs by infrared spectroscopic imaging. Analytical and Bioanalytical Chemistry, 400(9), 2775-2782. https://doi.org/10.1007/S00216-011-4941-3
Tanabe, Y., Nakamura, T., Fujioka, K., & Doi, O. (1979). Production and secretion of sex steroid hormones by the testes, the ovary, and the adrenal glands of embryonic and young chickens (Gallus domesticus). General and Comparative Endocrinology, 39(1), 26–33. https://doi.org/10.1016/0016-6480(79)90189-8
Veganzones, M. A., & Graña, M. (2019). A Research: Hyperspectral Image Processing Techniques. International Journal of Innovative Technology and Exploring Engineering, 8(9S2), 577–581. https://doi.org/10.35940/ijitee.I1120.0789S219
Vidal, M., & Amigo, J. M. (2012). Pre-processing of hyperspectral images. Essential steps before image analysis. Chemometrics and Intelligent Laboratory Systems, 117, 138–148. https://doi.org/10.1016/j.chemolab.2012.05.009
Wang, X., Liu, J., Chi, W., Wang, W., & Ni, Y. (2023). Advances in Hyperspectral Image Classification Methods with Small Samples: A Review. Remote Sensing, 15(15), 3795. https://doi.org/10.3390/rs15153795
Wang, X., Liu, J., Wang, W., Chi, W., & Feng, R. (2023). Weakly Supervised Hyperspectral Image Classification with Few Samples Based on Intradomain Sample Expansion. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 16, 5769–5781. https://doi.org/10.1109/JSTARS.2023.3283862
Webster, B., Hayes, W., & Pike, T. W. (2015). Avian Egg Odour Encodes Information on Embryo Sex, Fertility and Development. PLOS ONE, 10(1), e0116345. https://doi.org/10.1371/journal.pone.0116345
Weissmann, A., Reitemeier, S., Hahn, A., Gottschalk, J., & Einspanier, A. (2013). Sexing domestic chicken before hatch: A new method for in ovo gender identification. Theriogenology, 80(3), 199–205. https://doi.org/10.1016/j.theriogenology.2013.04.014
Xiang, X., Hu, G., Jin, Y., Jin, G., & Ma, M. (2022). Nondestructive characterization gender of chicken eggs by odor using SPME/GC-MS coupled with chemometrics. Poultry Science, 101(3), 101619. https://doi.org/10.1016/j.psj.2021.101619
Yokoya, N., Chan, J., & Segl, K. (2016). Potential of Resolution-Enhanced Hyperspectral Data for Mineral Mapping Using Simulated EnMAP and Sentinel-2 Images. Remote Sensing, 8(3), 172. https://doi.org/10.3390/rs8030172
Yokoya, N., Grohnfeldt, C., & Chanussot, J. (2017). Hyperspectral and Multispectral Data Fusion: A comparative review of the recent literature. IEEE Geoscience and Remote Sensing Magazine, 5(2), 29–56. https://doi.org/10.1109/MGRS.2016.2637824
Zhang, M., Wang, L., Zhang, L., & Huang, H. (2019). Compressive hyperspectral imaging with non-zero mean noise. Optics Express, 27(13), 17449. https://doi.org/10.1364/OE.27.017449
Zhang, W., Brown, E. R., Rahman, M., & Norton, M. L. (2013). Observation of terahertz absorption signatures in microliter DNA solutions. Applied Physics Letters, 102(2). https://doi.org/10.1063/1.4775696
Zhang, Y., Kong, X., Deng, L., & Liu, Y. (2023). Monitor water quality through retrieving water quality parameters from hyperspectral images using graph convolution network with superposition of multi-point effect: A case study in Maozhou River. Journal of Environmental Management, 342, 118283. https://doi.org/10.1016/j.jenvman.2023.118283
Zhu, Z. H., Ye, Z. F., & Tang, Y. (2021). Nondestructive identification for gender of chicken eggs based on GA-BPNN with double hidden layers. Journal of Applied Poultry Research, 30(4), 100203. https://doi.org/10.1016/j.japr.2021.100203
Zumbrink. L. B. Brenig, A. Foerster, J. Hurlin, & M. von Wenzlawowicz. (2020). Electrical anaesthesia of male chicken embryos in the second third of the incubation period in compliance with animal welfare. European Poultry Science (EPS), 84. https://doi.org/10.1399/eps.2020.315
Publicado
Cómo citar
Número
Sección
Licencia
Derechos de autor 2024 Juan Ernesto Hernandez-Valdez, Daniel Castro-Salinas, Cesar Eduardo Honorio-Javes, Fredy Marcial Pajuelo-Risco
Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial 4.0.
Los autores conservan sus derechos de autor sin restricciones.
