PhD in Veterinary Sciences for Animal Health and Food Safety

Contacts

Supervisor

Dominga Soglia

Curriculum vitae

Curriculum Vitae

Phd thesis

“Near-Infrared Spectroscopy and Genetics approaches to predict meat quality and improve production performance in local Piedmontese chicken breeds "

 

• Scientific background/state of the art

In the 1960s, the emergence of agricultural industrialization supplanted the breeding of local chicken breeds, in favor of commercial hybrid, making their presence marginal. Today, the reinterest in local breeds responds to the terms of environmental sustainability, biodiversity and quality product (Padhi, 2016). In Piemonte region, two local chicken breeds, Bianca di Saluzzo and Bionda Piemontese, are raised for meat production. However, they are considered slow-growing breeds (Soglia et al., 2020). Their lower production performance represents a limit for the breeders who have to face with the fast growth of the commercial line. To address this, the study of the genetic polymorphisms and their correlation with productive traits is essential for improving performance while preserving biodiversity. Furthermore, the consideration of public regarding meat quality has gradually increased in the recent years. This growing demand for high-quality product has positively impacted local chicken production, as these breeds are recognized for offering superior meat quality. This requirement has increased interest in Near-Infrared (NIR) Spectroscopy due to its ability to provide rapid information about the molecular bonds and chemical constituents useful for characterizing foods and quality measurements (Andrés et al., 2007). This technique has been used successfully in several fields of food and feed analysis (Oh, 1995), but no studies are available on chicken meat (Zheng et al., 2023).

The combination of Near-Infrared Spectroscopy and genetic studies presents a promising approach for the valorization, in term of meat quality and production performance, of local chicken breeds.

• Aims

The main aim of my project is to valorise meat quality and optimize the production performance of local chicken breeds through the use of innovative laboratory techniques. The project focuses on identifying DNA polymorphisms and analyzing RNA expression of candidate genes to discover genetic markers associated with productivity and meat quality. These markers will be valuable for breeding programs aimed at improving the performance of local breed and preserve thier superior meat characteristics. To reach this, correlation between polymorphisms and phenotypic data will be conducted combining genetics with NIR analysis. 

• Materials and methods

Genetic analysis 

Breast muscles, livers, spleens, brains and feathers were collected after slaughtering for RNA expression and DNA polymorphism analysis. A whole transcriptome study was conducted on feathers samples to avoid the euthanasia of the animals. The extracted RNA was sent to Azenta Life Science to identify marker genes linked to metabolisms involved in growth performances or other significant functions. Candidate genes identified in this process, will then be analyzed using NGS sequencing (Miseq platform), to test the association of genetic polymorphisms with carcass parameters and meat quality traits. 

Meat Quality 

Meat quality is typically assessed based on its physical and chemical properties. Physical properties include color, tenderness, water-holding capacity, and pH, while chemical parameters involve moisture, protein and fat content. Meat color is evaluatedusing the L*, a*, b* color space, where L* represents perceptual lightness, a* and b* denote the color dimensions. Tenderness is measured by the shear force, and water-holding capacity is assessed using the “weep or purge” method, as described by Warner (2014). Standard laboratory techniques are employed to measure chemical parameteres (Dabbou et al., 2019).

NIR analysis 

Each breast and thigh samples were analysed using both NIRSystems 5000 spectrophotometer (Agilent) and SCiO device (by Consumer Physics) to predict meat quality parameters. The obtained spectra will be matched with corresponding qualitative traits (genetics polymorphisms) and with the quantitative traits (meat's chemical and physical composition). This comparison will allow the evaluation of NIR analysis' effectiveness in accurately predicting the quality of chicken meat based on these parameters.

Depending on the above-mentioned variables, dedicated statistical and bioinformatics tools will be applied to highlight possible significant differences.

 

References

• Andrés S., Murray I., Navajas E.A., Fisher A.V., Lambe N.R., Bünger L. “Prediction of sensory characteristics of lamb meat samples by near infrared reflectance spectroscopy” (2007). Meat Science 76: 509-516.
• Dabbou S., Gasco L., Lussiana C., Brugiapaglia A., Biasato I., Renna M., Cavallarin L., Gai F. and Schiavone A. “Yellow mealworm (Tenebrio molitor L.) larvae inclusion in diets for free-range chickens: effect on meat quality and fatty acid profile” (2019). Renewable Agriculture and food System 35(5).
• Kubota S., Vandee A., Keawnakient P., Molee W., Yongsawatdikul J. and Molee “Effects of the MC4R, CAPN1, and ADSL genes on body weight and purine content in slow-growing chickens” (2019). Poultry Science 98: 4327–4337.
• Oh E.K., Grossklaus D. “Measurement of the Components in Meat Patties by near-Infrared Reflectance Spectroscopy” (1995). Meat Sci. 41, 157–162.
• Padhi M.K. “Importance of Indigenous Breeds of Chicken for Rural Economy and Their Improvements for Higher Production Performance” (2016). Hindawi Publishing Corporation Scientifica.
• Prieto N., Pawluczyk O., Gugan M.E.R., Aalhus J.L. “A review of the principles and applications of near infrared spectroscopy to characterize meat, fat, and meat products” (2017). Applied Spectoscopy 71(7): 1403-1426
• Relaix F., Bencze M., Borok M. J., Der Vartanian A., Gattazzo F., Mademtzoglou D., Perez-Diaz S., Prola A., Reyes-Fernandez P. C., Rotini A. and Taglietti V. “Perspectives on skeletal muscle stem cells” (2021). Nature Communication 12:692.
• Soglia D., Sacchi P., Sartore S., Maione S., Schiavone A., De Marco M., Bottero M.T., Dalmasso A., Pattono D., Rasero R.“Distinguishing industrial meat from that of indigenous chickens with molecular markers” (2017) Poult. Sci: 96, 2552–2561
• Soglia D., Sartore S., Maione S., Schiavone A., Dabbou S., Nery J., Zaniboni L., Marelli S., Sacchi P., Rasero R. “Growth Performance Analysis of Two Italian Slow-Growing Chicken Breeds: Bianca di Saluzzo and Bionda Piemontese” (2020). Animals: 10(6), 969.
• Tjørve K.M.C., Tjørve E. “The use of Gompertz models in growth analyses, and new Gompertz-model approach: An addition to the unified-Richards family” (2017). PLoS ONE 12, e0178691.
• Warner R.D. “Measuremments of Water-holding capacity and color: objective and subjective” (2014). Encyclopedia of Meat Sciences 2e
• Zhang S., Han R.L., Gao Z.Y., Zhu S.K., Tian Y.D., Sun G.R., Kang X.T. “A novel 31-bp indel in the paired box 7 (PAX7) gene is associated with chicken performance traits” (2014). Brit. Poult. Sci. 55, 31–36.
• Zheng X., Chen L., Li X. and Zhang D. “Non-Destructive Detection of Meat Quality Based on Multiple Spectral Dimension Reduction Methods by Near-Infrared Spectroscopy” (2023). Foods 12, 300.
• Xu H.Y, Wang Y., Liu Y.P., Wang J. and Zhu Q. “Polymorphisms and expression of the chicken POU1F1 gene associated with carcass traits” (2012). Molecular Biology Report 39, 8363-8371.

Research activities

Co supervisor

Achille Schiavone, Federica Raspa

Abstract

• EAAP, European Federation of Animal Science (01-05/09/2024); Firenze, Italy: 

“Feather’s transcriptome analysis in local chickens fed two different diets: a possible marker to study lipid metabolism". N. Stoppani, F. Raspa, E. Fiorilla, S. Maione, C. Mugnai, A. Schiavone, D. Soglia.

“Potential use of a pocket near-infrared spectroscopy device to directly discriminate local chicken meat". N. Stoppani, C.L. Manuelian, S. Sciuto, E.E. Cappone, M. Gariglio, P.L. Acutis, A. Schiavone, D. Soglia.

• European Poultry Conference (EPC) (24-28/06/24); Valencia, Spain:

“Effect of a high-energ diet on liver stress and lipid metabolisms, meat and carcass traits in a slow-growing chicken breed”. Stoppani, F. Raspa, E. Fiorilla, C. Mugnai, V. Zambotto, S. Nurisso, A. Schiavone, D. Soglia.

“Recovering Italian poultry treasures: reviving the Millefiori Piemontese breed”. E.E. Cappone, V. Bongiorno, E. Fiorilla, N. Stoppani, F. Gai, V. Zambotto, D. Soglia, M. Gariglio, A. Schiavone.

• IEE-MeAVeAS (22-24/04/2024); Torino, Italy:

“First application of near-infrared spectroscopy to classify Bionda Piemontese chicken meat". Stoppani, E. Albanell, V.Zambotto, D. Soglia, C. Mugnai, A. Schiavone, C.L. Manuelian.

“Measuring ethological parameters and their correlation with corticosterone levels in three slow-growing Piedmontese chicken breeds”. E.E. Cappone, V. Bongiorno, E. Fiorilla, M. Gariglio, E. Macchi, I. Manenti, N. Stoppani, D. Soglia, A. Schaivone.

• Game of Research (16/12/2023); Veterinary Medicin, University of Turin:

“Preliminary near-infreared spectroscopy analysis to predict chicken meat quality". N. Stoppani, S. Sciuto, C.L. Manuelian, E.E. Cappone, M. Gariglio, P.L. Acutis, A. Sciavone and D. Soglia

• ASPA 25th Congress (13-16/06/2023); Monopoli, Italy:

“Evaluation of the effect of the breeding system on the expression of liver genes in local slow-growing chicken breeds”. F. Raspa, N. Stoppani, D. Soglia, F. Perini, E. Fiorilla, M. Profiti, S. Maione, A. Schiavone, P. Sacchi, E. Lasagna and C. Mugnai.

“Effect of bakery by-products inclusion in the broiler’s diet on growth performance, carcass yeld and gene expression profiling". K. Srikanthithasan, M. Gariglio, E. Fiorilla, A. Giorgino, L. Dellepiane, E. Diaz Cuna, D. Sola, V. Bongiorno, S. Bergagna, A. Schiavone, F. Raspa, M. Profiti, N. Stoppani, D. Soglia and C. Forte.

“Multiplex Digital Expression Gene Analysis (MuDEGA) of 11 liver poultry genes whit NGS approach”. F. Raspa, N. Stoppani, F. Perini, E. Fiorilla, M. Profiti, S. Maione, A. Schiavone, P. Sacchi, E. Lasagna, C. Mugnai and D. Soglia.

• Game of Research (15/12/2022); Veterinary Medicin, University of Turin:

“Study of productive and reproductive genetic marker in local chicken breed: DNA polymorphisms and RNA expression molecular analysis”. N.Stoppani and D. Soglia.

Personal Training

Statistical Analysis

Descriptive statistical analysis.

Wilcoxon test, Kruskal-Wallis, test chi-square, t-test.

Study of the structure of variance, covariance and correlation matrices.

Principal Component Analysis (PCA), Cluster analysis, Partial Least Square Regression (PLSR) and Disciminant Analysis.

Honors and Awards

• 75^th EAAP Annual Meeting (1^st-5^th September 2024, Firenze)

Winner of the EAAP Scholarship: “Feather’s transcriptome analysis in local chickens fed with two different diets: a possible marker to study lipid metabolism”

• XVI European Poultry Conference (24^th- 28^th June 2024, Valencia)

Winner of the Youth Program: “Effect of a high-energy diet on liver stress and lipid metabolisms, meat and carcass traits in a slow-growing chicken breed”

• Game of Research (16^th December 2023, Torino)

1^st BEST ORAL PRESENTATION: “Preliminary Near-Infrared Spectroscopy analysis to predict chicken meat quality”

• Game of Research (15^th December 2022, Torino)

2^nd BEST POSTER: “Study of productive and reproductive genetic marker in local chicken breed: DNA polymorphisms and RNA expression molecular analysis

Publications

All of my research products