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Ghavi Hossein-Zadeh N. Evidence of additive genetic variation for major milk proteins in dairy cows: A meta-analysis. J Anim Breed Genet 2024; 141:379-389. [PMID: 38230949 DOI: 10.1111/jbg.12850] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Revised: 10/10/2023] [Accepted: 01/07/2024] [Indexed: 01/18/2024]
Abstract
In the past, there have been reports of genetic parameters for milk proteins in various dairy cattle populations. The high variability among genetic parameter estimates has been caused by this. This study aimed to use a random-effects meta-analysis model to compile published estimates of genetic parameter for major milk proteins of α-lactalbumin, β-lactoglobulin, sum of whey proteins, casein, αs1-casein, αs2-casein, β-casein, and κ-casein in dairy cows. The study used a total of 140 heritability and 256 genetic correlation estimates from 23 papers published between 2004 and 2022. The estimated range of milk protein heritability is from 0.284 (for α-lactalbumin in milk) to 0.596 (for sum of whey proteins). The genetic correlation estimates between casein and milk yield, milk fat and protein percentages were -0.461, 0.693, and 0.976, respectively (p < 0.05). The genetic correlation estimates between milk proteins expressed as a percentage of milk were significant and varied from 0.177 (between β-lactoglobulin and κ-casein) to 0.892 (between αs1-casein and αs2-casein). Moderate-to-high heritability estimates for milk proteins and their low genetic associations with milk yield and composition indicated the possibility for improving milk proteins in a genetic selection plan with negligible correlated effects on production traits in dairy cows.
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Singh A, Kumar A, Thakur MS, Khare V, Jain A, Tiwari SP. Genetic analysis of milk minerals in dairy cattle: a review. J Appl Genet 2024; 65:375-381. [PMID: 38286942 DOI: 10.1007/s13353-024-00832-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 12/22/2023] [Accepted: 01/19/2024] [Indexed: 01/31/2024]
Abstract
Mineral composition in milk can affect its nutritional as well as physio-chemical properties of milk and is considered an important trait in the evaluation of milk quality. The composition and concentration of milk minerals could be altered with natural source of variation including nutrition and genetics. The effect of diet on milk minerals is well studied. However, genetic effects on the milk minerals have recently gained the attention. This review provides an overview of the genetic variation of milk minerals, and the genomic regions associated with mineral concentration in the milk are also discussed. The difference of milk minerals between breeds and the genetic parameters including heritability estimates and correlation among minerals indicates that milk minerals are under strong genetic control. Recently, the genome-wide association study (GWAS) has explored several regions associated with milk minerals and thus provides a new genetic source for improving the milk quality through genomics-assisted breeding. Hence, a combination of the qualitative and molecular approaches can be exploited to improving the nutritional quality of cattle milk in terms of its mineral composition.
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Affiliation(s)
- Akansha Singh
- College of Veterinary Science and Animal Husbandry, NDVSU, Jabalpur, 482001, M.P, India.
| | - Amit Kumar
- ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, 243122, U.P., India
| | - Mohan Singh Thakur
- College of Veterinary Science and Animal Husbandry, NDVSU, Jabalpur, 482001, M.P, India
| | - Vaishali Khare
- College of Veterinary Science and Animal Husbandry, NDVSU, Jabalpur, 482001, M.P, India
| | - Asit Jain
- College of Veterinary Science and Animal Husbandry, NDVSU, Jabalpur, 482001, M.P, India
| | - Sita Prasad Tiwari
- Nanaji Deshmukh Veterinary Science University, Jabalpur, 482004, M.P., India
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3
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Du C, Ren X, Chu C, Ding L, Nan L, Sabek A, Hua G, Yan L, Zhang Z, Zhang S. Assessing the relationship between somatic cell count and the milk mid-infrared spectrum in Chinese Holstein cows. Vet Rec 2023; 193:e3560. [PMID: 37899290 DOI: 10.1002/vetr.3560] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 08/30/2023] [Accepted: 09/19/2023] [Indexed: 10/31/2023]
Abstract
BACKGROUND Milk produced by dairy cows is a complex combination of many components, but the effect of mastitis has only been investigated for a few of these components. Milk mid-infrared (MIR) spectra can reflect the global composition of milk, and this study aimed to detect the relationships between milk MIR spectral wavenumbers and milk somatic cell count (SCC)-a sensitive biomarker for mastitis. METHODS Pearson correlation analysis was used to calculate the correlation coefficient between somatic count score (SCS) and spectral wavenumbers. A general linear mixed model was applied to investigate the effect of three different classes of SCC (low, middle and high) on spectral wavenumbers. RESULTS The mean correlation coefficient between the 'fingerprint region' (wavenumbers 925-1582 cm-1 ) and the SCS was higher than that for other regions of the MIR spectrum, and the specific wavenumber with the strongest correlation with the SCS was within the 'fingerprint region'. SCC class had a significant (p < 0.05) effect on 639 spectral wavenumbers. In particular, some spectral wavenumbers within the 'fingerprint region' were highly affected by the SCC class. LIMITATION The data were collected from only one province in China, so the generalisability of the findings may be limited. CONCLUSION SCC had close relationships with milk spectral wavenumbers related to important milk components or chemical bonds.
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Affiliation(s)
- Chao Du
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, China
- College of Animal Science and Veterinary Medicine, Henan Institute of Science and Technology, Xinxiang, China
| | - Xiaoli Ren
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, China
- Henan Dairy Herd Improvement Center, Zhengzhou, China
| | - Chu Chu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, China
| | - Lei Ding
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, China
| | - Liangkang Nan
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, China
| | - Ahmed Sabek
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, China
- Department of Veterinary Hygiene and Management, Faculty of Veterinary Medicine, Benha University, Moshtohor, Egypt
| | - Guohua Hua
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, China
| | - Lei Yan
- Henan Dairy Herd Improvement Center, Zhengzhou, China
| | - Zhen Zhang
- Henan Dairy Herd Improvement Center, Zhengzhou, China
| | - Shujun Zhang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, China
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Konuspayeva G, Al-Gedan MM, Alzuraiq F, Faye B. Some Variation Factors of Freezing Point in Camel Milk. Animals (Basel) 2023; 13:ani13101657. [PMID: 37238087 DOI: 10.3390/ani13101657] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 05/03/2023] [Accepted: 05/09/2023] [Indexed: 05/28/2023] Open
Abstract
The freezing point degree of milk (FPD) is a classical indicator of cow milk quality. In camel milk, few references are available in the literature regarding the main factors of variation. In the present paper, two methods of FPD determination were used: the Reference method (RM) (using Cryostar) and the Express method (EM), using a milk analyzer (Milkoscan-FT1). The RM was used to determine FPD in 680 bulk raw or pasteurized camel milk samples. Regarding EM, 736 individual milk samples, 1323 bulk samples, 635 samples of pasteurized milk and 812 samples of raw milk used for cheese making were available. The variability of FPD was investigated according to month, lactation stage, milk composition, milk production and microbiological status. Correlations between methods were explored. FPD was highly correlated with most of the milk components and tended to decrease in cases of high contamination by coliforms or high total flora count. However, the weak significant correlations between the two methods indicated the necessity to specifically calibrate an automatic milk analyzer for camel milk.
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Affiliation(s)
- Gaukhar Konuspayeva
- Faculty of Biology and Biotechnology, Al-Farabi Kazakh National University, 71 Avenue Al-Farabi, Almaty 050040, Kazakhstan
| | - Mubarak M Al-Gedan
- Conservation and Genetic Improvement Center, Camel Project UTF/SAU/044/SAU, P.O. Box 761, Al-Kharj 11942, Saudi Arabia
| | - Fuad Alzuraiq
- Conservation and Genetic Improvement Center, Camel Project UTF/SAU/044/SAU, P.O. Box 761, Al-Kharj 11942, Saudi Arabia
| | - Bernard Faye
- UMR-SELMET, CIRAD-ES, Campus International de Baillarguet, CEDEX 5, 34938 Montpellier, France
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5
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Moore SS, Costa A, Penasa M, Callegaro S, De Marchi M. How heat stress conditions affect milk yield, composition, and price in Italian Holstein herds. J Dairy Sci 2023; 106:4042-4058. [PMID: 37080787 DOI: 10.3168/jds.2022-22640] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 12/21/2022] [Indexed: 04/22/2023]
Abstract
An edited data set of 700 bulk and 46,338 test-day records collected between 2019 and 2021 in 42 Holstein-dominated farms in the Veneto Region (North of Italy) was available for the present study. Information on protein, fat and lactose content, somatic cell count, and somatic cell score was available in bulk milk as well as individual test-day records, whereas urea concentration (mg/dL), differential somatic cell count (%), and milk yield (kg/d) were available for test-day records only. Milk features were merged with meteorological data retrieved from 8 weather stations located maximum 10 km from the farms. The daily and weekly temperature-humidity index (THI; wTHI) and maximum daily (MTHI) and weekly temperature-humidity index were associated with each record to evaluate the effect of heat stress conditions on milk-related traits through linear mixed models. Least squares means were estimated to evaluate the effect of THI and, separately, of MTHI on milk characteristics correcting for conventional systematic factors. Overall, heat stress conditions lowered the quality of both bulk milk and test-day records, with fat and protein content being greatly reduced, and somatic cell score and differential somatic cell count augmented. Milk yield was not affected by either THI or MTHI in this data set, but the effect of elevated THI and MTHI was in general stronger on test-day records than on bulk milk. Farm-level economic losses of reduced milk quality rather than reduced yield as consequence of elevated THI or MTHI was estimated to be between $23.57 and $43.98 per farmer per day, which is of comparable magnitude to losses resulting from reduced production. Furthermore, MTHI was found to be a more accurate indicator of heat stress experienced by a cow, explaining more variability of traits compared with THI. The negative effect of heat stress conditions on quality traits commences at lower THI/MTHI values compared with milk yield. Thus, a progressive farmers' income loss due to climatic changes is already a reality and it is mainly due to deterioration of milk quality rather than quantity in the studied area.
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Affiliation(s)
- S Sterup Moore
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, 35020 Legnaro, Italy
| | - A Costa
- Department of Veterinary Medical Sciences (DIMEVET), Alma Mater University of Bologna, 40064 Ozzano dell'Emilia, Italy.
| | - M Penasa
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, 35020 Legnaro, Italy
| | - S Callegaro
- Department of Agriculture, Food, Environment and Forestry (DAGRI), University of Firenze, 50144 Florence, Italy
| | - M De Marchi
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, 35020 Legnaro, Italy
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Across countries implementation of handheld near-infrared spectrometer for the on-line prediction of beef marbling in slaughterhouse. Meat Sci 2023; 200:109169. [PMID: 37001445 DOI: 10.1016/j.meatsci.2023.109169] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2022] [Revised: 03/14/2023] [Accepted: 03/16/2023] [Indexed: 03/22/2023]
Abstract
Only few studies have used Near-Infrared (NIR) spectroscopy to assess meat quality traits directly in the chiller. The aim of this study was therefore to investigate the ability of a handheld NIR spectrometer to predict marbling scores on intact meat muscles in the chiller. A total of 829 animals from 2 slaughterhouses in France and Italy were involved. Marbling was assessed according to the 3G (Global Grading Guaranteed) protocol using 2 different scores. NIR measurements were collected by performing 5 scans at different points of the Longissimus thoracis. An average MSA marbling score of 330-340 was obtained in the two countries. The prediction models provided a R2 in external validation between 0.46 and 0.59 and a standard error of prediction between 83.1 and 105.5. Results did provide a moderate prediction of the marbling scores but can be useful in the European industry context to predict classes of MSA marbling.
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Magro S, Costa A, De Marchi M, Manuelian CL. Milk-related performances of Murciano-Granadina goats reared in Italy compared to cosmopolitan breeds. ITALIAN JOURNAL OF ANIMAL SCIENCE 2022. [DOI: 10.1080/1828051x.2022.2101946] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/16/2022]
Affiliation(s)
- Silvia Magro
- Dipartimento di Agronomia, Animali, Alimenti, Risorse naturali e Ambiente, Università di Padova, Legnaro, Italy
| | - Angela Costa
- Dipartimento di Agronomia, Animali, Alimenti, Risorse naturali e Ambiente, Università di Padova, Legnaro, Italy
| | - Massimo De Marchi
- Dipartimento di Agronomia, Animali, Alimenti, Risorse naturali e Ambiente, Università di Padova, Legnaro, Italy
| | - Carmen L. Manuelian
- Dipartimento di Agronomia, Animali, Alimenti, Risorse naturali e Ambiente, Università di Padova, Legnaro, Italy
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8
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FRANZOI M, COSTA A, VIGOLO V, PENASA M, DE MARCHI M. Effect of pasteurization on coagulation properties of bovine milk and the role of major composition traits and protein fractions. J Food Compost Anal 2022. [DOI: 10.1016/j.jfca.2022.104808] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/16/2022]
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9
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Mordvinova V, Sviridenko G, Ostroukhova I, Shukhalova O, Mamykin D. Study of the influence of the process of freezing milk on the safety of its properties of cheese suitability. BIO WEB OF CONFERENCES 2022. [DOI: 10.1051/bioconf/20224601009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
The article presents the results of studies of the effect of freezing on the change in the physicochemical, microbiological and technological properties of goat milk and the preservation of its qualities of cheese suitability. A statistically significant dependence of the composition of milk on the duration of storage in a frozen state was revealed. There was no significant effect of freezing and defrosting modes on the quality indicators of milk. It has been established that changes in the technological properties of frozen goat milk after defrosting, such as the duration of coagulation and the ability to syneresis, are insignificant in comparison with defrosted cow's milk.
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10
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Ghavi Hossein-Zadeh N. A meta-analysis of genetic parameter estimates for milk and serum minerals in dairy cows. J DAIRY RES 2022; 89:1-10. [PMID: 35193720 DOI: 10.1017/s0022029922000127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
This study aimed to conduct a meta-analysis based on a random-effects model to combine different published heritability estimates and genetic correlations for milk and serum minerals in dairy cows. In total, 59 heritability and 25 genetic correlation estimates from 12 articles published between 2009 and 2021 were used. The heritability estimates for milk macro-minerals were moderate to high and ranged from 0.311 (for Na) to 0.420 (for Ca). On the other hand, milk micro-minerals had lower heritabilities with a range from 0.013 (for Fe) to 0.373 (for Zn). The heritability estimates for serum macro-minerals were generally low and varied from 0.126 (for K) to 0.206 (for Mg). The estimates of genetic correlation between milk macro-minerals varied from -0.024 (between Na and K) to 0.625 (between Mg and P). The genetic correlations of milk Ca and P with milk yield were -0.171 and -0.211, respectively. The estimates of genetic parameters reported in this meta-analysis study are appropriate to utilize in breeding plans when valid estimates are not available for milk minerals in dairy cow populations.
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11
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Franzoi M, Costa A, Penasa M, De Marchi M. Genetic background of calcium and phosphorus phases predicted from milk mid-infrared spectra of Holstein cows. ITALIAN JOURNAL OF ANIMAL SCIENCE 2021. [DOI: 10.1080/1828051x.2021.1912663] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Affiliation(s)
- Marco Franzoi
- Dipartimento di Agronomia, Animali, Alimenti, Risorse naturali e Ambiente, University of Padova, Legnaro, Italy
| | - Angela Costa
- Dipartimento di Agronomia, Animali, Alimenti, Risorse naturali e Ambiente, University of Padova, Legnaro, Italy
| | - Mauro Penasa
- Dipartimento di Agronomia, Animali, Alimenti, Risorse naturali e Ambiente, University of Padova, Legnaro, Italy
| | - Massimo De Marchi
- Dipartimento di Agronomia, Animali, Alimenti, Risorse naturali e Ambiente, University of Padova, Legnaro, Italy
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12
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Zaalberg RM, Poulsen NA, Bovenhuis H, Sehested J, Larsen LB, Buitenhuis AJ. Genetic analysis on infrared-predicted milk minerals for Danish dairy cattle. J Dairy Sci 2021; 104:8947-8958. [PMID: 33985781 DOI: 10.3168/jds.2020-19638] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Accepted: 03/26/2021] [Indexed: 11/19/2022]
Abstract
A group of milk components that has shown potential to be predicted with milk spectra is milk minerals. Milk minerals are important for human health and cow health. Having an inexpensive and fast way to measure milk mineral concentrations would open doors for research, herd management, and selective breeding. The first aim of this study was to predict milk minerals with infrared milk spectra. Additionally, milk minerals were predicted with infrared-predicted fat, protein, and lactose content. The second aim was to perform a genetic analysis on infrared-predicted milk minerals, to identify QTL, and estimate variance components. For training and validating a multibreed prediction model for individual milk minerals, 264 Danish Jersey cows and 254 Danish Holstein cows were used. Partial least square regression prediction models were built for Ca, Cu, Fe, K, Mg, Mn, Na, P, Se, and Zn based on 80% of the cows, selected randomly. Prediction models were externally validated with 8 herds based on the remaining 20% of the cows. The prediction models were applied on a population of approximately 1,400 Danish Holstein cows with 5,600 infrared spectral records and 1,700 Danish Jersey cows with 7,200 infrared spectral records. Cows from this population had 50k imputed genotypes. Prediction accuracy was good for P and Ca, with external R2 ≥ 0.80 and a relative prediction error of 5.4% for P and 6.3% for Ca. Prediction was moderately good for Na with an external R2 of 0.63, and a relative error of 18.8%. Prediction accuracies of milk minerals based on infrared-predicted fat, protein, and lactose content were considerably lower than those based on the infrared milk spectra. This shows that the milk infrared spectrum contains valuable information on milk minerals, which is currently not used. Heritability for infrared-predicted Ca, Na, and P varied from low (0.13) to moderate (0.36). Several QTL for infrared-predicted milk minerals were observed that have been associated with gold standard milk minerals previously. In conclusion, this study has shown infrared milk spectra were good at predicting Ca, Na, and P in milk. Infrared-predicted Ca, Na, and P had low to moderate heritability estimates.
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Affiliation(s)
- R M Zaalberg
- Center for Quantitative Genetics and Genomics, Aarhus University, Blichers Allé 20, DK-8830 Tjele, Denmark.
| | - N A Poulsen
- Department of Food Science, Aarhus University, Agro Food Park 48, 8200 Aarhus N, Denmark
| | - H Bovenhuis
- Animal Breeding and Genomics, Wageningen University and Research, 6700AH, Wageningen, The Netherlands
| | - J Sehested
- Department of Animal Science, Aarhus University, Blichers Allé 20, DK-8830 Tjele, Denmark
| | - L B Larsen
- Department of Food Science, Aarhus University, Agro Food Park 48, 8200 Aarhus N, Denmark
| | - A J Buitenhuis
- Center for Quantitative Genetics and Genomics, Aarhus University, Blichers Allé 20, DK-8830 Tjele, Denmark
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Saugo M, Franzoi M, Niero G, De Marchi M. Mineral equilibrium in commercial curd and predictive ability of near-infrared spectroscopy. J Dairy Sci 2021; 104:3947-3955. [PMID: 33485688 DOI: 10.3168/jds.2020-18712] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Accepted: 10/26/2020] [Indexed: 11/19/2022]
Abstract
Curd samples (n = 83) from 3 European dairy companies were analyzed for micellar and soluble mineral fractions content using inductively coupled plasma optical emission spectrometry as a gold standard method. The same curd samples were analyzed through 3 different near-infrared (NIR) instruments, and NIR spectra were merged with reference data. Prediction equations were developed using modified partial least squares analysis, and the accuracy of prediction was evaluated through leave-one-out cross validation. Overall, NIR spectroscopy was capable of predicting micellar and soluble mineral fractions in curd, but with differences among instruments. Fitting statistics showed that the visible NIR instrument in reflectance mode outperformed the NIR instrument in transmittance mode as well as the portable NIR instrument in reflectance mode. Prediction accuracies for most of the analyzed mineral fractions can be used for curd quality control in dairy companies and to aid in decision-making during the cheesemaking process.
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Affiliation(s)
- M Saugo
- Department of Agronomy, Food, Natural resources, Animals and Environment, University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy
| | - M Franzoi
- Department of Agronomy, Food, Natural resources, Animals and Environment, University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy
| | - G Niero
- Department of Agronomy, Food, Natural resources, Animals and Environment, University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy.
| | - M De Marchi
- Department of Agronomy, Food, Natural resources, Animals and Environment, University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy
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Niero G, Costa A, Franzoi M, Visentin G, Cassandro M, De Marchi M, Penasa M. Genetic and Non-Genetic Variation of Milk Total Antioxidant Activity Predicted from Mid-Infrared Spectra in Holstein Cows. Animals (Basel) 2020; 10:ani10122372. [PMID: 33322019 PMCID: PMC7764824 DOI: 10.3390/ani10122372] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Revised: 12/02/2020] [Accepted: 12/09/2020] [Indexed: 01/03/2023] Open
Abstract
Simple Summary The total antioxidant activity (TAA) of food is important for human health and results from the contribution of different nutraceutical compounds. Direct determination of TAA in food is time-consuming and expensive. Infrared technologies allow the prediction of difficult-to-measure traits with certain accuracy in several organic matrices, including TAA of bovine milk. In order to understand the background of TAA and identify potential strategies to improve this feature in bovine milk, we explored its non-genetic sources of variation and estimated heritability and correlations with traits of economic interest in a large database of Holstein cows. Abstract Food antioxidants enhance products shelf life and stability during technological treatments through the maintenance of their physical and chemical properties. Moreover, they are endowed with several positive effects on human health, including cell membranes preservation, enzyme functionality, and DNA integrity. Milk has been described in relation to a wide array of fat soluble and water-soluble antioxidant compounds, in particular vitamin A, C, and E, lactoferrin and peptides derived from casein and whey proteins. The total antioxidant activity (TAA) of milk is a novel and scarcely explored trait, defined as the sum of antioxidant contributions of the aforementioned compounds. On this background, the aims of the present study were to investigate the variability of milk TAA on a large scale exploiting predictions obtained through mid-infrared (MIR) spectroscopy and to estimate genetic parameters of this trait in Holstein cows. Individual milk samples were collected between January 2011 and December 2018 during the routine milk recording procedure. Samples were analysed for gross composition through MIR spectroscopy and MIR spectra were stored. Milk TAA was then predicted (pTAA) from the stored milk MIR spectra (111,653 test-day records of 9519 cows in 344 herds) using the previously developed prediction model; considering the prediction accuracy, pTAA might be considered a proxy of the TAA determined through the reference method. Overall, pTAA averaged 7.16 mmoL/L of Trolox equivalents, showed a nadir around 40 days after calving and increased thereafter, following a linear trend up to the end of lactation. The lowest pTAA was observed in milk sampled from June to September. Milk pTAA was heritable (0.401 ± 0.015) and genetically associated to fat yield (0.366 ± 0.049), crude protein (CP) yield (0.238 ± 0.052), fat percentage (0.616 ± 0.022) and CP percentage (0.754 ± 0.015). The official selection index of Italian Holstein put the 49% of the emphasis on fat and protein yield and percentage; therefore, it derives that an indirect favourable selection for milk pTAA should be already in progress in Italian Holstein population.
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Affiliation(s)
- Giovanni Niero
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell’Università 16, 35020 Padova, Italy; (G.N.); (M.F.); (M.C.); (M.D.M.); (M.P.)
| | - Angela Costa
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell’Università 16, 35020 Padova, Italy; (G.N.); (M.F.); (M.C.); (M.D.M.); (M.P.)
- Correspondence: ; Tel.: +39-049-8272632
| | - Marco Franzoi
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell’Università 16, 35020 Padova, Italy; (G.N.); (M.F.); (M.C.); (M.D.M.); (M.P.)
| | - Giulio Visentin
- Department of Veterinary Medical Sciences (DIMEVET), Alma Mater Studiorum—University of Bologna, Via Tolara di Sopra 50, 40064 Bologna, Italy;
| | - Martino Cassandro
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell’Università 16, 35020 Padova, Italy; (G.N.); (M.F.); (M.C.); (M.D.M.); (M.P.)
| | - Massimo De Marchi
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell’Università 16, 35020 Padova, Italy; (G.N.); (M.F.); (M.C.); (M.D.M.); (M.P.)
| | - Mauro Penasa
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Viale dell’Università 16, 35020 Padova, Italy; (G.N.); (M.F.); (M.C.); (M.D.M.); (M.P.)
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15
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Zanon T, Costa A, De Marchi M, Penasa M, Koenig S, Gauly M. Milk yield and quality of Original Brown cattle reared in Italian alpine region. ITALIAN JOURNAL OF ANIMAL SCIENCE 2020. [DOI: 10.1080/1828051x.2020.1825997] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Affiliation(s)
- Thomas Zanon
- Facoltà 0di Scienze e Tecnologie, Free University of Bolzano, Bolzano, Italy
| | - Angela Costa
- Dipartimento di Agronomia, Animali, Alimenti, Risorse naturali e Ambiente, University of Padova, Legnaro, Italy
| | - Massimo De Marchi
- Dipartimento di Agronomia, Animali, Alimenti, Risorse naturali e Ambiente, University of Padova, Legnaro, Italy
| | - Mauro Penasa
- Dipartimento di Agronomia, Animali, Alimenti, Risorse naturali e Ambiente, University of Padova, Legnaro, Italy
| | - Sven Koenig
- Institut für Tierzucht und Haustiergenetik, Justus-Liebig University Giessen, Giessen, Germany
| | - Matthias Gauly
- Facoltà 0di Scienze e Tecnologie, Free University of Bolzano, Bolzano, Italy
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16
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Duchemin SI, Nilsson K, Fikse WF, Stålhammar H, Buhelt Johansen L, Stenholdt Hansen M, Lindmark-Månsson H, de Koning DJ, Paulsson M, Glantz M. Genetic parameters for noncoagulating milk, milk coagulation properties, and detailed milk composition in Swedish Red Dairy Cattle. J Dairy Sci 2020; 103:8330-8342. [PMID: 32600755 DOI: 10.3168/jds.2020-18315] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2020] [Accepted: 04/21/2020] [Indexed: 12/23/2022]
Abstract
The rennet-induced coagulation ability of milk is important in cheese production. For Swedish Red Dairy Cattle (RDC), this ability is reduced because of a high prevalence of noncoagulating (NC) milk. In this study, we simultaneously combined genetic parameters for NC milk, milk coagulation properties, milk composition, physical traits, and milk protein composition. Our aim was to estimate heritability and genetic and phenotypic correlations for NC milk and 24 traits (milk coagulation properties, milk composition, physical traits, and milk protein composition). Phenotypes and ∼7,000 SNP genotypes were available for all 600 Swedish RDC. The genotypes were imputed from ∼7,000 SNP to 50,000 SNP. Variance components and genetic parameters were estimated with an animal model. In Swedish RDC, a moderate heritability estimate of 0.28 was found for NC milk. For the other 24 traits, heritability estimates ranged from 0.12 to 0.77 (standard errors from 0.08 to 0.18). A total of 300 phenotypic and genetic correlations were estimated. For phenotypic and genetic correlations, 172 and 95 were significant, respectively. In general, most traits showing significant genetic correlations also showed significant phenotypic correlations. In this study, phenotypic and genetic correlations with NC milk suggest that many correlations between traits exist, making it difficult to predict the real consequences on the composition of milk, if selective breeding is applied on NC milk. We speculate that some of these consequences may lead to changes in the composition of milk, most likely affecting its physical and organoleptic properties. However, our results suggest that κ-casein could be used as an indicator trait to predict the occurrence of NC milk at the herd level.
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Affiliation(s)
- S I Duchemin
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, PO Box 7023, SE-750 07 Uppsala, Sweden.
| | - K Nilsson
- Department of Food Technology, Engineering and Nutrition, Lund University, PO Box 124, SE-221 00, Lund, Sweden
| | - W F Fikse
- Växa Sverige, PO Box 288, SE-751 05 Uppsala, Sweden
| | - H Stålhammar
- Viking Genetics, PO Box 64, SE-532 21, Skara, Sweden
| | | | | | - H Lindmark-Månsson
- Department of Food Technology, Engineering and Nutrition, Lund University, PO Box 124, SE-221 00, Lund, Sweden
| | - D-J de Koning
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, PO Box 7023, SE-750 07 Uppsala, Sweden
| | - M Paulsson
- Department of Food Technology, Engineering and Nutrition, Lund University, PO Box 124, SE-221 00, Lund, Sweden
| | - M Glantz
- Department of Food Technology, Engineering and Nutrition, Lund University, PO Box 124, SE-221 00, Lund, Sweden
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17
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Tiplady KM, Lopdell TJ, Littlejohn MD, Garrick DJ. The evolving role of Fourier-transform mid-infrared spectroscopy in genetic improvement of dairy cattle. J Anim Sci Biotechnol 2020; 11:39. [PMID: 32322393 PMCID: PMC7164258 DOI: 10.1186/s40104-020-00445-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Accepted: 03/09/2020] [Indexed: 11/22/2022] Open
Abstract
Over the last 100 years, significant advances have been made in the characterisation of milk composition for dairy cattle improvement programs. Technological progress has enabled a shift from labour intensive, on-farm collection and processing of samples that assess yield and fat levels in milk, to large-scale processing of samples through centralised laboratories, with the scope extended to include quantification of other traits. Fourier-transform mid-infrared (FT-MIR) spectroscopy has had a significant role in the transformation of milk composition phenotyping, with spectral-based predictions of major milk components already being widely used in milk payment and animal evaluation systems globally. Increasingly, there is interest in analysing the individual FT-MIR wavenumbers, and in utilising the FT-MIR data to predict other novel traits of importance to breeding programs. This includes traits related to the nutritional value of milk, the processability of milk into products such as cheese, and traits relevant to animal health and the environment. The ability to successfully incorporate these traits into breeding programs is dependent on the heritability of the FT-MIR predicted traits, and the genetic correlations between the FT-MIR predicted and actual trait values. Linking FT-MIR predicted traits to the underlying mutations responsible for their variation can be difficult because the phenotypic expression of these traits are a function of a diverse range of molecular and biological mechanisms that can obscure their genetic basis. The individual FT-MIR wavenumbers give insights into the chemical composition of milk and provide an additional layer of granularity that may assist with establishing causal links between the genome and observed phenotypes. Additionally, there are other molecular phenotypes such as those related to the metabolome, chromatin accessibility, and RNA editing that could improve our understanding of the underlying biological systems controlling traits of interest. Here we review topics of importance to phenotyping and genetic applications of FT-MIR spectra datasets, and discuss opportunities for consolidating FT-MIR datasets with other genomic and molecular data sources to improve future dairy cattle breeding programs.
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Affiliation(s)
- K M Tiplady
- 1Research and Development, Livestock Improvement Corporation, Private Bag 3016, Hamilton, 3240 New Zealand.,2School of Agriculture, Massey University, Ruakura, Hamilton, 3240 New Zealand
| | - T J Lopdell
- 1Research and Development, Livestock Improvement Corporation, Private Bag 3016, Hamilton, 3240 New Zealand
| | - M D Littlejohn
- 1Research and Development, Livestock Improvement Corporation, Private Bag 3016, Hamilton, 3240 New Zealand.,2School of Agriculture, Massey University, Ruakura, Hamilton, 3240 New Zealand
| | - D J Garrick
- 2School of Agriculture, Massey University, Ruakura, Hamilton, 3240 New Zealand
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