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Magro S, Sneddon NW, Costa A, Chiarin E, Penasa M, De Marchi M. Does the age of milk affect its mid-infrared spectrum and predictions? Food Chem 2024; 441:138355. [PMID: 38219360 DOI: 10.1016/j.foodchem.2024.138355] [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: 09/18/2023] [Revised: 12/15/2023] [Accepted: 01/01/2024] [Indexed: 01/16/2024]
Abstract
Milk of dairy species commonly undergo standardized official analyses, these that may require chemical preservation and transportation to a certified laboratory. In this context, storage duration is an important factor that can potential affect both milk chemical analyses and its mid-infrared spectrum. We analysed milk samples at different time points/ages to assess repeatability and reproducibility of mid-infrared predicted traits (e.g., fat and protein). Using spectral data, we also evaluated the ability of spectroscopy coupled with chemometrics to discriminate samples according to their age. Although the main components of milk remained consistently reproducible across age (days), changes in the spectrum due to sample aging and deterioration of the matrix were detectable. Using a discriminant analysis, we achieved a classification accuracy of 77% in validation. Predicting milk age using mid-infrared spectra is feasible, allowing for sample monitoring within circuits where maximum reliability is needed, e.g., bulk or individual milk samples for legal/official use or payment systems.
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Affiliation(s)
- S Magro
- Department of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy
| | - N W Sneddon
- School of Agriculture and Environment, Massey University, Private Bag 11 222, Palmerston North 4442, New Zealand
| | - A Costa
- Department of Veterinary Medical Sciences, University of Bologna, Via Tolara di Sopra 43, 40064 Ozzano dell'Emilia (BO), Italy.
| | - E Chiarin
- Department of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova, Viale dell'Università 16, 35020 Legnaro (PD), Italy
| | - M Penasa
- 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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2
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Atashi H, Chen Y, Wilmot H, Bastin C, Vanderick S, Hubin X, Gengler N. Single-step genome-wide association analyses for selected infrared-predicted cheese-making traits in Walloon Holstein cows. J Dairy Sci 2023; 106:7816-7831. [PMID: 37567464 DOI: 10.3168/jds.2022-23206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Accepted: 05/01/2023] [Indexed: 08/13/2023]
Abstract
This study aimed to perform genome-wide association study to identify genomic regions associated with milk production and cheese-making properties (CMP) in Walloon Holstein cows. The studied traits were milk yield, fat percentage, protein percentage, casein percentage (CNP), calcium content, somatic cell score (SCS), coagulation time, curd firmness after 30 min from rennet addition, and titratable acidity. The used data have been collected from 2014 to 2020 on 78,073 first-parity (485,218 test-day records), 48,766 second-parity (284,942 test-day records), and 21,948 third-parity (105,112 test-day records) Holstein cows distributed in 671 herds in the Walloon Region of Belgium. Data of 565,533 single nucleotide polymorphisms (SNP), located on 29 Bos taurus autosomes (BTA) of 6,617 animals (1,712 males), were used. Random regression test-day models were used to estimate genetic parameters through the Bayesian Gibbs sampling method. The SNP solutions were estimated using a single-step genomic BLUP approach. The proportion of the total additive genetic variance explained by windows of 50 consecutive SNPs (with an average size of ∼216 KB) was calculated, and regions accounting for at least 1.0% of the total additive genetic variance were used to search for positional candidate genes. Heritability estimates for the studied traits ranged from 0.10 (SCS) to 0.53 (CNP), 0.10 (SCS) to 0.50 (CNP), and 0.12 (SCS) to 0.49 (CNP) in the first, second, and third parity, respectively. Genome-wide association analyses identified 6 genomic regions (BTA1, BTA14 [4 regions], and BTA20) associated with the considered traits. Genes including the SLC37A1 (BTA1), SHARPIN, MROH1, DGAT1, FAM83H, TIGD5, MROH6, NAPRT, ADGRB1, GML, LYPD2, JRK (BTA14), and TRIO (BTA20) were identified as positional candidate genes for the studied CMP. The findings of this study help to unravel the genomic background of a cow's ability for cheese production and can be used for the future implementation and use of genomic evaluation to improve the cheese-making traits in Walloon Holstein cows.
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Affiliation(s)
- H Atashi
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium; Department of Animal Science, Shiraz University, 71441-13131 Shiraz, Iran.
| | - Y Chen
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium
| | - H Wilmot
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium; National Fund for Scientific Research (FRS-FNRS), 1000 Brussels, Belgium
| | - C Bastin
- National Fund for Scientific Research (FRS-FNRS), 1000 Brussels, Belgium
| | - S Vanderick
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium
| | - X Hubin
- Elevéo asbl Awé Group, 5590 Ciney, Belgium
| | - N Gengler
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium
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3
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Cole J, Makanjuola B, Rochus C, van Staaveren N, Baes C. The effects of breeding and selection on lactation in dairy cattle. Anim Front 2023; 13:55-63. [PMID: 37324206 PMCID: PMC10266753 DOI: 10.1093/af/vfad044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/17/2023] Open
Affiliation(s)
- John B Cole
- URUS Group LP, Madison, WI 53718
- Department of Animal Sciences, University of Florida, Gainesville
- Department of Animal Science, North Carolina State University, Raleigh
| | - Bayode O Makanjuola
- Centre for Genetic Improvement of Livestock, University of Guelph, N1G 2W4, Canada
| | - Christina M Rochus
- Centre for Genetic Improvement of Livestock, University of Guelph, N1G 2W4, Canada
| | - Nienke van Staaveren
- Centre for Genetic Improvement of Livestock, University of Guelph, N1G 2W4, Canada
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4
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Nakov G, Trajkovska B, Atanasova-Pancevska N, Daniloski D, Ivanova N, Lučan Čolić M, Jukić M, Lukinac J. The Influence of the Addition of Hemp Press Cake Flour on the Properties of Bovine and Ovine Yoghurts. Foods 2023; 12:foods12050958. [PMID: 36900475 PMCID: PMC10001388 DOI: 10.3390/foods12050958] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Revised: 02/21/2023] [Accepted: 02/22/2023] [Indexed: 03/12/2023] Open
Abstract
Hemp press cake flour (HPCF) is a by-product of hemp oil production rich in proteins, carbohydrates, minerals, vitamins, oleochemicals, and phytochemicals. The purpose of this study was to investigate how the addition of HPCF to bovine and ovine plain yoghurts at concentrations of 0%, 2%, 4%, 6%, 8%, and 10% could change the physicochemical, microbiological, and sensory properties of the yoghurts, focusing on the improvement of quality and antioxidant activity, and the issue of food by-products and their utilisation. The results showed that the addition of HPCF to yoghurts significantly affected their properties, including an increase in pH and decrease in titratable acidity, change in colour to darker, reddish or yellowish hue, and a rise in total polyphenols and antioxidant activity during storage. Yoghurts fortified with 4% and 6% HPCF exhibited the best sensory properties, thus maintaining viable starter counts in the yoghurts during the study period. There were no statistically significant differences between the control yoghurts and the samples with 4% added HPCF in terms of overall sensory score while maintaining viable starter counts during the seven-day storage. These results suggest that the addition of HPCF to yoghurts can improve product quality and create functional products and may have potential in sustainable food waste management.
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Affiliation(s)
- Gjore Nakov
- College of Sliven, Technical University of Sofia, 59 Bourgasko Shaussee Blvd., 8800 Sliven, Bulgaria
| | - Biljana Trajkovska
- Faculty of Biotechnical Sciences, University “St. Kliment Ohridski”, 7000 Bitola, North Macedonia
| | - Natalija Atanasova-Pancevska
- Faculty of Natural Sciences and Mathematics-Skopje, Department of Microbiology and Microbial Biotechnology, Ss. Cyril and Methodius University in Skopje, 1000 Skopje, North Macedonia
| | - Davor Daniloski
- Advanced Food Systems Research Unit, Institute for Sustainable Industries and Liveable Cities, College of Health and Biomedicine, Victoria University, Melbourne, VIC 8001, Australia
- Teagasc Food Research Centre, Food Chemistry and Technology Department, Moorepark, Fermoy, P61 C996 Cork, Ireland
| | - Nastia Ivanova
- College of Sliven, Technical University of Sofia, 59 Bourgasko Shaussee Blvd., 8800 Sliven, Bulgaria
| | - Mirela Lučan Čolić
- Faculty of Food Technology Osijek, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia
| | - Marko Jukić
- Faculty of Food Technology Osijek, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia
- Correspondence: ; Tel.: +385-31224308
| | - Jasmina Lukinac
- Faculty of Food Technology Osijek, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia
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5
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Development of a gallic acid based time temperature indicator with adjustable activation energy. Food Control 2023. [DOI: 10.1016/j.foodcont.2022.109396] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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6
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Hayes E, Greene D, O’Donnell C, O’Shea N, Fenelon MA. Spectroscopic technologies and data fusion: Applications for the dairy industry. Front Nutr 2023; 9:1074688. [PMID: 36712542 PMCID: PMC9875022 DOI: 10.3389/fnut.2022.1074688] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 12/05/2022] [Indexed: 01/12/2023] Open
Abstract
Increasing consumer awareness, scale of manufacture, and demand to ensure safety, quality and sustainability have accelerated the need for rapid, reliable, and accurate analytical techniques for food products. Spectroscopy, coupled with Artificial Intelligence-enabled sensors and chemometric techniques, has led to the fusion of data sources for dairy analytical applications. This article provides an overview of the current spectroscopic technologies used in the dairy industry, with an introduction to data fusion and the associated methodologies used in spectroscopy-based data fusion. The relevance of data fusion in the dairy industry is considered, focusing on its potential to improve predictions for processing traits by chemometric techniques, such as principal component analysis (PCA), partial least squares regression (PLS), and other machine learning algorithms.
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Affiliation(s)
- Elena Hayes
- University College Dublin (UCD) School of Biosystems and Food Engineering, University College Dublin, Dublin, Ireland,Teagasc Food Research Centre, Moorepark, Fermoy, Ireland
| | - Derek Greene
- University College Dublin (UCD) School of Computer Science, University College Dublin, Dublin, Ireland
| | - Colm O’Donnell
- University College Dublin (UCD) School of Biosystems and Food Engineering, University College Dublin, Dublin, Ireland
| | - Norah O’Shea
- Teagasc Food Research Centre, Moorepark, Fermoy, Ireland
| | - Mark A. Fenelon
- University College Dublin (UCD) School of Biosystems and Food Engineering, University College Dublin, Dublin, Ireland,Teagasc Food Research Centre, Moorepark, Fermoy, Ireland,*Correspondence: Mark A. Fenelon,
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7
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Atashi H, Bastin C, Wilmot H, Vanderick S, Hubin X, Gengler N. Genome-wide association study for selected cheese-making properties in Dual-Purpose Belgian Blue cows. J Dairy Sci 2022; 105:8972-8988. [PMID: 36175238 DOI: 10.3168/jds.2022-21780] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Accepted: 06/21/2022] [Indexed: 01/05/2023]
Abstract
This study aimed to estimate genetic parameters and identify genomic region(s) associated with selected cheese-making properties (CMP) in Dual-Purpose Belgian Blue (DPBB) cows. Edited data were 46,301 test-day records of milk yield, fat percentage, protein percentage, casein percentage, milk calcium content (CC), coagulation time (CT), curd firmness after 30 min from rennet addition (a30), and milk titratable acidity (MTA) collected from 2014 to 2020 on 4,077 first-parity (26,027 test-day records), and 3,258 second-parity DPBB cows (20,274 test-day records) distributed in 124 herds in the Walloon Region of Belgium. Data of 28,266 SNP, located on 29 Bos taurus autosomes (BTA) of 1,699 animals were used. Random regression test-day models were used to estimate genetic parameters through the Bayesian Gibbs sampling method. The SNP solutions were estimated using a single-step genomic BLUP approach. The proportion of the total additive genetic variance explained by windows of 25 consecutive SNPs (with an average size of ∼2 Mb) was calculated, and regions accounting for at least 1.0% of the total additive genetic variance were used to search for candidate genes. Heritability estimates for the included CMP ranged from 0.19 (CC) to 0.50 (MTA), and 0.24 (CC) to 0.41 (MTA) in the first and second parity, respectively. The genetic correlation estimated between CT and a30 varied from -0.61 to -0.41 and from -0.55 to -0.38 in the first and second lactations, respectively. Negative genetic correlations were found between CT and milk yield and composition, while those estimated between curd firmness and milk composition were positive. Genome-wide association analyses results identified 4 genomic regions (BTA1, BTA3, BTA7, and BTA11) associated with the considered CMP. The identified genomic regions showed contrasting results between parities and among the different stages of each parity. It suggests that different sets of candidate genes underlie the phenotypic expression of the considered CMP between parities and lactation stages of each parity. The findings of this study can be used for future implementation and use of genomic evaluation to improve the cheese-making traits in DPBB cows.
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Affiliation(s)
- H Atashi
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium; Department of Animal Science, Shiraz University, 71441-65186 Shiraz, Iran.
| | - C Bastin
- Walloon Breeders Association, 5590 Ciney, Belgium
| | - H Wilmot
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium; National Fund for Scientific Research (FRS-FNRS), Rue d'Egmont 5, B-1000 Brussels, Belgium
| | - S Vanderick
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium
| | - X Hubin
- Walloon Breeders Association, 5590 Ciney, Belgium
| | - N Gengler
- TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium
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8
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Correddu F, Gaspa G, Cesarani A, Macciotta NPP. Phenotypic and genetic characterization of the occurrence of noncoagulating milk in dairy sheep. J Dairy Sci 2022; 105:6773-6782. [PMID: 35840399 DOI: 10.3168/jds.2021-21661] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Accepted: 04/25/2022] [Indexed: 11/19/2022]
Abstract
Milk coagulation ability is of central importance for the sheep dairy industry because almost all sheep milk is destined for cheese processing. The occurrence of milk with impaired coagulation properties is an obstacle to cheese processing and, in turn, to the profitability of the dairy companies. In this work, we investigated the causes of noncoagulation of sheep milk; specifically, we studied the effect of milk physicochemical properties on milk coagulation status [coagulating and noncoagulating (NC) milk samples, which do or do not coagulate within 30 min, respectively], and whether mid-infrared spectroscopy (MIR) could be used to assess variability in coagulation status. We also investigated the genetic background of milk coagulation ability. Individual milk samples were collected from 996 Sarda ewes farmed in 47 flocks located in Sardinia (Italy). Considered traits were daily milk yield, milk composition traits, and milk coagulation properties (rennet coagulation time, curd firming time, and curd firmness), and MIR spectra were acquired. About 9% of samples did not coagulate within 30 min. A logistic regression approach was used to test the effect of milk-related traits on milk coagulation status. A principal component (PC) analysis was carried out on the milk MIR spectra, and PC scores were then used as covariates in a logistic regression model to assess their relationship with milk coagulation status. Results of the present work demonstrated that the probability of having NC samples increases as milk contents of proteins and chlorides and somatic cell score increase. The analysis of PC extracted from milk spectra that influenced coagulation status highlighted key regions associated with lactose and protein concentrations, and others not associated with routinely collected milk composition traits. These results suggest that the occurrence of NC is mostly related to damage of the epithelium secretory mammary cells, which occurs with the advancement of a lactation or due to unhealthy mammary gland status. Genetic analysis of milk coagulation status and of the extracted PC confirmed the genetic background of the milk coagulability of sheep milk.
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Affiliation(s)
- F Correddu
- Department of Agricultural Sciences, University of Sassari, 07100 Sassari, Italy.
| | - G Gaspa
- Department of Agricultural, Forestry and Alimentary Sciences, University of Torino, 10095 Grugliasco, Italy
| | - A Cesarani
- Department of Agricultural Sciences, University of Sassari, 07100 Sassari, Italy
| | - N P P Macciotta
- Department of Agricultural Sciences, University of Sassari, 07100 Sassari, Italy
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Liburdi K, Cucci S, Esti M. Oilseed Extracts from Local Markets as Promising Coagulant Agents for Milk from Various Mammalian Species. Foods 2022; 11:foods11142137. [PMID: 35885380 PMCID: PMC9317146 DOI: 10.3390/foods11142137] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Revised: 07/11/2022] [Accepted: 07/12/2022] [Indexed: 12/10/2022] Open
Abstract
The aim of this study was to identify novel milk coagulants to be used in cheesemaking. For this purpose, aqueous extracts from safflower (Carthamus tinctorius), sunflower (Helianthus annuus), flax (Linum usitatissimum) and sesame (Sesamum indicum) seeds were tested for their caseinolytic (CA) and milk coagulating properties (MCA) in skim milk at temperatures of 25, 37, 50, 65 and 80 °C. The seed oil samples with the highest temperature ranges in regard to coagulation efficiency were then tested in cow, buffalo, goat and sheep milks and the MCA and curd yield (CY) parameters were measured at different temperatures. Due to their high milk coagulation efficiency (CE) in all types of milk and at different temperatures, the sesame and sunflower seed extracts proved to be particularly interesting and their CY parameters were similar to those obtained with animal rennet. Moreover, our results confirm that oilseed coagulants are capable of coagulating milk and can also be considered as potential animal rennet substitutes. This study provides valuable insights into the development of potential vegetable coagulants that could be used for various production processes aimed at specific target consumers.
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Xiao S, Wang Q, Li C, Liu W, Zhang J, Fan Y, Su J, Wang H, Luo X, Zhang S. Rapid identification of A1 and A2 milk based on the combination of mid-infrared spectroscopy and chemometrics. Food Control 2022. [DOI: 10.1016/j.foodcont.2021.108659] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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11
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Challenging Sustainable and Innovative Technologies in Cheese Production: A Review. Processes (Basel) 2022. [DOI: 10.3390/pr10030529] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
It is well known that cheese yield and quality are affected by animal genetics, milk quality (chemical, physical, and microbiological), production technology, and the type of rennet and dairy cultures used in production. Major differences in the same type of cheese (i.e., hard cheese) are caused by the rennet and dairy cultures, which affect the ripening process. This review aims to explore current technological advancements in animal genetics, methods for the isolation and production of rennet and dairy cultures, along with possible applications of microencapsulation in rennet and dairy culture production, as well as the challenge posed to current dairy technologies by the preservation of biodiversity. Based on the reviewed scientific literature, it can be concluded that innovative approaches and the described techniques can significantly improve cheese production.
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12
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Application of Optical Quality Control Technologies in the Dairy Industry: An Overview. PHOTONICS 2021. [DOI: 10.3390/photonics8120551] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Sustainable development of the agricultural industry, in particular, the production of milk and feed for farm animals, requires accurate, fast, and non-invasive diagnostic tools. Currently, there is a rapid development of a number of analytical methods and approaches that meet these requirements. Infrared spectrometry in the near and mid-IR range is especially widespread. Progress has been made not only in the physical methods of carrying out measurements, but significant advances have also been achieved in the development of mathematical processing of the received signals. This review is devoted to the comparison of modern methods and devices used to control the quality of milk and feed for farm animals.
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Manuelian CL, Vigolo V, Righi F, Simoni M, Burbi S, De Marchi M. MIR and Vis/NIR spectroscopy cannot authenticate organic bulk milk. ITALIAN JOURNAL OF ANIMAL SCIENCE 2021. [DOI: 10.1080/1828051x.2021.1954559] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Affiliation(s)
- Carmen L. Manuelian
- Dipartimento di Agronomia, Animali, Alimenti, Risorse Naturali e Ambiente, University of Padova, Legnaro, Italy
| | - Vania Vigolo
- Dipartimento di Agronomia, Animali, Alimenti, Risorse Naturali e Ambiente, University of Padova, Legnaro, Italy
| | - Federico Righi
- Dipartimento di Scienze Medico-Veterinarie, University of Parma, Parma, Italy
| | - Marica Simoni
- Dipartimento di Scienze Medico-Veterinarie, University of Parma, Parma, Italy
| | - Sara Burbi
- Centre for Agroecology, Water and Resilience, Coventry University, Ryton-on-Dunsmore, UK
| | - Massimo De Marchi
- Dipartimento di Agronomia, Animali, Alimenti, Risorse Naturali e Ambiente, University of Padova, Legnaro, Italy
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14
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Du C, Nan L, Li C, Sabek A, Wang H, Luo X, Su J, Hua G, Ma Y, Zhang S. Influence of Estrus on the Milk Characteristics and Mid-Infrared Spectra of Dairy Cows. Animals (Basel) 2021; 11:ani11051200. [PMID: 33921998 PMCID: PMC8143516 DOI: 10.3390/ani11051200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Revised: 04/08/2021] [Accepted: 04/19/2021] [Indexed: 11/26/2022] Open
Abstract
Simple Summary Some studies have confirmed the variation in milk profiles when dairy cows show estrus. However, only a few milk components, such as fat, protein, and lactose, have been investigated so far, and thus any changes in the many other parts of milk’s composition due to estrus are unknown. Milk mid-infrared (MIR) spectra consist of wavenumbers, which provide insight into the chemical composition of milk. The MIR spectrum reflects the global composition of milk, but this information is currently underused. In this study, we considered MIR wavenumbers as traits, and directly studied the spectral information as a way to study the estrus of dairy cows linked to milk composition. This research provides a deeper understanding of the milk MIR spectrum and may lead to new approaches for estrus detection in dairy cows from routine milk analysis, thereby guiding an opportune insemination time. Abstract Milk produced by dairy cows is a complex combination of many components. However, at present, changes in only a few milk components (e.g., fat, protein, and lactose) during the estrus cycle in dairy cows have been documented. Mid-infrared (MIR) spectroscopy is a worldwide method routinely used for milk analysis, as MIR spectra reflect the global composition of milk. Therefore, this study aimed to investigate the changes in milk MIR spectra and milk production traits (fat, protein, lactose, urea, total solids (TS), and solid not fat (SnF)) due to estrus. Cows that were successfully inseminated, leading to conception, were included. Cows confirmed to be pregnant were considered to be in estrus at the day of insemination (day 0). A general linear mixed model, which included the random effect of cows, the fixed classification effects of parity number, days in relation to estrus, as well as the interaction between parity number and days in relation to estrus, was applied to investigate the changes in milk production traits and 1060 milk infrared wavenumbers, ranging from 925 to 5011 cm−1, of 371 records from 162 Holstein cows on the days before (day −3, day −2, and day −1) and on the day of estrus (day 0). The days in relation to estrus had a significant effect on fat, protein, urea, TS, and SnF, whose contents increased from day −3 to day 0. Lactose did not seem to be significantly influenced by the occurrence of estrus. The days in relation to estrus had significant effects on the majority of the wavenumbers. Besides, we found that some of the wavenumbers in the water absorption regions were significantly changed on the days before and on the day of estrus. This suggests that these wavenumbers may contain useful information. In conclusion, the changes in the milk composition due to estrus can be observed through the analysis of the milk MIR spectrum. Further analyses are warranted to more deeply explore the potential use of milk MIR spectra in the detection of estrus.
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Affiliation(s)
- Chao Du
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China; (C.D.); (L.N.); (A.S.); (H.W.); (X.L.); (J.S.); (G.H.)
| | - Liangkang Nan
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China; (C.D.); (L.N.); (A.S.); (H.W.); (X.L.); (J.S.); (G.H.)
| | - Chunfang Li
- Hebei Livestock Breeding Station, Shijiazhuang 050000, China; (C.L.); (Y.M.)
| | - Ahmed Sabek
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China; (C.D.); (L.N.); (A.S.); (H.W.); (X.L.); (J.S.); (G.H.)
- Department of Veterinary Hygiene and Management, Faculty of Veterinary Medicine, Benha University, Moshtohor 13736, Egypt
| | - Haitong Wang
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China; (C.D.); (L.N.); (A.S.); (H.W.); (X.L.); (J.S.); (G.H.)
| | - Xuelu Luo
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China; (C.D.); (L.N.); (A.S.); (H.W.); (X.L.); (J.S.); (G.H.)
| | - Jundong Su
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China; (C.D.); (L.N.); (A.S.); (H.W.); (X.L.); (J.S.); (G.H.)
| | - Guohua Hua
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China; (C.D.); (L.N.); (A.S.); (H.W.); (X.L.); (J.S.); (G.H.)
| | - Yabing Ma
- Hebei Livestock Breeding Station, Shijiazhuang 050000, China; (C.L.); (Y.M.)
| | - Shujun Zhang
- Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China; (C.D.); (L.N.); (A.S.); (H.W.); (X.L.); (J.S.); (G.H.)
- Correspondence: or
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15
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Abstract
Table grape quality is of importance for consumers and thus for producers. Its objective quality is usually determined by destructive methods mainly based on sugar content. This study proposed to evaluate the possibility of hyperspectral imaging to characterize table grapes quality through its sugar (TSS), total flavonoid (TF), and total anthocyanin (TA) contents. Different data pre-treatments (WD, SNV, and 1st and 2nd derivative) and different methods were tested to get the best prediction models: PLS with full spectra and then Multiple Linear Regression (MLR) were realized after selecting the optimal wavelengths thanks to the regression coefficients (β-coefficients) and the Variable Importance in Projection (VIP) scores. All models were good at showing that hyperspectral imaging is a relevant method to predict sugar, total flavonoid, and total anthocyanin contents. The best predictions were obtained from optimal wavelength selection based on β-coefficients for TSS and from VIPs optimal wavelength windows using SNV pre-treatment for total flavonoid and total anthocyanin content. Thus, good prediction models were proposed in order to characterize grapes while reducing the data sets and limit the data storage to enable an industrial use.
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16
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Niero G, Bobbo T, Callegaro S, Visentin G, Pornaro C, Penasa M, Cozzi G, De Marchi M, Cassandro M. Dairy Cows' Health during Alpine Summer Grazing as Assessed by Milk Traits, Including Differential Somatic Cell Count: A Case Study from Italy. Animals (Basel) 2021; 11:ani11040981. [PMID: 33915759 PMCID: PMC8067137 DOI: 10.3390/ani11040981] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Revised: 02/07/2021] [Accepted: 03/25/2021] [Indexed: 11/23/2022] Open
Abstract
Simple Summary Dairy herds in alpine areas usually adopt summer grazing, mainly to reduce feeding costs. This practice is related to the maintenance of local traditions and to the manufacturing of niche dairy products. However, it is important to assess the impact of this practice on cattle health. This case study investigated how milk-related health traits vary across extensive grazing during the summer period, using data collected in a dairy herd whose cows were repeatedly controlled for individual milk samples. Although the transition from barn farming to pasture led to a reduction in milk production, proper grazing management can make dairy cows more resilient in terms of udder health and metabolic efficiency. Findings of the present research report suggested that pasture can be adopted to maintain dairy herd sustainability without impairing animal health. Abstract Extensive summer grazing is a dairy herd management practice frequently adopted in mountainous areas. Nowadays, this activity is threatened by its high labour demand, but it is fundamental for environmental, touristic and economic implications, as well as for the preservation of social and cultural traditions. Scarce information on the effects of such low-input farming systems on cattle health is available. Therefore, the present case study aimed at investigating how grazing may affect the health status of dairy cows by using milk traits routinely available from the national milk recording scheme. The research involved a dairy herd of 52 Simmental and 19 Holstein × Simmental crossbred cows. The herd had access to the pasture according to a rotational grazing scheme from late spring up to the end of summer. A total of 616 test day records collected immediately before and during the grazing season were used. Individual milk yield was registered during the milking procedure. Milk samples were analysed for composition (fat, protein, casein and lactose contents) and health-related milk indicators (electrical conductivity, urea and β-hydroxybutyrate) using mid-infrared spectroscopy. Somatic cell count (SCC) and differential SCC were also determined. Data were analysed with a linear mixed model, which included the fixed effects of the period of sampling, cow breed, stage of lactation and parity, and the random effects of cow nested within breed and the residual. The transition from barn farming to pasture had a negative effect on milk yield, together with a small deterioration of fat and protein percentages. Health-related milk indicators showed a minor deterioration of the fat to protein ratio, differential SCC and electrical conductivity, particularly towards the end of the grazing season, whereas the somatic cell score and β-hydroxybutyrate were relatively constant. Overall, the study showed that, when properly managed, pasture grazing does not have detrimental effects on dairy cows in terms of udder health and efficiency. Therefore, the proper management of cows on pasture can be a valuable solution to preserve the economic, social and environmental sustainability of small dairy farms in the alpine regions, without impairing cows’ health.
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Affiliation(s)
- Giovanni Niero
- Department of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova, Viale dell’Università 16, 35020 Legnaro, Italy; (G.N.); (T.B.); (S.C.); (C.P.); (M.P.); (M.D.M.); (M.C.)
| | - Tania Bobbo
- Department of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova, Viale dell’Università 16, 35020 Legnaro, Italy; (G.N.); (T.B.); (S.C.); (C.P.); (M.P.); (M.D.M.); (M.C.)
| | - Simone Callegaro
- Department of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova, Viale dell’Università 16, 35020 Legnaro, Italy; (G.N.); (T.B.); (S.C.); (C.P.); (M.P.); (M.D.M.); (M.C.)
| | - Giulio Visentin
- Department of Veterinary Medical Sciences, Alma Mater Studiorum University of Bologna, Via Tolara di Sopra 50, 40064 Ozzano dell’Emilia, Italy
- Correspondence: ; Tel.: +39-051-20-97047
| | - Cristina Pornaro
- Department of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova, Viale dell’Università 16, 35020 Legnaro, Italy; (G.N.); (T.B.); (S.C.); (C.P.); (M.P.); (M.D.M.); (M.C.)
| | - Mauro Penasa
- Department of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova, Viale dell’Università 16, 35020 Legnaro, Italy; (G.N.); (T.B.); (S.C.); (C.P.); (M.P.); (M.D.M.); (M.C.)
| | - Giulio Cozzi
- Department of Animal Medicine, Production and Health, University of Padova, Viale dell’Università 16, 35020 Legnaro, Italy;
| | - Massimo De Marchi
- Department of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova, Viale dell’Università 16, 35020 Legnaro, Italy; (G.N.); (T.B.); (S.C.); (C.P.); (M.P.); (M.D.M.); (M.C.)
| | - Martino Cassandro
- Department of Agronomy, Food, Natural Resources, Animals and Environment, University of Padova, Viale dell’Università 16, 35020 Legnaro, Italy; (G.N.); (T.B.); (S.C.); (C.P.); (M.P.); (M.D.M.); (M.C.)
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17
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Bahadi M, Ismail AA, Vasseur E. Fourier Transform Infrared Spectroscopy as a Tool to Study Milk Composition Changes in Dairy Cows Attributed to Housing Modifications to Improve Animal Welfare. Foods 2021; 10:foods10020450. [PMID: 33670588 PMCID: PMC7922570 DOI: 10.3390/foods10020450] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 02/10/2021] [Accepted: 02/13/2021] [Indexed: 11/16/2022] Open
Abstract
Animal welfare status is assessed today through visual evaluations requiring an on-farm visit. A convenient alternative would be to detect cow welfare status directly in milk samples, already routinely collected for milk recording. The objective of this study was to propose a novel approach to demonstrate that Fourier transform infrared (FTIR) spectroscopy can detect changes in milk composition related to cows subjected to movement restriction at the tie stall with four tie-rail configurations varying in height and position (TR1, TR2, TR3 and TR4). Milk mid-infrared spectra were collected on weekly basis. Long-term average spectra were calculated for each cow using spectra collected in weeks 8–10 of treatment. Principal component analysis was applied to spectral averages and the scores of principal components (PCs) were tested for treatment effect by mixed modelling. PC7 revealed a significant treatment effect (p = 0.01), particularly for TR3 (configuration with restricted movement) vs. TR1 (recommended configuration) (p = 0.03). The loading spectrum of PC7 revealed high loadings at wavenumbers that could be assigned to biomarkers related to negative energy balance, such as β-hydroxybutyrate, citrate and acetone. This observation suggests that TR3 might have been restrictive for cows to access feed. Milk FTIR spectroscopy showed promising results in detecting welfare status and housing conditions in dairy cows.
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Affiliation(s)
- Mazen Bahadi
- McGill IR Group, McGill University, Sainte Anne de Bellevue, QC H9X 3V9, Canada;
- Correspondence:
| | - Ashraf A. Ismail
- McGill IR Group, McGill University, Sainte Anne de Bellevue, QC H9X 3V9, Canada;
| | - Elsa Vasseur
- Department of Animal Science, McGill University, Sainte Anne de Bellevue, QC H9X 3V9, Canada;
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18
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Appropriate Data Quality Checks Improve the Reliability of Values Predicted from Milk Mid-Infrared Spectra. Animals (Basel) 2021; 11:ani11020533. [PMID: 33670810 PMCID: PMC7922538 DOI: 10.3390/ani11020533] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Accepted: 02/14/2021] [Indexed: 11/23/2022] Open
Abstract
Simple Summary There is a growing interest in using milk mid-infrared (MIR) spectrometry to obtain new phenotypes to assist in the complex management of dairy farms. These predictive values can be erroneous for many reasons, even if the prediction equations used are accurate. Unfortunately, there is no quality protocol routinely implemented to detect those abnormal predictive values in the database recorded by dairy herd improvement (DHI) organizations, except for fat and protein contents. However, for financial and practical reasons, it is unfeasible to adapt the quality protocol commonly used in milk laboratories to improve the accuracy of those traits. So, this study proposes three different statistical methods that would be easy to implement by DHI organizations to detect abnormal values and limit the spectral extrapolation in order to improve the accuracy of MIR-based predictive values. Abstract The use of abnormal milk mid-infrared (MIR) spectrum strongly affects prediction quality, even if the prediction equations used are accurate. So, this record must be detected after or before the prediction process to avoid erroneous spectral extrapolation or the use of poor-quality spectral data by dairy herd improvement (DHI) organizations. For financial or practical reasons, adapting the quality protocol currently used to improve the accuracy of fat and protein contents is unfeasible. This study proposed three different statistical methods that would be easy to implement by DHI organizations to solve this issue: the deletion of 1% of the extreme high and low predictive values (M1), the deletion of records based on the Global-H (GH) distance (M2), and the deletion of records based on the absolute fat residual value (M3). Additionally, the combinations of these three methods were investigated. A total of 346,818 milk samples were analyzed by MIR spectrometry to predict the contents of fat, protein, and fatty acids. Then, the same traits were also predicted externally using their corresponded standardized MIR spectra. The interest in cleaning procedures was assessed by estimating the root mean square differences (RMSDs) between those internal and external predicted phenotypes. All methods allowed for a decrease in the RMSD, with a gain ranging from 0.32% to 41.39%. Based on the obtained results, the “M1 and M2” combination should be preferred to be more parsimonious in the data loss, as it had the higher ratio of RMSD gain to data loss. This method deleted the records based on the 2% extreme predictions and a GH threshold set at 5. However, to ensure the lowest RMSD, the “M2 or M3” combination, considering a GH threshold of 5 and an absolute fat residual difference set at 0.30 g/dL of milk, was the most relevant. Both combinations involved M2 confirming the high interest of calculating the GH distance for all samples to predict. However, if it is impossible to estimate the GH distance due to a lack of relevant information to compute this statistical parameter, the obtained results recommended the use of M1 combined with M3. The limitation used in M3 must be adapted by the DHI, as this will depend on the spectral data and the equation used. The methodology proposed in this study can be generalized for other MIR-based phenotypes.
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19
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Bērziņš K, Harrison SDL, Leong C, Fraser-Miller SJ, Harper MJ, Diana A, Gibson RS, Houghton LA, Gordon KC. Qualitative and quantitative vibrational spectroscopic analysis of macronutrients in breast milk. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2021; 246:118982. [PMID: 33017792 PMCID: PMC7684643 DOI: 10.1016/j.saa.2020.118982] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Revised: 08/23/2020] [Accepted: 09/17/2020] [Indexed: 06/11/2023]
Abstract
Raman and attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy were used to analyze 208 breast milk samples as part of a larger research study. Comprehensive qualitative and quantitative analysis was carried out using chemometric methods: principal component analysis (PCA) and partial least squares (PLS) regression. The obtained information on the main macronutrients (protein, fat and carbohydrate) were primarily evaluated in relation to the available metadata of the samples, where study location and respective primary food sources revealed a stronger differentiation in fat composition than its absolute content. The limitations and challenges of using both spectroscopic techniques for the type of analysis are also highlighted.
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Affiliation(s)
- Kārlis Bērziņš
- The Dodd-Walls Centre for Photonic and Quantum Technologies, Department of Chemistry, University of Otago, Dunedin 9016, New Zealand
| | - Samuel D L Harrison
- The Dodd-Walls Centre for Photonic and Quantum Technologies, Department of Chemistry, University of Otago, Dunedin 9016, New Zealand
| | - Claudia Leong
- Department of Human Nutrition, University of Otago, Dunedin 9016, New Zealand
| | - Sara J Fraser-Miller
- The Dodd-Walls Centre for Photonic and Quantum Technologies, Department of Chemistry, University of Otago, Dunedin 9016, New Zealand
| | - Michelle J Harper
- Department of Human Nutrition, University of Otago, Dunedin 9016, New Zealand
| | - Aly Diana
- Department of Human Nutrition, University of Otago, Dunedin 9016, New Zealand; Faculty of Medicine, Universitas Padjadjaran, West Java, Indonesia
| | - Rosalind S Gibson
- Department of Human Nutrition, University of Otago, Dunedin 9016, New Zealand
| | - Lisa A Houghton
- Department of Human Nutrition, University of Otago, Dunedin 9016, New Zealand
| | - Keith C Gordon
- The Dodd-Walls Centre for Photonic and Quantum Technologies, Department of Chemistry, University of Otago, Dunedin 9016, New Zealand.
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20
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Kuchtík J, Šustová K, Sýkora V, Kalhotka L, Pavlata L, Konečná L. Changes in the somatic cells counts and total bacterial counts in raw goat milk during lactation and their relationships to selected milk traits. ITALIAN JOURNAL OF ANIMAL SCIENCE 2021. [DOI: 10.1080/1828051x.2021.1913077] [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)
- Jan Kuchtík
- Ústav chovu a šlechtění zvířat, Faculty of AgriSciences (FA), Mendel University in Brno, Brno, Czech Republic
| | - Květoslava Šustová
- Ústav technologie potravin, Mendel University in Brno, Brno, Czech Republic
- Katedra gastronomie a hotelového managementu, College of Business and Hotel Management, Brno, Czech Republic
| | - Vladimír Sýkora
- Ústav technologie potravin, Mendel University in Brno, Brno, Czech Republic
| | - Libor Kalhotka
- Ústav agrochemie, půdoznalství, mikrobiologie a výživy rostlin, Mendel University in Brno, Brno, Czech Republic
| | - Leoš Pavlata
- Ústav výživy zvířat a pícninářství, Mendel University in Brno, Brno, Czech Republic
| | - Leona Konečná
- Ústav chovu a šlechtění zvířat, Faculty of AgriSciences (FA), Mendel University in Brno, Brno, Czech Republic
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21
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Rogoskii I, Mushtruk M, Titova L, Snezhko O, Rogach S, Blesnyuk O, Rosamaha Y, Zubok T, Yeremenko O, Nadtochiy O. Engineering management of starter cultures in study of temperature of fermentation of sour-milk drink with apiproducts. POTRAVINARSTVO 2020. [DOI: 10.5219/1437] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The article considers the solution of problematic issues of engineering management of poly fermentation in the study of fermentation temperature of sour-milk drink with apiproducts. In the development of fermented dairy products, the components that are part of them, changes in their composition, and properties in the interconnection are considered as a technological system. The authors took into account that food technologies based on the use of the pure culture of one microorganism are limited by the capabilities of its fermentation system systems, the ultimate goal may not be achieved even by changing the conditions and parameters of cultivation. To successfully carry out fermentation processes in the technological system, a combination of cultures, associations of microorganisms with a wide range of fermentation products in contrast to one culture is promising to use. All experimental samples on a set of indicators prevailed control ones. The leader was a sample fermented with yeast with an equal ratio of cultures at a temperature of 38 – 40 °C. The authors found that the set of indicators of finished products for the production of sour-milk drinks with a complex of apiproducts, it is necessary to choose a three-strain poly fermentation product with a congruent ratio of cultures and set optimal fermentation regimes 39 ±1ºC for 5.0 ±0.3 hours.
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22
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Soyeurt H, Grelet C, McParland S, Calmels M, Coffey M, Tedde A, Delhez P, Dehareng F, Gengler N. A comparison of 4 different machine learning algorithms to predict lactoferrin content in bovine milk from mid-infrared spectra. J Dairy Sci 2020; 103:11585-11596. [PMID: 33222859 DOI: 10.3168/jds.2020-18870] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2020] [Accepted: 08/10/2020] [Indexed: 01/19/2023]
Abstract
Lactoferrin (LF) is a glycoprotein naturally present in milk. Its content varies throughout lactation, but also with mastitis; therefore it is a potential additional indicator of udder health beyond somatic cell count. Condequently, there is an interest in quantifying this biomolecule routinely. First prediction equations proposed in the literature to predict the content in milk using milk mid-infrared spectrometry were built using partial least square regression (PLSR) due to the limited size of the data set. Thanks to a large data set, the current study aimed to test 4 different machine learning algorithms using a large data set comprising 6,619 records collected across different herds, breeds, and countries. The first algorithm was a PLSR, as used in past investigations. The second and third algorithms used partial least square (PLS) factors combined with a linear and polynomial support vector regression (PLS + SVR). The fourth algorithm also used PLS factors, but included in an artificial neural network with 1 hidden layer (PLS + ANN). The training and validation sets comprised 5,541 and 836 records, respectively. Even if the calibration prediction performances were the best for PLS + polynomial SVR, their validation prediction performances were the worst. The 3 other algorithms had similar validation performances. Indeed, the validation root mean squared error (RMSE) ranged between 162.17 and 166.75 mg/L of milk. However, the lower standard deviation of cross-validation RMSE and the better normality of the residual distribution observed for PLS + ANN suggest that this modeling was more suitable to predict the LF content in milk from milk mid-infrared spectra (R2v = 0.60 and validation RMSE = 162.17 mg/L of milk). This PLS +ANN model was then applied to almost 6 million spectral records. The predicted LF showed the expected relationships with milk yield, somatic cell score, somatic cell count, and stage of lactation. The model tended to underestimate high LF values (higher than 600 mg/L of milk). However, if the prediction threshold was set to 500 mg/L, 82% of samples from the validation having a content of LF higher than 600 mg/L were detected. Future research should aim to increase the number of those extremely high LF records in the calibration set.
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Affiliation(s)
- H Soyeurt
- TERRA research and teaching centre, Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium.
| | - C Grelet
- Valorisation of agricultural products, Walloon Research Centre, Gembloux, Belgium
| | - S McParland
- Animal and Grassland Research and Innovation Centre, Teagasc, Moorepark, Fermoy, Co. Cork, Ireland
| | - M Calmels
- Research and development, Seenovia, Saint-Berthevin, France
| | - M Coffey
- Livestock Breeding, Animal and Veterinary Sciences, Scotland's Rural College, Midlothian, UK
| | - A Tedde
- TERRA research and teaching centre, Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
| | - P Delhez
- TERRA research and teaching centre, Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium; National fund for Scientific Research, Brussels, Belgium
| | - F Dehareng
- Valorisation of agricultural products, Walloon Research Centre, Gembloux, Belgium
| | - N Gengler
- TERRA research and teaching centre, Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
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23
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Classification of Different Blueberry Cultivars by Analysis of Physical Factors, Chemical and Nutritional Ingredients, and Antioxidant Capacities. J FOOD QUALITY 2020. [DOI: 10.1155/2020/9474158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Blueberry fruits of different cultivars are featured with different quality indices. In this work, three types of quality factors, including 6 physical parameters, 12 chemical and nutritional components, and 3 antioxidant indices, were measured to compare and classify blueberry fruits from 12 different cultivars in China. Using the autoscaled data of quality factors, unsupervised principal component analysis was performed for exploratory analysis of intercultivar differences and the influences of quality factors. A supervised classification method, partial least squares discriminant analysis (PLSDA), was combined with the global particle swarm optimization algorithm (PSO) and two multiclass strategies, one-versus-rest (OVR) and one-versus-one (OVO), to select discriminative quality factors and develop classification models of the 12 cultivars. As a result, OVO-PLSDA with 8 quality factors could achieve the classification accuracy of 0.915. This study will provide new insights into the quality variations and key factors among different blueberry cultivars.
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24
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Lim JY, Lee CL, Kim GH, Bang YJ, Rhim JW, Yoon KS. Using lactic acid bacteria and packaging with grapefruit seed extract for controlling Listeria monocytogenes growth in fresh soft cheese. J Dairy Sci 2020; 103:8761-8770. [PMID: 32713695 DOI: 10.3168/jds.2020-18349] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2020] [Accepted: 05/13/2020] [Indexed: 11/19/2022]
Abstract
Various cheese products are involved in outbreaks of listeriosis worldwide due to high consumption and prolonged refrigerated storage. The objective of this study was to determine the efficacy of using lactic acid bacteria and packaging with grapefruit seed extract (GSE) for controlling Listeria monocytogenes growth in soft cheese. Leuconostoc mesenteroides and Lactobacillus curvatus isolated from kimchi were used as a starter culture to make a soft cheese, which was inoculated with a cocktail strain of L. monocytogenes. The soft cheese was packed with low-density polyethylene, biodegradable polybutylene adipate-co-terephthalate (PBAT), low-density polyethylene with GSE, or PBAT with GSE and stored at 10°C and 15°C. Leuconostoc mesenteroides (LcM) better inhibited the growth of L. monocytogenes than Lb. curvatus. The PBAT with GSE film showed the best control for the growth of L. monocytogenes. When both LcM and PBAT with GSE were applied to the soft cheese, the growth of L. monocytogenes was inhibited significantly more than the use of LcM or PBAT with GSE alone. In all test groups, water activity, pH, and moisture on a fat-free basis decreased, and titratable acidity increased compared with the control group. These results suggest that LcM isolated from kimchi and PBAT with GSE packaging film can be used as a hurdle technology to lower the risk of L. monocytogenes in soft cheese at the retail market.
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Affiliation(s)
- J Y Lim
- Department of Food and Nutrition, College of Human Ecology, Kyung Hee University, Seoul 02447, Republic of Korea
| | - C L Lee
- Department of Food and Nutrition, College of Human Ecology, Kyung Hee University, Seoul 02447, Republic of Korea
| | - G H Kim
- Department of Food and Nutrition, College of Human Ecology, Kyung Hee University, Seoul 02447, Republic of Korea
| | - Y J Bang
- Department of Food and Nutrition, College of Human Ecology, Kyung Hee University, Seoul 02447, Republic of Korea
| | - J W Rhim
- Department of Food and Nutrition, College of Human Ecology, Kyung Hee University, Seoul 02447, Republic of Korea
| | - K S Yoon
- Department of Food and Nutrition, College of Human Ecology, Kyung Hee University, Seoul 02447, Republic of Korea.
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25
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Kobus-Cisowska J, Szymanowska-Powałowska D, Szymandera-Buszka K, Rezler R, Jarzębski M, Szczepaniak O, Marciniak G, Jędrusek-Golińska A, Kobus-Moryson M. Effect of fortification with calcium from eggshells on bioavailability, quality, and rheological characteristics of traditional Polish bread spread. J Dairy Sci 2020; 103:6918-6929. [PMID: 32505401 DOI: 10.3168/jds.2019-18027] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2019] [Accepted: 03/28/2020] [Indexed: 11/19/2022]
Abstract
Hen eggshells are a rich and natural source of calcium and can serve as a biofunctional food ingredient. Enriching the traditional Polish bread spread (sersmażony) with micronized eggshell is an attractive proposition for consumers who require easily available calcium. The present study aimed to evaluate the use of micronized eggshells as a source of bioavailable calcium in bread spread. The study evaluated the effect of selected biocomponents on calcium bioavailability by using an in vitro digestion model. The enrichment of bread spread with eggshell, lysine, vitamin D3, and vitamin K enhanced all examined physicochemical variables except water activity. Enrichment with eggshells increased calcium levels >2.5-fold compared with the control sample. As an ingredient of bread spread, lysine is an important rheological factor. The bioavailability of calcium was higher in samples with lysine and vitamin K compared with samples that contained eggshell alone.
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Affiliation(s)
- Joanna Kobus-Cisowska
- Department of Gastronomy Sciences and Functional Foods, Poznan University of Life Sciences, 60-637 Poznan, Poland
| | | | - Krystyna Szymandera-Buszka
- Department of Gastronomy Sciences and Functional Foods, Poznan University of Life Sciences, 60-637 Poznan, Poland
| | - Ryszard Rezler
- Department of Physics and Biophysics, Poznan University of Life Sciences, 60-637 Poznań, Poland
| | - Maciej Jarzębski
- Department of Physics and Biophysics, Poznan University of Life Sciences, 60-637 Poznań, Poland
| | - Oskar Szczepaniak
- Department of Gastronomy Sciences and Functional Foods, Poznan University of Life Sciences, 60-637 Poznan, Poland.
| | - Grzegorz Marciniak
- Department of Macroeconomics and Agricultural Economics, Poznan University of Economics and Business, 61-875 Poznań, Poland
| | - Anna Jędrusek-Golińska
- Department of Gastronomy Sciences and Functional Foods, Poznan University of Life Sciences, 60-637 Poznan, Poland
| | - Małgorzata Kobus-Moryson
- Department of Gastronomy Sciences and Functional Foods, Poznan University of Life Sciences, 60-637 Poznan, Poland
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El Jabri M, Trossat P, Wolf V, Beuvier E, Rolet-Répécaud O, Gavoye S, Gaüzère Y, Belysheva O, Gaudillière N, Notz E, Grosperrin P, Laithier C, Delacroix-Buchet A. Mid-infrared spectrometry prediction of the cheese-making properties of raw Montbéliarde milks from herds and cheese dairy vats used for the production of Protected Designation of Origin and Protected Geographical Indication cheeses in Franche-Comté. J Dairy Sci 2020; 103:5992-6002. [PMID: 32331888 DOI: 10.3168/jds.2019-17491] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2019] [Accepted: 02/19/2020] [Indexed: 11/19/2022]
Abstract
Franche-Comté is the primary producing region of Protected Designation of Origin cheeses in France. Normally, mid-infrared (MIR) prediction models for cheese-making property (CMP) traits are developed using individual bovine milks. However, considering the requests of all actors in the dairy sector, the present study aimed to assess the feasibility of MIR spectroscopy to develop CMP equations of Montbéliarde herd and dairy vat milks. For this purpose, 22 CMP traits were analyzed on samples collected in 2016 (half in February-March and half in May-June) from 100 commercial herds and 70 dairy vats (55 cheese dairies) located in Franche-Comté. These characteristics included 11 rennet coagulation traits and 8 lactic acidification traits measured in either soft cheese or pressed cooked cheese conditions and 3 laboratory curd yields. Models of MIR prediction for each of the 22 CMP traits were built using partial least squares regression with external validation by dividing the data set into calibration (70%) and validation (30%) sets. We confirmed that the variability of milk traits depends largely on the production scale and is higher for individual milk than for herd milk and even higher for vat milk. The best prediction models were obtained in herd milk samples for curd yields expressed in dry matter or fresh, with a coefficient of determination (R2) in external validation of 0.78 and 0.77, respectively. As with individual milk, these traits are closely related to the gross composition of the milk and therefore easier to predict by MIR spectroscopy. However, these curd yield traits were poorly predicted (R2 = 0.58) in vat milk samples due to their lower variability. In herd milk samples, prediction models of other CMP traits were poorly accurate except for the ratio of the time to obtain a standard firmness to the rennet coagulation time in soft cheese or pressed cooked cheese conditions, which showed R2 > 0.66 in external validation. Such trait is important in qualifying the behavior of milk during cheese production. Prediction models of other CMP traits for either herd or vat milk samples had poor accuracy, and further work is needed to improve their performance.
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Affiliation(s)
- M El Jabri
- Institut de l'Elevage, F-75012 Paris, France
| | | | - V Wolf
- Conseil Elevage 25-90, F-25640 Roulans, France
| | - E Beuvier
- INRAE, URTAL, F-39800, Poligny, France
| | | | - S Gavoye
- ACTALIA, F-39800 Poligny, France
| | - Y Gaüzère
- Ecole Nationale d'Industrie Laitière et des Biotechnologies, F-39800 Poligny, France
| | - O Belysheva
- Ecole Nationale d'Industrie Laitière et des Biotechnologies, F-39800 Poligny, France
| | | | - E Notz
- Centre Technique des Fromages Comtois, F-39800, Poligny, France
| | | | - C Laithier
- Institut de l'Elevage, F-75012 Paris, France
| | - A Delacroix-Buchet
- Université Paris Saclay, INRAE, AgroParisTech, GABI, F-78350 Jouy-en-Josas, France.
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Opportunities and limitations of milk mid-infrared spectra-based estimation of acetone and β-hydroxybutyrate for the prediction of metabolic stress and ketosis in dairy cows. J DAIRY RES 2020; 87:196-203. [PMID: 32308161 DOI: 10.1017/s0022029920000230] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Subclinical (SCK) and clinical (CK) ketosis are metabolic disorders responsible for big losses in dairy production. Although Fourier-transform mid-infrared spectrometry (FTIR) to predict ketosis in cows exposed to great metabolic stress was studied extensively, little is known about its suitability in predicting hyperketonemia using individual samples, e.g. in small dairy herds or when only few animals are at risk of ketosis. The objective of the present research was to determine the applicability of milk metabolites predicted by FTIR spectrometry in the individual screening for ketosis. In experiment 1, blood and milk samples were taken every two weeks after calving from Holstein (n = 80), Brown Swiss (n = 72) and Swiss Fleckvieh (n = 58) cows. In experiment 2, cows diagnosed with CK (n = 474) and 420 samples with blood β-hydroxybutyrate [BHB] <1.0 mmol/l were used to investigate if CK could be detected by FTIR-predicted BHB and acetone from a preceding milk control. In experiment 3, correlations between data from an in farm automatic milk analyser and FTIR-predicted BHB and acetone from the monthly milk controls were evaluated. Hyperketonemia occurred in majority during the first eight weeks of lactation. Correlations between blood BHB and FTIR-predicted BHB and acetone were low (r = 0.37 and 0.12, respectively, P < 0.0001), as well as the percentage of true positive values (11.9 and 16.6%, respectively). No association of FTIR predicted ketone bodies with the interval of milk sampling relative to CK diagnosis was found. Data obtained from the automatic milk analyser were moderately correlated with the same day FTIR-predicted BHB analysis (r = 0.61). In conclusion, the low correlations with blood BHB and the small number of true positive samples discourage the use of milk mid-infrared spectrometry analyses as the only method to predict hyperketonemia at the individual cow level.
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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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Santos Monteiro S, Albertina Silva Beserra Y, Miguel Lisboa Oliveira H, Pasquali MADB. Production of Probiotic Passion Fruit ( Passiflora edulis Sims f. flavicarpa Deg.) Drink Using Lactobacillus reuteri and Microencapsulation via Spray Drying. Foods 2020; 9:foods9030335. [PMID: 32178366 PMCID: PMC7143088 DOI: 10.3390/foods9030335] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2020] [Revised: 02/15/2020] [Accepted: 02/18/2020] [Indexed: 11/28/2022] Open
Abstract
Probiotic foods offer many benefits to human health, causing increased interest in the development of new food products that exploit such benefits. However, traditional dairy foods are being replaced by other non-dairy foods to provide additional sources of benefits provided by bioactive molecules. Therefore, the objective of the present work was to study the production process of a probiotic fruit drink and then microencapsulate the probiotic pulp to stabilize the drink further. Passion fruit pulp (Passiflora edulis Sims f. flavicarpa Deg.) was fermented with Lactobacillus reuteri under different temperature conditions in combination with different pHs to find the best fermentation conditions. Different from dairy sources, the optimal conditions for the growth of Lactobacillus reuteri in the passion fruit pulp were found to be 30 °C at pH 3.18, where phenolic compounds could also be used as a secondary metabolic pathway. Spray-drying was performed using different conditions for microencapsulation. Process yields and Lactobacillus reuteri survival showed the dependency of droplet sizes, whereas phenolic compound retention was increased when higher amounts of gelatin were used. Therefore, the development of a new food product comprising a powdered fruit pulp rich in probiotic and phenolic compounds was possible.
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Roy L, Halder A, Singh S, Patwari J, Singh P, Bhattacharya K, Mondal S, Pal SK. Spectroscopy of an intrinsic fluorophore in animal and plant milk for potential identification of their quality. J Dairy Sci 2020; 103:1366-1376. [DOI: 10.3168/jds.2019-17034] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2019] [Accepted: 10/07/2019] [Indexed: 11/19/2022]
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Smith SL, Denholm SJ, Coffey MP, Wall E. Energy profiling of dairy cows from routine milk mid-infrared analysis. J Dairy Sci 2019; 102:11169-11179. [PMID: 31587910 DOI: 10.3168/jds.2018-16112] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2018] [Accepted: 07/24/2019] [Indexed: 01/04/2023]
Abstract
The balance of body energy within and across lactations can have health and fertility consequences for the dairy cow. This study aimed to create a large calibration data set of dairy cow body energy traits across the cow's productive life, with concurrent milk mid-infrared (MIR) spectral data, to generate a prediction tool for use in commercial dairy herds. Detailed phenotypic data from 1,101 Holstein Friesian cows from the Langhill research herd (SRUC, Scotland) were used to generate energy balance (EB) and effective energy intake (EI), both in megajoules per day. Pretreatment of spectral data involved standardization to account for drift over time and machine. Body energy estimates were aligned with their spectral data to generate a prediction of these traits based on milk MIR spectroscopy. After data edits, partial least squares analysis generated prediction equations with a coefficient of determination from split sample 10-fold cross validation of 0.77 and 0.75 for EB and EI, respectively. These prediction equations were applied to national milk MIR spectra on over 11 million animal test dates (January 2013 to December 2016) from 4,453 farms. The predictions generated from these were subject to phenotypic analyses with a fixed regression model highlighting differences between the main dairy breeds in terms of energy traits. Genetic analyses generated heritability estimates for EB and EI ranging from 0.12 to 0.17 and 0.13 to 0.15, respectively. This study shows that MIR-based predictions from routinely collected national data can be used to generate predictions of dairy cow energy turnover profiles for both animal management and genetic improvement of such difficult and expensive-to-record traits.
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Affiliation(s)
- S L Smith
- Scotland's Rural College (SRUC), Edinburgh EH9 3JG, UK
| | - S J Denholm
- Scotland's Rural College (SRUC), Edinburgh EH9 3JG, UK.
| | - M P Coffey
- Scotland's Rural College (SRUC), Edinburgh EH9 3JG, UK
| | - E Wall
- Scotland's Rural College (SRUC), Edinburgh EH9 3JG, UK
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Cellesi M, Correddu F, Manca MG, Serdino J, Gaspa G, Dimauro C, Macciotta NPP. Prediction of Milk Coagulation Properties and Individual Cheese Yield in Sheep Using Partial Least Squares Regression. Animals (Basel) 2019; 9:ani9090663. [PMID: 31500237 PMCID: PMC6770130 DOI: 10.3390/ani9090663] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Revised: 09/02/2019] [Accepted: 09/05/2019] [Indexed: 12/31/2022] Open
Abstract
Simple Summary Considered that all sheep milk in Italy is destined for cheese processing, traits describing rennet coagulation aptitude should be among the most important selection goals for dairy breeds. To reduce the costs and logistics related to the large-scale recording of these traits, mid-infrared (MIR) spectroscopy could be conveniently used to generate reliable predictions without any additional cost. The aims of this research were to predict the milk coagulation properties (MCP) and individual cheese yield (ILCY) in sheep by MIR spectrometry using partial least squares regression (PLS), and to compare different data pre-treatment procedures. The prediction results observed in the present study, although moderate, suggest the possibility of adding novel phenotypes (e.g., MCP and ILCY) in breeding schemes for dairy sheep breeds. Mid-infrared spectroscopy coupled with PLS regression could allow the prediction of phenotypes at the population level without additional costs. Abstract The objectives of this study were (i) the prediction of sheep milk coagulation properties (MCP) and individual laboratory cheese yield (ILCY) from mid-infrared (MIR) spectra by using partial least squares (PLS) regression, and (ii) the comparison of different data pre-treatments on prediction accuracy. Individual milk samples of 970 Sarda breed ewes were analyzed for rennet coagulation time (RCT), curd-firming time (k20), and curd firmness (a30) using the Formagraph instrument; ILCY was measured by micro-manufacturing assays. An Furier-transform Infrared (FTIR) milk-analyzer was used for the estimation of the milk gross composition and the recording of MIR spectrum. The dataset (n = 859, after the exclusion of 111 noncoagulating samples) was divided into two sub-datasets: the data of 700 ewes were used to estimate prediction model parameters, and the data of 159 ewes were used to validate the model. Four prediction scenarios were compared in the validation, differing for the use of whole or reduced MIR spectrum and the use of raw or corrected data (locally weighted scatterplot smoothing). PLS prediction statistics were moderate. The use of the reduced MIR spectrum yielded the best results for the considered traits, whereas the data correction improved the prediction ability only when the whole MIR spectrum was used. In conclusion, PLS achieves good accuracy of prediction, in particular for ILCY and RCT, and it may enable increasing the number of traits to be included in breeding programs for dairy sheep without additional costs and logistics.
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Affiliation(s)
- Massimo Cellesi
- Dipartimento di Agraria, Sezione di Scienze Zootecniche, Università degli Studi di Sassari, Viale Italia 39, 07100 Sassari, Italy.
| | - Fabio Correddu
- Dipartimento di Agraria, Sezione di Scienze Zootecniche, Università degli Studi di Sassari, Viale Italia 39, 07100 Sassari, Italy.
| | - Maria Grazia Manca
- Dipartimento di Agraria, Sezione di Scienze Zootecniche, Università degli Studi di Sassari, Viale Italia 39, 07100 Sassari, Italy.
| | - Jessica Serdino
- Dipartimento di Agraria, Sezione di Scienze Zootecniche, Università degli Studi di Sassari, Viale Italia 39, 07100 Sassari, Italy.
| | - Giustino Gaspa
- Dipartimento di Scienze Agrarie Alimentari e Forestali, Università di Torino, 10095 Grugliasco, Italy.
| | - Corrado Dimauro
- Dipartimento di Agraria, Sezione di Scienze Zootecniche, Università degli Studi di Sassari, Viale Italia 39, 07100 Sassari, Italy.
| | - Nicolò Pietro Paolo Macciotta
- Dipartimento di Agraria, Sezione di Scienze Zootecniche, Università degli Studi di Sassari, Viale Italia 39, 07100 Sassari, Italy.
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Franceschi P, Malacarne M, Formaggioni P, Cipolat-Gotet C, Stocco G, Summer A. Effect of Season and Factory on Cheese-Making Efficiency in Parmigiano Reggiano Manufacture. Foods 2019; 8:foods8080315. [PMID: 31382575 PMCID: PMC6722500 DOI: 10.3390/foods8080315] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2019] [Revised: 07/31/2019] [Accepted: 08/01/2019] [Indexed: 11/16/2022] Open
Abstract
The assessment of the efficiency of the cheese-making process (ECMP) is crucial for the profitability of cheese-factories. A simple way to estimate the ECMP is the measure of the estimated cheese-making losses (ECL), expressed by the ratio between the concentration of each constituent in the residual whey and in the processed milk. The aim of this research was to evaluate the influence of the season and cheese factory on the efficiency of the cheese-making process in Parmigiano Reggiano cheese manufacture. The study followed the production of 288 Parmigiano Reggiano cheese on 12 batches in three commercial cheese factories. For each batch, samples of the processed milk and whey were collected. Protein, casein, and fat ECL resulted in an average of 27.01%, 0.72%, and 16.93%, respectively. Both milk crude protein and casein contents were negatively correlated with protein ECL, r = −0.141 (p ≤ 0.05), and r = −0.223 (p ≤ 0.001), respectively. The same parameters resulted in a negative correlation with casein ECL (p ≤ 0.001) (r = −0.227 and −0.212, respectively). Moreover, fat ECL was correlated with worse milk coagulation properties and negatively correlated with casein content (r = −0.120; p ≤ 0.05). In conclusion, ECLs depend on both milk characteristics and season.
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Affiliation(s)
- Piero Franceschi
- Department of Veterinary Science, University of Parma, Via del Taglio 10, I-43126 Parma, Italy
| | - Massimo Malacarne
- Department of Veterinary Science, University of Parma, Via del Taglio 10, I-43126 Parma, Italy.
| | - Paolo Formaggioni
- Department of Veterinary Science, University of Parma, Via del Taglio 10, I-43126 Parma, Italy.
| | - Claudio Cipolat-Gotet
- Department of Veterinary Science, University of Parma, Via del Taglio 10, I-43126 Parma, Italy
| | - Giorgia Stocco
- Department of Veterinary Science, University of Parma, Via del Taglio 10, I-43126 Parma, Italy
| | - Andrea Summer
- Department of Veterinary Science, University of Parma, Via del Taglio 10, I-43126 Parma, Italy
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Aiello A, Pizzolongo F, Manzo N, Romano R. A New Method to Distinguish the Milk Adulteration with Neutralizers by Detection of Lactic Acid. FOOD ANAL METHOD 2019. [DOI: 10.1007/s12161-019-01594-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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El Jabri M, Sanchez MP, Trossat P, Laithier C, Wolf V, Grosperrin P, Beuvier E, Rolet-Répécaud O, Gavoye S, Gaüzère Y, Belysheva O, Notz E, Boichard D, Delacroix-Buchet A. Comparison of Bayesian and partial least squares regression methods for mid-infrared prediction of cheese-making properties in Montbéliarde cows. J Dairy Sci 2019; 102:6943-6958. [PMID: 31178172 DOI: 10.3168/jds.2019-16320] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2019] [Accepted: 04/23/2019] [Indexed: 01/17/2023]
Abstract
Assessing the cheese-making properties (CMP) of milks with a rapid and cost-effective method is of particular interest for the Protected Designation of Origin cheese sector. The aims of this study were to evaluate the potential of mid-infrared (MIR) spectra to estimate coagulation and acidification properties, as well as curd yield (CY) traits of Montbéliarde cow milk. Samples from 250 cows were collected in 216 commercial herds in Franche-Comté with the objectives to maximize the genetic diversity as well as the variation in milk composition. All coagulation and CY traits showed high variability (10 to 43%). Reference analyses performed for soft (SC) and pressed cooked (PCC) cheese technology were matched with MIR spectra. Prediction models were built on 446 informative wavelengths not tainted by the water absorbance, using different approaches such as partial least squares (PLS), uninformative variable elimination PLS, random forest PLS, Bayes A, Bayes B, Bayes C, and Bayes RR. We assessed equation performances for a set of 20 CMP traits (coagulation: 5 for SC and 4 for PCC; acidification: 5 for SC and 3 for PCC; laboratory CY: 3) by comparing prediction accuracies based on cross-validation. Overall, variable selection before PLS did not significantly improve the performances of the PLS regression, the prediction differences between Bayesian methods were negligible, and PLS models always outperformed Bayesian models. This was likely a result of the prior use of informative wavelengths of the MIR spectra. The best accuracies were obtained for curd yields expressed in dry matter (CYDM) or fresh (CYFRESH) and for coagulation traits (curd firmness for PCC and SC) using the PLS regression. Prediction models of other CMP traits were moderately to poorly accurate. Whatever the prediction methodology, the best results were always obtained for CY traits, probably because these traits are closely related to milk composition. The CYDM predictions showed coefficient of determination (R2) values up to 0.92 and 0.87, and RSy,x values of 3 and 4% for PLS and Bayes regressions, respectively. Finally, we divided the data set into calibration (2/3) and validation (1/3) sets and developed prediction models in external validation using PLS regression only. In conclusion, we confirmed, in the validation set, an excellent prediction for CYDM [R2 = 0.91, ratio of performance to deviation (RPD) = 3.39] and a very good prediction for CYFRESH (R2 = 0.84, RPD = 2.49), adequate for analytical purposes. We also obtained good results for both PCC and SC curd firmness traits (R2 ≥ 0.70, RPD ≥1.8), which enable quantitative prediction.
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Affiliation(s)
- M El Jabri
- Institut de l'Elevage, F-75012 Paris, France.
| | - M-P Sanchez
- GABI, INRA, AgroParisTech, Université Paris-Saclay, F-78350 Jouy-en-Josas, France
| | | | - C Laithier
- Institut de l'Elevage, F-75012 Paris, France
| | - V Wolf
- Conseil Elevage 25-90, F-25640 Roulans, France
| | | | - E Beuvier
- URTAL, INRA, F-39800 Poligny, France
| | | | - S Gavoye
- ACTALIA, F-39800 Poligny, France
| | - Y Gaüzère
- Ecole Nationale d'Industrie Laitière et des Biotechnologies, F-39800 Poligny, France
| | - O Belysheva
- Ecole Nationale d'Industrie Laitière et des Biotechnologies, F-39800 Poligny, France
| | - E Notz
- Centre Technique des Fromages Comtois, F-39800 Poligny, France
| | - D Boichard
- GABI, INRA, AgroParisTech, Université Paris-Saclay, F-78350 Jouy-en-Josas, France
| | - A Delacroix-Buchet
- GABI, INRA, AgroParisTech, Université Paris-Saclay, F-78350 Jouy-en-Josas, France
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Bista A, Hogan SA, O'Donnell CP, Tobin JT, O'Shea N. Evaluation and validation of an inline Coriolis flowmeter to measure dynamic viscosity during laboratory and pilot-scale food processing. INNOV FOOD SCI EMERG 2019. [DOI: 10.1016/j.ifset.2019.05.004] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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38
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Su WH, Sun DW. Mid-infrared (MIR) Spectroscopy for Quality Analysis of Liquid Foods. FOOD ENGINEERING REVIEWS 2019. [DOI: 10.1007/s12393-019-09191-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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Tiplady KM, Sherlock RG, Littlejohn MD, Pryce JE, Davis SR, Garrick DJ, Spelman RJ, Harris BL. Strategies for noise reduction and standardization of milk mid-infrared spectra from dairy cattle. J Dairy Sci 2019; 102:6357-6372. [PMID: 31030929 DOI: 10.3168/jds.2018-16144] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2018] [Accepted: 03/04/2019] [Indexed: 01/02/2023]
Abstract
The use of Fourier-transform mid-infrared (FTIR) spectroscopy is of interest to the dairy industry worldwide for predicting milk composition and other novel traits that are difficult or expensive to measure directly. Although there are many valuable applications for FTIR spectra, noise from differences in spectral responses between instruments is problematic because it reduces prediction accuracy if ignored. The purpose of this study was to develop strategies to reduce the impact of noise and to compare methods for standardizing FTIR spectra in order to reduce between-instrument variability in multiple-instrument networks. Noise levels in bands of the infrared spectrum caused by the water content of milk were characterized, and a method for identifying and removing outliers was developed. Two standardization methods were assessed and compared: piecewise direct standardization (PDS), which related spectra on a primary instrument to spectra on 5 other (secondary) instruments using identical milk-based reference samples (n = 918) analyzed across the 6 instruments; and retroactive percentile standardization (RPS), whereby percentiles of observed spectra from routine milk test samples (n = 2,044,094) were used to map and exploit primary- and secondary-instrument relationships. Different applications of each method were studied to determine the optimal way to implement each method across time. Industry-standard predictions of milk components from 2,044,094 spectra records were regressed against predictions from spectra before and after standardization using PDS or RPS. The PDS approach resulted in an overall decrease in root mean square error between industry-standard predictions and predictions from spectra from 0.190 to 0.071 g/100 mL for fat, from 0.129 to 0.055 g/100 mL for protein, and from 0.143 to 0.088 g/100 mL for lactose. Reductions in prediction error for RPS were similar but less consistent than those for PDS across time, but similar reductions were achieved when PDS coefficients were updated monthly and separate primary instruments were assigned for the North and South Islands of New Zealand. We demonstrated that the PDS approach is the most consistent method to reduce prediction errors across time. We also showed that the RPS approach is sensitive to shifts in milk composition but can be used to reduce prediction errors, provided that secondary-instrument spectra are standardized to a primary instrument with samples of broadly equivalent milk composition. Appropriate implementation of either of these approaches will improve the quality of predictions based on FTIR spectra for various downstream applications.
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Affiliation(s)
- K M Tiplady
- Research and Development, Livestock Improvement Corporation, Private Bag 3016, Hamilton 3240, New Zealand; School of Agriculture, Massey University, Ruakura, Hamilton 3240, New Zealand.
| | - R G Sherlock
- Research and Development, Livestock Improvement Corporation, Private Bag 3016, Hamilton 3240, New Zealand
| | - M D Littlejohn
- Research and Development, Livestock Improvement Corporation, Private Bag 3016, Hamilton 3240, New Zealand; School of Agriculture, Massey University, Ruakura, Hamilton 3240, New Zealand
| | - J E Pryce
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC 3083, Australia; School of Applied Systems Biology, La Trobe University, Bundoora, VIC 3083, Australia
| | - S R Davis
- Research and Development, Livestock Improvement Corporation, Private Bag 3016, Hamilton 3240, New Zealand
| | - D J Garrick
- School of Agriculture, Massey University, Ruakura, Hamilton 3240, New Zealand
| | - R J Spelman
- Research and Development, Livestock Improvement Corporation, Private Bag 3016, Hamilton 3240, New Zealand
| | - B L Harris
- Research and Development, Livestock Improvement Corporation, Private Bag 3016, Hamilton 3240, New Zealand
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40
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Manuelian C, Penasa M, Giangolini G, Boselli C, Currò S, De Marchi M. Short communication: Fourier-transform mid-infrared spectroscopy to predict coagulation and acidity traits of sheep bulk milk. J Dairy Sci 2019; 102:1927-1932. [DOI: 10.3168/jds.2018-15259] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2018] [Accepted: 11/11/2018] [Indexed: 01/27/2023]
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41
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Niero G, Penasa M, Costa A, Currò S, Visentin G, Cassandro M, De Marchi M. Total antioxidant activity of bovine milk: Phenotypic variation and predictive ability of mid-infrared spectroscopy. Int Dairy J 2019. [DOI: 10.1016/j.idairyj.2018.08.014] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
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42
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Interactions between polyols and wheat biopolymers in a bread model system fortified with inulin: A Fourier transform infrared study. Heliyon 2018; 4:e01017. [PMID: 30560212 PMCID: PMC6289941 DOI: 10.1016/j.heliyon.2018.e01017] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2018] [Revised: 11/05/2018] [Accepted: 12/04/2018] [Indexed: 02/08/2023] Open
Abstract
One of the ways to improve food safety and reduce community health risks is fortification of these products with inulin. Inulin, in spite of the effects and nutritional benefits, will also have undesirable effects on the quality and shelf life of bread. In this study, the interactions between polyols as improvers (i.e. glycerol, sorbitol and propylene glycol) and major biopolymers of wheat flour (i.e. starch and gluten) were examined in model systems fortified with Serish inulin by Fourier transform infrared (FTIR) spectroscopy. The changes in starch structure were estimated focusing on the ratios of the heights of the bands at 1047 and 1022 cm-1 which expresses the quantity of ordered starch to amorphous starch. At first and 5th days of storage, this ratio of control sample was higher than polyol treated samples. It was proved from Gaussian-Lorenzian curve fitting that the relative contribution of characteristic peaks of β-turns and intramolecular β-sheets was consecutively increased when polyol proportion of models increased. Whereas, content of intermolecular β-sheets and α-helix was slightly decreased with increasing of polyols in the models. Briefly, polyols especially 5% propylene glycol, could be used to reduce the undesirable effects of inulin on the quality parameters of dough and bread.
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43
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Chen D, Zhao X, Li X, Wang J, Wang C. Milk compositional changes of Laoshan goat milk from partum up to 261 days postpartum. Anim Sci J 2018; 89:1355-1363. [DOI: 10.1111/asj.13062] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2018] [Accepted: 05/23/2018] [Indexed: 12/22/2022]
Affiliation(s)
- Di Chen
- College of Food Science and Engineering; Qilu University of Technology (Shandong Academy of Sciences); Jinan China
| | - Xuan Zhao
- College of Food Science and Engineering; Qilu University of Technology (Shandong Academy of Sciences); Jinan China
| | - Xiangying Li
- College of Food Science and Engineering; Qilu University of Technology (Shandong Academy of Sciences); Jinan China
| | - Jianmin Wang
- College of Animal Science and Veterinary Medicine; Shandong Agricultural University; Taian China
| | - Cunfang Wang
- College of Food Science and Engineering; Qilu University of Technology (Shandong Academy of Sciences); Jinan China
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44
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van Gastelen S, Mollenhorst H, Antunes-Fernandes E, Hettinga K, van Burgsteden G, Dijkstra J, Rademaker J. Predicting enteric methane emission of dairy cows with milk Fourier-transform infrared spectra and gas chromatography–based milk fatty acid profiles. J Dairy Sci 2018; 101:5582-5598. [DOI: 10.3168/jds.2017-13052] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2017] [Accepted: 02/09/2018] [Indexed: 11/19/2022]
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45
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Henihan LE, O’Donnell CP, Esquerre C, Murphy EG, O’Callaghan DJ. Quality Assurance of Model Infant Milk Formula Using a Front-Face Fluorescence Process Analytical Tool. FOOD BIOPROCESS TECH 2018. [DOI: 10.1007/s11947-018-2112-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/16/2022]
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46
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Panikuttira B, O'Shea N, Tobin JT, Tiwari BK, O'Donnell CP. Process analytical technology for cheese manufacture. Int J Food Sci Technol 2018. [DOI: 10.1111/ijfs.13806] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Bhavya Panikuttira
- School of Biosystems and Food Engineering; University College Dublin; Belfield D4 Dublin Ireland
| | - Norah O'Shea
- Food Chemistry and Technology Department; Teagasc Food Research Centre; Moorepark, Fermoy Co.Cork Ireland
| | - John T. Tobin
- Food Chemistry and Technology Department; Teagasc Food Research Centre; Moorepark, Fermoy Co.Cork Ireland
| | - Brijesh K. Tiwari
- Food Chemistry and Technology Department; Teagasc Food Research Centre; Ashtown D15 Dublin Ireland
| | - Colm P. O'Donnell
- School of Biosystems and Food Engineering; University College Dublin; Belfield D4 Dublin Ireland
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47
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Manuelian C, Visentin G, Boselli C, Giangolini G, Cassandro M, De Marchi M. Short communication: Prediction of milk coagulation and acidity traits in Mediterranean buffalo milk using Fourier-transform mid-infrared spectroscopy. J Dairy Sci 2017; 100:7083-7087. [DOI: 10.3168/jds.2017-12707] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2017] [Accepted: 05/05/2017] [Indexed: 12/17/2022]
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48
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Grelet C, Pierna JAF, Dardenne P, Soyeurt H, Vanlierde A, Colinet F, Bastin C, Gengler N, Baeten V, Dehareng F. Standardization of milk mid-infrared spectrometers for the transfer and use of multiple models. J Dairy Sci 2017; 100:7910-7921. [PMID: 28755945 DOI: 10.3168/jds.2017-12720] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2017] [Accepted: 06/05/2017] [Indexed: 11/19/2022]
Abstract
An increasing number of models are being developed to provide information from milk Fourier transform mid-infrared (FT-MIR) spectra on fine milk composition, technological properties of milk, or even cows' physiological status. In this context, and to take advantage of these existing models, the purpose of this work was to evaluate whether a spectral standardization method can enable the use of multiple equations within a network of different FT-MIR spectrometers. The piecewise direct standardization method was used, matching "slave" instruments to a common reference, the "master." The effect of standardization on network reproducibility was assessed on 66 instruments from 3 different brands by comparing the spectral variability of the slaves and the master with and without standardization. With standardization, the global Mahalanobis distance from the slave spectra to the master spectra was reduced on average from 2,655.9 to 14.3, representing a significant reduction of noninformative spectral variability. The transfer of models from instrument to instrument was tested using 3 FT-MIR models predicting (1) the quantity of daily methane emitted by dairy cows, (2) the concentration of polyunsaturated fatty acids in milk, and (3) the fresh cheese yield. The differences, in terms of root mean squared error, between master predictions and slave predictions were reduced after standardization on average from 103 to 17 g/d, from 0.0315 to 0.0045 g/100 mL of milk, and from 2.55 to 0.49 g of curd/100 g of milk, respectively. For all the models, standard deviations of predictions among all the instruments were also reduced by 5.11 times for methane, 5.01 times for polyunsaturated fatty acids, and 7.05 times for fresh cheese yield, showing an improvement of prediction reproducibility within the network. Regarding the results obtained, spectral standardization allows the transfer and use of multiple models on all instruments as well as the improvement of spectral and prediction reproducibility within the network. The method makes the models universal, thereby offering opportunities for data exchange and the creation and use of common robust models at an international level to provide more information to the dairy sector from direct analysis of milk.
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Affiliation(s)
- C Grelet
- Valorization of Agricultural Products Department, Walloon Agricultural Research Center, 5030 Gembloux, Belgium
| | - J A Fernández Pierna
- Valorization of Agricultural Products Department, Walloon Agricultural Research Center, 5030 Gembloux, Belgium
| | - P Dardenne
- Valorization of Agricultural Products Department, Walloon Agricultural Research Center, 5030 Gembloux, Belgium
| | - H Soyeurt
- Agriculture, Bio-Engineering, and Chemistry Department, University of Liège, Gembloux Agro-Bio Tech, 5030 Gembloux, Belgium
| | - A Vanlierde
- Valorization of Agricultural Products Department, Walloon Agricultural Research Center, 5030 Gembloux, Belgium
| | - F Colinet
- Agriculture, Bio-Engineering, and Chemistry Department, University of Liège, Gembloux Agro-Bio Tech, 5030 Gembloux, Belgium
| | - C Bastin
- Walloon Breeding Association, B-5590 Ciney, Belgium
| | - N Gengler
- Agriculture, Bio-Engineering, and Chemistry Department, University of Liège, Gembloux Agro-Bio Tech, 5030 Gembloux, Belgium
| | - V Baeten
- Valorization of Agricultural Products Department, Walloon Agricultural Research Center, 5030 Gembloux, Belgium
| | - F Dehareng
- Valorization of Agricultural Products Department, Walloon Agricultural Research Center, 5030 Gembloux, Belgium.
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49
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Bonfatti V, Tiezzi F, Miglior F, Carnier P. Comparison of Bayesian regression models and partial least squares regression for the development of infrared prediction equations. J Dairy Sci 2017. [PMID: 28647337 DOI: 10.3168/jds.2016-12203] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
The objective of this study was to compare the prediction accuracy of 92 infrared prediction equations obtained by different statistical approaches. The predicted traits included fatty acid composition (n = 1,040); detailed protein composition (n = 1,137); lactoferrin (n = 558); pH and coagulation properties (n = 1,296); curd yield and composition obtained by a micro-cheese making procedure (n = 1,177); and Ca, P, Mg, and K contents (n = 689). The statistical methods used to develop the prediction equations were partial least squares regression (PLSR), Bayesian ridge regression, Bayes A, Bayes B, Bayes C, and Bayesian least absolute shrinkage and selection operator. Model performances were assessed, for each trait and model, in training and validation sets over 10 replicates. In validation sets, Bayesian regression models performed significantly better than PLSR for the prediction of 33 out of 92 traits, especially fatty acids, whereas they yielded a significantly lower prediction accuracy than PLSR in the prediction of 8 traits: the percentage of C18:1n-7 trans-9 in fat; the content of unglycosylated κ-casein and its percentage in protein; the content of α-lactalbumin; the percentage of αS2-casein in protein; and the contents of Ca, P, and Mg. Even though Bayesian methods produced a significant enhancement of model accuracy in many traits compared with PLSR, most variations in the coefficient of determination in validation sets were smaller than 1 percentage point. Over traits, the highest predictive ability was obtained by Bayes C even though most of the significant differences in accuracy between Bayesian regression models were negligible.
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Affiliation(s)
- V Bonfatti
- Department of Comparative Biomedicine and Food Science, University of Padova, 35020, Legnaro, Italy.
| | - F Tiezzi
- Department of Animal Science, North Carolina State University, Raleigh 27695
| | - F Miglior
- Centre for Genetic Improvement of Livestock, University of Guelph, Guelph, N1G 2W1, Ontario, Canada; Canadian Dairy Network, Guelph, N1K 1E5, Ontario, Canada
| | - P Carnier
- Department of Comparative Biomedicine and Food Science, University of Padova, 35020, Legnaro, Italy
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50
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McParland S, Berry DP. The potential of Fourier transform infrared spectroscopy of milk samples to predict energy intake and efficiency in dairy cows. J Dairy Sci 2017; 99:4056-4070. [PMID: 26947296 DOI: 10.3168/jds.2015-10051] [Citation(s) in RCA: 43] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2015] [Accepted: 01/14/2016] [Indexed: 12/18/2022]
Abstract
Knowledge of animal-level and herd-level energy intake, energy balance, and feed efficiency affect day-to-day herd management strategies; information on these traits at an individual animal level is also useful in animal breeding programs. A paucity of data (especially at the individual cow level), of feed intake in particular, hinders the inclusion of such attributes in herd management decision-support tools and breeding programs. Dairy producers have access to an individual cow milk sample at least once daily during lactation, and consequently any low-cost phenotyping strategy should consider exploiting measureable properties in this biological sample, reflecting the physiological status and performance of the cow. Infrared spectroscopy is the study of the interaction of an electromagnetic wave with matter and it is used globally to predict milk quality parameters on routinely acquired individual cow milk samples and bulk tank samples. Thus, exploiting infrared spectroscopy in next-generation phenotyping will ensure potentially rapid application globally with a negligible additional implementation cost as the infrastructure already exists. Fourier-transform infrared spectroscopy (FTIRS) analysis is already used to predict milk fat and protein concentrations, the ratio of which has been proposed as an indicator of energy balance. Milk FTIRS is also able to predict the concentration of various fatty acids in milk, the composition of which is known to change when body tissue is mobilized; that is, when the cow is in negative energy balance. Energy balance is mathematically very similar to residual energy intake (REI), a suggested measure of feed efficiency. Therefore, the prediction of energy intake, energy balance, and feed efficiency (i.e., REI) from milk FTIRS seems logical. In fact, the accuracy of predicting (i.e., correlation between predicted and actual values; root mean square error in parentheses) energy intake, energy balance, and REI from milk FTIRS in dairy cows was 0.88 (20.0MJ), 0.78 (18.6MJ), and 0.63 (22.0MJ), respectively, based on cross-validation. These studies, however, are limited to results from one research group based on data from 2 contrasting production systems in the United Kingdom and Ireland and would need to be replicated, especially in a range of production systems because the prediction equations are not accurate when the variability used in validation is not represented in the calibration data set. Heritable genetic variation exists for all predicted traits. Phenotypic differences in energy intake also exists among animals stratified based on genetic merit for energy intake predicted from milk FTIRS, substantiating the usefulness of such FTIR-predicted phenotypes not only for day-to-day herd management, but also as part of a breeding strategy to improve cow performance.
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Affiliation(s)
- S McParland
- Animal and Grassland Research and Innovation Center, Teagasc, Moorepark, Fermoy, Co. Cork, Ireland.
| | - D P Berry
- Animal and Grassland Research and Innovation Center, Teagasc, Moorepark, Fermoy, Co. Cork, Ireland
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