Application of mid-infrared spectroscopy to enhance bovine milk technological traits in dairy industry � Massimo DE MARCHI, � Martino CASSANDRO, Mauro PENASA �
Summary � 1. Why mid-infrared spectroscopy (MIRS)? � 2. What are milk technological traits? � 3. Can MIRS predict milk technological traits? � ü � Milk coagulation properties � ü Milk acidity � ü � Milk mineral composition � ü � Heat coagulation time � 4. How can milk technological traits be used in dairy industry? � ü � Milk payment systems � ü � Genetics and breeding � 5. Which traits in the future? � 6. Conclusions � � April 16, 2015 – Namur (Belgium) – Prof. Massimo DE MARCHI – massimo.demarchi@unipd.it �
Why mid-infrared spectroscopy (MIRS)? � 1. We need “new phenotypes” - the concept of quality is changing (in relation to market requirements) � De Marchi et al., 2014. Invited review: Mid-infrared spectroscopy as phenotyping tool for milk traits. J. Dairy Sci. 97:1171-1186 � April 16, 2015 – Namur (Belgium) – Prof. Massimo DE MARCHI – massimo.demarchi@unipd.it �
Why mid-infrared spectroscopy (MIRS)? � 1. We need “new phenotypes” - the concept of quality is changing (in relation to market requirements) � 2. Fast, cheap, and high-throughput method � 3. It is widely used to predict traditional traits in official milk-recording schemes worldwide � 4. Several laboratories have been storing spectral data to predict a posteriori several phenotypes � � De Marchi et al., 2014. Invited review: Mid-infrared spectroscopy as phenotyping tool for milk traits. J. Dairy Sci. 97:1171-1186 � April 16, 2015 – Namur (Belgium) – Prof. Massimo DE MARCHI – massimo.demarchi@unipd.it �
Why mid-infrared spectroscopy (MIRS)? � 1. We need “new phenotypes” - the concept of quality is changing (in relation to market requirements) � 2. Fast, cheap, and high-throughput method � 3. It is widely used to predict traditional traits in official milk-recording schemes worldwide � 4. Several laboratories have been storing spectral data to predict a posteriori several phenotypes � 5. A phenotype should show good to optimal accuracy of prediction, depending on its use (Berry et al., 2012) � � De Marchi et al., 2014. Invited review: Mid-infrared spectroscopy as phenotyping tool for milk traits. J. Dairy Sci. 97:1171-1186 � April 16, 2015 – Namur (Belgium) – Prof. Massimo DE MARCHI – massimo.demarchi@unipd.it �
Why mid-infrared spectroscopy (MIRS)? � 1. Fatty acid composition (Soyeurt et al., 2006, 2008, 2011; Rutten et al., 2009; De Marchi et al., 2011; Ferrand et al., 2011; Maurice-Van Eijndhoven et al., 2013) � 2. Milk protein composition (Luginbühl, 2002; Sørensen et al., 2003; Etzion et al., 2004; De Marchi et al., 2009; Bonfatti et al., 2011; Rutten et al., 2011) � 3. Melamine content (Balabin and Smirnov, 2011) � 4. Ketone bodies (Heuer et al., 2001; de Roos et al., 2007; van Knegsel et al., 2010; van der Drift et al., 2012) � 5. Body energy status (McParland et al., 2011) � 6. Free amino acid (McDermott et al., 2015) � 7. ... and milk technological traits � April 16, 2015 – Namur (Belgium) – Prof. Massimo DE MARCHI – massimo.demarchi@unipd.it �
What are milk technological traits? � 1. Traits that characterize milk for its destination � April 16, 2015 – Namur (Belgium) – Prof. Massimo DE MARCHI – massimo.demarchi@unipd.it �
What are milk technological traits? � 1. Traits that characterize milk for its destination � 2. Milk features related to cheese production � ü The volume of milk processed for cheese manufacturing is growing worldwide (by 2% annually - FAOSTAT, 2014 ) � ü Milk coagulation properties (MCP) affect the efficiency of the cheese-making process (Bynum and Olson, 1982; Riddell-Lawrence and Hicks, 1989) � ü Milk acidity [pH and titratable acidity (TA)], milk mineral composition [Calcium (Ca) and Phosphorus (P)] (Toffanin et al., 2015) � ü Cheese yield (what is the reference for cheese yield?) � April 16, 2015 – Namur (Belgium) – Prof. Massimo DE MARCHI – massimo.demarchi@unipd.it �
What are milk technological traits? � 1. Traits that characterize milk for its destination � 2. Milk features related to cheese production � 3. Milk features related to the production of milk powder � ü Heat coagulation time (HCT) is of great importance for the dairy industry since all milk intended for human consumption is subjected to heat treatments � ü Milk with high heat susceptibility (i.e., low HCT) is not suitable for milk processability, especially for the production of milk powder (mechanical obstruction of machinery) (Visentin et al., 2015) � April 16, 2015 – Namur (Belgium) – Prof. Massimo DE MARCHI – massimo.demarchi@unipd.it �
Can MIRS predict milk technological traits? � 1. Milk coagulation properties (MCP) � MILK PREPARATION � RIPENING � COAGULATION � SALTING � SYNERESIS � COOKING � (depends on the type of cheese) � April 16, 2015 – Namur (Belgium) – Prof. Massimo DE MARCHI – massimo.demarchi@unipd.it �
Can MIRS predict milk technological traits? � 1. Milk coagulation properties (MCP) � a. Lactodynamograph (Formagraph) � April 16, 2015 – Namur (Belgium) – Prof. Massimo DE MARCHI – massimo.demarchi@unipd.it �
Can MIRS predict milk technological traits? � 1. Milk coagulation properties (MCP) � a. Lactodynamograph (Formagraph) � b. Common measures of MCP are rennet coagulation time (RCT; min), curd-firming time (k 20 ; min), and curd firmness (a 30 ; mm) � 0" 30" 60" min" � MILK"+"Rennet" a 60 ,"mm" a 30 ,"mm" RCT,"min" K 20 ,"min;"a"="20"mm" April 16, 2015 – Namur (Belgium) – Prof. Massimo DE MARCHI – massimo.demarchi@unipd.it �
Can MIRS predict milk technological traits? � 1. Milk coagulation properties (MCP) � a. Lactodynamograph (Formagraph) � b. Common measures of MCP are rennet coagulation time (RCT; min), curd-firming time (k 20 ; min), and curd firmness (a 30 ; mm) � � Optimum Good Bad � April 16, 2015 – Namur (Belgium) – Prof. Massimo DE MARCHI – massimo.demarchi@unipd.it �
Can MIRS predict milk technological traits? � 1. Milk coagulation properties (MCP) � a. Common measures of MCP are rennet coagulation time (RCT; min), curd-firming time (k 20 ; min), and curd firmness (a 30 ; mm) � b. Lactodynamograph (Formagraph) � c. Sources of variation of MCP: � ü instrument and methodology of analyses (Pretto et al., 2011) � ü milk quality composition (e.g., protein composition, TA, SCC - Okigbo et al., 1985; Politis and Ng-Kwai-Hang, 1988; Formaggioni et al., 2001; De Marchi et al., 2007) � ü DIM (e.g., Penasa et al., 2014) , herd and environmental conditions � ü species, breed (Macheboeuf et al., 1993; Auldist et al., 2002; Bencini, 2002; Park et al., 2007; De Marchi et al., 2007, 2008; Martin et al., 2009) � ü additive genetic variation (Ikonen et al., 1999; Tyriseva ̈ et al., 2004, 2008; Cassandro et al., 2008; Comin et al., 2008; Vallas et al., 2010) � April 16, 2015 – Namur (Belgium) – Prof. Massimo DE MARCHI – massimo.demarchi@unipd.it �
Can MIRS predict milk technological traits? � 1. Milk coagulation properties (MCP) � De Marchi et al., 2014. Invited review: Mid-infrared spectroscopy as phenotyping tool for milk traits. J. Dairy Sci. 97:1171-1186 � April 16, 2015 – Namur (Belgium) – Prof. Massimo DE MARCHI – massimo.demarchi@unipd.it �
Can MIRS predict milk technological traits? � 1. Milk coagulation properties (MCP) � April 16, 2015 – Namur (Belgium) – Prof. Massimo DE MARCHI – massimo.demarchi@unipd.it �
Can MIRS predict milk technological traits? � 1. Milk coagulation properties (MCP) � 2. Milk acidity (pH and TA): � a. affects the aggregation rate of paracasein micelles, the reactivity of rennet, and the rate of syneresis � b. milk with low acidity is generally considered unsuitable for cheese-making, because of negative effects on the rheology of the rennet curd and on the textural properties of the cheese paste � c. favorable relationships of TA with MCP and cheese yield (Pretto et al., 2013) � April 16, 2015 – Namur (Belgium) – Prof. Massimo DE MARCHI – massimo.demarchi@unipd.it �
Can MIRS predict milk technological traits? � 1. Milk coagulation properties (MCP) � 2. Milk acidity (pH and TA) � Authors � Acidity Trait � n � 1-VR � Visentin et al., 2014 � pH � 553 � 0.71 � Toffanin et al., 2015 � TA � 208 � 0.74 � 1-VR = coefficient of determination in validation � April 16, 2015 – Namur (Belgium) – Prof. Massimo DE MARCHI – massimo.demarchi@unipd.it �
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