This book is the result of more than 20 years of experience in working with near-infrared spectroscopy for raw milk analysis. The totality of this work presents extensive possibilities for milk spectral measurements that can be carried out in dairy. Moving beyond the standard milk components such as fat, protein, or lactose, this book presents near-infrared spectroscopy as a method that can also be used in disease diagnostics. The measurements and experimental results presented here are all based on the utilization of usually neglected near-infrared regions―regions with strong absorbance of water. The author has found the water – light interaction discussed to be an immensely rich source of information, not only on milk composition but also on the physiological status of the animals involved. A special section of the book is dedicated to exploration of potential interfering factors that may influence the analysis and contribute to the robustness of the models. The research described in this book served as a basis for the development of the novel discipline aquaphotomics and is of interest to anyone working in this field.
Author(s): Roumiana Tsenkova, Jelena Muncan
Publisher: Springer
Year: 2021
Language: English
Pages: 351
City: Cham
Preface
About This Book
Part I Introduction: Why Aquaphotomics for Bio-diagnostics?
Part II NIRS for Determining the Composition of Milk from an Individual Cow
Part III Somatic Cell Count Determination in Milk from an Individual Cow
Part IV Influence of Perturbation on Measurements of Milk Composition
Part V Physiological Studies of Dairy Cows
Part VI Functional Studies of Dairy Cows
Part VII Conclusion and Future Perspectives
Contents
About the Authors
Abbreviations
Part I Introduction: Why Aquaphotomics for Bio-diagnostics?
1 Milk Quality Management: State of the Art and Contemporary Requirements
References
2 Near-Infrared Spectroscopy for Milk Quality Analysis: The State of the Art
References
3 Aquaphotomics for Bio-diagnostics: Advancing Beyond the State of the Art
References
Part II NIRS for Determining the Composition of Milk from an Individual Cow
4 Milk Fat Measurement
4.1 Introduction
4.2 Material and Methods
4.2.1 Samples
4.2.2 Reference Analysis
4.2.3 NIR Spectra Acquisition
4.2.4 Data Analysis
4.3 Results and Discussion
4.4 Conclusions
References
5 Milk Protein Measurement
5.1 Introduction
5.2 Material and Methods
5.2.1 Samples
5.2.2 Reference Analysis
5.2.3 NIR Spectra Acquisition
5.2.4 Data Analysis
5.2.5 Results and Discussion
5.3 Conclusions
References
6 Milk Lactose Measurement
6.1 Introduction
6.2 Experimental
6.2.1 Samples
6.2.2 Reference Analysis
6.2.3 NIR Spectra Acquisition
6.2.4 Data Analysis
6.3 Results and Discussion
6.4 Conclusions
References
7 Milk Urea Nitrogen Measurement
7.1 Introduction
7.2 Material and Methods
7.2.1 Instrumentation
7.2.2 Reference Analysis
7.2.3 Procedures
7.2.4 Data Analysis
7.3 Results and Discussion
7.4 Conclusions
References
8 Milk Fatty Acids Measurement
8.1 Introduction
8.2 Material and Methods
8.2.1 Milk Samples
8.2.2 Instrumentation and Procedures
8.2.3 Reference Analysis
8.2.4 Data Analysis
8.3 Results and Discussion
8.3.1 Reference FA Analysis by Gas Chromatography
8.3.2 Initial Exploration of NIR Spectra and Preliminary Regression Analysis
8.3.3 Development of NIR Equations to Predict Individual FA Using the 1600–1800 nm Region
8.4 Conclusion
References
Part III Somatic Cell Count Determination in Milk from an Individual Cow
9 Near-Infrared Spectroscopy: A New Diagnostic Tool for Determination of Somatic Cell Count
9.1 Introduction
9.2 Material and Methods
9.2.1 Samples
9.2.2 Reference Analysis
9.2.3 NIR Spectra Acquisition
9.2.4 Data Analysis
9.3 Results and Discussion
9.4 Conclusions
References
10 Non-destructive Somatic Cell Count Measurement Using Near-Infrared Spectra of Milk in the 400–1,100 nm Short Wavelength Region
10.1 Introduction
10.2 Material and Methods
10.2.1 Samples
10.2.2 NIR Spectra Acquisition
10.2.3 Reference Analysis
10.2.4 Data Analysis
10.3 Results and Discussion
10.4 Conclusions
References
11 Measurement of Somatic Cell Count in the 700–1,100 nm Short Wavelength Region Using PLS Regression and Referenced Data
11.1 Introduction
11.2 Material and Methods
11.2.1 Instrumentation
11.2.2 Reference analysis
11.2.3 Procedures
11.2.4 Data Analysis
11.3 Results and Discussion
11.4 Conclusion
References
12 Measurement of Somatic Cell Count in the 700–1,100 nm Short Wavelength Region: Comparison of At-Line and On-Line Measurement Modes
12.1 Introduction
12.2 Material and Methods
12.2.1 Milk Samples and NIR Spectra
12.2.2 Reference analysis
12.2.3 Data Analysis
12.3 Results and Discussion
12.4 Conclusions
References
13 Influence of Sample Thickness and Individual Characteristics of Each Cow on Milk Composition Measurement in the Spectral Region from 700 to 1,100 nm
13.1 Introduction
13.2 Material and Methods
13.2.1 Samples
13.2.2 NIR Spectra Acquisition
13.2.3 Data Analysis
13.3 Results
13.4 Discussion
References
Part IV Influence of Perturbation on Measurements of Milk Composition
14 Influence of Individual Characteristics of Each Cow on Milk Composition Measurement in the Spectral Region from 1,100 to 2,400 nm
14.1 Introduction
14.2 Material and Methods
14.2.1 Samples
14.2.2 NIR Spectra Acquisition
14.2.3 Data Analysis
14.3 Results and Discussion
14.3.1 Milk Composition Analysis
14.3.2 Data Analysis
14.4 Conclusions
References
16 Mastitis Influence on Milk Composition Measurement in the Spectral Region from 1,100 to 2,400 nm
16.1 Introduction
16.2 Material and Methods
16.2.1 Samples
16.2.2 Reference Analysis
16.2.3 NIR Spectra Acquisition
16.2.4 Data Analysis
16.3 Results and Discussion
16.4 Conclusions
References
17 Interrelation Between the Composition and Near-Infrared Spectra of Milk, Blood Plasma and Rumen Juice of Lactating Cows
17.1 Introduction
17.2 Experimental
17.2.1 Samples
17.2.2 Reference Analysis
17.2.3 Instrumentation
17.2.4 Data Analysis
17.3 Results and Discussion
17.3.1 Milk Composition and Correlation with the Spectra of Rumen Juice and Blood Plasma
17.3.2 Rumen Juice Composition and Correlation with the Spectra of Milk
17.3.3 Blood Plasma Composition and Correlation with Milk Spectra
17.4 Conclusions
References
18 Near-Infrared Spectra of Urine for Mastitis Diagnostics
18.1 Introduction
18.2 Material and Methods
18.2.1 Urine and Milk Samples
18.2.2 Urine Spectra
18.2.3 Data Analysis
18.3 Results and Discussion
18.4 Conclusions
References
Part V Physiological Studies of Dairy Cows
19 Mastitis Diagnostics Based on the Near-Infrared Spectra of Cow’s Milk, Blood and Urine
19.1 Introduction
19.2 Material and Methods
19.2.1 Samples
19.2.2 Spectral Acquisition
19.2.3 Data Analysis
19.3 Results and Discussion
19.4 Conclusions
References
20 Near-Infrared Spectra of Udder Quarter Foremilk for Measurement of Both Somatic Cell Count and Absolute Electrical Conductivity and for Diagnosis of Mastitis
20.1 Introduction
20.2 Material and Methods
20.2.1 Milk Samples and Measurement of SCC and of Absolute Electrical Conductivity
20.2.2 NIR Spectra Acquisition
20.2.3 Data Analysis
20.3 Results
20.3.1 Quantitative Determination of SCC and AEC by NIRS
20.3.2 Qualitative Analysis of Milk Samples—Classification-Based Disease Diagnosis
20.4 Discussion
20.5 Conclusions
References
21 Real-Time Near-Infrared Spectroscopy of Udder Tissue for Mastitis Diagnosis
21.1 Introduction
21.2 Material and Methods
21.2.1 Samples
21.2.2 NIR Spectra Acquisition
21.2.3 Milk Constituents Reference Analysis
21.2.4 Data Analysis
21.3 Results and Discussion
21.3.1 Initial Spectral Exploration and Outlier Detection
21.3.2 Exploration of Differences Between Udder Quarters
21.3.3 Mastitis Diagnosis Based on the NIR Spectra of Udder Quarter Tissues
21.4 Conclusions
References
22 Estrus Detection in Dairy Cows Using Near-Infrared Spectroscopy and Aquaphotomics
22.1 Introduction
22.2 Material and Methods
22.2.1 Experiment 1: Measurements of Progesterone in Blood and in Milk
22.2.2 Experiment 2: The Water Spectral Pattern of Milk as a Biomarker of Estrus
22.3 Results and Discussion
22.3.1 Progesterone Measurements
22.3.2 Water Spectral Pattern of Milk as a Biomarker of Estrus
22.4 Conclusions
References
23 Two-Dimensional Correlation Analysis of the Near-Infrared Spectra of Milk and Milk Constituents: Temporal Study of Postpartum Adaptation in Dairy Cows
23.1 Introduction
23.2 Material and Methods
23.2.1 Samples
23.2.2 NIR Spectra Acquisition
23.2.3 Data Preprocessing and Analysis
23.3 Results and Discussion
23.3.1 NIR Spectra of Milk
23.3.2 Generalized 2D-Correlation Analysis: Near-Infrared Spectra of Milk
23.3.3 Generalized 2D-Correlation Analysis: Milk Constituents
23.4 Conclusions
References
Part VI Functional Studies of Dairy Cows
24 Two-Dimensional Near-Infrared Correlation Spectroscopy of an Individual Cow’s Milk for Functional Study of Somatic Cell Count Changes in Milk
24.1 Introduction
24.2 Material and Methods
24.3 Analysis
24.3.1 Data Sectioning and Preprocessing
24.3.2 Correlation Analysis
24.4 Results and Discussion
24.5 Conclusions
References
25 Wavelet Transform of Near-Infrared Individual Cow’s Milk for Single-Spectrum Mastitis Diagnosis
25.1 Introduction
25.2 Material and Methods
25.2.1 Samples
25.2.2 Reference Analysis
25.2.3 NIR Spectra Acquisition
25.2.4 Data Analysis
25.3 Results and Discussion
25.4 Conclusions
References
26 Artificial Neural Network Applied to Near-Infrared Spectra of Raw Milk for Dairy Cow Feeding Management
26.1 Introduction
26.2 Experimental
26.2.1 Feeding Experiments and Milk Samples
26.2.2 NIR Spectra Acquisition
26.2.3 Reference Analysis
26.2.4 Neural Network
26.3 Results and Discussion
26.4 Conclusions
References
27 Artificial Intelligence in Dairy Farming: The Near-Infrared Approach
27.1 Introduction
27.2 Material and Methods
27.2.1 Samples
27.2.2 NIR Spectra Acquisition
27.2.3 Reference Analysis
27.2.4 Data Analysis
27.3 Results and Discussion
27.4 Conclusions
References
Part VII Conclusion and Future Perspectives
28 Conclusion and Future Perspectives
References
