Roumiana Tsenkova, Jelena Muncan
Aquaphotomics for Bio-diagnostics in Dairy
Applications of Near-Infrared Spectroscopy
Roumiana Tsenkova, Jelena Muncan
Aquaphotomics for Bio-diagnostics in Dairy
Applications of Near-Infrared Spectroscopy
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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…mehr
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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.
Produktdetails
- Produktdetails
- Verlag: Springer / Springer Nature Singapore / Springer, Berlin
- Artikelnr. des Verlages: 978-981-16-7113-5
- 1st ed. 2022
- Seitenzahl: 352
- Erscheinungstermin: 16. November 2021
- Englisch
- Abmessung: 241mm x 160mm x 25mm
- Gewicht: 694g
- ISBN-13: 9789811671135
- ISBN-10: 9811671133
- Artikelnr.: 62556087
- Verlag: Springer / Springer Nature Singapore / Springer, Berlin
- Artikelnr. des Verlages: 978-981-16-7113-5
- 1st ed. 2022
- Seitenzahl: 352
- Erscheinungstermin: 16. November 2021
- Englisch
- Abmessung: 241mm x 160mm x 25mm
- Gewicht: 694g
- ISBN-13: 9789811671135
- ISBN-10: 9811671133
- Artikelnr.: 62556087
Prof. Roumiana Tsenkova holds both masters and doctoral degrees in Automation Engineering from the Technical University, Rousse, Bulgaria, as well as a second doctorate in Agriculture from Hokkaido University, Japan. Her investigations in near-infrared spectroscopy (NIRS) started by developing a sensor for disease diagnostics (mammary gland inflammation) at Moscow Agricultural Academy of Science, Russia. In 1990, Dr. Tsenkova was awarded a Japanese Monbusho Scholarship for post-doctoral studies on sensors for robotic milking at Obihiro University, Japan and in 1992, she moved to Hokkaido University as a researcher, to develop NIRS technology for biomonitoring. In 1996 Prof. Tsenkova started working at Kobe University where, as a tenured professor, she taught Fluid Mechanics and Biomeasurement Technology. Since 2015, she serves as an adjunct professor at the prestigious Medical Faculty of Keio University in Tokyo. In April, 2021 Prof. Tsenkova founded the Aquaphotomics Research Department at Kobe University, the first such department in the world, solely devoted to the aquaphotomics studies, where she holds a position of the specially appointed professor. Prof. Tsenkoväs primary area of interest is the use of NIRS and multivariate analyses for biodiagnostics and biomonitoring related to functional studies in life science, biotechnology, and agriculture. She was the first ever to apply NIRS for disease diagnostics. In 2005, at the International Conference of NIRS, she proposed and gave a name to the new discipline called aquaphotomics as a new scientific field to study the collective characterization and quantification of pools of water molecules that have the same molecular vibration and translate into structure, function, and dynamics of organisms or aqueous systems. Her work is recognized throughout the world as attested by numerous invited talks, collaborative studies, and fifteen international and Japanese patents. Dr. Tsenkova has written more than 100 peer reviewed papers and book chapters, and received many international awards, among them the Tomas Hirschfeld Award for her work on NIRS for Disease Diagnosis and Pathogen Identification. Dr. Jelena Muncan obtained her Ph.D. degree in Biomedical Engineering (2014) at the University of Belgrade, Serbia, in the field of non-invasive glucose sensing. In 2017, she received Japanese Society for Promotion of Science post-doctoral research fellowship at Kobe University, Bio measurement Technology Laboratory of Graduate School of Agriculture where, under the guidance of Prof. Dr. Roumiana Tsenkova, she was researching applications of aquaphotomics for non-invasive mastitis diagnosis in dairy cows. She is currently a specially appointed assistant professor at the Aquaphotomics Research Department, Kobe University, Japan. Dr. Muncan¿s research area is very wide and highly multidisciplinary, encompassing characterization of nanomaterials/materials/biomaterials and their interaction with water, food preservation, water quality, biomedical diagnostics, monitoring, and therapy. In all these research projects, aquaphotomics plays key role. Her research efforts are directed at better understanding the role water plays in aqueous and biological systems and harvesting the new knowledge for technological applications. Jelena Mun¿an is the author or co-author of more than 100 publications published in international journals and monographs as well as presented at various international conferences worldwide.
Part I: Introduction.- 1. Milk Quality Management: State of the Art and Contemporary Requirements.- 2. Near-infrared Spectroscopy for Milk Quality Analysis: The State of the Art.- 3. Aquaphotomics: Advancing Beyond the State of the Art.- Part II: NIRS for Individual Cow's Milk Composition Measurement.- 4. Milk Fat Measurement.- 5. Milk Protein Measurement.- 6. Milk Lactose Measurement.- 7. Milk Urea Nitrogen Measurement.- 8. Milk Fatty Acids Measurement.- Part III: NIRS for Somatic Cell Count Determination in Individual Cow's Milk.- 9. Near-infrared Spectroscopy: A New Diagnostic Tool for Determination of Somatic Cell Count.- 10. Non-destructive Somatic Cell Count Measurement Using Near-Infrared Spectra of Milk in the 400-1,100 nm Short Wavelength Region.- 11. Measurement of Somatic Cell Count in the 700-1,100 nm Short Wavelength Region using PLS Regression and Referenced Data.- 12. Measurement of Somatic Cell Count in the 700-1,100 nm Short Wavelength Region: Comparison of At-line and On-line Measurement Modes.- Part IV: Perturbation Influence on NIRS Measurement of Milk Composition.- 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.- 14. Influence of Individual Characteristics of Each Cow on Milk Composition Measurement in the Spectral Region from 1,100 to 2,400 nm.- 15. Mastitis Influence on Protein Measurement in the spectral region from 700 to 1,100 nm.- 16. Mastitis Influence on Milk Composition Measurement in the Spectral Region from 1,100 to 2,400 nm.- Part V: Near Infrared Spectroscopy for Physiological Studies of Dairy Cows.- 17. Interrelation between the Composition and Near-Infrared Spectra of Milk, Blood Plasma and Rumen Juice of Lactating Cows.- 18. Near-Infrared Spectra of Urine for Mastitis Diagnostics.- 19. Mastitis Diagnostics based on the Near-Infrared Spectra of Cow's Milk, Blood and Urine.- 20. Near-Infrared Spectra of Udder Quarter Foremilk for Measurement of Both Somatic Cell Count and Absolute Electrical Conductivity and for Diagnosis of Mastitis.- 21. Real-time Near-Infrared Spectroscopy of Udder Tissue for Mastitis Diagnosis.- 22. Estrus Detection in Dairy Cows Using Near-Infrared Spectroscopy and Aquaphotomics.- Part VI: Near Infrared Spectroscopy and Artificial Intelligence for Functional Studies of Dairy Cows.- 23. Two-dimensional Correlation Analysis of the Near-Infrared Spectra of Milk and Milk Constituents: Temporal Study of Post-partum Adaptation in 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.- 25. Wavelet Transform of Near-Infrared Individual Cow's Milk for Single-Spectrum Mastitis Diagnosis.- 26. Artificial Neural Network Applied to Near-Infrared Spectra of Raw Milk for Dairy Cow Feeding Management.- 27. Artificial Intelligence in Dairy Farming: The Near-Infrared Approach.- Part VII: Conclusion and Future Perspectives.- 28. Conclusion and Future Perspectives.
Part I: Introduction.- 1. Milk Quality Management: State of the Art and Contemporary Requirements.- 2. Near-infrared Spectroscopy for Milk Quality Analysis: The State of the Art.- 3. Aquaphotomics: Advancing Beyond the State of the Art.- Part II: NIRS for Individual Cow’s Milk Composition Measurement.- 4. Milk Fat Measurement.- 5. Milk Protein Measurement.- 6. Milk Lactose Measurement.- 7. Milk Urea Nitrogen Measurement.- 8. Milk Fatty Acids Measurement.- Part III: NIRS for Somatic Cell Count Determination in Individual Cow’s Milk.- 9. Near-infrared Spectroscopy: A New Diagnostic Tool for Determination of Somatic Cell Count.- 10. Non-destructive Somatic Cell Count Measurement Using Near-Infrared Spectra of Milk in the 400–1,100 nm Short Wavelength Region.- 11. Measurement of Somatic Cell Count in the 700–1,100 nm Short Wavelength Region using PLS Regression and Referenced Data.- 12. Measurement of Somatic Cell Count in the 700–1,100 nm Short Wavelength Region: Comparison of At-line and On-line Measurement Modes.- Part IV: Perturbation Influence on NIRS Measurement of Milk Composition.- 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.- 14. Influence of Individual Characteristics of Each Cow on Milk Composition Measurement in the Spectral Region from 1,100 to 2,400 nm.- 15. Mastitis Influence on Protein Measurement in the spectral region from 700 to 1,100 nm.- 16. Mastitis Influence on Milk Composition Measurement in the Spectral Region from 1,100 to 2,400 nm.- Part V: Near Infrared Spectroscopy for Physiological Studies of Dairy Cows.- 17. Interrelation between the Composition and Near-Infrared Spectra of Milk, Blood Plasma and Rumen Juice of Lactating Cows.- 18. Near-Infrared Spectra of Urine for Mastitis Diagnostics.- 19. Mastitis Diagnostics based on the Near-Infrared Spectra of Cow’s Milk, Blood and Urine.- 20. Near-Infrared Spectra of Udder Quarter Foremilk for Measurement of Both Somatic Cell Count and Absolute Electrical Conductivity and for Diagnosis of Mastitis.- 21. Real-time Near-Infrared Spectroscopy of Udder Tissue for Mastitis Diagnosis.- 22. Estrus Detection in Dairy Cows Using Near-Infrared Spectroscopy and Aquaphotomics.- Part VI: Near Infrared Spectroscopy and Artificial Intelligence for Functional Studies of Dairy Cows.- 23. Two-dimensional Correlation Analysis of the Near-Infrared Spectra of Milk and Milk Constituents: Temporal Study of Post-partum Adaptation in 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.- 25. Wavelet Transform of Near-Infrared Individual Cow’s Milk for Single-Spectrum Mastitis Diagnosis.- 26. Artificial Neural Network Applied to Near-Infrared Spectra of Raw Milk for Dairy Cow Feeding Management.- 27. Artificial Intelligence in Dairy Farming: The Near-Infrared Approach.- Part VII: Conclusion and Future Perspectives.- 28. Conclusion and Future Perspectives.
Part I: Introduction.- 1. Milk Quality Management: State of the Art and Contemporary Requirements.- 2. Near-infrared Spectroscopy for Milk Quality Analysis: The State of the Art.- 3. Aquaphotomics: Advancing Beyond the State of the Art.- Part II: NIRS for Individual Cow's Milk Composition Measurement.- 4. Milk Fat Measurement.- 5. Milk Protein Measurement.- 6. Milk Lactose Measurement.- 7. Milk Urea Nitrogen Measurement.- 8. Milk Fatty Acids Measurement.- Part III: NIRS for Somatic Cell Count Determination in Individual Cow's Milk.- 9. Near-infrared Spectroscopy: A New Diagnostic Tool for Determination of Somatic Cell Count.- 10. Non-destructive Somatic Cell Count Measurement Using Near-Infrared Spectra of Milk in the 400-1,100 nm Short Wavelength Region.- 11. Measurement of Somatic Cell Count in the 700-1,100 nm Short Wavelength Region using PLS Regression and Referenced Data.- 12. Measurement of Somatic Cell Count in the 700-1,100 nm Short Wavelength Region: Comparison of At-line and On-line Measurement Modes.- Part IV: Perturbation Influence on NIRS Measurement of Milk Composition.- 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.- 14. Influence of Individual Characteristics of Each Cow on Milk Composition Measurement in the Spectral Region from 1,100 to 2,400 nm.- 15. Mastitis Influence on Protein Measurement in the spectral region from 700 to 1,100 nm.- 16. Mastitis Influence on Milk Composition Measurement in the Spectral Region from 1,100 to 2,400 nm.- Part V: Near Infrared Spectroscopy for Physiological Studies of Dairy Cows.- 17. Interrelation between the Composition and Near-Infrared Spectra of Milk, Blood Plasma and Rumen Juice of Lactating Cows.- 18. Near-Infrared Spectra of Urine for Mastitis Diagnostics.- 19. Mastitis Diagnostics based on the Near-Infrared Spectra of Cow's Milk, Blood and Urine.- 20. Near-Infrared Spectra of Udder Quarter Foremilk for Measurement of Both Somatic Cell Count and Absolute Electrical Conductivity and for Diagnosis of Mastitis.- 21. Real-time Near-Infrared Spectroscopy of Udder Tissue for Mastitis Diagnosis.- 22. Estrus Detection in Dairy Cows Using Near-Infrared Spectroscopy and Aquaphotomics.- Part VI: Near Infrared Spectroscopy and Artificial Intelligence for Functional Studies of Dairy Cows.- 23. Two-dimensional Correlation Analysis of the Near-Infrared Spectra of Milk and Milk Constituents: Temporal Study of Post-partum Adaptation in 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.- 25. Wavelet Transform of Near-Infrared Individual Cow's Milk for Single-Spectrum Mastitis Diagnosis.- 26. Artificial Neural Network Applied to Near-Infrared Spectra of Raw Milk for Dairy Cow Feeding Management.- 27. Artificial Intelligence in Dairy Farming: The Near-Infrared Approach.- Part VII: Conclusion and Future Perspectives.- 28. Conclusion and Future Perspectives.
Part I: Introduction.- 1. Milk Quality Management: State of the Art and Contemporary Requirements.- 2. Near-infrared Spectroscopy for Milk Quality Analysis: The State of the Art.- 3. Aquaphotomics: Advancing Beyond the State of the Art.- Part II: NIRS for Individual Cow’s Milk Composition Measurement.- 4. Milk Fat Measurement.- 5. Milk Protein Measurement.- 6. Milk Lactose Measurement.- 7. Milk Urea Nitrogen Measurement.- 8. Milk Fatty Acids Measurement.- Part III: NIRS for Somatic Cell Count Determination in Individual Cow’s Milk.- 9. Near-infrared Spectroscopy: A New Diagnostic Tool for Determination of Somatic Cell Count.- 10. Non-destructive Somatic Cell Count Measurement Using Near-Infrared Spectra of Milk in the 400–1,100 nm Short Wavelength Region.- 11. Measurement of Somatic Cell Count in the 700–1,100 nm Short Wavelength Region using PLS Regression and Referenced Data.- 12. Measurement of Somatic Cell Count in the 700–1,100 nm Short Wavelength Region: Comparison of At-line and On-line Measurement Modes.- Part IV: Perturbation Influence on NIRS Measurement of Milk Composition.- 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.- 14. Influence of Individual Characteristics of Each Cow on Milk Composition Measurement in the Spectral Region from 1,100 to 2,400 nm.- 15. Mastitis Influence on Protein Measurement in the spectral region from 700 to 1,100 nm.- 16. Mastitis Influence on Milk Composition Measurement in the Spectral Region from 1,100 to 2,400 nm.- Part V: Near Infrared Spectroscopy for Physiological Studies of Dairy Cows.- 17. Interrelation between the Composition and Near-Infrared Spectra of Milk, Blood Plasma and Rumen Juice of Lactating Cows.- 18. Near-Infrared Spectra of Urine for Mastitis Diagnostics.- 19. Mastitis Diagnostics based on the Near-Infrared Spectra of Cow’s Milk, Blood and Urine.- 20. Near-Infrared Spectra of Udder Quarter Foremilk for Measurement of Both Somatic Cell Count and Absolute Electrical Conductivity and for Diagnosis of Mastitis.- 21. Real-time Near-Infrared Spectroscopy of Udder Tissue for Mastitis Diagnosis.- 22. Estrus Detection in Dairy Cows Using Near-Infrared Spectroscopy and Aquaphotomics.- Part VI: Near Infrared Spectroscopy and Artificial Intelligence for Functional Studies of Dairy Cows.- 23. Two-dimensional Correlation Analysis of the Near-Infrared Spectra of Milk and Milk Constituents: Temporal Study of Post-partum Adaptation in 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.- 25. Wavelet Transform of Near-Infrared Individual Cow’s Milk for Single-Spectrum Mastitis Diagnosis.- 26. Artificial Neural Network Applied to Near-Infrared Spectra of Raw Milk for Dairy Cow Feeding Management.- 27. Artificial Intelligence in Dairy Farming: The Near-Infrared Approach.- Part VII: Conclusion and Future Perspectives.- 28. Conclusion and Future Perspectives.