Chemical lean determination of boneless beef and lamb using a halogen moisture analyser
Peter Watkins
CSIRO Agriculture and Food, 671 Sneydes Road, Werribee, Vic., 3030, Australia. Email: Peter.Watkins@csiro.au
Animal Production Science 61(7) 715-720 https://doi.org/10.1071/AN20445
Submitted: 31 July 2020 Accepted: 21 January 2021 Published: 2 March 2021
Journal Compilation © CSIRO 2021 Open Access CC BY
Abstract
Context: Chemical lean (CL) is an important metric used by the Australian meat industry to describe fat content of meat product. It is a minimum meat specification included in contracts between Australian vendors of bulk packed boneless manufacturing meat and overseas or domestic buyers and can be regarded as the complement of chemically determined fat in meat (% fat, CL = 100-% fat). The microwave moisture method is commonly used for measuring CL content of meat in Australian abattoirs, relying on a relationship between CL and moisture content of boneless meat. It is regarded as a quick and easy method to use. More recently, newer methods for moisture analysis have become available which may also be suitable for CL determination, including commercial halogen moisture analysers (HMAs). HMAs use a halogen lamp as a source of infrared radiation that is absorbed by a sample, which then results in moisture loss.
Aims: This study aimed to compare the use of HMAs for CL determination of beef and lamb to that obtained from Soxhlet extraction technique, which is the AOAC Final Action Method for determining fat in meat and accepted as the reference method for fat determination. Additionally, the study sought to validate the use of HMAs as a method for CL determination in the Australian meat industry.
Methods: HMAs were used to determine the moisture content of six beef and one lamb samples, which were used to calculate the CL content. The fat content of the samples was also determined using Soxhlet fat extraction. Passing-Bablok regression and Bland-Altman plot analysis were used to identify any differences and bias between the methods, respectively.
Key results: Passing-Bablok regression showed that there was no difference between methods, while Bland-Altman plot analysis indicated no bias was evident between the methods. While some differences were apparent between approaches either due to using moisture as a proxy for fat/CL compared with continual solvent extraction or sample heterogeneity, sufficient agreement existed between results to lie within an acceptance criterion of 1.2 CL units.
Conclusion: The use of HMAs was substantiated as a method for CL determination in the Australian meat industry and has been accredited by AUS-MEAT Ltd as a method for boneless beef and lamb.
Implications: HMAs can be used in the Australian meat industry for CL determination and represent a relatively simpler and easier approach for this important industry metric.
Keywords: chemical lean, chemistry, fat determination, meat quality.
References
Anonymous (2015) Drying oven vs. halogen moisture analyzer: a practical guide to compare methods. (Mettler Toledo AG: Greifensee, Switzerland)Bilić-Zulle L (2011) Comparison of methods: passing and Bablok regression. Biochemia Medica 21, 49–52.
| Comparison of methods: passing and Bablok regression.Crossref | GoogleScholarGoogle Scholar | 22141206PubMed |
Carstensen B, Gurrin L, Ekstrøm CT, Figurski M (2020) ‘MethComp: analysis of agreement in method comparison studies.’ Available at https://CRAN.R-project.org/package=MethComp.
Doğan NÖ (2018) Bland-Altman analysis: a paradigm to understand correlation and agreement. Turkish Journal of Emergency Medicine 18, 139–141.
| Bland-Altman analysis: a paradigm to understand correlation and agreement.Crossref | GoogleScholarGoogle Scholar | 30533555PubMed |
Eustace IJ, McPhail NG (2006) Meat technology information sheet: a guide to calibration and verification of accuracy for instruments for estimation of chemical lean content for manufacturing. Available at http://meatupdate.csiro.au/chemical-lean.pdf.
Eustace IJ, McPhail NG, Small A (2006) Meat technology information sheet: microwave method for chemical lean determination. Available at http://meatupdate.csiro.au/infosheets/Microwave%20Method%20for%20chemical%20Lean%20Determination%20-%201997.pdf.
Giavarina D (2015) Understanding Bland Altman analysis. Biochemia Medica 25, 141–151.
| Understanding Bland Altman analysis.Crossref | GoogleScholarGoogle Scholar | 26110027PubMed |
Kalra A (2017) Decoding the Bland–Altman plot: basic review. Journal of the Practice of Cardiovascular Sciences 3, 36–38.
| Decoding the Bland–Altman plot: basic review.Crossref | GoogleScholarGoogle Scholar |
Kopp-Schneider A, Hielscher T (2019) How to evaluate agreement between quantitative measurements. Radiotherapy and Oncology: Journal of the European Society for Therapeutic Radiology and Oncology 141, 321–326.
| How to evaluate agreement between quantitative measurements.Crossref | GoogleScholarGoogle Scholar |
Passing H, Bablok W (1983) A new biometrical procedure for testing the equality of measurements from two different analytical methods. Application of linear regression procedures for method comparison studies in clinical chemistry, part I. Clinical Chemistry and Laboratory Medicine 21, 709–720.
| A new biometrical procedure for testing the equality of measurements from two different analytical methods. Application of linear regression procedures for method comparison studies in clinical chemistry, part I.Crossref | GoogleScholarGoogle Scholar |
Payne RB (1997) Method comparison: evaluation of least squares, deming and Passing/Bablok regression procedures using computer simulation. Annals of Clinical Biochemistry 34, 319–320.
| Method comparison: evaluation of least squares, deming and Passing/Bablok regression procedures using computer simulation.Crossref | GoogleScholarGoogle Scholar | 9158833PubMed |
Pearce KL (2016) Improving lamb lean meat yield. Available at https://www.sheepcrc.org.au/files/pages/publications/publications/improving-lamb-lean-meat-yield/Lean_Meat_Yield_Manual_-_Web_Feb16.pdf.
R Core Team (2018) ‘R: a language and environment for statistical computing.’ (R Foundation for Statistical Computing: Vienna, Austria)
Vander Heyden Y, Smeyers-Verbeke J (2007) Set-up and evaluation of interlaboratory studies. Journal of Chromatography A 1158, 158–167.
| Set-up and evaluation of interlaboratory studies.Crossref | GoogleScholarGoogle Scholar | 17339041PubMed |
Watkins P, Stockham K, Stewart S, Gardner G (2021) Contemporary chemical lean determination used in the Australian meat processing industry: a method comparison. Meat Science 171, 108289
| Contemporary chemical lean determination used in the Australian meat processing industry: a method comparison.Crossref | GoogleScholarGoogle Scholar | 32889306PubMed |
