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    Metrics and methods for quality and safety assurance of milk powder under diverse conditions : A thesis submitted in partial fulfilment of the requirements for the Degree of Doctor of Philosphy at Lincoln University

    Ejeahalaka, Kizito K.
    Abstract
    Global dairy producers are moving steadily towards producing differentiated products aimed at niche markets with greater emphasis on maximising resource utilisation and meeting consumer preferences. Consequently, fat-filled milk powders (FMP) are produced by partial or whole replacement of milk fat with vegetable oils to increase the sales of underutilised skimmed milk powders (SMP), while cows with specialised characteristics and requirements may be aggregated into different herds for targeted nutritional management to reduce the milk fatty acids (FA) that are often associated with negative health effects, offering improved economic returns. Rapid methods are therefore desirable for independent verification of product quality and origin for validation and traceability of such products. We explore the use of near infrared spectroscopy (NIRS), combined with chemometrics and diverse modelling strategies, for this purpose. This study was carried out in five stages: i) the segregation of freeze-dried raw milk samples from individual cows from different herds under the same or differing feeding regimes; ii) the formulation of model FMP types according to differing protocols that reflect the differing fat sources (i.e., coconut (CO), palm (PO), soya bean (SBO) and sunflower (SFO)) used in their manufacture; iii) the adulteration of model FMP types with differing concentrations of chemical adulterants such as melamine and urea; iv) the accelerated storage of model FMP types for 7 weeks at 40°C and 90 % RH; and v) the validation of the applicability of all the models developed for model FMP types using commercial samples covering 7 FMP brands collected from Nigerian markets. We found that NIRS can reliably segregate freeze-dried raw milk from individual cows/herds for product innovation, providing quality assurance and traceability benefits, but may not be adequate in correlating their FA profiles in accordance with the Beer’s law. The replacement of milk fat with PO, SBO and SFO resulted in FMP that were less atherogenic than whole milk powder (WMP). The PO FMP had spectral profiles and lipid indices closest to WMP but SBO and SFO FMP types offered the best indices that may support arterial health. Chemometric models developed with the NIR spectral profiles, particularly the PLS-DA models provided substantive differentiation (i.e., zero false negative and positive values with mean efficiency of 100 %) among the model FMP products. The adulteration of the model FMP types with different concentrations (i.e., 0.01 to 16.00 %) of melamine and urea resulted in some compositional alterations in the sample matrices. The NIRS profiles of CO and PO FMP types highlighted that CO had high specificity for the chemical adulterants while PO appeared to have contrasting abilities and masking their presence. The SIMCA multilevel models developed using the hierarchical modelling strategies were able to detect, confirm and differentiate the adulterations with an efficiency ranging from 89.8 to 100.0 %. The concentrations of the chemical adulterants in FMP were predicted with minimal errors (R²p ≥ 0.96 and RSR ≤ 0.19) at ≥ 1.00 % adulteration level. Generally, NIRS had lower limit of detection for melamine than urea, and their concentrations were better predicted in FMP. The accelerated storage of the model FMP types for 7 weeks at 40°C and 90 % RH significantly altered their FA, amino acids (AA) and NIR spectral profiles. The PO FMP type recorded the least spectral and FA profile alterations but the milk fat replacement with vegetable oils did not make FMP more stable than WMP. The multiclass SIMCA models provided firm differentiation of the fresh and the aged FMP samples. The PLSR models predicted the storage time with high efficiency (NSE ≥ 0.90) and low errors (RSR ≤ 0.28), indicative of FMP freshness and stability. The 7 FMP brands collected from Nigeria were of acceptable integrity and they were successfully used to validate the applicability of the qualitative and quantitative models developed in this project. This study has demonstrated the potential of NIRS as a rapid and low-cost method for robust and extensive routine authentication of dried milk powder in general and FMP in particular.... [Show full abstract]
    Keywords
    melamine; urea; fatty acids; amino acids; accelerated storage; chemometrics; random selection; traceability; fat-filled milk powder; near-infrared spectroscopy (NIRS); Soft Independent Modelling of Class Analogy (SIMCA); Partial Least Square Discriminant Analysis (PLS-DA); Partial Least Square Regression (PLSR); Interval Partial Least Square (iPLS); vegetable oil; milk adulteration; kennard-stone (KS) algorithm; Food Science
    Fields of Research
    0908 Food Sciences; 090804 Food Packaging, Preservation and Safety; 030106 Quality Assurance, Chemometrics, Traceability and Metrological Chemistry
    Date
    2020
    Type
    Thesis
    Collections
    • Doctoral (PhD) Theses [873]
    • Department of Wine, Food and Molecular Biosciences [598]
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