A method of testing the quality of milk using optical capillaries
Bibliographic record
Abstract
The milk quality is determined by its visual appearance, absence of adulterating substances and ability to meet specific quality standards for somatic cell count (SCC), and bacteria count. There exist several diagnostic tests of milk quality. Some of them are applicable on dairy farms, like, for example, the California Mastitis Test (CMT) and the Milk Conductivity Test (MCT). Other tests, such as the bulk milk bacterial count, the bulk tank somatic cell count and tests for adulterants like water, sediments or antibiotics, are used in laboratories. The knowledge required to successfully apply the existing milk quality tests can be rather extensive and pertains both to the methodology and the diagnostic capabilities of a given test. Therefore, there is a need for new simple and low-cost methods of milk quality testing. This paper presents a new method of milk quality classification using low-cost optical capillaries. In this method, milk quality is determined by observation of milk behaviour under specific heating conditions using a simple low-cost photonic system with optical capillaries. We show that the optical capillary is a suitable tool for analysing liquids showing high scattering of light, such as milk. Full Text: PDF References: El-Rashidy A.A., Fox L.K., Gay J.M.,Diagnosis of Staphylococcus aureus intramammary infection by detection of specific antibody titer in milk, J. Dairy Sci., vol. 75, pp. 1430-1435, 1992. [CrossRef] Reinemann D.J., Mein G.A., Bray D.R., et al.,Troubleshooting high bacteria counts in farm milk, Univ. Wisconsin Coop Ext Pub A3705, Madison WI, 1999. Karlsson A.O., Ipsen R., Ardo Y.,Relationship between physical properties of casein micelles and rheology of skim milk concentrate, J. Dairy Sci. Vol. 80 pp. 3784-3797, 2005. [CrossRef] McMahon D.J., Brown R.J., Composition, structure and integrity of casein micelles: a review, J. Dairy Sci, vol. 67, pp. 499-512, 1984. [CrossRef] Dress P., Belz M., Klein K.F., Grattan K.T.V., Franke H.,Water-core-waveguide for pollution measurements in the deep ultra-violet, Applied Optics, vol. 37, pp. 4991-4997, 1998. [CrossRef] Romaniuk R., Dorosz J.,Technology of soft-glass optical fiber capillaries, Proc. of SPIE, vol. 6347, pp. 634710, 2006. [CrossRef] Borecki M, Korwin Pawlowski M., Wrzosek P., Szmidt J.,Capillaries as the components of photonic sensor micro-systems, J. of MS&T, vol. 19, pp. 065202, 2008. Borecki M.,Intelligent Fiber Optic Sensor for Estimating the Concentration of a Mixture-Design and Working Principle, Sensors, vol. 7, pp. 384-399, 2007. [CrossRef]
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".