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Application of statistical process control for monitoring bulk tank milk somatic cell count of smallholder dairy farms

BACKGROUND AND AIM: Consistency in producing raw milk with less variation in bulk tank milk somatic cell count (BMSCC) is important for dairy farmers as their profit is highly affected by it in the long run. Statistical process control (SPC) is widely used for monitoring and detecting variations in...

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Autores principales: Punyapornwithaya, Veerasak, Sansamur, Chalutwan, Singhla, Tawatchai, Vinitchaikul, Paramintra
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Veterinary World 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7750230/
https://www.ncbi.nlm.nih.gov/pubmed/33363337
http://dx.doi.org/10.14202/vetworld.2020.2429-2435
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author Punyapornwithaya, Veerasak
Sansamur, Chalutwan
Singhla, Tawatchai
Vinitchaikul, Paramintra
author_facet Punyapornwithaya, Veerasak
Sansamur, Chalutwan
Singhla, Tawatchai
Vinitchaikul, Paramintra
author_sort Punyapornwithaya, Veerasak
collection PubMed
description BACKGROUND AND AIM: Consistency in producing raw milk with less variation in bulk tank milk somatic cell count (BMSCC) is important for dairy farmers as their profit is highly affected by it in the long run. Statistical process control (SPC) is widely used for monitoring and detecting variations in an industrial process. Published reports on the application of the SPC method to smallholder farm data are very limited. Thus, the purpose of this study was to assess the capability of the SPC method for monitoring the variation of BMSCC levels in milk samples collected from smallholder dairy farms. MATERIALS AND METHODS: Bulk tank milk samples (n=1302) from 31 farms were collected 3 times/month for 14 consecutive months. The samples were analyzed to determine the BMSCC levels. The SPC charts, including the individual chart (I-chart) and the moving range chart (MR-chart), were created to determine the BMSCC variations, out of control points, and process signals for each farm every month. The interpretation of the SPC charts was reported to dairy cooperative authorities and veterinarians. RESULTS: Based on a set of BMSCC values as well as their variance from SPC charts, a series of BMSCC data could be classified into different scenarios, including farms with high BMSCC values but with low variations or farms with low BMSCC values and variations. Out of control points and signals or alarms corresponding to the SPC rules, such as trend and shift signals, were observed in some of the selected farms. The information from SPC charts was used by authorities and veterinarians to communicate with dairy farmers to monitor and control BMSCC for each farm. CONCLUSION: This study showed that the SPC method can be used to monitor the variation of BMSCC in milk sampled from smallholder farms. Moreover, information obtained from the SPC charts can serve as a guideline for dairy farmers, dairy cooperative boards, and veterinarians to manage somatic cell counts in bulk tanks from smallholder dairy farms.
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spelling pubmed-77502302020-12-23 Application of statistical process control for monitoring bulk tank milk somatic cell count of smallholder dairy farms Punyapornwithaya, Veerasak Sansamur, Chalutwan Singhla, Tawatchai Vinitchaikul, Paramintra Vet World Research Article BACKGROUND AND AIM: Consistency in producing raw milk with less variation in bulk tank milk somatic cell count (BMSCC) is important for dairy farmers as their profit is highly affected by it in the long run. Statistical process control (SPC) is widely used for monitoring and detecting variations in an industrial process. Published reports on the application of the SPC method to smallholder farm data are very limited. Thus, the purpose of this study was to assess the capability of the SPC method for monitoring the variation of BMSCC levels in milk samples collected from smallholder dairy farms. MATERIALS AND METHODS: Bulk tank milk samples (n=1302) from 31 farms were collected 3 times/month for 14 consecutive months. The samples were analyzed to determine the BMSCC levels. The SPC charts, including the individual chart (I-chart) and the moving range chart (MR-chart), were created to determine the BMSCC variations, out of control points, and process signals for each farm every month. The interpretation of the SPC charts was reported to dairy cooperative authorities and veterinarians. RESULTS: Based on a set of BMSCC values as well as their variance from SPC charts, a series of BMSCC data could be classified into different scenarios, including farms with high BMSCC values but with low variations or farms with low BMSCC values and variations. Out of control points and signals or alarms corresponding to the SPC rules, such as trend and shift signals, were observed in some of the selected farms. The information from SPC charts was used by authorities and veterinarians to communicate with dairy farmers to monitor and control BMSCC for each farm. CONCLUSION: This study showed that the SPC method can be used to monitor the variation of BMSCC in milk sampled from smallholder farms. Moreover, information obtained from the SPC charts can serve as a guideline for dairy farmers, dairy cooperative boards, and veterinarians to manage somatic cell counts in bulk tanks from smallholder dairy farms. Veterinary World 2020-11 2020-11-13 /pmc/articles/PMC7750230/ /pubmed/33363337 http://dx.doi.org/10.14202/vetworld.2020.2429-2435 Text en Copyright: © Punyapornwithaya, et al. http://creativecommons.org/licenses/by/4.0 Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Punyapornwithaya, Veerasak
Sansamur, Chalutwan
Singhla, Tawatchai
Vinitchaikul, Paramintra
Application of statistical process control for monitoring bulk tank milk somatic cell count of smallholder dairy farms
title Application of statistical process control for monitoring bulk tank milk somatic cell count of smallholder dairy farms
title_full Application of statistical process control for monitoring bulk tank milk somatic cell count of smallholder dairy farms
title_fullStr Application of statistical process control for monitoring bulk tank milk somatic cell count of smallholder dairy farms
title_full_unstemmed Application of statistical process control for monitoring bulk tank milk somatic cell count of smallholder dairy farms
title_short Application of statistical process control for monitoring bulk tank milk somatic cell count of smallholder dairy farms
title_sort application of statistical process control for monitoring bulk tank milk somatic cell count of smallholder dairy farms
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7750230/
https://www.ncbi.nlm.nih.gov/pubmed/33363337
http://dx.doi.org/10.14202/vetworld.2020.2429-2435
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