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Effect of milking hygiene, herd size, water hardness and temperature-humidity index on milk quality of dairy farms

ABSTRACT

The objective of this study was to evaluate the effect of milking hygiene practices, herd size, water hardness, and temperature-humidity index (THI) on the physicochemical and microbiological characteristics of raw milk, and standard plate count (SPC) in milking machines of dairy farms in the central region of Mexico. Data were collected from fifty-three dairy farms during one year. The evaluated effects included milking hygiene conditions (good, medium, poor), herd size (1-50, 51-100, 101-150, ≥151 heads), water hardness (soft or moderately hard), and THI (comfortable or stressful). The increase in milking hygiene produced greater milk yield (MY) and energy corrected milk (ECM) but lower protein content, and decreased the individual bacterial count (IBC) and somatic cell count (SCC). The MY, ECM, protein content, IBC, and SCC were higher on bigger farms. The use of soft water reduced MY, IBC, and SCC, but improved fat, lactose, total solids (TS), and non-fat solids (NFS). Heat stress negatively affected fat, protein, TS, NFS, acidity, freezing point (FP), SCC, and methylene blue dye reduction test. Poor milking hygiene contributes to higher SPC in milking machine parts. Water hardness and THI did not affect SPC in all milking machine parts. Proper milking hygiene practices, larger herd size, softer water, lower THI, and adequate cleaning and disinfection of the milking machine parts benefits the physicochemical and microbiological quality of the milk.

dairy; heat stress; milking practices; water characteristics

1. Introduction

Around the world, there are approximately 150 million households engaged in milk production, most of which are small and family-operated. The majority of them are in developing countries ( Douphrate et al., 2013Douphrate, D. I.; Hagevoort, G. R.; Nonnenmann, M. W.; Kolstrup, C. L.; Reynolds, S. J.; Jakob, M. and Kinsel, M. 2013. The dairy industry: A brief description of production practices, trends, and farm characteristics around the world. Journal of Agromedicine 18:187-197. https://doi.org/10.1080/1059924X.2013.796901
https://doi.org/10.1080/1059924X.2013.79...
; Lowder et al., 2016Lowder, S. K.; Skoet, J. and Raney, T. 2016. The number, size, and distribution of farms, smallholder farms, and family farms worldwide. World Development 87:16-29. https://doi.org/10.1016/j.worlddev.2015.10.041
https://doi.org/10.1016/j.worlddev.2015....
; FAO, 2021FAO - Food and Agriculture Organization of the United Nations. 2021. Gateway to dairy production and products. Milk production. Available at: <http://www.fao.org/dairy-production-products/production/en/>. Accessed on: Aug. 28, 2021.
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). With more than six billion consumers of milk and milk products, milk production contributes to household livelihoods, food security, and nutrition for people ( Adesogan and Dahl, 2020Adesogan, A. T. and Dahl, G. E. 2020. Milk Symposium Introduction: Dairy production in developing countries. Journal of Dairy Science 103:9677-9680. https://doi.org/10.3168/jds.2020-18313
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). Milk provides relatively quick returns for small-scale producers and is an important source of cash income ( Kapaj, 2018Kapaj, A. 2018. Factors that influence milk consumption world trends and facts. European Journal of Business Economics and Accountancy 6:14-18. ). In Mexico, 50% of dairy farmers are small, but they contribute with 37% of national production ( Val-Arreola et al., 2006Val-Arreola, D.; Kebreab, E. and France, J. 2006. Modeling small-scale dairy farms in central Mexico using multi-criteria programming. Journal of Dairy Science 89:1662-1672. https://doi.org/10.3168/jds.S0022-0302(06)72233-0
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; Rapsomanikis, 2015Rapsomanikis, G. 2015. The economic lives of smallholder farmers: An analysis based on household data from nine countries. Food and Agriculture Organization of the United Nations, Rome. Available at: <http://www.fao.org/3/a-i5251e.pdf>. Accessed on: July 25, 2021.
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). A small farm in Mexico is one with an average of 13 mature cows, with an average production of 14 L/d ( Méndez y Cazarín et al., 2000Méndez y Cazarín, M. D.; Tzintzun Rascó, R. and Val Arreola, D. 2000. Evaluación productiva, de efecto ambiental y de problemas relevantes en explotaciones lecheras de pequeña escala. Livestock Research for Rural Development 12:9. Available at: <http://www.lrrd.org/lrrd12/1/manu121.htm>. Accessed on: Jun 30, 2022.
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).

The objective of dairy farms is to produce milk in sufficient quantity and quality to ensure its profitability, also guaranteeing quality and safety of the product to protect the health of consumers and promote its commercialization ( Popescu and Angel, 2009Popescu, A. and Angel, E. 2009. Analysis of milk quality and its importance for milk processors. Lucrări ştiinţifice Zootehnie şi Biotehnologii 42:501-506. ; Kapaj and Deci, 2017Kapaj, A. and Deci, E. 2017. World milk production and socio-economic factors effecting its consumption. p.107-115. In: Dairy in human health and disease across the lifespan. Academic Press, London, UK. https://doi.org/10.1016/B978-0-12-809868-4.00007-8
https://doi.org/10.1016/B978-0-12-809868...
; Berge and Baars, 2020Berge, A. C. and Baars, T. 2020. Raw milk producers with high levels of hygiene and safety. Epidemiology and Infection 148:e14. https://doi.org/10.1017/S0950268820000060
https://doi.org/10.1017/S095026882000006...
). Milk and its derivatives provide essential micro- and macronutrients to the diet ( Marangoni et al., 2019Marangoni, F.; Pellegrino, L.; Verduci, E.; Ghiselli, A.; Bernabei, R.; Calvani, R.; Cetin, I.; Giampietro, M.; Perticone, F.; Piretta, L.; Giacco, R.; La Vecchia, C.; Brandi, M. L.; Ballardini, D.; Banderali, G.; Bellentani, S.; Canzone, G.; Cricelli, C.; Faggiano, P.; Ferrara, N.; Flachi, E.; Gonnelli, S.; Macca, C.; Magni, P.; Marelli, G.; Marrocco, W.; Miniello, V. L.; Origo, C.; Pietrantonio, F.; Silvestri, P.; Stella, R.; Strazzullo, P.; Troiano, E. and Poli, A. 2019. Cow’s milk consumption and health: A health professional’s guide. Journal of the American College of Nutrition 38:197-208. https://doi.org/10.1080/07315724.2018.1491016
https://doi.org/10.1080/07315724.2018.14...
). The quality of raw milk is determined by its nutritional, organoleptic, hygienic, and sanitary attributes, which must be acceptable for agroindustry and human consumption ( Murphy et al., 2016Murphy, S. C.; Martin, N. H.; Barbano, D. M. and Wiedmann, M. 2016. Influence of raw milk quality on processed dairy products: How do raw milk quality test results relate to product quality and yield? Journal of Dairy Science 99:10128-10149. https://doi.org/10.3168/jds.2016-11172
https://doi.org/10.3168/jds.2016-11172...
). The general criteria applied to evaluate the quality of raw milk are its physicochemical characteristics and a low content of microorganisms and somatic cells ( Barbano and Lynch, 2006Barbano, D. M. and Lynch, J. M. 2006. Major advances in testing of dairy products: Milk component and dairy product attribute testing. Journal of Dairy Science 89:1189-1194. https://doi.org/10.3168/jds.S0022-0302(06)72188-9
https://doi.org/10.3168/jds.S0022-0302(0...
; Cincović et al., 2010Cincović, M. R.; Belić, B. M.; Toholj, B. D.; Radović, I. V. and Vidović, B. R. 2010. The influence of THI values at different periods of lactation on milk quality and characteristics of lactation curve. Journal of Agricultural Sciences 55:235-241. ). Many factors can affect milk quality, such as herd size and management practices ( Wenz et al., 2007Wenz, J. R.; Jensen, S. M.; Lombard, J. E.; Wagner, B. A. and Dinsmore, R. P. 2007. Herd management practices and their association with bulk tank somatic cell count on United States dairy operations. Journal of Dairy Science 90:3652-3659. https://doi.org/10.3168/jds.2006-592
https://doi.org/10.3168/jds.2006-592...
; Zucali et al., 2011Zucali, M.; Bava, L.; Tamburini, A.; Brasca, M.; Vanoni, L. and Sandrucci, A. 2011. Effects of season, milking routine and cow cleanliness on bacterial and somatic cell counts of bulk tank milk. Journal of Dairy Research 78:436-441. https://doi.org/10.1017/s0022029911000598
https://doi.org/10.1017/s002202991100059...
), good hygiene practices during collection and processing of milk ( Cempírková, 2007Cempírková, R. 2007. Contamination of cow’s raw milk by psychrotrophic and mesophilic microflora in relation to selected factors. Czech Journal of Animal Science 52:387-393. https://doi.org/10.17221/2325-CJAS
https://doi.org/10.17221/2325-CJAS...
; Elmoslemany et al., 2010Elmoslemany, A. M.; Keefe, G. P.; Dohoo, I. R.; Wichtel, J. J.; Stryhn, H. and Dingwell, R. T. 2010. The association between bulk tank milk analysis for raw milk quality and on-farm management practices. Preventive Veterinary Medicine 95:32-40. https://doi.org/10.1016/j.prevetmed.2010.03.007
https://doi.org/10.1016/j.prevetmed.2010...
), and environmental factors as heat stress measured by temperature-humidity index (THI) ( Bertocchi et al., 2014Bertocchi, L.; Vitali, A.; Lacetera, N.; Nardone, A.; Varisco, G. and Bernabucci, U. 2014. Seasonal variations in the composition of Holstein cow’s milk and temperature–humidity index relationship. Animal 8:667-674. https://doi.org/10.1017/S1751731114000032
https://doi.org/10.1017/S175173111400003...
; Zeinhom et al., 2016Zeinhom, M. M.; Abdel Aziz, R. L.; Mohammed, A. N. and Bernabucci, U. 2016. Impact of seasonal conditions on quality and pathogens content of milk in Friesian cows. Asian-Australasian Journal of Animal Sciences 29:1207-1213. https://doi.org/10.5713/ajas.16.0143
https://doi.org/10.5713/ajas.16.0143...
).

Good-quality raw milk is essential for producing quality milk and derivate products. However, there is limited information on the influence of various management factors on bulk tank physicochemical and bacterial counts on dairy farms ( Murphy and Boor, 2000Murphy, S. C. and Boor, K. J. 2000. Trouble-shooting sources and causes of high bacteria counts in raw milk. Dairy Food Environmental Sanitation 20:606-611. ). Therefore, this study aimed to evaluate the effect of milking hygiene practices, herd size, water hardness, and heat stress on the physicochemical characteristics and sanitary quality of raw milk on typical dairy farms from the central region of Mexico.

2. Material and Methods

2.1. Study site

The present study met the guidelines of the local Research Ethics Committee. The study was conducted in Jalisco Highlands region, located in the Mesa Central or southern plateau of Mexico (latitude 21°23'18.4" N and longitude 102°14'03.5" W, and average 1,902 m a.s.l.). The average annual rainfall is 658.5 mm, and the maximum temperature reaches 30 °C during the summer and the minimum of 7 °C during the winter ( INEGI, 2017INEGI - Instituto Nacional de Estadística y Geografía. 2017. Anuario estadístico y geográfico de Jalisco 2017. Instituto Nacional de Estadística y Geografía, México. Available at: <https://transparencia.info.jalisco.gob.mx/transparencia/informacion-fundamental/10360>. Accessed on: July 25, 2021.
https://transparencia.info.jalisco.gob.m...
). The geology is complex, composed of fractured volcanic rocks, as well as conglomerates, sandstones, and continental sediments. The farm water sources include groundwater (depth >100 to 400 m) and surface waters from dams, streams, lagoons, and ponds (CEAJ, 2005).

This region produces 60% of the total milk in the state of Jalisco and 19% of Mexico’s production ( SIAP, 2021SIAP - Servicio de Información Agroalimentaria y Pesquera. 2021. SAGARPA, México. Available at: <https://www.gob.mx/siap/acciones-y-programas/produccion-pecuaria>. Accessed on: Aug. 21, 2021.
https://www.gob.mx/siap/acciones-y-progr...
). The small dairy farm is the predominant system. Depending on the surface and conditions of the cultivation field, the productive system can be intensive or semi-intensive systems. The livestock diet includes grains, cut fodder, and crop residues ( Soltero-Gardea and Negrete-Ramos, 1997Soltero-Gardea, S. and Negrete-Ramos, L. F. 1997. Rangelands of the State of Jalisco and its livestock industry. Rangelands 19:22-25. ). Holstein-Friesian is the predominant dairy breed. Producers carry out preventive medicine and modern reproductive practices, although hygienic milking practices are variable among producers. The milk is sold to dairy processors or used for the elaboration of cheese and other dairy products ( Montiel-Olguín et al., 2019Montiel-Olguín, L. J.; Estráda-Cortés, E.; Espinosa-Martínez, M. A.; Mellado, M.; Hernández-Vélez, J. O.; Martínez-Trejo, G.; Ruiz-López, F. J. and Vera-Avila, H. R. 2019. Risk factors associated with reproductive performance in small-scale dairy farms in Mexico. Tropical Animal Health and Production 51:229-236. ).

2.2. Data collection

Fifty-three farms were selected to participate following the criteria: acceptance to participate in the study, shipping of milk to a local dairy processor, previous records of the constancy and compliance in the daily delivery of milk to the processor, and use of milking parlors equipped with modern milking technology. The chosen dairy farms were visited prior to the beginning of the study to evaluate herd size, compliance with milking hygiene practices, and water hardness.

The classification of dairy farms by milking hygiene was in agreement with the Official Mexican Standard NMX-F-730-COFOCALEC-2015, Milk product system - Dairy foods, recommended hygiene practices for obtaining milk. Compliance with the official recommendations for hygienic milking practices included the revision of facilities and equipment, livestock management, milking process, personnel, storage, and conservation of milk. The coding used in farms classification was: Good = dairy farms that satisfactorily comply with all the recommended milking hygiene practices; Medium = dairy farms that satisfactorily comply with more than half of the recommended hygiene practices; and Poor = dairy farms that satisfactorily comply with less than half of the recommended practices.

Number of cows in milk at the beginning of the study served for farm size classification. Looking for farm size class values close to the quartiles ( Ma et al., 2020Ma, W.; Renwick, A. and Zhou, X. 2020. Short communication: The relationship between farm debt and dairy productivity and profitability in New Zealand. Journal of Dairy Science 103:8251-8256. https://doi.org/10.3168/jds.2019-17506
https://doi.org/10.3168/jds.2019-17506...
), herds were divided into four categories as follows: 1-50, 51-100, 101-150, and ≥151 heads.

Water hardness was determined using an EDTA titration based on Method 2340C from Standard Methods ( Clesceri et al., 1999Clesceri, L. S.; Greenberg, A. E. and Eaton, A. D. 1999. Standard methods for the examination of water and wastewater. 20th ed. American Public Health Association, American Water Works Association, and Water Environment Federation. Alexandria, VA. ). According to the criteria indicated by Bagley et al. (1997)Bagley, C. V.; Kotuby-Amacher, J. and Farrell-Poe, K. 1997. Analysis of water quality for livestock. Animal Health Fact Sheet. All Archived Publications. Paper 106. Utah State University. Available at: <http://digitalcommons.usu.edu/extension_histall/106>. Accessed on: Aug. 27, 2021.
http://digitalcommons.usu.edu/extension_...
, water hardness was classified as soft water (0 to 60 mg L1 CaCO3) and moderately hard water (61-120 mg L1 CaCO3). Climatic values (temperature and relative humidity) were obtained from a meteorological station located in the vicinity of the study site. The THI was calculated according to the following equation ( Mader et al., 2006Mader, T. L.; Davis, M. S. and Brown-Brandl, T. 2006. Environmental factors influencing heat stress in feedlot cattle. Journal of Animal Science 84:712-719. https://doi.org/10.2527/2006.843712x
https://doi.org/10.2527/2006.843712x...
):

T H I = 0.8 × ambient temperature + [ ( % relative humidity ÷ 100 ) × ( ambient temperature 14.4 ) ] + 46.4

In agreement with Dikmen and Hansen (2009)Dikmen, S. and Hansen, P. J. 2009. Is the temperature-humidity index the best indicator of heat stress in lactating dairy cows in a subtropical environment? Journal of Dairy Science 92:109-116. https://doi.org/10.3168/jds.2008-1370
https://doi.org/10.3168/jds.2008-1370...
and Kadzere et al. (2002)Kadzere, C. T.; Murphy, M. R.; Silanikove, N. and Maltz, E. 2002. Heat stress in lactating dairy cows: a review. Livestock Production Science 77:59-91. https://doi.org/10.1016/S0301-6226(01)00330-X
https://doi.org/10.1016/S0301-6226(01)00...
, THI was classified as comfortable if THI ≤72 or stressful if THI >72.

On enrolled farms, cows were milked twice daily (at 07:00 and 17:00 h). Raw milk was stored at approximately 4 °C in the chilled on-farm bulk tank. The dairy processor collects the chilled milk daily (pooled milk from the morning and evening milking). The plant routinely performs physicochemical analysis on receipt of milk. Records of milk yield (MY, kg cow d1), fat (g L1), protein (g L1), lactose (g L1), total solids (TS, g L1), non-fat solids (NFS, g L1), acidity (g L1), freezing point (FP, °H), and density (g L1) were retrieved and stored in a database.

Fat, protein, lactose, TS, and NFS values were determined through infrared spectrometry (Milkoscan FT-120, Foss A/S, Hillerod, Denmark). Physicochemical analysis was determined on each sample according to AOAC methods (AOAC, 2016). Acidity was determined by titration (AOAC method 947.05). The freezing point was determined (AOAC method 990.22) with Gerber Cryoscope C1 equipment (Gerber Instruments AG, Effretikon, Switzerland). Density (specific gravity) was determined using a pycnometer (AOAC method 925.22). Energy-corrected milk (ECM, kg d1) adjusted to 3.5 percent fat and 3.2 percent protein was calculated using the following equation ( Hutjens, 2010Hutjens, M. F. 2010. Benchmarking your feed efficiency, feed costs, and income over feed cost. Advances in dairy technology: Proceedings of the Western Canadian Dairy Seminar 22:3-10. ):

ECM = ( 0.323 × milk yield ) + ( 12.82 × fat yield ) + ( 7.13 × protein yield )

Analysis of individual bacterial counts (IBC; bacteria mL1) and somatic cell counts (SCC; cells mL1) were performed using an automatic analyzer (BacSomatic, FOSS Electric A/S, Hilleroed, Denmark). The methylene blue dye reduction test (MBRT) was performed in duplicate according to the method described by Atherton and Newlander (1977)Atherton, H. V. and Newlander, J. A. 1977. Chemistry and testing of dairy products. 4th ed. AVI, Westport, CT. , considering 5 h as good-quality milk and less than 2 h as poor-quality milk.

Dairy farms were visited monthly before afternoon milking for the bacteriological sampling of milking machine parts. Milk pump, teat cup, milk claw, wash line, milk line, and milk receiver were sampled by swabbing the edges and internal surfaces of each with a sterile swab moistened in 1 g L1 peptone water, which was then immersed in a tube with 1 mL of peptone water solution. Samples were transported to the laboratory under refrigeration (4 °C) no later than 12 h after collection and subjected to inoculation (in triplicate) on Petri dishes with 15 mL of plate count agar. Plates were incubated at 37 °C for 24 h before colony counting. The microbiological analysis procedure complied with ISO: 4833:2003 method and AOAC 966.23 method (AOAC, 2016).

2.3. Statistical analyses

The statistical analysis was performed using SAS software (Statistical Analysis System, University edition). Normality assumptions were previously tested using the Shapiro-Wilk test, and homogeneity of variance (homoscedasticity) using Bartlett’s test. Data were analyzed as a repeated measures design using the PROC MIXED procedure of SAS statistical package. The farm was the experimental unit, and the collection day was the repeated measurement. The model included the effects of milking hygiene conditions, herd size, water hardness, and temperature-humidity index. The analysis was carried out using the Restricted Maximum Likelihood (REML method) with repeated measurements and the ID assigned to the farm as subject, to specify the variation within farms over time. The RANDOM instruction was used to adjust for variation due to the effect between farms. Analyses were conducted using multiple covariance structures to determine the most appropriate by the smallest Akaike and Schwarz’s Bayesian criteria. An autoregressive structure was used for the physicochemical characteristics MY, ECM, fat, protein, lactose, and FP, and the standard plate count (SPC) in the milking machine parts. Moreover, a variance component structure was used for the physicochemical characteristics TS, NFS acidity, and density, and the bacteriological characteristics IBC, SCC, and MBRT. For analyses, the SCC and bacteria data were transferred to log10 base.

Differences between means were established using the PDIFF instruction. The option ADJUST=TUKEY was used to request a multiple comparison adjustment. Results are presented as least squares means ± SEM and considered significant if P<0.05.

3. Results

In the study, a total of fifty-three dairy farms were evaluated. According to their milking practices, 34 dairy farms presented good milking practices, 16 presented medium milking practices, and three presented poor milking practices. According to herd size, 14 farms had 1-50 cows, 14 farms 51-100 cows, 13 farms 101-150 cows, and 12 farms ≥150 cows. Regarding THI, of all the farms evaluated, 30 of them presented a comfortable THI and 23 presented stressful THI.

3.1. Physicochemical characteristics of raw milk

Dairy farms with good hygienic conditions produced greater (P<0.05) MY and ECM but lower protein content than those with medium or poor hygienic conditions ( Table 1 ). Moreover, dairy farms with poor hygienic conditions produced the lowest (P<0.05) MY, ECM, and lactose content. However, independently of milking hygiene practices, the milk content of fat, TS, NFS, acidity, FP, or density were unaffected (P>0.05).

Table 1
Effects of herd size, milking hygiene, water hardness and THI on physicochemical characteristics of raw milk of fifty-three dairy farms in the highlands of central Mexico1

Herd size affected (P<0.001) MY, ECM, fat, protein, TS, NFS, and FP variables, but did not affect (P>0.05) lactose, acidity and density ( Table 1 ). The largest farms (≥151 heads) produce higher (P<0.05) MY and ECM than farms with 101-150 heads, while farms below 100 heads produce the lowest (P<0.05) MY and ECM. Fat content and FP were similar (P>0.05) among farms greater than 51 heads, but reduced (P>0.05) on farms with the smallest herd size (1-50 heads). The protein content in milk increases (P<0.05) in larger herd sizes (≥151 heads), similar (P>0.05) between farms with 51-100 and 101-150 heads, and reduced on farms with smaller herds (1-50 heads). The TS and NFS content were greatest (P<0.05) in 101-150 and >150 head farms, but lowest (P<0.05) on farms with smaller herd sizes.

On dairy farms where soft water is available, MY was reduced (P<0.001) by 1.7%, although fat (2.0%), lactose (3.0%), TS (2.0%), and NFS (1.1%) increased (P<0.001) when compared with dairy farms where hard water is available. Water hardness did not affect (P>0.05) ECM, protein content, acidity, FP, density, or temperature measurements ( Table 1 ).

Temperature-humidity index influenced all physicochemical characteristics of raw milk, except density. When THI >72, the MY, ECM, and lactose content increased 5.8, 5.7, and 1.4%, respectively. However, fat (0.09%), protein (1.6%), TS (1.5%), NFS (2.1%), acidity (0.8%), and FP (0.1%) were reduced.

3.2. Sanitary characteristics of raw milk

Better milking hygiene practices reduce (P<0.05) individual IBC and SCC in milk, and increase (P<0.05) time for MBRT. Lower (P<0.05) IBC and SCC were observed on dairy farms with softer water compared with farms with moderate water hardness, but MBRT was unaffected (P>0.05) by water hardness ( Table 2 ).

Table 2
Effects of herd size, milking hygiene, water hardness, and THI on bacteriological characteristics of raw milk of fifty-three dairy farms in the highlands of central Mexico1

The IBC and SCC increased (P<0.001) but MBRT decreased (P<0.001) with increase in herd size. Farms with larger herds (≥101 heads) showed the highest (P<0.05) IBC and SCC and the lowest MBRT values. However, IBC was similar (P>0.05) among farms ranged 1 to 150 heads. The lowest SCC and highest MBRT were observed (P<0.05) on smaller dairy farms (1-50 heads). The THI did not affect (P>0.05) IBC, but negatively affected (P<0.001) SCC and MBRT in raw milk.

3.3. Bacteriological count in milking machine parts

The SPC was higher (P<0.05) in all parts of the milking machine on dairy farms with poor milking hygiene compared with farms with good or regular milking hygiene ( Table 3 ). In addition, the SPC in the milk pump and milk claw increased (P<0.05) on farms with 101-150 heads, decreased on the smallest farms with 1-50 and 51-100 heads, and was lower on the larger farms (≥151 heads). A lower SPC (P<0.05) was observed in teat cups of dairy farms greater than 151 heads compared with farms with a lower number of heads. In wash line and milk line parts, greater SPC was observed on medium-sized farms (51-100 and 100-150 heads), but was minor on the smaller (1-50 heads) and larger (≥151 heads) farms. The SPC in milk receiver was similar (P>0.05) among farms with 1-50, 51-100, and 101-150 heads, but reduced (P<0.05) on farms ≥151 heads. However, water hardness and THI did not affect (P>0.05) SPC in milking machine parts ( Table 3 ).

Table 3
Effects of herd size, milking hygiene, water hardness, and THI on standard plate count (log10 ufc swab−1) in milking machine parts of fifty-three dairy farms in the highlands of central Mexico1

4. Discussion

4.1. Physicochemical characteristics of raw milk

Suranindyah et al. (2015)Suranindyah, Y.; Wahyuni, E.; Bintara, S. and Purbaya, G. 2015. The effect of improving sanitation prior to milking on milk quality of dairy cow in farmer group. Procedia Food Science 3:150-155. https://doi.org/10.1016/j.profoo.2015.01.016
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reported that improving environmental and pre-milking sanitation increased milk quality, density, and non-fat solids. In addition, Moroni et al. (2018)Moroni, P.; Nydam, D. V.; Ospina, P. A.; Scillieri-Smith, J. C.; Virkler, P. D.; Watters, R. D.; Welcome, F. L.; Zurakowski, M. J.; Ducharme, N. G. and Yeager, A. E. 2018. Diseases of the teats and udder. p.389-465. In: Rebhun’s diseases of dairy cattle. 3rd ed. Peek, S. F. and Divers, T. J., eds. Elsevier. https://doi.org/10.1016/B978-0-323-39055-2.00008-5
https://doi.org/10.1016/B978-0-323-39055...
stated that good hygiene and management practices that include pre-milking udder preparation (wet cleaning and massage) is reflected in a state of well-being of the cows and improvement in milk secretion. Therefore, it is to be expected that the stables categorized with better milking hygiene conditions will obtain an improvement in milk production.

In agreement with our results, previous studies carried out both in Mexico ( Carranza-Trinidad et al. 2007Carranza-Trinidad, R. G.; Macedo-Barragán, R.; Cámara-Córdoba, J.; Sosa-Ramírez, J.; Meraz-Jiménez, A. J. and Valdivia-Flores, A. G. 2007. Competitividad en la cadena productiva de leche del estado de Aguascalientes, México. Agrociencia 41:701-709. ; García-Muñiz et al., 2007García-Muñiz, J. G.; Mariscal-Aguayo, D. V.; Caldera-Navarrete, N. A.; Ramírez-Valverde, R.; Estrella-Quintero, H. and Núñez-Domínguez, R. 2007. Variables relacionadas con la producción de leche de ganado Holstein en agroempresas familiares con diferente nivel tecnológico. Interciencia 32:841-846. ; Romo-Bacco et al., 2014Romo-Bacco, C. E.; Valdivia-Flores, A. G.; Carranza-Trinidad, R. G.; Cámara-Córdova, J.; Zavala-Arias, M. P.; Flores-Ancira, E. and Espinosa-García, J. A. 2014. Brechas de rentabilidad económica en pequeñas unidades de producción de leche en el altiplano central mexicano. Revista Mexicana de Ciencias Pecuarias 5:273-290. ) and worldwide ( Allore et al., 1997Allore, H. G.; Oltenacu, P. A. and Erb, H. N. 1997. Effects of season, herd size, and geographic region on the composition and quality of milk in the northeast. Journal of Dairy Science 80:3040-3049. https://doi.org/10.3168/jds.S0022-0302(97)76271-4
https://doi.org/10.3168/jds.S0022-0302(9...
; Weersink and Tauer, 1991Weersink, A. and Tauer, L. W. 1991. Causality between dairy farm size and productivity. American Journal of Agricultural Economics 73:1138–1145. https://doi.org/10.2307/1242442
https://doi.org/10.2307/1242442...
; Simensen et al., 2010Simensen, E.; Østerås, O.; Bøe, K. E.; Kielland, C.; Ruud, L. E. and Næss, G. 2010. Housing system and herd size interactions in Norwegian dairy herds; associations with performance and disease incidence. Acta Veterinaria Scandinavica 52:14. https://doi.org/10.1186/1751-0147-52-14
https://doi.org/10.1186/1751-0147-52-14...
; Dong et al., 2016Dong, F.; Hennessy, D. A.; Jensen, H. H. and Volpe, R. J. 2016. Technical efficiency, herd size, and exit intentions in U.S. dairy farms. Agricultural Economics 47:533-545. https://doi.org/10.1111/agec.12253
https://doi.org/10.1111/agec.12253...
; Gargiulo et al., 2018Gargiulo, J. I.; Eastwood, C. R.; Garcia, S. C. and Lyons, N. A. 2018. Dairy farmers with larger herd sizes adopt more precision dairy technologies. Journal of Dairy Science 101:5466-5473. https://doi.org/10.3168/jds.2017-13324
https://doi.org/10.3168/jds.2017-13324...
), suggest that milk production and farm productivity increase as the herd size increases associated with a higher technological level in larger companies. In addition, previous reports ( Allore et al., 1997Allore, H. G.; Oltenacu, P. A. and Erb, H. N. 1997. Effects of season, herd size, and geographic region on the composition and quality of milk in the northeast. Journal of Dairy Science 80:3040-3049. https://doi.org/10.3168/jds.S0022-0302(97)76271-4
https://doi.org/10.3168/jds.S0022-0302(9...
; Oleggini et al., 2001Oleggini, G. H.; Ely, L. O. and Smith, J. W. 2001. Effect of region and herd size on dairy herd performance parameters. Journal of Dairy Science 84:1044-1050. https://doi.org/10.3168/jds.S0022-0302(01)74564-X
https://doi.org/10.3168/jds.S0022-0302(0...
) described that larger size herds had not only higher MY, but higher fat and protein contents in milk.

Energy-corrected milk was developed to put all cows on an equal basis for comparative purposes by equating to a common term various outputs of milk having distinct chemical components such as fat, protein, and lactose ( Tyrrell and Reid, 1965Tyrrell, H. F. and Reid, J. T. 1965. Prediction of the energy value of cow’s milk. Journal of Dairy Science 48:1215-1223. https://doi.org/10.3168/jds.S0022-0302(65)88430-2
https://doi.org/10.3168/jds.S0022-0302(6...
). This indicator can be used as a predictor of dry matter intake ( Mazumder and Kumagai, 2006Mazumder, M. A. R. and Kumagai, H. 2006. Analyses of factors affecting dry matter intake of lactating dairy cows. Animal Science Journal 77:53-62. https://doi.org/10.1111/j.1740-0929.2006.00320.x
https://doi.org/10.1111/j.1740-0929.2006...
) and as a decision tool to make adjustments in the diet ( Boerman et al., 2015Boerman, J. P.; Potts, S. B.; VandeHaar, M. J.; Allen, M. S. and Lock, A. L. 2015. Milk production responses to a change in dietary starch concentration vary by production level in dairy cattle. Journal of Dairy Science 98:4698-4706. https://doi.org/10.3168/jds.2014-8999
https://doi.org/10.3168/jds.2014-8999...
), in addition to being a trait to consider for the genetic selection of dairy cattle ( Li et al., 2018Li, B.; Fikse, W. F.; Løvendahl, P.; Lassen, J.; Lidauer, M. H.; Mäntysaari, P. and Berglund, B. 2018. Genetic heterogeneity of feed intake, energy-corrected milk, and body weight across lactation in primiparous Holstein, Nordic Red, and Jersey cows. Journal of Dairy Science 101:10011-10021. https://doi.org/10.3168/jds.2018-14611
https://doi.org/10.3168/jds.2018-14611...
). In agreement with our results, Adamczyk et al. (2017)Adamczyk, K.; Makulska, J.; Jagusiak, W. and Węglarz, A. 2017. Associations between strain, herd size, age at first calving, culling reason and lifetime performance characteristics in Holstein-Friesian cows. Animal 11:327-334. https://doi.org/10.1017/s1751731116001348
https://doi.org/10.1017/s175173111600134...
reported improvements in ECM as herd size increased (>100 cows) in Polish Holstein-Friesian cows.

Water is an essential nutrient to sustain life and optimize growth, lactation, and reproduction of dairy cattle ( Beede, 2005Beede, D. K. 2005. Assessment of water quality and nutrition for dairy cattle. Proceedings of the Mid-South Ruminant Nutrition Conference. Arlington, TX. ; Golher et al., 2021Golher, D. M.; Patel, B. H. M.; Bhoite, S. H.; Syed, M. I.; Panchbhai, G. J. and Thirumurugan, P. 2021. Factors influencing water intake in dairy cows: a review. International Journal of Biometeorology 65:617-625. https://doi.org/10.1007/s00484-020-02038-0
https://doi.org/10.1007/s00484-020-02038...
). Water hardness is expressed as the sum of calcium and magnesium concentration reported in equivalent amounts of calcium carbonate ( Clesceri et al., 1999Clesceri, L. S.; Greenberg, A. E. and Eaton, A. D. 1999. Standard methods for the examination of water and wastewater. 20th ed. American Public Health Association, American Water Works Association, and Water Environment Federation. Alexandria, VA. ). It is generally accepted that water hardness does not affect animal performance or water intake ( Looper and Waldner, 2002Looper, M. L. and Waldner, D. N. 2002. Water for dairy cattle. Cooperative Extension Service, New Mexico State University. Guide D-107. p1-5. ). Crooks (2020)Crooks, A. 2020. Understanding limits for livestock water. Weld Labs. Available at: <https://weldlabs.com/livestock-water-guide.pdf>. Accessed on: Sept. 22, 2021.
https://weldlabs.com/livestock-water-gui...
even mentioned that there may be health benefits if livestock drinks hard water, because dietary requirements for magnesium and calcium are more easily met.

However, there is limited research about the effects of water hardness on milk production or its physicochemical composition. In a recent study, Senevirathne et al. (2018)Senevirathne, N. D.; Anderson, J. L. and Rovai, M. 2018. Growth performance and health of dairy calves given water treated with a reverse osmosis system compared with municipal city water. Journal of Dairy Science 101:8890-8901. https://doi.org/10.3168/jds.2018-14800
https://doi.org/10.3168/jds.2018-14800...
investigated the effects of ad libitum drinking reverse osmosis water (17 mg L1, considered soft water) versus municipal/city water (249 mg L1, considered very hard water) on growth, nutrient utilization, and health scores of calves. They observed that hard water consumption increased (P = 0.01) mean daily water intake by 5.2%; however, soft water consumption increased (P<0.01) nutrient intake (DMI, crude protein, ether extract, starch, and neutral detergent fiber) at the postweaning period in 5.1%. In addition, Solomon et al. (1995)Solomon, R.; Mion, J.; Ben-Ghedalia, D. and Zomberg, Z. 1995. Performance of high producing dairy cows offered drinking water of high and low salinity in the Arava Desert. Journal of Dairy Science 78:620-624. https://doi.org/10.3168/jds.S0022-0302(95)76672-3
https://doi.org/10.3168/jds.S0022-0302(9...
reported that high-producing dairy cows managed under desert conditions supplied with desalinized drinking water instead of the natural salty water from wells consumed 9.4% more water and produced 2.1 kg d1 more milk, that contains more fat and protein (P<0.05).

Furthermore, several studies ( Arce-Cordero et al., 2021Arce-Cordero, J. A.; Monteiro, H. F.; Brandao, V. L. N.; Dai, X.; Bennett, S. L. and Faciola, A. P. 2021. Effects of calcium–magnesium carbonate and calcium–magnesium hydroxide as supplemental sources of magnesium on microbial fermentation in a dual-flow continuous culture. Translational Animal Science 5:txaa229. https://doi.org/10.1093/tas/txaa229
https://doi.org/10.1093/tas/txaa229...
; Crawford et al., 2008Crawford, G. I.; Keeler, C. D.; Wagner, J. J.; Krehbiel, C. R.; Erickson, G. E.; Crombie, M. B. and Nunnery, G. A. 2008. Effects of calcium magnesium carbonate and roughage level on feedlot performance, ruminal metabolism, and site and extent of digestion in steers fed high-grain diets. Journal of Animal Science 86:2998-3013. https://doi.org/10.2527/jas.2007-0070
https://doi.org/10.2527/jas.2007-0070...
; Schaefer et al., 1982Schaefer, D. M.; Wheeler, L. J.; Noller, C. H.; Keyser, R. B. and White, J. L. 1982. Neutralization of acid in the rumen by magnesium oxide and magnesium carbonate. Journal of Dairy Science 65:732-739. https://doi.org/10.3168/jds.S0022-0302(82)82260-1
https://doi.org/10.3168/jds.S0022-0302(8...
) suggest that the controlled inclusion of mineral elements such as sodium bicarbonate, calcium carbonate, or magnesium carbonate in the diet of lactating dairy cows acts as dietary buffers, improving the gastrointestinal pH. Therefore, the mineral content in the water could have an effect at this level. Although in the present study, the water consumption and ruminal pH were not measured, the results suggested a change in water intake or ruminal buffering that may be associated with the water mineral content.

Dairy cattle suffer heat stress when the temperature is out of the thermoneutral zone ( Allen et al., 2013Allen, J. D.; Anderson, S. D.; Collier, R. J. and Smith, J. F. 2013. Managing heat stress and its impact on cow behavior. p.150-162. In: Proceedings of the Western Dairy Management Conference. Reno, NV. Available at: <http://www.wdmc.org/2013/Managing%20Heat%20Stress%20and%20Its%20Impact%20on%20Cow%20Behavior.pdf>. Accessed on: Sep. 15, 2015.
http://www.wdmc.org/2013/Managing%20Heat...
; Hansen, 1990Hansen, P. J. 1990. Effects of coat colour on physiological responses to solar radiation in Holsteins. Veterinary Record 127:333-334. ). Although the thermoneutral zone is between 5 and 25 °C, heat stress is not only related to temperature but also to air humidity, which in conjunction alters the cow’s capacity to dissipate heat (Qi, et al., 2015; Rhoads et al., 2009Rhoads, M. L.; Rhoads, R. P.; VanBaale, M. J.; Collier, R. J.; Sanders, S. R.; Weber, W. J.; Crooker, B. A. and Baumgard, L. H. 2009. Effects of heat stress and plane of nutrition on lactating Holstein cows: I. Production, metabolism, and aspects of circulating somatotropin. Journal of Dairy Science 92:1986-1997. https://doi.org/10.3168/jds.2008-1641
https://doi.org/10.3168/jds.2008-1641...
). Heat stress occurs when the THI index is >72 ( Kadzere et al., 2002Kadzere, C. T.; Murphy, M. R.; Silanikove, N. and Maltz, E. 2002. Heat stress in lactating dairy cows: a review. Livestock Production Science 77:59-91. https://doi.org/10.1016/S0301-6226(01)00330-X
https://doi.org/10.1016/S0301-6226(01)00...
; Zeinhom et al., 2016)Zeinhom, M. M.; Abdel Aziz, R. L.; Mohammed, A. N. and Bernabucci, U. 2016. Impact of seasonal conditions on quality and pathogens content of milk in Friesian cows. Asian-Australasian Journal of Animal Sciences 29:1207-1213. https://doi.org/10.5713/ajas.16.0143
https://doi.org/10.5713/ajas.16.0143...
. However, it depends on factors such as breed, diet, milk production level, age, and housing conditions ( Roenfeldt, 1998)Roenfeldt, S. 1998. You can’t afford to ignore heat stress. Dairy Manage. 35:6-12. .

The negative effects of heat stress on milk production and composition have been widely studied in dairy cattle ( Qi et al., 2015Qi, L.; Bravo-Ureta, B. E. and Cabrera, V. E. 2015. From cold to hot: Climatic effects and productivity in Wisconsin dairy farms. Journal of Dairy Science 98:8664-8677. https://doi.org/10.3168/jds.2015-9536
https://doi.org/10.3168/jds.2015-9536...
; Lambertz et al., 2014Lambertz, C.; Sanker, C. and Gauly, M. 2014. Climatic effects on milk production traits and somatic cell score in lactating Holstein-Friesian cows in different housing systems. Journal of Dairy Science 97:319-329. https://doi.org/10.3168/jds.2013-7217
https://doi.org/10.3168/jds.2013-7217...
; Ji et al., 2020Ji, B.; Banhazi, T.; Perano, K.; Ghahramani, A.; Bowtell, L.; Wang, C. and Li, B. 2020. A review of measuring, assessing and mitigating heat stress in dairy cattle. Biosystems Engineering 199:4-26. https://doi.org/10.1016/j.biosystemseng.2020.07.009
https://doi.org/10.1016/j.biosystemseng....
). High-producing cows are much more susceptible to heat stress than low-producing animals ( Gantner et al., 2017Gantner, V.; Bobic, T.; Gantner, R.; Gregic, M.; Kuterovac, K.; Novakovic, J. and Potocnik, K. 2017. Differences in response to heat stress due to production level and breed of dairy cows. International Journal of Biometeorology 61:1675-1685. https://doi.org/10.1007/s00484-017-1348-7
https://doi.org/10.1007/s00484-017-1348-...
) because of the increased metabolic heat, making it more difficult for cows to preserve their thermoregulatory mechanism and maintain the body temperature in a thermoneutral zone and physiological homeostasis ( Kadzere et al., 2002Kadzere, C. T.; Murphy, M. R.; Silanikove, N. and Maltz, E. 2002. Heat stress in lactating dairy cows: a review. Livestock Production Science 77:59-91. https://doi.org/10.1016/S0301-6226(01)00330-X
https://doi.org/10.1016/S0301-6226(01)00...
). Other studies reported a lack of a significant relationship between MY and rectal temperature ( Dikmen and Hansen, 2009Dikmen, S. and Hansen, P. J. 2009. Is the temperature-humidity index the best indicator of heat stress in lactating dairy cows in a subtropical environment? Journal of Dairy Science 92:109-116. https://doi.org/10.3168/jds.2008-1370
https://doi.org/10.3168/jds.2008-1370...
), attributing it to the fact that cows have a greater capacity for adaptation and regulation of body temperature through physiological modifications ( Bernabucci et al., 2010Bernabucci, U.; Lacetera, N.; Baumgard, L. H.; Rhoads, R. P.; Ronchi, B. and Nardone, A. 2010. Metabolic and hormonal acclimation to heat stress in domesticated ruminants. Animal 4:1167-1183. https://doi.org/10.1017/S175173111000090X
https://doi.org/10.1017/S175173111000090...
) or even genetic inheritance ( Ravagnolo and Misztal, 2000Ravagnolo, O. and Misztal, I. 2000. Genetic component of heat stress in dairy cattle, parameter estimation. Journal of Dairy Science 83:2126-2130. https://doi.org/10.3168/jds.S0022-0302(00)75095-8
https://doi.org/10.3168/jds.S0022-0302(0...
).

Similar to our results, several studies ( Bouraoui et al., 2002Bouraoui, R.; Lahmarb, M.; Majdoub, A.; Djemali, M. and Belyea, R. 2002. The relationship of temperature-humidity index with milk production of dairy cows in a Mediterranean climate. Animal Research 51:479-491. https://doi.org/10.1051/animres:2002036
https://doi.org/10.1051/animres:2002036...
; Tao et al., 2020Tao, S.; Rivas, R. M. O.; Marins, T. N.; Chen, Y. C.; Gao, J. and Bernard, J. K. 2020. Impact of heat stress on lactational performance of dairy cows. Theriogenology 150:437-444. https://doi.org/10.1016/j.theriogenology.2020.02.048
https://doi.org/10.1016/j.theriogenology...
; Zeinhom et al., 2016Zeinhom, M. M.; Abdel Aziz, R. L.; Mohammed, A. N. and Bernabucci, U. 2016. Impact of seasonal conditions on quality and pathogens content of milk in Friesian cows. Asian-Australasian Journal of Animal Sciences 29:1207-1213. https://doi.org/10.5713/ajas.16.0143
https://doi.org/10.5713/ajas.16.0143...
) reported that milk components decreased (P<0.05) in cows exposed to heat stress conditions. Levit et al. (2021)Levit, H.; Pinto, S.; Amon, T.; Gershon, E.; Kleinjan-Elazary, A.; Bloch, V.; Ben Meir, Y. A.; Portnik, Y.; Jacoby, S.; Arnin, A.; Miron, J. and Halachmi, I. 2021. Dynamic cooling strategy based on individual animal response mitigated heat stress in dairy cows. Animal 15:100093. https://doi.org/10.1016/j.animal.2020.100093
https://doi.org/10.1016/j.animal.2020.10...
and Ouellet et al. (2019)Ouellet, V.; Cabrera, V. E.; Fadul-Pacheco, L. and Charbonneau, E. 2019. The relationship between the number of consecutive days with heat stress and milk production of Holstein dairy cows raised in a humid continental climate. Journal of Dairy Science 102:8537-8545. https://doi.org/10.3168/jds.2018-16060
https://doi.org/10.3168/jds.2018-16060...
reported that heat stress conditions negatively affect ECM in dairy cows. In this regard, the reduction of fat content could be due to the lower dry matter intake and minor proportions of acetate in the rumen ( Bandaranayaka and Holmes, 1976Bandaranayaka, D. D. and Holmes, C. W. 1976. Changes in the composition of milk and rumen contents in cows exposed to a high ambient temperature with controlled feeding. Tropical Animal Health and Production 8:38-46. https://doi.org/10.1007/BF02383364
https://doi.org/10.1007/BF02383364...
; Bernabucci et al., 2015)Bernabucci, U.; Basiricò, L.; Morera, P.; Dipasquale, D.; Vitali, A.; Piccioli Cappelli, F. and Calamari, L. 2015. Effect of summer season on milk protein fractions in Holstein cows. Journal of Dairy Science 98:1815-1827. https://doi.org/10.3168/jds.2014-8788
https://doi.org/10.3168/jds.2014-8788...
. In addition, the reduction in protein and lactose content could be due to the direct effect of heat stress on mammary gland synthesis (Bernaucchi et al., 2010; Cowley et al., 2015)Cowley, F. C.; Barber, D. G.; Houlihan, A. V. and Poppi, D. P. 2015. Immediate and residual effects of heat stress and restricted intake on milk protein and casein composition and energy metabolism. Journal of Dairy Science 98:2356-2368. https://doi.org/10.3168/jds.2014-8442
https://doi.org/10.3168/jds.2014-8442...
.

Furthermore, the stressful conditions in the study area occurred from mid-spring to mid-summer in April to August, coinciding with the season in which forage plants are stimulated to grow by the effects of the increase in temperature and humidity in this region. Gorlier et al. (2012)Gorlier, A.; Lonati, M.; Renna, M.; Lussiana, C.; Lombardi, G. and Battaglini, L. M. 2012. Changes in pasture and cow milk compositions during a summer transhumance in the western Italian Alps. Journal of Applied Botany and Food Quality 85:216-223. reported that the nutritional composition of the pastures depends on variations in their botanical and phenological composition, thus affecting the quality of the milk. In agreement with our results, Dahl et al. (1998)Dahl, G. E.; Chastain, J. P. and Peters, R. R. 1998. Manipulation of photoperiod to increase milk production in cattle: biological, economic and practical considerations. p.259-265. In: Proceedings of the Fourth International Dairy Housing Conference. Chastain, J. P., ed. American Society of Agricultural Engineers, St. Joseph, MI. reported that the percentages of fat, protein, and TS are higher during the winter and lower during the summer. This variation could be related to changes in the availability and quality of food and climatic conditions.

During the rainy season, the pastures are low in fiber; therefore, the levels of fat in the milk are decreased. In addition, with the high temperature and relative humidity, the intake levels decrease. However, during the autumn and winter (dry season), the availability and quality of the pasture decrease, providing hay or agricultural waste with higher fiber content, thus increasing the levels of fat but decreasing milk production. The same factors could have affected the FP in this study because their values depend on TS content in the milk. ( Zagorska and Ciprovica, 2013Zagorska, J. and Ciprovica, I. 2013. Evaluation of factors affecting freezing point of milk. International Journal of Biological, Biomolecular, Agricultural, Food and Biotechnological Engineering 7:106-111. ).

4.2. Sanitary characteristics of raw milk

Low bacterial count in milk is an important parameter to guarantee a safe product for consumers and preserve sensory traits and shelf life of milk and milk derivatives ( Murphy et al., 2016Murphy, S. C.; Martin, N. H.; Barbano, D. M. and Wiedmann, M. 2016. Influence of raw milk quality on processed dairy products: How do raw milk quality test results relate to product quality and yield? Journal of Dairy Science 99:10128-10149. https://doi.org/10.3168/jds.2016-11172
https://doi.org/10.3168/jds.2016-11172...
). The microbial contamination of raw milk can occur from a variety of sources like dirty udders and animals, facilities, personnel, and milking equipment ( Elmoslemany et al., 2010Elmoslemany, A. M.; Keefe, G. P.; Dohoo, I. R.; Wichtel, J. J.; Stryhn, H. and Dingwell, R. T. 2010. The association between bulk tank milk analysis for raw milk quality and on-farm management practices. Preventive Veterinary Medicine 95:32-40. https://doi.org/10.1016/j.prevetmed.2010.03.007
https://doi.org/10.1016/j.prevetmed.2010...
; Kelly et al., 2009Kelly, P. T.; O’Sullivan, K.; Berry, D. P.; More, S. J.; Meaney, W. J.; O’Callaghan, E. J. and O’Brien, B. 2009. Farm management factors associated with bulk tank total bacterial count in Irish dairy herds during 2006/07. Irish Veterinary Journal 62:36. https://doi.org/10.1186/2046-0481-62-1-36
https://doi.org/10.1186/2046-0481-62-1-3...
). As expected and in agreement with previous studies ( Gibson et al., 2008Gibson, H.; Sinclair, L. A.; Brizuela, C. M.; Worton, H. L. and Protheroe, R. G. 2008. Effectiveness of selected premilking teat-cleaning regimes in reducing teat microbial load on commercial dairy farms. Letters in Applied Microbiology 46:295-300. https://doi.org/10.1111/j.1472-765X.2007.02308.x
https://doi.org/10.1111/j.1472-765X.2007...
; Ózsvári and Ivanyos, 2021Ózsvári, L. and Ivanyos, D. 2021. Milking practices on commercial Holstein-Friesian farms. Revista Brasileira de Zootecnia 50:e20200280. https://doi.org/10.37496/rbz5020200280
https://doi.org/10.37496/rbz5020200280...
; Erdem and Okuyucu, 2019Erdem, H. and Okuyucu, I. C. 2019. Influence of hygiene status of cows on somatic cell count and milk components during summer season. Large Animal Review 25:7-10. ) the present study determined that better milking hygiene procedures help to reduce the total bacterial count in raw milk. Corresponding with our results, Berry et al. (2006)Berry, D. P.; O’Brien, B.; O’Callaghan, E. J.; Sullivan, K. O. and Meaney, W. J. 2006. Temporal trends in bulk tank somatic cell count and total bacterial count in Irish dairy herds during the past decade. Journal of Dairy Science 89:4083-4093. https://doi.org/10.3168/jds.s0022-0302(06)72453-5
https://doi.org/10.3168/jds.s0022-0302(0...
observed a positive relationship (P<0.05) between SCC and IBC, whereas Álvarez-Fuentes et al. (2012)Álvarez-Fuentes, G.; Herrera-Haro, J. G.; Alonso-Bastida, G. and Barreras-Serrano, A. 2012. Calidad de la leche cruda en unidades de producción familiar del sur de Ciudad de México. Archivos de Medicina Veterinaria 44:237-242. https://doi.org/10.4067/S0301-732X2012000300005
https://doi.org/10.4067/S0301-732X201200...
reported that better hygienic conditions produced lower SCC and higher reductase time (P<0.05).

Our results corroborate several studies ( Barkema et al., 1998Barkema, H. W.; Schukken, Y. H.; Lam, T. J. G. M.; Beiboer, M. L.; Benedictus, G. and Brand, A. 1998. Management practices associated with low, medium, and high somatic cell counts in bulk milk. Journal of Dairy Science 81:1917-1927. https://doi.org/10.3168/jds.S0022-0302(98)75764-9
https://doi.org/10.3168/jds.S0022-0302(9...
; Sadeghi-Sefidmazgi and Rayatdoost-Baghal, 2014Sadeghi-Sefidmazgi, A. and Rayatdoost-Baghal, F. 2014. Effects of herd management practices on somatic cell counts in an arid climate. Revista Brasileira de Zootecnia 43:499-504. https://doi.org/10.1590/S1516-35982014000900007
https://doi.org/10.1590/S1516-3598201400...
; Wenz et al., 2007Wenz, J. R.; Jensen, S. M.; Lombard, J. E.; Wagner, B. A. and Dinsmore, R. P. 2007. Herd management practices and their association with bulk tank somatic cell count on United States dairy operations. Journal of Dairy Science 90:3652-3659. https://doi.org/10.3168/jds.2006-592
https://doi.org/10.3168/jds.2006-592...
; Zucali et al., 2011Zucali, M.; Bava, L.; Tamburini, A.; Brasca, M.; Vanoni, L. and Sandrucci, A. 2011. Effects of season, milking routine and cow cleanliness on bacterial and somatic cell counts of bulk tank milk. Journal of Dairy Research 78:436-441. https://doi.org/10.1017/s0022029911000598
https://doi.org/10.1017/s002202991100059...
) which stated that a low SCC is associated with better management practices in the herd (good bedding, free-stall barns, wearing gloves during milking and shade-providing) and pre-milking udder preparation (teat disinfection, and the use of washable towels for teat cleaning or a wet disposable tissue for udder cleaning).

The MBRT is a widely used milk quality test that measures bacterial contamination in milk. In this test, bacterial activity changes the blue color of methylene in milk to white as the oxygen level diminishes due to bacterial activity. The shorter time for milk to change color, the more contaminated the milk ( Moran, 2012Moran, J. 2012. Milk harvesting and hygiene. p.161-173. In: Managing high grade dairy cows in the tropics. CSIRO Publishing, Collingwood, Australia. ). The lower value for MBRT observed in milk from farms with poor milking hygiene (higher IBC and SCC) confirm the usefulness of this simple but effective technique to detect the quality of raw milk ( Pérez-Lomas et al., 2020Pérez-Lomas, M.; Cuaran-Guerrero, M. J.; Yépez-Vásquez, L.; Pineda-Flores, H.; Núñez-Pérez, J.; Espin-Valladares, R.; Recalde-Posso, E.; Trujillo-Toledo, L. E. and Pais-Chanfrau, J. M. 2020. The extended methylene blue reduction test and milk quality. Foods and Raw Materials 8:140-148. https://doi.org/10.21603/2308-4057-2020-1-140-148
https://doi.org/10.21603/2308-4057-2020-...
).

Our results corroborated those of De Silva et al. (2016)De Silva, S. A. S. D.; Kanugala, K. A. N. P. and Weerakkody, N. S. 2016. Microbiological quality of raw milk and effect on quality by implementing good management practices. Procedia Food Science 6:92-96. https://doi.org/10.1016/j.profoo.2016.02.019
https://doi.org/10.1016/j.profoo.2016.02...
, who reported a reduction (10.8 to 16.5%) in milk bacterial counts after implementing good milking practices, and a strong relationship (r2= 0.91) between MBRT and milk bacterial counts. In light of the results obtained in the present study, the need to implement a permanent evaluation and an improvement of the hygienic procedures in facilities, equipment, animals, and personnel on dairy farms becomes evident, to provide a higher-quality product to the consumer.

Around the world, dairy farmers are trying to increase their herd size to benefit from economies of scale derived from lower investments per cow, lower variable costs per unit of production, and higher labor efficiency ( Bailey et al., 1997Bailey, K.; Hardin, D.; Spain, J.; Garret, J.; Hoehne, J.; Randle, R.; Ricketts, R.; Steevens, B. and Zulovich, J. 1997. An economic simulation study of large-scale dairy units in the Midwest. Journal of Dairy Science 80:205-214. https://doi.org/10.3168/jds.S0022-0302(97)75929-0
https://doi.org/10.3168/jds.S0022-0302(9...
; Espinoza-Ortega et al., 2007Espinoza-Ortega, A.; Espinosa-Ayala, E.; Bastida-López, J.; Castañeda-Martínez, T. and Arriaga-Jordán, C. M. 2007. Small-scale dairy farming in the highlands of central Mexico: Technical, economic and social aspects and their impact on poverty. Experimental Agriculture 43:241-256. https://doi.org/10.1017/S0014479706004613
https://doi.org/10.1017/S001447970600461...
; Fariña and Chilibroste, 2019Fariña, S. R. and Chilibroste, P. 2019. Opportunities and challenges for the growth of milk production from pasture: The case of farm systems in Uruguay. Agricultural Systems 176:102631. https://doi.org/10.1016/j.agsy.2019.05.001
https://doi.org/10.1016/j.agsy.2019.05.0...
). In the US, Norman et al. (2000)Norman, H. D.; Miller, R. H.; Wright, J. R. and Wiggans, G. R. 2000. Herd and state means for somatic cell count from dairy herd improvement. Journal of Dairy Science 83:2782-2788. https://doi.org/10.3168/jds.S0022-0302(00)75175-7
https://doi.org/10.3168/jds.S0022-0302(0...
and Oleggini et al. (2001)Oleggini, G. H.; Ely, L. O. and Smith, J. W. 2001. Effect of region and herd size on dairy herd performance parameters. Journal of Dairy Science 84:1044-1050. https://doi.org/10.3168/jds.S0022-0302(01)74564-X
https://doi.org/10.3168/jds.S0022-0302(0...
reported that larger herds have a lower SCC compared with smaller herds, suggesting that with expansion comes an increased level of knowledge and better udder health. The improvement of SCC on larger herd size farms should be expected if we consider that a better economy should be accompanied by greater participation of consultants and veterinarians. However, studies carried out in Mexico ( León-Galván et al., 2015León-Galván, M.; Barboza-Corona, J. E.; Lechuga-Arana, A. A.; Valencia-Posadas, M.; Aguayo, D. D.; Cedillo-Pelaez, C.; Martínez-Ortega, E. A. and Gutierrez-Chavez, A. J. 2015. Molecular detection and sensitivity to antibiotics and bacteriocins of pathogens isolated from bovine mastitis in family dairy herds of central Mexico. BioMed Research International 2015:615153. https://doi.org/10.1155/2015/615153
https://doi.org/10.1155/2015/615153...
; Manjarrez-Lopez et al., 2012) and other countries ( Allore et al., 1997Allore, H. G.; Oltenacu, P. A. and Erb, H. N. 1997. Effects of season, herd size, and geographic region on the composition and quality of milk in the northeast. Journal of Dairy Science 80:3040-3049. https://doi.org/10.3168/jds.S0022-0302(97)76271-4
https://doi.org/10.3168/jds.S0022-0302(9...
; Archer et al., 2013Archer, S. C.; Mc Coy, F.; Wapenaar, W. and Green, M. J. 2013. Association of season and herd size with somatic cell count for cows in Irish, English, and Welsh dairy herds. The Veterinary Journal 196:515-521. https://doi.org/10.1016/j.tvjl.2012.12.004
https://doi.org/10.1016/j.tvjl.2012.12.0...
; Simensen et al., 2010Simensen, E.; Østerås, O.; Bøe, K. E.; Kielland, C.; Ruud, L. E. and Næss, G. 2010. Housing system and herd size interactions in Norwegian dairy herds; associations with performance and disease incidence. Acta Veterinaria Scandinavica 52:14. https://doi.org/10.1186/1751-0147-52-14
https://doi.org/10.1186/1751-0147-52-14...
; Whitaker et al., 2000Whitaker, D. A.; Kelly, J. M. and Smith, S. 2000. Disposal and disease rates in 340 British dairy herds. Veterinary Record 146:363-367. https://doi.org/10.1136/vr.146.13.363
https://doi.org/10.1136/vr.146.13.363...
) reported that an increase in herd size is generally associated with an increased SCC in raw milk. The results suggest that more attention is required to optimize udder health management as herds increase cow numbers on dairy farms in the studied region of Mexico.

There is limited research about the effects of water hardness on the bacterial count or SCC in milk. Elmoslemany et al. (2009)Elmoslemany, A. M.; Keefe, G. P.; Dohoo, I. R. and Jayarao, B. M. 2009. Risk factors for bacteriological quality of bulk tank milk in Prince Edward Island dairy herds. Part 1: Overall risk factors. Journal of Dairy Science 92:2634-2643. https://doi.org/10.3168/jds.2008-1812
https://doi.org/10.3168/jds.2008-1812...
reported that herds with medium or high water hardness were 2.5 and 4.7 times, more likely than herds with lower hardness scores to have a high bacterial count in bulk tank milk. In another study, the same authors ( Elmoslemany et al., 2010Elmoslemany, A. M.; Keefe, G. P.; Dohoo, I. R.; Wichtel, J. J.; Stryhn, H. and Dingwell, R. T. 2010. The association between bulk tank milk analysis for raw milk quality and on-farm management practices. Preventive Veterinary Medicine 95:32-40. https://doi.org/10.1016/j.prevetmed.2010.03.007
https://doi.org/10.1016/j.prevetmed.2010...
) observed that water quality influences bacterial counts in bulk tank milk, because on the farms that account with a water purification system (P<0.01) or water softener (P<0.1), the risk to have elevated bacterial count in the bulk tank is reduced. Authors explain that hard water can reduce the effectiveness of cleaning chemicals and may lead to the formation of biofilms or deposits on the milking system ( Cords et al., 2001Cords, B. R.; Dychdala, G. R. and Richter, F. L. 2001. Cleaning and sanitizing in milk production and processing. p.567-606. In: Applied dairy microbiology. 2nd ed. Marth, E. H. and Steele, J. L., eds. CRC Press. ). Biofilms are self-aggregated, stratified microbial communities, constituted by one or several kinds of bacteria and a self-produced matrix of extracellular polymeric substances ( Flemming et al., 2016)Flemming, H. C.; Wingender, J.; Szewzyk, U.; Steinberg, P.; Rice, S. A. and Kjelleberg, S. 2016. Biofilms: an emergent form of bacterial life. Nature Reviews Microbiology 14:563-575. https://doi.org/10.1038/nrmicro.2016.94
https://doi.org/10.1038/nrmicro.2016.94...
. In this regard, Wang et al. (2019)Wang, T.; Flint, S. and Palmer, J. 2019. Magnesium and calcium ions: roles in bacterial cell attachment and biofilm structure maturation. Biofouling 35:959-974. https://doi.org/10.1080/08927014.2019.1674811
https://doi.org/10.1080/08927014.2019.16...
stated that calcium and magnesium ions are important nutrients required by bacteria for growth and cell maintenance and play multifaceted roles both in the initial adhesion of bacteria and in the maturation of the biofilm. Therefore, the greater water hardness could also influence the environmental microorganisms on dairy farms.

Although the values of bacterial counts and SCC are generally related, this was not the case in the present study. Climatologic factors affect the incidence of various diseases in dairy cows, such as mastitis ( Morse et al., 1988Morse, D.; DeLorenzo, M. A.; Wilcox, C. J.; Collier, R. J.; Natzke, R. P. and Bray, D. R. 1988. Climatic effects on occurrence of clinical mastitis. Journal of Dairy Science 71:848-853. https://doi.org/10.3168/jds.S0022-0302(88)79626-5
https://doi.org/10.3168/jds.S0022-0302(8...
; Whitaker et al., 2000Whitaker, D. A.; Kelly, J. M. and Smith, S. 2000. Disposal and disease rates in 340 British dairy herds. Veterinary Record 146:363-367. https://doi.org/10.1136/vr.146.13.363
https://doi.org/10.1136/vr.146.13.363...
; Zeinhom et al., 2016Zeinhom, M. M.; Abdel Aziz, R. L.; Mohammed, A. N. and Bernabucci, U. 2016. Impact of seasonal conditions on quality and pathogens content of milk in Friesian cows. Asian-Australasian Journal of Animal Sciences 29:1207-1213. https://doi.org/10.5713/ajas.16.0143
https://doi.org/10.5713/ajas.16.0143...
), and therefore it is expected that milk SCC observed a seasonal pattern ( Elmoslemany et al., 2010Elmoslemany, A. M.; Keefe, G. P.; Dohoo, I. R.; Wichtel, J. J.; Stryhn, H. and Dingwell, R. T. 2010. The association between bulk tank milk analysis for raw milk quality and on-farm management practices. Preventive Veterinary Medicine 95:32-40. https://doi.org/10.1016/j.prevetmed.2010.03.007
https://doi.org/10.1016/j.prevetmed.2010...
; Quintão et al., 2017Quintão, L. C.; Cunha, A. F. D.; Bragança, L. J.; Coelho, K. S.; Nunes, M. F. and Saraiva, L. H. G. 2017. Evolution and factors influencing somatic cell count in raw milk from farms in Viçosa, state of Minas Gerais. Acta Scientiarum. Animal Sciences 39:393-399. https://doi.org/10.4025/actascianimsci.v39i4.35364
https://doi.org/10.4025/actascianimsci.v...
; Olde Riekerink et al., 2007Olde Riekerink, R. G. M.; Barkema, H. W. and Stryhn, H. 2007. The effect of season on somatic cell count and the incidence of clinical mastitis. Journal of Dairy Science 90:1704-1715. https://doi.org/10.3168/jds.2006-567
https://doi.org/10.3168/jds.2006-567...
). The results obtained in the present study could be explained by the complexity of changes in milk microbiota influenced by the climatic conditions and the specific conditions of hygiene and farm management.

The microbiota of raw milk originates from multiple sources of contamination (udder, milking system, and farm environment), which initiate from the microbial load in milk from the udder and continuously increase as it flows to the bulk tank. Therefore, the final microbiota composition in the bulk tank is highly diverse ( Parente et al., 2020Parente, E.; Ricciardi, A. and Zotta, T. 2020. The microbiota of dairy milk: A review. International Dairy Journal 107:104714. https://doi.org/10.1016/j.idairyj.2020.104714
https://doi.org/10.1016/j.idairyj.2020.1...
). Furthermore, Porcellato et al. (2021)Porcellato, D.; Smistad, M.; Bombelli, A.; Abdelghani, A.; Jørgensen, H. J. and Skeie, S. B. 2021. Longitudinal study of the bulk tank milk microbiota reveals major temporal shifts in composition. Frontiers in Microbiology 12:616429. https://doi.org/10.3389/fmicb.2021.616429
https://doi.org/10.3389/fmicb.2021.61642...
demonstrated that a persistent and farm-specific microbiota is observed in the bulk tank, but changes in composition within the same farm are mostly driven by bacterial genera associated with mastitis (e.g., Staphylococcus and Streptococcus ), and correlated with the weather (temperature and humidity) but not with farm settings, such as milking system or herd size. On the other hand, although MBRT is a good general indicator of the level of bacterial contamination in milk, its results can be influenced by the composition of the microbiota and the variation in growth rate and the reducing action of different types of bacteria present in milk ( Taponen et al., 2019Taponen, S.; McGuinness, D.; Hiitiö, H.; Simojoki, H.; Zadoks, R. and Pyörälä, S. 2019. Bovine milk microbiome: a more complex issue than expected. Veterinary Research 50:44. https://doi.org/10.1186/s13567-019-0662-y
https://doi.org/10.1186/s13567-019-0662-...
; Karakashev et al., 2003Karakashev, D.; Galabova, D. and Simeonov, I. 2003. A simple and rapid test for differentiation of aerobic from anaerobic bacteria. World Journal of Microbiology and Biotechnology 19:233-238. https://doi.org/10.1023/A:1023674315047
https://doi.org/10.1023/A:1023674315047...
; Rodrigues et al., 2017Rodrigues, M. X.; Lima, S. F.; Canniatti-Brazaca, S. G. and Bicalho, R. C. 2017. The microbiome of bulk tank milk: characterization and associations with somatic cell count and bacterial count. Journal of Dairy Science 100:2536-2552. https://doi.org/10.3168/jds.2016-11540
https://doi.org/10.3168/jds.2016-11540...
).

4.3. Bacteriological count in milking machine parts

The SPC is a useful indicator of the bacterial count. Although it does not measure the total bacterial count present, it does evaluate the number of aerobic and mesophilic bacteria present in the sample ( Chambers, 2002Chambers, J. V. 2002. The microbiology of raw milk. p.39-90. In: Dairy microbiology handbook: The microbiology of milk and milk products. 3rd ed. Robinson, R. K., ed. John Wiley & Sons Inc., New York, USA. https://doi.org/10.1002/0471723959.ch2
https://doi.org/10.1002/0471723959.ch2...
). The microbial contamination of bulk tank milk will occur by bacterial contamination of teats and udder, contamination of milking equipment surfaces, or by the presence of mastitis-causing microorganisms from the udder ( Murphy and Boor, 2000Murphy, S. C. and Boor, K. J. 2000. Trouble-shooting sources and causes of high bacteria counts in raw milk. Dairy Food Environmental Sanitation 20:606-611. ). Milking machine components are made of rubber, steel, or plastic, materials that easily form bacterial biofilms that can be a source of milk contamination, even if adequate hygiene and sanitation are applied ( Teixeira et al., 2005Teixeira, P.; Lopes, Z.; Azeredo, J.; Oliveira, R. and Vieira, M. J. 2005. Physico-chemical surface characterization of a bacterial population isolated from a milking machine. Food Microbiology 22:247-251. https://doi.org/10.1016/j.fm.2004.03.010
https://doi.org/10.1016/j.fm.2004.03.010...
). Thus, proper cleaning and disinfection of the milking machine parts will reduce bacterial cross-infection between cows, reducing bacterial counts and SCC in milk ( Moroni et al., 2018Moroni, P.; Nydam, D. V.; Ospina, P. A.; Scillieri-Smith, J. C.; Virkler, P. D.; Watters, R. D.; Welcome, F. L.; Zurakowski, M. J.; Ducharme, N. G. and Yeager, A. E. 2018. Diseases of the teats and udder. p.389-465. In: Rebhun’s diseases of dairy cattle. 3rd ed. Peek, S. F. and Divers, T. J., eds. Elsevier. https://doi.org/10.1016/B978-0-323-39055-2.00008-5
https://doi.org/10.1016/B978-0-323-39055...
).

Our results are in agreement with those of Bava et al. (2011)Bava, L.; Zucali, M.; Sandrucci, A.; Brasca, M.; Vanoni, L.; Zanini, L. and Tamburini, A. 2011. Effect of cleaning procedure and hygienic condition of milking equipment on bacterial count of bulk tank milk. Journal of Dairy Research 78:211-219. https://doi.org/10.1017/s002202991100001x
https://doi.org/10.1017/s002202991100001...
, who conducted a study to describe the characteristics of cleaning procedures for milking equipment applied on intensive dairy farms in Italy. They reported that farms classified as high and low milk total bacteria count significantly differed both in terms of liners and receiver bacterial contamination of milking machine. The results of the present study demonstrate the importance of proper milking hygiene, as it will allow the reduction of bacterial counts and improve the quality of the milk produced.

As observed in the present study, different parts of the milking machine can vary in bacterial counts. In this regard, Richard (1981)Richard, J. 1981. Bacteriological examination of pipeline milking machines by rinsing the entire system. Journal of Applied Bacteriology 50:433-442. https://doi.org/10.1111/j.1365-2672.1981.tb04247.x
https://doi.org/10.1111/j.1365-2672.1981...
indicated that most microorganisms are present in the joints and complex parts of the milking machine and not on the surface of the equipment. Therefore, the profound cleanliness of milking equipment is necessary to reduce the number of microorganisms present in the milking machine.

No research reports were found regarding the relationship between farm size and SPC on the milking machine. In the present study, the sanitary quality of the milk worsened as the herd size increased, and the same phenomenon was observed in the SPC of farms with 1 to 150 heads. However, the larger farms (≥151) obtained the lowest SCP in all milking machine parts. The above can be explained by better cleaning and disinfection of the milking machine on the larger dairy farms; however, better hygiene procedures were not necessarily carried out during the milking process on these farms.

Reinemann et al. (2013) stated that acid washing is necessary to dissolve inorganic mineral deposits, therefore improper washing allows mineral precipitation on the surface of the milking equipment, allowing bacterial adhesion and formation of biofilms. In addition, Ohnstad (2013)Ohnstad, I. 2013. Effective cleaning of the milking machine. Livestock 18:28-31. https://doi.org/10.1111/j.2044-3870.2012.00174.x
https://doi.org/10.1111/j.2044-3870.2012...
indicated that farm water hardness evaluation is necessary to wash the tank and the milking equipment efficiently. This procedure allows using the correct amount of detergent and frequency of acid wash. However, in this study, the water hardness did not alter the SPC on milking machine parts, probably because the water in the area was only soft or moderately hard, but hard water with values greater than 121 mg CaCO3 L1 (ppm) was never observed.

Elmoslemany et al. (2010)Elmoslemany, A. M.; Keefe, G. P.; Dohoo, I. R.; Wichtel, J. J.; Stryhn, H. and Dingwell, R. T. 2010. The association between bulk tank milk analysis for raw milk quality and on-farm management practices. Preventive Veterinary Medicine 95:32-40. https://doi.org/10.1016/j.prevetmed.2010.03.007
https://doi.org/10.1016/j.prevetmed.2010...
and Soler et al. (1995)Soler, A.; Ponsell, C.; De Paz, M. and Nunez, M. 1995. The microbiological quality of milk produced in the Balearic Islands. International Dairy Journal 5:69-74. https://doi.org/10.1016/0958-6946(94)P1599-9
https://doi.org/10.1016/0958-6946(94)P15...
reported that summer temperatures may allow microorganism growth on milking equipment, especially under improper sanitation of milking equipment. Our results match those of Bramley et al. (1984)Bramley, A. J.; McKinnon, C. H.; Staker, R. T. and Simpkin, D. L. 1984. The effect of udder infection on the bacterial flora of the bulk milk of ten dairy herds. Journal of Applied Bacteriology 57:317-323. https://doi.org/10.1111/j.1365-2672.1984.tb01396.x
https://doi.org/10.1111/j.1365-2672.1984...
, who did not observe differences in the bacterial counts of rinsing of the milking machines obtained in summer and winter. The authors attribute the farm cleaning procedures as the main source of bacterial contamination and not to seasonal ambient conditions. In the present study, THI did not affect the bacterial counts in the different parts of the milking machine, which indicates that homogeneous cleaning and sanitation is generally carried out throughout the year in each particular dairy farm.

5. Conclusions

Milking hygiene practices, herd size, water hardness, and heat stress have a remarkable impact on milk quality and bacteriological count of the milking machine on dairy farms. Proper milking hygiene practices, softer water, and adequate cleaning and disinfection of the milking machine parts improve the milk quality. Although the larger herds showed better physicochemical characteristics of the milk, they also showed worse individual bacterial count and somatic cell count. Heat stress negatively affects the physicochemical and microbiological quality of the milk.

Acknowledgments

The authors express their gratitude to the 53 small-scale dairy farmers involved in this study, to undergraduate student Angel Aguilar for his invaluable technical assistance during the experimental procedures, and to the staff at the milk processing plant that kindly provided the milk database. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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Publication Dates

  • Publication in this collection
    12 May 2023
  • Date of issue
    2023

History

  • Received
    30 Oct 2021
  • Accepted
    25 Jan 2023
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