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Li Y, Cheng Z, Ma W, Qiu Y, Liu T, Nan B, Li M, Sun L, Liu W, Yin H, Wang C, Li X, Zang C. Effect of Exogenous Melatonin on Performance and Mastitis in Dairy Cows. Vet Sci 2024; 11:431. [PMID: 39330810 PMCID: PMC11435509 DOI: 10.3390/vetsci11090431] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2024] [Revised: 09/09/2024] [Accepted: 09/11/2024] [Indexed: 09/28/2024] Open
Abstract
Mastitis is an important factor affecting the health of cows that leads to elevated somatic cell counts in milk, which can seriously affect milk quality and result in huge economic losses for the livestock industry. Therefore, the aim of this trial was to investigate the effect of melatonin on performance and mastitis in dairy cows. Forty-eight Holstein cows with a similar body weight (470 ± 10 kg), parity (2.75 ± 1.23), number of lactation days (143 ± 43 days), BCS (3.0-3.5), milk yield (36.80 ± 4.18 kg), and somatic cell count (300,000-500,000 cells/mL) were selected and randomly divided into four groups: control (CON group), trial Ⅰ (T80 group), trial Ⅱ (T120 group), and trial Ⅲ (T160 group). Twelve cows in trial groups I, II, and III were pre-dispensed 80, 120, and 160 mg of melatonin in edible glutinous rice capsules along with the basal ration, respectively, while the control group was fed an empty glutinous rice capsule along with the ration. The trial period was 37 days, which included a 7-day adaptive phase followed by a 30-day experimental period. At the end of the trial period, feeding was ended and the cows were observed for 7 days. Milk samples were collected on days 0, 7, 14, 21, 28, and 37 to determine the somatic cell number and milk composition. Blood samples were collected on days 0, 15, 30, and 37 of the trial to determine the serum biochemical indicators, antioxidant and immune indicators, and the amount of melatonin in the blood. The results showed that the somatic cell counts of lactating cows in the CON group were lower than those in the T120 group on days 14 (p < 0.05) and 28 (p < 0.01) at 1 week after melatonin cessation. The milk protein percentage and milk fat percentage of cows in the T120 group were higher than those in the CON group (p < 0.01). The total protein and globulin content in the T120 group were higher than those in the CON group (p < 0.01). In terms of antioxidant capacity and immunity, the cows 1 week after melatonin cessation showed higher superoxide dismutase activity and interleukin-10 contents (p < 0.01) compared with the CON group and lower malondialdehyde and tumor necrosis factor-alpha contents (p < 0.01) compared with the T120 group. The melatonin content in the T120 group was increased relative to that in the other groups. In conclusion, exogenous melatonin can increase the content of milk components, reduce the somatic cell count, and improve the antioxidant capacity and immune responses to a certain extent. Under the experimental conditions, 120 mg/day melatonin is recommended for mid- to late-lactation cows.
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Affiliation(s)
- Yunmeng Li
- Xinjiang Laboratory of Herbivore Nutrition for Meat and Milk, College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China; (Y.L.); (Z.C.); (W.M.); (T.L.); (B.N.); (M.L.); (L.S.); (H.Y.); (C.W.); (X.L.)
| | - Zhiqiang Cheng
- Xinjiang Laboratory of Herbivore Nutrition for Meat and Milk, College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China; (Y.L.); (Z.C.); (W.M.); (T.L.); (B.N.); (M.L.); (L.S.); (H.Y.); (C.W.); (X.L.)
| | - Wenting Ma
- Xinjiang Laboratory of Herbivore Nutrition for Meat and Milk, College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China; (Y.L.); (Z.C.); (W.M.); (T.L.); (B.N.); (M.L.); (L.S.); (H.Y.); (C.W.); (X.L.)
| | - Yaqi Qiu
- Karamay Green City Agricultural Development Co., Karamay 834000, China;
| | - Tuo Liu
- Xinjiang Laboratory of Herbivore Nutrition for Meat and Milk, College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China; (Y.L.); (Z.C.); (W.M.); (T.L.); (B.N.); (M.L.); (L.S.); (H.Y.); (C.W.); (X.L.)
| | - Bingyu Nan
- Xinjiang Laboratory of Herbivore Nutrition for Meat and Milk, College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China; (Y.L.); (Z.C.); (W.M.); (T.L.); (B.N.); (M.L.); (L.S.); (H.Y.); (C.W.); (X.L.)
| | - Mengfei Li
- Xinjiang Laboratory of Herbivore Nutrition for Meat and Milk, College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China; (Y.L.); (Z.C.); (W.M.); (T.L.); (B.N.); (M.L.); (L.S.); (H.Y.); (C.W.); (X.L.)
| | - Long Sun
- Xinjiang Laboratory of Herbivore Nutrition for Meat and Milk, College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China; (Y.L.); (Z.C.); (W.M.); (T.L.); (B.N.); (M.L.); (L.S.); (H.Y.); (C.W.); (X.L.)
| | - Wentao Liu
- Xinjiang Urumqi Rural Revitalization Guidance Service Center, Urumqi 830000, China;
| | - Haina Yin
- Xinjiang Laboratory of Herbivore Nutrition for Meat and Milk, College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China; (Y.L.); (Z.C.); (W.M.); (T.L.); (B.N.); (M.L.); (L.S.); (H.Y.); (C.W.); (X.L.)
| | - Caidie Wang
- Xinjiang Laboratory of Herbivore Nutrition for Meat and Milk, College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China; (Y.L.); (Z.C.); (W.M.); (T.L.); (B.N.); (M.L.); (L.S.); (H.Y.); (C.W.); (X.L.)
| | - Xiaobin Li
- Xinjiang Laboratory of Herbivore Nutrition for Meat and Milk, College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China; (Y.L.); (Z.C.); (W.M.); (T.L.); (B.N.); (M.L.); (L.S.); (H.Y.); (C.W.); (X.L.)
| | - Changjiang Zang
- Xinjiang Laboratory of Herbivore Nutrition for Meat and Milk, College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China; (Y.L.); (Z.C.); (W.M.); (T.L.); (B.N.); (M.L.); (L.S.); (H.Y.); (C.W.); (X.L.)
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Medeiros GC, Ferraz JBS, Pedrosa VB, Chen SY, Doucette JS, Boerman JP, Brito LF. Genetic parameters for udder conformation traits derived from Cartesian coordinates generated by robotic milking systems in North American Holstein cattle. J Dairy Sci 2024; 107:7038-7051. [PMID: 38762108 DOI: 10.3168/jds.2023-24208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Accepted: 04/01/2024] [Indexed: 05/20/2024]
Abstract
Udder conformation is directly related to milk yield, cow health, workability, and welfare. Automatic milking systems (AMS, also known as milking robots) have become popular worldwide, and the number of dairy farms adopting these systems has increased considerably over the past years. In each milking visit, AMS record the location of the 4 teats as Cartesian coordinates in an xyz plan, which can then be used to derive udder conformation traits. Because AMS generate a large amount of data for individual cows per milking visit, they can contribute to an accurate assessment of important traits such as udder conformation without the addition of human classifier errors (in subjective scoring systems). Therefore, the primary objectives of this study were to estimate genomic-based genetic parameters for udder conformation traits derived from AMS records in North American Holstein cattle and to assess the genetic correlation between the derived traits for evaluating the feasibility of multitrait genomic selection for breeding cows that are more suitable for milking in AMS. The Cartesian teat coordinates measured during each milking visit were collected by 36 milking robots in 4,480 Holstein cows from 2017 to 2021, resulting in 5,317,488 records. A total of 4,118 of these Holstein cows were also genotyped for 57,600 SNPs. Five udder conformation traits were derived: udder balance (UB, mm), udder depth (UD, mm), front teat distance (FTD, mm), rear teat distance (RTD, mm), and distance front-rear (DFR, mm). In addition, 2 traits directly related to cow productivity in the system were added to the study: daily milk yield (DY) and milk electroconductivity (EC; as an indicator of mastitis). Variance components and genetic parameters for UB, UD, FTD, RTD, DFR, DY, and EC were estimated based on repeatability animal models. The estimates of heritability (± SE) for UB, UD, FTD, RTD, DFR, DY, and EC were 0.41 ± 0.02, 0.79 ± 0.01, 0.53 ± 0.02, 0.40 ± 0.02, 0.65 ± 0.02, 0.20 ± 0.02, and 0.46 ± 0.02, respectively. The repeatability estimates (± SE) for UB, UD, FTD, RTD, and DFR were 0.82 ± 0.01, 0.93 ± 0.01, 0.87 ± 0.01, 0.83 ± 0.01, and 0.88 ± 0.01, respectively. The strongest genetic correlations were observed between FTD and RTD (0.54 ± 0.03), UD and DFR (-0.47 ± 0.03), DFR and FTD (0.32 ± 0.03), and UD and FTD (-0.31 ± 0.03). These results suggest that udder conformation traits derived from Cartesian coordinates from AMS are moderately to highly heritable. Furthermore, the moderate genetic correlations between these traits should be considered when developing selection subindexes. The most relevant genetic correlations between traits related to cow milk productivity and udder conformation traits were between UD and EC (-0.25 ± 0.03) and between DFR and DY (0.30 ± 0.04), in which both genetic correlations are favorable. These findings will contribute to the design of genomic selection schemes for improving udder conformation in North American Holstein cattle, especially in precision dairy farms.
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Affiliation(s)
- Gabriel C Medeiros
- Department of Veterinary Medicine, College of Animal Sciences and Food Engineering, University of São Paulo, Pirassununga, SP, 13635-900, Brazil; Department of Animal Sciences, Purdue University, West Lafayette, IN 47907
| | - Jose Bento S Ferraz
- Department of Veterinary Medicine, College of Animal Sciences and Food Engineering, University of São Paulo, Pirassununga, SP, 13635-900, Brazil
| | - Victor B Pedrosa
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907
| | - Shi-Yi Chen
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907; Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu, Sichuan, 611130, China
| | - Jarrod S Doucette
- Agriculture Information Technology (AgIT), Purdue University, West Lafayette, IN 47907
| | | | - Luiz F Brito
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907.
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Huang CH, Furukawa K, Kusaba N. Estimating the nonlinear interaction between somatic cell score and differential somatic cell count on milk production by parity using generalized additive models. J Dairy Sci 2023; 106:7942-7953. [PMID: 37562643 DOI: 10.3168/jds.2022-22958] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Accepted: 04/30/2023] [Indexed: 08/12/2023]
Abstract
This observational study aimed to use somatic cell score (SCS) and differential somatic cell count (DSCC), the combined proportion of polymorphonuclear leukocytes and lymphocytes in somatic cells, to investigate how mastitis affected milk production. Using generalized additive models, we analyzed 50,618 test-day records from 8,081 lactations from 7,912 cows in 197 herds between January 2021 and March 2022 to estimate the nonlinear interaction between SCS and DSCC, and the effects of lactation stages and seasons on milk yield, milk component percentages, and milk component yields by parity of cows. The results show that the interaction between SCS and DSCC on these traits was significant, nonlinear, and complex. When DSCC was high, the negative effects of SCS were minimal, even when SCS reached 8 (i.e., 3,200,000 somatic cells/mL). Cows with high DSCC could have milk yields similar to healthy cows, implying that these cows may have been in the early stages of mastitis and that the milk yield had yet to be affected. Contrastingly, when DSCC was low, milk loss due to high SCS was drastic, especially for cows in third or later lactations, whose milk yield could reduce from more than 35 kg/d to less than 15 kg/d (-59.9%). This tremendous milk loss in high-parity cows was likely due to their higher milk yield and higher risks of chronic mastitis. High SCS and low DSCC also led to a pronounced change in milk composition. The decrease in the percentage of lactose can be directly related to the damage of inflammation to the mammary gland, while the increase in fat and protein percentages was more attributable to the concentration effect resulting from the reduced milk yield. Compared with analyses based on categorized SCS and DSCC values, modeling these 2 indices directly helps us more precisely assess mastitis effects on milk yield and milk composition. For efficient milk production, our results indicate that we should prevent high-parity cows from entering a state of high SCS and low DSCC.
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Affiliation(s)
- Che-Hsuan Huang
- Field Center of Animal Science and Agriculture, Obihiro University of Agriculture and Veterinary Medicine, Obihiro, Hokkaido, 080-8555 Japan
| | - Kenji Furukawa
- Tokachi Federation of Agricultural Cooperatives, Obihiro, Hokkaido, 080-0013 Japan
| | - Nobuyuki Kusaba
- Field Center of Animal Science and Agriculture, Obihiro University of Agriculture and Veterinary Medicine, Obihiro, Hokkaido, 080-8555 Japan.
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Bonestroo J, Fall N, Hogeveen H, Emanuelson U, Klaas IC, van der Voort M. The costs of chronic mastitis: A simulation study of an automatic milking system farm. Prev Vet Med 2023; 210:105799. [PMID: 36436383 DOI: 10.1016/j.prevetmed.2022.105799] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 11/09/2022] [Accepted: 11/12/2022] [Indexed: 11/18/2022]
Abstract
Mastitis is a production disease in dairy farming that causes economic losses. Especially chronic mastitis (i.e., mastitis cases continuing longer than 28 days) can substantially affect the risk of transmission of intramammary infections (IMI) and total milk production losses. Insights into the impact of chronic mastitis on production and farm economics are needed to guide chronic mastitis decision-making. We aimed to estimate the costs of chronic mastitis with a Monte Carlo simulation model in which the costs of chronic mastitis were estimated as part of the total mastitis costs. The model simulated milk yields, IMI dynamics, somatic cell count (SCC), and pregnancy status on an average Dutch dairy farm with 100 cow places over 9 years. The model was parameterized using information from the literature and actual sensor data from automatic milking system (AMS) farms. The daily subclinical milk production losses were modeled using a generalized additive model and sensor data. Transmission of IMI was modeled as well. The model results indicated median total costs of mastitis of € 230 per generic IMI case (i.e., a weighted average of all pathogens). The most substantial cost factors were the extra mastitis cases due to transmission, culling, and milk production losses. Other significant costs originated from dry cow treatments and diverted milk. The model also indicated median total costs due to chronic mastitis of € 118 (51 % of the total mastitis costs). The share of chronic mastitis relative to the total mastitis costs was substantial. Transmission of contagious bacteria had the largest share among the chronic mastitis costs (51 % of the costs of chronic cases). The large share of chronic mastitis costs in the total mastitis costs indicates the economic importance of these mastitis cases. The results of the study point to the need for future research to focus on chronic mastitis and reducing its presence on the AMS dairy farm.
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Affiliation(s)
- John Bonestroo
- DeLaval International AB, Gustaf De Lavals väg 15, 147 21 Tumba, Sweden; Swedish University of Agricultural Sciences, Dep't Clinical Sciences, POB 7054, SE-750 07 Uppsala, Sweden; Wageningen University and Research, Business Economics Group, Hollandseweg 1, 6706 KN Wageningen, the Netherlands.
| | - Nils Fall
- Swedish University of Agricultural Sciences, Dep't Clinical Sciences, POB 7054, SE-750 07 Uppsala, Sweden
| | - Henk Hogeveen
- Wageningen University and Research, Business Economics Group, Hollandseweg 1, 6706 KN Wageningen, the Netherlands
| | - Ulf Emanuelson
- Swedish University of Agricultural Sciences, Dep't Clinical Sciences, POB 7054, SE-750 07 Uppsala, Sweden
| | | | - Mariska van der Voort
- Wageningen University and Research, Business Economics Group, Hollandseweg 1, 6706 KN Wageningen, the Netherlands
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Matera R, Di Vuolo G, Cotticelli A, Salzano A, Neglia G, Cimmino R, D’Angelo D, Biffani S. Relationship among Milk Conductivity, Production Traits, and Somatic Cell Score in the Italian Mediterranean Buffalo. Animals (Basel) 2022; 12:ani12172225. [PMID: 36077945 PMCID: PMC9455038 DOI: 10.3390/ani12172225] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 08/23/2022] [Accepted: 08/25/2022] [Indexed: 11/16/2022] Open
Abstract
The measurement of milk electrical conductivity (EC) is a relatively simple and inexpensive technique that has been evaluated as a routine method for the diagnosis of mastitis in dairy farms. The aim of this study was to obtain further knowledge on relationships between EC, production traits and somatic cell count (SCC) in Italian Mediterranean Buffalo. The original dataset included 5411 records collected from 808 buffalo cows. Two mixed models were used to evaluate both the effect of EC on MY, PP and FP and EC at test-day, and the effect of EC on somatic cell score (SCS) by using five different parameters (EC_param), namely: EC collected at the official milk recording test day (EC_day0), EC collected 3 days before official milk recording (EC_day3), and three statistics calculated from EC collected 1, 3 and 5 days before each test-day, respectively. All effects included in the model were significant for all traits, with the only exception of the effect of EC nested within parity for FP. The relationship between EC and SCS was always positive, but of different magnitude according to the parity. The regression of EC on SCS at test-day using different EC parameters was always significant except when the regression parameter was the slope obtained from a linear regression of EC collected over the 5-day period. Moreover, in order to evaluate how well the different models fit the data, three parameters were used: the Average Information Criteria (AIC), the marginal R2 and the conditional R2. According to AIC and to both the Marginal and Conditional R2, the best results were obtained when the regression parameter was the mean EC estimated over the 5-day period.
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Affiliation(s)
- Roberta Matera
- Dipartimento di Medicina Veterinaria e Produzioni Animali, Università degli Studi di Napoli Federico II, 80131 Naples, Italy
| | - Gabriele Di Vuolo
- Istituto Zooprofilattico Sperimentale del Mezzogiorno, 80055 Portici, Italy
| | - Alessio Cotticelli
- Dipartimento di Medicina Veterinaria e Produzioni Animali, Università degli Studi di Napoli Federico II, 80131 Naples, Italy
| | - Angela Salzano
- Dipartimento di Medicina Veterinaria e Produzioni Animali, Università degli Studi di Napoli Federico II, 80131 Naples, Italy
- Correspondence:
| | - Gianluca Neglia
- Dipartimento di Medicina Veterinaria e Produzioni Animali, Università degli Studi di Napoli Federico II, 80131 Naples, Italy
| | - Roberta Cimmino
- Associazione Nazionale Allevatori Specie Bufalina (ANASB), 81100 Caserta, Italy
| | - Danila D’Angelo
- Dipartimento di Medicina Veterinaria e Produzioni Animali, Università degli Studi di Napoli Federico II, 80131 Naples, Italy
| | - Stefano Biffani
- Istituto di Biologia e Biotecnologia Agraria (IBBA), Consiglio Nazionale delle Ricerche, 20133 Milan, Italy
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Ohmic heating treatment in high-protein vanilla flavored milk: Quality, processing factors, and biological activity. Food Res Int 2022; 161:111827. [DOI: 10.1016/j.foodres.2022.111827] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2022] [Revised: 07/28/2022] [Accepted: 08/19/2022] [Indexed: 11/23/2022]
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