The Impact of Seasonality in Pasture-Based Production Systems on Milk Composition and Functionality

Timlin, Mark; Tobin, John T.; Brodkorb, André; Murphy, Eoin G.; Dillon, P.; Hennessy, Deirdre; O’Donovan, M.; Pierce, K.M.; O’Callaghan, Tom F.

doi:10.3390/foods10030607

Cited by 52 publications

(23 citation statements)

References 242 publications

(482 reference statements)

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“…This is due to the importance of grass in the production system of these farms. This practice is in line with what is very common in Ireland and New Zealand, where seasonal calving is largely adopted, so local farms can take advantage of their animal production potential at the time of grass growing [45]. Additionally, in our study, only 30% of farms minimized calving during summer.…”

Section: Discussionsupporting

confidence: 85%

Production and Health Management from Grazing to Confinement Systems of Largest Dairy Bovine Farms in Azores: A Farmers’ Perspective

Medeiros

Fernández-Novo

Astiz³

et al. 2021

Animals

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The intensification of bovine milk production in the Azores has led farmers to increase farm size and specialization in grasslands, implementing confined and semi-confined production systems. Fixed milking parlours (FMP) have progressively gained more popularity, at the expense of conventional mobile milking systems (MMS). The present study aimed to evaluate the associations between production and health management in dairy cattle farms, with FMP or MMS, in grasslands (São Miguel, Azores), according to the farmers’ perspective. A total of 102 questions about production and health management were surveyed in 105 farms with >30 dairy cows each. Farms with FMP were associated (p ≤ 0.05) with larger herd size, better facilities, and specialized management, however, the adoption of preventive and biosecurity measures should be improved by these farmers. MMS farms implemented a lower level of disease prevention or control programs, less frequent transhumance, and showed a wider vocation to dual-purpose (milk and cross beef) than FMP farms. In conclusion, MMS and FMP farms tried to optimize yield and economic viability in different ways using grasslands. Several biosecurity and health prevention constraints were identified for improvement.

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Section: Discussionsupporting

confidence: 85%

Production and Health Management from Grazing to Confinement Systems of Largest Dairy Bovine Farms in Azores: A Farmers’ Perspective

Medeiros

Fernández-Novo

Astiz³

et al. 2021

Animals

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“…Changes in dairy cattle milk composition across lactation are more noticeable in seasonal pasture-based farming systems (compared with nonseasonal systems), where compact calving periods are used so that peak lactation volumes are matched with peak grass growth (Timlin et al, 2021). Although NZ dairy systems are mainly pasture-based, intensification has resulted in widespread use of supplement feed to offset the effect of high-stocking rates and ensure that the nutritional requirements of cows are met.…”

Section: Confounding Between Pregnancy Status and Stage Of Lactation ...mentioning

confidence: 99%

Pregnancy status predicted using milk mid-infrared spectra from dairy cattle

Tiplady

Trinh

Davis

et al. 2022

Journal of Dairy Science

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Accurate and timely pregnancy diagnosis is an important component of effective herd management in dairy cattle. Predicting pregnancy from Fouriertransform mid-infrared (FT-MIR) spectroscopy data is of particular interest because the data are often already available from routine milk testing. The purpose of this study was to evaluate how well pregnancy status could be predicted in a large data set of 1,161,436 FT-MIR milk spectra records from 863,982 mixed-breed pasturebased New Zealand dairy cattle managed within seasonal calving systems. Three strategies were assessed for defining the nonpregnant cows when partitioning the records according to pregnancy status in the training population. Two of these used records for cows with a subsequent calving only, whereas the third also included records for cows without a subsequent calving. For each partitioning strategy, partial least squares discriminant analysis models were developed, whereby spectra from all the cows in 80% of herds were used to train the models, and predictions on cows in the remaining herds were used for validation. A separate data set was also used as a secondary validation, whereby pregnancy diagnosis had been assigned according to the presence of pregnancy-associated glycoproteins (PAG) in the milk samples. We examined different ways of accounting for stage of lactation in the prediction models, either by including it as an effect in the prediction model, or by pre-adjusting spectra before fitting the model. For a subset of strategies, we also assessed prediction accuracies from deep learning approaches, utilizing either the raw spectra or images of spectra. Across all strategies, prediction accuracies were highest for models using the unadjusted spectra as model predictors. Strategies for cows with a subsequent calving performed well in herdindependent validation with sensitivities above 0.79, specificities above 0.91 and area under the receiver operating characteristic curve (AUC) values over 0.91. However, for these strategies, the specificity to predict nonpregnant cows in the external PAG data set was poor (0.002-0.04). The best performing models were those that included records for cows without a subsequent calving, and used unadjusted spectra and days in milk as predictors, with consistent results observed across the training, herd-independent validation and PAG data sets. For the partial least squares discriminant analysis model, sensitivity was 0.71, specificity was 0.54 and AUC values were 0.68 in the PAG data set; and for an image-based deep learning model, the sensitivity was 0.74, specificity was 0.52 and the AUC value was 0.69. Our results demonstrate that in pasture-based seasonal calving herds, confounding between pregnancy status and spectral changes associated with stage of lactation can inflate prediction accuracies. When the effect of this confounding was reduced, prediction accuracies were not sufficiently high enough to use as a sole indicator of pregnancy status.

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“…Grass-fed dairy systems are best suited to regions with a temperate climate, plentiful rainfall and fertile soils that can enable cows to be maintained outdoors grazing pasture for the majority of their lactation, whereby calving periods are synchronised for milk production to coincide with the grass growing periods of the year, that is, spring-calving dairy herds. However, this seasonal approach to milk production poses challenges to dairy manufacturers, due to synchronised changes in milk composition and quality as the herd transitions through early, mid and late stages of lactation (see review by Timlin et al, 2021). The definition of grass-fed, as such, can vary from region to region, often differing in the levels of fresh pasture in the diet, the type of grass or portion of required access to outdoor paddocks per day or per lactation.…”

Section: Grass-fed Milkmentioning

confidence: 99%

Irish research response to dairy quality in an era of change

O’Brien

Beresford

Cotter

et al. 2022

Irish Journal of Agricultural and Food Research

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The Irish dairy sector is recognised for its very significant contribution to the national economic status; it is now worth ∼€5 billion annually and represents the largest food and drink export category, which, in turn, represents one of the four largest manufacturing industries in the country. Given anticipated further growth in global demand for dairy products and the positive attributes and capabilities that Ireland has to meet that demand, in terms of pasture-based production and cost competitiveness, it is incumbent for the sector to attain the highest quality milk and dairy products. The combined collaborative approach between research and industry has ensured significant progress and enabled Ireland to remain at the forefront globally in terms of production of quality milk and dairy products. This paper highlights some specific scientific platforms and technologies currently shaping the industry in this regard and discusses current research activity as well as anticipating key requirements for future progress. While research, and farm and processing plant management have accomplished very significant advances in milk and dairy product quality, some overarching emerging challenges include product substitution and sustainability. Some key pillars for the future have been identified on which a strong, efficient dairy sector can be maintained and progressed. Specifically, the use of evidence-based information and real-time measures in prediction and decision-making will be a crucial pillar for the dairy sector of the future. This can promote an approach of proactive maintenance and optimisation of production through improved predictability and control of manufacturing processes.

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The Impact of Seasonality in Pasture-Based Production Systems on Milk Composition and Functionality

Cited by 52 publications

References 242 publications

Production and Health Management from Grazing to Confinement Systems of Largest Dairy Bovine Farms in Azores: A Farmers’ Perspective

Production and Health Management from Grazing to Confinement Systems of Largest Dairy Bovine Farms in Azores: A Farmers’ Perspective

Pregnancy status predicted using milk mid-infrared spectra from dairy cattle

Irish research response to dairy quality in an era of change

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