The impact of mycotoxins on dairy cow health and milk production

В статье представлены материалы о влиянии микотоксинов на здоровье и продуктивность молочного скота. В настоящее время наибольшую опасность для здоровья животных представляют яды микроскопических грибов — микотоксины, что требует разработки методов их устранения по всей цепочке — от поля до потребителя. Известно, что споры грибов, продуцирующих токсины, живут в почве и оттуда передаются растениям, а затем зёрнам. Микотоксины — это вторичные метаболиты грибов, такие как афлатоксины (AF), продуцируемые видами Aspergillus, фумонизины (FUM), зеараленон (ZEN), токсин T-2 (T-2) дезоксиниваленол (DON), продуцируемый видами Fusarium, охратоксин A (OTA), продуцируемый видами Penicillium, и многие другие. Потребление кормов, загрязнённых этими токсинами, вызывает у животных микотоксикозы, которые характеризуются рядом клинических признаков в зависимости от вида токсинов. У животных снижается продуктивность и поедаемость кормов, увеличивается восприимчивость к различным заболеваниям. Существует две формы микотоксикозов: острые микотоксикозы, возникающие из-за потребления высокой разовой дозы микотоксинов, и хронические микотоксикозы из-за постоянного потребления низких уровней микотоксинов в течение продолжительного времени. Хронический токсикоз, вызванный низким уровнем воздействия микотоксинов в течение продолжительного времени, представляет собой более распространённую проблему для здоровья животных и качества пищевых продуктов для людей. В целом объёмистые корма и зерновые компоненты, входящие в состав рациона, подвержены загрязнению афлатоксинами на всех этапах производства кормов, таких как сбор, транспортировка, хранение, переработка и упаковка. В последнее время учёные стали уделять больше внимания загрязнению кормов микотоксинами и механизмам борьбы с разными группами токсинов. Основной задачей при производстве кормов является снижение концентрации токсинов на всех этапах — от поля до рациона животных. This article focuses on the effect of mycotoxins on dairy cow health and productivity. To this day toxins produced by various fungi are one of the most serious dangers for cattle. It is known that spores usually contaminate plant and later grain material from soil. Mycotoxins are secondary metabolites such as aflatoxins (AF) produced by Aspergillus spp., fumonisins (FUM), zearalenone (ZEN), T-2 (T-2), deoxynivalenol (DON) produced by Fusarium spp., ochratoxin A (OTA) produced by Penicillium spp., and many others. Toxin-contaminated forage causes mycotoxicoses of different severity depending on toxin type. Livestock shows low productivity and appetite but high susceptibility to diseases There are two types of mycotoxicoses: acute mycotoxicoses, caused by high concentration of toxins and the chronic ones, occurring due to constant long consumption of low toxin levels. Chronic toxicosis is a more common problem for animal health and food quality. Bulk and grain feed are highly affected by aflatoxins at such production stages as harvesting, transporting, storage, processing and packaging. Lately scientists drew more attention to toxin contamination issue and methods controlling their accumulation. The main task when producing forage is to reduce toxin concentration at all the production stages.

DIGITAL COW HEALTH MONITORING TECHNOLOGIES

Обоснован рост требований к системе мониторинга здоровья и физиологического состояния животных для решения задач по увеличению срока продуктивного хозяйственного использования высокопродуктивных коров на крупных молочных комплексах. Анализ основных причин выбраковки коров в племенных хозяйствах Ленинградской области свидетельствует, что большую часть болезней при беспривязном содержании коров с доением в доильных залах можно выявить и предотвратить на ранних стадиях, тщательно фиксируя и оперативно реагируя на «сигналы коров», характеризующие активность, особенности передвижения, нахождение в различных зонах животноводческих помещений, потребление корма и воды, руминацию, внешний вид. Проведен анализ возможностей и ограничений существующих и разрабатываемых автоматических систем мониторинга здоровья и физиологического состояния животных, таких как: ошейники с транспондерами, ушные бирки c трехосным акселерометром, болюсы. Рассмотрены тенденции и перспективы разработки и освоения в молочном животноводстве цифровых технологий обработки и анализа визуальной информации, получаемой круглосуточно с камер наблюдения, с применением элементов «искусственного интеллекта», нейросетевых алгоритмов. Мониторинг поведенческих сигналов животных с помощью современных цифровых технологий может стать решением актуальных производственно-экономических задач: сохранение здоровья высокопродуктивных коров в больших стадах в условиях автоматизированного производства молока, увеличение продолжительности их хозяйственного использования, улучшение воспроизводства стада, рост экономической эффективности отрасли. The growth of requirements for the system of monitoring the health and physiological state of animals for solving the problems of increasing the period of productive economic use of highly productive cows at large dairy complexes has been substantiated. Analysis of the main reasons for the culling of cows in the breeding farms of the Leningrad Region shows that most of the diseases in case of loose housing of cows with milking in milking parlors can be detected and prevented at early stages by carefully recording and promptly responding to “cow signals” characterizing activity , peculiarities of movement, being in various zones of livestock buildings, consumption of feed and water, rumination, appearance. The analysis of the possibilities and limitations of existing and developed automatic systems for monitoring the health and physiological state of animals, such as collars with transponders, ear tags, boluses, is carried out. Trends and prospects for the development and development of digital technologies for processing and analysis of visual information received around the clock from surveillance cameras using elements of "artificial intelligence" and neural network algorithms are considered.

Key issues in dairy herd health management

Dairy herd health management benefits dairy farmers, the environment, dairy cows and citizens. It is an important part of modern dairy farm veterinary care. Dairy herd health management is assessing, monitoring and improving the health of dairy cows at a population level. Good herd health management takes a holistic approach and is ongoing and cyclical. All members of the dairy farm team and their advisors are involved, decisions are informed by data generated by the herd. These data may come from numerous sources. The data are processed and analysed to monitor cow health, target investigations and evaluate progress. To make lasting change on farms, advisors must communicate appropriately with farm managers to understand behaviour and motivate change. This chapter reviews these aspects of dairy herd health management, giving practical suggestions on how to get started, how to incorporate herd health management into business models and how to maintain momentum.

Milk Lactose as a Biomarker of Subclinical Mastitis in Dairy Cows

Bovine subclinical mastitis can cause great harm to dairy herds because of its negative impact on milk production and quality and cow health. Improved diagnostic tools are needed to maximise the control of subclinical mastitis distribution and ensure the high quality of milk as an industrial product. Between 2015 and 2020, seventy-two dairy herds were screened for bovine subclinical mastitis causative agents to identify the relationship between seasons, lactose levels and subclinical mastitis infection. The predominant species found in the milk samples were mixed microbiota, coagulase-negative Staphylococcus and Staphylococcus aureus. Yeasts were found exclusively in autumn, while Enterococcus spp. and Escherichia coli were only found in summer and autumn. A negative correlation was detected between milk lactose and number of somatic cells in milk (−0.471; p < 0.001). The lactose levels in milk were closely associated with the prevalence (%) of subclinical mastitis pathogens, such as Streptococcus agalactiae (y = −1.8011x + 10.867, R2 = 0.9298), Staph. aureus (y = −3.5216x + 25.957, R2 = 0.8604) and other Streptococci (y = −0.5956x + 7.6179, R2 = 0.6656). These findings suggest that milk lactose may be used as a biomarker of suspected udder inflammation in modern health prevention programmes for cows to reduce the prevalence of subclinical mastitis pathogens in dairy cattle herds.

Machine learning prediction of sleep stages in dairy cows from heart rate and muscle activity measures

Sleep is important for cow health and shows promise as a tool for assessing welfare, but methods to accurately distinguish between important sleep stages are difficult and impractical to use with cattle in typical farm environments. The objective of this study was to determine if data from more easily applied non-invasive devices assessing neck muscle activity and heart rate (HR) alone could be used to differentiate between sleep stages. We developed, trained, and compared two machine learning models using neural networks and random forest algorithms to predict sleep stages from 15 variables (features) of the muscle activity and HR data collected from 12 cows in two environments. Using k-fold cross validation we compared the success of the models to the gold standard, Polysomnography (PSG). Overall, both models learned from the data and were able to accurately predict sleep stages from HR and muscle activity alone with classification accuracy in the range of similar human models. Further research is required to validate the models with a larger sample size, but the proposed methodology appears to give an accurate representation of sleep stages in cattle and could consequentially enable future sleep research into conditions affecting cow sleep and welfare.

Interspecies information systems

This article introduces a new class of socio-technical systems, interspecies information systems (IIS) by describing several examples of these systems emerging through the use of commercially available data-driven animal-centered technology. When animal-centered technology, such as pet wearables, cow health monitoring, or even wildlife drones captures animal data and inform humans of actions to take towards animals, interspecies information systems emerge. I discuss the importance of understanding them as information systems rather than isolated technology or technology-mediated interactions, and propose a conceptual model capturing the key components and information flow of a general interspecies information system. I conclude by proposing multiple practical challenges that are faced in the successful design, engineering and use of any IIS where animal data informs human actions.