239 Poultry chain management by IK4-Tekniker SADA p.a. SA Exafan Porphyrio (Industry Innovation)

 

 

239 Industry Innovation – Poultry chain management by IK4-Tekniker SADA p.a. SA Exafan Porphyrio

In Significant Impact Groups: Precision Livestock Farming & Early detection \ Sensor technology
Species targeted: Poultry;
Age: Not stated;
Summary:
Optimising production, transport and processing of poultry meat by automated ambient monitoring and control, and data analyses.

Where to find the original material: https://www.iof2020.eu/trials/meat/poultry-chain-management;
Country: ES

232 Happy cow by Connecterra VetVice Wageningen University & Research ZLTO (Industry Innovation)

 

 

232 Industry Innovation – Happy cow by Connecterra VetVice Wageningen University & Research ZLTO

In Significant Impact Groups: Precision Livestock Farming & Early detection \ Sensor technology
Species targeted: Dairy;
Age: Adult;
Summary:
Improving dairy farm productivity through IoT technology and machine learning technologies.

Where to find the original material: https://www.iof2020.eu/trials/dairy/happy-cow;
Country: NL

230 Remote dairy quality by Qlip BV DMK ZLTO (Industry Innovation)

 

 

230 Industry Innovation – Remote dairy quality by Qlip BV DMK ZLTO

In Significant Impact Groups: Precision Livestock Farming & Early detection \ Sensor technology
Species targeted: Dairy;
Age: Adult;
Summary:
Assuring remote quality of accurate instruments, analysis and pro-active control in the dairy chain.

Where to find the original material: https://www.iof2020.eu/trials/dairy/remote-milk-quality;
Country: NL

228 Early Lameness Detection Through Machine Learning by Waterford Institute of Technology ENGS Dairy University of Strathclyde Herdsy (Industry Innovation)

 

 

228 Industry Innovation – Early Lameness Detection Through Machine Learning by Waterford Institute of Technology ENGS Dairy University of Strathclyde Herdsy

In Significant Impact Groups: Precision Livestock Farming & Early detection \ Sensor technology
Species targeted: Dairy;
Age: Adult;
Summary:
Using machine learning to identify early lameness in cattle at an early stage to increase animal welfare and lower treatment costs.

Where to find the original material: https://www.iof2020.eu/trials/dairy/lameness-detection-through-machine-learning
Country: NE

227 Multi-sensor cow monitoring by MOONSYST INC (Industry Innovation)

227 Industry Innovation – Multi-sensor cow monitoring by MOONSYST INC

In Significant Impact Groups: Precision Livestock Farming & Early detection \ Sensor technology
Species targeted: Dairy;
Age: Adult;
Summary:
Achieving more efficient and sustainable livestock farming through a unique Smart Rumen Monitoring System and cloud-based data processing application.

Where to find the original material: https://www.iof2020.eu/trials/dairy/multi-sensor-cow-monitoring;
Country: NL

Use of Thermal Imaging to Diagnose Lameness

Lameness is accepted as causing the biggest loss of income on dairy farms, and second only to mastitis as the leading cause of antibiotic use. It is also widely reported that lameness is under-diagnosed as in many studies ony 25% of lame cows are diagnosed. Observational detection is subjective, requires skill, and is time consuming so the low detection rates are understandable.

Technology, such as Cow Alert, has enabled automatic lameness scoring. Monitoring cows 24 hours per day, 7 days a week has resulted in a much higher detection rate. Indeed it often identifies lame cows at an earlier time than experienced stockpersons would. Thermal imaging cameras can be used to best effect to investigate the cause of lameness on these cows. They can differentiate between foul infections that require antibiotic treatment, and the majority of causes that don’t. Furthermore, thermal imaging can pinpoint the exact location of a sole ulcer enabling foot trimmers to be precise in their area of investigation. In early cases, it can even identify the lame foot, or establish that the cause of lameness is not in the foot.

The use of thermal imaging validates the lameness alerts of Cow Alert, and directs and motivates the stockman to treat the cow appropriately and at the earliest possible opportunity. It gives confidence that the hoof-knife is being used in the correct location, and will therefore locate ulcers/white line disease that would otherwise not be found. This improves animal wellbeing, reduces milk loss, and reduces the amount of antibiotics used.

Monitoring microclimate parameters in dairy farms

The use of precision tools on dairy farms gives the farmer or manager the opportunity to make essential decisions in real time, in accordance with the information received from the animal or shelter. There is a SMART Zoo Tech system for monitoring microclimate parameters for measuring, logging, and monitoring the temperature, humidity, dew point, carbon dioxide (CO2) concentration, ammonia (NH3) and dust particles (PM 2.5) 24/7. The information is stored in the database available to the farmer, and the exceedances are sent to the farmer by mobile phone in the form of an alert. It is found that there is a very close correlation between individual cow production and microclimate parameters. On a hot summer day when the average atmospheric temperature was 34oC, in the shelter the temperature varied between 23.45oC at 4:00 am and 31.04oC at 5:00 pm. There were also fluctuations in relative humidity and ammonia levels in the shelter after 4:00 pm. The farmer received phone alerts for every microclimate parameter every hour in the second half of the day. With regard to milk production, it is known that for the dairy cow the optimum temperature range is between 9 and 16oC. During the observed period there was a decrease in milk production, and on the reference day the milk production was 10% lower than two days prior.

87 Biosensors for on-farm diagnosis of mastitis (Research paper, Martins, 2019)

 

 

Significant Impact Group(s): Precision Livestock Farming & Early detection \ Sensor technology ; Pathogen management
Species targeted: Dairy; Age: Adult;
Outcome Parameter(s): Mastitis indicative markers

Summary: Bovine mastitis is an inflammation of the mammary gland caused by a large number of infectious agents with devastating consequences for the dairy industry. Management of mastitis usually means using antibiotics to treat and prevent the disease, which can be problematic because of increased antimicrobial resistance. Typical diagnostic methods are based on somatic cell counts (SCC) and plate-culture techniques. But these methods are not quick and there is quite a lot of interest in making faster solutions that could provide onsite information, which would speed up the choice of treatment.

Biosensors are tools that can convert the presence of biological particles into an electric signal. Together with microfluidics, biosensors can be used in the development of automated and portable diagnostic devices. This review describes current approaches for mastitis diagnosis and the latest outcomes in biosensors and lab-on-chip devices with the potential to become real alternatives to standard practices.

Research paper: Martins – 2019 – Biosensors for on-farm diagnosis of mastitis – https://doi.org/10.3389/fbioe.2019.00186
Where to find the original material (in English):
https://www.frontiersin.org/articles/10.3389/fbioe.2019.00186/full;

Country: Portugal
Tags: dairy, mastitis, diagnositcs

87 Research paper – Martins – 2019 – Biosensors for on-farm diagnosis of mastitis

Health Benefits of Monitoring Rumination

It is now common for neckcollars and eartags to measure rumination, as well as activity, in automatic heat detection systems. However there is a greater benefit in the use of rumination data as an early warning health alert. Not only are cows monitored 24 hours a day and alerts sent to the stockman when a problem arises – allowing time to be focused on animals that need attention – but a reduction in rumination rate is an earlier symptom than the more obvious signs of sickness that are traditionally seen. This early diagnosis leads to a wider range of potential treatments, many curative averting the need of antibiotic use, making the symptoms less severe and allowing a much quicker recovery.

For example, at the South West Dairy Development Centre, the Smartbow eartag identified reduced rumination at 3 days post calving, prompting a vet diagnosis of a dilated abomasum – the first stage of a DA. Appropriate treatment avoided the need for an operation – and the corresponding antibiotic use – and resulted in a quickly recovered cow.

Similarly monitoring rumination can identify early stages of ketosis, acidosis, mastitis and even the time of calving. Monitoring rumination at a herd/ group can identify Sub Acute Ruminal Acidosis, suboptimal dry cow transition diets, and even poor forage quality.

Remotely monitoring rumination rate can also indicate if a treatment has been successful. Two technologies – Cow Manager and SmaXtec (a rumen bolus) also include temperature in the health alert algorithm.

Monitoring rumination can save time, improve animal health, reduce stress, improve treatment outcomes, increase production and reduce antibiotic use.

WEBINAR: How can the management of clinical and subclinical mastitis be supported by sensor systems?

An exciting line-up of speakers hosted online by IDF (https://www.fil-idf.org/) on 14th October 2020:

  • Detection of severe clinical mastitis DR ILKA KLAAS, DELAVAL INTERNATIONAL AB, DENMARK
  • Detection of mild/moderate mastitis DR GUNNAR DALEN, TINE DAIRIES SA, NORWAY
  • Detection to support dry off decisions PROF. DAVID KELTON, UNIVERSITY OF GUELPH, CANADA & DR ALFONSO
    ZECCONI, UNIVERSITA DEGLI STUDI DI MILANO, ITALY
  • Detection of herd level mastitis problems DR HONIG HEN, VETERINARY SERVICE, MINISTRY OF AGRICULTURE,
    ISRAEL
  • Conclusions: Thinking outside the box: Novel ways to utilize sensor data to improve mastitis management PROF. HENK HOGEVEEN, WAGENINGEN UNIVERSITY, NETHERLANDS
  • Questions and Answers on Zoom chat

Watch the webinar here:

 

Download the presentation here