Source: CORNELL UNIVERSITY submitted to NRP
NOVEL MULTIMODAL SENSOR TECHNOLOGY FOR EARLY DISEASE DETECTION IN PRE-WEANED DAIRY BREED CALVES
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
ACTIVE
Funding Source
AFRI COMPETITIVE GRANT
Reporting Frequency
Annual
Accession No.
1032336
Grant No.
2024-67015-42368
Cumulative Award Amt.
$300,000.00
Proposal No.
2023-10953
Multistate No.
(N/A)
Project Start Date
Jul 1, 2024
Project End Date
Jun 30, 2026
Grant Year
2024
Program Code
[A1261]- Inter-Disciplinary Engagement in Animal Systems
Recipient Organization
CORNELL UNIVERSITY
(N/A)
ITHACA,NY 14853
Performing Department
(N/A)
Non Technical Summary
There is growing interest in the use of precision livestock technologies (PLT) for dairy calf management. However, there are few sensors commercially available and validated for use in this population. The long-term goal of this research is to optimize pre-weaned dairy calf management using PLT to improve calf health through early disease detection, customized treatment recommendations, and monitoring for recovery. The interdisciplinary project described in this seed grant proposal aims to address the first stage of this long-term goal through design and development of a novel multimodal sensor technology embedded into the nipple from which calves receive milk at automated milk feeding (AMF) stations. We propose to integrate three sensor modalities (pressure, vibration, and contact thermography) within the nipple from which calves feed. The objectives of this project will be to develop this novel PLT for calves fed milk via nipple feeder; to measure and characterize suckling behavior over time at multiple levels (individual feeding, day, 60 d pre-weaning period); and, to describe deviations in normal suckle behavior associated with health and disease in dairy calves prior to weaning. Preliminary activities will focus on sensor development, testing, and validation. Preliminary data will characterize normal suckle behavior and inform sensor placement around the nipple. The anticipated impact of this novel PLT development for calves is to leverage existing behaviors and activities (i.e., feeding milk to pre-weaned calves) to assist dairy producers with calf health management and thus improve calf health, welfare, and make more efficient use of farm staffing resources.
Animal Health Component
30%
Research Effort Categories
Basic
70%
Applied
30%
Developmental
(N/A)
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
30734101170100%
Knowledge Area
307 - Animal Management Systems;

Subject Of Investigation
3410 - Dairy cattle, live animal;

Field Of Science
1170 - Epidemiology;
Goals / Objectives
There is growing interest in the use of precision livestock technologies (PLT) for dairy calf management. However, there are few sensors commercially available and validated for use in this population. The long-term goal of this research is to optimize pre-weaned dairy calf management using PLT to improve calf health through early disease detection, customized treatment recommendations, and monitoring for recovery. The interdisciplinary project described in this seed grant proposal aims to address early disease detection, the first stage of the long-term goal, by developing a novel multimodal sensor technology embedded into the nipple from which calves receive milk. The objectives of this project will be 1) to develop this novel PLT for calves fed milk via nipple feeder; 2) to measure and characterize suckling behavior over time at multiple levels (individual feeding, day, 60 d pre-weaning period); and 3) to describe deviations in suckle behavior associated with health and disease.
Project Methods
Objectives. The research objectives of this seed grant will be to: R1) test and validate sensor modalities for integration with nipples at automated milk feeding (AMF) stations; R2) validate, measure, and characterize suckle behavior at multiple levels (within and between calves, individual feeding visit, across feeding visits in a day, and across days in the pre-weaning period); and, R3) describe deviations in suckle behavior for health and disease.Methods: R1. All sensors need to be designed to withstand a variety of environmental conditions. Sensors embedded into nipples need to withstand environmental conditions, and continue to be thin, flexible, and stretchable to not be obtrusive to the usual suckle behavior while conforming to the shape of the deformable nipple. The Co-PD will leverage their previous work on multimodal fabric-based sensor technologyand modify it to make it more robust to environmental fluctuations in temperature, moisture, negative pressure from sucking, as well as compression and shear forces from chewing. The pressure sensor prototype is nearing readiness for field deployment and testing. Funding from this proposal would support the addition of thermal sensing integration and acoustic vibration for testing and validation on farm. A data-acquisition module will be developed for all sensor data collection and storage at high enough frequency rates to capture and characterize suckle behaviors. Each data source will be synchronized and collected at the same frequency with timestamps for data post-processing. Individual calf identification will be recorded at the automated milk feeding station using existing RFID ear tags along with individual feeding data from the AMF station. Testing and validation with be performed at a single cooperating commercial dairy farm in upstate New York (letter of support provided). A convenience sample of dairy calves will be enrolled in the testing of each prototype. Prototypes will be tested at a single feeding station available to one group of 20 calves. It is estimated that up to 5 prototypes will be tested in the field sequentially as modifications and sensor integration occur. R2 & R3. Validation will involve intensive daily health monitoring performed by trained personnel in the Dr. von Königslöw laboratory to collect daily health scores. Targetted collection of serum on d 2 with be used to estimate transfer of passive immunity, blood gas analysiswill be performed at neonatal calf diarrhea(NCD) diagnosis, thoracic auscultationand thoracic ultrasoundwill be performed bi-weekly from d 7 - 60. Fecal samples and nasal swabs will be collected and stored at first sign of NCD or bovine respiratory disease, respectively. A subset of samples will be analyzed to identify relevant pathogens. A convenience sample will be enrolled representing 50 calves at the participating farm in upstate New York. Calves will be followed from the time they are introduced to the AMF (d 4) until weaning at approximately d 60 of life. It is estimated that 15,000 (50 calves x 5 visits/d x 60 d) time series data records of pressure, temperature, and sound/vibration will be collected. As such, we can use temporal convolution networks (TCNs) or multimodal transformers such as CMXby treating the distributed tactile data as a tactile image. Model inputs will include all synchronized sensor channels concatenated as a vector along with health outcome labels (healthy/diseased/recovered) as determined through the on-farm daily health monitoring described above. If required, a modality-specific encoder can be explored to create and concatenate low-dimensional vector representation of each modality (pressure, temperature, sound/vibration) to pass as inputs to the prediction network. These research questions are open for exploration and validation. This novel data will be used to establish a baseline and within and between calf variation in sensor data at multiple levels (feeding, day, 60 d pre-weaning period). Deviations in suckle behavior will be described and characterized for healthy and diseased calves.Plans for communicating results. Data will be made available through publications and presentations at scientific meetings and seminars throughout the project timeline. We expect to publish our research findings in peer-reviewed scientific journals. Any thesis and/or dissertations resultant from the proposed study will be deposited online at eCommons (https://ecommons.cornell.edu). It is anticipated that future projects will include a substantial extension component.Evaluating Outcomes. Data records will be monitored to prevent interruptions in data collection and will be backed up both on and off site. Model validation using one-calf-out cross validation as well as k-fold cross-validation will be used to see if the performance of our data-driven model can generalize to unseen calves or unseen data. Success will be the equivalence or better performanace than the manual performance of objective health scoringand point of care testing.

Progress 07/01/24 to 06/30/25

Outputs
Target Audience:Summary Farm owners, managers, employees, consultants, and veterinarians play an important role in the rearing of dairy replacements females. The aim of this research is to inform decisions on early disease intervention, monitor recovery, and improve overall dairy calf health and welfare. The anticipated impact of this novel livestock technologyfor calves is to leverage existing behaviors and activities (i.e., feeding milk to pre-weaned calves) to assist dairy producers with calf health management and make more efficient use of farm staffing resources. This would in turn increase the profitability of the dairy operation given that calf health is tied to future health and productivity in the herd. It would also provide an opportunity for farm employees to develop new skills and knowledge in the use of new technologies on farm. Target audience reached 07/01/2024 - 06/30/2025 In this time period, 2 of the 3 sensing modalities have undergone proof of concept field studies and prototype development within the research groups of both the PI and co-PI, respectively. This work has currentlyreached students, scientists, consultants, and veterinarians in the form of scientific conference presentations, manuscripts, and student course reports. Once prototypes are deployed in the field within the next 12-months, we anticipate reaching other members of our target audience such as farm owners, managers, and employees. This next step will be invaluable as it will help refine sensor design to maximize impact on farm. Presentations: Gottwald, K.R., McArt, J.A.A, Sipka, A.S., Bhattacharjee, T. and von Konigslow, T.E. 2025. Associations of oral temperature with disease outcomes and inflammation in pre-weaned dairy heifers. American Dairy Science Association, Louisville, Kentucky. Gottwald, K.R., McArt, J.A.A., Bhattacharjee, T., von Konigslow, T.E. 2024. Oral temperature as an indicator of fever in pre-weaned dairy calves. American Association of Bovine Practitioners Conference, Columbus, Ohio. Seely, C.R., Gottwald, K.R., Xu, B., McArt, J.A.A., Bhattacharjee, T., and von Konigslow, T.E. 2024. Descriptive characteristics of suckle physiology, milk intake, and health in neonatal dairy calves. American Association of Bovine Practitioners Conference, Columbus, Ohio. Manuscripts: Gottwald, K.R., McArt, J.A.A., Bhattacharjee, T., and von Konigslow, T.E. Oral temperature as an indicator of fever in pre-weaned dairy calves. J. Dairy Sci. Comm. (Pre-print) https://doi.org/10.3168/jdsc.2025-0787. Changes/Problems:The largest challenge in conducting this interdisciplinary research is in the identification of young professionals or students with the appropriate skills and interest to work on the design and development of this novel sensor technology in Dr. Bhattacharjee's robotics laboratory. There is growing interest in the use of precision livestock technologies in animal agriculture, as such, there appears to be more researchers interested in studying these technologies in the disciplines of veterinary science, epidemiology, and animal sciences. Funded projects such as this will help increase the visibility and interest in disciplines such as computer sciences, robotics, and engineering. Another significant challenge, relating to the first, is the estimation of the time required to develop, test, and modify prototypes for field deployment. What opportunities for training and professional development has the project provided?The students and young professionals listed below were supported in part or whole by USDA NIFA funding proportional to the work they conducted on this project. Graduate student in Dr. Bhattacharjee's lab: 1.Amber Li, BCSstudent, emphasis in robotics 2.Tina Cheng, BCS student, emphasis in robotics Graduate students and Postdoctoral research Associates in Dr. von Königslöw's lab: 1.Tyler Ward, PhD student 2.Beibei Xu, PhD 3.Katie Gottwald, PhD candidate How have the results been disseminated to communities of interest?07/01/2024 - 06/30/2025 Presentations: Gottwald, K.R., McArt, J.A.A, Sipka, A.S., Bhattacharjee, T. and von Konigslow, T.E. 2025. Associations of oral temperature with disease outcomes and inflammation in pre-weaned dairy heifers. American Dairy Science Association, Louisville, Kentucky. Gottwald, K.R., McArt, J.A.A., Bhattacharjee, T., von Konigslow, T.E. 2024. Oral temperature as an indicator of fever in pre-weaned dairy calves. American Association of Bovine Practitioners Conference, Columbus, Ohio. Seely, C.R., Gottwald, K.R., Xu, B., McArt, J.A.A., Bhattacharjee, T., and von Konigslow, T.E. 2024. Descriptive characteristics of suckle physiology, milk intake, and health in neonatal dairy calves. American Association of Bovine Practitioners Conference, Columbus, Ohio. Manuscripts: Gottwald, K.R., McArt, J.A.A., Bhattacharjee, T., and von Konigslow, T.E. Oral temperature as an indicator of fever in pre-weaned dairy calves. J. Dairy Sci. Comm. (Pre-print) https://doi.org/10.3168/jdsc.2025-0787. Student reports and presentations within Cornell: Li, A., Cheng, T., von Konigslow, T.E, Bhattacharjee, T.2025. Multimodal Sensorized Feeding Nipple for Disease Detection in Calves. Cornell Bower Computer Science. Report and poster presentation. Li, A., Cheng, T., von Konigslow, T.E,Bhattacharjee, T.2025. Multimodal Sensorized Feeding Nipple for Disease Detection in Calves. Cornell Department of Computer Science. Presented at Cornell Bower Computer Science Robotics Day 2025. What do you plan to do during the next reporting period to accomplish the goals?Concept validations studies performed at a single cooperatingdairy farm in upstate New York. These studies involved intensive health monitoring performed by trained personnel in the Dr. von Königslöw laboratory to collect health scores (Calf Health Scorer app; University of Wisconsin, Maddison, WI; McGuirk, 2008). Targetted collection of serum in the first week of lifewith be used to estimate passive transfer of maternal immunity (Misco DD-2 refractometer, Solon, OH), blood gas analysis (iStat 1, Abbott Point of Care, Orlando, FL) will be performed at neonatal calf diarrhea (NCD) diagnosis, thoracic auscultation (3M Littman Core digital stethoscope, Emeryville, CA) and thoracic ultrasound (EasiScan: Go, IMV, Rochester, MN; Buczinski et al., 2015, 2018) will be performed bi-weekly when validating respiratory sound and vibration sensing. A respiratory sound and vibration concept validation study was initiated in April 2025 and is currently ongoing. Prototype development and testingperformedin Dr. Bhattacharjee's full stack robotics lab. Field testing will be conductedat a single cooperatingdairy farm in upstate New York. More extensive testing in the field is slated tobegin fall of 2025. IACUC #: 2022-0161, 2023-0264, 2025-0058

Impacts
What was accomplished under these goals? Accomplishments: 07/01/2024 - 06/30/2025 Within the first year of this project, 2 of the 3 sensing modalities (pressure and temperature) have published proof of concept field studies, conducted by the von Königslöw lab, supporting their inclusion in this multimodal sensor. The third of the 3 sensing modalities (sound) has a proof-of-concept field study currently under way. In parallel to these field investigations, prototype development in the Bhattacharjee lab is ongoing with prototype versions being tested and informed by the work conducted in the von Königslöw lab. · For pressure sensing, a field study was conducted to measure suckle pressure using impression film-wrapped nipples. This study was funded by the Cornell Institute of Digital Agriculture (2022-95) and published in Agriculture (https://www.mdpi.com/2077-0472/15/17/1831). The results support the use of pressure sensing for detecting calves with neonatal calf diarrhea and helped inform prototype development for the work supported by this award (Objective 1). A second manuscript is in progress with the support of this award to describe deviations in suckle pressure in sick and healthy calves (Objective 3). · For temperature sensing, a field study was conducted to measure oral and rectal temperatures in calves using digital contact thermometers. This study was funding by this award and was recently published in the Journal of Dairy Science Communications (https://doi.org/10.3168/jdsc.2025-0787). The results support the use of oral temperature sensing to detect fevers in calves and helped inform the development of a second round of prototypes now with both pressure and temperature sensing (Objective 1). A second manuscript is in progress with the support of this award to describe deviations in temperature in sick and healthy calves (Objective 3). · A field study is currently in progress to look at including individual sound measurements as a means to classify sick and healthy calves. This work is particularly interested in application for detecting and predicting bovine respiratory disease. Prototype development towards the inclusion of this third sensing modality is anticipated in year 2 of this award. Overall, progress is being made towards Objectives 1 and 3. Once a field ready prototype is deployed data will be collected to advance towards Objective 2. This work has currentlyreached students, scientists, consultants, and veterinarians in the form of scientific conference presentations, manuscripts, and student course reports. Once prototypes are deployed in the field within the next 12-months, we anticipate reaching other members of our target audience such as farm owners, managers, and employees. This next step will be invaluable as it will help refine sensor design to maximize impact on farm.

Publications

  • Type: Peer Reviewed Journal Articles Status: Accepted Year Published: 2025 Citation: Gottwald, K.R., McArt, J.A.A., Bhattacharjee, T., and von Konigslow, T.E. Oral temperature as an indicator of fever in pre-weaned dairy calves. J. Dairy Sci. Comm. (Pre-print) https://doi.org/10.3168/jdsc.2025-0787.