Abstract
Increased global temperatures and climatic anomalies, such as heatwaves, as a product of climate change, are impacting the heat stress levels of farm animals. These impacts could have detrimental effects on the milk quality and productivity of dairy cows. This research used four years of data from a robotic dairy farm from 36 cows with similar heat tolerance (Model 1), and all 312 cows from the farm (Model 2). These data consisted of programmed concentrate feed and weight combined with weather parameters to develop supervised machine learning fitting models to predict milk yield, fat and protein content, and actual cow concentrate feed intake. Results showed highly accurate models, which were developed for cows with a similar genetic heat tolerance (Model 1: n = 116, 456; R = 0.87; slope = 0.76) and for all cows (Model 2: n = 665, 836; R = 0.86; slope = 0.74). Furthermore, an artificial intelligence (AI) system was proposed to increase or maintain a targeted level of milk quality by reducing heat stress that could be applied to a conventional dairy farm with minimal technology addition.
Highlights
Robotic dairy farms or Automated Milking Systems (AMS) are the result of the implementation of state of the art technology related to robotics to increase milk yield through increased efficiency and automation [1,2]
During the four years included in this study (2016–2019), there was a clear variation within seasons reflected by environmental parameters (THI) and milk productivity parameters (Figure 2)
The managerial advantages that could be obtained by implementing the system proposed are: (i) milk volume and quality information available in real-time, per cow, and according to daily environmental conditions; (ii) prediction of actual concentrate feed intake per cow for feed monitoring management compared to programmed concentrate feed; (iii) real-time information to manage heat stress in a per cow basis to increase efficiency and maintain milk volumes and quality set as objectives, and (iv) data recorded from specific dairy farms can be incorporated in the model to increase the accuracy of target predictions
Summary
Robotic dairy farms or Automated Milking Systems (AMS) are the result of the implementation of state of the art technology related to robotics to increase milk yield through increased efficiency and automation [1,2]. Global demands will be accompanied by 14 million traditional dairy farms shutting down production due to increased competitiveness and requirements for guaranteed milk quality and animal welfare [4] The latter is considered a growing concern for consumers, which is achieved by AMS since it is based on the “milking when they like” system increasing wellbeing and welfare of cows [5]. Further potential advances to AMS technologies have been researched in recent years through the implementation of biometrics monitoring of animals to assess physiological changes in production systems [6] Some of these technologies are noninvasive using visible (RGB) imagery/video, and infrared thermal imagery for heart rate, respiration rate, and body temperature assessments. These technologies could result in improvements in the monitoring of heat stress in farm animals
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