Abstract
Simple SummarySensors, routinely collected on-farm tests, and other repeatable, high-throughput measurements can provide novel phenotype information on a frequent basis. Information from these sensors and high-throughput measurements could be harnessed to monitor or predict individual dairy cow feed intake. Predictive algorithms would allow for genetic selection of animals that consume less feed while producing the same amount of milk. Improved monitoring of feed intake could reduce the cost of milk production, improve animal health, and reduce the environmental impact of the dairy industry. Moreover, data from these information sources could aid in animal management (e.g., precision feeding and health detection). In order to implement tools, the relationship of measurements with feed intake needs to be established and prediction equations developed. Lastly, consideration should be given to the frequency of data collection, the need for standardization of data and other potential limitations of tools in the prediction of feed intake. This review summarizes measurements of feed efficiency, factors that may impact the efficiency and feed consumption of an animal, tools that have been researched and new traits that could be utilized for the prediction of feed intake and efficiency, and prediction equations for feed intake and efficiency presented in the literature to date.Feed for dairy cattle has a major impact on profitability and the environmental impact of farms. Sustainable dairy production relies on continued improvement in feed efficiency as a way to reduce costs and nutrient loss from feed. Advances in breeding, feeding and management have led to the dilution of maintenance energy and thus more efficient dairy cattle. Still, many additional opportunities are available to improve individual animal feed efficiency. Sensing technologies such as wearable sensors, image-based and high-throughput phenotyping technologies (e.g., milk testing) are becoming more available on commercial farm. The application of these technologies as indicator traits for feed intake and efficiency related traits would be advantageous to provide additional information to predict and manage feed efficiency. This review focuses on precision livestock technologies and high-throughput phenotyping in use today as well as those that could be developed in the future as possible indicators of feed intake. Several technologies such as milk spectral data, activity, rumen measures, and image-based phenotypes have been associated with feed intake. Future applications will depend on the ability to repeatably measure and calibrate these data across locations, so that they can be integrated for use in predicting and managing feed intake and efficiency on farm.
Highlights
Known as gross feed efficiency (GFE), is the proportion of output to input, or the amount of milk output produced per one unit of feed intake in lactating dairy cattle
Feed saved is defined as the reduced feed intake between an animal’s actual feed intake and the predicted intake-based accounting for milk production and maintenance requirements using body weight (BW) and Residual feed intake (RFI) [12]
Automated scales connected to milking systems and camera-based imaging systems may allow for monitoring of body weight over time
Summary
Improvements in feed efficiency will positively impact the environment by reducing greenhouse gas emissions of cattle and manure (Food and Agriculture Organization of the United Nations) [3] as well as land requirements for manure disposal and water needs [4,5]. New methods and technologies are needed to monitor feed intake in the dairy industry since current technologies that measure individual feed intake are not practical on commercial farms. The objective of this review is to discuss new opportunities to use data from state-of-the-art technologies such as sensing technologies and high-throughput lab data to monitor feed intake and other factors known to impact various definitions of efficiency
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