Technical Name Big Data Analytic Technology for Broiler Specification PredictionFeeding Condition Optimizing for Smart Agriculture
Project Operator National Tsing Hua University
Project Host 簡禎富
The technology develops an algorithm to estimate the average weight of broilers in poultry houses every hour. In addition, using the prediction resultshistorical broiler carcass distribution information to predict the average weightslaughtering specification distribution of each farm for the next 7 days. The technology enables agribusiness to accurately schedule the appropriate time for each farm to meet the market's specificationsreduce losseswaste. The technology has been validated in the broiler industry, achieving an accuracy of 98 in weight predictionan error rate of 6 in specification prediction.
Scientific Breakthrough
This technology allows contract farmers to monitor the growth status of broilers immediatelymore accurately control the environmental temperaturehumidity to shorten the feeding cycle. Besides, the technology allows agribusiness to accurately determine the optimal time of slaughtering for each farm to fulfill the market demand for meat specifications, to reduce substandard meatthe waste of feeding resources.
Industrial Applicability
The technology is an important basic data application for the livestock breeding industry. In the future, even if the industry does not necessarily need specification prediction, the algorithm can be used with other breeding parameters to make predictionssuggestions. The technology can be implemented in both the quality control of the final productthe cost control of the production process.
Keyword Smart Agriculture Poultry farming Big Data Analytic Broiler Feeding Specification Prediction Production and sales balance Feeding Condition Optimization Weight estimation Digital Transformation for Agribusiness Smart Operation
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