In order to improve the labor consumption, energy consumption, low yield and uneven quality of the traditional mushroom industry's compost production and fermentation methods, the Taiwan Agricultural Research Institute
The crop disaster early warning and notification system integrates the real-time weather information, forecasting, and crops critical thresholds to provide useful and instant information to the
Taiwan Agricultural Research Institute, Council of Agriculture, Executive Yuan and Industrial Technology Research Institute collaborate on developing an early-warning intelligent system for
The traditional asparagus management mode has resulted in uneven yield and quality, serious diseases, and concentrated production period. The cultivation monitoring system and crop traceability management are based on
We build a regression model with luminosity below light saturation point as independent to predict the yield and harvesting period of vegetables in protected structures.
The investigation of vegetable seedlings physiological parameters is aimed to investigate the reaction between different kinds of vegetables and in different environments. It may provide optimized environmental control parameters as
In this work we use hyperspectral images combined with AI technology to develop non-destructive detection methods to establish three quality identification models for internal browning of pineapple tissues, bruise, and sound of fruit
The plant growth light source modules specially developed for Eustoma, Indian jujube and Sugar apple can reduce the electricity cost during the annual cultivation period. This technology develops special spectrum composition and
The quality control of agricultural products is a very important issue. Traditional methods use manual sampling. The disadvantage is that the procedures are complicated and time consuming, and the test results cannot be obtained immediately.
In response to the future development of smart agriculture, a set of facility crop leaf area real-time monitoring systems are developed in this research. The systems can remotely measure the leaf area and send the data back to the