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 cloud for big data analysis applications. Leaf area is one of the crop characteristics, the leaf area index can be utilized and extended to estimate the yield of facility crops and to provide suggestions for cultivation management. A relational model, which based on th

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. The disadvantage of invasive inspection is that it destroys the test samples and makes them unable to be sold or eaten. Therefore, it is difficult to detect in large quantities or comprehensively, and cannot be widely used. Hyperspectral detection technology

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 light source timing control technology for the above-mentioned crops. The benefits achieved by this technology are that it can save more than 15% of electricity compared with traditional light sources, and the number of flowering and fruit setting increases by more than

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, which assists the industry in grading the quality of export. The internal browning detection technology of pineapple cold damage is based on the summer fruit to establish a detection model, and its training accuracy rate is 89.4%. After using the winter fruit to cr

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 the basis for the promotion of the vegetable nursery industry. This investigation including the most important vegetable crops, and have been investigated for many years. By analyze the Seedlings Physiological Parameters of the environment data, we may predict the s

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 integration of Smart Agriculture System, Blockly and R language allows us to sensor light, upload yield data and predict harvest period. The results will be transcribed into Google Sheets and available for farmers to schedule their greenhouses, workers and machines.

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 IoT which as the basis of intelligent production decision systems. To improve the domestic asparagus production and plan the management model of annual stable production.

Taiwan Agricultural Research Institute, Council of Agriculture, Executive Yuan and Industrial Technology Research Institute collaborate on developing an early-warning intelligent system for physiological diseases of citrus fruit to help citrus farmers prevent fruit sunburn, reduce the consumption of materials and manpower, and decrease crop costs. Based on a micro-meteorology intelligent sensing module and an infrared thermal image-sensing prototype, we obtained sunburn threshold and correlation

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 farmers as a correspondence to disaster reduction and avoidance. The content of this system includes the web version of real-time weather information such as the latest activity information which have real-time observation data, weather forecast of cultivation area and disaster infor