A mobile application is introduced for lettuce industry under the smart agriculture

We develop a monitoring and forewarning system to detect planthoppers in paddy fields. Our detection algorithm consists of two stages. At the first stage, we extract the main paddy in the middle of an image by some traditional image processing techniques. At the second stage, we use a convolutional neural network to detect planthoppers within the extracted region. Our detection model is revised from the Single Shot MultiBox Detector (SSD). The original SSD model usually misrecognizes reflected l

In this paper, as shown in Fig. 1, the dual

Floricultural crops are vulnerable to rain

This research employed ray tracing to design a light-emitting diode (LED) lamp for saury fishing with an optimized light distribution that focus light into a fishing net beside a fishing vessel. In the simulation analysis, the average irradiance of LEDs without the designed lens was 0.83 times the incandescent lamps, whereas the average irradiance of the LEDs with the designed lens was 1.6 times the incandescent lamps. Considering the usage habits of saury fishing boats, the experiment

This comprehensive report analyzes agricultural performance and productivity trends with data from 1961 to 2015.

The robotic feed pusher is a smart forage-feeding intelligent with a power-saving device had been introduced to Taiwan by Livestock Research Institute in 2017. It has effectively replaces the manpower requirement of 3 to 4 hours per day and increases the eating times and intake of the cows.

In this study, ‘TNG17’ pineapples were placed on walk-in growth chamber at 7.5℃ for 3 and 4 week, and put them back at room temperature for 5 day, respectively. We recorded the internal browning extent and physiological variables such as enzyme activity, sugar and ascorbic acid content at different time point. Results showed that variables with significant effect were polyphenol oxidase, peroxidase, sucrose, glucose and ascorbic acid, and the correspondent regression coefficients were 0.32, -0.1

One of the core components of integrated pest management is monitoring. In this work, an automatic insect pest monitoring system is presented. The system can automatically record the number of insect pests trapped in sticky paper traps using a deep learning based image processing algorithm. Through the system, the temporal insect counts were analyzed to show the trend and pattern found from the insect counts that can be used by the farmers for decision-making. Furthermore, the analyzed data are