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The achievement of labor saving and intelligentization of tea industry

The tea industry is dominated by labor-intensive and experience-intensive small-scale farmers. In recent years, due to the aging of the agricultural population, there has been a substantial shortage of agricultural labor. With the abnormal climate year after year, the cultivation and management of tea gardens are also challenged by extreme weather. Instability of tea yield has seriously affected farmers' income. Therefore, labor-saving machinery is urgently needed to assist the development of the tea industry, as well as smart management tools to collect climate and environmental parameters to help farmers in natural disaster warning and prediction of production period.

During the development of smart agriculture, Tea Research and Extension Station(TRES) developed labor-saving smart management technology from field production and harvesting to tea factories. For example, "Pre-casting Tea Seedling Technology of Tea Planting Machine" can increase the efficiency and reduce the workload of operator, and improve the survival rate of planting; " Two-way Communication System of Tea Garden Pest and Disease Identification " allows experts of plant protection to Instantly provide diagnosis and suggestions of prevention and control of pest and disease; and the application of "Ride-on Tea Plucking Machine" and "Tea Garden Automatic Drip Irrigation System" can not only relieve the demand for manpower in the tea industry, but also save production costs. In addition, TRES further builds the "Taiwan Tea Production Management Information Platform", which uses micro-meteorological sensing devices and the Internet of Things to conduct long-term monitoring of tea tree production and establish an early warning model, so that production strategies can be adjusted in real time in response to changes in climate and water resources. This platform also provides expert advice on field production and early warning of pests and diseases related to tea farmers and tea enterprises.

After introducing technologies related to smart agriculture in tea gardens, various labor-saving and smart agricultural machinery can reduce tea production costs by 30% (manpower requirements, irrigation water requirements, etc.). Because the platform as stated above provides warning information in advance, the loss rate of natural disasters can be reduced by 20%. The component analysis of tea leaves and primarily processed tea can improve the uniformity of tea products and the value of tea products by 10-20%, also it can increase the willingness of customers to purchase. TRES also builds a commercial tea production alliance.



The Popularize of Ride-on Tea Plucking Machine

The farmer uses the riding machine to cost down the business payment and improve the efficiency. Now, Taiwan Tea industry is suffering from the labor getting older, and the payment still higher. Taiwan Tea cost is also high, so we can’t provide enough tea for domestic demand. Cause the import tea more and more. Now, we a 600-hectare tea garden for demonstration which was managing by the riding machine, and to develop attached fertilizing machine improving the efficiency of labor .By this way, the mechanized tea garden management could be more popular in Taiwan.

Traction machine with tea planting machine

The renewal of tea gardens requires deep plowing, loosening, ditching and planting. Moreover, the traditional planting operations require the most workers, and planting operations are still done manually. In order to solve the problem of lack of labor in planting, we have developed a "traction machine attached to the tea planting machine", which is 5-6 times more efficient than traditional artificial planting. The manpower required for mechanical planting is 20% of that for manual planting, and planting operations are greatly reduced burden.

Tea Garden Automatic Drip Irrigation System

Timely and appropriate irrigation of tea gardens can significantly improve the quality and yield of tea leaves. The application of automatic drip irrigation system can save labors and water resources. The environmental data is transmitted back to the central control computer through the Internet of Things. According to meteorological factors such as soil temperature and humidity, electrical conductivity, air temperature and humidity, and rainfall, the appropriate irrigation amount is imported, and an irrigation decision-making system is initially established.

The calculation software of Tea yield prediction model

Based on the tea tree variety and tea buds growing and climatic data of different altitude, assessed with 3 modes, which are multi -variable analysis, mechanism mode (CGR model), and regression mode, the pattern performance evaluation indicators R2, NRMSE, MAPE and other indicators evaluations. Comprehensive performance pointed out that the prediction of prediction with a mechanism model is more accurate. Based on the mechanism model, the development of tea tree production forecasting software was developed, and it was placed on the information platform. Farmers can input the buds blooming and harvesting day to obtain the tea buds weight and leaves numbers after harvesting, and the farmers will knew the day is harvesting properatly or not. So, farmers could arrange harvesting labors in right time.

Set up the tea area micro -weather station

We had set up 23 micro-weather stations in major tea areas in Taiwan providing the weather data to farmers. When disasters happened, the meteorological conditions can be grasped and to set up disaster weather parameters as a condition for starting disaster rescue or insurance.

Taiwan Tea Garden Prpduction Management Information Platform

"Taiwan Tea Production Management Information Platform" is a tea industry expert decision-making system that can display tea garden management information from 10 monitoring tea garden in the five major tea districts in Taiwan, as well as 21 micro-weather stations in Taiwan and the central weather of some tea districts.The main functions include the meteorological data and historical meteorological data of each tea area, the growth status of tea trees, the prediction of tea tree growth, the diseases and insect pests of tea gardens and the recommended medication, the data of expert advice, the climate warning function, etc.