数字化乳业试验场已设定自己的目标，即对现有的耕地和棚舍的数字解决方案进行演示。 此外，还将审核它们是否适合家庭型经营。 在试验场将对操作和使用经验进行记录，对现有的欠缺进行说明，并对解决方法和技巧作出提示和指导。 伴随此过程还将举办经济合作伙伴和制造商的论坛。这样做旨在通过减少不兼容性来改善各单独系统间的网络连接，这是实践中的一个重要问题。
This project analyzes and assesses the effectiveness of the current robotic and farm management systems at modern dairy farms to support farm owners in their management decisions.
Once shortcomings have been identified, the project tries to develop cost effective solutions to improve the technologies applied. The project looks at all elements of the dairy farm system: sensor-aided technologies for the application of manure, interconnected barn technologies, sensor-aided pasture yield estimation, optimization of feeding ratios and connection of all sensor-based systems which are analyzing the behavior and performance of the dairy cows.
The project is implemented by the Bavarian State Research Centre for Agriculture and cooperates with local dairy farmers and companies that manufacture the technologies for the digital dairy barn.
Further information in German can be found on https://www.lfl.bayern.de/digimilch
This project aims for the sustainable improvement of pig husbandry with special regard to animal welfare, conservation of natural resources and farm profitability through a farm management software called DigiSchwein. An early warning system to detect sick pigs, monitoring pig behavior in the barn by using cameras, and sensors to monitor the time period when pregnant sows give birth are tested in the project.
The project is implemented by the Chamber of Agriculture of the federal state Lower Saxony in cooperation with local universities and research institutions.
AgriSens aims to utilize publicly available satellite images in combination with sensors in the fields to provide farmers with precise information about soil properties, soil moisture and the health status of their crops. This enables farmers to specify the use of irrigation or fertilizers, while saving resources and reducing CO2 emissions.
This technology can also be used to detect the exact location of smaller and bigger stones in the fields, which can cause substantial damage to agricultural machinery, especially in northern Germany.
The project is implemented by a consortium of several German universities and research institutions and is coordinated by the German Research Centre for Geosciences (GFZ).
More information can be found here in German: https://www.agrisens-demmin.de/
Agro Nordwest aims to transfer existing research findings of digitization in agriculture into practical applications for farmers. There is a direct cooperation with farmers in the field, evaluating the use of small, automated robots and traditional tractors with regard to efficiency and economic benefits.
Through the use of drones equipped with multispectral cameras and other sensors, digital field maps are produced to enable the use of weeding robots or tractor-driven mechanical weeding devices which render spraying of herbicides pointless. The project also conducts research on data security at farm level and has elaborated training modules to educate farmers in the use of digital tools for their farm operations.
The project is implemented by the German Research Center for Artificial Intelligence (DFK) in cooperation with private farms and companies dealing with agricultural machinery.
The website can be accessed in German and English: https://www.agro-nordwest.de/en/
Experimental field BeSt-SH focuses on farm management and how the use of interconnected digital tools can improve resource efficiency and increase farm profitability at the same time.
The researcher from the Technical University of Kiel have developed a digital model of a farm to simulate and analyze both the whole workflow and input flows to optimize daily work with the help of digital tools to achieve highest efficiency in terms of economic and ecological sustainability.
The project aims to educate farmers about the possibilities of digitization in their farms so that the often abstract idea of digitization becomes tangible and useful. How to use modern digital tools to adhere to current laws and regulations, taking the environmental conditions of the field into account and optimize the economic benefits without endangering the natural resource base.
The project is implemented by the University of Kiel together with the local chamber of agriculture and private farms.
The website is available in German: https://best-sh.de/
The whole life cycle of cattle is in the center of this research project, starting from optimal care for the newborn calf, timely detection of young cows for insemination to feeding schemes and tracking schemes for cattle in and outside of barns.
The project analyzes existing digital technologies for cattle farmers and is aiming to harmonize, farm management systems from different companies. Ensuring interconnectivity of different systems is one of the major challenges. The optimization of work flows at farm level and an increase of animal welfare are intended as project results.
The project is implemented across four federal states; the University of Bonn coordinates the activities of the project together with its partners from research, the state chamber of agriculture and demonstration farms like Haus Düsse.
Fore more information in German visit https://cattlehub.de/
The main aim of Diabek is to make farmers aware about the beneficial use of digital technologies, even for part-time or small-scale farmers. The project provides trainings to farmers to enable them to use satellite-based maps on their own PCs for the precise application of fertilizer and pesticides. This will result in less inputs, reduced leakage of nutrients into groundwater and will help to increase the image of agriculture among the general public.
To validate these assumptions, the project also carries out consumer surveys. The project is coordinated by the University of Weihenstephan (near Munich) with collaboration from private companies and farmers.
More information on Diabek can be found here in German: https://diabek.hswt.de/
Developing cost-effective digital solutions for small-scale vineyards, e.g. GPS-based precision planting of new vineyards, the optimization of plant protection measures or the development of a device to analyze the quality determining properties of grapes which can be used on spot within the vineyard.
The use of sensors during grape harvesting can help to separate unripe or grapes of lower quality from the good ones to increase the product quality.
The project is carried out by the Julius Kühn-Institute, Federal Research Centre for Cultivated Plants, Institute for Grapevine Breeding in collaboration with the University of Kaiserslautern and other public and private partners.
For more information in German visit https://digivine.org/
DIWAKOPTER utilizes multicopter drones in viticulture and fruit orchards as well as in selected field crops. Drones with spectral cameras to detect diseases at individual plant level are used to enable targeted application of pesticides or leaf fertilization to minimize harmful effects of fertilizers in the environment. Use of drones in steep hillside vineyards to eliminate dangerous manual work and the use of sensors to determine the health status of the grapes to decide whether an application of pesticide is necessary or not are analyzed in this project.
The project is carried out by the Technical University of Geisenheim, one of the leading German universities for viticulture, located near Mainz, the capital of the State Rhineland Palatinate.
For more information please visit https://www.diwakopter.de/
DiWenkLa tries to enable small-scale farmers in areas like the black forest to utilize digital solutions in crop production, orchards, vegetable production as well as for horse and cattle husbandry in semi urban areas. Horse husbandry in the vicinity of large cities has become an important income-generating activity for many farmers.
Research is carried out on topics like effective utilization of small grassland plots through digital solutions (pasture management, pasture yield estimation) as well as automatic feeding systems and semi or fully automated manure removal in cattle barns. The project develops fully automated mechanical weeding devices equipped with high-speed cameras.
The project is coordinated by the University of Hohenheim (near Stuttgart) in cooperation with state-run agricultural institutions and a local university in collaboration with a range of private farms and companies.
For more information visit https://www.diwakopter.de/
EF Southwest promotes farm management systems to support agriculture value chains in Rhineland Palatia, especially in rural areas where digital infrastructure is not yet well-developed.
To minimize loss of data in data clouds the projects supports farmers to establish farm-size data servers (decentralizing data in a device called Hofbox “Farm Server”). The server can be connected to sensors at farm level and public data server to support the farmer with the official documentation requirements. One subcomponent of the project is working on the sustainable utilization of animal manure.
The project is coordinated by the regional ministry for commerce and agriculture in cooperation with private companies as well as public demonstration and private farms.
Moe information in Germn can be found here: http://ef-sw.de/
EXPRESS concentrates on digital solutions for crop production in eastern Germany. The researchers are using different kind of high-end sensors to monitor plant health and responses to water stress under changing climatic conditions. Based on the developed models it is possible to provide accurate predictions about the occurrence of certain plant diseases. One subproject is researching on the traceability of agricultural products using block chain technology.
The project is coordinated by the University of Leipzig in cooperation with the Helmholtz Centre for Environmental Research and two private farms which specialize on fruit orchards and vineyards.
More information in German is available here: https://www.digitalisierung-landwirtschaft.de/experimentierfelder/
FarmerSpace aims to provide farmers with accurate information about the health status of their field crops through the utilization of sensors and drones equipped with multispectral cameras. The identification of the exact spots where plants are affected will enable farmers to apply pesticides in a targeted way and thereby reducing the amount of pesticides applied. The use of autonomous, small robotic devices for mechanical weeding is another element of this project.
Special emphasis is given to the sugar beet crop as the Institute of Sugar beet Research is one of the implementing partners of this project which is coordinated by the University of Göttingen.
For more information please visit https://www.farmerspace.uni-goettingen.de/
Landnetz looks for solutions on how to connect machinery, sensors and external computer systems to enable smart farming in rural areas, especially within rural areas of eastern Germany where infrastructure is still lacking broadband access. The researchers are testing campus networks at farm sites in rural areas; these are networks which were originally used in industrial estates. Mobile datacenters in trailers are connecting all digital tools on the farm. Apart from increasing efficiency and profitability of the farm enterprises, the digital revitalization of rural areas should also make modern agriculture more attractive for young urban talents.
The project is implemented by the University of Dresden in cooperation with the Saxon State Institute for Agriculture and the Fraunhofer Research Institute for Traffic and Infrastructure and selected private farms.
For more information visit https://landnetz.eu/
Dr. Markus Gandorfer 领导着农业工程和畜牧研究所（巴伐利亚州立农业研究所）的数字农业工作组。 Markus Gandorfer学习的是园林学专业，然后攻读了关于精准农业的经济生态学评估的博士学位，并最终取得了农业经济学专业邻域的大学授课资格。 Mr. Gandorfer 的工作重点是评估数字农业技术以及数字技术在农业和社会中的接受度。
MyEasyFarm是法国农业科技初创公司，总部位于兰斯，由弗朗索瓦·蒂埃拉特（Francois Thiérart）于2017年创立。 MyEasyFarm为农民和合作社提供了一种解决方案，可以通过简单且网络化的方式使用精准农业，以提高效率和可持续性。这家初创公司通过ISOBUS的认证，可以与农业机械设备（无论制造商如何）交换数据，无论是使用USB还是以连接模式进行交换，以实现真正的可变速率应用和自动可追溯性。 MyEasyFarm还为食品产业的利益相关者（农民，合作社，农用工业）提供了一个平台，可以通过改作物周期来测量和减少农业中的CO2排放量和储存量。