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　　AI changes the 5 ways of agriculture(英中雙語)

With the development of time technology, artificial intelligence and agriculture are becoming inseparable, and it brings exciting infinite possibilities. From seed germination, to the preservation of crop integrity, to the actual harvesting process, whether from agricultural products to field farming techniques, or from planting to improving harvesting quality, both AI and machine learning have been rapidly used in agriculture. Artificial intelligence in agriculture can be divided into five categories:

隨著時代科技的發(fā)展，人工智能和農(nóng)業(yè)正變得密不可分，它帶來了令人興奮的無限可能性。從種子發(fā)芽，到保持作物的完整性，再到實際的收獲過程，無論是從農(nóng)產(chǎn)品到田間耕作技術(shù)，還是從種植到提高采收質(zhì)量，人工智能和機器學(xué)習(xí)都在農(nóng)業(yè)領(lǐng)域得到了迅速的應(yīng)用。農(nóng)業(yè)中的人工智能可以分為五類：

]agricultural robot

農(nóng)業(yè)機器人

Now many technicians are developing and programming autonomous robots to handle important agricultural tasks, such as harvesting crops with higher capacity and faster speeds than humans, and the emergence of automation could help solve labor shortages.

現(xiàn)在許多技術(shù)人員都在開發(fā)自主機器人并對其進行編程，以處理重要的農(nóng)業(yè)任務(wù)，比如用比人類更高的產(chǎn)能和更快的速度收割莊稼， 自動化的出現(xiàn)有助于解決勞動力短缺的問題。

Crop and soil monitoring

作物和土壤監(jiān)測

Computer vision and deep learning algorithms can be used to process data captured by drones, as well as using software technologies to monitor crop and soil health. As deforestation barren soils and causes waterlogging and salinity, the development of soil analysis machines may become critical in the next few years.

可以利用計算機視覺和深度學(xué)習(xí)算法來處理無人機捕捉到的數(shù)據(jù)，以及采用軟件技術(shù)來監(jiān)測作物和土壤健康狀況。由于砍伐森林使土壤變得貧瘠，并造成澇漬和鹽堿化，土壤分析機器的發(fā)展在未來幾年內(nèi)可能變得至關(guān)重要。

The ability to control the weeds

控制雜草的能力

Today, about 250 kinds of weeds have resistance to herbicides, in the researchers of corn and soybean crop weeds out of control research, agricultural economy costs about $43 billion, therefore, the use of automation and robot technology to help farmers find more effective ways to make the crops from weeds is particularly important.

如今，約有250種雜草已經(jīng)對除草劑產(chǎn)生了抗性，在科研人員對玉米和大豆作物的雜草失控影響研究中，每年農(nóng)業(yè)經(jīng)濟會因這一問題損失約430億美元，因此，使用自動化和機器人技術(shù)幫助農(nóng)民找到更有效的方法來使莊稼不受雜草侵害尤為重要。

Usage of drones

無人機的使用

By 2027, the agricultural drone market is expected to reach $480 million by 2027, and the use of drones is designed to help users increase crop yields and reduce costs. First programming the route of the drone, once deployed, the device will use computer vision to record images, and the captured data will be uploaded through algorithms to integrate and analyze the captured images and data to provide a detailed analysis report.

到2027年，農(nóng)業(yè)領(lǐng)域的無人機市場預(yù)計將達到4.8億美元，而無人機的使用旨在幫助用戶提高作物產(chǎn)量和降低成本。首先編程無人機的路線，一旦部署該設(shè)備將利用計算機視覺記錄圖像，并將捕獲的數(shù)據(jù)上傳，通過算法來整合和分析捕獲的圖像和數(shù)據(jù)，以提供詳細(xì)的分析報告。

Proper use of chemical fertilizer

化肥的正確使用

Machine learning algorithms combined with satellites can be used to predict weather, analyze the sustainability of crops and assess pests and diseases on farms. Some agricultural software can now tell users where they need fertilizer, which can reduce fertilizer use by nearly 40 percent.

與衛(wèi)星相結(jié)合的機器學(xué)習(xí)算法可以用于預(yù)測天氣、分析作物的可持續(xù)性以及評估農(nóng)場是否存在病蟲害，現(xiàn)在一些農(nóng)業(yè)軟件可以告訴用戶哪里需要化肥，這樣可以減少近40%的化肥使用量。

The emergence of artificial intelligence can not only help improve agricultural efficiency, but also address the challenges facing the industry, including crop yield, soil health and herbicide resistance. Agricultural robots will become an important application of artificial intelligence in agriculture, allowing farmers to receive the latest training to ensure that these technologies are used and continue to improve, which in the long run will also help prove the instrumental value of new technologies.

人工智能的出現(xiàn)，不但可以幫助提高農(nóng)業(yè)效率，還能解決行業(yè)面臨的挑戰(zhàn)，包括作物產(chǎn)量、土壤健康和除草劑抗性。農(nóng)業(yè)機器人將成為人工智能在農(nóng)業(yè)領(lǐng)域的重要應(yīng)用，通過可行的機制來解決上述問題，能讓農(nóng)民接受最新的培訓(xùn)，以確保這些技術(shù)得到使用并繼續(xù)改進，從長遠(yuǎn)來看，這也有助于證明新技術(shù)的工具價值。