Artificial Intelligence In “Agriculture”, Is It

 Considerable For Future Generation?

Anil Kumar Kummari

When Norman Borlaug, the father of the green revolution, won the Nobel Prize in 1970, the Nobel Committee remarked, "more than any other single person of this age, he has helped provide bread for a hungry world." Borlaug’s introduction of disease resistant high-yielding crop varieties and advanced agricultural practices was a game changer, as agriculture yields increased tremendously and helped save millions from starvation.

Half a century after Borlaug received the Nobel Prize, we live in a world where yield growth is plateauing and the total land under cultivation is decreasing. Changing weather patterns and water availability is altering productivity in certain agricultural regions. The world population is expected to reach 9.7 billion by 2050. China and India, the two largest countries in the world, have populations totalling around one billion. In four years, by 2022, India is predicted to have the largest population in the world, surpassing China.

This means we need new ways to grow food that are smarter and helps regulate our use of land, water and energy in order to feed the planet and avoid a global food crisis.

However, why AI is necessary in Agriculture?

Experts predicting that artificial intelligence will provide the answer by the introducing 

Image recognition and insight (Drones, Sensors)

Agricultural drones scan fields and Provide new ways of increasing crop yields through in-depth field analysis, long-distance crop spraying and high-efficiency crop monitoring and seeding or analyse plant health. Farm activities can become much more effective when drone data, IoT and computer vision technologies join forces to optimize strategies. Very recently, Aerialtronics, manufacturer of unmanned aircraft systems, partnered with IBM to bring the IBM Watson IoT Platform and the Visual Recognition APIs to commercial drones in order to capture images, analyze them in near-real time, identify areas of concern and take actions. These artificial intelligence systems will save time, increase safety and reduce potential human error while improving effectiveness. Agriculture could benefit greatly out of it.

Determine the best options to maximise return on crops

The use of cognitive technologies in agriculture could help determine the best crop choice or the best hybrid seed choices for a crop mix adapted to various objectives, conditions and better suited for farm’s needs. Watson can use diverse capabilities to understand how seeds react to different soil types, weather forecasts and local conditions. By analysing and correlating information about weather, type of seeds, types of soil or infestations in a certain area, probability of diseases, data about what worked best, year to year outcomes, marketplace trends, prices or consumer needs, farmers can make decisions to maximize return on crops.

 Automated irrigation systems

Automated irrigation systems are designed to utilise real-time machine learning to constantly maintain desired soil conditions to increase average yields. Not only does this require significantly less labour and have the potential to drive down production costs, but with 70% of the world’s freshwater used for agriculture, the ability to better manage how it’s used will also have a huge impact on the world’s water supply.

Driver less tractors

Combining ever-more sophisticated software with ‘off-the-shelf’ technologies such as sensors, radars and GPS systems, farmers will soon be able to hand this century-old machine over to robots. With autonomous harvests, farmers will reduce pressures on an already strained workforce and allow more acreage to be worked for longer times.

Crop health monitoring

Similarly, conventional crop health monitoring methods are incredibly time-consuming and are generally categorical in nature. In comparison, companies developing automated detection and analysis technologies – such as hyperspectral imaging and 3D laser scanning – will substantially increase the precision and volume of data collected. With the ability for microscopic data collection, farmers will be able to produce diagnostics specific to individual plots or even single plants.

1) Case Study

NatureSweet, which grows tomatoes on six farms in the United States and Mexico, is using artificial intelligence to better control pests and diseases in its greenhouses.

Farms are increasingly using technology to grow crops, from task-tracking systems that monitor watering and seeding to drones that capture aerial images.

So far, NatureSweet's weekly harvests have grown 2% to 4%. This may seem modest, but the results makes a big difference when growing millions of pounds of tomatoes a year. NatureSweet installed 10 cameras in greenhouse ceilings. The cameras continuously take photos of the crops below. Prospera's software has been trained to recognize trouble, such as insect infestations or dying plants. 
NatureSweet has also experimented with using the cameras to forecast when plants are ready to be harvested.

The cameras from Prospera monitor the plants 24/7 and provide instant feedback.

Adrian Almeida, chief innovation officer at NatureSweet, believes artificial intelligence will eventually improve his greenhouses tomato yields by 20%.

Agricultural AI or AgriAI can revolutionize the traditional agricultural practices, which are currently being implemented. Farmers can grow multiple crops in the same amount of space and can monitor all the crops with the least effort. This will increase the crop production and variety thus helping the farmers and the state. Anyway increasing AI will decreases workforce in agriculture, which is highly employed sector. For the developed countries, it is meaning full to adopt AI in Agriculture. However, for the developing and under developing countries it will increase the GDP, Unemployment and Economic Imbalance.

Refences:-

1.     http://www.thewp-group.co.uk/Is_Artificial_Intelligence_the_future_of_farming.html

2.     http://money.cnn.com/2017/07/26/technology/future/farming-ai-tomatoes/index.html