Agricultural Chemicals

Tech-savvy Chinese farmers use drones to spray pesticide

Daily Mail

Farmers in China have caught up with the country's booming drone trend and started using unmanned aircraft to spray pesticide onto the fields. Not only that, a team of villagers in central China recently bought 30 of these bug-zapping vehicles in hope of turning it into a new business. Zhu Xiwang and his neighbours said they hoped their squad of agri-drones to could help them start a pest-killing service, according to, an affiliation to People's Daily Online. This £24.8K flat pack folding home takes just SIX HOURS to build Pictures show the 30 drones lining up on a field, ready to take off. The unmanned aircraft, known by its model name MG-1S, is produced by Shenzhen-based Da Jiang Innovation, one of the largest drone manufacturers in China.

Real World Deep Learning: Neural Networks for Smart Crops


To produce high-quality food and feed a growing world population with the given amount of arable land in a sustainable manner, we must develop new methods of sustainable farming that increase yield while minimizing chemical inputs such as fertilizers, herbicides, and pesticides. I and my colleagues are working on a robotics-centered approaches to address this grand challenge. My name is Andres Milioto, and I am a research assistant and Ph.D. student in robotics at the Photogrammetry and Robotics Lab ( Together with Philipp Lottes, Nived Chebrolu, and our supervisor Prof. Dr. Cyrill Stachniss we are developing an adaptable ground and aerial robots for smart farming in the context of the EC-funded project "Flourish" (, where we collaborate with several other Universities and industry partners across Europe. The Flourish consortium is committed to develop new robotic methods for sustainable farming that aim at minimizing chemical inputs such as fertilizers, herbicides, and pesticides in order to reduce the side-effects on our environment.

How John Deere's New AI Lab Is Designing Farm Equipment For A More Sustainable Future


The company spent $305 million to acquire Blue River Technology, a startup with computer vision and machine learning technology that can identify weeds–making it possible to spray herbicides only where they're needed. "What Blue River Technology allows us to do is move to the plant level, and start managing at that plant level," says Alex Purdy, director of John Deere Labs. Now, using computer vision tech to identify and spray only weeds, farmers can switch to other herbicides–including, potentially, organic herbicides that the weeds haven't evolved to resist (and that might otherwise kill the cotton, if they were sprayed everywhere). Computer vision and machine learning technology can also be used in every other step of farming: tilling soil, planting seeds in the optimal locations, spraying fertilizer or nutrients, and harvesting.

John Deere advancing machine learning in agriculture sector


Blue River Technology The new technology will reduce the need for herbicides by almost 95 percent because computer vision and artificial intelligence will allow the machines to identify, and make management decisions about every single plant in the field, only applying an herbicide to those plants that need treating. "We are using computer vision, robotics, and machine learning to help smart machines detect, identify, and make management decisions about every single plant in the field." Using computer vision and artificial intelligence, smart machines can detect, identify, and make management decisions about every single plant in the field. Using computer vision and artificial intelligence, smart machines can detect, identify, and make management decisions about every single plant in the field.


IEEE Spectrum Robotics Channel

During the Hands Free Hectare project, no human set foot on the field between planting and harvest--everything was done by robots. To make these decisions, robot scouts (including drones and ground robots) surveyed the field from time to time, sending back measurements and bringing back samples for humans to have a look at from the comfort of someplace warm and dry and clean. With fully autonomous farm vehicles, you can use a bunch of smaller ones much more effectively than a few larger ones, which is what the trend has been toward if you need a human sitting in the driver's seat. Robots are only going to get more affordable and efficient at this sort of thing, and our guess is that it won't be long before fully autonomous farming passes conventional farming methods in both overall output and sustainability.

9 AgTech Startups Using AI to Grow Smarter - Nanalyze


One of the big reasons we're rooting for the future is that the world's biggest tech fund, the SoftBank Vision Fund, planted $200 million in the biggest agtech funding round ever for San Francisco-based Plenty. Founded in 2015, Germany's PEAT has developed a free app called Plantix that uses machine learning and computer vision, technologies within the broader AI umbrella, to identify the problem with a plant from just a picture. We've seen the benefits of AI and computer vision on agriculture with another company called Blue River Technology, which has developed a system that can actually "see" weeds so that farmers can dramatically reduce the use of pesticides. This year's $200 million mega-round to Plenty and $305 million exit by Blue River show that the sector is drawing serious attention.

AgriAi-Deep Learning In Agriculture


The resources for farming like water, fertilizers, agricultural land etc. Improved Efficiency of Farmer – Different factors like irrigation, seed, weather conditions, soil, fertilizers, weed, crop diseases etc. Identifying Crop Diseases – Deep Learning has been used for the identification of crop diseases. Peat Technology provides easy solutions for crop disease diagnosis and monitoring, automated disease detection and advanced tools for automated disease detection for precision farming.



John Deere, established in 1837 to manufacture hand tools, announced it had acquired Blue River Technology, founded in 2011, late Wednesday. John Stone, an executive in the company's intelligent-solutions group, says Blue River's computer-vision technology will help Deere's equipment view and understand the crops it is working with. Stone says that Blue River's technology can make a larger impact on productivity because it makes decisions up close, on the ground. That system can target weeds with squirts of herbicide no larger than a postage stamp.

AI for Good: How advanced crop intelligence can help solve food production challenges


By being more effective in how they target crops, growers expe rience the economic benefits of reduced costs for crop protection, reduced crop threats, and therefore increased yields. Gamaya's precision agriculture services equip growers with information about the location, type, and intensity of the weeds infesting their fields. Targeted spraying reduces chemical usage, thereby significantly reducing the farm er's costs, lowering the negative impacts to the environment, and on human health, and likely slows the spread of herbicide-resistance. Not only is the cam era itself small, but it compresses data 100 times more efficiently than other hyperspectral cam eras, making our data processing quicker, less complex, and less expensive than with other hyperspectral sensors.

Farm Robot Learns What Weeds Look Like, Smashes Them

AITopics Original Links

Bonirob is more than 90 percent effective in destroying weeds in carrot cultivation trials. While the world's first fully-robotic farm will operate indoors, traditional outdoor farms aren't immune to the coming robotic revolution. Bonirob, developed by Bosch's Deepfield Robotics, is billed to eliminate some of the most tedious tasks in modern farming, plant breeding, and weeding. The autonomous robot is built to be a mobile plant lab, able to decide which strains of plant are most apt to survive insects and viruses and how much fertilizer they would need, and then smash any weeds with a ramming rod. Bonirob employs a type of machine learning (a stab at artificial intelligence) called decision tree learning.