NASK researchers train convolutional neural networks to confirm horse identity based on eye images

Researchers at Columbia University automate the process of sex-sorting tsetse flies with machine learning

Researchers from UCSC have pilot-tested an artificial intelligence irrigation system which may be able to save 70% more water than other irrigation methods.

Researchers from the University of Technology Sydney aim at ensure livestock are in peak condition leading up to sale by analysing cattle through AI

Scientists at Japan’s National Institute of Advanced Industrial Science and Technology are testing artificial cross-pollination of flowers with drones that mimics bees

University of Montana is testing an app with which beekeepers will be able to try to find out what is troubling a colony by listening to the buzz

University of the Philippines researchers are exploring making pesticides safer for consumption by analysing molecular chemistry using deep learning

Verily aims to reduce infected mosquitos population with computer vision

Abundant Robotics device autonomously harvests apples using machine vision to identify appropriate fruit

Alibaba Group detects pigs' pregnancy seven times quicker using facial recognition technology

Blue River Technology offers deep learning technology which is aspiring to reduce herbicide usage by offering a more precise and targeted spray application

Farmers are able to quickly identify issues such as crop stress and disease and pest infestation on heatmaps enabled by drones and machine learning

ICRISAT and Microsoft advise farmers on when to sow crops resulting in a 10-30% yield per hectare increase by using machine learning

Iron Ox fully automates the growing process end-to-end with the potential of 30 times more produce than traditional farms

Makoto Cucumber Farm automatically sorts cucumbers based on shape, length and distortion using deep machine vision

McCain will test Resson's image recognition algorithms for crop condition monitoring to optimise potato yields and reduce costs

PEAT identifies 400 diseases and pests from farmers' uploaded photos on their new mobile app

Researchers from the University of Lincoln have built a learning computer system to early detect potentially harmful flaws in production and packaging of potatoes

Slantrange aims at measuring crop populations and detecting weeds with machine vision

Small Robot Company develops robots to monitor crops and soil to maximise yield

Small Robot Company offers precision micro-spraying and physical weeding using robots aiming to reduce chemical usage by up to 95%

Small Robot Company offers robot for precision drilling and planting for per plant accuracy

Tanimura & Antle farm automates lettuce thinning with machine vision

ecoRobotix aims to reduce the amount of herbicide farmers use by 20 times with robotics and machine vision

Researchers at Stanford University aim to detect illegal polluting from farms using a convolutional neural network

SunSelect enables greenhouse farmers to more accurately forecast their future harvests with machine learning

TellusLabs aims at providing accurate prediction of natural resources and agricultural yields with machine learning

The National Institution for Transforming India partners with IBM to develop a crop yield prediction model using AI

The US Department of Natural Resources used deep learning vision analysis of satellite imagery to predict the size of soya and corn crops well before harvesting

Cargill offers facial recognition technology for farmers in collaboration with Cainthus