The peaking need for agriculture robots on a global scale is accredited to the ever-rising world population and a relative reduction in the average available agriculture workforce. Urban migration has had an adverse impact on Agricultural practice and the methods involved in it. As more and more educated crowd moves towards the city to realise the ‘Million Dollar American Dream’, innovation in agriculture takes a back seat. But in recent years, notable efforts have been taken in this sector. Introduction of Agriculture robots is expected to replace the scarce human labour. These robots bring with them advantages such as constant work rates under a diverse array of harsh environmental conditions, a reduction in the use of chemicals and pesticides applied to crops, and the heavily sought-after concept of precision agriculture.

A cocktail of modern technology and traditional wisdom is all set to get the party going in Agriculture.

1. AI to determine Time Sowing

Microsoft’s Cortana intelligence Suite is imparting an overview of factors that determine a healthy crop yield. It will give insights on soil health and also suggest ways to use fertilizers efficiently in addition to the seven days’ weather forecast.
This program commenced across 7 villages of Andhra Pradesh roughly involving 175 farmers. These farmers were asked to wait until an SMS was sent to them before they could begin ploughing and sowing. Though sceptical, these farmers followed the instructions as imparted.
As monsoon set in, the faith finally paid off. A record yield with an increase of 30 – 40% was noted.

The right time for sowing reduces the risk of yield loss due to pests and also increases crop efficiency by using climate data to our advantage.

“Sowing date as such is very critical to ensure that farmers harvest a good crop. And if it fails, it results in a loss as a lot of costs is incurred for seeds, as well as the fertilizer applications.” – Dr Suhas P. Wani, Director, Asia Region, ICRISAT

2. Weed Control

Blue River Technology has designed and integrated computer vision and machine learning technology that will enable farmers to reduce the use of herbicides by spraying only where weeds are present, optimizing the use of inputs in farming – a key objective of precision agriculture. In a research study conducted by the Weed Science Society of America on the impact of uncontrolled weeds on corn and soybean crops, annual losses to farmers are estimated at $43 billion.

In recent developments, MOLINE, Illinois (September 6, 2017) — Deere & Company (NYSE: DE) has signed a definitive agreement to acquire Blue River Technology, which is based in Sunnyvale, California and is a leader in applying machine learning to agriculture.

3. Crop Harvesting & Soil Monitoring

Agriculture is projected to experience a 6 percent decline in agricultural workers from 2014 to 2024.

Harvest CROO Robotics has developed a robot to help strawberry farmers pick and pack their crops. Lack of labourers has reportedly led to millions of dollars of revenue losses in key farming regions such as California and Arizona. Harvest CROO Robotics claims that its robot can harvest 8 acres in a single day and replace 30 human labourers.
In the short video below, the Harvest CROO team provides a demonstration of the robot:

PEAT – Machine Vision for Diagnosing Pests / Soil Defects

PEAT (Progressive Environmental & Agricultural Technologies) is a deep learning AgTech Startup. Deforestation and degradation of soil quality remain significant threats to food security and have a negative impact on the economy.
Berlin-based agricultural tech startup PEAT has developed a deep learning application called Plantix that reportedly identifies potential defects and nutrient deficiencies in the soil. The analysis is conducted by software algorithms which correlate particular foliage patterns with certain soil defects, plant pests and diseases.
The image recognition app identifies possible defects through images captured by the user’s smartphone camera. Users are then provided with soil restoration techniques, tips and other possible solutions and can become a part of this community as explained in the short video below:

4. Diagnosing Soil Defects

Similar to the Plantix app, California-based Trace Genomics, provides soil information farmers. Ace investor Illumina helped develop the technology which uses machine learning to provide clients with a sense of their soil’s strengths and weaknesses. Healthy Crop Production is the main aim of this technology.

As of February 2017, the company has raised $8 million in total equity funding from six firms including the Illumina Accelerator. Product packages begin at $199 for the Pathogen Screen.

5. Automated Irrigation Systems

Traditional irrigation management is an arduous task. This is coupled with a heavy reliance on historical weather conditions to predict required resources. Thankfully, though, 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.

The ‘Digital Farm’ Of the future is in the making.