Extensive technological knowledge is not necessary, but an understanding of the basic principles and its operational implications is important. They need to quickly immerse themselves on the technologies available and need to be able to sensibly assess its benefits to the farm.
“If you are going to go where corn grows, take a cutting tool with you.” Farm managers need to use the right tools at their disposal. Drawing upon traditional farming proverbs, viable strategies may be found: Amidst these dramatic technological changes, farmers need to manage their farms in new ways. With such transformation, digital farms require digital farmers. The AI revolution is transforming farming and agriculture and provides multiple pathways for abundant harvests in all corners of the world. Farmers are now super-empowered to find the right crop, for the right place and at the right time (Bagchi, 2018). Similar to other industries, farms face constraints relating to the use of AI such as investment costs, compatibility with current tech infrastructure, skills and resource availability, privacy, security, and possible regulatory issues.ĭespite these potential constraints, the stage is set for cognitive farms, precision farming, and agricultural intelligence. Predictive analytics – AI tools have been created to predict changes in weather patterns, pest infestation or soil erosion in order to improve planning and farm management. These tools help farmers take a glimpse of the future and assist them in making informed decisions.
This can lead to productivity gains with indefatigability, minimization of errors, and consistency of work quality.
#FARM MANAGER 2019 MANUAL#
For example, a farm manager can use a drone to scan a large track of land and identify the exact location of plant disease or pest infestation in real time.Īutomation and robotics - in order to speed up manual work or manage manpower shortages, robots are used in farm activities such as fruit picking and lettuce thinning among many others. This boosts information accuracy and aids in decision making. This terrain is now characterized by enhancements such as:Įxtensive data capture and analysis – farms now have the ability to set up, track and analyze a multitude of data points thereby helping farmers make better decisions. The cognitive farmĪdvances in AI and related technologies lead to smart farms or farming models with high cognitive ability. It is evident that farm managers have a wide assortment of tools at their disposal to boost farming and agricultural intelligence. Examples of farming activities and AI companies Farming Activities Table 1 shows examples of companies with products catering to farming and agriculture. There is an abundance of AI tools in the market. An AI app called Climate Basic identifies the optimal location to plant corn based on temperature, erosion, precipitation and soil quality in order to optimize yield (Rao, 2017). Their AI architecture and cameras monitor plants 24/7 and provide instant feedback (McFarland, 2017). For example, Nature Sweet when growing their tomatoes uses AI for pest control and disease study. There are several successful cases that demonstrate the value of AI in farming and agriculture. This is a very impressive growth forecast for any industry by any standard.
In this scenario, there are important questions farm managers need to grapple with: Which AI tools are best to use? How do I use them? Is AI a worthwhile investment? Should I make the move now or wait for a better time after I’ve seen evidences of successful AI models? Is the grass really greener in the world of AI? Land of promiseĪccording to a Markets and Markets Report (2019), the agricultural AI market is presently valued at around $519 million and is projected to grow to $2.6 billion by 2025. Artificial intelligence has offered countless tools for industries around the world to use, including agriculture.