By 2050, we must produce 60 percent more food to feed a world population of 9.3 billion. Given the current industry challenges, doing that with a farming-as-usual approach could be tricky.

This is where Artificial Intelligence can come to our rescue. The AI in Agriculture Market is projected to grow from $1.7 billion in 2023 to $4.7 billion by 2028, highlighting the pivotal role of advanced technologies in this sector. Artificial intelligence (AI) has a lot of potential in agriculture and is already being used in various ways to increase efficiency and productivity

Three key challenges farmers face

1. Pests: Pests devour approximately 40% of global agricultural productivity annually, costing at least $70 billion. From locust swarms decimating fields in Africa to fruit flies affecting orchards, the impact is global, and financial repercussions are colossal.

2. Soil Quality and Irrigation: Soil degradation affects nearly 33% of the Earth's soil, diminishing its ability to grow crops, leading to a loss of about $400 billion. Water scarcity and inefficient irrigation further dent agricultural output. Agriculture uses 70% of the world's accessible freshwater, but 60% of it is wasted due to leaky irrigation systems.

3. Weeds: Despite advancements in agricultural practices, weeds cause significant declines in crop yield and quality. Around 1800 weed species reduce plant production by about 31.5%, leading to economic losses of about $32 billion annually.

How AI can help us

Artificial Intelligence is often used as a catchall phrase. Here, it refers to the systematic collection of data, pertinent use of analytics ranging from simple descriptive summaries to deep learning algorithms, and advanced technologies such as computer vision, the internet of things, and geospatial analytics.

AI detection systems automate pest identification and monitoring using cameras and sensors that collect data such as heat, movement, and sound. Machine learning algorithms analyze these data points against massive datasets, enabling AI to identify pests and recommend treatment plans.

Machine learning applications use supervised and unsupervised methods to support data analysis procedures, generating sufficient elements to provide a statistical solution to the problems requiring these techniques.

Artificial intelligence (AI) has the potential to revolutionize weed management by providing more efficient and accurate methods for identifying and controlling weeds. Here are some ways AI is being used in weed management:

Weed identification: AI can be used to develop image recognition systems that can identify weeds with a high degree of accuracy. This can help farmers and growers to quickly identify and classify different types of weeds, and then take appropriate measures to control them.

Precision weed control: AI-powered tools such as drones, robots, and autonomous vehicles can be used for precision weed control. These tools can scan the fields and identify weeds, and then apply herbicides or other control measures only to the affected areas, reducing the amount of herbicide used and minimizing the impact on
non-target organisms.

Predictive modeling: AI can be used to develop predictive models that can help farmers and growers to forecast weed growth and identify the best time to apply herbicides or other control measures. This can help to optimize weed management strategies and reduce the cost and environmental impact of weed control.

Weed mapping: AI can be used to create high-resolution weed maps that can help farmers and growers to identify weed hotspots and plan their weed management strategies accordingly.

Overall, the use of AI in weed management can lead to more efficient and effective weed control, reduce the use of herbicides, and minimize the impact of weed management on the environment.AI has the potential to revolutionize the way we produce and consume food, making agriculture more efficient, sustainable, and profitable. AI in weed management is basically more efficient in terms of reduce the use of herbicides which are generally toxic or harm-full for human health, crop plants when use at high rate and with overuse of herbicides without any consideration polluted the ground water and when herbicides are applied more than required, some amount of herbicides are remain active in soil for considerable period of time and it affect germination of successively sensitive crops. AI has limitation on its application as well. One of major limitation is initial high investment which cannot afford by small and marginal farmers. However, AI is beneficial for farmers and growers as compared to cost.