Farmers face hefty challenges to AI adoption in agriculture sector

Farmers face hefty challenges to AI adoption in agriculture sector
Farmers face hefty challenges to AI adoption in agriculture sector

M. Salman Raza

MULTAN, Dec 12 (APP): Farmers of Southern Punjab face challenges in effectively application of Artificial Intelligence (AI) for increasing crops’ cultivation which result in declining the overall crops yield followed by ultimate rising commodity prices in the country.

Agriculture is a major industry in Pakistan which contributes around 20% to the overall GDP and employs almost 50% of it’s’ population, directly or indirectly.

The AI has the potential to help confront one of humanity’s biggest upcoming challenges of feeding extra two billion people by 2050 with only 4% of additional land will be available for cultivation — projected by Pakistan and Gilf Economist (PAGE), a leading weekly financial magazine in its report titled “Artificial Intelligence: The future of Agriculture”.

These are the tools to assess operations coupled with tracking to reap its benefits such as decreasing crop waste, improving food security, minimizing need for chemicals on crops and using resources sustainably. According to research of Sustainable Development Policy Institute (SDPI), presently the three major applications of AI can be used in the country.

Firstly, the Agricultural Robots: It has the capacity to independently handle basic harvesting tasks at a faster pace with greater volume as compared to humans.

This also includes efficient ways such as computer vision for farmers to protect crops from weeds without affecting the crop. Secondly, a major use of technology can monitor and analyze data.

This will tackle many issues like degradation of soil quality that is a major contributor to food insecurity and have overall negative impact on yield.

Computers can use deep learning algorithms to store and process data captured by drones, GPS and field sensors installed in tractors etc.

regarding potential defects and nutrient deficiencies in the soil and crop. This data can be used to monitor the health and readiness of crop and soil with regard to certain defects and diseases. It would enable farmers to take appropriate measures.

Lastly, predictive analytics also have a role to play in the form of precision farming. Machine learning models can be used to track and predict external factors that impact the yield such as temperature changes, rainfall, wind speed and market shifts etc.

For example, an existing app in Pakistan already provides weather notifications, whereas machine learning can take this a step further by customizing the predictions based on the needs of each client. Challenges for Technology Adoption included:

Firstly, there is lack of adequate crops data required for application of such technology. In order to match up all different variables and their possibilities, system requires a lot of different combinations of soil types, weather, seed variety, fertility, water availability, time period etc. Secondly, it may be hard to sell such technology in areas where agricultural technology is not common.

Farmers likely need help to adopt it. Third, new technologies often seem confusing and unreasonably expensive because AgriTech providers fail to clearly explain why their solutions are useful and how exactly they should be implemented.

One of the major hurdles is that Pakistan is in very early stages of this revolution, thus, it needs extensive testing and endorsement for the AI based applications.

It would also require farmers to be equipped with training to ensure they use the technologies effectively by understanding the data and insights provided by experts.

A long-term plan combined with adequate funding is needed to test these technologies in the field. The key to AI being accepted by everybody is the transparency of data and fairness in algorithms. These are the biggest issues that AI needs to tackle.

Commenting over the challenges of farmers, Assistant Professor of computer science from Muhammad Nawaz Sharif (MNS) Agricultural University having expertise in AI subject, Dr Ayesha Hakim said, as an early player in this industry, Pakistan is struggling with data availability and documenting it accurately that is essential for training the algorithm and mining the data. She said the university used to conduct training workshops for farmers hailing not only from Multan, remote districts of the Southern belt.

She said it’s a challenge to process and analyze web content, preparing audio, video files with creating easy text to educate harvesters about the use of technology.

She admitted that there are financial constraints to the technology usage, thus urged upon the authority to ‘subsidize the issue’ locally.

Comparing with New Zealand surviving with agro-based economy, she anticipated that the local cultivators would need a decade to familiarize with the new invention. “It’s in nowhere that 100% technology used, but needs to have access and acceptance of the network by maximum people” said VC of MNS Agricultural University Professor Dr Asif Ali. It’s not for everyone but for the young farmers particularly who want to protect their fields.

Replying query about promotion, the VC said recently an MoU is signed between the university and Concave Agri, a European company, to hold advertisement about AI usage at mass level. Dr Ayeaha said the university’s management is trying to get two projects including Cacophony and Mosquitoes Surveillance from New Zealand to save our potential fields from flies attacks by calculating ‘wind beat frequency’ from affected areas.

By collecting data on plant growth, AI can help produce crops that are less prone to disease and better adapted to weather conditions. In addition, farmers would be able to hold spray only at the targeted area where pests or flies detected. It wouldn’t only help them save money by avoiding spray to the whole of the field, protect human health from hazards of spray and overall environment, she said. Analyzing market demand, forecasting prices, and determining the optimal time for sowing and harvesting are key challenges farmers can solve with AI, she said.

AI can help judge insight of soil health, provide fertilizer’s recommendation, monitoring weather and track the readiness to produce crop, she added. According to VC MNS Agricultural University, this is also a challenge for software companies. They should approach farmers gradually, giving them simpler technology first via agriculture trading platform.

Privacy and security threats like cyber attacks and data leaks may cause farmers serious problems. Unfortunately, many farms are vulnerable to these threats. “There’s still a lot of work to be done by technology providers to help farmers implement it the right way” said the VC.

Government has the capacity to provide ‘agriculture credit’ to small farmers to enable them invest in these inputs and techniques. “Change is inevitable, whether you like it or not. Let’s not give in to the fear of possibilities” said Dr. Asif Ali. He elaborated; a drone camera flies over a field to take images within minutes.

The images will be used to forecast about weather changing pattern, moisture, wind pace, soil condition, harvesting time and detection crops’ diseases at affected areas. Modern spray machines with some particular sensors for detection and elimination of harmful weeds in the agriculture fields can be introduced by the dint of artificial technology in the country.